应用"极值剔除"和"逐步消空"法建立太原机场11月份辐射大雾预报指标集

本文介绍了利用“极值剔除”和“逐步消空”方法建立太原机场11月份辐射大雾预报指标集的具体过程，并对得出的预报指标进行回报检验，以证实其在业务中的切实可行性。     

鹤壁市春旱动态监测及分析

利用鹤壁市淇县1971～2000年降水、底墒、蒸发资料，建立了适用于对春旱进行实时业务监测的动态模型；根据干旱指数大小确定春旱等级，并通过实例对比分析证实干旱指数在分析干旱动态演变过程中的作用。     

冬小麦遥感冠层温度监测土壤含水量的试验研究

在冬小麦主要生育期(2002年4月初到5月底),对不灌溉的冬小麦测定了冠层温度、地温、气温以及土壤含水量,计算了冠气温差且分析了冠层温度和冠气温差与不同土层厚度的土壤含水量相关关系。结果表明:14:00的冠层温度能较好地反映20cm土层的土壤含水量变化,但与其它各土层相关性有较大的波动性;14:00的冠气温差能较好地反映40cm以上土层的土壤含水量变化,二者的相关性很高,在20cm、40cm土层,两者相关系数R2分别为0.98866、0.99389,这为用区域遥感数据反演主要生育期冬小麦的冠气温差进而监测区域40cm土壤含水量提供了实验性的依据;拔节期和灌浆期,用14:00冠气温差来拟合各土壤层的土壤含水量有较高的精度,从而为用区域遥感数据监测区域土壤含水量提供了经验性的模型。     

Damage Evaluation of Agro-meteorological Hazards in the Maize-Growing Region of Songliao Plain,China: Case Study of Lishu County of Jilin Province

Agro-meteorological hazards such as drought, waterlogging and cool summer occur with very high frequency and affect maize production and social-economic development in the maize-growing region of Songliao Plain, China. Moreover, both the frequency of these hazards and loss from them are considered to be increasing with global warming. The purpose of this paper is to quantitatively analyze the relationships between the fluctuation of maize yield and drought, waterlogging and cool summer, and to evaluate the consequences of these hazards in the maize-growing area of Songliao Plain, taking Lishu county as a case study area based on GIS (Geographic Information System). Crop yield-climate analysis and regression analysis were employed to analyze and quantify relationships between the fluctuation of maize yield and drought, waterlogging and cool summer, and to evaluate the consequences of these hazards. The parameters and model of damage evaluation were presented using weighted comprehensive analysis, and the degree of damage of drought, waterlogging and cool summer to maize production was comprehensively evaluated and regionalized. It is shown that from 1949 to 1990, the negative value years of the fluctuation of maize yield due to meteorological hazards accounted for 55% of seasons, of which 14% was caused by drought, 30% by waterlogging, 4% by cool summer and drought, 9% by cool summer and waterlogging, 13% by drought and waterlogging, 30% by drought, waterlogging and cool summer. Studies on the instability and spatial variation of the fluctuations in maize yield in Lishu county showed that the middle plains are stable areas to climatic influence, while southeastern hills and low mountains, the low lands of the plains along the East Liao River and the western plain are unstable areas in terms of areas in maize yield. The synthetic index of the degree of damage to maize of drought, waterlogging and cool summer showed a strong positive correlation with the ratio of the amount damaged to the normal yield of maize. This suggests that this index can be used to evaluate such damage. The degree of damage of drought, waterlogging and cool summer to maize in Lishu county shows the regional characteristics, which increase gradually from the center to the west and east, this being almost identical with the spatial distribution of the fluctuation of maize yield due to these hazards. This study can be expected to provide the basis for developing strategies to mitigate agro-meteorological hazards and reducing the losses from them, and adjust the medium and long-term distribution of agricultural activities so as to adapt to environmental changes.     

2004年陕西春季沙尘天气环流特征分析

应用我们已经建立的《阳泉市短期冰雹预报系统》分析预报阳泉市2004年6月份出现的连续冰雹天气,特别是该系统中的指标叠加方法,效果较好。     

Model identification for hydrological forecasting under uncertainty

Methods for the identification of models for hydrological forecasting have to consider the specific nature of these models and the uncertainties present in the modeling process. Current approaches fail to fully incorporate these two aspects. In this paper we review the nature of hydrological models and the consequences of this nature for the task of model identification. We then continue to discuss the history (“The need for more POWER‘’), the current state (“Learning from other fields”) and the future (“Towards a general framework”) of model identification. The discussion closes with a list of desirable features for an identification framework under uncertainty and open research questions in need of answers before such a framework can be implemented.     

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of Tm3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Likely effects of climate change on groundwater availability in a Mediterranean region of Southeastern Spain

Groundwater resources are typically the main fresh water source in arid and semi‐arid regions. Natural recharge of aquifers is mainly based on precipitation; however, only heavy precipitation events (HPEs) are expected to produce appreciable aquifer recharge in these environments. In this work, we used daily precipitation and monthly water level time series from different locations over a Mediterranean region of Southeastern Spain to identify the critical threshold value to define HPEs that lead to appreciable aquifer recharge in this region. Wavelet and trend analyses were used to study the changes in the temporal distribution of the chosen HPEs (≥20 mm day^?1) over the observed period 1953–2012 and its projected evolution by using 18 downscaled climate projections over the projected period 2040–2099. The used precipitation time series were grouped in 10 clusters according to similarities between them assessed by using Pearson correlations. Results showed that the critical HPE threshold for the study area is 20 mm day^?1. Wavelet analysis showed that observed significant seasonal and annual peaks in global wavelet spectrum in the first sub‐period (1953–1982) are no longer significant in the second sub‐period (1983–2012) in the major part of the ten clusters. This change is because of the reduction of the mean HPEs number, which showed a negative trend over the observed period in nine clusters and was significant in five of them. However, the mean size of HPEs showed a positive trend in six clusters. A similar tendency of change is expected over the projected period. The expected reduction of the mean HPEs number is two times higher under the high climate scenario (RCP8.5) than under the moderate scenario (RCP4.5). The mean size of these events is expected to increase under the two scenarios. The groundwater availability will be affected by the reduction of HPE number which will increase the length of no aquifer recharge periods (NARP) accentuating the groundwater drought in the region. Copyright © 2016 John Wiley & Sons, Ltd.     

A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.