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Improving Regional Dynamic Downscaling with Multiple Linear Regression Model Using Components Principal Analysis : Precipitation over Amazon and Northeast Brazil
المؤلفون المشاركون
da Silva, Aline Gomes
e Silva, Claudio Moises Santos
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-07-10
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
In the current context of climate change discussions, predictions of future scenarios of weather and climate are crucial for the generation of information of interest to the global community.
Due to the atmosphere being a chaotic system, errors in predictions of future scenarios are systematically observed.
Therefore, numerous techniques have been tested in order to generate more reliable predictions, and two techniques have excelled in science: dynamic downscaling, through regional models, and ensemble prediction, combining different outputs of climate models through the arithmetic average, in other words, a postprocessing of the output data species.
Thus, this paper proposes a method of postprocessing outputs of regional climate models.
This method consists in using the statistical tool multiple linear regression by principal components for combining different simulations obtained by dynamic downscaling with the regional climate model (RegCM4).
Tests for the Amazon and Northeast region of Brazil (South America) showed that the method provided a more realistic prediction in terms of average daily rainfall for the analyzed period prescribed, after comparing with the prediction made by set through the arithmetic averages of the simulations.
This method photographed the extreme events (outlier) that the prediction by averaging failed.
Data from the Tropical Rainfall Measuring Mission (TRMM) were used to evaluate the method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
da Silva, Aline Gomes& e Silva, Claudio Moises Santos. 2014. Improving Regional Dynamic Downscaling with Multiple Linear Regression Model Using Components Principal Analysis : Precipitation over Amazon and Northeast Brazil. Advances in Meteorology،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-508923
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
da Silva, Aline Gomes& e Silva, Claudio Moises Santos. Improving Regional Dynamic Downscaling with Multiple Linear Regression Model Using Components Principal Analysis : Precipitation over Amazon and Northeast Brazil. Advances in Meteorology No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-508923
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
da Silva, Aline Gomes& e Silva, Claudio Moises Santos. Improving Regional Dynamic Downscaling with Multiple Linear Regression Model Using Components Principal Analysis : Precipitation over Amazon and Northeast Brazil. Advances in Meteorology. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-508923
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-508923
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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