A fundamental probability distribution for heavy rainfall

There is currently no physical understanding of the statistics of heavy precipitation. These statistics are, however, central to diagnosing climate change and making weather risk assessments. This work derives a fundamental rainfall distribution. Interpretation of the water balance equation gives a simple expression for precipitation as the product of mass flux or advected mass, specific humidity and precipitation efficiency. Statistical theory predicts that the tail of the distribution of the product of these three random variables will have a stretched exponential form with a shape parameter of 2/3. This is verified for a global daily precipitation data set. The stretched exponential tail explains the apparent ‘heavy’ tailed behaviour of precipitation under standard assumptions used in extreme value theory. The novel implications for climate change are that the stretched exponential shape is unlikely to change, although the scale may, and precipitation efficiency is important in understanding future changes in heavy precipitation.

[1]  D. Easterling,et al.  Trends in Intense Precipitation in the Climate Record , 2005 .

[2]  Nicholas J. Cook,et al.  Exact and general FT1 penultimate distributions of extreme wind speeds drawn from tail-equivalent Weibull parents , 2004 .

[3]  Demetris Koutsoyiannis,et al.  Statistics of extremes and estimation of extreme rainfall: II. Empirical investigation of long rainfall records / Statistiques de valeurs extrêmes et estimation de précipitations extrêmes: II. Recherche empirique sur de longues séries de précipitations , 2004 .

[4]  R. Magagi,et al.  Estimation of Latent Heating of Rainfall during the Onset of the Indian Monsoon Using TRMM PR and Radiosonde Data , 2004 .

[5]  K. Trenberth,et al.  The changing character of precipitation , 2003 .

[6]  M. Allen,et al.  Constraints on future changes in climate and the hydrologic cycle , 2002, Nature.

[7]  T. Wigley,et al.  Future changes in the distribution of daily precipitation totals across North America , 2002 .

[8]  D. Sornette Critical Phenomena in Natural Sciences: Chaos, Fractals, Selforganization and Disorder: Concepts and Tools , 2000 .

[9]  Kevin E. Trenberth,et al.  Conceptual Framework for Changes of Extremes of the Hydrological Cycle with Climate Change , 1999 .

[10]  David R. Easterling,et al.  Changes in the Probability of Heavy Precipitation: Important Indicators of Climatic Change , 1999 .

[11]  D. Abbs,et al.  A numerical modeling study to investigate the assumptions used in the calculation of probable maximum precipitation , 1999 .

[12]  K. Hennessy,et al.  Trends in total rainfall, heavy rain events and number of dry days in Australia, 1910–1990 , 1998 .

[13]  D. Lüthi,et al.  Heavy precipitation processes in a warmer climate , 1998 .

[14]  D. Sornette,et al.  Stretched exponential distributions in nature and economy: “fat tails” with characteristic scales , 1998, cond-mat/9801293.

[15]  D. Sornette,et al.  Extreme Deviations and Applications , 1997, cond-mat/9705132.

[16]  Thomas R. Karl,et al.  Trends in high-frequency climate variability in the twentieth century , 1995, Nature.

[17]  James C. Fankhauser,et al.  Estimates of Thunderstorm Precipitation Efficiency from Field Measurements in CCOPE , 1988 .

[18]  P. Alpert Mesoscale Indexing of the Distribution of Orographic Precipitation over High Mountains , 1986 .

[19]  David A. Woolhiser,et al.  Stochastic daily precipitation models: 2. A comparison of distributions of amounts , 1982 .

[20]  R. Lindzen,et al.  Tropical Wave-CISK with a Moisture Budget and Cumulus Friction , 1978 .

[21]  Ronald Biondini Cloud Motion and Rainfall Statistics , 1976 .

[22]  R. Barry,et al.  Atmosphere, Weather and Climate , 1968 .

[23]  E. Palmén Vertical Circulation and Release of Kinetic Energy during the Development of Hurricane Hazel into an Extratropical Storm , 1958 .

[24]  PhD Deepto Chakrabarty,et al.  DEPARTMENT OF PHYSICS , 2001 .