Space Weather: Physics,Effects and Predictability

The time varying conditions in the near-Earth space environment that may affect space-borne or ground-based technological systems and may endanger human health or life are referred to as space weather. Space weather effects arise from the dynamic and highly variable conditions in the geospace environment starting from explosive events on the Sun (solar flares), Coronal Mass Ejections near the Sun in the interplanetary medium, and various energetic effects in the magnetosphere–ionosphere–atmosphere system. As the utilization of space has become part of our everyday lives, and as our lives have become increasingly dependent on technological systems vulnerable to the space weather influences, the understanding and prediction of hazards posed by these active solar events have grown in importance. In this paper, we review the processes of the Sun–Earth interactions, the dynamic conditions within the magnetosphere, and the predictability of space weather effects on radio waves, satellites and ground-based technological systems today.     

Classification of space-weather complexes based on solar source type,characteristics of plasma flow,and geomagnetic perturbation induced by it

The space-weather complexes including characteristics of solar streams (parameters of the solar wind, components of the interplanetary magnetic-field vector) and temporal quantitative estimates of their geomagnetic effects (Dst index) are classified. Comparative and neural-network methods for this classification are developed. As a result of numerical neural-network experiments, types of solar streams responsible for generation of geomagnetic perturbations with different intensities are established. It is confirmed that, on the basis of the selected space weather complexes, it is possible to refine the influence of these streams on the electromagnetic state of the magnetic sphere and, hence, improve the accuracy of predictions of this state.     

Ionospheric space weather effects monitored by simultaneous ground and space based GNSS signals

Ionospheric space weather effects can degrade the performance of global navigation satellite systems (GNSS), i.e. their accuracy, reliability and availability. However, well established ground based and innovative space based GNSS measurements offer the unique chance for a permanent monitoring of the electron density structure of the global ionosphere–plasmasphere system. In this paper we review various types of perturbations in the ionospheric plasma density and distribution. In order to analyze these space weather effects we use 30 s sampled measurements provided by the global GPS ground tracking network of the IGS. Furthermore, to get a more comprehensive view on the perturbations analyzed also are simultaneously obtained GPS measurements onboard the LEO satellite CHAMP (challenging minisatellite payload). Whereas the ground based measurements show strong horizontal redistribution of plasma during ionospheric storms, the space-borne measurements indicate a severe vertical redistribution of the ionospheric plasma during the selected events. The role of the various dynamical forces such as meridional winds and electric fields is also discussed.     

Review of Chinese atmospheric science research over the past 70 years: Synoptic meteorology

Synoptic meteorology is a branch of meteorology that uses synoptic weather observations and charts for the diagnosis,study,and forecasting of weather.Weather refers to the specific state of the atmosphere near the Earth's surface during a short period of time.The spatial distribution of meteorological elements in the atmosphere can be represented by a variety of transient weather phenomena,which are caused by weather systems of different spatial and temporal scales.Weather is closely related to people's life,and its development and evolution have always been the focus of atmospheric scientific research and operation.The development of synoptic meteorology is closely related to the development of observation systems,dynamical theories and numerical models.In China,observation networks have been built since the early 1950 s.Up to now,a comprehensive meteorological observation systembased on ground,air and space has been established.In particular,the development of a new generation of dense radar networks,the development of the Fengyun satellite series and the implementation of a series of large field experiments have brought our understanding of weather from large-scale environment to thermal dynamics,cloud microphysical structure and evolution characteristics of meso and micro-scale weather systems.The development of observation has also promoted the development of theory,numerical model and simulation.In the early days,China mainly used foreign numerical models.Lately,China has developed numerical model systems with independent intellectual property rights.Based on the results of high-resolution numerical simulations,in-depth understanding of the initiation and evolution mechanism and predictability of weather at different scales has been obtained.Synoptic meteorology has gradually changed from an initially independent development to a multidisciplinary approach,and the interaction between weather and the change of climate and environment has become a hot and frontier topic in atmospheric science.This paper reviews the important scientific and technological achievements made in China over the past 70 years in the fields of synoptic meteorology based on the literatures in China and abroad,from six aspects respectively including atmospheric dynamics,synoptic-scale weather,typhoon and tropical weather,severe convective weather,numerical weather prediction and data assimilation,weather and climate,atmospheric physics and atmospheric environment.     

Influence of the Planetary Boundary Layer Physics on Medium-range Prediction of Monsoon over India

—The present study emphasizes the importance of proper representation of boundary layer physics in a general circulation model. The Turbulent Kinetic Energy (TKE) closure scheme incorpo rates important processes of the Planetary Boundary Layer (PBL) compared to a simplistic first-order closure model. Hence the model which has the TKE closure scheme is capable of simulating important weather systems associated with summer monsoon, such as monsoon depressions and lows that form over the Indian subcontinent quite well compared to the first-order closure model. The present study indicates better performance of the global model with the TKE scheme in the prediction of the monsoon circulation, including the tracks of the depressions over the Indian subcontinent. Medium-range weather prediction has also improved with the use of the TKE closure. However further studies are necessary to improve the forecast, with emphasis on boundary layer processes.     

Review of Understanding of Earth’s Hydrological Cycle: Observations,Theory and Modelling

Water is our most precious and arguably most undervalued natural resource. It is essential for life on our planet, for food production and economic development. Moreover, water plays a fundamental role in shaping weather and climate. However, with the growing global population, the planet’s water resources are constantly under threat from overuse and pollution. In addition, the effects of a changing climate are thought to be leading to an increased frequency of extreme weather causing floods, landslides and drought. The need to understand and monitor our environment and its resources, including advancing our knowledge of the hydrological cycle, has never been more important and apparent. The best approach to do so on a global scale is from space. This paper provides an overview of the major components of the hydrological cycle, the status of their observations from space and related data products and models for hydrological variable retrievals. It also lists the current and planned satellite missions contributing to advancing our understanding of the hydrological cycle on a global scale. Further details of the hydrological cycle are substantiated in several of the other papers in this Special Issue.     

Conditional nonlinear optimal perturbation: Applications to stability,sensitivity, and predictability

Conditional nonlinear optimal perturbation (CNOP) is a nonlinear generalization of linear singular vector (LSV) and features the largest nonlinear evolution at prediction time for the initial perturbations in a given constraint. It was proposed initially for predicting the limitation of predictability of weather or climate. Then CNOP has been applied to the studies of the problems related to predictability for weather and climate. In this paper, we focus on reviewing the recent advances of CNOP’s applications, which involves the ones of CNOP in problems of ENSO amplitude asymmetry, block onset, and the sensitivity analysis of ecosystem and ocean’s circulations, etc. Especially, CNOP has been primarily used to construct the initial perturbation fields of ensemble forecasting, and to determine the sensitive area of target observation for precipitations. These works extend CNOP’s applications to investigating the nonlinear dynamical behaviors of atmospheric or oceanic systems, even a coupled system, and studying the problem of the transition between the equilibrium states. These contributions not only attack the particular physical problems, but also show the superiority of CNOP to LSV in revealing the effect of nonlinear physical processes. Consequently, CNOP represents the optimal precursors for a weather or climate event; in predictability studies, CNOP stands for the initial error that has the largest negative effect on prediction; and in sensitivity analysis, CNOP is the most unstable (sensitive) mode. In multi-equilibrium state regime, CNOP is the initial perturbation that induces the transition between equilibriums most probably. Furthermore, CNOP has been used to construct ensemble perturbation fields in ensemble forecast studies and to identify sensitive area of target observation. CNOP theory has become more and more substantial. It is expected that CNOP also serves to improve the predictability of the realistic predictions for weather and climate events plays an increasingly important role in exploring the nonlinear dynamics of atmospheric, oceanic and coupled atmosphere-ocean system. Supported by National Basic Research Program of China (Grant Nos. 2006CB403606, 2007CB411800), National Natural Science Foundation of China (Grant Nos. 40830955, 40675030, 40505013), Institute of Atmospheric Physics, Chinese Academy of Sciences (Grant No. IAP07202), and LASG State Key Laboratory Special Fund     

Space Weather Forecasting at IZMIRAN

Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar–terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center’s forecasts.     

Geospace imaging using Thomson scattering

We evaluate the potential of imaging for the first time, the near-earth space plasma environment seamlessly from the ionosphere through the magnetosphere by remotely sensing Thomson scattering of solar visible light by geospace electrons. Using state of the art first principles models of the magnetosphere/ionosphere system, we show that the column emission rates are weak, generally less than 10 Rayleighs, but detectable with currently available instrument technology recently deployed for heliospheric imaging. We demonstrate that distinct features such as the bow shock, magnetosheath and magnetopause are detectable in synthetic images simulated using modified solar coronagraphs and white light imagers, providing that the large background signals are properly quantified. The availability of global geospace images of the electron concentration will enable major advances in our understanding of how Earth's near-space environment responds as a coupled system to changing solar forcings. Such images are expected to play a central role in space weather assessment and forecasting, from which significant capabilities will accrue, much as the imaging of the Earth's surface and lower atmosphere has advanced understanding and forecasting of tropospheric weather.     

国际地磁台网计划INTERMAGNET

本文介绍了国际地磁台网计划（INTERMAGNET）的目的、意义、提出、发展过程及未来趋势，强调指出它对地磁台站现代化建设，地磁学研究，地球物理学发展以及空间天气预报的影响及作用．地磁场和空间环境的全球性质越来越迫切地要求各国学术团体和组织进行大规模国际合作，而作为地学研究的基础—台站建设与观测，资料收集与交换，资源共享与扩展—更应成为地球科学家关心的重要问题与焦点。     

Effects of climate change on thermal properties of lakes and reservoirs, and possible implications

Meteorologic-driven processes exert large and diverse impacts on lakes’ internal heating, cooling, and mixing. Thus, continued global warming and climate change will affect lakes’ thermal properties, dynamics, and ecosystem. The impact of climate change on Lake Tahoe (in the states of California and Nevada in the United States) is investigated here, as a case study of climate change effects on the physical processes occurring within a lake. In the Tahoe basin, air temperature data show upward trends and streamflow trends indicate earlier snowmelt. Precipitation in the basin is shifting from snow to rain, and the frequency of intense rainfall events is increasing. In-lake water temperature records of the past 38 years (1970–2007) show that Lake Tahoe is warming at an average rate of 0.013°C/year. The future trends of weather variables, such as air temperature, precipitation, longwave radiation, downward shortwave radiation, and wind speed are estimated from predictions of three General Circulation Models (GCMs) for the period 2001–2100. Future trends of weather variables of each GCM are found to be different to those of the other GCMs. A series of simulation years into the future (2000–2040) is established using streamflows and associated loadings, and meteorologic data sets for the period 1994–2004. Future simulation years and trends of weather variables are selected so that: (1) future simulated warming trend would be consistent with the observed warming trend (0.013°C/year); and (2) future mixing pattern frequency would closely match with the historical mixing pattern frequency. Results of 40-year simulations show that the lake continues to become warmer and more stable, and mixing is reduced. Continued warming in the Tahoe has important implications for efforts towards managing biodiversity and maintaining clarity of the lake.     

Research on global change scientific satellites

Global change now poses a severe threat to the survival and development of mankind.Large-scale,real-time,highly accurate Earth observation from space has become a key technology used to observe global change.China is one of the most influential countries affecting and being affected by global change,yet it has no scientific satellite for global change research so far.Developing global change scientific satellites not only would meet an important demand of China,but also would be a valuable contribution to the world.By analyzing the mechanisms of space-based observation of variables sensitive to global change,this paper explores the concept of global change scientific satellites,and proposes a series of global change scientific satellites to establish a scientific observation system for global environmental change monitoring from space.     

Improving global rainfall forecasting with a weather type approach in Japan

An automated version of the weather type classification scheme was performed over Japan to characterize daily circulation conditions. A daily gridded field of mean sea-level pressure (MSLP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis dataset (ERA-interim) and the THORPEX Interactive Grand Global Ensemble (TIGGE) daily forecast dataset were used. The weather type is advantageous as it provides an opportunity to improve global rainfall prediction by refining statistical bias correction. We distinguished 11 weather types: anticyclone, cyclone, hybrid and eight purely wind directions. The results indicate that the main weather types contributing to the total volume of rainfall are cyclone, hybrid, purely westerly and northwest winds. A gamma-based bias correction decreases the global rainfall forecast root mean square by 10%, while specific weather type gamma bias correction accounts for 5–10% root mean square error reduction, with a total decrease of errors up to a maximum of 20%. Both global and weather type bias corrections improve the extreme dependency scores (EDS), but for different extreme rainfall thresholds. The study advocates the use of weather type bias-correction methods for extreme event rainfall intensity corrections higher than 100 mm/d.

EDITOR

A. Castellarin

ASSOCIATE EDITOR

A. Jain     

Standard normal homogeneity test as a tool to detect change points in climate-related river discharge variation: case study of the Kupa River Basin

ABSTRACT

The study addresses homogeneity testing of annual discharge time series for eight hydrological stations and five annual climate time series for one weather station in the Kupa River Basin, between Slovenia and Croatia, and global annual average surface temperature time series for the period 1961–2010. The standard normal homogeneity test (SNHT) was used to detect both abrupt and gradual linear trend homogeneity breaks. The results reveal natural change points at the beginning of the 1980s. Absolute homogeneity testing of average annual weather station-level air pressure, annual precipitation, differences between precipitation totals and potential evapotranspiration and surface runoff from the independent observation time series confirmed an abrupt shift, also at the beginning of the 1980s. The trend of local air temperature for 1985–2000, which partly coincides with global surface temperature trend for 1974–2005, strengthened the river discharge regime shift since the beginning of the 1980s. These results could improve climate variation monitoring and estimation of the impact of climate variation on the environment in the area. Generally, an indication of climate regime change points and an assessment of their duration could provide significant benefits for the society.     

Seasonal changes in diurnal variation of potential gradient at Fargo,North Dakota

Summary The atmospheric electric potential gradient was recorded continuously by a field mill at Fargo, North Dakota, for the period August, 1972–March, 1973. Hourly averages were taken by the equal areas technique to eliminate short period variations. The diurnal variation of monthly averages is shown for the fair weather periods and all weather. In addition, the diurnal variation is shown for all positive values of the potential gradient, which excludes periods of major local space charge generators, but includes periods when the potential gradient might be influenced by regional conditions not otherwise present during fair weather. For a given month the diurnal variation curves are generally similar, with the fair weather curve giving the highest values, and all weather curve giving the lowest values. The months September–November have similar curves with the lowest values and least deviation from the average. The months December–February have similar curves with the highest values.Harmonic analysis is used to compute the times of maxima and contributions to variance of the first four harmonics for each diurnal variation curve. The fair weather first harmonic accounts for the majority of variance and has a maximum near 19.5 h GMT. It is attributed to the global diurnal variation of potential gradient due to thunderstorm activity in the tropics. The second harmonic has one maximum occurring from 9–12 h local time and is attributed to the austausch effect of convection, where ions affect the conductivity of the air locally.The differences in these monthly diurnal variation curves emphasize that the season of year, weather conditions, and length of time over which data is averaged must be specified in atmospheric electricity studies if meaningful conclusions are to be drawn.     

泰安地震台重力扰动现象研究

利用滤波分析法对山东泰安地震台重力固体潮观测的分析表明,重力观测中存在大量高频扰动信号.通过与气象观测实况资料的对比发现,这些异常扰动信号除了受台风等热带气旋影响外,还明显与“冷空气”过境等区域强对流天气有关. 对泰安台JCZ-1甚宽频带地震仪观测资料的频谱分析和滤波处理进一步表明,区域强对流天气及台风对重力仪的影响频段均在1—8 s范围内,其中2—6 s区间影响最为显著; 强对流天气过程触发的扰动信号范围可以在1—16 s,但8 s后扰动信号对重力仪观测基本不造成影响,即重力仪对高频扰动信号的响应存在8 s的截止周期.JCZ-1甚宽频带地震仪的波谱分析还反映出扰动信号的动态特征,即强对流天气产生的扰动信号在发展、传播过程中,首先出现的信号频率较高,随着时间推移信号逐渐向低频演化,揭示了干扰信号传播的多普勒效应以及扰动信号激发源的移动特性.      

Estimation of global lightning activity and observations of atmospheric electric field

Variations in the global atmospheric electric circuit are investigated using a wide range of globally spaced instruments observing VLF (∼10 kHz) waves, ELF (∼300 Hz) waves, Schumann resonances (4–60 Hz), and the atmospheric fair weather electric field. For the ELF/VLF observations, propagation effects are accounted for in a novel approach using established monthly averages of lightning location provided by the Lightning Image Sensor (LIS) and applying known frequency specific attenuation parameters for daytime/nighttime ELF/VLF propagation. Schumann resonances are analyzed using decomposition into propagating and standing waves in the Earth-ionosphere waveguide. Derived lightning activity is compared to existing global lightning detection networks and fair weather field observations. The results suggest that characteristics of lightning discharges vary by region and may have diverse effects upon the ionospheric potential.     

地磁感应电流研究综述

因太阳活动而引起的地磁扰动,会在地球表面感生出地电场,从而在地表附近的导体系统中产生地磁感应电流(GICs).太阳表面的异常活动而引起的磁暴会导致强烈的GICs,严重威胁电信设备、电网、油气管道和铁路运输网络等基础设施系统的安全运行,已经成为最严重的空间天气灾害之一.因此,对GICs进行深入研究以建立对其做出迅速预测的能力,在科学和应用方面都有重要意义.本文综述了GICs的研究进展,从引入空间天气的概念开始,将GICs作为从太阳活动到太阳风再到地球扰动的空间天气链的最终环节;重点阐述了GICs的计算中所涉及的三个步骤:地球表面地磁场重建、感应地电场的计算,以及地面导体系统中GICs计算;对每一步骤中主要方法的相关原理和应用做了简要介绍与评估;最后总结了当前GICs的研究现状,并对未来GICs的研究方向与挑战进行了展望.     

Generalised formulation of composite filters and their application to earthquake engineering test systems

This paper addresses the problem of generating unmeasured kinetic data—and/or providing improvements in existing data—for the enhancement of performance characteristics of earthquake engineering test systems, such as shaking tables, reaction walls and other custom‐made test rigs. The approach relies upon the use of composite filters (CF), a method of data fusion that was originally conceived via transfer function formulation. The current work generalises the CF concept and extends its formulation into the state‐space domain, thereby providing a wider basis for application to test systems and their controllers, including those of a multivariable (coupled, multi‐axis) nature. Comparative simulation studies of shaking table control are presented that demonstrate the design techniques for state‐space CF and also their effectiveness for signal synthesis, noise suppression and performance improvement. Specific examples include the use of CF for displacement demand signal generation, velocity feedback generation and acceleration control. In each case, the essential principles behind CF—output signals with zero bias and zero drift—are consistently upheld. Copyright © 2017 John Wiley & Sons, Ltd.     

Enhancements to,and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS)

The National Oceanic and Atmospheric Administration's National Environmental Satellite Data and Information Service (NOAA/NESDIS) Interactive Multisensor Snow and Ice Mapping System (IMS) has undergone substantial changes since its inception in 1997. These changes include the data sources used to generate the product, methodology of product creation, and even changes in the output. Among the most notable of the past upgrades to the IMS are a 4‐km resolution grid output, ingest of an automated snow detection algorithm, expansion to a global extent, and a static Digital Elevation Model for mapping based on elevation. Further developments to this dynamic system will continue as NOAA strives to improve snow parameterization for weather forecast modeling. Several future short‐term enhancements will be evaluated for possible transition to operations before the Northern Hemisphere winter of 2006–2007. Current and historical data will be adopted to a geographic information systems (GIS) format before 2007, as well. Longer‐term enhancements are also planned to account for new snow data sources, mapping methodologies and user requirements. These modifications are being made with care to preserve the integrity of the long‐standing satellite‐derived snow record that is vital to global change detection. Published in 2007 by John Wiley & Sons, Ltd.