P1.17
Long-term variations in global and tropical precipitation derived from the GPCP monthly product

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Monday, 30 January 2006
Long-term variations in global and tropical precipitation derived from the GPCP monthly product
Exhibit Hall A2 (Georgia World Congress Center)
Robert Adler, NASA/GSFC, Greenbelt, MD; and G. Gu and G. J. Huffman

Global and large regional rainfall variations and possible long-term changes are examined using the 26-year (1979-2004) monthly dataset from the Global Precipitation Climatology Project (GPCP). One emphasis is to discriminate among the variations due to ENSO, volcanic events and possible long-term changes. Although the global change of precipitation in the data set is near zero, the data set does indicate an upward trend (0.13 mm/day/25yr) and a downward trend (-0.06 mm/day/25yr) over tropical oceans and lands (25S-25N), respectively. This corresponds to a 4% increase (ocean) and 2% decrease (land) during this time period. Simple techniques are derived to attempt to eliminate variations due to ENSO and major volcanic eruptions in the Tropics. Using only annual values two “volcano years” are determined by examining ocean-land coupled variations in precipitation related to ENSO and other phenomena. The outlier years coincide with Pinatubo and El Chicon eruptions. The ENSO signal is reduced by deriving mean ocean and land values for El Nino, La Nina and neutral conditions based on Nino 3.4 SST and normalizing the annual ocean and land precipitation to the neutral set of cases. The impact of the two major volcanic eruptions over the past 25 years is estimated to be about a 5% reduction in tropical rainfall. The modified data set (with ENSO and volcano effect at least partially removed) retains the same approximate linear change slopes over the data set period, but with reduced variance leading to significance tests with results in the 90-95% range. Inter-comparisons between the GPCP, SSM/I (1988-2004), and TRMM (1998-2004) satellite rainfall products and alternate gauge analyses over land are made to attempt to increase or decrease confidence in the changes seen in the GPCP analysis.