نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشیار، گروه مهندسی آبیاری و آبادانی، دانشکده کشاورزی، دانشکدگان کشاورزی و منابع طبیعی، دانشگاه تهران، کرج، ایران.
2 هواشناسی کشاورزی دانشگاه تهران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
The importance of choosing appropriate methods for data reconstruction is clearly evident. Given the increasing spread of climate change and its effects on plants and other living organisms, the need for accurate and reliable data is felt more than ever. Therefore, researchers and decision-makers should pay special attention to analyzing and selecting data reconstruction methods so that they can take steps towards optimal resource management and reducing the negative effects of climate change. The aim of this study was to investigate the effect of reconstructing random statistical gaps in the daily minimum and maximum temperature data of the Kohrang station (base station) using the multiple linear regression method and with the help of neighboring stations. For this purpose, 5 to 50 percent (with an interval of 5 percent) of the daily minimum and maximum temperature data at the Kohrang station were randomly considered statistical gaps. Then, data gaps were calculated using the multiple linear regression method and the estimation error was determined for different percentages of statistical gaps. Reconstruction errors were reviewed and evaluated on a monthly and annual basis.
کلیدواژهها [English]
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