1961～2015年雅鲁藏布江流域风蚀气候侵蚀力变化

根据雅鲁藏布江流域13个气象站观测资料,利用联合国粮农组织给出的公式计算雅鲁藏布江流域风蚀气候因子指数值,分析雅江风蚀气候侵蚀力基本特征。结果表明,雅江流域风蚀气候因子指数分布范围为4.2~31.9,平均值为14.7。从空间分布来看,风蚀气候因子指数由西向东呈减小趋势,西部可达40,东部加查-米林段降到了5左右。风蚀气候因子指数具有显著的季节变化,春季最大为8.5,冬季次之为5.2,夏季、秋季都很小。雅江流域风蚀气候因子指数年、春季、秋季、冬季下降趋势显著,夏季上升趋势不显著。通过Mann-Kendall（M-K）检验分析可知,风蚀气候因子指数在1987年发生突变。     

西北干旱荒漠区风蚀气候侵蚀力时空变化特征（英文）

土壤风蚀是制约西北干旱荒漠地区社会活动与经济发展的重要因素。为揭示西北干旱荒漠区土壤风蚀气候侵蚀力分布,通过中国区域地面长时间序列气象要素驱动数据,并结合Arc GIS软件分析,评估了该区风蚀气候侵蚀力时空变化与转移特征。研究结果显示：（1）西北干旱荒漠区在降水量、风速以及多年平均温度等气象因素均表现为随年代际递增的背景下,风蚀气候侵蚀力呈现出整体降低,大部分区域C值介于0-100,但在腹地及少数部分区域为增长趋势,C值高于150;(2)月际C值变化差异明显,春夏季最大、其次为冬季,最小为秋季;突变性检验发现风蚀气候侵蚀力在春季变异最强,有4个突变点,且长期处于波动式下降;（3）区域土壤风蚀程度由腹地向四周逐渐减小,且高侵蚀影响面积逐年递增;（4）风蚀气候侵蚀力时空转移变化特征表现为整体为小幅度衰减,但部分地区却表现为增加甚至明显增加趋势。研究成果可为西北干旱荒漠区风沙灾害防治提供相应的理论依据和科技支撑。     

风蚀气候侵蚀力研究进展

风蚀气候侵蚀力是土壤风蚀方程中的气候因子,计算模型经多次修正后已基本发展成熟,广泛应用于干旱半干旱地区风蚀气候条件评估与响应机理分析及其与风沙地貌、风沙灾害的相关性研究等方面,其中风蚀气候侵蚀力对区域气候变化的响应研究是当下的热点问题。目前,风蚀气候侵蚀力研究仍存在计算模型不完善、研究区域发展不平衡、气候变化响应分析不全面、风沙地貌及风沙灾害相关性争议较多等问题。未来应进一步从构建区域校准性计算模型、计算并分析沿海地区风蚀气候侵蚀力、综合分析风蚀气候侵蚀力对气候变化的响应、建立风沙地貌及风沙灾害相关的综合性风蚀气候评价指标等方面开展风蚀气候侵蚀力的研究。     

1980—2016年中国北方风蚀气候侵蚀力的变化

随着修订风蚀方程（RWEQ）的提出,采用增加了冻结因子的气候因子（WF）表达风蚀气候侵蚀力更具有科学性和必要性。基于中国北方风蚀区157个气象站1980—2016年的观测数据,逐月计算了各站点气候因子,并探讨了气候因子时空分布变化特征及影响因素。结果表明：(1)1980—1997年,年气候因子值表现为快速下降,从940.46kg/m下降到273.03 kg/m;而1998—2016年,年气候因子值表现相对稳定,在139.81～398.85 kg/m范围内波动。(2)春季气候因子值约占全年63%,其变化也显著高于其它季节,这也是土壤风蚀发生在春季的主要原因。(3)气候因子的高值区分布在新疆东部、青海西部、40°N以北的内蒙古中西部,这与气压中心和高大山体地形分布有关。     

1960-2017年阿拉善高原风蚀气候侵蚀力时空演变

根据阿拉善高原8个气象站观测资料,利用联合国粮农组织公式计算风蚀气候因子指数值（C值）,分析气候侵蚀力时空演变特征。结果表明：① 阿拉善高原C值为15.0~160.0,平均为67.7。② 从空间分布来看,C值由拐子湖分别向东南、西南减小;拐子湖站高达156.1,而阿拉善高原东南部的腾格里沙漠南缘C值为20~30;西南部合黎山一带C值下降至30~35。③ 季节变化明显,春季最大,夏季次之,秋季最小;春季和夏季的C值之和约占全年的62.6%。Mann-Kendall（M-K）检验分析表明,风蚀气候侵蚀力在1990年发生突变。拐子湖站年C值增加趋势显著,其余各站年C值均显著下降。风速是阿拉善高原风蚀气候侵蚀力的决定性气象因子。     

塔里木盆地风蚀气候侵蚀力的计算与分析

利用塔里木盆地周边及腹地13个气象站1961～2007年的观测资料,选择联合国粮农组织给出的风蚀气候因子指数计算公式,计算了塔里木盆地风蚀气候因子指数值,以此阐述了风蚀气候侵蚀力的基本特征。结果表明,多年平均风蚀气候因子指数C值的分布范围为6.3～39.6,整个盆地的平均值为17.5;从空间分布来看,C值由盆地西部向东部呈增大趋势,最大值出现在盆地东南缘的若羌;风蚀气候因子指数具有显著的季节变化,春季最大,夏季次之,秋季再次之,冬季最小;近50 a来,风蚀气候因子指数总体上呈减小趋势,说明风蚀气候侵蚀力在降低;风蚀气候侵蚀力主要受风速的作用,与降水的关系不显著。     

1960—2019年中国沿海地区风蚀气候侵蚀力的变化及其影响因素分析

基于中国主要沿海地区64个气象站点1960—2019年的观测数据,采用风蚀气候侵蚀力计算的FAO公式及Mann-Kendall检验模型、Morlet小波变换等方法,对中国沿海地区的风蚀气候侵蚀力及其变化进行了测算和分析。结果表明：(1)沿海地区年际风蚀气候侵蚀力介于0.34～197.32,平均值为38.78,与内陆干旱半干旱地区相近,其季节差异表现为冬季（14.13）>秋季（11.74）>春季（9.99）>夏季（2.57）;(2) 1960—2019年沿海地区年际、季节风蚀气候侵蚀力明显下降但不存在突变点,年际变化的第1主周期为12 a,季节变化主周期则分别为春季和冬季5 a、夏季与秋季26 a;(3)起沙风日数是中国沿海地区风蚀气候侵蚀力变化的主控正向因素,厄尔尼诺-南方涛动则通过影响降水量而间接负向驱动其变化,干旱和降水主要在风速减弱的冬季对风蚀气候侵蚀力产生较弱的负向影响。     

1961-2013年青藏高原雪雨比变化（英文）

On the basis of two gridded datasets of daily precipitation and temperature with a spatial resolution of 0.5°×0.5°, and meteorological station data released by the National Meteorological Information Center(NMIC) during 1961–2013, the spatial and temporal variations of total amount of precipitation, amount of rainfall, amount of snowfall and snowfall/rainfall ratio(S/R) in the Tibetan Plateau(TP) are analyzed using Sen's slope, the Mann–Kendall mutation test, Inverse Distance Weighting(IDW) and the Morlet wavelet. Total amount of precipitation and amount of rainfall generally show statistically significant increasing trends of 0.6 mm·a~(–1) and 1.3 mm·a~(–1), respectively, while amount of snowfall and S/R have significant decreasing trends of –0.6 mm·a~(–1) and –0.5% a~(–1), respectively. In most regions, due to significant increasing trends in total amount of precipitation and amount of rainfall, and significant decreasing trends in amount of snowfall, S/R shows a decreasing trend in the TP. Abrupt changes in total amount of precipitation, amount of rainfall, amount of snowfall and S/R are detected for 2005, 2004, 1996 and 1998, respectively. Total amount of precipitation, amount of rainfall, amount of snowfall and S/R are concentrated in cycles of approximately 5 years, 10 years, 16 years and 20 years, respectively. The trend magnitudes for total amount of precipitation and amount of rainfall all show decreasing-to-increasing trends with elevation, while amount of snowfall and S/R show decreasing trends.     

1961-2014年中国高温事件频率和强度的时空变化（英文）

In this study, we explored spatial patterns and the temporal trends in high-temperature events(HTEs) for the mainland of China during 1961–2014 based on a daily-maximum surface-air-temperature dataset of 494 stations and nonparametric trend detection methods. With three thresholds of 35°C(HTE35), 37°C(HTE37), and 40°C(HTE40), HTEs occurred in 82%, 71%, and 37% of the surveyed stations and showed an overall increasing trend in both frequency and intensity during 1961–2014. In northern and southeastern China, HTEs showed a significant increasing trend in both frequency and intensity, whilst a decreasing trend for both was observed in central China. Despite such regional heterogeneity, HTEs overwhelmingly presented three-phase characteristics in all three representative regions and throughout China; the phases are 1961–1980, 1980–1990, and 1990–2014. Both frequency and intensity of HTEs have strongly increased during 1990–2014 at 54.86%, 48.38%, and 23.28% of the investigated stations for HTE35, HTE37 and HTE40, respectively. These findings implied that HTEs adaptation should be paid further attention in the future over China because the wide spread distribution of HTEs and their increasing trends in both frequency and intensity during recent decades might pose challenges to the sustainability of human society and the ecosystem.     

1961-2005年中国霾日气候特征及变化分析

利用1961-2005 年中国霾日统计资料, 对中国霾的时空气候分布特征、变化趋势进行了详细分析, 并探讨了霾变化的可能原因及其与太阳总辐射、日照时数变化的关系。结果表明: 近45 年来, 中国年和四季霾日的空间分布特征均呈现东多西少的空间分布态势, 东部地区集中在三个多发区, 分别为长江中下游、华北和华南; 季节变化, 除东北地区、青藏高原、西北西部四季霾日均很少且变化不明显外, 其余大部分地区均呈现为冬季多, 夏季少, 春秋 季居中的特点。近45 年, 全国平均年霾日数呈现明显的增加趋势, 2004 年为最高值。我国东部大部地区主要呈现增加趋势, 尤其霾多发地区, 如长江中下游、珠江流域及河南西部等 地, 霾日增加幅度大, 趋势显著, 人类活动造成的大气污染物增加及天气气候变化是这些地区霾日呈现增加趋势的可能原因, 我国西部地区和东北大部地区则以减少趋势为主。华北、长江中下游地区、华南地区霾日变化趋势与日照时数变化趋势相反, 霾的增加是造成太阳总 辐射减少的主要原因之一。东北地区、西北地区、西南地区、青藏高原霾日变化和日照时数变化均呈现不明显的减少趋势, 但由于这些地区霾日发生少, 其变化不会对日照时数和太阳总辐射变化造成很大的影响。     

1961-2015年中国极端干旱时间演变特征（英文）

Understanding the past variations in extreme drought is especially beneficial to the improvement of drought resistance planning and drought risk management in China. Based on the monitoring data of meteorological stations from 1961 to 2015 and a meteorological drought index, the Standardized Precipitation Evapotranspiration Index(SPEI), the spatio-temporal variations in extreme drought at inter-decadal, inter-annual and seasonal scales in China were analyzed. The results revealed that 12 months cumulative precipitation with 1/2 to 5/8 of average annual precipitation will trigger extreme drought. From the period 1961–1987 to the period 1988–2015, the mean annual frequency of extreme drought(FED) increased along a strip extending from southwest China(SWC) to the western part of northeast China(NEC). The increased FED showed the highest value in spring, followed by winter, autumn and summer. There was a continuous increase in the decadal-FED from the 1990 s to the 2010 s on the Tibetan Plateau(TP), the southeast China(SEC) and the SW. During the period 1961–2015, the number of continuous drought stations was almost the same among 4 to 6 months and among 10 to 12 months of continuous drought, respectively. It can be inferred that drought lasting 6 or 12 months may lead to more severe drought disasters due to longer duration. The range of the longest continuous drought occurred in the 21 st century had widely increased compared with that in the 1980 s and the 1990 s. Our findings may be helpful for water resources management and reducing the risk of drought disasters in China.     

考虑季节变化的降雨侵蚀力计算方法（英文）

Rainfall erosivity is an important climatic factor for predicting soil loss.Through the application of high-resolution pluviograph data at 5 stations in Huangshan City,Anhui Province,China,we analyzed the performance of a modified Richardson model that incorporated the seasonal variations in parameters α and β.The results showed that(1) moderate to high seasonality was presented in the distribution of erosive rainfall,and the seasonality of rainfall erosivity was even stronger;(2) seasonal variations were demonstrated in both parameters α and β of the Richardson model;and(3) incorporating and coordinating the seasonality of parameters α and β greatly improved the predictions at the monthly scale.This newly modified model is therefore highly recommended when monthly rainfall erosivity is required,such as,in planning soil and water conservation practices and calculating the cover-management factor in the Universal Soil Loss Equation(USLE) and Revised Universal Soil Loss Equation(RUSLE).     

甘肃敦煌雅丹地质公园区风蚀气候侵蚀力特征

风蚀气候侵蚀力是潜在风力侵蚀强度的重要表征。基于2013年和2014年风速、降水和空气温度、湿度等气象要素的实地观测数据,对甘肃敦煌雅丹地质公园区的风蚀气候因子指数进行了逐月的计算和分析。结果表明：（1）研究区风蚀气候因子指数为151.98±0.13,是全国的三大极大值区之一;（2）研究区风蚀气候因子指数不同于全国干旱半干旱区基本季节变化特征,夏季最大,春夏季明显高于秋冬季,与新疆和田地区的季节变化特征相似;（3）研究区风蚀气候因子指数具有4—8月持续高值、9月至翌年3月持续低值的月变化特征;（4）风蚀气候因子指数的决定性气象因子是风速,而降水的减弱作用甚微;（5）一般来说,雅丹地貌分布区风蚀气候因子指数≥150。     

福建沿海地区风蚀气候侵蚀力的计算与分析

一、引言福建沿海地区在东亚季风环流背景条件下，受台湾海峡的狭管效应作用，风速强劲，加上沿海地区缺少地形动力抬升条件，故年降水量较少，且季节分配不均。春夏多雨湿润，秋冬少雨干燥。在这一特定的地理环境条件下，这一地区的下垫面多由红土台地和结构松散的风沙地构成，在干旱和大风条件下，易发生风沙危害和农田风蚀现象。风蚀气候侵蚀力是气候条件影响风蚀的可能程度的量度，国际上通常采用风蚀气候因子表示。表征风蚀气候侵蚀力的风蚀气候因子是过去20多年来国内外广泛应用的风蚀方程中五个自变量之一，是土地沙化和农田风蚀评判…     

1961-2012年北疆干旱时空变化

基于北疆38个气象站1961-2012年逐日的气象数据和综合气象干旱指数,探究了北疆干旱的时空演变特征。结果表明：1961-2012年,北疆旱情有所缓解,但干旱仍然频发,且全域性干旱较多,其中夏旱和秋旱较多且覆盖范围较大。干旱频次和干旱覆盖范围呈减少趋势,干旱强度逐渐减弱。四季中,冬季干旱缓解最为明显,其次是春季和夏季,秋季干旱略有缓解。空间上,自东南和东部向西北,旱情逐渐减轻。干旱强度和干旱频次中南部减势最明显,干旱频发会有所改善;东部减势较弱,干旱频发将会持续;西北部减势最弱,旱情仍持续较轻。气候变化下,北疆降水量和潜在蒸散量分别与综合气象干旱指数存在显著的正相关和负相关,北疆降水量的增加趋势和潜在蒸散量的减少趋势对北疆干旱缓解有重要的作用。     

2000–2012年中国北方海岸线时空变化（英文）

This study examined the spatial distribution of the continent coastline in northern China using remote sensing and GIS techniques,and calculated the fractal dimension of the coastline by box-counting method,with a time span from 2000 to 2012.Moreover,we analyzed the characteristics of spatial-temporal changes in the coastline's length and fractal dimension,the relationship between the length change and fractal dimension change,and the driving forces of coastline changes in northern China.During the research period,the coastline of the study area increased by 637.95 km,at a rate of 53.16 km per year.On the regional level,the most significant change in coastline length was observed in Tianjin and Hebei.Temporally,the northern China coastline grew faster after 2008.The most dramatic growth was found between 2010 and 2011,with an increasing rate of 2.49% per year.The fractal dimension of the coastline in northern China was increasing during the research period,and the most dramatic increase occurred in Bohai Rim.There is a strong-positive linear relationship between the historical coastline length and fractal dimension(the correlation coefficient was 0.9962).Through statistical analysis of a large number of local coastline changes,it can be found that the increase(or decrease) of local coastline length will,in most cases,lead to the increase(or decrease) of the whole coastline fractal dimension.Civil-coastal engineering construction was the most important factor driving the coastline change in northern China.Port construction,fisheries facilities and salt factories were the top three construction activities.Compared to human activities,the influence of natural processes such as estuarine deposit and erosion were relatively small.     

基于格点数据的1961-2012年祁连山山区面雨量特征分析（英文）

Based on a 0.5°×0.5° daily gridded precipitation dataset and observations in meteorological stations released by the National Meteorological Information Center,the interannual variation of areal precipitation in the Qilian Mountains during 1961–2012 is investigated using principal component analysis(PCA) and regression analysis,and the relationship between areal precipitation and drought accumulation intensity is also analyzed.The results indicate that the spatial distribution of precipitation in the Qilian Mountains can be well reflected by the gridded dataset.The gridded data-based precipitation in mountainous region is generally larger than that in plain region,and the eastern section of the mountain range usually has more precipitation than the western section.The annual mean areal precipitation in the Qilian Mountains is 724.9×108 m3,and the seasonal means in spring,summer,autumn and winter are 118.9×108 m3,469.4×108 m3,122.5×108 m3 and 14.1×108 m3,respectively.Summer is a season with the largest areal precipitation among the four seasons,and the proportion in summer is approximately 64.76%.The areal precipitation in summer,autumn and winter shows increasing trends,but a decreasing trend is seen in spring.Among the four seasons,summer have the largest trend magnitude of 1.7×108 m3?a–1.The correlation between areal precipitation in the mountainous region and dry-wet conditions in the mountains and the surroundings can be well exhibited.There is a negative correlation between drought accumulation intensity and the larger areal precipitation is consistent with the weaker drought intensity for this region.     

华北平原2002年和2012年农业土地利用变化（英文）

Based on the MODIS NDVI data and Landsat TM/ETM data of 2002 and 2012, this paper extracts the planting area of winter wheat–summer maize, single spring maize, cotton and forest/fruit trees, vegetable and paddy, and made the agricultural land use map of the North China Plain(NCP). Agricultural land use area accounted for 63.32% compared to the total area of the NCP in 2002. And it increased to 65.66% in 2012, which mainly caused by the vegetables and forest/fruit trees increasing. Planting areas of winter wheat–summer maize, cotton, single spring maize, forest/fruit trees, vegetables and paddy were 5031.21×10~3, 865.90×10~3, 1226.10×10~3, 1271.17×10~3, 648.02×10~3, 216.51×10~3 ha in 2012. Rank of changes was: vegetables(+45%) forest/fruit trees(+27.4%) paddy(–23.7%) cotton(–20.4%) single spring maize(+17.3%) winter wheat–summer maize(–0.6%). In developed region like Beijing and Tianjin, planting area of crops with high economic benefit(such as fruit trees and vegetables) increased significantly. Government policies for groundwater protection caused obvious decline of winter wheat cultivation in Hebei Province. Cotton planting in Shandong Province decreased more than 200,000 ha during 2002–2012. The data products will be published in the website: http://hydro.sjziam.ac.cn/Default.aspx. To clarify the agricultural land use in the NCP will be very helpful for the regional agricultural water consumption research, which is the serious problem in the NCP.     

1961—2015年雅鲁藏布江流域降雨侵蚀力

降雨是土壤侵蚀的主要动力,也是风水蚀复合区沙漠化的主要驱动力。研究降雨侵蚀力时空变化对雅鲁藏布江流域土壤侵蚀的监测、评估、预报和治理具有重要意义。利用1961—2015年雅鲁藏布江流域8个气象站日降雨量气象资料,采用趋势系数、气候倾向率、MK检验等研究方法对雅鲁藏布江流域降雨侵蚀力时空变化进行分析。结果表明:雅鲁藏布江流域年降雨侵蚀力平均值为758.1 MJ·mm·hm^-2·h^-1,变差系数Cv值为0.29,趋势系数r值为0.3140。空间分布呈现由东向西逐渐递减的特点,东部可达2 000 MJ·mm·hm^-2·h^-1以上,最西部仅为200MJ·mm·hm^-2·h^-1。雅鲁藏布江流域年降雨侵蚀力总体呈波动上升趋势,其中嘉黎和波密站年降雨侵蚀力上升趋势明显,日喀则、泽当站年降雨侵蚀力呈下降趋势。通过MK检验及滑动T检验得知,流域内年降雨侵蚀力在1982年发生突变,年侵蚀性降雨突变不显著。雅鲁藏布江流域年降雨侵蚀力与侵蚀性降雨相关性显著。     

1951–2010年中国农业水热气候条件的时空变化（英文）

Based on the daily observation data of 824 meteorological stations during 1951-2010 released by the National Meteorological Information Center, this paper evaluated the changes in the heat and moisture conditions of crop growth. An average value of ten years was used to analyze the spatio-temporal variation in the agricultural hydrothermal conditions within a 1 km2 grid. Next, the inter-annual changing trend was simulated by regression analysis of the agricultural hydrothermal conditions. The results showed that the contour lines for temperature and accumulated temperatures(the daily mean temperature ≥0°C) increased significantly in most parts of China, and that the temperature contour lines had all moved northwards over the past 60 years. At the same time, the annual precipitation showed a decreasing trend, though more than half of the meteorological stations did not pass the significance test. However, the mean temperatures in the hottest month and the coldest month exhibited a decreasing trend from 1951 to 2010. In addition, the 0°C contour line gradually moved from the Qinling Mountains and Huaihe River Basin to the Yellow River Basin. All these changes would have a significant impact on the distribution of crops and farming systems. Although the mechanisms influencing the interactive temperature and precipitation changes on crops were complex and hard to distinguish, the fact remained that these changes would directly cause corresponding changes in crop characteristics.