中国1km栅格月平均气温数据集

Monthly Temperature Dataset of China at 1 km Resolution

根据美国气候研究中心(NCEP/NCAR)全球近地表月平均气温要素数据结合数字高程模型(DEM)、归一化植被指数(NDVI)以及地理位置等要素之间定量关系,建立点至公里统计降尺度回归树模型,计算出中国2000年1月-2010年12月1 km空间分辨率月平均气温模型计算数据集。利用中国380个气象站点观测数据对其结果进行对比分析和验证,最终得到中国2000年1月-2010年12月间、1km分辨率、月平均气温数据集。该数据是可持续更新的中国公里网格月平均气温数据集。

Surface air temperature is an important parameter which controls land surface processes, and is crucial to ecological, environmental and hydrological modelling. Temperature records at meteorological stations have been widely used in modelling, but there has been an increasing use of temperature data in grid form, especially for remote sensing data. Although grid temperature can be estimated from in-situ temperature records using interpolation algorithms, low accuracy has been found in the estimations, due to limited distribution of ground stations, especially when there are insufficient sites to represent all land-cover types and terrain conditions in the area. The NCEP/NCAR reanalysis project has produced climate variables by using a "frozen" state-of-the-art global data assimilation system and a database as complete as possible. Although resolution of the NCEP data has a coarse resolution(0.5 degree), it provides global, consistent, and long-term estimation of climate variables. This dataset presents a downscaling approach for deriving monthly temperatures at 1 km resolution from the NCEP by utilizing derived relationships between monthly aggregated NCEP temperatures and other ground elements, i.e., terrain, vegetation and geographic locations. A regression tree model was chosen for detecting the possible relationships. Monthly temperatures at 1 km resolution during 2000 to 2010 of China’s land area have been produced using this approach. The final predicted temperatures were compared with observed records at 380 meteorological stations in China. The results indicated that the downscaled estimations can represent the spatial distribution and trends and the magnitude of temperatures on an inter-month basis, with R^2 values ranging from 0.861 to 0.948, and RMSE values from 1.88°C to 2.68°C.