Angular Distributions of Discrete Mesoscale Mapping Functions

The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.     

Results of the application of tropospheric corrections from different troposphere models for precise GPS rapid static positioning

In many surveying applications, determination of accurate heights is of significant interest. The delay caused by the neutral atmosphere is one of the main factors limiting the accuracy of GPS positioning and affecting mainly the height coordinate component rather than horizontal ones. Estimation of the zenith total delay is a commonly used technique for accounting for the tropospheric delay in static positioning. However, in the rapid static positioning mode the estimation of the zenith total delay may fail, since for its reliable estimation longer observing sessions are required. In this paper, several troposphere modeling techniques were applied and tested with three processing scenarios: a single baseline solution with various height differences and a multi-baseline solution. In specific, we introduced external zenith total delays obtained from Modified Hopfield troposphere model with standard atmosphere parameters, UNB3m model, COAMPS numerical weather prediction model and zenith total delays interpolated from a reference network solution. The best results were obtained when tropospheric delays derived from the reference network were applied.     

Ionospheric research and space weather services

This paper concentrates on those major areas where our current physical understanding and recent advances can lead to positive predictions of the expected effects of ionospheric activity on the near-Earth space environment and on technological systems which operate within this environment. It briefly describes some of the key links between solar activity and the various physical processes, which govern ionospheric plasma structure that has been under scientific examination over past several decades but has lately received significant importance in relation to the space weather services. Specific examples during extremely intense solar event show how ionospheric monitoring techniques that have contributed immense data sets and related empirical and theoretical formulations have been incorporated in different ionospheric specification and prediction models for real-time operational applications. Finally, the general question of what might be expected as a result of current activities within different European cooperative projects is addressed.     

The PFISR IPY observations of ionospheric climate and weather

The recently commissioned Poker Flat Incoherent Scatter Radar (PFISR) began a continuous operation measurement program for the duration of the International Polar Year (IPY). The IPY began on 1 March 2007 and is an 18-month period of intense polar study. PFISR began its IPY campaign on 1 March 2007 and this paper describes the first 10 months of observations. The PFISR IPY science goals revolve around distinguishing between ionospheric climate and weather variability, and to determine the relative role of geomagnetic weather from the magnetosphere versus that driven from the atmosphere below. This latter goal may well be aided by the fact that the IPY period is at solar minimum, a time when major geomagnetic activity occurrence should be minimized. However, as nature would have it once the IPY observations began it was found that geomagnetic activity was a recurrent feature lasting the entire 10 months being discussed here. The PFISR IPY database will also be used as a long-term fiducial data set against which ionospheric models are to be compared. Hence, this paper provides a documentation of the contents of the database. Case studies as well as statistical studies of how the ionospheric climate and weather can be separated are presented. A particular emphasis is placed upon the F-region ion temperature observations. These appear to provide a very direct measure of geomagnetic energy input to the ionosphere–thermosphere system. Examples are shown in which 150 K F-region ion temperature increases are associated with very moderate geomagnetic disturbances in which the daily average 3-h Kp is only 2.5.     

The weather forecast

Recent advances in the use of dynamical and statistical models to forecast the weather are described. High resolution physical-mathematical models can now predict the development of synoptic weather systems in great detail for a few days ahead, while large-scale phenomena like blocking can be predicted for about a week or more.The local forecasting problem is presently being attacked by statistical- and meso-scale models using the large-scale predictions as input parameters. Very encouraging results have been obtained to predict the local weather, in particular when the local weather is influenced by topography and the underlying surface.     

4D tropospheric tomography using GPS slant wet delays

Tomographic techniques are successfully applied to obtain 4D images of the tropospheric refractivity in a local dense network of global positioning system (GPS) receivers. We show here how GPS data are processed to obtain the tropospheric slant wet delays and discuss the validity of the processing. These slant wet delays are the observables in the tomographic processing. We then discuss the inverse problem in 4D tropospheric tomography making extensive use of simulations to test the system and define the resolution and the impact of noise. Finally, we use data from the Kilauea network in Hawaii for February 1, 1997, and a local 4 × 4 × 40 voxel grid on a region of 400 km² and 15 km in height to produce the corresponding 4D wet refractivity fields, which are then validated using forecast analysis from the European Center for Medium Range Weather Forecast (ECMWF). We conclude that tomographic techniques can be used to monitor the troposphere in time and space.     

Impact of number of realizations on the suitability of simulated weather data for hydrologic and environmental applications

Stochastic weather generators are widely used in hydrological, environmental, and agricultural applications to simulate weather time series. However, such stochastic models produce random outputs hence the question on how representative the generated data are if obtained from only one simulation run (realization) as is common practice. In this study, the impact of different numbers of realizations (1, 25, 50, and 100) on the suitability of generated weather data was investigated. Specifically, 50 years of daily precipitation, and maximum and minimum temperatures were generated for three weather stations in the Western Lake Erie Basin (WLEB), using three widely used weather generators, CLIGEN, LARSWG and WeaGETS. Generated results were compared with 50 years of observed data. For all three generators, the analyses showed that one realization of data for 50 years of daily precipitation, and maximum and minimum temperatures may not be representative enough to capture essential statistical characteristics of the climate. Results from the three generators captured the essential statistical characteristics of the climate when the number of realizations was increased from 1 to 25, 50 or 100. Performance did not improve substantially when realizations were increased above 25. Results suggest the need for more than a single realization when generating weather data and subsequently utilizing in other models, to obtain suitable representations of climate.     

天气和气候的时间序列特征分析

本文从天气和气候资料出发，提出气候的q阶（0≤q≤1）微商是天气，而天气可以近似为白噪声.在此基础上，利用描述自相似非马尔可夫随机过程的时间分数维扩散方程的分析成果，并结合时间序列的相关性分析，从理论上进一步指出气候信号的记忆性好于天气信号，且其概率密度分布的尾巴比较长.     

水汽螺旋度和热力螺旋度在华北强“桑拿天”过程中的分析及应用

"桑拿天"是发生在夏季高温、高湿环境之下的重要天气现象.而过去单靠温度这一变量来诊断预报"桑拿天",有较大难度.而且从已有的研究中,"桑拿天"多发生在下沉运动或相对稳定的环流背景下.因此,寻找一个简单有效、且使用方便的物理变量来揭示"桑拿天"高湿、高湿的综合特征,显得特别重要.本文在前人研究的基础上,将以往暴雨研究中的IM (Ingredients-based Methodology)理论方法拓展至"桑拿天"的研究,将过去表征桑拿天高温、高湿、下沉运动环流特点的这些单个物理量综合进IM方法,尝试性地引入热力螺旋度(TH)、水汽螺旋度(MH)、以及湿热力螺旋度(MTH)等,对发生在2002年7月30日-8月4日和2009年7月7-9日的两次华北地区高温高湿的强"桑拿天"过程进行动力识别和诊断,并与广义湿位涡(GMPV)进行对比分析.分析结果表明,MH的异常大值区相对集中在北京及其周边的华北地区的对流层低层,并维持.而TH的异常大值区涵盖的范围远大于我们要研究的华北地区"桑拿天"的爆发范围.即使结合了温、湿效应的MTH和GMPV的异常大值区,其涵盖的范围亦逊于MH对"桑拿天"的动力识别.可见,在夏季普遍高温的大环境下,湿度是华北闷热的"桑拿天"爆发的一个决定性因素.结合了环流特征与湿度效应的MH,是对"桑拿天"进行动力识别的一个优化因子,具有较大的实际应用价值.     

Conditioning temperature‐index model parameters on synoptic weather types for glacier melt simulations

Temperature‐index models are widely favoured as a pragmatic means of simulating glacier melt because of their generally good performance, computational simplicity and limited demands for in situ data. However, their coefficients are normally treated as temporally stationary, unrealistically assuming a constancy of the prevailing weather. We address this simplification by prescribing model coefficients as a function of synoptic weather type, in a procedure that utilizes reanalysis data and preserves the minimal data requirements of temperature‐index models. Using a cross‐validation procedure at Vestari Hagafellsjökull, Iceland, and Storglaciären, Sweden, we demonstrate that applying transient model coefficients, for three temperature‐index models, results in statistically significant increases in the skill with which melt is modelled: Median simulation improvements in the Nash–Sutcliffe efficiency coefficient of 7.3 and 23.6% are achieved when hourly and daily melt totals are evaluated respectively. Our weather‐type modelling approach also yields insight to processes driving parameter variability, revealing dependence that is consistent with a priori considerations of the surface energy balance. We conclude that incorporating weather types into temperature‐index models holds promise for improving their performance, as well as enhancing understanding variability in coefficient values. Copyright © 2014 John Wiley & Sons, Ltd.     

台阵地震学方法及对间断面结构的研究进展

地震台阵是为了监测核爆而发展起来的一种地震观测系统。近年来,地震台阵被推广到地球内部速度间断面的研究中并极大地推动了地震学的发展。本文主要介绍处理台阵资料的技术方法,如聚束、倾斜叠加、N次根叠加、频率波数法以及相位加权叠加等,并讨论各种方法的优缺点。在提取微弱但相关信号方面,重点讨论相位加权叠加方法及现有的研究成果。结果表明,这些方法都在不同程度上提高了记录的信噪比,高质量的台阵数据使得地球内部速度结构的成像研究更加精细。     

An evaluation of numerical weather prediction based rainfall forecasts

ABSTRACT

Assessment of forecast precipitation is required before it can be used as input to hydrological models. Using radar observations in southeastern Australia, forecast rainfall from the Australian Community Climate Earth-System Simulator (ACCESS) was evaluated for 2010 and 2011. Radar rain intensities were first calibrated to gauge rainfall data from four research rainfall stations at hourly time steps. It is shown that the Australian ACCESS model (ACCESS-A) overestimated rainfall in low precipitation areas and underestimated elevated accumulations in high rainfall areas. The forecast errors were found to be dependent on the rainfall magnitude. Since the cumulative rainfall observations varied across the area and through the year, the relative error (RE) in the forecasts varied considerably with space and time, such that there was no consistent bias across the study area. Moreover, further analysis indicated that both location and magnitude errors were the main sources of forecast uncertainties on hourly accumulations, while magnitude was the dominant error on the daily time scale. Consequently, the precipitation output from ACCESS-A may not be useful for direct application in hydrological modelling, and pre-processing approaches such as bias correction or exceedance probability correction will likely be necessary for application of the numerical weather prediction (NWP) outputs.

EDITOR M.C. Acreman ASSOCIATE EDITOR A. Viglione     

Using the Climate Forecast System Reanalysis as weather input data for watershed models

Obtaining representative meteorological data for watershed‐scale hydrological modelling can be difficult and time consuming. Land‐based weather stations do not always adequately represent the weather occurring over a watershed, because they can be far from the watershed of interest and can have gaps in their data series, or recent data are not available. This study presents a method for using the Climate Forecast System Reanalysis (CFSR) global meteorological dataset to obtain historical weather data and demonstrates the application to modelling five watersheds representing different hydroclimate regimes. CFSR data are available globally for each hour since 1979 at a 38‐km resolution. Results show that utilizing the CFSR precipitation and temperature data to force a watershed model provides stream discharge simulations that are as good as or better than models forced using traditional weather gauging stations, especially when stations are more than 10 km from the watershed. These results further demonstrate that adding CFSR data to the suite of watershed modelling tools provides new opportunities for meeting the challenges of modelling un‐gauged watersheds and advancing real‐time hydrological modelling. Copyright © 2013 John Wiley & Sons, Ltd.     

A case study of a dust storm weather situation in the Sudan in April 1973

Summary In connection with an invasion of cold air from the north over the Sudan in April 1973, a major dust storm or rather, a dust storm complex, passed over most of the Sudan.The weather development during this dust storm period is described and illustrated in detail with the aid of synoptic weather and visibility maps, as well as time sections based on SYNOP, METAR, and radiosonde reports from Sudanese meteorological stations.With the aid of the synoptic maps it has been possible to follow the development and movement of the dust storm complex and its relation to the cold fronts preceding the cold air invasion, to the intertropical front (ITF), and to thunderstorm highs which developed within the monsoon air south of the ITF during the initial stage. It was also possible to follow the latitudinal displacements of the ITF, which were caused by the weather systems and associated pressure changes in the harmattan and the monsoon air masses on both sides of it.At the beginning of the dust storm the cold fronts from the north were fairly distinct, but they gradually lost their frontal character. The cold air advection, however, gave rise to increased instability in the lower atmospheric layers, which facilitated the development of dust storms. Eventually the cold fronts merged with the ITF, which, on the other hand, constituted a sharp demarcation line between the harmattan and the monsoon air masses during the whole period, particularly with regard to the air borne dust. From the time sections and the synoptic maps it is evident that the discrepancy in concentration of air borne dust was very sharp along the ITF, particularly during the latter part of the dust storm period. When the ITF slowed down and eventually approached its southernmost position and, simultaneously, the cold air invasion ceased, the dust accumulated in part in the southeastern areas and was in part drained out of the Sudan to the southwest, passing the Central African Republic.     

Climatology of the occurrences of thundery weather over Gauhati airport

Summary The probability of occurrences of thundery weather over Gauhati airport has been investigated. During the pre-monsoon thunderstorm period, the months of April and May have higher probabilities for the occurrences of thundery weather and the month of March has, on average, medium probabilities. The probability for thundery weather, during the months of March and April, is the highest during >18 to 24 h and then decreases successively during 00 to 06 h, >12 to 18 h and >06 to 12 h in order. The month of May, being the transition season for sharp decrease of nor' westers, is an exception. The months June to September, during monsoon season, have high probabilities for a day being thundery; but the month of October, during which monsoon virtually withdraws, shows decreasing trend in probabilities for successive date-groups. During the whole of the monsoon months, the time-groups >12 to 18 h, >18 to 24 h, 00 to 06 h and >06 to 12 h rank first, second, third and fourth in the order of probability for a day being thundery.In April and May, the probabilities for the occurrences of thundery weather of MLL, LL and VLL groups are higher, but in the month of March, the probabilities for the occurrences of first two groups are higher and the third group has medium probability. During the months June to September, in the monsoon season, the probability for thundery weather of MLL and LL groups are higher but that of VLL group has the medium probability; during the month of October — the last month for monsoon season — MLL and LL have higher and medium probabilities for the occurrences of thundery weather.     

应用地基GPS遥感倾斜路径方向大气水汽总量

应用地基GPS沿倾斜路径方向遥测大气水汽总量,是获得测站周围水汽三维空间分布信息(水汽层析)的基础.本文介绍了地基GPS沿倾斜路径方向遥感大气水汽总量的原理和方法;首先用湿梯度、后处理残差联合计算接收机上空不同方位上大气水汽各向异性成分,在此基础上重构倾斜路径水汽总量.为验证GPS观测结果精度,用微波辐射计（WVR）与GPS一起进行了联合观测,不同观测地点和时间的对比结果表明,二者root mean square (RMS)误差小于4mm,证明应用此种方法地基GPS可较精确地反演出倾斜路径方向大气水汽总量,而且这种反演方法适合于近实时大气遥感探测.地基GPS测量具有全天候可连续观测等优点,可以弥补常规观测的不足,为气候研究提供高精度且连续的水汽数据资料;组网观测可以为数值天气预报提供好的初始场,提高模式预报精度.     

如何提高天气预报和气候预测的技巧？

从理论上探讨如何提高天气预报和气候预测的技巧.气候包括以小时为基本单位的昼夜循环、以日为基本单位的年(季节)循环、年代际循环和世纪循环等时间尺度的变化.这些气候变化存在确定的外强迫,是可以被认识和预报的.相对气候昼夜循环和年(季节)循环的偏差是天气尺度扰动.天气尺度的瞬变大气扰动可引发极端天气事件.有技巧的天气预报正是要通过天气尺度大气扰动信号,提前几天甚至十几天,预报出极端天气事件的发生.相对气候年代际和世纪循环的偏差是气候异常,有技巧的气候预测正是要预报出这种异常.距平天气图会大大提高短期和中期—延伸期天气预报的技巧,距平数值预报模式的研制也会加快提高中期—延伸期天气预报和气候预测的技巧.     

Estimating reference evapotranspiration using numerical weather modelling

Evapotranspiration is an important hydrological process and its estimation usually needs measurements of many weather variables such as atmospheric pressure, wind speed, air temperature, net radiation and relative humidity. Those weather variables are not easily obtainable from in situ measurements in practical water resources projects. This study explored a potential application of downscaled global reanalysis weather data using mesoscale modelling system 5 (MM5). The MM5 is able to downscale the global data down to much finer resolutions in space and time for use in hydrological investigations. In this study, the ERA‐40 reanalysis data are downscaled to the Brue catchment in southwest England. The results are compared with the observation data. Among the studied weather variables, atmospheric pressure could be derived very accurately with less than 0·2% error. On the other hand, the error in wind speed is about 200–400%. The errors in other weather variables are air temperature (<10%), relative humidity (5–21%) and net radiation (4–23%). The downscaling process generally improves the data quality (except wind speed) and provides higher data resolution in comparison with the original reanalysis data. The evapotranspiration values estimated from the downscaled data are significantly overestimated across all the seasons (27–46%) based on the FAO Penman–Monteith equation. The dominant weather variables are net radiation (during the warm period) and relative humidity (during the cold period). There are clear patterns among some weather variables and they could be used to correct the biases in the downscaled data from either short‐term in situ measurements or through regionalization from surrounding weather stations. Artificial intelligence tools could be used to map the downscaled data directly into evapotranspiration or even river runoff if rainfall data are available. This study provides hydrologists with valuable information on downscaled weather variables and further exploration of this potentially valuable data source by the hydrological community should be encouraged. Copyright © 2010 John Wiley & Sons, Ltd.     

中国空间天气研究进展

空间天气指太阳、行星际空间和地球空间(地球磁层、电离层、热层和中高层大气)的状态及其变化,它能够影响到天基和地基技术系统的运行和可靠性,危及人类的生存.空间天气计划包括观测和资料分析,研究和数值建模,预报和服务.本文评述了近十年来我国空间天气研究中的一些重要成果.     

Simulation of future climate scenarios with a weather generator

Numerous studies across multiple disciplines search for insights on the effects of climate change at local spatial scales and at fine time resolutions. This study presents an overall methodology of using a weather generator for downscaling an ensemble of climate model outputs. The downscaled predictions can explicitly include climate model uncertainty, which offers valuable information for making probabilistic inferences about climate impacts. The hourly weather generator that serves as the downscaling tool is briefly presented. The generator is designed to reproduce a set of meteorological variables that can serve as input to hydrological, ecological, geomorphological, and agricultural models. The generator is capable of reproducing a wide set of climate statistics over a range of temporal scales, from extremes, to low-frequency interannual variability; its performance for many climate variables and their statistics over different aggregation periods is highly satisfactory. The use of the weather generator in simulations of future climate scenarios, as inferred from climate models, is described in detail. Using a previously developed methodology based on a Bayesian approach, the stochastic downscaling procedure derives the frequency distribution functions of factors of change for several climate statistics from a multi-model ensemble of outputs of General Circulation Models. The factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. Using embedded causal and statistical relationships, the generator simulates future realizations of climate for a specific point location at the hourly scale. Uncertainties present in the climate model realizations and the multi-model ensemble predictions are discussed. An application of the weather generator in reproducing present (1961-2000) and forecasting future (2081-2100) climate conditions is illustrated for the location of Tucson (AZ). The stochastic downscaling is carried out using simulations of eight General Circulation Models adopted in the IPCC 4AR, A1B emission scenario.