一种基于频率的GCM日降水偏差校正方法改进及其在长江流域的应用

对全球气候模式(GCM)数据进行偏差校正是气候影响评估的前提和基础.通过在等比分布映射(ERCDFm)校正法中引入对降水频率的校正,增补了降水日数偏少情况下的小雨日数,保留了降水频率的长期变化信号,提高降水日数及总降水量的模拟效果.以长江流域1961-2005年的格点化日降水资料作为观测数据,对5个GCM模式历史期以及...     

Evaluation of remote sensing‐based evapotranspiration estimates using a water transfer numerical simulation under different vegetation conditions in an arid area

Daily actual evapotranspiration (AET) and seasonal AET values are of great practical importance in the management of regional water resources and hydrological modelling. Remotely sensed AET models and Landsat satellite images have been used widely in producing AET estimates at the field scale. However, the lack of validation at a high spatial frequency under different soil water conditions and vegetation coverages limits their operational applications. To assess the accuracies of remote sensing‐based AET in an oasis‐desert region, a total of 59 local‐scale daily AET time series, simulated using HYDRUS‐1D calibrated with soil moisture profiles, were used as ground truth values. Of 59 sampling sites, 31 sites were located in the oasis subarea and 28 sites were located in the desert subarea. Additionally, the locally validated mapping evapotranspiration at high resolution with internalized calibration surface energy balance model was employed to estimate instantaneous AET values in the area containing all 59 of the sampling sites using seven Landsat subimages acquired from June 5 to August 24 in 2011. Daily AET was obtained using extrapolation and interpolation methods with the instantaneous AET maps. Compared against HYDRUS‐1D, the remote sensing‐based method produced reasonably similar daily AET values for the oasis sites, while no correlation was observed for daily AET estimated using these two methods for the desert sites. Nevertheless, a reasonable monthly AET could be estimated. The correlation analysis between HYDRUS‐1D‐simulated and remote sensing‐estimated monthly AET values showed relative root‐mean‐square error values of 15.1%, 12.1%, and 12.3% for June, July, and August, respectively. The root mean square error of the summer AET was 10.0%. Overall, remotely sensed models can provide reasonable monthly and seasonal AET estimates based on periodic snapshots from Landsat images in this arid oasis‐desert region.     

Estimating daily inflows of large lakes using a water‐balance‐based runoff coefficient scaling approach

Daily river inflow time series are highly valuable for water resources and water environment management of large lakes. However, the availability of continuous inflow data for large lakes is still relatively limited, especially for large lakes situated within humid plain regions with tens or even hundreds of tributaries. In this study, we choose the fifth largest freshwater Lake Chaohu in China as our study area to introduce a new approach to reconstruct historical daily inflows at ungauged subcatchments of large lakes. This approach makes use of water level, lake surface rainfall, evaporation from the lake, and catchment rainfall observations. Rainfall–runoff relationship at a reference catchment was analysed to select rainfall input and estimate run‐off coefficient firstly, and the run‐off coefficient was then transferred to ungauged subcatchments to initially estimate daily inflows. Run‐off coefficient was scaled to adjust daily inflows at ungauged subcatchments according to water balance of the lake. This approach was evaluated using sparsely measured inflows at eight subcatchments of Lake Chaohu and compared with the commonly used drainage area ratio method. Results suggest that the inflow time series reconstructed from this approach consistent well to corresponding observations, with mean R² and Nash–Sutcliffe efficiency values of 0.69 and 0.6, respectively. This approach outperforms drainage area ratio method in terms of mean R² and Nash–Sutcliffe efficiency values. Accuracy of this approach holds well when the number of water‐level station being used decreased from four to one.     

不同权重的前期和始发日降雨量与泥石流产沙规模的分析——特大型泥石流灾害发生的思考

通过对特大型泥石流灾害发生的思考,详细分析了蒋家沟1995—1997年43场泥石流暴发的不同权重的前期和始发日降雨量与泥石流产沙规模的关系。分析结果表明：泥石流的产沙规模与不同权重降雨的入渗范围、深度的土体极限应力状态（C、Ф、P,）有关。根据不同权重的前期和始发日降雨量与泥石流产沙规模的关系,可以将泥石流分为：土力型（A）和迳流型（B）两大类型。土力型（A）泥石流有24场占总样本的55．81％,而其产沙量却占样本总产沙量的85％。迳流型（B）泥石流有19场占总样本的44．19％,但该类泥石流的产沙量只占样本总产沙量的15％。     

独山子台跨断层垂直形变观测资料干扰消除研究

结合多参考自适应噪声对消和小波模极大值去噪理论,研究了新疆独山子台跨断层垂直形变观测数据的干扰因素及消除方法,结果表明:利用气象温度数据和断层两盘温差数据作为两个噪声参考输入进行自适应噪声对消,可有效消除信号中的年周期变化;利用小波模极大值去噪方法,可以抑制信号中的高频白噪声成分,使信号畸变更加明显.仿真结果及实际应用均验证了此方法的有效性与实用性,消除干扰后的垂直形变数据与台站100 km范围内4级以上地震有较好的对应性,反映了独山子台对周边地区4级以上地震的映震能力.     

Trends of Temperature Extremes in China and its Relationship with Global temperature anomalies Relationship with Global Temperature Anomalies

Changes of temperature extremes over China were evaluated using daily maximum and minimum temperature data from 591 stations for the period 1961--2002. A set of indices of warm extremes, cold extremes and daily temperature range (DTR) extremes was studied with a focus on trends. The results showed that the frequency of warm extremes (F_WE) increased obviously in most parts of China, and the intensity of warm extremes (I_WE) increased significantly in northern China. The opposite distribution was found in the frequency and intensity of cold extremes. The frequency of high DTR extremes was relatively uniform with that of intensity: an obvious increasing trend was located over western China and the east coast, while significant decreases occurred in central, southeastern and northeastern China; the opposite distribution was found for low DTR extreme days. Seasonal trends illustrated that both F_WE and I_WE showed significant increasing trends, especially over northeastern China and along the Yangtze Valley basin in spring and winter. A correlation technique was used to link extreme temperature anomalies over China with global temperature anomalies. Three key regions were identified, as follows: northeastern China and its coastal areas, the high-latitude regions above 40^oN, and southwestern China and the equatorial eastern Pacific.     

近50年我国霜期的时空分布及变化趋势分析

利用国家气象信息中心最新整编的1954-2003年中国677个站霜的气象观测资料,分析了我国霜期的地理分布特征,揭示了近50年来我国不同地域霜期的变化趋势和年代际变化特征,探讨了气候变暖背景下霜期的响应.研究表明,除极少数地区外,我国霜期呈缩短的趋势,并且霜期显著缩短发生在20世纪90年代以后;近50年全国大部分地区的初霜日期呈推迟趋势而终霜日期呈提前趋势,这可能与日最低气温、日最低0cm地温的不断升高有关,而初霜日期的推迟和终霜日期的提前最终导致霜期的缩短.     

日气温数据缺测的插补方法试验与误差分析

对缺测气象观测记录进行插补是建立连续气象数据集的基础.将孤立1日或数日缺测资料进行插补的线性回归模型法应用于连续缺测数月的逐日最高、最低和平均气温的插补,并进行了一系列改进,包括:(1)用滑动选优法确定邻近参考气象站站数和数据样本时间窗的最佳值;(2)在记录缺测站与邻近参考站之间建立逐日气温的线性回归模型,并选取以最小绝对误差(Least Absolute Deviation,LAD)为目标函数求取模型参数的方法,取代以最小均方根误差为目标函数的最小二乘法(Least Squares Estimate,LAD)求解模型参数的方法,可提高计算效率和参数的稳定性;(3)进一步提出将LAD法与DeGaetano标准化序列法插补结果平均的综合插补方法,以减少极端误差.通过对湖北蔡甸气象站1961-2006年插补试验表明:(1)以4个邻近站和年数为8年、日数为15天时间窗的样本资料建模进行插补误差达到最小;(2)逐日最高、最低和平均气温的平均绝对误差分别为0.32℃、0.45℃、0.28℃,误差在±0.8℃以内的频次分别占总数的94.1%、84.8%、96.1%,观测值与插补值月相关系数在0.886以上.插补与观测资料平均值和相关系数分别通过了显著水平为0.05和0.01的检验.     

Modelling the temporal variation in snow-covered area derived from satellite images for simulating/forecasting of snowmelt runoff in Turkey/Modélisation de la variation temporelle de la surface enneigée à partir d'images satellitaires pour la simulation/prévision de l'écoulement de fonte nivale en Turquie

Abstract

Monitoring the change of snow-covered area (SCA) in a basin is vitally important for optimum operation of water resources, where the main contribution comes from snowmelt. A methodology for obtaining the depletion pattern of SCA, which is based on satellite image observations where mean daily air temperature is used, is applied for the 1997 water year and tested for the 1998 water year. The study is performed at the Upper Euphrates River basin in Turkey (10 216 km²). The major melting period in this basin starts in early April. The cumulated mean daily air temperature (CMAT) is correlated to the depletion of snow-covered area with the start of melting. The analysis revealed that SCA values obtained from NOAA-AVHRR satellite images are exponentially correlated to CMAT for the whole basin in a lumped manner, where R ² values of 0.98 and 0.99 were obtained for the water years 1997 and 1998, respectively. The applied methodology enables the interpolation between the SCA observations and extrapolation. Such a procedure reduces the number of satellite images required for analysis and provides solution for the cloud-obscured images. Based on the image availability, the effect of the number of images on the quality of snowmelt runoff simulations is also discussed. In deriving the depletion curve for SCA, if the number of images is reduced, the timing of image analysis within the snowmelt period is found very important. Analysis of the timing of satellite images indicated that images from the early and middle parts of the melt period are more important.     

Opposing Trends of Winter Cold Extremes over Eastern Eurasia and North America under Recent Arctic Warming

Under recent Arctic warming, boreal winters have witnessed severe cold surges over both Eurasia and North America, bringing about serious social and economic impacts. Here, we investigated the changes in daily surface air temperature (SAT) variability during the rapid Arctic warming period of 1988/89–2015/16, and found the daily SAT variance, mainly contributed by the sub-seasonal component, shows an increasing and decreasing trend over eastern Eurasia and North America, respectively. Increasing cold extremes (defined as days with daily SAT anomalies below 1.5 standard deviations) dominated the increase of the daily SAT variability over eastern Eurasia, while decreasing cold extremes dominated the decrease of the daily SAT variability over North America. The circulation regime of cold extremes over eastern Eurasia (North America) is characterized by an enhanced high-pressure ridge over the Urals (Alaska) and surface Siberian (Canadian) high. The data analyses and model simulations show the recent strengthening of the high-pressure ridge over the Urals was associated with warming of the Barents–Kara seas in the Arctic region, while the high-pressure ridge over Alaska was influenced by the offset effect of Arctic warming over the East Siberian–Chukchi seas and the Pacific decadal oscillation (PDO)–like sea surface temperature (SST) anomalies over the North Pacific. The transition of the PDO-like SST anomalies from a positive to negative phase cancelled the impact of Arctic warming, reduced the occurrence of extreme cold days, and possibly resulted in the decreasing trend of daily SAT variability in North America. The multi-ensemble simulations of climate models confirmed the regional Arctic warming as the driver of the increasing SAT variance over eastern Eurasia and North America and the overwhelming effect of SST forcing on the decreasing SAT variance over North America. Therefore, the regional response of winter cold extremes at midlatitudes to the Arctic warming could be different due to the distinct impact of decadal SST anomalies.