Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates
Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates
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DOI：
10.3354/cr010095
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发表时间：
1998-08-14
期刊：
影响因子：
1.1
通讯作者：
Richardson, CW
中科院分区：
文献类型：
--
作者：
Semenov, MA;Brooks, RJ;Richardson, CW
随机天气发生器被广泛用于各种研究，如水文应用、环境管理和农业风险评估。这类研究往往需要一长串的每日天气数据进行风险评估，而天气生成器可以生成任何长度的合成每日天气数据的时间序列。天气生成器还用于对观测数据进行插值，以生成新站点的合成天气数据，最近还用于构建气候变化情景。任何发生器都应进行测试，以确保其产生的数据符合其使用目的，所需的准确性将取决于数据的应用，并且发生器的性能在不同的气候下可能会有很大差异。本文的目的是测试和比较两种常用的天气发生器，即WGEN和LARS-WG，在美国，欧洲和亚洲的18个地点，选择代表一系列的气候。选择统计检验来比较观测到的和合成的天气数据的各种不同的天气特征，例如，潮湿和干燥系列的长度，降水的分布和霜冻的长度。LARS-WG生成器对天气变量使用了更复杂的分布，与WGEN生成器相比，往往更接近于观测数据，尽管两个生成器都没有准确再现数据的某些特征。随机天气发生器的发展和使用的影响进行了讨论。
Stochastic weather generators are used in a wide range of studies, such as hydrological applications, environmental management and agricultural risk assessments. Such studies often require long series of daily weather data for risk assessment and weather generators can produce time series of synthetic daily weather data of any length. Weather generators are also used to interpolate observed data to produce synthetic weather data at new sites, and they have recently been employed in the construction of climate change scenarios. Any generator should be tested to ensure that the data that it produces is satisfactory for the purposes for which it is to be used,The accuracy required will depend on the application of the data, and the performance of the generator may vary considerably for different climates. The aim of this paper is to test and compare 2 commonly-used weather generators, namely WGEN and LARS-WG, at 18 sites in the USA, Europe and Asia, chosen to represent a range of climates. Statistical tests were selected to compare a variety of different weather characteristics of the observed and synthetic weather data such as, for example, the lengths of wet and dry series, the distribution of precipitation and the lengths of frost spells. The LARS-WG generator used more complex distributions for weather variables and tended to match the observed data more closely than WGEN, although there are certain characteristics of the data that neither generator reproduced accurately. The implications for the development and use of stochastic weather generators are discussed.