官方服务：
资源简介：
WBNM models for existing and climate change scenarios
应用场景：
相关数据集
Climate change and tourism
data for a research on the effect of climate change and economic variables on international and domestic tourism
Figshare2022-01-06 更新50
Dataset underlying chapter 6 of dissertation F. van Oorschot
This dataset is used in chapter 6 of the PhD dissertation of F. van Oorschot (May 2024). The data is used to provide an analysis of global root zone storage capacity representation with: (1) predicted
Zenodo2024-05-21 更新10
Code for "Extreme temperatures, mortality, and adaptation: Evidence from the county level in China"
Extreme temperatures are known to cause adverse health outcomes. Yet knowledge on the magnitude of this effect in developing countries is limited due to data availability and reliability issues. Colle
Harvard Dataverse2024-01-27 更新00
1998-2017年中国印度河流域上游5公里水资源时空分布数据集
本数据是基于气象观测数据、水文站点数据，结合各种同化数据和遥感数据，通过耦合积雪、冰川和冻土物理过程的青藏高原多圈层水文模型系统WEB-DHM（基于水和能量平衡的分布式水文模型）制备生成，时间分辨率为月尺度，空间分辨率为5km，原始数据格式为ASCII文本格式，数据种类包括格网径流与蒸发（若蒸发小于0, 则表示凝华；若径流小于0，则表示当月降水小于蒸发）。若asc无法在arcmap中正常打开，请将
地球大数据科学工程2018-10-25 更新20
CLIMATE APPLICATIONS: The global mean level of the oceans is one of the most important indicators of climate change. It incorporates the reactions from several different components of the climate system. Precise monitoring of changes in the mean level of the oceans, particularly through the use of altimetry satellites, is vitally important, for understanding not just the climate but also the socioeconomic consequences of any rise in sea level.
CLIMATE APPLICATIONS: The global mean level of the oceans is one of the most important indicators of climate change. It incorporates the reactions from several different components of the climate syst
ESA Earth Online00
