Prashant Sardeshmukh

Prashant Sardeshmukh

Ph.D. Princeton University, 1982

Senior Research Scientist

NOAA/ESRL/Physical Sciences Division

E-mail: Prashant.D.Sardeshmukh@noaa.gov
Office: David Skaggs Research Center, 1D112
Phone: 303-497-6248
Web: Prashant Sardeshmukh

Research Interests

Diagnosis, modeling, and predictability of large-scale weather and climate variations on time scales of days to millennia.

Current Research: Is global warming significantly affecting daily weather extremes?

The answer to this trillion-dollar question depends not just on the mean shift of the probability density function (PDF) of daily weather anomalies, but also on changes in the width and shape of the PDF. The PDFs of daily weather are generally not Gaussian and are, therefore, not characterized by their mean and variance. One also has to account for their generally asymmetric and heavy-tailed character when assessing changes in tail probabilities. We are addressing this important issue using the longest global-atmospheric-circulation data set currently available, an ensemble of 56 equally likely estimates of the global atmospheric state within observational error bounds generated for every six hours from 1871 to the present in the Twentieth Century Reanalysis (20CR) project, a major international effort led by CIRES and NOAA (Compo et al., QJRMS, 2011). Specifically, we are using the mean, variance, skewness, and kurtosis of the daily data to fit so-called SGS (stochastically generated skewed) PDFs (Sardeshmukh and Sura, J. Clim., 2009) to the histograms of the daily values, and then using the fitted PDFs to draw inferences about tail probabilities. We have initially focused on the PDFs of daily indices of four prominent modes of sea-level pressure variability: the North Atlantic Oscillation (NAO), the North Pacific Oscillation (NPO), the tropical Pacific Walker Circulation (PWC), and the Annular Antarctic Oscillation (AAO). We have fitted SGS distributions to the histograms of these indices separately in the first and second halves of our 136-year record (1874 to 1942 and 1943 to 2010) and assessed the statistical significance of changes in the PDFs through extensive Monte Carlo integrations with a “weather generator” model whose parameters are consistent with those of the fitted distributions. Applying this rigorous significance-testing procedure, we find no significant change in the mean of the NAO and NPO, and a small but significant positive shift in the mean of PWC and AAO from the first to the
second half of the 136- year period. For the PDF as a whole, we find no significant changes in the PDFs of the NAO and NPO. The small positive
mean shifts of the PWC and AAO PDFs are associated with increased probabilities of large positive values and reduced probabilities of large negative values, but these changes are much smaller and statistically insignificant for extreme positive values, beyond about 2.5 standard deviations. These are important results and also underscore the danger of drawing inferences about changes in extreme-value statistics merely from shifts of the mean.

sardeshmukh2013AR

Probability density functions (PDFs) of standardized anomalous daily sea-level-pressure-based indices of the North Pacific Oscillation (NPO), North Atlantic Oscillation (NAO), Pacific Walker Circulation (PWC), and Annular Antarctic Oscillation (AAO). The PDFs are estimated for two 68-year periods, 1874 to 1942 (red) and 1943 to 2010 (blue), both as raw histograms (rectangles) and as fitted stochastically generated skewed (SGS) PDFs (curves). Results are shown for each one of the 56 members of the observational Twentieth Century Reanalysis ensemble. There are, thus, 56 red and 56 blue curves in each plot. Upper and lower segments of the red and blue rectangles show the range of raw counts for each anomaly size bin. The gray swath indicates 95 percent confidence intervals on the PDFs associated with using limited 68-year records, estimated from Monte Carlo simulations. The spread among the red and blue curves is, thus, a measure of observational uncertainty, whereas the gray swath is a measure of sampling uncertainty. The figure shows no statistically significant change in the PDFs of the NPO and NAO from the first to the second 68-year period, and a mean positive shift for the PWC and the AAO. Note, however, that there is no significant change in the extreme positive values of the PWC and AAO.


 

Publications

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