North Polar Radiative Flux Variability from 2002 through 2014

Description

Over the past several decades, due to the general warming of the climate, changes in North Polar regions have outpaced changes in lower latitudes. This has led to increased scrutiny of a region that is, in general, a difficult environment in which to maintain high-quality observations. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project produces the SYN1deg data product that provides climate-quality 3-hourly globally gridded and temporally complete maps of top-of-atmosphere, in-atmosphere, and surface fluxes. Fluxes are computed hourly using a radiative transfer code based on inputs, above 60 degrees of latitude, that depend primarily on observations from Terra and Aqua MODIS imagers and GMAO’s GEOS-5 reanalysis. SYN1Deg data are the initial source of TOA and surface fluxes used to derive the CERES Energy Balanced and Filled (EBAF) product providing monthly mean maps of TOA and surface fluxes that adjust the small net imbalance found in CERES over time to match ocean heat content. In this poster we validate calculated fluxes from the SYN1deg product against CERES observations at the Top of Atmosphere (TOA) and in situ observations from ARM's North Slope of Alaska site, BSRN (Tiksi, RU, Alert CA), ETH and NOAA data from Summit, Greenland and other surface sites where and when available. Comparison of calculated, monthly mean, surface fluxes at these sites show a small LW down bias of approximate 0% from a mean of 232 Wm-2 and a standard deviation of 21 Wm-2 or approximately 10%. SW down bias is larger at 3% of a mean downward SW flux of 113 Wm-2 with a standard deviation of 11 Wm-2 or again, approximately 10%. We also extract key variables from the SYN1deg data set including TOA and surface, upward, downward, and net fluxes and analyze time series of these data using Empirical Orthogonal Functions (EOFs) over the North Pole (90N to 60N). Comparisons of the spatial patterns and time histories indicate the SYN1deg and its input data sets are recovering the dynamic variability of the polar atmosphere geographically and over time. EOF analyses of important input variables such as skin temperature and cloud base height allows us to investigate the co-variability of these variables with the calculated radiative fluxes.