A Diagnostic Evaluation of Precipitation in CORDEX Models over Southern Africa

被引:103
作者
Kalognomou, Evangelia-Anna [1 ,2 ]
Lennard, Christopher [1 ,2 ]
Shongwe, Mxolisi [3 ]
Pinto, Izidine [1 ,2 ]
Favre, Alice [1 ,4 ]
Kent, Michael [1 ,2 ]
Hewitson, Bruce [1 ,2 ]
Dosio, Alessandro [5 ]
Nikulin, Grigory [6 ]
Panitz, Hans-Juergen [7 ]
Buechner, Matthias [8 ]
机构
[1] Univ Cape Town, ZA-7925 Cape Town, South Africa
[2] Aristotle Univ Thessaloniki, Lab Heat Transfer & Environm Engn, GR-54006 Thessaloniki, Greece
[3] South African Weather Serv, Pretoria, South Africa
[4] Univ Bourgogne, Ctr Rech Climatol, Biogeosci CNRS, Dijon, France
[5] Inst Environm & Sustainabil, European Commiss Joint Res Ctr, Ispra, Italy
[6] Swedish Meteorol & Hydrol Inst, Rossby Ctr, S-60176 Norrkoping, Sweden
[7] Karlsruher Inst Technol, Inst Meteorol & Klimaforsch, Karlsruhe, Germany
[8] Potsdam Inst Climate Impact Res, Potsdam, Germany
关键词
Climate prediction; Climate variability; Climatology; Regional models; REGIONAL CLIMATE MODEL; NUMERICAL WEATHER PREDICTION; FLUX CONVECTION SCHEME; PART I; PARAMETERIZATION SCHEMES; CUMULUS PARAMETERIZATION; RAINFALL ESTIMATION; PHYSICAL PARAMETERIZATIONS; INTERANNUAL VARIABILITY; INTERNAL VARIABILITY;
D O I
10.1175/JCLI-D-12-00703.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The authors evaluate the ability of 10 regional climate models (RCMs) to simulate precipitation over Southern Africa within the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. An ensemble of 10 regional climate simulations and the ensemble average is analyzed to evaluate the models' ability to reproduce seasonal and interannual regional climatic features over regions of the subcontinent. All the RCMs use a similar domain, have a spatial resolution of 50 km, and are driven by the Interim ECMWF Re-Analysis (ERA-Interim; 1989-2008). Results are compared against a number of observational datasets.In general, the spatial and temporal nature of rainfall over the region is captured by all RCMs, although individual models exhibit wet or dry biases over particular regions of the domain. Models generally produce lower seasonal variability of precipitation compared to observations and the magnitude of the variability varies in space and time. Model biases are related to model setup, simulated circulation anomalies, and moisture transport. The multimodel ensemble mean generally outperforms individual models, with bias magnitudes similar to differences across the observational datasets. In the northern parts of the domain, some of the RCMs and the ensemble average improve the precipitation climate compared to that of ERA-Interim. The models are generally able to capture the dry (wet) precipitation anomaly associated with El Nino (La Nina) events across the region. Based on this analysis, the authors suggest that the present set of RCMs can be used to provide useful information on climate projections of rainfall over Southern Africa.
引用
收藏
页码:9477 / 9506
页数:30
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