Seasonal Water Resources Management for Semiarid Areas: Bias-corrected and spatially disaggregated seasonal forecasts for the Karun Basin (Iran)

Project: Seasonal Water Resources Management for Semiarid Areas: Regionalized Global Data and Transfer to Practise - GRoW-SaWaM (BMBF): The SaWaM-Project, which is funded by the German Federal Ministry of Education and Research (BMBF) within the "Water as a global Resource (GRoW)“ initiative, aims at the development of methods and products for improving the water management in semi-arid regions. The methodological core of the project is a model chain, where global hydrometeorological information is first adapted towards five different study regions in Brazil (Rio São Francisco Basin), Iran (Karun Basin), Sudan and Ethiopia (Tekeze-Atbara and Blue Nile Basins), Ecuador and Peru (Catamayo-Chira Basin) and West-Africa (Niger and Volta Basins). Special focus is put on the application of seasonal hydrometeorological forecasts, which give information about the precipitation or temperature to be expected during the coming months. The regionalized information is then used as driving data for hydrological and ecosystem models, which allow for the description of water-management-related parameters and aspects both in the past, but also for the coming months. Further information can be found at http://grow-sawam.org/. Summary: This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D01 (Karun Basin, Iran). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

项目名称：半干旱地区季节性水资源管理：区域化全球数据与实践转化——GRoW-SaWaM（BMBF资助）。本项目由德国联邦教育与研究部（Bundesministerium für Bildung und Forschung, BMBF）在“水资源作为全球资源（Water as a global Resource, GRoW）”倡议框架下资助，旨在开发提升半干旱地区水资源管理水平的方法与产品。本项目的方法核心为一条模型链：首先将全球水文气象信息适配至五个不同研究区域，分别为巴西的圣弗朗西斯科河盆地（Rio São Francisco Basin）、伊朗的卡伦河盆地（Karun Basin）、苏丹与埃塞俄比亚的特克泽-阿特巴拉河及青尼罗河流域（Tekeze-Atbara and Blue Nile Basins）、厄瓜多尔与秘鲁的卡塔马约-奇拉河盆地（Catamayo-Chira Basin）以及西非的尼日尔与沃尔特河流域（Niger and Volta Basins）。项目特别聚焦于季节性水文气象预报的应用，此类预报可提供未来数月的降水或气温预测信息。经区域化处理的信息将作为驱动数据输入水文与生态系统模型，以此实现对过去及未来数月内与水资源管理相关的参数与场景的模拟分析。更多信息可访问 http://grow-sawam.org/。

数据集摘要：本数据集组包含针对SaWaM研究区域D01（伊朗卡伦河盆地）的区域化季节性预报数据。该数据集基于欧洲中期天气预报中心（European Centre for Medium Range Weather Forecast, ECMWF）最新发布的SEAS5季节性预报产品，并针对ECMWF的ERA5气候再分析数据中陆面部分的高分辨率再分析产品ERA5-Land进行了偏差校正与空间降尺度（Bias-Corrected and Spatially Disaggregated, BCSD）处理。因此，本数据集提供了一套时空一致的陆面变量集，可用于驱动水文模型，或评估季节性预报的区域预报技巧。当前，本数据集组包含1981年至2019年期间的逐日与逐月集合（再）预报数据。具体而言，2017年之前的预报包含25个集合成员，2017年及之后的预报包含51个集合成员，所有预报均从起报日起，提供未来215天的逐日与逐月降水、最高气温、最低气温、平均气温以及辐射量预报。