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Science Rendezvous > Posters
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Temperature and humidity profiling in the Arctic using millimeter-
and submillimeter-wave radiometry
Domenico Cimini (1,2), Ed R. Westwater(2,3), Albin J. Gasiewski(2),Vladimir Leuski(3)
(1)CETEMPS, University of L'Aquila, Italy
(2)Center for Environmental Technology, Department of Electrical and Computer Engineering, University of Colorado at Boulder
(3) CIRES
Water vapor during very cold and dry conditions is difficult to measure, either by in situ techniques or standard microwave radiometer/GPS measurements. To improve capabilities to measure low amounts of water vapour, the NOAA-CU Center for Environmental Technology (CET) has developed and deployed a Ground-Based Scanning Radiometer (GSR) during two important Arctic Experiments .The first was the Artic Winter Radiometric Experiment during March-April 2004 and the second is the Radiative Heating in Underexplored Bands Campaign (RHUBC) in February-March 2007. Both of these Intensive Observation Periods (IOPs) were conducted at the Atmospheric Radiation Measurement (ARM) Program’s ”Great White” field site near Barrow, Alaska. The primary goal of the 2004 deployment was to demonstrate that millimeter wavelength radiometers can substantially improve water vapor observations during the Arctic winter. The primary goal of the RHUBC 2007 deployment was to use the GSR data to supplement high spectral-resolution infrared observations of downwelling radiances observed across the near- and far-infrared spectrum.
The GSR operates over a broad frequency range (50 to 400 GHz), including several channels near the strong water vapor absorption lines at 183.31 and at 380.2 GHz The set of frequencies was selected for the simultaneous retrieval of atmospheric temperature and water vapour profiles, precipitable water vapor (PWV), and cloud liquid water path (LWP). The GSR performs an atmospheric scan and calibration sequence every 1-2 min that includes dwells at a discrete set of angles equally spaced in air mass followed by followed by observations of two external calibration targets. Rapid (14 ms) observations of internal noise sources are also part of the calibration-scene sequence.
For the RHUBC data, vertical profiles of temperature and water vapour were derived from brightness temperature data taken by the GSR. Our profile retrieval method, known as One-Dimensional Variational Assimilation Retrieval (1D-VAR), was applied to the radiometer data, and blended in an optimum manner with forecasts from the European Center for Medium Range Forecasts. The training set for the retrievals was based on the WVIOP-2004 data, from which covariance matrices for all relevant variables were obtained. These covariance matrices included those describing the forecast (or background) error, and the total error covariance error for the GSR. The 1D-VAR retrievals, when compared with Vaisala RS92 radiosondes, yielded profiles that were a dramatic improvement over the forecast alone in the first 1-2 km above the surface. Conversely, the radiometer data had only small impact on the retrievals above 3-km. The 1-D VAR retrievals achieved rms errors in temperature of about 1 °C up to about 5 km. The humidity profiles were also a marked improvement over the forecast alone. Statistics of 1D-VAR retrievals based on GSR data during RHUBC confirm the theoretical expectations for accuracy and vertical resolution, which outperforms results from other methods. The method is totally flexible and suitable for data assimilation in NWP models.
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