Analyses of the warm season rainfall climatology of the northeastern US using regional climate model simulations and radar rainfall fields

We examine the warm season (April-September) rainfall climatology of the northeastern US through analyses of high-resolution radar rainfall fields from the Hydro-NEXRAD system and regional climate model simulations using the weather research and forecasting (WRF) model. Analyses center on the 5-year period from 2003 to 2007 and the study area includes the New York-New Jersey metropolitan region covered by radar rainfall fields from the Fort Dix, NJ WSR-88D. The objective of this study is to develop and test tools for examining rainfall climatology, with a special focus on heavy rainfall. An additional emphasis is on rainfall climatology in regions of complex terrain, like the northeastern US, which is characterized by land-water boundaries, large heterogeneity in land use and cover, and mountainous terrain in the western portion of the region. We develop a 5-year record of warm season radar rainfall fields for the study region using the Hydro-NEXRAD system. We perform regional downscaling simulations for the 5-year study period using the WRF model. Radar rainfall fields are used to characterize the interannual, seasonal and diurnal variation of rainfall over the study region and to examine spatial heterogeneity of rainfall. Regional climate model simulations are characterized by a wet bias in the rainfall fields, with the largest bias in the high-elevation regions of the model domain. We show that model simulations capture broad features of the interannual, seasonal, and diurnal variation of rainfall. Model simulations do not capture spatial gradients in radar rainfall fields around the New York metropolitan region and land-water boundaries to the east. The model climatology of convective available potential energy (CAPE) is used to interpret the regional distribution of warm season rainfall and the seasonal and diurnal variability of rainfall. We use hydrologic and meteorological observations from July 2007 to examine the interactions of land surface processes and rainfall from a regional perspective.     

卫星遥感数据评估黄土高原陆面干湿程度研究

卫星遥感数据具有估算时空尺度上地表参量的优势,在陆地环境状况评估和监测等方面有很大的应用潜力.本文利用美国地球观测系统卫星搭载中等分辨率成像光谱仪（EOS/MODIS）在黄土高原2002-2010年期间获取的每16天归一化植被指数（NDVI）和每日地表温度（LST）数据,分析了黄土高原地区LST-NDVI空间的基本特征.结果发现：当研究区域足够大且遥感数据时间序列足够长时,LST-NDVI空间中（NDVI,LST）散点并非呈三角形或梯形分布.为了能够利用EOS/MODIS的NDVI和LST数据正确地评估陆面的干湿状况,本文给出了利用数据集合法确定LST-NDVI空间中干边和湿边的数值,即在LST-NDVI空间中,利用NDVI等值区间内LST最大值和最小值的集合代表干边和湿边的数值,并进一步证明了在LST-NDVI空间中干边和湿边数值并非呈线性关系.在分析LST-NDVI空间特征的基础上,通过构建地表温度-植被干旱指数（TVDI）,探讨其在评估黄土高原地区陆面的干湿状况的应用潜力.结果表明：由TVDI距平表征的陆面的干湿程度与局地降水距平有很好的关联性,二者在时空分布上有较好的对应关系.在我国陇东黄土高原塬区,TDVI数值与地面观测的表层土壤湿度有很好的相关性,相关系数在0.67以上,并通过显著性为1%的检验.由此说明：如果合理选取干边和湿边的数值,TDVI可应用于区域陆面干湿程度的客观评估.     

Modelling runoff using optical satellite remote sensing data in a high mountainous alpine catchment of Italy

Development of hydrological models for seasonal and real-time runoff forecast in rivers of high alpine catchments is useful for management of water resources. The conceptual models for this purpose are based on a temperature index and/or energy budget and can be either lumped or distributed over the catchment area. Remote sensing satellite data are most useful to acquire near real-time geophysical parameters in order to input to the distributed forecasting models. In the present study, integration of optical satellite remote sensing-derived information was made with ground meteorological and hydrological data, and predetermined catchment morphological parameters, to study the feasibility of application of a distributed temperature index snowmelt runoff model to one of the high mountainous catchments in the Italian Alps, known as Cordevole River Basin. Five sets of Landsat Multispectral Scanning System (MSS) and Thematic Mapper (TM) computer-compatible tapes (CCTs) were processed using digital image processing techniques in order to evaluate the snow cover variation quantitatively. Digital elevation model, slope and aspect parameters were developed and used during satellite data processing. The satellite scenes were classified as snow, snow under transition and snow free areas. A second-order polynomial fit has been attempted to approximate the snow depletion and to estimate daily snow cover areal extent for three elevation zones of the catchment separately. Model performance evaluation based on correlation coefficient, Nash–Sutcliffe coefficient and percentage volume deviation indicated very good simulation between measured and computed discharges for the entire snowmelt period. The use of average temperature values computed from the maximum and minimum temperatures into the model was studied and a suitable algorithm was proposed. © 1997 John Wiley & Sons, Ltd.     

星间加速度解算模式的模拟与分析

低低卫星跟踪卫星的观测量是两低轨卫星的星间距离或星间速度,星间加速度由星间速度通过数值微分导出,用星间加速度作为观测量可以避免解算卫星运动的变分方程,简化观测方程的建立,但数值微分会使观测噪声放大,从而影响重力位的解算精度.为了定量给出星间加速度观测模式的精度,本文分析并模拟验证了数值微分公式计算星间加速度的精度,导出了基于星间加速度的一般形式的观测方程,模拟计算了基于星间加速度的重力位模型.结果表明,采用星间加速度观测模式的解算精度要明显低于星间速度观测模式的解算精度.     

The water regime of the Monegros playa-lakes as established from ground and satellite data

The Monegros playa-lakes are isolated saline wetlands, locally named ‘saladas’, situated in a vulnerable semi-arid territory where agricultural expansion threatens the natural hydrologic cycle with regular artificial flooding, risking the survival of a valuable natural resource. This study aims to examine the water regime of these playa-lakes from climate data and available hydrologic records. These records are historical and limited to a series of weekly measurements of depth and of water extent extracted from Landsat imagery. We have characterized the hydrological behavior of the playa-lakes by treating ground and satellite data separately. For this purpose, the playa-lakes are first grouped according to the water occurrence episodes. Then their hydrologic status is related to the previous rainfall and also to ET₀, since there is a lack of local records of wind as well as brine or fresh water evaporation. The northern playa-lakes respond to rain faster than the southern ones. All playa-lakes have a significant relationship between water occurrence and rainfall accumulated within 180 days prior to an observation. A significant relationship between ET₀ and water occurrence was found for a shorter 15-day accumulation period. Quantifying the current water regime now is critical for monitoring the effects of expanding irrigation in adjacent lands. Remote sensing is well-suited to an environmental assessment for regions of difficult access with the added benefit of lowered field measurement cost. The hydrological data from the Monegros playa-lakes could be integrated with other playa environments worldwide to compare regionally specific climate conditions.     

Joint distribution of multiplicative errors in radar and satellite QPEs and its use in estimating the conditional exceedance probability

This paper characterizes the joint distribution of multiplicative errors (ME) in radar (R) and satellite (S) quantitative precipitation estimates (QPEs). A semi-parametric framework is established on the basis of this joint distribution to describe the probability of rainfall exceeding a particular threshold given concurrent R and S-based estimates (referred to as conditional exceedance probability, or CEP). This framework entails integrating copula-based joint distributions of MEs over a range of rainfall amounts to yield the joint probability of exceedance, which forms the basis for estimating CEP. In demonstrating this approach, MEs were computed for R (Weather Surveillance Radar-1988 Doppler) and S (Self-calibrating Multivariate Precipitation Retrieval) for central Texas over 2000–2007 using gauge records as the reference. Analysis of the MEs in R and S reveals a substantial correlation between the two, and it also shows that the interdependence is complex as a considerable portion of S QPEs are negatively biased while their concurrent R values are bias-neutral. CEP values from the semi-parametric approach is found to be generally superior to those empirically derived based on rainfall estimates: it yields values for a wide range of rainfall thresholds and suffers much fewer discontinuities and artifacts that the empirical results exhibit. For the lower range of S and R thresholds where sample size is relatively large (i.e., <20 mm h⁻¹ for the summer), the two sets of CEPs bear close resemblance, with both showing a relatively weak, but nevertheless substantial dependence on the threshold value for S. These findings confirm the plausibility of the semi-parametric CEP values, and demonstrate the utility of S QPEs in improving the confidence in rainfall exceedance under this framework.     

Sequential assimilation of a year-long time-series of SeaWiFS chlorophyll data into a 3D biogeochemical model on the French Mediterranean coast

The objective of this paper was to explore the potentialities of sequential statistical estimation methods to assimilate ocean color observations in a primary production model coupled to a 3D hydrodynamic model. The study site was the gulf of Fos—Rhone delta region on the French Mediterranean coast. The high rate of primary production generally observed in this area is mainly due to strong nutrient inputs of the Rhone River. The assimilation method is derived from the singular evolutive extended Kalman filter (SEEK), which uses an error subspace represented by multivariate empirical orthogonal functions (EOF). SeaWiFS chlorophyll data were assimilated by the ecosystem model during a simulation performed under realistic meteorological conditions for the year 2001. An ‘adaptive’ computing method of the EOF was applied in order to lower the instabilities of the filter. Data assimilation system permitted to reduce the mean absolute error between model and data from 1.51 to 0.77 mg m⁻³ thanks to the SEEK filter, showing a substantial 49% gain. Efficiency of the SEEK filter was then investigated considering several areas of interest inside the modelled domain. Finally, impact of the assimilation scheme on non-observed variables was illustrated and discussed. Throughout this experimentation the data assimilation system showed its potential regarding operational systems.     

An evaluation of surface-mine spoils area restoration in wyoming using rainfall simulation

A recently developed rainfall simulator was used to apply ‘rainstorms’ on restored spoils areas at two coal mining sites in Wyoming. Runoff and sediment yield were considerably greater from the reworked areas compared to similar measurements on nearby undisturbed areas. This may possibly be attributed to the fact that in the disturbed areas mean slopes were generally greater, there was more clay at the surface, and concentration of roots was not as great as in the undisturbed areas. The rainfall simulator appears to be a valuable tool in determining baseline data for later comparison with data form areas under rehabilitation.     

利用GRACE卫星重力数据监测关中地区地下水储量变化

关中地区作为一带一路重要的工农业发达地区之一,开展针对该地区地下水储量变化的监测和分析工作对揭示地下水储量变化特征与经济社会发展具有重要现实意义.本文基于2003—2014年GRACE卫星重力场模型数据,采用组合滤波及单一尺度因子方法反演了关中地区陆地水储量变化,扣除GLDAS地表水平均结果,对关中地区地下水储量变化进行了监测分析.将陆地水储量变化与GLDAS进行相关性分析,将地下水储量变化与WGHM地下水模型及实测地下水位结果进行对比分析.研究结果表明：①关中地区陆地水变化与GLDAS模型结果具有较强的相关性,相关系数多数大于0.7,其中与模型平均结果的相关系数可达0.8.② 2003—2008年关中地区地下水呈正增长趋势,增加速率为0.25 cm·a^-1,与同期实测数据变化趋势一致;但2003—2013年地下水存在长期亏损,亏损速率为-0.37 cm·a^-1等效水高,这与同时期WGHM估算结果-0.35 cm·a^-1十分吻合.③关中地区地下水存在明显的年变化特征,在2003—2014年期间地下水减少速率为-0.44 cm·a^-1,与该地区降雨量有较好的一致性,在降雨偏少的2008、2012和2013年,地下水也显著减少.

     

Estimation of maize yield by using a process-based model and remote sensing data in the Northeast China Plain

Climate change significantly impact on agriculture in recent year, the accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C₄ crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS–P–YEC (Remote-Sensing–Photosynthesis–Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS–P–YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002–2011. The 111 statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (p < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002 to 2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.     

Time series analysis of optical remote sensing data for the mapping of temporary surface water bodies in sub-Saharan western Africa

A map of temporary small water bodies (TSWB) at 1 km resolution was derived for the arid, semi-arid and dry sub-humid regions of sub-Saharan western Africa where the spatio-temporal distribution of actual surface water occurrence exhibits high inter- and intra-annual variability. Water bodies and humid areas have been mapped and characterized by the analysis of 10 daily small water bodies (SWB) maps based on SPOT VEGETATION (VGT) data spanning the period January 1999–September 2007. Further analysis of the SWB time series provided additional information about the seasonal recurrence of water bodies as well as their hydrological function. A map derived from a continuous time series assures the inclusion of temporary features, a clear advantage compared to other datasets, which are based on several single date observations. The method described in this paper targets at a rapid creation of TSWB maps based on the SWB time series for different time intervals and regions.An accuracy assessment has been carried out with a stratified random sampling approach and a one-stage cluster analysis that relies on high-resolution satellite data to verify the detected water bodies. The overall accuracy, considering only the commission error, is 95.4% for the whole study region, with best results in the arid and semi-arid climate zone. The method to map water bodies delivers satisfactory results, particularly for sparsely vegetated areas as well as flat areas of the study region. In more humid, more vegetated areas and in mountainous areas, the possibility of false detections increases due to surface characteristics.     

Topography and morphodynamics in the German Bight using SAR and optical remote sensing data

Morphological changes in coastal areas, especially in river estuaries, are of high interest in many parts of the world. Satellite data from both optical and radar sensors can help to monitor and investigate these changes. Data from both kinds of sensors being available for up to 30 years now, allow examinations over large timescales, while high resolution sensors developed within the last decade allow increased accuracy. So the creation of digital elevation models (DEMs) of, for example, the wadden sea from a series of satellite images is already possible. ENVISAT, successfully launched on March 1, 2002, continues the line of higher resolution synthetic aperture radar (SAR) imaging sensors with its ASAR instrument and now also allows several polarization modes for better separation of land and water areas. This article gives an overview of sensors and algorithms for waterline determination as well as several applications. Both optical and SAR images are considered. Applications include morphodynamic monitoring studies and DEM generation.

Hindcast of oil-spill pollution during the Lebanon crisis in the Eastern Mediterranean, July-August 2006

MOON (Mediterranean Operational Oceanography Network http://www.moon-oceanforecasting.eu) provides near-real-time information on oil-spill detection (ocean color and SAR) and predictions [ocean forecasts (MFS and CYCOFOS) and oil-spill predictions (MEDSLIK)]. We employ this system to study the Lebanese oil-pollution crisis in summer 2006 and thus to assist regional and local decision makers in Europe, regionally and locally. The MEDSLIK oil-spill predictions obtained using CYCOFOS high-resolution ocean fields are compared with those obtained using lower-resolution MFS hydrodynamics, and both are validated against satellite observations. The predicted beached oil distributions along the Lebanese and Syrian coasts are compared with in situ observations.The oil-spill predictions are able to simulate the northward movement of the oil spill, with the CYCOFOS predictions being in better agreement with satellite observations. Among the free MEDSLIK parameters tested in the sensitivity experiments, the drift factor appears to be the most relevant to improve the quality of the results.     

Influence of spatial distribution of sensors and observation accuracy on the assimilation of distributed streamflow data in hydrological modelling

The aim of this study is to assess the influence of sensor locations and varying observation accuracy on the assimilation of distributed streamflow observations, also taking into account different structures of semi-distributed hydrological models. An ensemble Kalman filter is used to update a semi-distributed hydrological model as a response to measured streamflow. Various scenarios of sensor locations and observation accuracy are introduced. The methodology is tested on the Brue basin during five flood events. The results of this work demonstrate that the assimilation of streamflow observations at interior points of the basin can improve the hydrological models according to the particular location of the sensors and hydrological model structure. It is also found that appropriate definition of the observation accuracy can affect model performance and consequent flood forecasting. These findings can be used as criteria to develop methods for streamflow monitoring network design.     

Modelling the water balance of a mesoscale catchment basin using remotely sensed land cover data

Hydrological modelling of mesoscale catchments is often adversely affected by a lack of adequate information about specific site conditions. In particular, digital land cover data are available from data sets which were acquired on a European or a national scale. These data sets do not only exhibit a restricted spatial resolution but also a differentiation of crops and impervious areas which is not appropriate to the needs of mesoscale hydrological models. In this paper, the impact of remote sensing data on the reliability of a water balance model is investigated and compared to model results determined on the basis of CORINE (Coordination of Information on the Environment) Land Cover as a reference. The aim is to quantify the improved model performance achieved by an enhanced land cover representation and corresponding model modifications. Making use of medium resolution satellite imagery from SPOT, LANDSAT ETM+ and ASTER, detailed information on land cover, especially agricultural crops and impervious surfaces, was extracted over a 5-year period (2000–2004). Crop-specific evapotranspiration coefficients were derived by using remote sensing data to replace grass reference evapotranspiration necessitated by the use of CORINE land cover for rural areas. For regions classified as settlement or industrial areas, degrees of imperviousness were derived. The data were incorporated into the hydrological model GROWA (large-scale water balance model), which uses an empirical approach combining distributed meteorological data with distributed site parameters to calculate the annual runoff components. Using satellite imagery in combination with runoff data from gauging stations for the years 2000–2004, the actual evapotranspiration calculation in GROWA was methodologically extended by including empirical crop coefficients for actual evapotranspiration calculations. While GROWA originally treated agricultural areas as homogeneous, now a consideration and differentiation of the main crops is possible. The accuracy was determined by runoff measurements from gauging stations. Differences in water balances resulting from the use of remote sensing data as opposed to CORINE were analysed in this study using a representative subcatchment. Resulting Nash–Sutcliff model efficiencies improved from 0.372 to 0.775 and indicate that the enhanced model can produce thematically more accurate and spatially more detailed local water balances. However, the proposed model enhancements by satellite imagery have not exhausted the full potential of water balance modelling, for which a higher temporal resolution is required.     

暴雨触发局部地震活动的一个典型例子:2010年6月广西凌云—凤山交界3级震群活动

在前期严重干旱的背景下,2010年6月27～30日广西西北部出现大暴雨过程,大范围积水成涝.降雨量最大的凌云、凤山交界于6月28日17时开始出现密集的微震活动,形成显著的震群事件.自6月28日至7月15日共记录地震2739次,其中2～2.9级(ML,下同)41次,3级以上地震3次,最大为7月1日10时27分3.2级地震...     

联合GNSS/RS多源数据反演三维大气水汽分布研究

大气水汽作为重要的温室气体之一, 其在全球气候变化研究及极端天气预警中起到重要作用.全球导航卫星系统(Global Navigation Satellite System, GNSS)水汽层析技术作为重构高时空分辨率大气水汽三维分布的重要手段之一, 目前得到了快速的发展和应用.但受GNSS观测信号几何特征的限制, 传统水汽层析模型仍无法解决观测分布不均和空余体素块多的问题.本文首次利用遥感(Remote Sensing, RS)卫星高水平分辨率信号的观测几何优势, 提出一种联合GNSS/RS多源数据的水汽层析方法, 用于反演高精度的三维大气水汽分布.利用徐州地区GNSS观测数据与MODIS、MERSI两种遥感水汽数据对该方法的可行性及精度进行验证.结果表明: 相比于传统GNSS层析模型, GNSS/RS层析模型的观测信号数量和网格穿刺率分别提高了38.41%和55.56%.分别以研究区域的探空站(58027)水汽廓线和ERA5再分析资料为参考值, 发现GNSS/RS层析模型的各类精度指标均优于传统模型, 其中平均均方根误差分别提高了29.68%和20.31%, 并且在不同高度层上GNSS/RS层析水汽产品质量也优于传统模型, 这表明GNSS/RS层析模型可有效改善层析结果质量, 反演出精确、可靠的大气水汽三维分布信息.

     

Comparison of the return period for landslide-triggering rainfall events in Japan based on standardization of the rainfall period

The intensity of rainfall events with potential to cause landslides has varying temporal characteristics. In this study, the time at which the 72-h accumulated rainfall reached its maximum was used to standardize the period of rainfall measurement. The proposed standardization of the rainfall period was used in conjunction with the return level of rainfall intensity, obtained from intensity–duration–frequency curves, to investigate rainfall intensity anomalies associated with 10 hazardous rainfall events that triggered numerous landslides at the regional scale in Japan. These landslides included shallow landslides in volcanic and non-volcanic areas, as well as deep-seated landslides. The rainfall events that triggered the shallow landslides were divided into two types: downpours that repeatedly reached close to the 100-year return level within approximately 3–4 h, and accumulated rainfall that reached close to 200–400 mm over longer time intervals but within 72 h. Lithological differences seemed unrelated to the differences between the two types of shallow-landslide-triggering rainfall; however, precipitation >1000 mm was necessary to trigger deep-seated landslides. Although the characteristics of the hyetographs differed markedly among the landslide-triggering rainfall events, all the landslides could have been triggered when the mean rainfall intensity reached the 100-year rainfall level during the standardized period. Thus, the landslide trigger can be evaluated indirectly based on the increase in the return level of the mean rainfall intensity, which could provide a means for estimating the time of landslide occurrence.     

运用多语言开发震害遥感评估系统数据库的研究

基于遥感提取地震灾情信息,需要处理高分辨率的大数据量遥感影像。采用数据库的方式,对系统处理过程中可能用到的图像文件、典型震害样本文件、系统特征模型库文件、GIS文件以及以往地震处理实例等文件进行管理,将系统各种资源融为一体,将提高地震应急震害遥感评估的效率,提高应急的速度。文中针对IDL在数据库管理方面的不足,提出了利用IDL与VB联合开发遥感图像数据库的解决方案,并具体介绍了图像数据库的实现方式。     

New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 1. Assessment of control climate

Widespread major flood events in both the UK and Europe over the last decade have focussed attention on perceived increases in rainfall intensities. The changing magnitude of such events may have significant impacts upon many sectors, particularly those associated with flooding, water resources and the insurance industry. Here, two methods are used to assess the performance of the HadRM3H model in the simulation of UK extreme rainfall: regional frequency analysis and individual grid box analysis. Both methods use L-moments to derive extreme value distributions of rainfall for 1-, 2-, 5- and 10-day events for both observed data from 204 sites across the UK (1961–1990) and gridded 50 km by 50 km data from the control climate integration of HadRM3H. Despite differences in spatial resolution between the observed and modelled data, HadRM3H provides a good representation of extreme rainfall at return periods of up to 50 years in most parts of the UK. Although the east–west rainfall gradient tends to be exaggerated, leading to some overestimation of extremes in high elevation western areas and an underestimation in eastern ‘rain shadowed’ regions, this suggests that the regional climate model will also have skill in predicting how rainfall extremes might change under enhanced greenhouse conditions.