4.2 Article

Evaluation of WRF Model Forecasts and Their Use for Hydroclimate Monitoring over Southern South America

期刊

WEATHER AND FORECASTING
卷 31, 期 3, 页码 1001-1017

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/WAF-D-15-0130.1

关键词

-

资金

  1. UNL project CAI+D
  2. Inter-American Institute for Global Change Research (IAI) [CRN3035, CRN3095]
  3. National Science Foundation
  4. NOAA [NA14NES4320003]
  5. ICER
  6. Directorate For Geosciences [1128040] Funding Source: National Science Foundation

向作者/读者索取更多资源

Weather forecasting and monitoring systems based on regional models are becoming increasingly relevant for decision support in agriculture and water management. This work evaluates the predictive and monitoring capabilities of a system based on WRF Model simulations at 15-km grid spacing over the La Plata basin (LPB) in southern South America, where agriculture and water resources are essential. The model's skill up to a lead time of 7 days is evaluated with daily precipitation and 2-m temperature in situ observations for the 2-yr period from 1 August 2012 to 31 July 2014. Results show high prediction performance with 7-day lead time throughout the domain and particularly over LPB, where about 70% of rain and no-rain days are correctly predicted. Also, the probability of detection of rain days is above 80% in humid regions. Temperature observations and forecasts are highly correlated (r > 0.80) while mean absolute errors, even at the maximum lead time, remain below 2.7 degrees C for minimum and mean temperatures and below 3.7 degrees C for maximum temperatures. The usefulness of WRF products for hydroclimate monitoring was tested for an unprecedented drought in southern Brazil and for a slightly above normal precipitation season in northeastern Argentina. In both cases the model products reproduce the observed precipitation conditions with consistent impacts on soil moisture, evapotranspiration, and runoff. This evaluation validates the model's usefulness for forecasting weather up to 1 week in advance and for monitoring climate conditions in real time. The scores suggest that the forecast lead time can be extended into a second week, while bias correction methods can reduce some of the systematic errors.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.2
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据