基于NCEP、ECMWF、MERRA三套再分析数据的全球山脉力矩数据集(1979-2012)

A Global Mountain Torque Dataset Based on Reanalysis of Three Previous Compilations

山脉力矩是大气与固体地球角动量交换的传输途径之一,直接影响大气环流的状态。作者采用Huang等(1999)修正的山脉力矩计算方法,利用目前较为广泛使用的NCEP(National Centers for Environmental Prediction)、ECMWF(European Centre for Medium-Range Weather Forecasts)和MERRA(The Modem Era Retrospective analysis for Research and Applications)三套再分析数据,计算得到全球范围内1979–2012年平均的山脉力矩空间分布数据;并计算了1979–2012历年欧亚大陆、北美洲和南美洲三个区域的山脉力矩距平,得到基于三套再分析数据的全球山脉力矩数据集。本数据集包括两部分:(1)1979–2012年欧亚大陆、北美洲和南美洲三个区域每年的山脉力矩距平数据;(2)1979–2012年平均的全球山脉力矩空间分布数据。其中基于NCEP数据的结果空间分辨率为T62高斯格点(192×94),基于ECMWF数据的结果空间分辨率为0.75°×0.75°的均匀格点(480×241),基于MERRA数据的结果空间格点为(2/3)°经度×(1/2)°纬度(540×361)。本数据集存储为.xlsx、.grd和.nc格式,由7个数据文件组成,数据量2.53 MB(压缩为1个文件,1.58 MB)。该数据集的研究成果已经发表在《气象学报》2017年第75卷第3期。

Mountain torque is one of the most important ways by which angular momentum is transported between the solid Earth and the atmosphere.This phenomenon is important because it can influence atmospheric circulation.We applied the method of Huang(1999)to calculate mountain torque based via reanalysis of data derived from NCEP(National Centers for Environmental Prediction),ECMWF(European Centre for Medium-Range Weather Forecasts)and MERRA(The Modem Era Retrospective analysis for Research and Applications).The dataset presented here comprises two parts:(1)anomalous mountain torque seen in Eurasia,North America,and South America over the period between 1979 and 2012;and(2)the spatial distribution of average global mountain torque between 1979 and 2012.Results showed that mountain torque spatial resolution values calculated from different reanalyzed datasets were not congruent with one another because NCEP comprised a T62 Gaussian grid encompassing 192×94 points,while ECMWF covered 0.75°×0.75°and encompassed 480×241 points,while MERRA covered 2/3°×1/2°and encompassed 540×361 points.We also integrated mountain torque from three regions in this study,Eurasia(1.5°N–77°N,169.5°W–26°E),North America(7.5°N–71.5°N,168°W–56°W),and South America(12°N–53.5°N,81.5°W–35°W).This dataset is archived in.xlsx,.grd,and.nc formats with the data size of 2.53 MB in seven files(compressed to one file,1.58 MB).The analysis related to this dataset was published in Acta Meteorologica Sinica in 2017(Vol.75,No.3).