双偏振雷达对贵州一次强对流过程的应用分析

利用习水双偏振雷达对2021年5月2日发生在贵州西北部的一次冰雹、短时强降水过程进行分析,结果表明：双偏振雷达能够很好区分出冰雹和短时强降水,并可以分析出冰雹相态演变：高空出现明显的冰雹特征(差分反射率因子Zdr、差分相移率Kdp小于0 dB,相关系数CC为0.9～0.95),随着高度降低Zdr和Kdp从负值向正值转变,CC增加到0.95左右,表明冰雹在下落过程中融化为包裹着水膜的小冰雹并伴随降水,这与地面观测事实一致。观测到CC谷、Zdr弧、Zdr柱、Kdp柱和典型的三体散射双偏振特征,这些特征对雹暴的演变有指示作用。短时强降水回波的Zdr和Kdp随反射率因子强度的增大而增大,CC＞0.95,Kdp大值区能更好的指示出短时强降水的位置。     

雷达反演水汽在华南前汛期短时临近降水预报应用试验

为了改善数值预报模式短时临近降水预报能力,采用雷达水汽反演同化方案来提高模式初始水汽场质量。以华南精细预报模式对2013年5月进行了冷启动、热启动和热启动加雷达水汽同化等3个对比试验,并进一步详细分析2013年5月8—9日广东西南部到珠三角地区强降雨过程,探讨雷达反演水汽对短时临近降水预报的影响作用。分析结果显示3个试验结果反映精细模式冷启动不利于1~6 h的降水预报,模式热启动能较好预报前6 h的降水,但对随后预报效果不佳。在热启动的基础上,考虑同化雷达反演的水汽后,不仅较好模拟前6 h的降水,也可以预报出6~12 h的降雨带变化趋势。     

对流电场产生电离层扰动的典型事例

用欧空局ＥＩＳＣＡＴ极光区非相干散射雷达观测资料、南极中山站电离层垂测站和我国１２０°Ｅ电离层站链ｆ０Ｆ２资料，分析了１９９１年５月２～３日一次主要由磁层对流引起的电离层扰动过程。从形态特征上看，它与热层中性大气参与的动力耦合过程明显地不同。对照比较表明，这是一次典型的磁层－电离层电动耦合事例。全球地磁站网资料从另一侧面证实，本文讨论的耦合机制是正确的。     

Spatial variability of rainfall on a sub‐kilometre scale

The variability of rainfall in space and time is an essential driver of many processes in nature but little is known about its extent on the sub‐kilometre scale, despite many agricultural and environmental experiments on this scale. A network of 13 tipping‐bucket rain gauges was operated on a 1·4 km² test site in southern Germany for four years to quantify spatial trends in rainfall depth, intensity, erosivity, and predicted runoff. The random measuring error ranged from 10% to 0·1% in case of 1 mm and 100 mm rainfall, respectively. The wind effects could be well described by the mean slope of the horizon at the stations. Except for one station, which was excluded from further analysis, the relative differences due to wind were in maximum ±5%. Gradients in rainfall depth representing the 1‐km² scale derived by linear regressions were much larger and ranged from 1·0 to 15·7 mm km^?1 with a mean of 4·2 mm km^?1 (median 3·3 mm km^?1). They mainly developed during short bursts of rain and thus gradients were even larger for rain intensities and caused a variation in rain erosivity of up to 255% for an individual event. The trends did not have a single primary direction and thus level out on the long term, but for short‐time periods or for single events the assumption of spatially uniform rainfall is invalid on the sub‐kilometre scale. The strength of the spatial trend increased with rain intensity. This has important implications for any hydrological or geomorphologic process sensitive to maximum rain intensities, especially when focusing on large, rare events. These sub‐kilometre scale differences are hence highly relevant for environmental processes acting on short‐time scales like flooding or erosion. They should be considered during establishing, validating and application of any event‐based runoff or erosion model. Copyright © 2009 John Wiley & Sons, Ltd.     

Bootstrap based artificial neural network (BANN) analysis for hierarchical prediction of monthly runoff in Upper Damodar Valley Catchment

Estimation of runoff is a prerequisite for many applications involving conservation and management of water resources. This study is undertaken in the Upper Damodar Valley Catchment (UDVC) having a drainage area of 17513.08 km² for prediction of monthly runoff. Thirty one microwatersheds and 15 sub-watersheds were selected from a total of 716 microwatersheds in the catchment area for this study. The feasibility of using different soil attributes (particle size distribution, organic matter content and apparent density), topographic attributes (primary, secondary and compound), geomorphologic attributes (basin, relief and network indices) and vegetation attribute as Normalized Difference Vegetation Index (NDVI), on prediction of monthly runoff were explored in this study. Principal Component Analysis (PCA) was applied to minimize the data redundancy of the input variables. Ten significant input variables namely; watershed length (km), elongation ratio, bifurcation ratio, area ratio, coarse sand (%), fine sand (%), elevation (m), slope (°), profile curvature (rad/m) and NDVI were selected. The selected input variables were added in hierarchy with monthly rainfall (mm) as inputs for prediction of monthly runoff (mm) using Bootstrap based artificial neural networks (BANN). The performance of the models was tested using Spearman’s correlation coefficient (r), coefficient of efficiency (COE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Best performance was observed for model with monthly rainfall, slope, coarse sand, bifurcation ratio and Normalized Difference Vegetation Index (NDVI) as inputs (r = 0.925 and COE = 0.839). Increase in number of input variables did not necessarily yield better performances of the BANN models. Selection of relevant inputs and their combinations were found to be key elements in determining the performance of BANN models. Annual runoff map was generated for all the microwatersheds utilizing the weights of the best performing BANN model. This study reveals that the specific combinations of soil, topography, geomorphology and vegetation inputs can be utilized for better prediction of monthly runoff.     

Rainfall network design using kriging and entropy

The spatial distribution of rainfall is related to meteorological and topographical factors. An understanding of the weather and topography is required to select the locations of the rain gauge stations in the catchment to obtain the optimum information. In theory, a well‐designed rainfall network can accurately represent and provide the needed information of rainfall in the catchment. However, the available rainfall data are rarely adequate in the mountainous area of Taiwan. In order to provide enough rainfall data to assure the success of water projects, the rainfall network based on the existing rain gauge stations has to be redesigned. A method composed of kriging and entropy that can determine the optimum number and spatial distribution of rain gauge stations in catchments is proposed. Kriging as an interpolator, which performs linear averaging to reconstruct the rainfall over the catchment on the basis of the observed rainfall, is used to compute the spatial variations of rainfall. Thus, the rainfall data at the locations of the candidate rain gauge stations can be reconstructed. The information entropy reveals the rainfall information of the each rain gauge station in the catchment. By calculating the joint entropy and the transmitted information, the candidate rain gauge stations are prioritized. In addition, the saturation of rainfall information can be used to add or remove the rain gauge stations. Thus, the optimum spatial distribution and the minimum number of rain gauge stations in the network can be determined. The catchment of the Shimen Reservoir in Taiwan is used to illustrate the method. The result shows that only seven rain gauge stations are needed to provide the necessary information. Copyright © 2007 John Wiley & Sons, Ltd.     

Spatial and temporal characteristics of droughts in the western part of Bangladesh

Spatial and temporal characteristics of droughts in the western part of Bangladesh have been analysed. Standardized precipitation index method is used to compute the severity of droughts from the rainfall data recorded in 12 rainfall gauge stations for the period of 1961–1999. An artificial neural network is used to estimate missing rainfall data. Geographic Information System (GIS) is used to map the spatial extent of droughts of different severities in multiple time scales. Critical analysis of rainfall is also carried to find the minimum monsoon and dry months rainfall require in different parts of the study area to avoid rainfall deficit. The study shows that the north and north‐western parts of Bangladesh are most vulnerable to droughts. A significant negative relationship between multiple ENSO index and rainfall is observed in some stations. Analysis of seasonal rainfall distribution, rainfall reliability and long‐term rainfall trend is also conducted to aid prediction of future droughts in the area. Copyright © 2007 John Wiley & Sons, Ltd.     

A cascade approach to continuous rainfall data generation at point locations

High-resolution temporal rainfall data sequences serve as inputs for a range of applications in planning, design and management of small (especially urban) water resources systems, including continuous flow simulation and evaluation of alternate policies for environmental impact assessment. However, such data are often not available, since their measurements are costly and time-consuming. One alternative to obtain high-resolution data is to try to derive them from available low-resolution information through a disaggregation procedure. This study evaluates a random cascade approach for generation of high-resolution rainfall data at a point location. The approach is based on the concept of scaling in rainfall, or, relating the properties associated with the rainfall process at one temporal scale to a finer-resolution scale. The procedure involves two steps: (1) identification of the presence of scaling behavior in the rainfall process; and (2) generation of synthetic data possessing same/similar scaling properties of the observed rainfall data. The scaling identification is made using a statistical moment scaling function, and the log–Poisson distribution is assumed to generate the synthetic rainfall data. The effectiveness of the approach is tested on the rainfall data observed at the Sydney Observatory Hill, Sydney, Australia. Rainfall data corresponding to four different successively doubled resolutions (daily, 12, 6, and 3 h) are studied, and disaggregation of data is attempted only between these successively doubled resolutions. The results indicate the presence of multi-scaling behavior in the rainfall data. The synthetic data generated using the log–Poisson distribution are found to exhibit scaling behaviors that match very well with that for the observed data. However, the results also indicate that fitting the scaling function alone does not necessarily mean reproducing the broader attributes that characterize the data. This observation clearly points out the extreme caution needed in the application of the existing methods for identification of scaling in rainfall, especially since such methods are also prevalent in studies of the emerging satellite observations and thus in the broader spectrum of hydrologic modeling.     

Estimation of precipitation condensation latent heat in rainy season over Qinghai-Tibet Plateau

The basic data for this research comprise the outgoing long-wave radiation(OLR) data observed by the United States National Oceanic and Atmospheric Administration(NOAA) series satellites from June 1974 through December 2005 over the area of 75°-105°E and 25°-40°N(totaling 91 grid zones when the horizontal resolution is 2.5° longitude by 2.5° latitude) and the monthly rainfall data recorded,from 1961 through 2005,by 93 conventional meteorological stations on the Qinghai-Tibet Plateau.Based on the research of the relation between rainfall and OLR and climate regionalization,a mathematic model was established for each region and grid zone,which is applied to estimate the monthly rainfall and then to estimate the monthly latent heat resulting from the condensation of precipitation year by year from 1961 through 2005.The results indicated that the multi-year average precipitation is 401.5 mm and the condensation latent heat is 18.55×1020 J in the eastern part of the Qinghai-Tibet Plateau;the increasing rate of condensation latent heat is 0.218×1020J/10a in the recent 45 years;that is to say,it will increase 1.2 percent in each decade.Furthermore,the total condensation latent heat and its variation rate in the Qinghai-Tibet Plateau are slightly larger than in the east to the plateau.     

An integrated lake-catchment approach for determining sediment source changes at Aqualate Mere,Central England

This paper raises fundamental questions about the sole use of paleolimnological techniques to identify sediment sources and develop catchment management plans. The concept of an integrated lake: catchment framework was established 30 years ago, yet paleolimnologists occasionally fail to appreciate the dynamics of the contributing catchment. This is especially critical when the predominant source of sediment accumulating in a lake is allochthonous. In this paper we argue that a detailed appraisal of catchment sources and investigation of historical documentary evidence is needed to identify and evaluate the relative significance of sediment sources. We used such an approach at Aqualate Mere, Shropshire, UK. Mineral magnetic and radionculide signatures of potential catchment sources and accumulating lake sediments were compared in an attempt to match the sources to sediments deposited in the Mere. Dated lake sediments indicate there has been an increase in sedimentation rate and the relative amount of minerogenic material delivered to the Mere over the last 200 years. In contrast to a previous study at the same site, there is no evidence to attribute this increase to an overspill from a nearby canal. Other catchment disturbances include landscaping in parkland surrounding the Mere in the early nineteenth century and drainage systems installed to improve catchment agriculture over the last ca. 150 years. Both activities may explain the change in sedimentation rates and types, independent of the hypothesized canal origin. Although our results exclude the canal as a major sediment source, identifying the contribution of other potential catchment sources remains problematic. ¹³⁷Cs inventories for the lake are similar to those recorded at a local reference site, suggesting little influx of ¹³⁷Cs-bearing topsoil, yet ¹³⁷Cs activities remain high in the upper 20–30 cm of the lake sediment profile, indicating a topsoil origin. Combined radionuclide and mineral magnetic signatures proved to be relatively poor discriminators of potential sources, and the high atmospheric pollution load from the West Midland conurbation has probably altered recent lake sediment signatures. Although further research is required to identify the origins of recent (last ca. 200 years) minerogenic sediment inputs to the Mere, we suggest that the combined lake: catchment approach offers a more rigorous method for understanding the impact of catchment disturbance than analysis of the paleolimnological record alone.