Simulating precipitation and temperature in the Lake Champlain basin using a regional climate model: limitations and uncertainties
Simulating precipitation and temperature in the Lake Champlain basin using a regional climate model: limitations and uncertainties
复制标题
使用区域气候模型模拟尚普兰湖盆地的降水和温度：局限性和不确定性
DOI：
10.1007/s00382-019-04987-8
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发表时间：
2019
期刊：
影响因子：
4.6
通讯作者：
B. Beckage
中科院分区：
文献类型：
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作者：
Huanping Huang;J. Winter;E. Osterberg;J. Hanrahan;C. Bruyère;P. Clemins;B. Beckage
尚普兰湖盆地对美国东北部和加拿大魁北克具有社会经济和生态意义。在过去三十年中，该地区的气温和极端降水事件一直在增加。准确、高分辨率的气候模拟对于评估尚普兰湖流域潜在的气候变化风险至关重要。我们评估了一个区域气候模型，天气研究和预报（WRF）模型的性能，降尺度的ERA中期再分析数据，4公里的尚普兰湖盆地。具体来说，我们比较了五个WRF实验的集合，这些实验具有不同的物理配置，使用单向，三重嵌套域（36，12和4 km），在三个5年的时间段（1980-1984，1995-1999和2010-2014）内，与网格观测数据集Daymet进行比较。我们发现，WRF模拟的尚普兰湖盆地一般重现所观察到的温度和降水的季节性周期，但有寒冷和潮湿的偏见。WRF对平均温度的模拟对辐射方案的选择最为敏感，而对平均降水的模拟对辐射、积云和微物理方案的选择最为敏感。我们发现，打开积云方案，提高了模拟的降水季节性循环在4公里的分辨率，但也大大提高了湿偏差。使用较粗的分辨率（36公里）产生较小的区域平均降水偏差，但没有改善模拟和观测到的月降水量之间的相关性。空间分辨率和关闭积云方案对模拟温度的影响较小。
The Lake Champlain Basin has socioeconomic and ecological significance for the Northeastern United States and Quebec, Canada. Temperatures and extreme precipitation events have been increasing across this region over the past three decades. Accurate, high-resolution climate simulations are critical to assessing potential climate change risk in the Lake Champlain Basin. We evaluate the performance of a regional climate model, the Weather Research and Forecasting (WRF) model, to downscale ERA-Interim reanalysis data to 4 km for the Lake Champlain Basin. Specifically, we compare an ensemble of five WRF experiments with different physics configurations using a one-way, triple-nested domain (36, 12, and 4 km) over three 5-year periods (1980–1984, 1995–1999, and 2010–2014) to Daymet, a gridded observational dataset. We find that WRF simulations of the Lake Champlain Basin generally reproduce the observed temperature and precipitation seasonal cycles, but have cold and wet biases. The simulation of mean temperature by WRF is most sensitive to the choice of radiation scheme, while the simulation of mean precipitation is most sensitive to the choice of radiation, cumulus, and microphysics scheme. We find that turning the cumulus scheme on improves the simulation of the precipitation seasonal cycle at a 4 km resolution, but also substantially enhances the wet bias. Using a coarser resolution (36 km) produces smaller regionally averaged precipitation biases, but not improved correlations between simulated and observed monthly precipitation. Both spatial resolution and turning the cumulus scheme off have minor effects on simulated temperature.