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  • Author or Editor: S. Y. Gao x
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F. Giorgi
,
E.-S. Im
,
E. Coppola
,
N. S. Diffenbaugh
,
X. J. Gao
,
L. Mariotti
, and
Y. Shi

Abstract

Because of their dependence on water, natural and human systems are highly sensitive to changes in the hydrologic cycle. The authors introduce a new measure of hydroclimatic intensity (HY-INT), which integrates metrics of precipitation intensity and dry spell length, viewing the response of these two metrics to global warming as deeply interconnected. Using a suite of global and regional climate model experiments, it is found that increasing HY-INT is a consistent and ubiquitous signature of twenty-first-century, greenhouse gas–induced global warming. Depending on the region, the increase in HY-INT is due to an increase in precipitation intensity, dry spell length, or both. Late twentieth-century observations also exhibit dominant positive HY-INT trends, providing a hydroclimatic signature of late twentieth-century warming. The authors find that increasing HY-INT is physically consistent with the response of both precipitation intensity and dry spell length to global warming. Precipitation intensity increases because of increased atmospheric water holding capacity. However, increases in mean precipitation are tied to increases in surface evaporation rates, which are lower than for atmospheric moisture. This leads to a reduction in the number of wet days and an increase in dry spell length. This analysis identifies increasing hydroclimatic intensity as a robust integrated response to global warming, implying increasing risks for systems that are sensitive to wet and dry extremes and providing a potential target for detection and attribution of hydroclimatic changes.

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S. Sorooshian
,
X. Gao
,
K. Hsu
,
R. A. Maddox
,
Y. Hong
,
H. V. Gupta
, and
B. Imam

Abstract

Recent progress in satellite remote-sensing techniques for precipitation estimation, along with more accurate tropical rainfall measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) instruments, have made it possible to monitor tropical rainfall diurnal patterns and their intensities from satellite information. One year (August 1998–July 1999) of tropical rainfall estimates from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system were used to produce monthly means of rainfall diurnal cycles at hourly and 1° × 1° scales over a domain (30°S–30°N, 80°E–10°W) from the Americas across the Pacific Ocean to Australia and eastern Asia.

The results demonstrate pronounced diurnal variability of tropical rainfall intensity at synoptic and regional scales. Seasonal signals of diurnal rainfall are presented over the large domain of the tropical Pacific Ocean, especially over the ITCZ and South Pacific convergence zone (SPCZ) and neighboring continents. The regional patterns of tropical rainfall diurnal cycles are specified in the Amazon, Mexico, the Caribbean Sea, Calcutta, Bay of Bengal, Malaysia, and northern Australia. Limited validations for the results include comparisons of 1) the PERSIANN-derived diurnal cycle of rainfall at Rondonia, Brazil, with that derived from the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) radar data; 2) the PERSIANN diurnal cycle of rainfall over the western Pacific Ocean with that derived from the data of the optical rain gauges mounted on the TOGA-moored buoys; and 3) the monthly accumulations of rainfall samples from the orbital TMI and PR surface rainfall with the accumulations of concurrent PERSIANN estimates. These comparisons indicate that the PERSIANN-derived diurnal patterns at the selected resolutions produce estimates that are similar in magnitude and phase.

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