Selected 2016 Awards

The breadth and number of achievements by CIRES researchers and staff speak to the quality of research conducted at the Institute. From lifetime achievement awards to recognition of emerging young talent, CIRES scientists are among the best of the best at what they do. Among the premier awards received by CIRES scientists during the 2016-2017 reporting period was a Presidential Early Career Award from the White House for Anne Perring and three teams that earned medals from the U.S. Department of Commerce.

CIRES Awards
The CIRES Members Council convenes an award committee every year, to assess nominations submitted by NOAA supervisors, CIRES colleagues, and others. The CIRES Outstanding Performance Awards—given in Science and Engineering and in Service—are targeted at projects that are novel, high impact and show remarkable creativity or resourcefulness. The CIRES Director selects the Ph.D. student recipient of the Reid Fellowship every other year, after reviewing nominations made by graduate advisors.

CIRES Outstanding Performance Awards

The CIRES Outstanding Performance Awards are targeted at projects that are novel, high impact, and show remarkable creativity or resourcefulness. In the Science and Engineering category, this may involve any work that is related to the scientific process (forming and testing hypotheses to further our understanding of the environmental sciences). In the Service category this may involve any work that facilitates, supports, enhances, or promotes work in the environmental sciences.

Science and Engineering
Gilbert Compo in NOAA’s Physical Sciences Laboratory won for leading the development of the 20th Century Reanalysis, which relies only on surface pressure records and extends back more than 100 years.
Derek Hageman in NOAA’s Global Monitoring Laboratory, for outstanding software development to support his division’s mission to collect and understand accurate, long-term atmospheric data.
George Millward in NOAA’s Space Weather Prediction Center, for his uncommon scientific creativity in transitioning an academic geospace model into operations.
Service
Kelly Carignan and Matthew Love in NOAA’s National Centers for Environmental Information, won for developing a 5-day tutorial in coastal digital elevation modeling, which forged strong U.S.-Canadian collaborations on tsunami safety and preparedness.
Marc Cloninger and Andrea Dietz on CIRES’ Finance team won for being “world-class enablers,” going above and beyond to help CIRES scientists navigate budgets, proposals, and university and NOAA systems.
Sandy Starkweather in NOAA’s Physical Sciences Laboratory won for her leadership and coordination of the Interagency Arctic Research Policy Committee’s Arctic Research Plan.

CIRES Medals and More

George C. and Joan A. Reid Scholarship Award, 2017
Neesha Schnepf in NOAA’s National Centers for Environmental Information (NCEI), is this year’s recipient of the George C. and Joan A. Reid Award, made possible by the Reids’ generous contribution to an endowed scholarship fund. Schnepf works in the NOAA NCEI geomagnetism group and is a PhD student in the University of Colorado Boulder’s Department of Geological Sciences. Advised by CIRES scientist Manoj Nair (NOAA NCEI) and CIRES Fellow Anne Sheehan (Geological Sciences), Schnepf studies the magnetic field associated with oceanic flow, and using variations in that field to determine more about issues such as tsunami propagation, the electrical structure of the lithosphere, and the circulation of ocean water.

CIRES Medals

CIRES scientists are often integral to NOAA award-winning science and engineering teams but cannot be given certain federal awards, such as the prestigious Department of Commerce Gold and Bronze medals. The CIRES Director recognizes the extraordinary achievements of CIRES scientists working in partnership with federal colleagues.

CIRES Gold Medal for scientific/engineering achievement
Michael Burek, Michele Cash, Stefan Codrescu, Tom DeFoor, Ratina Dodani, Richard Grubb, Jeff Johnson, Paul Loto’ainu, Alysha Reinard, William Rowland, and Meg Tilton were part of a team awarded a Department of Commerce Gold Medal in 2016 for their work on the Deep Space Climate Observatory mission, NOAA’s first operational space weather satellite. The CIRES scientists were critical to a team from the National Weather Service and the National Environmental Satellite, Data, and Information Service.

CIRES Gold Medal for scientific/engineering achievement
Gilbert Compo, Chesley McColl, and Prashant Sardeshmukh were part of a team in NOAA’s Physical Sciences Laboratory recognized with a Department of Commerce Gold Medal in 2016. Compo, Sardeshmukh and McColl and NOAA’s Jeff Whitaker created the 20th Century Reanalysis, a pioneering reconstruction of global weather and extremes using only surface pressure observations.

CIRES Bronze Medal for scientific/engineering achievement
Many CIRES scientists were part of a multi-institutional team that won a Department of Commerce Bronze Medal in 2017, for the El Niño Rapid Response Field Campaign. Federal and CIRES scientists in the Physical Sciences Laboratory of NOAA, the Aircraft Operations Center, and the NOAA ship Ronald H. Brown were involved in the mission.

Other State, Federal, and International Awards

International Awards
Waleed Abdalati, CIRES Director, Department of Geography, was selected to give the Tyndall Lecture at the December 2016 meeting of the American Geophysical Union: “Earth from Space: The Power of Perspective”

Jeffrey Deems, National Snow and Ice Data Center, received a visiting fellowship to work with the Snow Hydrology Research Group at the Swiss Federal Institute for Snow and Avalanche Research, in Davos, Switzerland.

Lisa Dilling, Director of CIRES’ Western Water Assessment, won the Leverhulme Visiting Professor Award from the UK Leverhulme Trust.

Bob Evans of NOAA’s Global Monitoring Laboratory received the Joseph C. Farman Award, from the International Ozone Commission, granted to outstanding scientists who have created and used high-quality, long-term time series of atmospheric measurements.

Florence Fetterer in the National Snow and Ice Data Center was a co-recipient of the Alan Berman Research Publication Award from the Naval Research Laboratory for a 2015 publication in Cryosphere. Fetterer also was part of the team awarded the 2016 International Data Rescue Award in the Geosciences from Elsevier and the Interdisciplinary Earth Data Alliance for their efforts in digitizing the Roger G. Barry Archive.

Noah Fierer, Jose-Luis Jimenez, Julienne Stroeve and Mark Serreze were recognized as “2016 Highly Cited Researchers” by Clarivate Analytics.

R. Michael Hardesty, affiliated with NOAA’s Chemical Sciences Laboratory, won a lifetime achievement award from the International Coordination-group for Laser Atmospheric Studies for “sustained outstanding and innovative achievements in the areas of lidar techniques, technologies, and observations.”

Birgit Hassler in NOAA’s Chemical Sciences Laboratory received the Dobson Award from the International Ozone Commission, for an early career scientist who published outstanding work in the atmospheric sciences.

Dale Hurst in NOAA’s Global Monitoring Laboratory, won the World Meteorological Organization’s Professor Vilho Väisälä Award for an outstanding research paper.
Jennifer Kay, CIRES Fellow, Department of Atmospheric and Oceanic Sciences, earned the American Meteorological Society Henry G. Houghton Award, given to promising young or early-career scientists who have demonstrated outstanding ability.

Lora Koenig of the National Snow and Ice Data Center was elected by the cryospheric community to serve as President of the American Geophysical Union’s Cryosphere Focus Group.

Larisza Krista, who works in National Centers for Environmental Information, served as keynote Speaker at the Royal Astronomical Society Specialist Meeting, Royal Astronomical Society (UK).

Stuart McKeen in NOAA’s Chemical Sciences Laboratory was part of a team awarded the 2016 Haagen-Smit Award Elsevier Press for an exceptional paper published in the journal Atmospheric Environment.

Judith Perlwitz, CIRES Fellow, NOAA Physical Sciences Laboratory, was elected a Fellow of the American Meteorological Society.

Irina Petropavlovskikh, in NOAA’s Global Monitoring Laboratory, was elected as Secretary of the International Ozone Commission—a 4-year, once-renewable position of leadership.

Allen Pope, National Snow and Ice Data Center, was named as one of “Sixteen Young Leaders Who Will Influence the Future of the Arctic” by the digital journalism project Arctic Deeply.

Anne Sheehan, CIRES Fellow, Geological Sciences, won the Zealand Geophysics Prize, given by the Royal Society of New Zealand.

Lesley Smith in the CIRES Education and Outreach group, was honored as a Fellow of the Association for the Sciences of Limnology and Oceanography.

Nikolay Zabotin of NOAA Physical Sciences Laboratory was elected to senior membership to the IEEE.

National and Other
Ravan Ahmadov, William Dubé, Jessica Gilman Abigail Koss, Brian Lerner, Rui Li, Stuart McKeen, David Parrish, Christoph Senff, Colm Sweeney, Chelsea Thompson, Patrick Veres, Rebecca Washenfelder, Carsten Warneke, and Bin Yuan from NOAA’s Global Monitoring and Chemical Sciences Laboratorys were co-authors on a paper that received an Outstanding Scientific Paper award in 2017, from the NOAA Office of Oceanic and Atmospheric Research. The paper, published in Nature in 2014, was “High winter ozone pollution from carbonyl photolysis in an oil and gas basin,” DOI:10.1038/nature13767.

Audra McClure-Begley, Geoff Dutton, Emrys Hall, Alexander Haugstad, Eric Hintsa, Dale Hurst, Allen Jordan, Richard Mclaughlin, Fred Moore, David Nance, Andrew Rollins, Troy Thornberry, and Laurel Watts in NOAA’s Global Monitoring Laboratory, were part of a team that earned a Group Achievement Award from NASA for the ATTREX (Airborne Tropical Tropopause Experiment) mission to advance understanding of the physical processes of the tropical tropopause layer and its role in the Earth’s climate.

Christopher Bond, Daniel Crumly, Amanda Leon, and Siri Jodha S. Khalsa in the National Snow and Ice Data Center were part of the SMAP (Soil Moisture Active Passive) Science Data System Team awarded a NASA Group Achievement Award.

Aditya Choukulkar, Emiel Hall, Mike Hardesty, Gary Hodges, John Holloway, Gerd Hubler, Guillaume Kirgis, Kathleen Lantz, and Christoph Senff, NOAA-based scientists in the Global Monitoring and Chemical Sciences Laboratorys, were part of a team who shared a NASA Group Achievement Award for their work on the DISCOVER-AQ mission (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality).

Dave Costa, Leslie Hartten, Darren Jackson, Paul E. Johnston, Don Murray, and Dan Wolfe in NOAA’s Physical Sciences Laboratory, were part of a NOAA team recognized with the NOAA Research Employees of the Year award, not available to non-federal scientists. The group of federal and cooperative institute scientists was honored for rapidly implementing and supporting a complex, multi-platform, multi-organizational field campaign to observe a rare, high-intensity El Niño event in the central, equatorial Pacific.

Raina Gough, Margaret Tolbert Group, was elected by NASA to serve as a “Participating Scientist” on the Mars Science Laboratory mission, 2016-2019.

Leslie Hartten in NOAA’s Physical Sciences Laboratory was honored with the NOAA Office of Oceanic and Atmospheric Research’s Diversity Award for exemplary service, serving as a mentor to many interns from various ethnic backgrounds at NOAA Boulder throughout the years.

Jose-Luis Jimenez, CIRES Fellow, Department of Chemistry and Biochemistry, was elected as a Fellow of the American Association for Aerosol Research (AAAR).

Jennifer Kay, CIRES Fellow, Department of Atmospheric and Oceanic Sciences, earned a National Science Foundation (NSF) CAREER Award, the NSF’s most prestigious award in support of junior faculty who exemplify the role of teacher-scholars.

Amanda Leon, in the National Snow and Ice Data Center, was part of an interagency team working on the NASA Soil Moisture Active Passive (SMAP) Applications Program, which won the Federal Laboratory Consortium’s Interagency Partnership Award.

Peter Molnar, CIRES Fellow, Geological Sciences, gave named lectures at Utah State University (Forster Lecture) and Lamont-Doherty Earth Observatory, Columbia University (Jardetzky Lecture).

Anne Perring in NOAA’s Chemical Sciences Laboratory, was awarded a Presidential Early Career Award for Scientists and Engineers (PECASE) in early 2017, one of 102 young scientists and engineers to receive this recognition. The PECASE is the highest honor bestowed by the U.S. government on early career scientists.

Jennifer Taylor in CIRES’ Education and Outreach was part of a team awarded the Climate Education and Resiliency for Denver Public Schools category of the CU Office for Outreach and Engagement Outreach Award for Interdisciplinary/Interdepartmental Faculty Groups.

Ronald Weaver, principal investigator and manager of the Snow and Ice Distributed Active Archive Center (DAAC) at CIRES’ National Snow and Ice Data Center, was one of nine people honored by the University of Colorado Boulder Regents in 2016. Weaver was awarded the University Medal in recognition of his lasting contributions to climate research and data management.

Systems & Predictions Models Development

Mobile surface radiation (SURFRAD) site operated by NOAA's Global Monitoring Laboratory Radiation Group located on the dry bed of northern Arizona’s Red Lake. Instrumentation is measuring the surface radiation budget.  2017 photo: Gary Hodges/CIRES and NOAA

GMD-01: Collect, Archive, and Analyze Global Surface Radiation Network Data

CIRES Lead: Gary Hodges

NOAA Lead: Joseph Michalsky

NOAA Theme: Climate Adaptation and Mitigation

Goals & Objectives: 

This project provides long term data for a network of sites on the amount of solar irradiation that reaches the Earth’s surface, including potentially harmful ultraviolet radiation. These measurements will indicate the mitigation strategies that might be necessary to maintain acceptable UV exposure and total irradiation exposure that is not excessively perturbed by human activity.

Accomplishments:

Since the last project update, we have completed the installation of new Multi-Filter Rotating Shadowband Radiometers (MFRSRs) and Multi-Filter Radiometers (MFRs) at all the fixed NOAA Global Monitoring Laboratory Radiation Group surface radiation (SURFRAD) stations. These spectral instruments include a 1625 nm channel that will provide better accuracy in the retrieval of aerosol optical properties, along with improvements in the measurement of other atmospheric variables. With paired units (MFRSR and MFR) at each site, we can now calculate spectral surface albedo. Effort is now underway to work through the data corrections and calibrations necessary to produce high-quality albedo data sets.
Along with the new spectral instruments, all SURFRAD stations now have an improved instrument for measuring direct normal broadband solar radiation. The new instrument will improve the uncertainty of that measurement by 50 percent, which is particularly significant as direct normal shortwave is about 90 percent of the of the total shortwave reaching Earth’s surface. To further improve our broadband shortwave and longwave measurements, we have replaced AC fans with DC units for all the ventilated instruments. The new DC fans produce less heat and move more air, which improves an intrinsic problem in these types of measurements known as the nighttime offset error.
Motivated by, and in conjunction with the new instrumentation, we made substantial site infrastructure improvements in the prior year. The SURFRAD program is a long-term measurement network, and it is crucial it operates with very little downtime. The effort put into the infrastructure is foundational to the success of the program, so the materials used and careful planning is in consideration of decades into the future, and not just “years.”
About five years ago, our Global Monitoring Laboratory Radiation Group assembled two mobile SURFRAD stations to be used in focused field campaigns in support of a wide variety of scientific research. In the past year, one station was operating in eastern Oregon in support of an experiment to improve wind forecasting in complex terrain. This short-term experiment has concluded and the station was removed in May. The other mobile station was removed from a location near Alamosa, Colorado. This station had provided valuable data to help improve short-term cloud forecasts in support of photovoltaic power generation. Now, it has been set up on a dry lake bed in northern Arizona to provide surface data for a validation study of the new GOES-16 satellite that was launched November 19, 2016.
With few exceptions, the mobile SURFRAD stations are identical in capability as the seven fixed sites. The data provided by these stations are core measurements for the science pursued, and in particular as input to the variety of computer models we employed in these studies.

This graphic shows the increasing density of weather data sources provided by MADIS to NOAA weather forecasters and the global weather forecasting community. The number of data sources has increased from about 20,000 to 64,000 during the development of this new data tool. Image: CIRES and NOAA

GSD-01: Innovative Weather Data Delivery Systems

CIRES Lead: Leon Benjamin

NOAA Lead: Gregory Pratt

NOAA Theme: NOAA Engagement Enterprise

Goals & Objectives: 

This project maintains and improves the advanced weather forecasting system and assures its accessibility for broad national use.

Accomplishments:

Our group’s Meteorological Assimilation Data Ingest System (MADIS) ingests data from NOAA data sources and non-NOAA providers, decodes the data, adds quality control, then encodes all of the observational data into a common format with uniform observational units and time stamps. It is also a conduct to transition observational projects from research to National Weather Service (NWS) operations. Our accomplishments in the last year include:

• Transitioning the NWS's Hydrometeorological Automated Data System (HADS) system into a high security system from a medium system and incorporated it into MADIS. This included adding automated processing updates, verification, and back-out system to update sites changes. This process followed the security rules to allow HADS to add and change sites during critical weather conditions when all changes normally are frozen. It is during those critical weather times that HADS has the greatest need to add new observations for life and safety reasons.
• Running Clarus quality control in MADIS at operations. It is being beta tested and is slated for official release in late 2017.
• Transitioning amdar.noaa.gov into MADIS, in which much work was done. MADIS was officially assigned the gate keeper role in vetting aircraft data access. We are still in the process of moving the amdar.noaa.gov websites.
• Quality controlling providers and sites that are constantly being added to MADIS. MADIS currently quality controls more than 3,000,000 observations per hour.
• Transitioning the creation of the Snow Telemetry (SNOTEL) NOAAport message. It is currently in beta testing and slated for operationalization in summer 2017.
• Transitioning the aircraft Eddy Dissipation Rate observations into NWS operations.
• Acting as the conduit to transition the GPS precipitable water (PWV) raw data from a private provider to NOAA and NWS forecasters.

The HRRR3 has improved convective forecasts from the operational version, HRRRv2. The figure shows the 13-h forecast for a storm system along a weak forced dryline from HRRRv3 (left panel) and HRRRv2 (right panel). Observed reflectivity (middle panel) shows the new HRRRv3 forecast has improved both storm structure and location. Image: RAP/HRRR development team in CIRES/NOAA

GSD-03: Improving Numerical Weather Prediction

CIRES Lead: Ming Hu

NOAA Lead: Georg Grell

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

This project focuses on improvements in numerical weather prediction by use of models through improved model design and implementation and optimal use of new and existing observations.

Accomplishments:

On August 23, 2016, we made the third version of Rapid Refresh (RAPv3) and the second version of the High-Resolution Rapid Refresh (HRRRv2) operational at the National Centers for Environmental Prediction of the National Weather Service.

Since then, we have made improvements for the next round of code updates in RAP and HRRR, including:

• adaption of a new hybrid vertical coordinate option in the Weather Research and Forecasting (WRF) Model,
• better representation of boundary-layer processes and sub-grid stratiform clouds in model physics,
• further increase in the ensemble weight in the Gridpoint Statistical Interpolation (GSI) hybrid analysis,
• addition of several new satellite radiance datasets,
• reduction of latent heating strength for RAP radar reflectivity assimilation,
• enhancements for Global Systems Laboratory cloud analysis, and
• surface observation assimilation near coast-lines.

The updated code had been well tested and showed improvement over RAPv3/HRRRv2 in prediction of temperature, relative humidity, winds aloft, and precipitation. The HRRR also showed substantial improvement in forecasts of conviction during the first six hours of the forecast.
In the summer and fall of 2016, we initiated experimental HRRR forecasts over Alaska, Hawaii, and Caribbean domains, with a 3-hour update frequency and 36-hour forecast length. Since early 2017, we have run a formal HRRR ensemble (HRRRE) in real time, providing probabilistic hazard guidance for heavy precipitation, intense snowfall, and severe thunderstorms. We evaluated HRRRE real-time ensemble forecasts during the Verification of the Origins of Rotation in Tornadoes EXperiment-Southeast (VORTEX-SE) field project, and the National Severe Storm Laboratory/ Storm Prediction Center (SPC) Spring Experiment.
Our work continued with development and refinement of a variational cloud analysis, a cloud assimilation procedure for camera data, and with Real-time Mesoscale Analysis and Rapidly Updating Analysis packages.
The team continued to improve reliability of probabilistic forecasts from the HRRR time-lagged ensemble (HRRR-TLE), notably through dynamic bias correction of precipitation forecasts. The HRRR-TLE product suite has been expanded to include aviation and fire weather concerns.
We have started working with the global Finite Volume Cubed-Sphere Dynamical Core (FV3) model in many aspects including physics package, software engineering, and more. Some of our team members are participating the sub-seasonal forecast project at the Climate Prediction Center of the National Centers for Environmental Prediction. We have delivered a set of multi-year hindcast model outputs, and the real time experiments will start soon.
Our verification team has augmented the modeling development verification system to add new regions for Alaska and Hawaii, to add new models new projections and new forecast hours, to implement verification for HRRR ensembles, and to implement a new algorithm for radius-categorical verification.

2017 xJet Compute System Expansion. Photo: Eric Schnepp/NOAA

GSD-05: Development of High-Performance Computing Systems

CIRES Lead: Eric Schnepp

NOAA Lead: Forrest Hobbs

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

This project will allow environmental applications of advanced computing to assimilate and use new technical developments in the field of high performance computing.

Accomplishments:

Over the past year, our researchers have helped support NOAA’s High Performance Computing (HPC) team in the Global Systems Laboratory (GSL). Work spanned several areas, including new system acquisition and planning, application optimization, software development, and user management and support.
In 2016, NOAA acquired an expansion to an existing HPC system to support the computational needs of Hurricane Forecast Improvement Project (HFIP) users. Our role in this acquisition included defining requirements, performing trade-off studies, system validation, and performance testing. The expansion increased xJet from 8,064 to 19,584 compute cores and represents a 23 percent increase in overall computational performance at GSL. In addition to the compute system expansion, NOAA acquired a 1-petabyte capacity expansion to one of three existing High Performance File Systems (HPFS), representing a 22 percent increase in overall HPFS storage at GSL.
Rocoto, a software system designed to help NOAA scientists improve the reliability of their computational experiments on NOAA’s HPC systems, saw important bug fixes and performance enhancements. An increasing number of NOAA’s GSL and HFIP scientists rely on Rocoto to help them construct complex job workflows that reliably complete. Also, other NOAA labs, including NCEP’s Environmental Modeling Center, have adopted Rocoto as a viable alternative to ecFlow for critical projects.
One of the more important experiments that we support on the HPC systems at GSL is the annual real-time hurricane season experiments for HFIP. The goal of this experiment is to demonstrate their ability to deliver improved hurricane forecasts. Our responsibility is to develop the tools and techniques for HFIP scientists to use so that their experiments can run reliably and on-time. Rocoto is a big part of this process. Well before the peak of hurricane season, we implemented a complex system based on reservations that guaranteed system resources to HFIP projects when needed. We closely monitored system utilization and reservation usage during the real-time hurricane season. During periods of low storm activity, we provided tools to HFIP projects to allow them to release unneeded resources, thereby letting the rest of the research and development community to execute as resources became available.

Example of a Terminal Radar Approach Control Gate Forecast of the impact of thunderstorms on arrival and departure route sectors for Atlanta (left image: courtesy of the Aviation Weather Center) and the corresponding TRACON Gate Forecast Verification Tool (right image: NOAA/CIRES).

GSD-06: Verification Techniques for Evaluation of Aviation Weather Forecasts

CIRES Lead: Matthew Wandishin

NOAA Lead: Jennifer Mahoney

NOAA Theme: Weather Ready Nation

Goals & Objectives: 

This project contributes to the prediction of specific weather related threats to aviation, thus potentially enhancing the safety of aviation.

Accomplishments:

Our evaluation of the global Graphical Turbulence Guidance (GTG-G) was delayed due to miscommunication between the product developer and the National Centers for Environmental Prediction (NCEP), who will be incorporating the algorithm into their global model post-processing suite. We held several coordination meetings with the United Kingdom Met Office (UKMO), NCEP, and the Aviation Weather Center (AWC) to establish an agreed upon plan for evaluating the new product in the context of the World Area Forecast System (WAFS) turbulence forecasts. We also began implementation of the GTG-G verification plan.
We completed the assessment of the Icing Product Alaska-Forecast (IPA-F) and reported it to the Federal Aviation Administration and the Alaska Aviation Weather Unit. Overall IPA-F provides an improved forecast over the current operational product, but some issues with IPA-F were noted and are being addressed by the product developers.
We nearly completed an assessment of the follow-on Icing Product Alaska-Diagnostic (IPA-D) nowcast during the reporting period, with the final reporting to be given in June. We found IPA-D provided little value above that which is available from IPA-F.
Our team completed an evaluation of the automated version of the Collaborative Convective Forecast Product (CCFP); the forecasts were found to perform better during the 2016 convective season than it did in the previous year, likely due to upgrades in the underlying models. Despite this improvement, the performance was still below the level that the human forecasters used to achieve (there were no human CCFP forecasts in 2015 and 2016).
We completed the Terminal Radar Approach Control (TRACON) Facilities Gate Forecast Verification Tool expansion to additional airports. A planned further expansion to include human forecaster adjustments to the automated forecast was delayed because of a delay in the implementation at AWC of the human component of the forecast and a lack of forecaster involvement.
The verification tool for wind-shift forecasts at airports is still in development. We held many consultations with National Weather Service management to establish agreed upon definitions of significant wind-shift events.
Our team conducted extensive research into suitable observations against which to verify the Ensemble Prediction of Oceanic Convective Hazards (EPOCH) forecast product. There is no single product that provides a reliable observation of convection at a global scale. As a result, we will need to combine several observation sets to assess the performance of the EPOCH forecasts.
Similar to with the GTG-G product, meetings were held with NCEP, the UKMO, and AWC to establish a verification plan for the EPOCH product in the context of the WAFS thunderstorm forecast product.
We are incorporating three web-based verification tools developed by the Forecast Impact and Quality Assessment Section—the Central Weather Service Unit Briefing and Verification Tool, the TRACON Gate Forecast Verification Tool, and the Event-based Verification and Evaluation of NWS gridded products Tool—into a common system knows as the Verification Services for Aviation Forecast Evaluation (VSAFE). VSAFE is planned for transition to the NWS to support verification of aviation forecasts supporting traffic flow management.
Our group completed core research projects on an object-oriented approach to verifying forecasts of convective initiation and on the application of a cluster-based presentation of forecast scenarios to a convective-allowing ensemble, as well as an investigation into observation platforms that can serve as truth sets for global convection.

GSD-07: Numerical Prediction Developmental Testbed Center

CIRES Lead: Ligia Bernardet

NOAA Lead: Stan Benjamin

NOAA Theme: Weather Ready Nation

Goals & Objectives: 

This project is directed toward maintenance and improvement of the hurricane prediction system and is supportive of government agencies and public information systems that provide hurricane warning.

Accomplishments:

CIRES and collaborators continued to act as a bridge between research and NOAA operations in the field of numerical weather prediction. Our activities focused on two fronts: O2R (transition of operational capabilities to the research community) and R2O (test, evaluation, and transition of new research and developments to operations).

Our accomplishments included:

• Public release and support of the HWRF (Hurricane Weather Research and Forecasting) model and GSI (Gridpoint Statistical Interpolation) data assimilation system. This involved testing code for public releases, creating and updating documentation and instructional materials, conducting tutorials, and answering questions from users.
• Support to the developers of the HWRF and GSI codes, by chairing developers' committees, conducting code management, and providing assistance in adding new capabilities to the software.
• Advancement of the CCPP (Common Community Physics Package), a library of physical parameterizations for use in NWP systems, by collecting requirements, formulating a design, and creating a beta version which includes an IPD (Interoperable Physics Driver) that can be used to connect the physics to a variety of models.
• Establishment of a hierarchical "test harness" for assessment of global models. This includes capability to run the GFS (Global Forecast System) in cycled data assimilation mode and produce diagnostics (water and energy budget, tropical cyclogenesis etc.) to inform model development.
• Development of a draft protocol for innovations in physical parameterizations to be transitioned from the research community to the NOAA operational global forecast system.
• Assessment of new capabilities for R2O, including
  • Regional 4D-EnVar (four-dimensional ensemble-variational data assimilation).
  • Alternate cumulus parameterization for HWRF and GFS.
  • Updates to the HWRF partial cloud parameterization and cloud overlap algorithm.
• Publishing a newsletter to inform the community of the activities undertaken by DTC.

References

Bernardet, L., L. Carson, and V. Tallapragada, 2016. The design of a modern information technology infrastructure to facilitate research to operations transition for NCEP’s modeling suites. Bull. Amer. Meteor. Soc., submitted.
Shao, H., J. Derber, X.-Y. Huang, M. Hu, K. Newman, D. Stark, M. Lueken, C. Zhou, L. Nance, Y.-H. Kuo, B. Brown, 2015: Bridging Research to Operations Transitions: Status and Plans of Community GSI. Bull. Amer. Meteor. Soc. DOI: http://dx.doi.org/10.1175/BAMS-D-13-00245.1
Tallapragada, V., L. Bernardet, M. K. Biswas, I. Ginis, Y. Kwon, Q. Liu, T. Marchok, D. Sheinin, B. Thomas, M. Tong, S. Trahan, W. Wang, R. Yablonsky, X. Zhang, 2016: Hurricane Weather Research and Forecasting (HWRF) Model: 2015 Scientific Documentation. NCAR Technical Note NCAR/522+STR, 116 pp. Available at http://opensky.ucar.edu/islandora/object/technotes:535.

GSD-09: Improve the AWIPS Weather Information System

CIRES Lead: Paul Schultz

NOAA Lead: Mike Kraus

NOAA Theme: NOAA Engagement Enterprise

Goals & Objectives: 

This project focuses on developing forecast tools for NWS forecasters using the AWIPS-2 system. It is directed at the computer user interface issues presented by advancements in (primarily weather) data technology, and by evolving practices in weather forecasting operations.

Accomplishments:

We made substantial improvement to the usability, performance, and stability of the Matrix Navigator, an AWIPS tool that allows forecasters to make quick comparisons between alternative forecast scenarios. We also refactored the entire Ensemble Tool for readability, and to ensure the contractor, Raytheon, could efficiently maintain it. We added two new features. The first makes images from contour products, which is expected to improve the utility of the spaghetti tool as the basis for user-custom decision support graphics. The second allows forecasters to efficiently mine the ensemble solution space for details not seen in default contour values; it allows the user to choose a specific contour, then change and redraw it one small increment at a time. These tasks were given highest priority by National Weather Service (NWS) forecasters who attended NOAA’s Forecaster Decision Support Environment workshop in September 2016, in Boulder, Colorado. A progress report was given to the annual convention of the American Meteorological Society in Seattle, Washington.

GSD-11: Improve RAP/HRRR for Wind and Solar Forecasts

CIRES Lead: Joe Olson

NOAA Lead: Melinda Marquis

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

This project focuses on improving the skill of Rapid Refresh and High-Resoluation Rapid Refresh forecasts of low-level winds and downward shortwave radiation, which are both useful for the electric power system.

Accomplishments:

We developed the boundary layer scheme used in the Rapid Refresh (RAP) and the High-Resolution Rapid Refresh (HRRR) including improvements to the local mixing in stable conditions and the addition of non-local mixing for unstable conditions. We accomplished the former by redesigning the formulation of the mixing length scales to better control the magnitude throughout a wide range of atmospheric conditions. And we accomplished the latter by the addition of a new mass-flux scheme. Both components demonstrated improvement over the previous version of the RAP and HRRR and were included in the code transfer to the National Center for Environmental Prediction for the next generation operational versions of the two models.
Another major accomplishment of our team was the addition of a hybrid vertical coordinate (HVC) to the RAP and HRRR. Our purpose was to reduce artificial numerical mixing caused by the traditional terrain-following vertical coordinate. The HVC code, originally written by colleagues at the National Center for Atmospheric Research (NCAR), was integrated into the RAP/HRRR code repository. Further code required the data assimilation, boundary condition updating, and post-processing software. We tested the code in both the RAP and HRRR for a set of retrospective simulation sampling all four seasons. Our results show that the majority of the improvement is in the upper-tropospheric temperature and relative humidity, with little or no impact in over variables or at other levels of the atmosphere. Although we found no improvement for low-level winds, the improvements to the upper-level humidity can translate into improved cloud forecasts over complex terrain, resulting in small positive improvements in forecasts of downward shortwave radiation.
Stochastic physics is a promising approach to help improve the spread and skill of ensemble forecast systems, providing forecasters with probabilistic information along with traditional deterministic forecasts. The implementation of stochastic parameter perturbations (SPP) into the RAP/HRRR physics, geared specifically for improving the spread of low-level winds and downward shortwave radiation, may provide valuable probabilistic information for the renewable energy industry. We made code changes in MYNN PBL (Mellor-Yamada-Nakanishi-Niino level 2.5 planetary boundary layer), surface layer scheme and RUC LSM (Rapid Update Cycle land surface model) to include SPP. Our team performed ensemble tests to determine optimal spatial and temporal decorrelation length scales. Our results from HRRR-based ensemble shows that SPP helps to improve the ensemble spread. With the addition of other traditional stochastic approaches, it is likely that the HRRR ensemble will be able to attain similar spread as other multi-physics ensembles but maintain better skill. We have outlined future work to achieve this goal.

Project NCEI-12 closed in 2016 due to NOAA reorganization.

Sea surface salinity computed in two coupled atmosphere-ocean configurations of NASA ModelE, developed at the NASA Goddard Institute for Space Studies. The top image shows the original ModelE code. The middle image shows the code after it was modularized and components were fitted with standard interfaces based on the Earth System Modeling Framework (ESMF). This standardization will enable modelers working with ModelE to exchange components more easily with other models at NASA and in the broader community. The bottom image shows the difference in values between the two configurations. Image: Carlos Cruz/NASA Goddard

GSD-12: NOAA Environmental Software Infrastructure and Interoperability Project

CIRES Lead: Cecelia DeLuca

NOAA Lead: Dave Zezula

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

The project advances understanding and improves predictions of the Earth system by delivering infrastructure software that enables new scientific discoveries, fosters inter-agency collaborations, and promotes resource efficiency.

Accomplishments:

Our Environmental Software Infrastructure and Interoperability (NESII) project continued to develop and deploy community model infrastructure software, working toward the goal of coordinating modeling activities across agencies.
During the last year, we made improvements in NESII products including the Earth System Modeling Framework (ESMF) software for building and coupling models and the National Unified Operational Prediction Capability (NUOPC) Layer, an extension to ESMF that increases the interoperability of model components across centers. Our team worked closely with teams at NOAA, NASA, Navy, the National Center for Atmospheric Research (NCAR), other federal centers, and universities to implement and update ESMF and NUOPC Layer software interfaces in their coupled modeling systems.
One of our goals for this year was to expand the collection of model components that conform to ESMF and NUOPC Layer interfaces, called the Earth System Prediction Suite (ESPS). An important addition to the ESPS this year was a new atmospheric model called the Finite Volume 3 Global Forecast System (FV3GFS). This atmospheric model will be included in numerous NOAA applications (for example, weather forecast, hurricane, seasonal) that are connected by a new unified modeling system for National Weather Service operations. The unified modeling system, or NEMS (NOAA Environmental Modeling System) is based on ESMF and NUOPC Layer coupling tools. Our first release of the FV3GFS under NEMS was in May 2017.
We collaborated with the NOAA Environmental Modeling Center (EMC) and other partners to deliver milestones for other applications running under NEMS. Our deliveries included improvements to a coupled atmosphere-ocean-ice seasonal prediction system, a coupled atmosphere-ionosphere system, a coupled atmosphere-ocean hurricane forecast system with moving nests, and a coupled atmosphere-wave system. These new milestones reflect additional feedbacks and greater physical fidelity.
Other milestones we achieved included a coupled atmosphere-ocean code based on NASA’s ModelE using the NUOPC Layer infrastructure, and a coupled regional atmosphere-land-ocean-hydrology code for the Navy. We collaborated with the Navy, NCAR, and university partners to complete a 20-year run of the Community Earth System Model (CESM) coupled to a high-resolution ocean. For a new project with CESM, EMC, and the Geophysical Fluid Dynamics Laboratory (GFDL), we will develop a multi-scale community NUOPC Layer-based coupler that these centers can share.
In addition to developing modeling infrastructure and the ESPS, we also continued to support data infrastructure for the Coupled Model Intercomparison Project 6 (CMIP6), an international effort that is the basis for climate assessments like the Intergovernmental Panel on Climate Change (IPCC). The CoG collaboration environment, developed by NESII, has become the primary U.S. interface for downloading data from the preceding experiment, CMIP5, and will be used for CMIP6. CoG is part of a federated data distribution environment managed by the Earth System Grid Federation, an international consortium. The main CoG installation is at CU Boulder, but there are separate CoG installations in France, Sweden, Germany, the U.K, U.S. federal labs, and other countries. Our team also delivered an extensive model metadata questionnaire for collecting information about the CMIP6 models.

Space Weather Understanding & Prediction

Comparison of (top) 10–100 MeV and (middle) 30–100 MeV integral fluxes observed by STEREO and GOES 11 during the December 2006 solar proton events. The GOES 11 integral fluxes are calculated by using the NOAA SWPC method and by using the cross-calibrated effective energies validated by this paper. (bottom) The solar wind dynamic pressure (Pdyn) from the NASA OMNI data set. All data here are 1 h averages. Image: Rodriguez et al. 2017.

NCEI-06: Satellite Anomaly Information Support

CIRES Lead: Juan Rodriguez

NOAA Lead: William Denig

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

Data and research from this project will be used to provide space environmental data and tools to satellite operators and designers.

Accomplishments:

This year, we contributed to the Satellite Anomaly Information Support project primarily through the publication of two peer-reviewed publications.
In the first publication (Rodriguez et al., 2017), we led an international team in the validation of a previously-published cross-calibration of the Geostationary Operational Environmental Satellite (GOES) solar proton data. This validation effort took advantage of a serendipitous series of solar proton events that occurred days after the launch of the two NASA Solar Terrestrial Relations Observatory (STEREO) spacecraft, while they were orbiting around the Earth just prior to the lunar swing-by that sent them into their separate orbits around the Sun. With their fine energy resolution, the STEREO solar proton measurements could be used to validate the cross-calibrations performed against the earlier NASA Interplanetary Monitoring Platform (IMP)-8 measurements of comparably fine energy resolution. We found that the STEREO observations agreed well with the cross-calibrated GOES observations, thereby establishing the accuracy of the earlier cross-calibrations. An important consequence of this result is that current GOES integral fluxes used by the NOAA Space Weather Prediction Center (SWPC) in their solar radiation storm alerts are too high by up to a factor of 3 (at >100 MeV). This paper received an Editors’ Highlight from the journal in which it was published.
Our team contributed to an NCEI publication (Redmon et al., 2017) in which a parametric charge accumulation model was used to determine whether a series of anomalies on the NOAA Polar Orbiting Environmental Satellites could be attributed to internal charging by >800 keV electron fluxes as originally proposed by NOAA. We found that internal charging now appears to be an unlikely root cause for this particular series of anomalies in the absence of an additional, enabling physical mechanism.

References:
Rodriguez, J. V., I. Sandberg, R. A. Mewaldt, I. A. Daglis, and P. Jiggens (2017), Validation of the effect of cross-calibrated GOES solar proton effective energies on derived integral fluxes by comparison with STEREO observations, Space Weather, 15, 290–309, doi:10.1002/2016SW001533.
Redmon, R. J., J. V. Rodriguez. C. Gliniak, and W. F. Denig (2017), Internal charge estimates for satellites in low earth orbit and space environment attribution, IEEE Transactions on Plasma Science, in press.

Example of the North American product on a five- by five-degree grid from 9/29/2016 at 08:43 UT created automatically and served on the Space Weather Prediction Center's public website. Image: NOAA

SWPC-01: Space Weather Information Technology and Data Systems

CIRES Lead: David Stone

NOAA Lead: Steven Hill

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

This project will determine the necessary research data systems and infrastructure required to successfully implement the empirical and physical scientific models of the space weather environment.

Accomplishments:

Our team successfully transitioned the University of Michigan’s Geospace Model into operations to serve NOAA’s Space Weather Prediction Center (SWPC) forecasters as well as power grid operators throughout the world. While the Geospace Model has diverse capabilities for specifying conditions in the near Earth space environment, the initial operational application is to specify regional geomagnetic activity at Earth’s surface (see image).
We transitioned the new North American total electron content (NATEC) U.S. and North America products to operations in order to serve single and dual frequency GPS applications. The model products are designed to specify vertical and slant TEC using a Kalman Filter data assimilation model in near real-time. These new changes include a larger assimilation grid and the addition of new GPS data in Alaska, Hawaii, Canada, and Mexico.
Our group assisted in the operational adaptation of a new real-time solar wind (RTSW) database schema that gives us the ability to easily switch between the aging Advanced Composition Explorer (ACE) satellite and the new DSCOVR satellite as sources for RTSW data. This work included retrofitting the remaining operational products which use RTSW data: Relativistic Electron Forecast Model (REFM), Aurora 30 minute forecast and Auroral 3-day forecast.
We deployed the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) Model total electron content (TEC) forecast product to our experimental website. This model illustrates the height of integrated electron density from the CTIPe model and aids the forecasters in nowcasting effects on GPS systems, satellite drag and electric power transmission.
We finished the last Red Hat Enterprise Linux (RHEL) 5 to RHEL 6 transition, which was for the ACE processor and its web products. This highly complex migration allowed SWPC to continue to operate under the tightening security requirements of the National Weather Service (NWS).
Our team provided timely operational support for the following critical systems and maintained a high customer satisfaction:

• SWPC’s public website
• Advanced Composition Explorer (ACE) processor
• Deep Space Climate Observatory (DSCOVR) ground data system
• Geostationary Environmental Satellite (GOES) processor and preprocessor
• WSA-Enlil model
• D Region absorption predictions (D-RAP)
• Air Force and Institute for Science and Engineering Simulation (ISES) message decoder (AIMED) processor
• Microsoft SQL server space weather data store (SWDS)

SWPC-02: Enhancement of Prediction Capacity for Solar Disturbances in the Geospace Environment

CIRES Lead: Alysha Reinard

NOAA Lead: Vic Pizzo

NOAA Theme: Weather Ready Nation

Goals & Objectives: 

This project will advance preparedness for solar storms affecting communication, transportation, and other U.S. infrastructure.

Accomplishments:

We have transfered the existing Global Oscillation Network Group (GONG) processing software to the Integrated Dissemination Program (IDP) and the software is working on their system. We are currently generating real-time magnetograms and H-alpha images. We have also been testing two methods for transfering data from the six GONG sites to the IDP. We have talked to the IDP about setting up an ftp webpage to provide the processed images and carrington maps to the Space Weather Prediction Center (SWPC) and other customers, in particular the National Center for Environmental Information (NCEI), the Air Force and the National Solar Observatory (NSO). These tasks have been delayed on the IDP side due to a backlog of projects that they are working through—this delay has affected our schedule. However, we now have the permissions needed to do our testing and we are working through validating the data products and determining which method of data transfer best meets our needs. We have been validating the data products by comparing the outputs produced by the IDP with the outputs produced at NSO. We have brought Jeff Johnson, a CIRES software engineer, onto the project to begin evaluating the software to (1) provide detailed knowledge of the processing software within SWPC and (2) identify potential improvements to the software. He has been getting up to speed on the project and will be traveling to Tuscon in June to get a detailed walkthrough of the software with the experts at the NSO.

Comparison of observed variability of total electron content (TEC) in 2012 (upper panel), derived from ground-based GNSS receivers, with results from WAM-IPE for June-July solstice (lower left panel) and for September-October equinox conditions. The peak values of TEC either side of the magnetic equator are associated with the equatorial ionospheric anomaly. The figure shows the seasonal change in variability, which is well represented by the model. The upper right panel illustrates that solar, geomagnetic, and lower atmosphere forcing contribute roughly equally to the variability. Image: CIRES/NOAA

SWPC-03: Analysis of the Role of the Upper Atmosphere in Space Weather Phenomena

CIRES Lead: Timothy Fuller-Rowell

NOAA Lead: Rodney Viereck

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

This project will use models to determine causes for variation in space weather, with implications for infrastructure protection.

Accomplishments:

In an effort to model the space weather system from the Sun to Earth, NOAA is transitioning three separate physical model components. These include the WSA-Enlil solar wind propagation model, the Michigan Geospace model of the magnetosphere (see SWPC-01), and a coupled model of the whole atmosphere and the ionosphere-plasmasphere-electrodynamics (WAM-IPE). We have already transitioned the first two of these components to operations at NOAA, and we will test the third component in an operational real-time setting in September 2017.
WAM is a whole atmosphere extension of the National Weather Service (NWS) Global Forecast System (GFS) operational weather model, which extends the top boundary from 60 km to ~600 km. WAM can also be run with the NWS data assimilation scheme for WAM to follow real changes in tropospheric weather. The WAM model is coupled to a new Ionosphere-Plasmasphere-Electrodynamics (IPE) model, using the Earth System Modeling Framework (ESMF), under the NOAA Environmental Modeling System. IPE is a time dependent, three-dimensional model of the ionosphere and plasmasphere. WAM provides us with the thermospheric properties of wind, composition, and temperature to the IPE, so it can respond to changes in terrestrial weather propagating upward and influencing the thermosphere. IPE will in turn provides time dependent, global, three-dimensional plasma densities for nine ion species, electron and ion temperatures, and both parallel and perpendicular velocities of the ionosphere and plasmasphere. IPE reproduces not only the climatology of global TEC observations, but the model also responds to changes in solar wind conditions during geomagnetic storms, and to terrestrial lower atmosphere changes, such as sudden stratospheric warmings (SSW). Our model follows the storm-time redistribution of plasma in the ionosphere and plasmasphere during an SSW, and the evolution of storm enhanced densities (SEDs) during a geomagnetic storm.
We have tested and validated the coupled WAM-IPE model with one-way coupling, where the winds, temperature, and composition from the neutral WAM code drive the IPE ionosphere. We have simulated several months with the one-way coupled model configuration to quantify the contribution of the three major sources of variability in the thermosphere-ionosphere system. These simulations demonstrated that during quiet-to-moderate geomagnetic activity, the three major sources—solar EUV radiation, geomagnetic, and lower atmosphere forcing—all contribute roughly equal amounts to the variability of thermosphere-ionosphere dynamics, electrodynamic, and plasma density.

North and south polar views of ground magnetic perturbations (dB) during a moderate Geomagnetic storm, as predicted by the University of Michigan Space Weather Modeling Framework (SWMF) model of the geospace environment. The model was transitioned at the Space Weather Prediction Center to full operations at the National Weather Service (NWS) on October 1st 2016. Image: NOAA SWPC

SWPC-04: Geospace Modeling Effort

CIRES Lead: George Millward

NOAA Lead: Howard Singer

NOAA Theme: Weather Ready Nation

Goals & Objectives: 

This project will use first-principles physics-based models to predict variations of space weather conditions in Earth’s near-space environment that affect critical infrastructure in space and on the ground.

Accomplishments:

Our aim has been to take the Space Weather Modeling Framework (SWMF) Geospace model, developed at the University of Michigan (UMICH), and transition it into full operations at the National Weather Service (NWS). The project has involved working closely with the model developers at UMICH to implement code and script changes needed for real-time, weather forecasting model usage. We have also worked with technical staff at the National Centers for Environmental Prediction Central Operation’s Production Management Branch (NCEP/NCO/PMB) on all aspects of the real-time system, including the ingestion of real-time satellite data used as model input and the dissemination of output products to the Space Weather Prediction Center and, for public consumption, to the web.
The 2016 NWS milestone for the project was to have an end-to-end system, fully operational, on the NWS supercomputers. We achieved this by the milestone date of October 1, 2016. Initial products included global maps of ground magnetic perturbations and estimations of global geomagetic indexes such as the planetary K value (Kp) and the Disturbance Storm Time Index (DST).
In May 2017 Millward was awarded a CIRES Science and Engineering Outstanding Performance Award “For Scientific creativity and resoursefulness in transitioning an academic-based geospace model into NOAA operations, serving space weather forecasters and power grid operators.”
 

Regional Sciences & Applications

CIRES researcher Guillaume Kirgis adjusts the TOPAZ laser system during the California Baseline Ozone Transport Study. Photo: Will VonDauster/NOAA

CSD-08: Remote Sensing Studies of the Atmosphere and Oceans

CIRES Lead: Christoph Senff

NOAA Lead: Alan Brewer

NOAA Theme: Weather Ready Nation

Goals & Objectives: 

This project will investigate atmospheric dynamics, including transport of atmospheric constituents over complex terrain, in coastal and open ocean regions, and from high altitudes to the surface. These studies have particular relevance to air quality, climate, ocean ecosystems, and renewable energy.

Accomplishments:

During the past year, our work under this project included studies to investigate transport processes of ozone in California, observe the wind and turbulence structure in the vicinity of wind farms, and improve the performance of the plankton-sensing NOAA Oceanographic Lidar.
We deployed the Tunable Optical Profiler for Aerosol and Ozone (TOPAZ) ozone lidar in late spring and summer 2016 to the San Joaquin Valley as part of the California Baseline Ozone Transport Study (CABOTS) to investigate the influence of trans-boundary ozone on surface air quality in the San Joaquin Valley, one of two “extreme” ozone non-attainment areas remaining in the United States. TOPAZ was located at the Visalia, California, airport and measured the vertical distribution of ozone during two, three-week intensive operating periods in May/June and July/August. We chose the two periods to contrast different ozone photochemical production and transport regimes.
We observed a complex, layered ozone structure above the San Joaquin Valley on most days of the study. These ozone layers aloft were attributed to regional, trans-Pacific, and stratosphere-to-troposphere transport. During the July/August intensive the primary source of ozone aloft was the Soberanes Fire that burned near Monterey, California. In most cases, these ozone layers were located above the top of the shallow (<1 km deep) boundary layer in the San Joaquin Valley and did not get mixed down to the surface. During CABOTS, transported ozone had only a limited impact on San Joaquin Valley surface air quality.
We continued around-the-clock observations of the wind field near wind farms in the Columbia River Gorge using two unattended NOAA Doppler lidars as part of the Second Wind Forecast Improvement Project, WFIP2. To help improve NOAA’s wind forecasts, we created two new data products: (1) a measurement uncertainty quantification framework, which was tested using data from previous experiments and was implemented in WFIP2 data processing, and (2) a new method to process the Doppler lidar data to retrieve wind profiles at a 1-km horizontal spacing along the scan direction of the lidar. The latter provides a powerful tool to study the evolution of the wind flow in complex terrain and to validate model forecasts of wind farm wakes.
We updated the NOAA Oceanographic Lidar with new amplifiers and tested a new detector. The new amplifiers have greatly improved the lidar’s performance, including better system calibration to allow quantification of chlorophyll concentrations in the Arctic Ocean.

Site study area. Image: Allen White/NOAA Physical Sciences Laboratory

PSD-19: Improving Wind and Extreme Precipitation Forecasting

CIRES Lead: Laura Bianco

NOAA Lead: Kelly Mahoney

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

This project will show how well models can predict air quality under specific weather conditions at locations where air quality typically is poor.

Accomplishmemts:

The Wind Forecast Improvement Project 2 (WFIP2) is a multi-institutional program to improve NOAA’s short-term weather forecast models and increase understanding of physical processes that affect wind energy generation in regions of complex terrain (Pacific Northwest with a focus on the Columbia River Gorge).
Our project builds on WFIP2 to:
(1) Enhance WFIP2 observations with a focus on moisture:
We investigate techniques for measuring humidity using wind profiling radars (WPRs) and microwave radiometers (MWRs). MWRs are passive instruments measuring integrated contents from atmospheric emissions. They retrieve profiles based on climatology (from nearby soundings) and neural network algorithms. These retrieval techniques work well for pressure and temperature, but less so for humidity. Clear-air radars (WPRs) are active instruments that emit signal that reflects off irregularities in the refractive index in the atmosphere. We can use the combination of MWR and WPR to calculate profiles of humidity. We are testing the technique on the data collected at the Boulder Atmospheric Observatory (BAO) in 2015. Testing is in progress and will be evaluated versus radiosonde launches available at the same site.
(2) Compute surface energy and moisture budgets:
We are evaluating soil moisture, local energy and moisture budgets at the Physics Site (5 km N-E from Wasco, OR). We have deployed the following observations especially for this project: soil moisture/temperature (in-situ measurements at 5, 10, 20, 50, 100 cm into the ground); GPS interferometric reflectometry (to derive near surface soil moisture with a new technique); near-surface meteorology; radiative fluxes; turbulent fluxes including evaporation and precipitation. Our approach is to compare observations with various models and investigate model improvements. We are investigating preliminary comparisons between the various observations to identify the behaviors of air temperature, soil temperature, soil moisture, and precipitation at this site.
(3) Improve quantitative precipitation estimation and quantitative precipitation forecasts:
To understand large-scale dynamics and moisture transport upstream and downstream of the Gorge, we have created a directory of storm-relevant quantities from the High Resolution Rapid Refresh model (HRRR, 3-km grid spacing). Eighteen storms with precipitation greater than about 1.5 inches over the mountains in Idaho have been found and carefully documented at http://www.esrl.noaa.gov/psd/people/dustin.swales/TheGorge/synoptics/ (including maps of integrated horizontal water vapor transport (IVT) and moisture convergence cross sections of moisture transport).
(4) Better understand moisture transport (atmospheric rivers, AR) throughout the Pacific:
To answer the question “how representative are Columbia Gorge AR extreme moisture flux cases?” we plan to place the extreme AR events in the context of past 150 years using 20th Century Reanalysis (20CR). Preliminary analysis on what better 20CR resolution has to be used for this purpose (20CR ver 2c at 2ox2o, or 20CR ver 3 at 0.5ox0.5o) are being conducted.
(5) Examine the influence of climate variability, especially tropical sea surface temperature (SST) on precipitation in this area:
We investigate the tropical influence on northwest U.S. precipitation. Our goal is to examine whether we can link variability in the precipitation field to the tropical climate (SST, subsurface ocean conditions) at different timescales, and identify the SST pattern(s) that are more conducive to precipitation variations in the northwestern United States (“sensitivity patterns”).

PSD-21: Develop and Prototype Experimental Regional Arctic Sea Ice Forecasting Capabilities

CIRES Lead: Amy Solomon

NOAA Lead: Janet Intrieri

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: 

A clearer separation of natural variations from anthropogenic influences in the climate system over the last 140 years will help explain climate variability better and improve the capacity for climate predictions.

Accomplishments:

This year, the NOAA-CIRES Sea Ice Forecasting team made daily quasi-operational 10-day forecasts of the 2016 Arctic Ocean freeze-up season (July-November) with an improved version of the Regional Arctic System Model (RASM-ESRL). We made the following model improvements for the 2016 freeze-up season:  updating the sea ice model, updating the land surface model, and replacing the mixed-layer ocean with a full dynamical ocean model to allow for the mixing of subsurface waters into the ocean mixed layer. We posted figures and animations of the daily forecasts on the NOAA/ESRL/PSD Experimental Sea Ice Forecast webpage (https://www.esrl.noaa.gov/psd/forecasts/seaice/) in real time, to allow users such as the NWS Alaska Sea Ice Program and the Arctic Testbed to assess the forecasts for use in their operations.
In addition, we ran a suite of hindcasts with a variety of initialization fields to identify the impact of ocean initial conditions on 10-day forecasts, and we completed studies to assess the performance of forecasts made during the 2015 freeze-up period. Diagnostics from these studies are posted on the NOAA/ESRL/PSD Experimental Sea Ice Forecast webpage.
In the off-season, the our team completed process-oriented diagnostics of observations from the 2015 ONR SeaState campaign (http://www.apl.washington.edu/project/project.php?id=arctic_sea_state) to be used for model verification. This work includes developing a novel approach to estimating sea ice thickness. We are using these observations to evaluate model simulations of ocean, sea ice, and atmospheric variability.
One objective we are completing in collaboration with the NOAA National Center for Environmental Prediction is determining to what extent a dynamical ocean model is required for subseasonal sea ice forecasts. Our preliminary results indicate that it is necessary to include the mixing of subsurface ocean water into the mixed layer for accurate forecasts, even on these short time scales. Our team is also working with the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) in Bologna, Italy to develop a state-of-the-art Arctic Ocean analysis for model validation and to forecast initial ocean conditions. This ocean analysis has horizontal resolution similar to the forecasts (10km). However, comparisons with the SeaState measurements indicate that the mixing of subsurface Pacific Ocean water into the mixed layer is underestimated in the analysis. This finding led to an additional collaboration with CMCC, where our team is compiling all available Arctic Ocean measurements for 2015 to be assimilated into the ocean analysis. We will determine if using the assimilated ocean analysis will improve the skill of the subseasonal forecasts.
Our team will also focus on simulating the impact of lower-level atmospheric jets. These jets may be playing an important role in the evolution of the sea ice by forcing strong winds and fluxes across the ice edge. We are using observations from the SeaState campaign to assess the model skill in simulating these jets and the RASM-ESRL model to determine the impact of these jets on the sea ice evolution.

Monthly SST trends during 1976-2099 for LMEs around North America. Trends computed for each model from the CMIP5 (red) and CESM-LENS (blue) experiments are shown in box and whiskers format, where the end points indicate the maximum and minimum values, the box boundaries are the inter-quartile (25% and 75%) range and the median is the central line. Image: Alexander et al (2017)

PSD-25: Linking Weather, Climate and Environmental Tipping Points

CIRES Lead: James Scott

NOAA Lead: Michael Alexander

NOAA Theme: Climate Adaptation and Mitigation

Goals & Objectives: 

Technology development such as described in this project is the basis for increased sophistication of measurement, which in turn supports improved modeling and prediction.

Accomplishments:

We published two papers in Climate Dynamics in March 2017 on sea surface temperature (SST) predictability in coastal regions, which included significant contributions from CIRES’ Gaelle Hervieux:
Hervieux, G., M. A. Alexander, C. A. Stock, M. G. Jacox, K. Pegion, E. Becker, F. Castruccio, and D. Tommasi (2017), More reliable coastal SST forecasts from the North American Multimodel Ensemble, Climate Dynamics, doi:10.1007/s00382-017-3652-7.
We analyzed the forecast skill of the North American Multimodel Ensemble (NMME) using three different metrics: anomaly correlation, root mean square error, and the Brier score. Our results indicate that current global climate forecast systems with relatively coarse oceanic and atmospheric resolution have skill in forecasting SST anomalies in many coastal Large Marine Ecosystems (LME). Forecast skill is highly dependent on the month being predicted, with certain months producing higher or lower seasonal predictability regardless of the initialization time and duration of the forecast. This forecast skill varied widely by region, with relatively high skill in the Pacific, especially in the Bering Sea and Gulf of Alaska, and in the vicinity of Newfoundland, but limited skill in regions along the U.S. East Coast.
Jacox, M. G., M. A. Alexander, C. A. Stock, and G. Hervieux (2017), On the skill of seasonal sea surface temperature forecasts in the California Current System and its connection to ENSO variability, Climate Dynamics, doi:10.1007/s00382-017-3608-y.
 Each of our coupled climate models in the NMME exhibits significant SST forecast skill in the California Current System (CCS). At short lead times (0-4 months), much of that skill can be attributed to persistence, while at longer leads skill above persistence emerges and in some cases extends for the full length of the forecast. Individual models, as well as the NMME multi-model mean, are particularly skillful for forecasts of February-April, regardless of initialization month. These late winter/spring forecasts also generate the greatest skill above persistence, as they coincide with times of low skill from persistence forecasts. In the case of Canadian Climate Model (CanCM4), we attribute the observed skill above persistence primarily to a predictable evolution of the CCS wind (and resultant upwelling) anomalies during moderate to strong El Niño Southern Ocsillation (ENSO) events.
Two other papers are still in preparation with significant contributions from CIRES scientists Antonietta Capotond, James Scott, and Matt Newman.

Earth System Dynamics, Variability, & Change

Estimated values of the tail-heaviness parameter E of the probability distribution of small-scale vertical velocities in stratiform cloud decks in the eastern Pacific Ocean on 15, 18, and 23 Nov 2008. Two different methods of data processing, labeled "K" and "W,” yielded similar results. Height is measured in "gates,” with Gate 1 indicating the top of the cloud and subsequent gates spaced at constant height (50m) intervals from that height. It was found that the height of the cloud top varied by as much as 400m, indicating that E depends on local physical conditions rather than absolute height. Image: C. Penland, C.R. Williams, A. Koepke, P. D. Sardeshmukh

PSD-20: Stochastic and Scale-award Parameterizations Informed by Observations

CIRES Lead: Prashant Sardeshmukh

NOAA Lead: Cecil Penland

NOAA Theme: Science and Technology Enterprise

Goals & Objectives: This project will show the relationship between regional climate changes around the globe and ocean surface temperatures changes. Climate changes may be forced to a large extent by both natural and anthropogenic changes in sea surface temperatures.

Accomplishments:

Ensemble prediction systems are essential for effective probabilistic weather and climate prediction. For robust decision making using such systems, an accurate accounting of uncertainties in both the forecast model and the observations used to initialize the model forecasts is critical. Our project focuses on the uncertainties in representing physical processes in atmospheric models. This uncertainty has two components: one directly related to the uncertainty in the model parameterizations of unresolved physical processes, and the other to the cascade to large scales of the local physical uncertainties by the flow dynamics.
We are developing a method that is more general and suitable for accounting for the model physics uncertainty than those currently used at major operational weather prediction centers. It is underpinned by a physically based stochastic differential equation that can efficiently generate the stochastically generated skew (SGS) probability distribution that is commonly seen in the statistics of atmospheric variables (Sardeshmukh, Compo, and Penland 2015 Journal of Climate). This method gives us the ability to represent the non-Gaussian aspects of the ensemble forecast probability distributions.
Our approach is to base the parameterizations on direct measurements of the appropriate variables. For example, precipitation is closely related to tropospheric vertical velocity. Thus, one aspect of our project has been the detailed examination of the turbulent vertical wind distributions from radar data taken at Darwin, Australia, and from a ship in the tropical East Pacific Ocean, the so-called VOCALS data set. Our instruments require clouds to register data, and we measure height from the top of the cloud. Our data were coarse-grained into time series at a sampling interval of one minute, and the SGS distribution was fitted to the resulting time series. The SGS distribution has three parameters, one of which (E) describes the fatness of the tails relative to that of a normal (Gaussian) probability distribution. Our other parameters are related to the variance and skewness of the distribution.
We obtained consistent results for turbulent vertical wind in the absence of a strong mean component, i.e., in the absence of strong convection. In all physical situations of this type, we found that the parameter E, indicating the probability of extreme kinetic energy events, was strongest toward the top and bottom of the cloud, and weakest in the center. This effect is shown for three days in November 2008 in the figure.

(a) – (f) Composite SSMIS satellite imagery of integrated water vapor (IWV in cm; see color scale) constructed from polar-orbiting swaths between 0000 and 1159 UTC on 20-25 January 2015. The dashed box in each panel shows the main region of interest for the study. Bold numbers mark the six frontal waves along the atmospheric river; the white star denotes the position of the NOAA Ron H Brown. Image: NOAA ESRL Physical Sciences Laboratory.

PSD-22: Predictive Understanding of Tropical-Extratropical Coupling, Moisture Transport and Heavy Precipitation

CIRES Lead: Darren Jackson

NOAA Lead: George Kiladis

NOAA Theme: Science and Technology Enterprise

Goals & Objectives:

This project addresses regional use of climate information.

Accomplishments:

We conducted process studies of atmospheric rivers (AR) along the U.S. West Coast using a diverse set of observations and modelling techniques. The team’s CalWater 2015 field program produced a unique set of observations from ship, aircraft, and land to conduct these process studies. A diagnostic study of a British Columbia AR landfall associated with heavy precipitation during the CalWater 2015 field campaign revealed the kinematic and thermodynamic structure of a long-lived AR that resulted in heavy precipitation in British Columbia. We integrated profile information from rawinsondes and dropsondes, radar observations from ship and aircraft, and surface sensible and latent heat flux observations from the ship in this study to develop a detailed description of processes associated with an AR.
We identified six transient frontal waves along the AR and the evolution of the AR structure and precipitation, described in a journal article that has been accepted for publication. In a separate AR study examining precipitation processes along the U.S. West Coast, we took aerosol observations along the coast of central California, which show an unexpected local source of ice nucleating particles (INP) contributing to precipitation along the coastal mountains during an wintertime AR event. These results highlight the need to examine both water vapor transport and aerosol contributions to precipitation processes along the West Coast.
We conducted model simulations using three climate models to investigate how the El Niño/Southern Oscillation (ENSO) impacts precipitation along the U.S. West Coast. Simulations conducted for a 34-year period (1979-2013) examined atmospheric circulation and precipitation patterns based on various ENSO states (El Niño, La Niña, neutral, all). Our results showed that precipitation and atmospheric circulation patterns remained similar for these different ENSO states, but wetter years have a greater frequency of precipitation days than drier years. We found these wetter years were associated with El Niño.

PSD-23: Lead the Planning and Execution of Large-Scale National and International, Multi-Institutional Field Campaigns to Observe and Understand the Coupled Behavior of the Atmosphere Over Land, Oceans, Ice, and Snow

CIRES Lead: Matt Newman

NOAA Lead: Allen White

NOAA Theme: Science and Technology Enterprise

Goals & Objectives:

This project specifically addresses regional climate predictions.

Accomplishments:

We conducted two major field programs under this project: the El Niño Rapid Response Experiment (ENRR) and the Southern Ocean Seagoing Air-Sea Flux System deployment as part of the CAPRICORN project (Clouds, Aerosols, Precipitation and Atmospheric Composition Over the Southern Ocean). More information can be found at https://www.esrl.noaa.gov/psd/news/2016/020516.html and https://www.esrl.noaa.gov/psd/news/2016/042516.html.
For ENRR, PSL was involved in observations from many places and platforms: Christmas Island, the NOAA research vessel Ronald H. Brown, the NOAA G-IV aircraft, and NASA’s Global Hawk aircraft. The goal of ENRR was to capture observations of tropical convection and coupling to mid-latitudes during the strong El Niño in the winter of 2015-2016. ENRR data are available in the PSL archive. We have just started research on the observations, but a few papers have been submitted including an overview to the Bulletin of the American Meteorological Society (Dole et al., Advancing Science and Services during the 2015-16 El Niño: The NOAA El Niño Rapid Response Field Campaign).
For the Southern Ocean study, we installed NOAA’s seagoing Air-Sea Flux System on a new research vessel, the research vessel Investigator, operated by Australia’s Commonwealth Scientific and Industrial Research Organisation (CSIRO). We are collaborating with CSIRO and scientists from the Australian Bureau of Meteorology to investigate the interaction of air-sea fluxes and boundary layer clouds, which will help expand the very sparse database of measurements in the Southern Ocean. The cruise was south of Hobart, New Zealand from March 12 - April 20, 2016. The PSL flux system operated at full efficiency; data are available at ftp://ftp1.esrl.noaa.gov/psd3/cruises/CAPRICORN_2016/Investigator/flux/. The CAPRICORN project added significantly to our limited inventory of direct flux observations at high latitudes.

Total rainfall across the Southern Plains in May 2015. Image: NOAA Climate.gov and PRISM climate group at Oregon State University

PSD-24: Enhancing Predictability of Weather and Climate Extremes

CIRES Lead: Judith Perlwitz

NOAA Lead: Martin Hoerling

NOAA Theme: Science and Technology Enterprise

Goals & Objectives:

This project attempts an improvement in basic knowledge through a novel combination of models that could extend weather prediction beyond two weeks.

Accomplishments:

Our team conducted several studies during the reporting period related to the attribution of extreme events. They include:

1. A paper on diagnosing human-induced dynamic and thermodynamic drivers of extreme rainfall, such as the one that triggered the May 2015 floods over Texas and Oklahoma (Cheng et al., submitted to J. Climate).
2. A study on how austral summer southern Africa precipitation extremes are forced by the El Niño-Southern Oscillation and the subtropical Indian ocean dipole (SIOD) southern Africa extremes. Model results show that the probability of extreme wet seasons is greatly increased during La Niña, especially when combined with a positive SIOD and greatly decreases during El Niño regardless of SIOD phasing (Hoell et al., submitted to Climate Dynamics).
3. A study on the linkage between the failed winter rains over Southern California and the strong El Niño during 2015/16. Our analysis using large ensembles of model simulations reveals that the December-February 2016 winter dryness was not a response to global boundary forcings nor was the extreme magnitude of observed 1998 wetness entirely reconcilable with a boundary-forced signal (Zhang et al., submitted J. Climate).
4. A study on the physical explanations for the unprecedented warm equatorial Pacific Ocean temperatures during El Niño 2015/16. Our results reveal that this record warm event appeared to reflect an anthropogenically-forced trend; whether they reflect changes in El Niño variability remains uncertain. (Newman et al., submitted to Bulletin of the American Meteorological Society, Special Issue on Explaining Extreme Events of 2016).
5. A study on the causes of the Record-Breaking U.S. Mid-Atlantic Snowstorm “Jonas.” We found that over the last century, extreme Mid-Atlantic snowstorms like Jonas have become more frequent. In contrast, model simulations suggest that anthropogenic climate change has made such storms less likely. (Wolter et al, submitted to Bulletin of the American Meteorological Society, Special Issue on Explaining Extreme Event of 2016)
6. A study on Extreme California Rains During Winter 2015-16 and related teleconnections. We found that the failure of heavy rains in Southern California during the strong El Niño of 2016, compared to the flooding rains of 1983, does not constitute a climate change effect. (Quan et al., submitted to Bulletin of the American Meteorological Society, Special Issue on Explaining Extreme Event of 2016)
7. Research on the relationship between droughts and heatwaves: We developed a conditional framework to assess whether there are detectable anthropogenic forced changes in the coupling strength between drought and heat wave.

Zonal average of change in ensemble spread of zonal wind [m/s] for 20-member ensembles valid for 120-hour forecasts. Left column is from experiments with FV3-GFS and right column is experiments with the old spectral GFS. Top row shows the change in ensemble spread from SPPT, middle row is for SHUM, and bottom row if for the SKEB. Changes in ensemble spread are relative to ensemble forecasts with no stochastic physics.  Results are average over forecasts in August 2014 (31 forecast for GFS, 7 forecasts for FV3-GFS). Image: CIRES/NOAA

PSD-26: Next Generation Global Prediction System

CIRES Lead: Phil Pegion

NOAA Lead: Jeff Whitker

NOAA Theme: Science and Technology Enterprise

Goals & Objectives:

This project provides measurements of climate related variables at the state of the art over a broad geographic area.

Accomplishments:

We completed the dynamical core selection process in August, 2016 with the release of the final report, available at https://www.weather.gov/media/sti/nggps/NGGPS%20Dycore%20Phase%202%20Test%20Report%20website.pdf. Our report recommended the selection of Geophysical Fluid Dynamics Laboratory’s (GFDL) Finite­ Volume Cubed-Sphere (FV3) Dynamical Core to replace the current spectral dynamical core that is in the Global Forecast System (GFS). A few months later, GFDL released the model code that contains the FV3 dynamical core integrated with the GFS physics suite. This model is referred to as the FV3-GFS.
Since the release of the FV3-GFS, we focused our work on porting the GFS stochastic physics suite, which operates in spectral space, to work on the FV3 grid (a cubed sphere). The initial port was just for the two simpler stochastic physics schemes: Stochastically Perturbed Physics Tendencies and stochastically perturbed boundary layer humidities. We tested the performance of these two schemes in cycled data assimilation and medium range forecasts. After determining the performance of these two schemes met expectations, we focused on the more complicated scheme, Stochastic Kinetic Energy Backscatter, which requires an estimate the amount of kinetic energy dissipated by the dynamical core, and passing this to the physics along with a 3-dimensional quasi-random pattern.
NCEP incorporated the FV3-GFS model into the NOAA Environmental Modeling System (NEMS) framework in March of 2017 and the stochastic physics suite was ported to the NEMS based FV3-GFS shortly thereafter. The model’s sensitivity to the stochastic physics in medium range forecasts (figure) is similar to the old GFS model, but there are enough differences that tuning will be need to optimize the model’s performance. We delivered the implementation of all three schemes to The National Centers for Environmental Prediction in the spring of 2017 for further testing and tuning.
Since the NEMS based FV3-GFS will replace the aging spectral model, the next generation of reanalysis and reforecasts should also use the new model. In order to proceed with this new model, and work out any bugs, we have started a low-resolution ‘scout’ reanalysis and reforecasts. The purpose of a scout run is to make sure all of the machinery for producing a reanalysis and reforecast is in place and working properly before switching to production with the full resolution system, which will use tremendous amounts of computing resources.

Air Quality in a Changing Climate

UWFPS 2017 participants with the NOAA Twin Otter at the Salt Lake City International Airport, January 2017. Photo credit: R. Militec and S. Brown.

CSD-01: Intensive Regional Field Studies of Climate-Air Quality Interdependencies

CIRES Lead: Andy Neuman

NOAA Lead: Tom Ryerson

NOAA Theme: Weather-Ready Nation

Goals & Objectives:

This project will characterize the emissions, transport processes, chemical transformations, and loss processes that contribute to regional and local air quality issues and to climate change on regional and global scales.

Accomplishments:

Our team led several intensive regional field studies conducted to enhance understanding of air quality and climate, using a variety of measurement platforms and locations. Our results from these field studies improve scientific understanding of emissions, atmospheric chemistry, and transport to support effective mitigation strategies and improve models to estimate future climate and air quality.
Our California Baseline Ozone Transport Study (CABOTS) made precise ozone measurements aloft to help the state of California understand the contributions of transport to the high surface ozone present in the San Joaquin Valley and to quantify California’s starting point for complying with the federal ozone standard. From late May through August 2016, the CABOTS field campaign used the Tunable Optical Profiler for Aerosol and oZone lidar (TOPAZ) to measure the vertical distribution of atmospheric ozone and aerosols. Understanding the variations in ozone entering California is becoming increasingly important as the state strives to meet the stricter federal ozone standard.
In the summer of 2016, we operated reactive nitrogen, ozone, and particle instruments aboard the NASA DC-8 aircraft in support of the NASA Atmospheric Tomography mission. Our field intensive work obtained global-scale in situ measurements by continuous airborne vertical profiling, to quantify the processes that control the short-lived climate forcing agents methane and ozone in the atmosphere.
From October - November, 2016, we performed extensive measurements at the Fire Science Laboratory in Missoula, Montana as part of the Fire Influence on Regional and Global Environments Experiment (FIREX). FIREX is a multi-year study of western North American fires assessing the impact of biomass burning on climate and air quality. Our team performed these laboratory studies of emissions and short-term processing of multiple fuel types in preparation  for examining fire influences on the atmosphere during a 2019 large-scale field campaign.
The urban air basins along Utah’s Wasatch Mountains experience severe particulate matter air pollution, with concentrations that exceed the federal standard on many winter days. Our Utah Winter Fine Particulate Study (UWFPS) used an instrumented NOAA Twin Otter aircraft to examine the sources and geographical variability of this pollution. During January and February 2017, we measured particle concentrations and composition, and gas phase particle precursors over Salt Lake City and the adjacent regions.

(a) WRF-Chem model domain and NUCAPS total precipitable water (TPW) for 1 June 2013, with no quality control (QC) filtering. Six tracks are shown, each comprising 32 NUCAPS profile locations used for this day in the scale variance analysis. (b) Normalized power spectral density of 500 hPa CH4 from NUCAPS (black) and from the WRF-Chem model (red) plotted versus wavenumber. The -5/3 power law slope (blue) and random noise (black dash) are also shown. Image: CIRES and NOAA

CSD-02: Chemistry, Emissions, and Trasnport Modeling Research

CIRES Lead: Stu McKeen

NOAA Lead: Michael Trainer

NOAA Theme: Climate Adaptation and Mitigation

Goals & Objectives:

This project will use field observations and laboratory studies to provide better representation of atmospheric chemical, physical, and dynamical processes in numberical models, which will improve predictions and projections of climate and air quality.

Accomplishments:

From June 2016 to May 2017, we submitted quarterly reports to NOAA’s Joint Polar Satellite System program (JPSS), documenting the progress of this cooperative project. The variance scaling properties of NOAA W-P3 aircraft data and model results (Weather Research and Forecasting Chemistry, WRF-Chem) in the middle troposphere for the SENEX-2013 (Southeast Nexus) study period were derived for 10 chemical and meteorological variables in the 10- to 200-km length-scale range. Both the model and aircraft data exhibit remarkable similarity in the scaling properties of all variables, close to the -5/3 scaling law for isentropic turbulence, thus illustrating the dominance of atmospheric turbulence in determining their scaling properties. We did a similar analysis for several variables within the NUCAPS (NOAA Unique Combined Atmospheric Processing System) satellite retrievals supplied by JPSS collaborators over the 100- to 1000-km length-scale range. While some satellite variables (e.g. 500 millibar water vapor, ozone, temperature) follow the -5/3 scaling law, methane and carbon monoxide depart significantly from the expected scaling, and exhibit characteristics of a noisy signal. Our consultations with NUCAPS collaborators led to two additional retrieval datasets being tested with stricter quality control filters, but with no improvement in the variance scaling. We extended the Fourier analysis of the satellite data to provide an estimate of the spatial averaging necessary to provide useful information. For both CH4 and CO this required vertical averaging from 100 millibar to the surface, and ~300-km horizontal averaging.

HRRR-Smoke forecast smoke concentrations over the continental United Status (CONUS domain for May 4, 00UTC. https://rapidrefresh.noaa.gov/hrrr/HRRRsmoke/. Image: NOAA

GSD-04: Improve Regional Air Quality Prediction

CIRES Lead: Ravan Ahmadov

NOAA Lead: Georg Grell

NOAA Theme: Science and Technology Enterprise

Goals & Objectives:

This project focuses on improving the numerical models that combine atmospheric transport and atmospheric chemistry for the purpose of making air quality forecasts for regions of interest and at specific locations.

Accomplishments:

In June 2016 we coupled High Resolution Rapid Refresh (HRRR) model with smoke. The HRRR-Smoke has been running in real time since June 2016. Every six hours a new HRRR-Smoke simulation starts to forecast smoke for next 36 hours. We estimate the biomass burning emissions using JPSS satellite-based fire radiative power data obtained in real time. We visualize and provide the HRRR-Smoke output to users via the following web-page: https://rapidrefresh.noaa.gov/hrrr/HRRRsmoke/
In addition to the continental United States (CONUS) domain, we also set up real-time HRRR-Smoke for the 3km-resolution Alaska domain.
Our team evaluated the HRRR-Smoke model for August, 2016.
We organized a WRF-Chem tutorial in February 2017 at the National Center for Atmospheric Research in Boulder, Colorado. There were about 40 participants from the United States and other countries. Lectures on a number of topics and hands-on exercises were offered during the tutorial.

Personnel Demographics

For an accessible PDF of these charts, click here.

Publications

CIRES scientists and faculty published at least 805 peer-reviewed papers during calendar year 2016. Below, we tabulate publications by first author affiliation, per NOAA request. CIRES scientists and faculty published additional non-refereed publications in 2016, many of them listed in the pages that follow. These citations represent a subset of all CIRES publications; our tracking process misses some, although improved tracking methods may be responsible for some increases over recent years. Moreover, publication counts are only one measure of CIRES’ impact. Additional information on how CIRES research is pushing the boundaries of scientific knowledge is summarized in “CIRES: Science in Service to Society”  and detailed throughout this report.

For an accessible version of this chart, and a full listing of publications, click here.