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  • Satellite-derived methane emissions from inundation in Bangladesh
    The uncertainty in methane (CH4) source strength of rice fields and wetlands is particularly high in South Asia CH4 budgets. We used satellite observations of CH4 column mixing ratios from Atmospheric Infrared Sounder (AIRS), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Greenhouse Gases Observing Satellite (GOSAT) to estimate the contribution of Bangladesh emissions to atmospheric CH4 concentrations. Using satellite-derived inundation area as a proxy for source area, we developed a simple inverse advection model that estimates average annual CH4 surface fluxes to be 4, 9, and 19 mg CH4 m−2 h−1 in AIRS, SCIAMACHY, and GOSAT, respectively. Despite this variability, our flux estimates varied over a significantly narrower range than reported values for CH4 surface fluxes from a survey of 32 studies reporting ground-based observations between 0 and 260 mg CH4 m−2 h−1. Upscaling our satellite-derived surface flux estimates, we estimated total annual CH4 emissions for Bangladesh to be 1.3 ± 3.2, 1.8 ± 2.0, 3.1 ± 1.6 Tg yr−1, depending on the satellite. Our estimates of total emissions are in line with the median of total emission values for Bangladesh reported in earlier studies. more
  • Tightening of Tropical Ascent and High Clouds Key to Precipitation Change in a Warmer Climate
    The change of global-mean precipitation under global warming and interannual variability is predominantly controlled by the change of atmospheric longwave radiative cooling. Here we show that tightening of the ascending branch of the Hadley Circulation coupled with a decrease in tropical high cloud fraction is key in modulating precipitation response to surface warming. The magnitude of high cloud shrinkage is a primary contributor to the intermodel spread in the changes of tropical-mean outgoing longwave radiation (OLR) and global-mean precipitation per unit surface warming (dP/dTs) for both interannual variability and global warming. Compared to observations, most Coupled Model Inter-comparison Project Phase 5 models underestimate the rates of interannual tropical-mean dOLR/dTs and global-mean dP/dTs, consistent with the muted tropical high cloud shrinkage. We find that the five models that agree with the observation-based interannual dP/dTs all predict dP/dTs under global warming higher than the ensemble mean dP/dTs from the B20 models analysed in this study. more
  • Improved AIRS temperature and moisture soundings with local a priori information for the 1DVAR method
    A moving-window regression technique was developed for obtaining better a priori information for one-dimensional variational (1DVAR) physical retrievals. Using this technique regression coefficients were obtained for a specific geographical 10° × 10° window and for a given season. Then, regionally obtained regression retrievals over East Asia were used as a priori information for physical retrievals. To assess the effect of improved a priori information on the accuracy of the physical retrievals, error statistics of the physical retrievals from clear-sky Atmospheric Infrared Sounder (AIRS) measurements during 4 months of observation (March, June, September, and December of 2010) were compared; the results obtained using new a priori information were compared with those using a priori information from a global set of training data classified into six classes of infrared (IR) window channel brightness temperature. This comparison demonstrated that the moving-window regression method can successfully improve the accuracy of physical retrieval. For temperature, root-mean-square error (RMSE) improvements of 0.1–0.2 and 0.25–0.5 K were achieved over the 150–300- and 900–1000-hPa layers, respectively. For water vapor given as relative humidity, the RMSE was reduced by 1.5%–3.5% above the 300-hPa level and by 0.5%–1% within the 700–950-hPa layer. more
  • Comparison of satellite-, model-, and radiosonde-derived convective available potential energy in the Southern Great Plains region
    Convective available potential energy (CAPE) is one of the physical quantities used by operational meteorologists when issuing severe-weather convective watches and warnings. Recent advances in satellite technology could provide timely observations of atmospheric temperature and water vapor profiles over the continental United States, but only limited validation exists in the literature to characterize uncertainties in CAPE derived from the new satellite sensors. In this study, 10 years of Vaisala, Inc., RS92 radiosonde observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site were matched to overpasses of the NASA Aqua satellite that were made from January 2005 through December 2014. Vertical profiles of temperature and water vapor from the NASA Atmospheric Infrared Sounder (AIRS) were extracted in a region surrounding the DOE ARM SGP central facility near Lamont, Oklahoma. Surface-based CAPE was computed using software consistent with methods used by the National Weather Service Storm Prediction Center. The one-to-one correspondence of the AIRS-derived CAPE with the ARM-radiosonde-derived CAPE has a correlation coefficient of only 0.34. Substitution of the ARM-radiosonde surface values into the AIRS profiles improves the correlation to 0.95. The use of AIRS profiles above the surface level provides surface-based CAPE values that are very similar to those computed from Vaisala radiosondes. These results suggest that a merging of surface observations with satellite-derived thermodynamic profiles could make better use of the satellite spatial coverage and temporal sampling for estimation of CAPE in near–real time. more