CHIRTSdaily

Assessing weather-related hazards in a changing climate requires data sets that have accurate high-resolution spatial mean fields, good performance in data-sparse regions, and limited sources of non-stationary errors. High-resolution mean fields are important because impacts on health, agriculture, and other sectors are always local and typically non-linear. Impacts on humans or crops will be related to extremes in specific locations, and these impacts will often be strongly related to the variations in the absolute value of the weather variable under consideration. At present, there is a dearth of accurate information supporting the monitoring and evaluation of extreme temperatures in many food-insecure regions. Such extremes can wilt crops or decimate livestock herds, setting the stage for famine. Yet our ability to track these extremes in countries without weather station observations remains very limited. To address this limitation, the Climate Hazards Center (CHC) has developed a quasi-global (60°S – 70°N), high-resolution (0.05° x 0.05°, approx. 5km) data set of daily maximum and minimum temperatures, which we refer to as CHIRTS-daily. The CHIRTS-daily development and validation process is outlined in Figure 1. Briefly, the monthly fields from the CHIRTSmax1 data series are temporally disaggregated using downscaled fields from version 5 of the European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA52,3). The ERA5 has been shown to have robust performance with respect to spatial covariance and daily anomalies. However, ERA5 shows significant cool bias globally, and most notably in Africa. This cool bias in turn results in ERA5 underrepresenting the number of extreme hot days globally, and most notably in Africa. Figure 2 quantifies the representation of hot days for ERA5, CHIRTS-daily, Princeton’s Global Meteorological Forcing dataset (PGF), and stations from the ~15,000 Berkeley Earth database. Table 1 quantifies the difference in mean number of hot days between 2007-2016 and 1983-1992 for these products.

搜集汇总

背景与挑战

背景概述

CHIRTS-daily是一个全球高分辨率（约5公里）每日温度数据集，覆盖60°S至70°N范围，结合了CHIRTSmax月数据和ERA5再分析数据，以准确监测极端温度事件，尤其适用于数据稀疏地区如非洲，支持健康、农业等领域的应用。