A spatial time series framework for simulating daily precipitation at regional scales

In this paper, a framework for stochastic spatiotemporal modeling of daily precipitation in a hindcast mode is presented. Observed precipitation levels in space and time are modeled as a joint realization of a collection of space-indexed time series, one for each spatial location. Time series model parameters are spatially varying, thus capturing space-time interactions. Stochastic simulation, i.e., the procedure of generating alternative precipitation realizations (synthetic fields) over the space-time domain of interest (Deutsch and Journel, 1998), is employed for ensemble prediction. The simulated daily precipitation fields reproduce a data-based histogram and spatiotemporal covariance model, and identify the measured precipitation values at the rain gauges (conditional simulation). Such synthetic precipitation fields can be used in a Monte Carlo framework for risk analysis studies in hydrologic impact assessment investigations.

[1]  Jinwon Kim,et al.  Simulation of a Precipitation Event in the Western United States , 1995 .

[2]  S. R. Searle Linear Models , 1971 .

[3]  É. Leblois,et al.  Mapping mean monthly runoff pattern using EOF analysis , 2000 .

[4]  P. Kyriakidis A Geostatistical Framework for Area-to-Point Spatial Interpolation , 2004 .

[5]  A. Journel,et al.  Posterior identification of histograms conditional to local data , 1994 .

[6]  D. Cayan,et al.  Precipitation structure in the Sierra Nevada of California during winter , 1999 .

[7]  Phaedon C. Kyriakidis,et al.  Stochastic modeling of atmospheric pollution: a spatial time-series framework. Part I: methodology , 2001 .

[8]  Clayton V. Deutsch,et al.  GSLIB: Geostatistical Software Library and User's Guide , 1993 .

[9]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[10]  D. Plane,et al.  A Shift-Share Method for the Analysis of Regional Fertility Change: An Application to the Decline in Childbearing in Italy, 1952-1991 , 2003 .

[11]  Norman L. Miller,et al.  Numerical prediction of precipitation and river flow over the Russian River watershed during the January 1995 California storms , 1996 .

[12]  Marc F. P. Bierkens,et al.  Space-time modeling of water table depth using a regionalized time series model and the Kalman Filter , 2001 .

[13]  Phaedon C. Kyriakidis,et al.  Geostatistical Space–Time Models: A Review , 1999 .

[14]  H. J. Thiébaux The Power of the Duality in Spatial–Temporal Estimation , 1997 .

[15]  Michael F. Hutchinson,et al.  Stochastic space-time weather models from ground-based data , 1995 .

[16]  Timothy C. Coburn,et al.  Geostatistics for Natural Resources Evaluation , 2000, Technometrics.

[17]  I. Rodríguez‐Iturbe,et al.  Random Functions and Hydrology , 1984 .

[18]  Dong-Jun Seo,et al.  Simulation of precipitation fields from probabilistic quantitative precipitation forecast , 2000 .

[19]  F. Giorgi,et al.  Approaches to the simulation of regional climate change: A review , 1991 .

[20]  H. Storch,et al.  Statistical Analysis in Climate Research , 2000 .

[21]  D. Wilks Multisite generalization of a daily stochastic precipitation generation model , 1998 .

[22]  A. R. Rao,et al.  Estimation of variables at ungaged locations by empirical orthogonal functions , 1991 .

[23]  P. Goovaerts Spatial orthogonality of the principal components computed from coregionalized variables , 1993 .

[24]  Phaedon C. Kyriakidis,et al.  Geostatistical Mapping of Precipitation from Rain Gauge Data Using Atmospheric and Terrain Characteristics , 2001 .

[25]  Clayton L. Hanson,et al.  Spatial variability and interpolation of stochastic weather simulation model parameters , 2000 .

[26]  O. E. Tveito,et al.  Generation of runoff series at ungauged locations using empirical orthogonal functions in combination with kriging , 1992 .

[27]  Phaedon C. Kyriakidis,et al.  Uncertainty propagation of regional climate model precipitation forecasts to hydrologic impact assessment , 2001 .

[28]  R. Chandler,et al.  Analysis of rainfall variability using generalized linear models: A case study from the west of Ireland , 2002 .

[29]  N. Miller,et al.  River Flow Response to Precipitation and Snow Budget in California during the 1994/95 Winter , 1998 .