利用动态降尺度技术建立印度高分辨率气候预测数据集

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Anasuya Barik, Sanjeeb Kumar Sahoo, Sarita Kumari, Somnath Baidya Roy
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引用次数: 0

摘要

高分辨率气候预测是了解气候变化的区域影响和制定适当的适应/减缓战略的宝贵资源。在这项研究中,我们利用最先进的天气研究与预报(WRF)模型,对 RCP8.5 情景下经过偏差校正的社区地球系统模型(CESMv1)气候预测进行动态降尺度处理,开发了印度上空 10 公里网格水文气象数据集。降尺度 CESM 数据集(DSCESM)以三种时间分辨率(日、月和月气候学)存档于世界气候数据中心(WDCC)门户网站,分别为当前(2006-2015 年)、本世纪中期(2041-2050 年)和本世纪末(2091-2100 年)。数据集包括 2 米气温、累计降水总量、风速、相对湿度、显热通量和潜热通量,以及地表短波辐射和外向长波辐射。所有 DSCESM 变量都根据 2006-2015 年期间的再分析数据和站点观测数据进行了评估。该数据集有助于我们定量了解印度的区域气候变化。它还可与农业、水文、火灾和其他应用模型结合使用,用于评估气候变化对各部门的影响,帮助制定有效的适应/缓解战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

High-resolution climate projection dataset over India using dynamical downscaling

High-resolution climate projection dataset over India using dynamical downscaling

High-resolution climate projections are valuable resources for understanding the regional impacts of climate change and developing appropriate adaptation/mitigation strategies. In this study, we developed a 10-km gridded hydrometeorological dataset over India by dynamic downscaling of the bias-corrected Community Earth System Model (CESMv1) climate projections under RCP8.5 scenario using the state-of-the-art Weather Research and Forecasting (WRF) model. The downscaled CESM dataset (DSCESM) is archived in the World Data Center for Climate (WDCC) portal at three temporal resolutions (daily, monthly and monthly climatology) for current (2006–2015), mid-century (2041–2050) and end-century (2091–2100) periods. The dataset includes 2-m air temperature, total accumulated precipitation, wind speed, relative humidity, sensible and latent heat fluxes, along with surface shortwave and outgoing longwave radiation. All the DSCESM variables were evaluated against reanalysis data and station observations for the period 2006–2015. This dataset can help us quantitatively understand regional climate change in India. It can also be used in conjunction with agricultural, hydrological, fire and other application models for climate change impact assessment on various sectors to help develop effective adaptation/mitigation strategies.

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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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