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==Model output statistics 模式输出统计==
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==模式输出统计==
{{Main|Model output statistics}}
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由于基于大气动力学方程的预报模式无法完美地决定近地天气状况,人们开发了统计修正的方法来尝试解决这个问题。统计模型基于数值天气模式、地面观测站、特定地点的气候条件产生的三维场。这些统计模型被统称为模式输出统计 model output statistics(MOS),<ref>{{cite book|url=https://books.google.com/books?id=blEMoIKX_0IC&pg=PA188|page=189|title=When nature strikes: weather disasters and the law|author=Baum, Marsha L.|publisher=Greenwood Publishing Group|year=2007|isbn=978-0-275-22129-4}}</ref> 并由美国国家气象局开发为一套完整的天气预报模式。<ref name="MOS">{{cite book|title=Model output statistics forecast guidance|author=Harry Hughes|publisher=United States Air Force Environmental Technical Applications Center|year=1976|pages=1–16}}</ref>美国空军在1983年根据其动态天气模式开发了自己的MOS。<ref name="L. Best, D. L. and S. P. Pryor 1983 1–90"/>
Because forecast models based upon the equations for atmospheric dynamics do not perfectly determine weather conditions near the ground, statistical corrections were developed to attempt to resolve this problem. Statistical models were created based upon the three-dimensional fields produced by numerical weather models, surface observations, and the climatological conditions for specific locations.  These statistical models are collectively referred to as [[model output statistics]] (MOS),<ref>{{cite book|url=https://books.google.com/books?id=blEMoIKX_0IC&pg=PA188|page=189|title=When nature strikes: weather disasters and the law|author=Baum, Marsha L.|publisher=Greenwood Publishing Group|year=2007|isbn=978-0-275-22129-4}}</ref> and were developed by the [[National Weather Service]] for their suite of weather forecasting models.<ref name="MOS">{{cite book|title=Model output statistics forecast guidance|author=Harry Hughes|publisher=United States Air Force Environmental Technical Applications Center|year=1976|pages=1–16}}</ref> The [[United States Air Force]] developed its own set of MOS based upon their dynamical weather model by 1983.<ref name="L. Best, D. L. and S. P. Pryor 1983 1–90"/>
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Because forecast models based upon the equations for atmospheric dynamics do not perfectly determine weather conditions near the ground, statistical corrections were developed to attempt to resolve this problem. Statistical models were created based upon the three-dimensional fields produced by numerical weather models, surface observations, and the climatological conditions for specific locations.  These statistical models are collectively referred to as model output statistics (MOS), and were developed by the National Weather Service for their suite of weather forecasting modelsThe United States Air Force developed its own set of MOS based upon their dynamical weather model by 1983.
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模型输出统计不同于完美的预测图(prog),后者假定数值天气预报指导的输出是完美的。<ref>{{cite book|url=https://books.google.com/books?id=QwzHZ-wV-BAC&pg=PA1144|page=1144|title=Fog and boundary layer clouds: fog visibility and forecasting|author=Gultepe, Ismail|publisher=Springer|year=2007|isbn=978-3-7643-8418-0}}</ref>而MOS可以修正因网格分辨率不足以及模型偏差等模式无法解决的局地效应。MOS中的预报参数包括最高和最低温度、未来数小时降雨可能性、预期降水量、降水在自然界中结冰的可能性、雷暴可能性、云量和地面风。<ref>{{cite book|url=https://books.google.com/books?id=Xs9LiGpNX-AC&pg=PA171|page=172|author1=Barry, Roger Graham |author2=Richard J. Chorley |name-list-style=amp |title=Atmosphere, weather, and climate|publisher=Psychology Press|year=2003|isbn=978-0-415-27171-4}}</ref>
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由于基于大气动力学方程式的预报模式不能完全确定近地天气状况,因此开发了统计修正以试图解决这一问题。基于数值天气模型、地面观测和特定地点的气候条件产生的三维场,建立了统计模型。这些统计模型统称为模型输出统计(MOS) ,由国家气象局为他们的一套天气预报模型开发。到1983年,美国空军根据其动态天气模型开发了自己的一套 MOS。
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【终稿】由于基于大气动力学方程的预报模式无法完美地决定近地天气状况,人们开发了统计修正的方法来尝试解决这个问题。统计模型基于数值天气模式、地面观测站、特定地点的气候条件产生的三维场。这些统计模型被统称为模式输出统计(MOS),并由美国国家气象局开发为一套完整的天气预报模式。美国空军在1983年根据其动态天气模式开发了自己的MOS。
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Model output statistics differ from the ''perfect prog'' technique, which assumes that the output of numerical weather prediction guidance is perfect.<ref>{{cite book|url=https://books.google.com/books?id=QwzHZ-wV-BAC&pg=PA1144|page=1144|title=Fog and boundary layer clouds: fog visibility and forecasting|author=Gultepe, Ismail|publisher=Springer|year=2007|isbn=978-3-7643-8418-0}}</ref>  MOS can correct for local effects that cannot be resolved by the model due to insufficient grid resolution, as well as model biases.  Forecast parameters within MOS include maximum and minimum temperatures, percentage chance of rain within a several hour period, precipitation amount expected, chance that the precipitation will be frozen in nature, chance for thunderstorms, cloudiness, and surface winds.<ref>{{cite book|url=https://books.google.com/books?id=Xs9LiGpNX-AC&pg=PA171|page=172|author1=Barry, Roger Graham  |author2=Richard J. Chorley |name-list-style=amp |title=Atmosphere, weather, and climate|publisher=Psychology Press|year=2003|isbn=978-0-415-27171-4}}</ref>
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Model output statistics differ from the perfect prog technique, which assumes that the output of numerical weather prediction guidance is perfect.  MOS can correct for local effects that cannot be resolved by the model due to insufficient grid resolution, as well as model biases.  Forecast parameters within MOS include maximum and minimum temperatures, percentage chance of rain within a several hour period, precipitation amount expected, chance that the precipitation will be frozen in nature, chance for thunderstorms, cloudiness, and surface winds.
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模型输出统计不同于完美的前端技术,前端技术假设数值天气预报指导的输出是完美的。MOS 可以修正由于网格分辨率不足以及模型偏差而无法由模型解决的局部效应。MOS 内的预报参数包括最高和最低气温、几个小时内降雨的百分比、预期降水量、降水在自然界结冰的可能性、雷暴的可能性、云量和地面风。
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【终稿】模型输出统计不同于完美的预测图(prog),后者假定数值天气预报指导的输出是完美的。而MOS可以修正因网格分辨率不足以及模型偏差等模式无法解决的局地效应。MOS中的预报参数包括最高和最低温度、未来数小时降雨可能性、预期降水量、降水在自然界中结冰的可能性、雷暴可能性、云量和地面风。
      
== Applications ==
 
== Applications ==
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