1543—2001年北疆区域年降水量变化特征分析

征,同时200 a左右的周期变化特征也较为明显,且不同历史时期的周期变化特征存在明显差异.突变检验表明,均值突变尺度在50～100 a尺度上更为明显,公元1613-1643年,1731-1792年的突变表现为年降水量的增加,而公元1669-1712年的突变则表现为年降水量的减少;方差突变则以18世纪80年代最为明显.     

The extent of desertification on Saudi Arabia

Desertification is the process that turns productive deserts into non-productive deserts as a result of poor land-management. Desertification reduces the ability of land to support life, affecting wild species, domestic animals, agricultural crops and humans. The reduction in plant cover that accompanies desertification leads to accelerated soil erosion by wind and water. South Africa is losing approximately 300–400 million tons of topsoil every year. As vegetation cover and soil layer are reduced, rain fall impact and run-off increases. This paper discusses the extent of desertification, its potential threat to sustained irrigated agriculture and possible measures adopted to control ongoing desertification processes to minimize the loss of agricultural productivity in an arid country such as the Kingdom of Saudi Arabia.     

Bayesian foreground analysis with CMB data

The quality of CMB observations has improved dramatically in the last few years, and will continue to do so in the coming decade. Over a wide range of angular scales, the uncertainty due to instrumental noise is now small compared to the cosmic variance. One may claim with some justification that we have entered the era of precision CMB cosmology. However, some caution is still warranted: The errors due to residual foreground contamination in the CMB power spectrum and cosmological parameters remain largely unquantified, and the effect of these errors on important cosmological parameters such as the optical depth τ and spectral index n_s is not obvious. A major goal for current CMB analysis efforts must therefore be to develop methods that allow us to propagate such uncertainties from the raw data through to the final products. Here we review a recently proposed method that may be a first step towards that goal.     

基于同步风场的机载SAR海浪参数反演方法

针对机载合成孔径雷达(SAR)对海探测特点,采用多入射角法从SAR数据本身得到与海浪参数反演区域时空匹配的同步海面风速和风向,并结合线性变换关系,计算得到海浪初猜谱对应的仿真SAR图像谱,将仿真SAR图像谱和观测SAR图像谱输入代价函数中进行迭代运算,通过非线性方程的解算得到最适海浪谱;采用交叉谱法去除海浪传播180°方向模糊,最终得到海浪参数。论文提出的基于同步风场的机载SAR海浪参数反演方法,充分利用了机载SAR海洋环境探测的优势,解决了传统SAR海浪参数反演中初猜谱构造依赖外部风场的问题,机载同步飞行试验的海浪参数反演结果与浮标观测值的有效波高、波向的均方根误差分别为0.23 m和13.23°,验证了该方法的有效性,可为机载SAR海浪参数反演业务化提供支持。     

Ghost fishing in European waters: Impacts and management responses

In this paper we review levels of net loss, what happens to the gear once it has been lost, and the resulting levels of ‘ghost catches’ made in passive net fisheries in the EU. We also consider ghost catches resulting from lost gear in other types of fisheries, and the extent to which the value of ghost catches has been quantified. We consider why fishing gear is lost, and profile common management responses. We present a cost benefit model to assess the relative cost effectiveness of different management measures, and suggest that gear retrieval programmes may provide less value for money than other management responses.     

A multiscaling‐based intensity–duration–frequency model for extreme precipitation

Rainfall intensity–duration–frequency (IDF) curves are a standard tool in urban water resources engineering and management. They express how return levels of extreme rainfall intensity vary with duration. The simple scaling property of extreme rainfall intensity, with respect to duration, determines the form of IDF relationships. It is supposed that the annual maximum intensity follows the generalized extreme value (GEV) distribution. As well known, for simple scaling processes, the location parameter and scale parameter of the GEV distribution obey a power law with the same exponent. Although, the simple scaling hypothesis is commonly used as a suitable working assumption, the multiscaling approach provides a more general framework. We present a new IDF relationship that has been formulated on the basis of the multiscaling property. It turns out that the GEV parameters (location and scale) have a different scaling exponent. Next, we apply a Bayesian framework to estimate the multiscaling GEV model and to choose the most appropriate model. It is shown that the model performance increases when using the multiscaling approach. The new model for IDF curves reproduces the data very well and has a reasonable degree of complexity without overfitting on the data.     

Mapping of climatic parameters under climate change impacts in Iran

ABSTRACT

This research aims to provide a comprehensive evaluation of climate change effects on temperature, precipitation and potential evapotranspiration over the country of Iran for the time periods 2010–2039, 2040–2069 and 2070–2099, and under scenarios A2 and B2. After preparation of measured temperature and precipitation data and calculation of potential evapotranspiration for the base time period of 1960–1990 for 46 meteorological stations (with a nationwide distribution), initial zoning of these three parameters over the country was attempted. Maximum and minimum temperatures and values of precipitation were obtained from the HadCM3 model under scenarios A2 and B2 for the three time periods, and these data were downscaled. Corresponding maps were prepared for the three parameters in the three time periods, and spatial and temporal variations of these climatic parameters under scenarios A2 and B2 were extracted and interpreted. Results showed that the highest increase in temperature would occur in western parts of the country, but the highest increase of potential evapotranspiration would occur in the central region of Iran. However, precipitation would vary temporally and spatially in different parts of the country depending on the scenario used and the time period selected.

Editor Z. W. Kundzewicz; Associate editor not assigned     

An approach for the determination of precipitation input for worst-case flood modelling

ABSTRACT

There is a lack of suitable methods for creating precipitation scenarios that can be used to realistically estimate peak discharges with very low probabilities. On the one hand, existing methods are methodically questionable when it comes to physical system boundaries. On the other hand, the spatio-temporal representativeness of precipitation patterns as system input is limited. In response, this paper proposes a method of deriving spatio-temporal precipitation patterns and presents a step towards making methodically correct estimations of infrequent floods by using a worst-case approach. A Monte Carlo approach allows for the generation of a wide range of different spatio-temporal distributions of an extreme precipitation event that can be tested with a rainfall–runoff model that generates a hydrograph for each of these distributions. Out of these numerous hydrographs and their corresponding peak discharges, the physically plausible spatio-temporal distributions that lead to the highest peak discharges are identified and can eventually be used for further investigations.

Editor A. Castellarin; Associate editor E. Volpi     

Historical trends in Florida temperature and precipitation

Because of its low topographic relief, unique hydrology, and the large interannual variability of precipitation, Florida is especially vulnerable to climate change. In this paper, we investigate a comprehensive collection of climate metrics to study historical trends in both averages and extremes of precipitation and temperature in the state. The data investigated consist of long‐term records (1892–2008) of precipitation and raw (unadjusted) temperature at 32 stations distributed throughout the state. To evaluate trends in climate metrics, we use an iterative pre‐whitening method, which aims to separate positive autocorrelation from trend present in time series. Results show a general decrease in wet season precipitation, most evident for the month of May and possibly tied to a delayed onset of the wet season. In contrast, there seems to be an increase in the number of wet days during the dry season, especially during November through January. We found that the number of dog days (above 26.7 °C) during the year and during the wet season has increased at many locations. For the post‐1950 period, a widespread decrease in the daily temperature range (DTR) is observed mainly because of increased daily minimum temperature (Tmin). Although we did not attempt to formally attribute these trends to natural versus anthropogenic causes, we find that the urban heat island effect is at least partially responsible for the increase in Tmin and its corresponding decrease in DTR at urbanized stations compared with nearby rural stations. In the future, a formal trend attribution study should be conducted for the region. Copyright © 2012 John Wiley & Sons, Ltd.