...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Climate >Evaluation of the Surface Climatology over the Conterminous United States in the North American Regional Climate Change Assessment Program Hindcast Experiment Using a Regional Climate Model Evaluation System
【24h】

Evaluation of the Surface Climatology over the Conterminous United States in the North American Regional Climate Change Assessment Program Hindcast Experiment Using a Regional Climate Model Evaluation System

机译：使用区域气候模型评估系统，在北美区域气候变化评估计划的后播实验中评估美国本土的地表气候

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Surface air temperature, precipitation, and insolation over the conterminous United States region from the North American Regional Climate Change Assessment Program (NARCCAP) regional climate model (RCM) hindcast study are evaluated using the Jet Propulsion Laboratory (JPL) Regional Climate Model Evaluation System (RCMES). All RCMs reasonably simulate the observed climatology of these variables. RCM skill varies more widely for the magnitude of spatial variability than the pattern. The multimodel ensemble is among the best performers for all these variables. Systematic biases occur across these RCMs for the annual means, with warm biases over the Great Plains (GP) and cold biases in the Atlantic and the Gulf of Mexico (GM) coastal regions. Wet biases in the Pacific Northwest and dry biases in the GM/southern Great Plains also occur in most RCMs. All RCMs suffer problems in simulating summer rainfall in the Arizona-New Mexico region. RCMs generally overestimate surface insolation, especially in the eastern United States. Negative correlation between the biases in insolation and precipitation suggest that these two fields are related, likely via clouds. Systematic variations in biases for regions, seasons, variables, and metrics suggest that the bias correction in applying climate model data to assess the climate impact on various sectors must be performed accordingly. Precipitation evaluation with multiple observations reveals that observational data can be an important source of uncertainties in model evaluation; thus, cross examination of observational data is important for model evaluation.
机译：使用喷气推进实验室（JPL）区域气候模式评估系统评估了北美区域气候变化评估计划（NARCCAP）区域气候模型（RCM）后预报研究中美国本土附近的地表气温，降水和日照（ RCMES）。所有RCM都合理地模拟了这些变量的观测气候。与模式相比，RCM技能在空间可变性的幅度上变化更大。在所有这些变量中，多模型合奏是性能最好的。这些RCM在年度平均值上会出现系统性偏差，其中大平原（GP）会出现温暖的偏差，而大西洋和墨西哥湾（GM）沿海地区会出现冷偏差。大多数RCM中也出现了西北太平洋的湿偏向和GM /南部大平原的干偏向。在亚利桑那州-新墨西哥州地区，所有RCM都在模拟夏季降雨方面遇到问题。 RCM通常会高估表面日射量，尤其是在美国东部。日照偏差与降水偏差之间的负相关表明这两个场可能是通过云相关的。区域，季节，变量和度量的偏差的系统变化表明，在应用气候模型数据评估气候对各个部门的影响时，必须进行偏差校正。多次观测的降水评估表明，观测数据可能是模型评估中不确定性的重要来源。因此，观测数据的交叉检查对于模型评估很重要。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号