Spatial and temporal pattern of precipitation and drought in Gansu Province, Northwest China

Drought is one of the most harmful natural hazards in Gansu Province in Northwest China. The changes of precipitation affect the severity of drought. In order to recognize the trend of precipitation and understand the effect of rainfall change on water resources management and drought severity, Mann–Kendall test was used. Standardized Precipitation Index (SPI) was calculated to reconstruct the drought at different time scales and analyze the frequency of drought occurrence in the recent 50 years. The results show that the SPI is applicable in Gansu Province. The number of severe droughts differs among regions: it is more obvious as a 3-month drought in the Yellow River Basin and the Yangtze River Basin than in the Inland River Basin, and other droughts at 6-, 9-, and 12-month time scales have the same effect in the three regions. Mann–Kendall test results show that there is an upward trend in the summer periods and a downward trend in the autumn-winter-spring intervals ranging from 10.5 mm/10 years to −37.4 mm/10 years, which affect the local water resources management, droughts mitigation, and agriculture decision making. This situation poses challenges for future study.     

50a来洮河流域降水径流变化趋势分析

洮河流域 40多年水文实测资料分析表明 ,由于受气候变化及人类活动影响 ,流域降水和径流特征发生了明显变化 ,降水与径流总体呈下降趋势 ,其下降的线性斜率分别为 - 0 .86～ - 1.34mm·a-1和 - 1.5 7～ - 3.36m3·s-1·a-1;而气温呈缓慢上升趋势 ,其上升的线性斜率为 0 0 2℃·a-1.降水的减少和温度的升高已经导致甘南草原荒漠化 ,使许多湿地和湖泊干涸 ;径流的减少和温度增加在近2 0a来有进一步加剧的趋势 .     

兰州雨量谱的气候变化与极端化趋势

利用兰州站1951-2005年逐日降水观测资料,进行雨量划分级别,分析了55 a来兰州分级降水雨量谱和极端降水的气候变化和发展趋势.研究表明:兰州年降水量逐年波动下降,长期变化趋势为每10 a下降9.0 mm,近20 a达到每10 a下降22.6 mm;年降水日数的长期变化趋势为每10 a下降3.6 d,近20 a为每10 a下降3.7 d.主要是由于小、中雨级的降水减少明显造成.兰州近20 a大雨以上级别的极端降水量增多,变化趋势为每10 a增加9.9 mm,年降水日数的变化趋势为每10 a增加0.4d.兰州年降水强度的长期变化趋势为每10 a上升0.1 mm·d1,其中小雨、中雨级别的贡献并不明显,主要的增加贡献是由大雨以上级别的降水强度增加所导敢的.极端降水的强度在近20 a的变化趋势为每10 a增加5.7 mm·d-1.兰州近20 a的年降水量中极端降水量占的比例由15.9%上升至1 6.2%;极端降水日数增加,其比例从1.8%上升至2.0%,在2000年极端降水所占的比例更是达到雨量的25.4%和雨日的4.0%水半,呈现出向极端降水增强的发展趋势.     

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.     

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.     

震前云下增温异常及其时段特征

利用卫星热红外图像资料做地震短临预报, 主要依据的是地表大气增温异常在卫星图像上的亮温反映。 但在阴云密布的天气条件下, 这种预报方法却受到了限制, 因为卫星无法探测到地面或水面是否有增温异常。 通过气象资料分析, 得知云层或其他气象条件引起的降温并不能改变震前地表温度增加的趋势。 某些地震之前虽然震中及其附近地区天空阴云密布, 地面增温幅度却可高达十几度。 云下增温曲线可划分为3个时段(即A、 B、 C段), 其中A段与C段分别为增温前与震后的温度变化曲线, 多与日照时间呈正相关关系, 特别是A段的这种关系更具普遍性。 然而, 反映震前地面增温特征的B段却与日照时间没有明显的相关性, 可见这种持续增温、 与云量无关的波状增温等都主要不是由日照或气象条件引起的, 而是一种与地下应力作用、 气体释放、 瞬变电场等有关的震兆现象。 因此, 提高对云下增温的系统观测能力, 是改善热红外地震预报的有效途径。