NICAM–LETKF JAXA Research Analysis (NEXRA) Version 2.0

IF 3.3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Geoscience Data Journal Pub Date : 2025-05-20 DOI:10.1002/gdj3.70011

Shuhei Matsugishi, Ying-Wen Chen, Koji Terasaki, Kaya Kanemaru, Shunji Kotsuki, Hisashi Yashiro, Kosuke Yamamoto, Masaki Satoh, Takuji Kubota, Takemasa Miyoshi

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引用次数: 0

Abstract

The NICAM–LETKF JAXA Research Analysis (NEXRA) version 2.0 has been released on the JAXA-NEXRA Analysis website. This dataset is produced using the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and the Local Ensemble Transform Kalman Filter (LETKF)-based atmospheric data assimilation system. The system assimilates in situ atmospheric observations, satellite data, and satellite-derived precipitation data into global atmospheric simulations. NEXRA provides a 128-member ensemble surface output (2D) and an analysis of ensemble mean and spread (3D) covering the period from January 2019 to June 2024. This dataset supports ensemble studies in geoscience research and serves practical applications, including initial conditions for hindcast simulations with atmospheric models, boundary conditions for ocean and land models, and investigations into spatiotemporal variations in atmospheric variability.

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NICAM-LETKF JAXA研究分析（NEXRA） 2.0版

NICAM-LETKF JAXA研究分析（NEXRA） 2.0版已在JAXA-NEXRA分析网站上发布。该数据集是使用非流体静力二十面体大气模式（NICAM）和基于局部集合变换卡尔曼滤波（LETKF）的大气数据同化系统生成的。该系统将现场大气观测、卫星数据和卫星衍生降水数据纳入全球大气模拟。NEXRA提供了一个涵盖2019年1月至2024年6月期间的128个集合表面输出（2D）和集合平均和扩展（3D）分析。该数据集支持地球科学研究中的集合研究，并服务于实际应用，包括使用大气模式进行后降模拟的初始条件，海洋和陆地模式的边界条件，以及对大气变率时空变化的调查。

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来源期刊

Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES

CiteScore

5.90

自引率

9.40%

发文量

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.