DOI: 10.1175/JCLI-D-12-00235.1
Scopus记录号: 2-s2.0-84874795692
论文题名: Metrics and diagnostics for precipitation-related processes in climate model short-range hindcasts
作者: Ma H.-Y. ; Xie S. ; Boyle J.S. ; Klein S.A. ; Zhang Y.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 5 起始页码: 1516
结束页码: 1534
语种: 英语
Scopus关键词: Climate simulation
; Deep convection
; Fast process
; Hindcasts
; Intense precipitation
; Intercomparisons
; Lower probabilities
; Model evaluation/performance
; Moist process
; Moist static energy
; Operational analysis
; Precipitation intensity
; Regional analysis
; Short-range predictions
; Time-scales
; Tropical convection
; Tropical precipitation
; Tropical rainfall measuring missions
; Climate models
; Moisture
; Plasma diagnostics
; Precipitation (chemical)
; Rain gages
; Regional planning
; Tropics
; Lasers
; atmospheric convection
; climate modeling
; hindcasting
; numerical model
; precipitation (climatology)
; rainfall
; relative humidity
; timescale
; tropical meteorology
; troposphere
; United States
英文摘要: In this study, several metrics and diagnostics are proposed and implemented to systematically explore and diagnose climate model biases in short-range hindcasts and quantify how fast hindcast biases approach to climate biases with an emphasis on tropical precipitation and associated moist processes. A series of 6-day hindcasts with NCAR and the U.S.Department of Energy Community AtmosphereModel, version 4 (CAM4) and version 5 (CAM5), were performed and initialized with ECMWF operational analysis every day at 0000 UTC during the Year of Tropical Convection (YOTC). An AtmosphericModel Intercomparison Project (AMIP) type of ensemble climate simulations was also conducted for the same period. The analyses indicate that initial drifts in precipitation and associated moisture processes ("fast processes") can be identified in the hindcasts, and the biases share great resemblance to those in the climate runs. Comparing to Tropical Rainfall Measuring Mission (TRMM) observations, model hindcasts produce too high a probability of low- to intermediate-intensity precipitation at daily time scales during northern summers, which is consistent with too frequently triggered convection by its deep convection scheme. For intense precipitation events (>25 mm day-1), however, the model produces a much lower probability partially because the model requires a much higher column relative humidity than observations to produce similar precipitation intensity as indicated by the proposed diagnostics. Regional analysis on precipitation bias in the hindcasts is also performed for two selected locations where most contemporary climate models show the same sign of bias. Based on moist static energy diagnostics, the results suggest that the biases in the moisture and temperature fields near the surface and in the lower and middle troposphere are primarily responsible for precipitation biases. These analyses demonstrate the usefulness of thesemetrics and diagnostics to diagnose climate model biases. © 2013 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51988
Appears in Collections: 气候变化事实与影响
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作者单位: Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA, United States
Recommended Citation:
Ma H.-Y.,Xie S.,Boyle J.S.,et al. Metrics and diagnostics for precipitation-related processes in climate model short-range hindcasts[J]. Journal of Climate,2013-01-01,26(5)