天山巴音布鲁克盆地汛期水资源变化趋势及其影响因素分析

利用1982—2018年巴音布鲁克气象站逐日气象资料和开都河流上游大山口水文站逐月径流量资料，采用Morlet小波分析、气候敏感与水量平衡法，时间序列分析等方法，分析了汛期（5—9月）巴音布鲁克盆地地表径流量变化趋势及气候变化与人工增水作业对径流量的影响。结果表明：近37 a巴音布鲁克盆地汛期地表径流量呈增加趋势，突变年份为1989年，存在主周期依次为14 a、22 a、4 a 、7 a的周期变化，具有17~27 a、11~16 a年代际尺度和4~8 a年际尺度的丰枯位相交替变化特征。降水量是影响径流量变化的主导气候因素，对径流量变化的平均影响率为73.1%。因人工增水因素影响，盆地的降水可分为自然降水和人工催化降水，其中自然降水在历史期（1982—1993年）为69.5%，作业前期（1994—2006年）为59.28%，作业后期（2007—20018年）为74.56%，而人工催化降水在人工增水期（1994—2018年）对径流量变化的平均影响率为7.93%，表明径流量对降水的依赖程度正大幅增加，同时人工增水作业对径流量也有一定增加作用。     

1953—2014年丽水日照时数周期演变规律

利用丽水市1953—2014年逐月日照资料,采用趋势分析方法对年代际、年际和季节日照时数变化趋势进行分析,利用Morlet小波分析和多窗口谱 (Multi Taper Method) 研究日照时数的周期特征,并重建显著周期信号,分析日照时数不同时间尺度显著周期的演变规律。结果表明：丽水日照时数呈极显著下降趋势,每10 a减少35%。夏季日照时数最多,且减少趋势最明显,其次是秋季。Morlet小波和多窗口谱分析结果均显示：年代际尺度准12 a周期最为显著,年际尺度6 a和2～4 a周期也较明显。最显著的准12 a周期信号,其振幅随时间变化具有3个明显的缓变包络。     

用小波分析方法诊断鄂尔多斯市降水周期变化

利用1971—2008年鄂尔多斯市降水资料,使用Morlet小波分析方法分析了多雨区和少雨区降水的年际和年代际变化特征。结果表明:在年际尺度上,多雨区年降水有明显的14a和6a左右的变化周期,多雨区夏季降水有明显的15a和8a左右的变化周期;少雨区年降水有明显的14a和5a左右的变化周期,少雨区夏季降水有明显的12~15a和6a左右的变化周期;年代际变化尺度上,近38a鄂尔多斯市多雨区和少雨区夏季平均降水总量没有明显的变化特征。     

1953—2011年信江流域径流量变化特征及归因分析

利用信江流域梅港水文控制站1953—2011年径流量观测资料和11个气象站同期气象观测资料,采用统计方法、Mann-Kendall非参数检验方法、Morlet小波分析法,对信江流域径流量年内、年际变化的不均匀性、长期趋势、周期变化,及其与气候因素的相关性等进行分析。结果显示,信江流域多年平均径流量呈缓慢增大趋势,但具有显著的年际和年代际变化特征,振荡周期明显,年际变化的主要周期为6—8 a,年代际变化的主要周期为准22 a,在20世纪70—90年代最明显。年流量以主汛期(4—6月)为最多,春、夏季(3—8月)径流变差系数小,水量稳定,冬季变差系数大,水量不稳定。流域径流量与气候因素中的降水、蒸发具有显著的相关性,而人类活动中的城镇化、经济、人口等因素对径流变化起到了一定的辅助作用。     

近50年新疆温度降水配置演变及其尺度特征

用小波多分辨分析方法研究近20年新疆出现的高温多雨型气候的时间尺度特征及其演变趋势。新疆近55年温度和降水的小波功率谱分析显示,二者在年际尺度上都有2—4和6—8 a的显著周期分量,在年代际尺度上有准16 a周期;但它们的时间演变和时间平均谱都存在差异,导致温度和降水配置演变比较复杂,呈现非平稳性。正交小波分解证实,温度和降水年际变化的高频部分具有显著的负相关,除个别几年外几乎都是高温少雨或低温多雨配置;在年际变化的低频部分,即6—8 a尺度部分,高温少雨/低温多雨及高温多雨/低温少雨配置交替出现,55a平均而言二者相关性不显著。在年代际以上尺度,二者的能量主要集中在约50 a以上尺度部分,16—32 a尺度部分方差贡献很小。在降水和温度时间序列中去除趋势后发现,50 a以上尺度部分具有稳定的高温多雨/低温少雨配置。因此,近20年新疆高温多雨型气候的出现主要是二者50—60 a尺度成分的正位相和线性增加趋势部分叠加形成的,其中降水主要是年代际尺度成分的贡献,温度主要是线性增暖趋势即全球变暖的影响结果。     

贵州西部汛期降水特征及环流形势分析

利用贵州西部6个代表测站1961—2007-05-09的逐月降水量资料,对贵州西部汛期降水的时间变化特征进行了诊断分析,采用滑动t-检验法和Yam amoto法对贵州西部汛期降水进行突变检测;用Morlet小波分析了汛期降水的多时间尺度的变化特征。结果表明:近50 a来贵州西部汛期降水呈下降趋势,存在着明显的年际、年代际变化特征;汛期降水在2002年附近发生了突变;在年代际尺度上存在显著的16 a周期振荡,年际尺度上有一个9 a和5 a的周期振荡较为显著。     

滁州市汛期雨量多尺度时间变化特征及其GA-BP模型预测

利用集合经验模态分解EEMD方法分析了滁州地区汛期雨量的多尺度时间变化特征,以国家气候中心的百余项环流指数作为预报因子并利用主成分分析进行预测因子优化,在此基础上建立基于GA-BP神经网络的汛期雨量气候预测模型,研究结果表明:该地区1961—2017年汛期雨量存在准2 a、4 a的年际尺度及准11 a、16 a的年代际尺度周期变化特征,总体趋势在20世纪80年代之前、20世纪80年代—21世纪及21世纪以来3个时段分别对应增多—减少—增多的趋势;基于GA-BP神经网络的两种方案对滁州地区7个站的预测误差分别为122 mm和144 mm,其中利用主成分分析进行因子优化的方案预测效果更好。     

基于SSA-BP神经网络模型的全球入海径流量未来变化趋势

入海径流是水循环的重要环节,探究气候变化背景下全球入海径流量的时空变化特征,可为水资源合理利用提供依据。基于全球376条外流河逐月流量、ERA5-LAND再分析资料和10个全球气候模式,构建基于SSA-BP神经网络的降水径流关系模型,分析全球入海径流量在历史时期(1961—2020年)和未来(2021—2100年)3种情景(SSP1-2.6、SSP3-7.0和SSP5-8.5)下的时空变化特征。研究发现：(1)全球尺度上,1961—2020年,多年平均入海年径流量为37423 km³。2021—2100年,全球入海年径流量在未来3种情景下均呈增加趋势,SSP1-2.6情景下趋势显著。与基准期相比,21世纪末期增幅最大。(2)洲际尺度上,历史时期,非洲入海径流量呈显著减少趋势,北美洲呈显著增加趋势。2021—2100年,亚洲、北美洲在3种情景下呈增加趋势,大洋洲呈减少趋势,其余各大洲情景间差异明显。(3)纬向分布上,历史时期,南北半球低纬度变化趋势不显著;北半球中纬度呈弱减少趋势,南半球中纬度呈显著减少趋势;北半球高纬度呈显著增加趋势。2021—2100年,从低到高...     

1980~2018年龙泉驿区降水的多尺度特征

应用趋势分析、Morlet小波分析以及Mann-Kendall突变检验等方法,研究了1980~2018年龙泉驿区降水整体趋势,包括降水的年际变化和季节性趋势,以及降水日数和月、旬、日降水的集中性特征。结果表明:龙泉驿区年降水量整体下降趋势明显,存在3a和9a振荡周期;降水日数存在7~8a和12a振荡主周期,以及4a振荡次周期。可引发龙泉驿区地质灾害活动的降水主要发生在7月和8月,二者降水量在年代际尺度上的变化趋势相反。旬降水量与日降水量均呈明显的准正态分布规律,旬降水量主要集中时段是7月下旬与8月中旬,日降水量较大值也出现在7月与8月。      

近47a华南前汛期旱涝特征

采用华南61站47a（1958-2004年）前汛期（4-6月）逐日降水资料,利用统计方法对华南前汛期的旱涝特征进行了研究。结果表明：47a来华南有12个涝年和12个旱年发生,较严重的旱涝年主要发生在20世纪50年代末至70年代中期以及90年代以后;前汛期旱涝变化以2～4a的年际尺度周期最为显著;4、5月旱涝的年代际变化特征较为一致,而5月与6月在年代际尺度上具有一定的反位相变化特征;地理分布上,可将华南地区前汛期降水分为5个旱涝异常气候区。近47a来桂南、粤西和东南沿海地区呈现旱—涝—旱的变化特征,而桂北区由旱转涝趋于雨涝的趋势明显,东北部山区由涝转旱趋于干旱的趋势明显。     

Influences of Freshwater from Major Rivers on Global Ocean Circulation and Temperatures in the MIT Ocean General Circulation Model

Responses of global ocean circulation and temperature to freshwater runoff from major rivers were studied by blocking regional runoff in the global ocean general circulation model(OGCM)developed at the Massachusetts Institute of Technology.Runoff into the tropical Atlantic,the western North Pacific,and the Bay of Bengal and northern Arabian Sea were selectively blocked.The blocking of river runoff first resulted in a salinity increase near the river mouths(2 practical salinity units).The saltier and,therefore,denser water was then transported to higher latitudes in the North Atlantic,North Pacific,and southern Indian Ocean by the mean currents.The subsequent density contrasts between northern and southern hemispheric oceans resulted in changes in major ocean currents.These anomalous ocean currents lead to significant temperature changes(1°C-2°C)by the resulting anomalous heat transports.The current and temperature anomalies created by the blocked river runoff propagated from one ocean basin to others via coastal and equatorial Kelvin waves.This study suggests that river runoff may be playing an important role in oceanic salinity,temperature,and circulations;and that partially or fully blocking major rivers to divert freshwater for societal purposes might significantly change ocean salinity,circulations,temperature,and atmospheric climate.Further studies are necessary to assess the role of river runoff in the coupled atmosphere-ocean system.     

Correlations of Climate and Streamflow in Three Minnesota Streams

Correlations between four climate parameters and streamflow in three Minnesota streams were investigated. Runoff values measured over periods of up to 37 years were correlated with precipitation, air temperature, wind, and dew point temperature. The overall objective was to examine if relationships can be obtained which require only readily available input parameters without calibration. Such relationships would be of great use, e.g. to compute future lake water budgets without recourse to more detailed and complex hydrologic runoff models. Monthly, seasonal, and annual time frames were investigated. A seasonal time frame using 3 month averages gave the closest fit for the linear regressions without time lag. Although the watershed sizes varied from 360 to 49,600 square kilometers, the 3 month period seemed sufficiently long to average long term hydrologic processes such as infiltration, evaporation, and groundwater flow. An equation was found for each season (3 months) for each of the rivers. Winter (December, January, February) regressions required only precipitation data; spring regressions required air temperature and precipitation; summer and fall regressions were found with precipitation, air temperature, dew point temperature, and wind speed. The coefficients in the regression equations were related to the watershed characteristics. The r² values were highest for the Zumbro River in spring (0.69) and lowest for the Baptism River in winter (0.14). Root mean square error values ranged from 2.8 mm/mo for the Mississippi River in winter to 18 mm/mo for the Baptism River in spring. The coefficients of variability (CV) ranged from 0.24 to 0.52. Overall the results were disappointing but not all bad. Climate parameters without watershed parameters can characterize runoff only within limits. To project possible future runoff averages the GISS GCM-values for the 2 × CO₂ climate scenario were applied to the seasonal runoff regression equations. The projections were that the spring runoff values would decrease by up to 35% while in the other seasons streamflows would increase by up to 50%. Annual runoff would not change significantly enough to be predictable. The results were in the range of changes predicted by other investigations using very different techniques. Since predictions were based on equations found with past records, it was implied that the land cover would remain unchanged in the 2 × CO₂ environment. This may be unrealistic and needs further investigation.     

River Runoff Effects on the Coastal Water Transparency in the Western Black Sea

Using the data of long-term observations of the Secchi disk visibility depth and water salinity (1947-2000) and satellite monitoring of chlorophyll a concentration (1978-1986), their seasonal spatial distributions and intraannual variability in the coastal waters of the western Black Sea are considered. The estimates of seasonal variations are obtained for the coastal zone of the sea. A good agreement is demonstrated between intraannual variations in the salinity of transformed river water, chlorophyll a concentration, and transparency in the areas where these waters propagate. We studied the effects of the Danube River runoff and transformed river water on the phytoplankton development and chlorophyll a concentration which largely define water transparency.     

Sensitivity of the Humboldt Current system to global warming: a downscaling experiment of the IPSL-CM4 model

The impact of climate warming on the seasonal variability of the Humboldt Current system ocean dynamics is investigated. The IPSL-CM4 large scale ocean circulation resulting from two contrasted climate scenarios, the so-called Preindustrial and quadrupling CO₂, are downscaled using an eddy-resolving regional ocean circulation model. The intense surface heating by the atmosphere in the quadrupling CO₂ scenario leads to a strong increase of the surface density stratification, a thinner coastal jet, an enhanced Peru–Chile undercurrent, and an intensification of nearshore turbulence. Upwelling rates respond quasi-linearly to the change in wind stress associated with anthropogenic forcing, and show a moderate decrease in summer off Peru and a strong increase off Chile. Results from sensitivity experiments show that a 50% wind stress increase does not compensate for the surface warming resulting from heat flux forcing and that the associated mesoscale turbulence increase is a robust feature.     

Mid-Holocene to present-day evolution of the Indian monsoon in transient global simulations

The low-frequency evolution of Indian rainfall mean-state and associated interannual-to-decadal variability is discussed for the last 6000 years from a multi-configuration ensemble of fully coupled global transient simulations. This period is marked by a shift of Indian Summer Monsoon Rainfall (ISMR) distribution towards drier conditions, including extremes, and a contraction of the rainy season. The drying is larger in simulations with higher horizontal resolution of the atmosphere and revised land surface hydrology. Vegetation–climate interactions and the way runoff is routed to ocean modulate the timing of the monsoon onset but have negligible effects on the evolution of seasonal rainfall amounts in our modeling framework in which carbon cycling is always active. This drying trend is accompanied by changes in ISMR interannual-to-decadal variability decreasing over north and south India but increasing over central India (20°–25° N). The ISMR interannual-to-decadal variability is decomposed into six physically consistent regimes using a clustering technique to further characterize its changes and associated teleconnections. From 6 to 3.8 kyr bp, the century-to-century modulations in the frequency of occurrence associated to the regimes are asynchronous between the simulations. Orbitally-driven trends can only be detected for two regimes over the whole 6–0 kyr bp period. These two regimes reflect increased influence of ENSO on both ISMR and Indian Ocean Dipole as the inter-hemispheric energy gradient weakens. Severe long-term droughts are also shown to be a combination of long-term drying and internally generated low-frequency modulations of the interannual-to-decadal variability.

     

Perceptions of climate and ocean change impacting the resources and livelihood of small-scale fishers in the South Brazil Bight

Coastal fishing communities are closely linked to the biological and ecological characteristics of exploited resources and the physical conditions associated with climate and ocean dynamics. Thus, the human populations that depend on fisheries are inherently exposed to climate variability and uncertainty. This study applied an ethno-oceanographic framework to investigate the perceptions of fishers on climate and ocean change to better understand the impacts of climate change on the coastal fishing communities of the South Brazil Bight. Seven coastal fishing communities that cover the regional diversity of the area were selected. Fishers were interviewed using a semi-structured questionnaire. The results suggest that fishers have detected climate-related changes in their environment such as reduced rainfall, increased drought events, calmer sea conditions, increases in air and ocean temperatures, changes in wind patterns and shoreline erosion. The perceptions of the fishers were compared to the available scientific data, and correlations were found with rainfall, wind speed and air and ocean temperatures. New hypotheses were raised based on the perceptions of fishers about sea level, coastal currents and sea conditions such as the hypothesis that the sea has become calmer. These perceived changes have positive and negative effects on the yields and livelihoods of fishers. The present work is the first evaluation of the perceptions of fishers on climate and ocean change and brings new understandings of climate-fishery-human interactions as well as provides inputs for future adaptation plans.     

Quantitative evaluation of climatic variability and risks for wheat yield in India

This study comprises (1) an analysis of recent climate trends at two sites in north-west India (Ludhiana in Punjab and Delhi) and (2) an impact and risk assessment for wheat yields associated with climatic variability. North-west Indian agriculture is dominated by rice-wheat rotation in which the wheat season (‘rabi’, November to March) is characterized by predominantly dry conditions—superimposed by very high inter-annual variability of rainfall (17 to 260 mm in Ludhiana and <1 to 155 mm in Delhi). While rainfall remained without discernable trend over the last three decades, minimum and average temperatures showed increasing trends of 0.06 and 0.03°C year^???1, respectively, at Ludhiana. The site in (metropolitan) Delhi was apparently influenced by city-effects, which was noticeable from the decrease in solar radiation of 0.09 MJ m^???2 day^???1 year^???1. The CERES-wheat model was used to calculate yields of rainfed wheat that were at both locations highly correlated with seasonal rainfall. An assessment framework was developed to quantify yield impacts due to rainfall variability in three steps: (1) data from different years were aggregated into four classes, i.e., years with scarce, low, moderate, and high rainfall, (2) yield records of each rainfall class were ranked according to yield to facilitate (3) a comparison of yields with identical rank, i.e. among the best yield of each class, the second-best, etc. The class with moderate rainfall was taken as baseline yield to compute yield impacts of other rainfall scenarios. Years with scarce rainfall resulted in only 34% (Ludhiana) and 35% (Delhi) of the baseline yield. The yields in years with low rainfall accounted for 61% (Delhi) and 49% (Ludhiana) of the baseline yields. In Ludhiana, high rainfall years resulted in 200% yield as compared to the baseline yield, whereas they reached only 105% in Delhi. Low-intensity (1× and 3×) irrigation decreased the relative yield losses, but entailed a higher vulnerability in terms of absolute yield losses. Only high-intensity (4×) irrigation buffered wheat yields against adverse rainfall years. Early sowing was beneficial for wheat yields under all rainfall scenarios. The framework could be a valuable decision-support tool at the farm level where seasonal rainfall variability is high.     

When timing matters-considering changing temporal structures in runoff response surfaces

Scenario-neutral response surfaces illustrate the sensitivity of a simulated natural system, represented by a specific impact variable, to systematic perturbations of climatic parameters. This type of approach has recently been developed as an alternative to top-down approaches for the assessment of climate change impacts. A major limitation of this approach is the underrepresentation of changes in the temporal structure of the climate input data (i.e., the seasonal and day-to-day variability) since this is not altered by the perturbation. This paper presents a framework that aims to examine this limitation by perturbing both observed and projected climate data time series for a future period, which both serve as input into a hydrological model (the HBV model). The resulting multiple response surfaces are compared at a common domain, the standardized runoff response surface (SRRS). We apply this approach in a case study catchment in Norway to (i) analyze possible changes in mean and extreme runoff and (ii) quantify the influence of changes in the temporal structure represented by 17 different climate input sets using linear mixed-effect models. Results suggest that climate change induced increases in mean and peak flow runoff and only small changes in low flow. They further suggest that the effect of the different temporal structures of the climate input data considerably affects low flows and floods (at least 21% influence), while it is negligible for mean runoff.     

Rainfall variability and seasonality in northern Bangladesh

This paper aimed at the analysis of rainfall seasonality and variability for the northern part of South-Asian country, Bangladesh. The coefficient of variability was used to determine the variability of rainfall. While rainfall seasonality index (SI ) and mean individual seasonality index (\( \overline{SI_i} \)) were used to identify seasonal contrast. We also applied Mann-Kendall trend test and sequential Mann-Kendall test to determine the trend in seasonality. The lowest variability was found for monsoon among the four seasons whereas winter has the highest variability. Observed variability has a decreasing tendency from the northwest region towards the northeast region. The mean individual seasonality index (0.815378 to 0.977228) indicates that rainfall in Bangladesh is “markedly seasonal with a long dry season.” It was found that the length of the dry period is lower at the northeastern part of northern Bangladesh. Trend analysis results show no significant change in the seasonality of rainfall in this region. Regression analysis of \( \overline{SI_i} \) and SI, and longitude and mean individual seasonality index show a significant linear correlation for this area.     

Evaluating spatial scales of climate variability in sub-Saharan Africa

Summary Spatial scales of variability in seasonal rainfall over Africa are investigated by means of statistical and numerical techniques. In the statistical analysis spatial structure is studied using gridded 0.5° resolution monthly data in the period 1948–1998. The de-seasonalized time series are subjected to successive principal component (PC) analysis, allowing the number of modes to vary from 10 to 24, producing cells of varying dimension. Then the original rainfall data within each cell are cross-correlated (internal), then averaged and compared with the adjacent cells (external) for each PC solution. By considering the ratio of internal to external correlation, the spatial scales of rainfall variability are evaluated and an optimum solution is found whose cell dimensions are approximately 10⁶ km². The aspect of scale is further studied for southern Africa by consideration of numerical model ensemble simulations over the period 1985–1999 forced with observed sea surface temperatures (SSTs). The hindcast products are compared with observed January to March (JFM) rainfall, based on a station-satellite merged analysis of precipitation (CMAP) data at 2.5° resolution. Validations for different sized areas indicate that cumulative standardized errors are greatest at the scale of a single grid cell (10⁴ km²) and decrease 20–30% by averaging over successively larger areas (10⁶ km²).