Tropical Rainfall Climatology and Its Relation to Surface Temperature from TRMM and GPM Satellites

A climatology of tropical surface rain has previously been developed based on a composite of sixteen years (1998-2013) of both passive microwave and radar precipitation products from Tropical Rainfall Measuring Mission (TRMM) Version 7 (V7) data. This Tropical Composite Climatology (TCC) is now improved and extended through 2017 by combining the new TRMM V8data with the data from the Global Precipitation Measurement (GPM) mission. The TRMM V8 rainfall products are produced with algorithms nearly identical to those of GPM V06 dataproviding a consistent set of retrievals for the climatology.

Our next step is to utilize all the TRMM and GPM products to investigate inter-annual and other variations of surface precipitation in relation to variations in surface temperature (e.g., related to ENSO). These precipitation-temperature relations are important to understand climate variations on the inter-annual to inter-decadal scale, especially in this era of global warming.

Our previous studies using TRMM V7 data show that over the tropical ocean, GPCP and TRMM Microwave Imager (TMI) rainfall data have large and similar slopes against ocean-wide sea surface temperature (SST) anomalies, while the monthly rainfall anomalies derived from the TRMM Precipitation Radar (PR) exhibit much shallower slopes against the SST anomalies. Overall, it is found that the PR-based surface precipitation-temperature slopes do not confirm slopes based on passive microwave observations. Our more recent and similar studies using GPM V05 data revealed that the relations between precipitation and temperature variation from GPM Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) have a better agreement with each other in the first 2.5 years of GPM than with the same data from TRMM, although substantial differences still exist.

A series of comparison studies focusing on the difference of precipitation-temperature relations from PR to those from TMI, GMI, and even DPR indicate that the most likely reason for the difference is that the TRMM PR V7 is underestimating convective rainfall due to the insufficient attenuation correction. In particular, the underestimation is amplified during periods of heavy rain, for example during El Niño’s over ocean.

With the new and extended GPM V06 data available recently and the upcoming improved TRMM V8 data that use the same algorithms as GPM V06, we will re-examine the relationship between precipitation and surface temperature from TRMM V8 (1998-2013) and GPM V06 (2014-2018) data. The results will be reported in detail at the conference.