摘要
青藏高原近几十年来温度升高趋势明显,是全球变化研究的热点问题之一。然而,青藏高原气象站点数目较少且空间分布严重不均,在一定程度上影响了对青藏高原气候变化的认识。卫星遥感为大尺度气候变化研究提供了一条新的途径。本研究基于多种MODIS遥感数据、DEM数据和地形指数数据提取了月平均白天/夜间地表温度、月无云天数、月平均地表反照率、月平均NDVI、月平均NDSI、海拔和CTI指数等空间自变量,运用Cubist算法通过交叉验证和参数优化构建月平均气温、月平均最高气温和月平均最低气温估算模型,生成青藏高原2001–2020年1 km分辨率遥感月平均气温、月平均最高气温和月平均最低气温数据集。本数据集有助于进一步客观认识青藏高原温度变化规律,为研究青藏高原气候变化提供数据支撑。
The Tibetan Plateau has experienced a rapid climate rise in recent years,which is a hot issue in the study of global change.However,the meteorological stations are sparsely and unevenly distributed on the Tibetan Plateau,which negatively influences the spatial representativeness of meteorological data on the climate change of the whole plateau.Satellite remote sensing provides a new approach to the large-scale research on the climate change.First,we extracted the monthly daytime land surface temperature,monthly nighttime land surface temperature,monthly clear sky days,monthly surface albedo,monthly NDVI,monthly NDSI,altitude,astronomical radiation radiance and CTI from MODIS remote sensing data,DEM data and CTI datasets.Then,we employed the Cubist algorithm to develop models for estimating monthly average,maximum and minimum air temperature through cross-validation and parameter tuning.Finally,we obtained dataset of MODIS-based monthly air temperature with a spatial resolution of 1 km on the Tibetan Plateau from 2001 to 2020.The dataset is helpful for further understanding the climate change on the Tibetan Plateau,and provides important database for the climate change research on the Tibetan Plateau.
作者
莫亚萍
徐永明
刘勇洪
陈惠娟
祝善友
MO Yaping;XU Yongming;LIU Yonghong;CHEN Huijuan;ZHU Shanyou(School of Geography and Remote Sensing,Nanjing University of Information Science&Technology,Nanjing,210044,P.R.China;CMA Earth System Modeling and Prediction Centre,Beijing 100081,P.R.China)
基金
国家自然科学基金面上项目(41871028)
国家对地观测科学数据中心开放基金(NODAOP2021004)
江苏省研究生科研创新计划项目(KYCX22_1175)。
