2016Geophysical Research LettersOpen access

Development of a 0.5° global monthly raining day product from 1901 to 2010

Susan Stillman, Xubin Zeng

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Abstract

Abstract While several long‐term global data sets of monthly precipitation amount (P) are widely available, only the Climate Research Unit (CRU) provides long‐term global monthly raining day number (N) data (i.e., daily precipitation frequency in a month), with P/N representing the daily precipitation intensity. However, because CRU N is based on a limited number of gauges, it is found to perform poorly over data sparse regions. By combining the CRU method with a short‐term gauge‐satellite merged global daily precipitation data set (Climate Prediction Center morphing technique) and a global long‐term monthly precipitation data set (Global Precipitation Climatology Centre) with far more gauges than used in CRU, a new 0.5° global N data set from 1901 to 2010 is developed, which differs significantly from CRU N. Compared with three independent regional daily precipitation products over the U.S., China, and South America based on much denser gauge networks than used in CRU, the new product shows significant improvement over CRU N.

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Abstract While several long‐term global data sets of monthly precipitation amount (P) are widely available, only the Climate Research Unit (CRU) provides long‐term global monthly raining day number (N) data (i.e., daily precipitation frequency in a month), with P/N representing the daily precipitation intensity. However, because CRU N is based on a limited number of gauges, it is found to perform poorly over data sparse regions. By combining the CRU method with a short‐term gauge‐satellite merged global daily precipitation data set (Climate Prediction Center morphing technique) and a global long‐term monthly precipitation data set (Global Precipitation Climatology Centre) with far more gauges than used in CRU, a new 0.5° global N data set from 1901 to 2010 is developed, which differs significantly from CRU N. Compared with three independent regional daily precipitation products over the U.S., China, and South America based on much denser gauge networks than used in CRU, the new product shows significant improvement over CRU N.

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Available abstract

Abstract While several long‐term global data sets of monthly precipitation amount (P) are widely available, only the Climate Research Unit (CRU) provides long‐term global monthly raining day number (N) data (i.e., daily precipitation frequency in a month), with P/N representing the daily precipitation intensity. However, because CRU N is based on a limited number of gauges, it is found to perform poorly over data sparse regions. By combining the CRU method with a short‐term gauge‐satellite merged global daily precipitation data set (Climate Prediction Center morphing technique) and a global long‐term monthly precipitation data set (Global Precipitation Climatology Centre) with far more gauges than used in CRU, a new 0.5° global N data set from 1901 to 2010 is developed, which differs significantly from CRU N. Compared with three independent regional daily precipitation products over the U.S., China, and South America based on much denser gauge networks than used in CRU, the new product shows significant improvement over CRU N.

Key concepts: Cru, Precipitation, Climatology, Environmental science, Meteorology, Term (time), Data set, Geography

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