Geoscientific Model Development

Geoscientific Model Development

地球科学模型开发

  • 3区 中科院分区
  • Q1 JCR分区

期刊简介

《Geoscientific Model Development》是由Copernicus Gesellschaft mbH出版社于2008年创办的英文国际期刊(ISSN: 1991-959X,E-ISSN: 1991-9603),该期刊长期致力于地球科学:综合领域的创新研究,主要研究方向为GEOSCIENCES, MULTIDISCIPLINARY。作为SCIE收录期刊(JCR分区 Q1,中科院 3区),本刊采用OA开放获取模式(OA占比1%),以发表地球科学:综合领域等方向的原创性研究为核心(研究类文章占比98.52%%)。凭借严格的同行评审与高效编辑流程,期刊年载文量精选控制在338篇,确保学术质量与前沿性。成果覆盖Web of Science、Scopus等国际权威数据库,为学者提供推动地球科学领域高水平交流平台。

投稿咨询

投稿提示

Geoscientific Model Development审稿周期约为 较慢,6-12周 。该刊近年未被列入国际预警名单,年发文量约338篇,录用竞争适中,主题需确保紧密契合地球科学前沿。投稿策略提示:避开学术会议旺季投稿以缩短周期,语言建议专业润色提升可读性。

  • 地球科学 大类学科
  • English 出版语言
  • 是否预警
  • SCIE 期刊收录
  • 338 发文量

中科院分区

中科院 SCI 期刊分区 2023年12月升级版

Top期刊 综述期刊 大类学科 小类学科
地球科学
3区
GEOSCIENCES, MULTIDISCIPLINARY 地球科学:综合
3区

中科院 SCI 期刊分区 2022年12月升级版

Top期刊 综述期刊 大类学科 小类学科
地球科学
2区
GEOSCIENCES, MULTIDISCIPLINARY 地球科学:综合
2区

JCR分区

按JIF指标学科分区 收录子集 分区 排名 百分位
学科:GEOSCIENCES, MULTIDISCIPLINARY SCIE Q1 41 / 253

84%

按JCI指标学科分区 收录子集 分区 排名 百分位
学科:GEOSCIENCES, MULTIDISCIPLINARY SCIE Q1 33 / 253

87.15%

CiteScore

CiteScore SJR SNIP CiteScore 排名
CiteScore:8.6 SJR:2.055 SNIP:1.319
学科类别 分区 排名 百分位
大类:Mathematics 小类:Modeling and Simulation Q1 22 / 324

93%

大类:Mathematics 小类:General Earth and Planetary Sciences Q1 15 / 195

92%

期刊发文

  • Forecasting tropical cyclone tracks in the northwestern Pacific based on a deep-learning model

    Author: Wang, Liang; Wan, Bingcheng; Zhou, Shaohui; Sun, Haofei; Gao, Zhiqiu

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 8, pp. 2167-2179. DOI: 10.5194/gmd-16-2167-2023

  • Climate impacts of parameterizing subgrid variation and partitioning of landsurface heat fluxes to the atmosphere with the NCAR CESM1.2

    Author: Yin, Ming; Han, Yilun; Wang, Yong; Sun, Wenqi; Deng, Jianbo; Wei, Daoming; Kong, Ying; Wang, Bin

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 1, pp. 135-156. DOI: 10.5194/gmd-16-135-2023

  • A nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wavesimulation

    Author: Huang, Hao; Song, Pengyang; Qiu, Shi; Guo, Jiaqi; Chen, Xueen

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 1, pp. 109-133. DOI: 10.5194/gmd-16-109-2023

  • WRF-ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer

    Author: Zhong, Xiaohui; Ma, Zhijian; Yao, Yichen; Xu, Lifei; Wu, Yuan; Wang, Zhibin

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 1, pp. 199-209. DOI: 10.5194/gmd-16-199-2023

  • Ocean Modeling with Adaptive REsolution (OMARE; version 1.0) - refactoring the NEMO model (version 4.0.1) with the parallel computing framework of JASMIN - Part 1: Adaptive grid refinement in an idealized double-gyre case

    Author: Zhang, Yan; Wang, Xuantong; Sun, Yuhao; Ning, Chenhui; Xu, Shiming; An, Hengbin; Tang, Dehong; Guo, Hong; Yang, Hao; Pu, Ye; Jiang, Bo; Wang, Bin

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 2, pp. 679-704. DOI: 10.5194/gmd-16-679-2023

  • Monthly-scale extended predictions using the atmospheric model coupled with a slab ocean

    Author: Wang, Zhenming; Zhang, Shaoqing; Jin, Yishuai; Jia, Yinglai; Yu, Yangyang; Gao, Yang; Yu, Xiaolin; Li, Mingkui; Lin, Xiaopei; Wu, Lixin

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 2, pp. 705-717. DOI: 10.5194/gmd-16-705-2023

  • SHAFTS (v2022.3): a deep-learning-based Python package for simultaneous extraction of building height and footprint from sentinel imagery

    Author: Li, Ruidong; Sun, Ting; Tian, Fuqiang; Ni, Guang-Heng

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 2, pp. 751-778. DOI: 10.5194/gmd-16-751-2023

  • AttentionFire_v1.0: interpretable machine learning fire model for burned-area predictions over tropics

    Author: Li, Fa; Zhu, Qing; Riley, William J.; Zhao, Lei; Xu, Li; Yuan, Kunxiaojia; Chen, Min; Wu, Huayi; Gui, Zhipeng; Gong, Jianya; Randerson, James T.

    Journal: GEOSCIENTIFIC MODEL DEVELOPMENT. 2023; Vol. 16, Issue 3, pp. 869-884. DOI: 10.5194/gmd-16-869-2023