five

A high spatial resolution Extended Spring Indices database over American and European regions

收藏
DataCite Commons2024-03-19 更新2024-07-03 收录
下载链接:
https://data.4tu.nl/datasets/aca56a60-8fcc-45b5-b817-50b68d4b5c63/1
下载链接
链接失效反馈
官方服务:
资源简介:
This repository contains a high spatial resolution database of spring onset indicators derived from the Extended Spring Indices (SI-x) phenological models as well as the code used to generate these phenological products. The SI-x models transform daily minimum and maximum temperatures into a set of consistent indices that track the timing of first leaf and first bloom for key indicator species, and that also allow the calculation of the so-called damage index by subtracting the date of first leaf from the date of the last freeze.<br>This dataset is available at 1 km spatial resolution and covers American (1980 to 2022) and European regions (1950 to 2020).The first leaf and first bloom indices are validated with ground phenological observations collected over both regions.The American product is based on DAYMET version 4 (https://daymet.ornl.gov/) and the European region on a downscaled E-Obs database version 3 (ftp://palantir.boku.ac.at/Public/ClimateData).<br>This product can support both scientists and decision makers in their quest to hind- and forecast climate change impacts in these areasIn the USA this product is recognized as an official climate change indicator (https://www.globalchange.gov/indicators/start-of-spring)<br>An interactive visualization of this database is available here: https://emma.users.earthengine.app/view/spring-onset<br>For more information see our publications:A Matlab© toolbox for calculating spring indices from daily meteorological data (https://doi.org/10.1016/j.cageo.2015.06.015 )Development and analysis of spring plant phenology products: 36 years of 1-km grids over the conterminous US (https://doi.org/10.1016/j.agrformet.2018.06.028)A long-term 1 km gridded database of continental-scale spring onset products (under review)
提供机构:
4TU.ResearchData
创建时间:
2024-03-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作