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首页> 外文期刊>Agricultural and Forest Meteorology >Modelling solar radiation over complex terrains using monthly climatological data.
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Modelling solar radiation over complex terrains using monthly climatological data.

机译：使用月度气候数据模拟复杂地形上的太阳辐射。

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摘要

Meteorological stations placed in remote areas (such as mountainous sites) often record only precipitation and air temperature data, summarised into monthly tables. There is therefore a need for appropriate methods to estimate solar radiation data from monthly inputs. It is important to know the quality and characteristics of the estimates made in order to understand what impacts the modelled data may have on the use to which they are meant. This paper evaluates the behaviour of two empirical models based on the difference between maximum and minimum air temperatures and compares results with a newly developed model, for 24 stations (11 for model calibration, the rest for model validation) in Italian sites. The new model (SRMCT, solar radiation model for complex terrains) replaces the minimum air temperature with a monthly function and uses rainy days number to correct the air temperature range. Comparisons were made using a fuzzy-logic-based multiple-statistics assessment approach (Irad). An appraisal of the temporal distribution of mean errors over a year was also performed. The new model produced the best overall estimates. The two air temperature-based models can be an alternative approach when only air temperature data are available, but at many sites they introduced large inaccuracies and seasonal patterns in the error distribution. The study demonstrates the appropriateness of both air temperature range and rain correction factors for monthly based solar radiation estimates. At the same time, it shows the value and importance of using a range of assessment statistics, even aggregated into an overall indicator, to evaluate model estimates..
机译：偏远地区（如山区）的气象站通常仅记录降水和气温数据，汇总为月度表。因此，需要一种适当的方法来根据每月的投入估算太阳辐射数据。重要的是要了解所做估计的质量和特征，以便了解建模数据可能对预期用途产生的影响。本文根据最高和最低气温之间的差异评估了两个经验模型的行为，并将结果与​​最新开发的模型进行了比较，在意大利站点中有24个站点（其中11个用于模型校准，其余的用于模型验证）。新模型（SRMCT，复杂地形的太阳辐射模型）以每月函数代替最低气温，并使用雨天数来校正气温范围。使用基于模糊逻辑的多元统计评估方法（Irad）进行比较。还对一年中平均误差的时间分布进行了评估。新模型产生了最佳的总体估计。当仅可获得空气温度数据时，这两种基于空气温度的模型可以作为一种替代方法，但是在许多站点，它们在误差分布中引入了很大的误差和季节性模式。这项研究证明了气温范围和降雨校正因子对于基于月度太阳辐射估算的适用性。同时，它显示了使用一系列评估统计数据（甚至汇总为总体指标）评估模型估计的价值和重要性。

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