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首页> 外文期刊>International Journal of Biometeorology: Journal of the International Society of Biometeorology >Stochastic simulation of daily air temperature and precipitation from monthly normals in North America north of Mexico
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Stochastic simulation of daily air temperature and precipitation from monthly normals in North America north of Mexico

机译：墨西哥北部北美北美地区每月气温和降水的随机模拟

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摘要

A simple, stochastic daily temperature and precipitation generator (TEMPGEN) was developed to generate inputs for the study of the effects of climate change on models driven by daily weather information when climate data are available as monthly summaries. The model uses as input only 11 sets of monthly normal statistics from individual weather stations. It needs no calibration, and was parameterized and validated for use in Canada and the continental United States. Monthly normals needed are: mean and standard deviation of daily minimum and maximum temperature, first and second order autoregressive terms for daily deviations of minimum and maximum temperatures from their daily means, correlation of deviations of daily minimum and maximum temperatures, total precipitation, and the interannual variance of total precipitation. The statistical properties and distributions of daily temperature and precipitation data produced by this generator compared quite favorably with observations from 708 stations throughout North America (north of Mexico). The algorithm generates realistic seasonal patterns, variability and extremes of temperature, precipitation, frost-free periods and hot spells. However, it predicts less accurately the daily probability of precipitation, extreme precipitation events and the duration of extreme droughts.
机译：开发了一个简单的随机日温度和降水量生成器（TEMPGEN），以生成输入，用于在气候数据作为月度摘要可用时研究气候变化对由每日天气信息驱动的模型的影响。该模型仅使用来自各个气象站的11组每月正常统计数据作为输入。它不需要校准，并且已经过参数化和验证，可以在加拿大和美国本土使用。每月所需的法线是：每日最低和最高温度的平均值和标准偏差，最低和最高温度与每日平均值的每日偏差的一阶和二阶自回归项，每日最低和最高温度的偏差，总降水量以及总降水量的年际变化。该发生器产生的每日温度和降水量数据的统计特性和分布与北美（墨西哥北部）708个站点的观测结果相比非常有利。该算法生成逼真的季节性模式，温度，降水，无霜期和炎热季节的变化性和极端性。但是，它不能准确地预测每天的降水概率，极端降水事件和极端干旱的持续时间。

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