Latest Resources




  • Observational Evidence for Desert Amplification Using Multiple Satellite Datasets
    Desert amplification identified in recent studies has large uncertainties due to data paucity over remote deserts. Here we present observational evidence using multiple satellite-derived datasets that desert amplification is a real large-scale pattern of warming mode in near surface and low-tropospheric temperatures. Trend analyses of three long-term temperature products consistently confirm that near-surface warming is generally strongest over the driest climate regions and this spatial pattern of warming maximizes near the surface, gradually decays with height, and disappears in the upper troposphere. Short-term anomaly analyses show a strong spatial and temporal coupling of changes in temperatures, water vapor and downward longwave radiation (DLR), indicating that the large increase in DLR drives primarily near surface warming and is tightly associated with increasing water vapor over deserts. Atmospheric soundings of temperature and water vapor anomalies support the results of the long-term temperature trend analysis and suggest that desert amplification is due to comparable warming and moistening effects of the troposphere. Likely, desert amplification results from the strongest water vapor feedbacks near the surface over the driest deserts, where the air is very sensitive to changes in water vapor and thus efficient in enhancing the longwave greenhouse effect in a warming climate. more
  • The Change in Low Cloud Cover in a Warmed Climate Inferred from AIRS, MODIS, and ERA-Interim
    Decreases in subtropical low cloud cover (LCC) occur in climate model simulations of global warming. In this study 8-day-averaged observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) spanning 2002–14 are combined with European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis to compute the dependence of the observed variability of LCC on various predictor variables. Large-scale thermodynamic and dynamic predictors of LCC are selected based on insight from large-eddy simulations (LESs) and observational analysis. It is found that increased estimated inversion strength (EIS) is associated with increased LCC. Drying of the free troposphere is associated with decreased LCC. Decreased LCC accompanies subsidence in regions of relatively low EIS; the opposite is found in regions of high EIS. Finally, it is found that increasing sea surface temperature (SST) leads to a decrease in LCC. These results are in keeping with previous studies of monthly and annual data. Based upon the observed response of LCC to natural variability of the control parameters, the change in LCC is estimated for an idealized warming scenario where SST increases by 1 K and EIS increases by 0.2 K. For this change in EIS and SST the LCC is inferred to decrease by 0.5%–2.7% when the regression models are trained on data observed between 40°S and 40°N and by 1.1%–1.4% when trained on data from trade cumulus–dominated regions. When the data used to train the regression model are restricted to stratocumulus-dominated regions the change in LCC is highly uncertain and varies between −1.6% and +1.4%, depending on the stratocumulus-dominated region used to train the regression model. more
  • Validation of INSAT-3D temperature and moisture sounding retrievals using matched radiosonde measurements
    An evaluation of temperature and moisture profiles retrieved from a geostationary Indian National Satellite (INSAT-3D) sounder, launched in 2013, is performed against collocated radiosonde (RAOB) observation measurements of more than 1 year. This evaluation is carried out in terms of bias and root mean square error (RMSE) in temperature and relative humidity. An error analysis is carried out for different surface types, different seasons and day/night cases. The key finding of this study is that INSAT-3D retrievals show good agreement with RAOB measurements with overall RMSE accuracies ~1–2 K and 10–20%, respectively, for temperature and relative humidity in the troposphere. However, the temperature and relative humidity retrievals over land or in dry atmosphere show degraded performance. This degradation might be related to uncertainty in surface emissivity over land and possibility of undetected cloud in dry atmospheric condition. In addition to it, a similar analysis is carried out to assess the relative performance of INSAT-3D-retrieved profiles, Atmospheric Infrared Sounder (AIRS) L2 Standard Physical Retrieval (AIRS-only) version 6 (AIRS2RET) profiles and European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) reanalysis with respect to spatially and temporally collocated RAOBs. In this analysis, temperature and moisture profiles from RAOBs serve as reference measurements and all retrievals and ERA-interim are compared with RAOBs. AIRS and INSAT-3D temperature retrievals gave comparable accuracies in upper and lower troposphere where as the quality degrades in middle troposphere resulting in larger errors. This may be due to improper bias correction coefficients used for brightness temperature of clear sky pixels before physical retrievals. In case of relative humidity, INSAT-3D profiles have comparable accuracies as AIRS in troposphere. more
  • Impact of satellite data assimilation on the predictability of monsoon intraseasonal oscillations in a regional model
    This study reports the improvement in the predictability of circulation and precipitation associated with monsoon intraseasonal oscillations (MISO) when the initial state is produced by assimilating Atmospheric Infrared Sounder (AIRS) retrieved temperature and water vapour profiles in Weather Research Forecast (WRF) model. Two separate simulations are carried out for nine years (2003 to 2011) . In the first simulation, forcing is from National Centers for Environmental Prediction (NCEP, CTRL) and in the second, apart from NCEP forcing, AIRS temperature and moisture profiles are assimilated (ASSIM). Ten active and break cases are identified from each simulation. Three dimensional temperature states of identified active and break cases are perturbed using twin perturbation method and carried out predictability tests. Analysis reveals that the limit of predictability of low level zonal wind is improved by four (three) days during active (break) phase. Similarly the predictability of upper level zonal wind (precipitation) is enhanced by four (two) and two (four) days respectively during active and break phases. This suggests that the initial state using AIRS observations could enhance predictability limit of MISOs in WRF. More realistic baroclinic response and better representation of vertical state of atmosphere associated with monsoon enhance the predictability of circulation and rainfall. more