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Prabhakara, Cuddapah

Publications and source records attributed to Prabhakara, Cuddapah.

Inference of Global Mean Temperature Trend and Climate Change from MSU and AMSU

Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) radiometers flown on the NOAA operational satellite series are potentially valuable as global temperature monitoring devices. Spencer and Christy pioneered the analysis of mid-tropospheric temperature, given by MSU Channel 2 (Ch 2) at 53.74 GHz, to derive the global temperature trend. Also, in addition to monitoring global temperature, these microwave radiometers have the potential to reveal interannual climate signals in tropics. We have analyzed the data of MSU Ch 2 and AMSU Ch 5 (53.6 GHz) from the NOAA operational satellites for the period 1980 to 2000, utilizing the NOAA calibration procedure. The data are corrected for the satellite orbital drift based on the temporal changes of the on-board warm blackbody temperature. From our analysis, we find that the global temperature increased at a rate of 0.13 +/- 0.05 Kdecade(sup -1) during 1980 to 2000. From an Empirical Orthogonal Function (EOF) analysis of the MSU global data, we find that the mid-tropospheric temperature in middle and high latitudes responds to the ENSO forcing during the Northern Hemisphere Winter in a distinct manner. This mid-latitude response is opposite in phase to that in the tropics. This result is in accord with simulations performed with an ECMWF global spectral model. This study shows a potential use of the satellite observations for climatic change.

Prabhakara, Cuddapah↗

TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85min, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we have developed a TMI algorithm to retrieve convective and stratiform rain. In this algorithm, two parameters are used to classify three kinds of thunderstorms (Cbs) based on the T85 data: a) the magnitude of scattering depression deduced from local T85mi, and b) the mean horizontal gradient of T85 around such minima. Initially, the algorithm is optimized or tuned utilizing the PR and TMI data of a few MCS events. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (greater than or equal to 20 mm/hr) rain rates are retrieved on the average with an accuracy of about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Prabhakara, Cuddapah↗