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Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm
المؤلفون المشاركون
Gao, Lu
Bernhardt, Matthias
Schulz, Karsten
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-07-10
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Precipitation is an essential input parameter for land surface models because it controls a large variety of environmental processes.
However, the commonly sparse meteorological networks in complex terrains are unable to provide the information needed for many applications.
Therefore, downscaling local precipitation is necessary.
To this end, a new machine learning method, LASSO algorithm (least absolute shrinkage and selection operator), is used to address the disparity between ERA-Interim forecast precipitation data (0.25° grid) and point-scale meteorological observations.
LASSO was tested and validated against other three downscaling methods, local intensity scaling (LOCI), quantile-mapping (QM), and stepwise regression (Stepwise) at 50 meteorological stations, located in the high mountainous region of the central Alps.
The downscaling procedure is implemented in two steps.
Firstly, the dry or wet days are classified and the precipitation amounts conditional on the occurrence of wet days are modeled subsequently.
Compared to other three downscaling methods, LASSO shows the best performances in precipitation occurrence and precipitation amount prediction on average.
Furthermore, LASSO could reduce the error for certain sites, where no improvement could be seen when LOCI and QM were used.
This study proves that LASSO is a reasonable alternative to other statistical methods with respect to the downscaling of precipitation data.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Gao, Lu& Schulz, Karsten& Bernhardt, Matthias. 2014. Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm. Advances in Meteorology،Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-474259
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Gao, Lu…[et al.]. Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm. Advances in Meteorology No. 2014 (2014), pp.1-16.
https://search.emarefa.net/detail/BIM-474259
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Gao, Lu& Schulz, Karsten& Bernhardt, Matthias. Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm. Advances in Meteorology. 2014. Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-474259
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-474259
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