NONLINEAR PROCESSES IN GEOPHYSICS
ISSN:1023-5809

NONLINEAR PROCESSES IN GEOPHYSICS

NONLINEAR PROC GEOPH
学科领域:地球科学
是否预警:不在预警名单内
是否OA:
录用周期:较慢,6-12周
新锐分区:地球科学3区
年发文量:39
影响因子:2.4
JCR分区:Q2

基本信息

《地球物理学中的非线性过程》(Nonlinear Processes in Geophysics,NPG)是一本国际性、跨学科、非盈利性期刊,致力于打破地球和空间科学中标准方法经常面临的僵局。因此,它寻求颠覆性和创新性的概念和方法,以及这些概念和方法的原始应用,以解决地球科学系统中普遍存在的复杂性,以及相互作用的社会和生物系统。这种系统是非线性的,其响应与扰动强烈地不成比例,并且在尺度上表现出相关的极端可变性。
1023-5809SCIE/Scopus收录/DOAJ开放期刊
2.4
2.5
2026年3月发布
点击查看历史分区趋势    >
大类学科小类学科Top期刊综述期刊
地球科学3区
GEOSCIENCES, MULTIDISCIPLINARY 地球科学:综合
4区
MATHEMATICS, INTERDISCIPLINARY APPLICATIONS 数学跨学科应用
3区
METEOROLOGY & ATMOSPHERIC SCIENCES 气象与大气科学
3区
PHYSICS, FLUIDS & PLASMAS 物理:流体与等离子体
3区
N/A
WOS期刊SCI分区  2024-2025最新升级版
按JIF指标学科分区收集子录JIF分区JIF排名百分位
学科:GEOSCIENCES, MULTIDISCIPLINARY
SCIE
Q2
118/258
学科:MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
SCIE
Q2
36/136
学科:METEOROLOGY & ATMOSPHERIC SCIENCES
SCIE
Q3
65/111
学科:PHYSICS, FLUIDS & PLASMAS
SCIE
Q2
17/41
按JCR指标学科分区收集子录JCR分区JCR排名百分位
学科:GEOSCIENCES, MULTIDISCIPLINARY
SCIE
Q3
146/258
学科:MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
SCIE
Q3
72/136
学科:METEOROLOGY & ATMOSPHERIC SCIENCES
SCIE
Q3
70/111
学科:PHYSICS, FLUIDS & PLASMAS
SCIE
Q3
25/41
52
39
7%0较慢,6-12周EUR1310地学-地球化学与地球物理
16.7%
时间预警情况
2026年03月发布的新锐学术版不在预警名单中
2025年03月发布的2025版不在预警名单中
2024年02月发布的2024版不在预警名单中
2023年01月发布的2023版不在预警名单中
2021年12月发布的2021版不在预警名单中
2020年12月发布的2020版不在预警名单中
97.44%100%-
CiteScore:3.10
SJR:0.701
SNIP:0.833
学科类别分区排名百分位
大类:Earth and Planetary Sciences
小类:Geophysics
Q2
73 / 177
大类:Earth and Planetary Sciences
小类:Geochemistry and Petrology
Q2
74 / 163
大类:Earth and Planetary Sciences
小类:Statistical and Nonlinear Physics
Q3
32 / 61

期刊高被引文献

Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-143-2019
Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-251-2019
Generalization properties of feed-forward neural networks trained on Lorenz systems
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/npg-26-381-2019
Revising the stochastic iterative ensemble smoother
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-325-2019
Statistical post-processing of ensemble forecasts of the height of new snow
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-339-2019
A prototype stochastic parameterization of regime behaviour in the stably stratified atmospheric boundary layer
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/npg-26-401-2019
Data assimilation using adaptive, non-conservative, moving mesh models
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-175-2019
Statistical hypothesis testing in wavelet analysis: theoretical developments and applications to Indian rainfall
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-91-2019
Inverting Rayleigh surface wave velocities for crustal thickness in eastern Tibet and the western Yangtze craton based on deep learning neural networks
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-61-2019
Numerical bifurcation methods applied to climate models: analysis beyond simulation
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-359-2019
Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-211-2019
Fluctuations of finite-time Lyapunov exponents in an intermediate-complexity atmospheric model: a multivariate and large-deviation perspective
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-195-2019
Competition between chaotic advection and diffusion: stirring and mixing in a 3-D eddy model
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-37-2019
Exploring the sensitivity of Northern Hemisphere atmospheric circulation to different surface temperature forcing using a statistical-dynamical atmospheric model
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-1-2019
Application of fractal models to delineate mineralized zones in the Pulang porphyry copper deposit, Yunnan, southwestern China
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-267-2019
The adaptive particle swarm optimization technique for solving microseismic source location parameters
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-163-2019
Particle clustering and subclustering as a proxy for mixing in geophysical flows
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-307-2019
Mahalanobis distance-based recognition of changes in the dynamics of a seismic process
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-291-2019
A fast approximation for 1-D inversion of transient electromagnetic data by using a back propagation neural network and improved particle swarm optimization
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/npg-26-445-2019
Negentropy anomaly analysis of the borehole strain associated with the M s 8.0 Wenchuan earthquake
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-371-2019
On fluctuating momentum exchange in idealised models of air–sea interaction
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-457-2019
Denoising stacked autoencoders for transient electromagnetic signal denoising
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-13-2019
Characterization of the South Atlantic Anomaly
来源期刊:Nonlinear Processes in GeophysicsDOI:10.5194/NPG-26-25-2019

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