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Climate change analysis in southern Telangana region, Andhra Pradesh using LARS-WG model

机译:基于LARS-WG模型的安得拉邦Telangana南部地区的气候变化分析

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Weather-generating models are widely used for studying the climate change over longer periods. LARS-WG model was evaluated for southern Telangana region (Hayathnagar, Yacharam and Rajendranagar). A 30-year base weather data (1980-2010) was used to generate the long-term weather series from 2011 to 2060. The results of t and F tests at probability of 5% for comparing means and standard deviations of monthly rainfall and air temperatures indicated that the observed and predicted series for the base period are within acceptable limits. The statistics of model efficiency indicates that mean monthly rainfall and daily air temperature are close to the predicted series over the base period. The model efficiency was highest in the case of Rajendranagar (98.75%). The root mean square error and sum of square error varied from 0.4 to 1.3 mm and 615 to 1745 mm respectively. The model predicted the maximum increase in average annual rainfall of 5.16% in 2030 and 9.5% in 2060 for Yacharam compared to Hayathnagar and Rajendranagar over the normal annual rainfall of the base period (1980-2010). However, the model predicted increase in average seasonal rainfall for Hayathnagar (6.2% in 2030 and 8.8% in 2060). In case of air temperature, the model predicted increase in maximum temperature in the range 1-1.53% and 2.5% for 2030 and 2060 respectively, for these locations whereas minimum temperature decreased in the range 3.7-10.2% and 6.3-11.7% respectively, for 2030 and 2060. The performance of LARS-WG model was ranked high with maximum model efficiency in all selected mandals of Ranga Reddy district in southern Telangana. This model can be replicated in other mandals of southern Telangana as climate characteristics of the present mandals are similar to other districts in the region.
机译:天气生成模型被广泛用于研究较长时期的气候变化。 LARS-WG模型在Telangana南部地区(Hayathnagar,Yacharam和Rajendranagar)进行了评估。使用30年的基础天气数据(1980-2010)生成了2011年至2060年的长期天气序列。t和F检验的结果的概率为5%,用于比较每月降雨和空气的平均值和标准偏差温度表明基期的观测序列和预测序列均在可接受的范围内。模型效率的统计数据表明,在基准期内,平均每月降雨量和每日气温接近于预测序列。在Rajendranagar的情况下,模型效率最高(98.75%)。均方根误差和平方和之和分别从0.4到1.3 mm和615到1745 mm不等。该模型预测,在基期的正常年降雨量(1980-2010年)中,亚哈拉姆邦的20年平均降雨量最大增幅分别为2030年的5.16%和2060年的9.5%,与Hayathnagar和Rajendranagar相比。但是,该模型预测了Hayathnagar的平均季节性降雨量将增加(2030年为6.2%,2060年为8.8%)。在空气温度的情况下,模型预测,在这些位置,2030年和2060年的最高温度分别升高1-1.53​​%和2.5%,而最低温度分别降低3.7-10.2%和6.3-11.7%。在2030年和2060年期间,LARS-WG模型的性能在泰兰加纳州南部Ranga Reddy地区的所有选定的中部中以最高的模型效率名列前茅。该模型可以在泰兰加纳州南部的其他海域中复制,因为目前这些海域的气候特征与该地区其他地区相似。

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