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1.
Detectability of Summer Dryness Caused by Greenhouse Warming 总被引：14，自引：0，他引：14
This study investigates the temporal and spatial variation of soil moisture associated with global warming as simulated by long-term integrations of a coupled ocean-atmosphere model conducted earlier. Starting from year 1765, integrations of the coupled model for 300 years were performed for three scenarios: increasing greenhouse gases only, increasing sulfate-aerosol loading only and the combination of both radiative forcings. The integration with the combined radiative forcings reproduces approximately the observed increases of global mean surface air temperature during the 20th century. Analysis of this integration indicates that both summer dryness and winter wetness occur in middle-to-high latitudes of North America and southern Europe. These features were identified in earlier studies. However, in the southern part of North America where the percentage reduction of soil moisture during summer is quite large, soil moisture is decreased for nearly the entire annual cycle in response to greenhouse warming. A similar observation applies to other semi-arid regions in subtropical to middle latitudes such as central Asia and the area surrounding the Mediterranean Sea. On the other hand, annual mean runoff is greatly increased in high latitudes because of increased poleward transport of moisture in the warmer model atmosphere. An analysis of the central North American and southern European regions indicates that the time when the change of soil moisture exceeds one standard deviation about the control integration occurs considerably later than that of surface air temperature for a given experiment because the ratio of forced change to natural variability is much smaller for soil moisture compared with temperature. The corresponding lag time for runoff change is even greater than that of either precipitation or soil moisture for the same reason. Also according to the above criterion, the inclusion of the effect of sulfate aerosols in the greenhouse warming experiment delays the noticeable change of soil moisture by several decades. It appears that observed surface air temperature is a better indicator of greenhouse warming than hydrologic quantities such as precipitation, runoff and soil moisture. Therefore, we are unlikely to notice definitive CO2-induced continental summer dryness until several decades into the 21st century. 相似文献
2.
借助于概率密度函数(PDF)拟合和经验正交函数(EOF)展开以及小波分析等方法,本文分析了中国东北地区夏季近十年间(1988-1999年)旬平均土壤湿度(0～50 cm层次)垂直分布结构的时空变化特征。结果表明,从区域分布来看,东北夏季土壤湿度的高值中心主要位于牡丹江流域和松嫩平原南侧,而从土壤水分的垂直分布特征来看,其湿润度绝大多数测站(除个别地区呈多峰态外)基本呈上干下湿,服从Weibull分布的单峰偏态型。各层土壤湿度在6月中旬和8月上旬变化最大,并存在以3 a为主的周期振荡。 相似文献
3.
An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois. 相似文献
4.
Processes acting at the interface between the land surface and the atmosphere have a strong impact on the European summer climate, particularly during extreme years. These processes are to a large extent associated with soil moisture (SM). This study investigates the role of soil moisture?Catmosphere coupling for the European summer climate over the period 1959?C2006 using simulations with a regional climate model. The focus of this study is set on temperature and precipitation extremes and trends. The analysis is based on simulations performed with the regional climate model CLM, driven with ECMWF reanalysis and operational analysis data. The set of experiments consists of a control simulation (CTL) with interactive SM, and sensitivity experiments with prescribed SM: a dry and a wet run to determine the impact of extreme values of SM, as well as experiments with lowpass-filtered SM from CTL to quantify the impact of the temporal variability of SM on different time scales. Soil moisture?Cclimate interactions are found to have significant effects on temperature extremes in the experiments, and impacts on precipitation extremes are also identified. Case studies of selected major summer heat waves reveal that the intraseasonal and interannual variability of SM account for 5?C30% and 10?C40% of the simulated heat wave anomaly, respectively. For extreme precipitation events on the other hand, only the wet-day frequency is impacted in the experiments with prescribed soil moisture. Simulated trends for the past decades, which appear consistent with projected changes for the 21st century, are identified to be at least partly linked to SM-atmosphere feedbacks. 相似文献
5.
Spatiotemporal modeling of monthly soil temperature using artificial neural networks 总被引：2，自引：1，他引：1
Wei Wu Xiao-Ping Tang Nai-Jia Guo Chao Yang Hong-Bin Liu Yue-Feng Shang 《Theoretical and Applied Climatology》2013,113(3-4):481-494
Soil temperature data are critical for understanding land–atmosphere interactions. However, in many cases, they are limited at both spatial and temporal scales. In the current study, an attempt was made to predict monthly mean soil temperature at a depth of 10 cm using artificial neural networks (ANNs) over a large region with complex terrain. Gridded independent variables, including latitude, longitude, elevation, topographic wetness index, and normalized difference vegetation index, were derived from a digital elevation model and remote sensing images with a resolution of 1 km. The good performance and robustness of the proposed ANNs were demonstrated by comparisons with multiple linear regressions. On average, the developed ANNs presented a relative improvement of about 44 % in root mean square error, 70 % in mean absolute percentage error, and 18 % in coefficient of determination over classical linear models. The proposed ANN models were then applied to predict soil temperatures at unsampled locations across the study area. Spatiotemporal variability of soil temperature was investigated based on the obtained database. Future work will be needed to test the applicability of ANNs for estimating soil temperature at finer scales. 相似文献
6.
A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean-atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere. 相似文献
7.
Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment 总被引：8，自引：0，他引：8
Guiling Wang 《Climate Dynamics》2005,25(7-8):739-753
This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models
by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models
are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly
over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude
Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture
storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models
are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia,
and the South Africa in all seasons, and over much of the Amazon and West Africa in the June–July–August (JJA) season and
the Asian monsoon region in the December–January–February (DJF) season. Since the only major areas of future wetness predicted
with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it
is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable
consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes
of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major
part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface
parameterization. 相似文献
8.
Soil wetness, in both its global distribution and the seasonal change, has been mainly estimated by the water balance approach
using the bucket model which regards the soil wetness as soil moisture. The soil moisture data of Mintz and Serafini is one
of the representatives examples, however, this method has problems since it does not incorporate the effects of flooding,
snow accumulation on the ground, and so on. In this study, we use the Amazon and Volga river basin to carry out a case study
to evaluate these problems. In the Amazon river basin, the annual range of the entire terrestrial water storage, about 400 mm,
can be mainly explained by the rising and falling of the water level, and flooding around river channels, although soil moisture
data of Mintz and Serafini is almost constant throughout the year. In the Volga river basin, snow accumulates on the ground
producing 80 mm of water equivalent during winter, however the soil moisture data of Mintz and Serafini is almost saturated
in winter.
Received: 30 October 1996 / Accepted: 4 June 1997 相似文献
9.
根据Palmer气象干旱指数 (PDSI) 的中间量Palmer湿润指数原理, 计算了西北地区东部冬小麦农气观测站延安、咸阳等多个站点1961—2000年逐月Palmer湿润指数, 对各站点的冬小麦不同发育期的旱涝情况做了初步的验证和应用。Palmer湿润指数与Z指数对比结果表明:Palmer湿润指数对农作物旱情分析更具有客观性, 分析结果更符合实际情况, 因而可以作为我国西北地区东部农作物旱涝的评估工具。 相似文献
10.
2009/2010年冬季云南干旱的进一步研究——前期土壤湿度影响的数值模拟 总被引：1，自引：0，他引：1
采用新一代中尺度数值模式WRFv3.2版本,模拟研究了前期(秋季)土壤湿度异常对云南冬季降水的影响。数值模拟试验结果和一系列分析清楚表明,前期(秋季)土壤湿度的异常偏低,会导致云南地区冬季(12月1日~2月28日)降水的显著减少;前期土壤湿度减少一半,可以使云南冬季的降水量平均减少30%以上,小部分区域减少达50%以上,影响十分明显。大气环流及其主要参量模拟结果的对比分析清楚表明,持续的西偏北气流和干气团的控制以及云南地区大气散度场和垂直运动场等的异常是导致降水量减少的直接原因。对降水过程的分析表明,前期土壤湿度减少对降水过程的频次和发生时间的影响较小,但对各次过程的降水强度影响明显。这是前期土壤湿度减少所导致的包括区域性蒸发量和热通量等大气物理过程的改变决定的。本研究数值模拟结果与关于区域性土壤湿度异常影响机理的已有结论基本一致。 相似文献
11.
Global simulations with the Bureau of Meteorology Research Centre climate model coupled to the CHAmeleon Surface Model (CHASM) are used to explore the sensitivity of simulated changes in evaporation, precipitation, air temperature and soil moisture resulting from a doubling of carbon dioxide in the atmosphere. Five simulations, using prescribed sea surface temperatures, are conducted which are identical except in the level of complexity used to represent the surface energy balance. The simulation of air temperature, precipitation, evaporation and soil moisture at 1 2 CO2 and at 2 2 CO2 are generally sensitive at statistically significant levels to the complexity of the surface energy balance representation (i.e. the level of complexity used to represent these processes affects the simulated climate). However, changes in mean quantities, resulting from a doubling of atmospheric CO2, are generally insensitive to the surface energy balance complexity. Conversely, changes in the spatial and temporal variance of evaporation and soil moisture are sensitive to the surface energy balance complexity. The addition of explicit canopy interception to the simplest model examined here enables that model to capture the change in the variance of evaporation simulated by the more complex models. In order to simulate changes in the variability of soil moisture, an explicit parameterization of bare soil evaporation is required. Overall, our results increase confidence that the simulation by climate models of the mean impact of increasing CO2 on climate are reliable. Changes in the variability resulting from increased CO2 on air temperature, precipitation or evaporation are also likely to be reliable since climate models typically use sufficiently complex land surface schemes. However, if the impact of increased CO2 on soil moisture is required, then a more complex surface energy balance representation may be needed in order to capture changes in variability. Overall, our results imply that the level of complexity used by most climate models to represent the surface energy balance is appropriate and does not contribute significant uncertainty in the simulation of changes resulting from increasing CO2. Our results only relate to surface energy balance complexity, and major uncertainties remain in how to model the surface hydrology and changes in the physiology, structural characteristics and distribution of vegetation. Future developments of land surface models should therefore focus on improving the representation of these processes. 相似文献
12.
地气耦合系统中温湿变化的数值模拟 总被引：4，自引：1，他引：4
本文提出了计算地气耦合系统中温度和湿度变化的一维数值模式,在土壤中,利用热量平衡和水份平衡原理计算土壤温度和湿度,在大气中,考虑了长短波辐射、云量和凝结等因素对大气温湿变化的影响。选择一种代表性土壤对模式进行了检验,结果发现,模式能较好地模拟诸多物理量的日变化过程。计算表明,大气和土壤的初始温湿分布,对结果有较大影响。本文的原理可应用于大气环流模式中陆气相互作用过程的参数化。 相似文献
13.
Through an Australia-China climate change bilateral project, we analyzed results of 51-year global offline simulations over China using the Australian community atmosphere biosphere land exchange (CABLE) model, focusing on integrated studies of its surface energy, water and carbon cycle at seasonal, interannual and longer time-scales. In addition to the similar features in surface climatology between the CABLE simulation and those derived from the global land-surface data assimilation system, comparison of surface fluxes at a CEOP reference site in northeast China also suggested that the seasonal cycles of surface evaporation and CO2 flux are reasonably simulated by the model. We further assessed temporal variations of model soil moisture with the observed variations at a number of locations in China. Observations show a soil moisture recharge–discharge mechanism on a seasonal time scale in central-east China, with soil moisture being recharged during its summer wet season, retained in its winter due to low evaporation demand, and depleted during early spring when the land warms up. Such a seasonal cycle is shown at both 50- and 100-cm soil depths in observations while the model only shows a similar feature in its lower soil layers with its upper layer soil moisture varying tightly with rainfall seasonal cycle. In the analysis of the model carbon cycle, the net primary productivity (NPP) has similar spatial patterns as the ones derived from an ecosystem model with remote sensing. The simulated interannual variations of NPP by CABLE are consistent with the results derived from remote sensing-based and process-based studies over the period of 1981–2000. Nevertheless an upward trend from observations is not presented in the model results. The model shows a downward trend primarily due to the constant CO2 concentration used in the experiment and a large increase of autotrophic respiration caused by an upward trend in surface temperature forcing data. Furthermore, we have compared river discharge data from the model experiments with observations in the Yangtze and Yellow River basins in China. In the Yangtze River basin, while the observed interannual variability is reasonably captured, the model significantly underestimates its river discharge, which is consist with its overestimation of evaporation in the region. In the Yellow River basin, the magnitudes of the river discharge is similar between modeled and observed but its variations are less skillfully captured as seen in the Yangtze River region. 相似文献
14.
Ensembles of boreal summer atmospheric simulations, spanning a 15-year period (1979–1993), are performed with the ARPEGE climate model to investigate the influence of soil moisture on climate variability and potential predictability. All experiments are forced with observed monthly mean sea surface temperatures. In addition to a control experiment with interactive soil moisture boundary conditions, two sensitivity experiments are performed. In the first, the interannual variability of the deep soil moisture is removed during the whole season, through a relaxation toward the monthly mean model climatology. In the second, only the variability of the initial soil moisture conditions is suppressed. While it is shown that soil moisture strongly contributes to the climate variability simulated in the control experiment, an analysis of variance indicates that soil moisture does not represent a significant source of predictability in most continental areas. The main exception is the North American continent, where climate predictability is clearly reduced through the use of climatological initial conditions. Using climatological soil moisture boundary conditions does not lead to strong and homogeneous impacts on potential predictability, thereby suggesting that the climate signals driven by the sea surface temperature variability are not generally amplified by interactive soil moisture and that the relevance of soil moisture for seasonal forecasting is mainly an initial value problem. 相似文献
15.
H. Douville 《Climate Dynamics》1998,14(3):151-172
Global soil moisture data of high quality and resolution are not available by direct observation, but are useful as boundary
and initial conditions in comprehensive climate models. In the framework of the GSWP (Global Soil Wetness Project), the ISBA
land-surface scheme of Météo-France has been forced with meteorological observations and analyses in order to study the feasibility
of producing a global soil wetness climatology at a 1°×1° horizontal resolution. A control experiment has been performed from
January 1987 to December 1988, using the ISLSCP Initiative I boundary conditions. The annual mean, the standard deviation
and the normalised annual harmonic of the hydrologic fields have been computed from the 1987 monthly results. The global maps
which are presented summarise the surface hydrologic budget and its annual cycle. The soil wetness index and snow cover distributions
have been compared respectively to the results of the ECMWF reanalysis and to satellite and in situ observations. The simulated
runoff has been validated against a river flow climatology, suggesting a possible underestimation over some large river basins.
Besides the control run, other simulations have been performed in order to study the sensitivity of the hydrologic budget
to changes in the surface parameters, the precipitation forcing and the runoff scheme. Such modifications have a significant
impact on the partition of total precipitation into evaporation and runoff. The sensitivity of the results suggests that soil
moisture remains one of the most difficult climatological parameters to model and that any computed soil wetness climatology
must be considered with great caution.
Received: 3 January 1997 / Accepted: 19 August 1987 相似文献
16.
17.
This paper presents an indication of the possible effects of climate change on monthly mean soil moisture at a fine spatial resolution (50 m) over the scale of a landscape (100–250 km2). Soil moisture is modelledusing daily time series of rainfall and potential evapotranspiration to drive a simple hydrological model operating on individual hillslopes and explicitly including, on a conceptual level, the lateral movement of water. Climate change is represented by the UKTR scenario and model results are provided at two time slices (the years 2030–2040 and 2060–2070) for five areasof ecological interest, forming a north-south transect across the U.K. The results are given in terms of the distribution of the monthly mean soil moisture change by soil type. The spread of values reflects the effect of the topographic control on the lateral movement of water. The results show a small increase in wetness at the Cairngorm site, a very slight decrease in summer soil moisture at the Moor House site and a very marked fall in soil moisture for the three more southerly sites. The importance of soil type in determining the availability of water to plants, the changing areal extent above specified soil moisture thresholds, and the implications for ecological change and conservation are discussed. 相似文献
18.
基于NCAR大气模式CAM3.1模式,设计了有、无土壤湿度年际异常两组试验对中国区域近40a(1961-2000年)气候进行了模拟。从气候态和年际变率的角度,通过分析两组试验的差值场来探讨土壤湿度年际异常对气候模拟的影响,并初步探讨了影响的可能机制。结果表明:模式模拟的温度和降水对土壤湿度的年际异常非常敏感,土壤湿度的年际变化对中国春夏季气候及其年际变率均有显著影响。当不考虑土壤湿度年际异常时,模式模拟的春夏季平均温度、最高温度、最低温度在我国大范围内降低,春夏季降水在东部大部分地区明显减少,西部增加。而模式模拟的春夏季温度、降水年际变率在中国大部分地区减弱。但当考虑土壤湿度的年际变化,则能在一定程度上提高模式对气候年际变率的模拟能力。在进一步分析表明土壤湿度年际异常时,主要通过改变地表能量通量和环流场,对温度、降水产生影响。当不考虑土壤湿度年际异常时,地表净辐射通量减少,地表温度降低,感热通量减少。感热通量差值场的空间变化和温度差值场的空间变化一致,感热通量对温度有一定影响。而潜热通量差值场的空间变化和降水的差值场的空间变化一致,可见降水受地表潜热通量的影响。土壤湿度年际异常引起的环流场的变化也是导致气候变化的原因之一,地表能量和环流场年际变率的改变对春夏季气候年际变率存在一定影响。 相似文献
19.
本模式为针对大气环流模式所发展的一个简单的陆面过程模式，它包含:（1）地表温度计算，（2）冠层叶面贮水量和土壤湿度计算，（3）陆面与大气之间的水分和能量交换。对于表面温度和含水量的计算，采用的是联立求解计算方案，即耦合计算。植被冠层叶面的辐射特性和冠层形态对冠层中的辐射交换的影响得到有效和尽可能简单的模拟。另外，植被的气孔阻抗、表面与大气之间的水热交换通量和土壤中的水热输导作了较为细致的描写。利用此模式开展了对两个不同覆盖类型的陆面过程的模拟，模拟和观测的表面通量、温度和湿度较为相近。 相似文献
20.
来自大气内部的季节气候可预测性初探 总被引：3，自引：0，他引：3
这是一个十分初步的工作结果.通常认为,气候的季节-年际可预测性主要来自缓慢变化的大气外强迫的异常(如海表温度、积雪、土壤温度和湿度等).作者从大气月平均风场异常的持续性以及与东亚季风年际异常相关的全球大气环流异常特征两个方面初步探讨东亚夏季气候的可预测性.初步结果说明,大气月平均风场在对流层上层和平流层下层的热带区域及一些关键区域可持续性可以超过一个季节,并且与东亚季风有显著相关,从而使得从大气内部变化来考虑东亚夏季风气候仍然有一定的可预测性. 相似文献