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1.
何文英  陈洪滨  李军 《地球物理学报》1954,63(10):3573-3584
复杂多变的陆地表微波比辐射率,造成陆面上星载微波观测反演大气参数较为困难,也使得许多卫星微波资料不易同化应用到数值模式,因此迫切需要提供准确可靠的陆面微波地表比辐射率信息.随着卫星观测技术的迅速发展,利用丰富的星载被动微波观测直接反演陆面微波比辐射率成为一种主要手段.国外针对星载微波成像仪和微波垂直探测器开展较为系统的陆面微波比辐射率研究,建立不同类型的地表比辐射率反演方法,开发地表比辐射率参数化方法并应用于辐射资料同化.对于卫星观测反演陆面微波比辐射率存在的问题,开展了评估分析和方法订正.国内利用卫星观测也开展了一些陆面微波比辐射率研究工作,尚需要系统、综合的提炼.对于地表特征复杂的中国地区,还需要评估认识不同陆面微波比辐射率反演方法在我国适用情况,需要增强陆面微波比辐射率数据质量的认识以及业务应用.  相似文献   

2.
The warming over the Tibetan Plateau(TP) is very significant during last 30 years,but the thermal forcing has been weakened.The thermal weakening is attributed mainly to the enhancement of the TOA(top of atmosphere) outgoing radiation.This enhancement is opposite to the greenhouse-gas-induced weakening of the global mean TOA outgoing radiation and is also unable to be explained by the observed decrease of total cloud cover.This study presents the importance of cloud height change and the warming over the TP in modulating the TOA radiation budget and thus the thermal forcing during spring and summer.On the basis of surface observations and satellite radiation data,we found that both the TOA outgoing shortwave radiation and longwave radiation were enhanced during this period.The former enhancement is due mainly to the increase of low-level cloud cover,which has a strong reflection to shortwave radiation,especially in summer.The latter enhancement is caused mainly by the planetary warming,and it is further enhanced by the decrease of total cloud cover in spring,as clouds extinguish outgoing longwave radiation emitted from the land surface.Therefore,the radiative cooling enhancement and thus the thermal weakening over the TP is a response of the earth-atmosphere system to the unique change of cloud cover configuration and the rapid warming of the land surface.However,these trends in cloud cover and TOA outgoing radiation are not well represented in four reanalyses.  相似文献   

3.
The climate warming is mainly due to the increase in concentrations of anthropogenic greenhouse gases, of which CO2 is the most important one responsible for radiative forcing of the climate. In order to reduce the great estimation uncertainty of atmospheric CO2 concentrations, several CO2-related satellites have been successfully launched and many future greenhouse gas monitoring missions are planned. In this paper, we review the development of CO2 retrieval algorithms, spatial interpolation methods and ground observations. The main findings include: 1) current CO2 retrieval algorithms only partially account for atmospheric scattering effects; 2) the accurate estimation of the vertical profile of greenhouse gas concentrations is a long-term challenge for remote sensing techniques; 3) ground-based observations are too sparse to accurately infer CO2 concentrations on regional scales; and 4) accuracy is the primary challenge of satellite estimation of CO2 concentrations. These findings, taken as a whole, point to the need to develop a high accuracy method for simulation of carbon sources and sinks on the basis of the fundamental theorem of Earth’s surface modelling, which is able to efficiently fuse space- and ground-based measurements on the one hand and work with atmospheric transport models on the other hand.  相似文献   

4.
Water vapor plays a crucial role in atmospheric processes that act over a wide range of temporal and spatial scales, from global climate to micrometeorology. The determination of water vapor distribution in the atmosphere and its changing pattern is very important. Although atmospheric scientists have developed a variety of means to measure precipitable water vapor(PWV) using remote sensing data that have been widely used, there are some limitations in using one kind satellite measurements for PWV retrieval over land. In this paper, a new algorithm is proposed for retrieving PWV over land by combining different kinds of remote sensing data and it would work well under the cloud weather conditions. The PWV retrieval algorithm based on near infrared data is more suitable to clear sky conditions with high precision. The 23.5 GHz microwave remote sensing data is sensitive to water vapor and powerful in cloud-covered areas because of its longer wavelengths that permit viewing into and through the atmosphere. Therefore, the PWV retrieval results from near infrared data and the indices combined by microwave bands remote sensing data which are sensitive to water vapor will be regressed to generate the equation for PWV retrieval under cloud covered areas. The algorithm developed in this paper has the potential to detect PWV under all weather conditions and makes an excellent complement to PWV retrieved by near infrared data. Different types of surface exert different depolarization effects on surface emissions, which would increase the complexity of the algorithm. In this paper, MODIS surface classification data was used to consider this influence. Compared with the GPS results, the root mean square error of our algorithm is 8 mm for cloud covered area. Regional consistency was found between the results from MODIS and our algorithm. Our algorithm can yield reasonable results on the surfaces covered by cloud where MODIS cannot be used to retrieve PWV.  相似文献   

5.
We review the methodologies used to quantify climate feedbacks in coupled models. The method of radiative kernels is outlined and used to illustrate the dependence of lapse rate, water vapor, surface albedo, and cloud feedbacks on (1) the length of the time average used to define two projected climate states and (2) the time separation between the two climate states. Except for the shortwave component of water vapor feedback, all feedback processes exhibit significant high-frequency variations and intermodel variability of feedback strengths for sub-decadal time averages. It is also found that the uncertainty of lapse rate, water vapor, and cloud feedback decreases with the increase in the time separation. The results suggest that one can substantially reduce the uncertainty of cloud and other feedbacks with the accumulation of accurate, long-term records of satellite observations; however, several decades may be required.  相似文献   

6.
Using the National Center for Atmospheric Research (NCAR) general circulation model (CCM2), a suite of alternative cloud radiation parameterizations has been tested. Our methodology relies on perpetual July integrations driven by ±2 K sea surface temperature forcing. The tested parameterizations include relative humidity based clouds and versions of schemes involving a prognostic cloud water budget. We are especially interested in testing the effect of cloud optical thickness feedbacks on global climate sensitivity. All schemes exhibit negative cloud radiation feedbacks, i.e., cloud moderates the global warming. However, these negative net cloud radiation feedbacks consist of quite different shortwave and longwave components between a scheme with interactive cloud radiative properties and several schemes with specified cloud water paths. An increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn negative shortwave feedbacks for the interactive radiative scheme, while a decrease in cloud amount leads to a positive shortwave feedback for the other schemes. For the longwave feedbacks, a decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while no distinct changes in effective high cloudiness and the resulting feedback are exhibited for the scheme with interactive radiative properties. The resulting magnitude of negative net cloud radiation feed-back is largest for the scheme with interactive radiative properties. Even though the simulated values of cloud radiative forcing for the present climate using this method differ most from the observational data, the approach shows great promise for the future.  相似文献   

7.
Skin temperatures that reflect the radiating temperature of a surface observed by infrared radiometers are one of the most widely available products from polar orbiting and geostationary satellites and the most commonly used satellite data in land surface assimilation. Past work has indicated that a simple land surface scheme with a few key parameters constrained by observations such as skin temperatures may be preferable to complex land use schemes with many unknown parameters. However, a true radiating skin temperature is sometimes not a prognostic variable in weather forecast models. Additionally, recent research has shown that skin temperatures cannot be directly used in surface similarity forms for inferring fluxes. This paper examines issues encountered in using satellite derived skin temperatures to improve surface flux specifications in weather forecast and air quality models. Attention is given to iterations necessary when attempting to nudge the surface energy budget equation to a desired state. Finally, the issue of mathematical operator splitting is examined in which the surface energy budget calculations are split with the atmospheric vertical diffusion calculations. However, the high level of connectivity between the surface and first atmospheric level means that the operator splitting leads to high frequency oscillations. These oscillations may hinder the assimilation of skin temperature derived moisture fluxes.  相似文献   

8.
Understanding the role of clouds in climate change remains a considerable challenge. Traditionally, this challenge has been framed in terms of understanding cloud feedback. However, recent work suggests that under increasing levels of atmospheric carbon dioxide, clouds not only amplify or dampen climate change through global feedback processes, but also through rapid (days to weeks) tropospheric temperature and land surface adjustments. In this article, we use the Met Office Hadley Centre climate model HadGSM1 to review these recent developments and assess their impact on radiative forcing and equilibrium climate sensitivity. We estimate that cloud adjustment contributes ~0.8?K to the 4.4?K equilibrium climate sensitivity of this particular model. We discuss the methods used to evaluate cloud adjustments, highlight the mechanisms and processes involved and identify low level cloudiness as a key cloud type. Looking forward, we discuss the outstanding issues, such as the application to transient forcing scenarios. We suggest that the upcoming CMIP5 multi-model database will allow a comprehensive assessment of the significance of cloud adjustments in fully coupled atmosphere–ocean-general-circulation models for the first time, and that future research should exploit this opportunity to understand cloud adjustments/feedbacks in non-idealised transient climate change scenarios.  相似文献   

9.
Spatially distributed hydrometeorological and plant information within the mountainous tropical Panama Canal watershed is used to estimate parameters of the Penman–Monteith evapotranspiration formulation. Hydrometeorological data from a few surface climate stations located at low elevations in the watershed are complemented by (a) typical wet‐ and dry‐season fields of temperature, wind, water vapour and pressure produced by a mesoscale atmospheric model with a 3 × 3 km2 spatial and hourly temporal resolution, and (b) leaf area index fields estimated over the watershed during a few years using satellite data with two different spatial and temporal resolutions. The mesoscale model estimates of spatially distributed surface hydrometeorological variables provide the basis for the extrapolation of the surface climate station data to produce input for the Penman–Monteith equation. The satellite information and existing digital spatial databases of land use and land cover form the basis for the estimation of Penman–Monteith spatially distributed parameter values. Spatially distributed 3 × 3 km2 potential evapotranspiration estimates are obtained for the 3300 km2 Panama Canal watershed. Estimates for Gatun Lake within the watershed are found to reproduce well the monthly and annual lake evaporation obtained from submerged pans. Sensitivity analysis results of potential evapotranspiration estimates with respect to cloud cover, dew formation, leaf area index distribution and mesoscale model estimates of surface climate are presented and discussed. The main conclusion is that even the limited spatially distributed hydrometeorological and plant information used in this study contributes significantly toward explaining the substantial spatial variability of potential evapotranspiration in the watershed. These results also allow the determination of key locations within the watershed where additional surface stations may be profitably placed. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

10.
利用现有大气本底站的大气CO2浓度观测信息,综合考虑不同经济区划与土地覆盖类型对应的CO2浓度差异及其季节变化规律,构建模式区域内以月为单位的网格化大气CO2浓度非均匀动态分布数据模型.由此数据模型驱动RegCM4-CLM3.5区域气候模式运行,对东亚区2000年3月—2009年2月之间的气候变化特征进行了模拟,进而对大气CO2浓度非均匀动态分布可能引起的区域气候效应进行了初步研究.结果表明:目前气候模式中CO2浓度的常态均匀分布假设可能将温室效应夸大了10%左右.对大气CO2浓度非均匀动态分布影响气温变化的可能机制进行研究表明:CO2的自身效应(改变大气透射率)并不是导致Exp2试验温度降低的主要原因.大气CO2浓度的变化影响了大气与植物胞间CO2分压差,陆地植被通过改变气孔阻力适应这种变化,气孔阻力的变化直接影响到植物与大气间水分的交换,这种作用一方面通过蒸发冷却改变环境温度,另一方面,蒸发水分改变了近地面层湿度,进而水汽扩散到空中影响低云的分布.冬季,植物处于非生长季,对大气CO2浓度变化响应微弱,湿度和低云变化不明显;夏季,植物生长旺盛,由CO2生理学强迫激发的云反馈效应强烈,其效果是使中低云趋于增加,进而减弱了到达对流层低层的太阳短波辐射,造成温室效应减弱.  相似文献   

11.
卫星重力梯度测量与地球引力场的精度研究   总被引：1，自引：0，他引：1  
本文根据地球引力位的球谐函数展开式,利用重力梯度张量各分量导出了位系数模型的精度估计公式.从三方面进行了研究:假定卫星重力梯度仪测量精度,探讨用重力梯度数据确定地球重力场模型的精度;求出位系数模型和大气阻力引起的重力梯度卫星的轨道误差;最后,反求轨道误差和位系数误差对重力梯度测量值的影响.数值计算表明,与地面技术和常规卫星方法相比,卫星梯度测量可使重力场模型的精度至少提高3-5倍;利用重力梯度张量全分量求得的重力值精度比单用径向分量Vrr的结果提高40％以上;若仅顾及位系数模型和大气阻力误差,则轨道误差对梯度测量值的影响△Vi3（i=3,2,1）至少可分别在1/4和1/3弧圈内达到△Vi3≤σ（仪器精度）.  相似文献   

12.
This study aims at evaluating the uncertainty in the prediction of soil moisture (1D, vertical column) from an offline land surface model (LSM) forced by hydro-meteorological and radiation data. We focus on two types of uncertainty: an input error due to satellite rainfall retrieval uncertainty, and, LSM soil-parametric error. The study is facilitated by in situ and remotely sensed data-driven (precipitation, radiation, soil moisture) simulation experiments comprising a LSM and stochastic models for error characterization. The parametric uncertainty is represented by the generalized likelihood uncertainty estimation (GLUE) technique, which models the parameter non-uniqueness against direct observations. Half-hourly infra-red (IR) sensor retrievals were used as satellite rainfall estimates. The IR rain retrieval uncertainty is characterized on the basis of a satellite rainfall error model (SREM). The combined uncertainty (i.e., SREM + GLUE) is compared with the partial assessment of uncertainty. It is found that precipitation (IR) error alone may explain moderate to low proportion of the soil moisture simulation uncertainty, depending on the level of model accuracy—50–60% for high model accuracy, and 20–30% for low model accuracy. Comparisons on the basis of two different sites also yielded an increase (50–100%) in soil moisture prediction uncertainty for the more vegetated site. This study exemplified the need for detailed investigations of the rainfall retrieval-modeling parameter error interaction within a comprehensive space-time stochastic framework for achieving optimal integration of satellite rain retrievals in land data assimilation systems.  相似文献   

13.
Using remotely-sensed data, various soil moisture estimation models have been developed for bare soil areas. Previous studies have shown that the brightness temperature (BT) measured by passive microwave sensors were affected by characteristics of the land surface parameters including soil moisture, vegetation cover and soil roughness. Therefore knowledge of vegetation cover and soil roughness is important for obtaining frequent and global estimations of land surface parameters especially soil moisture.In this study, a model called Simultaneous Land Parameters Retrieval Model (SLPRM) that is an iterative least-squares minimization method is proposed. The algorithm estimates surface soil moisture, land surface temperature and canopy temperature simultaneously in vegetated areas using AMSR-E (Advance Microwave Scanning Radiometer-EOS) brightness temperature data. The simultaneous estimations of the three parameters are based on a multi-parameter inversion algorithm which includes model construction, calibration and validation using observations carried out for the SMEX03 (Soil Moisture Experiment, 2003) region in the South and North of Oklahoma.Roughness parameter has also been included in the algorithm to increase the soil parameters retrieval accuracy. Unlike other methods, the SLPRM method works efficiently in all land covers types.The study focuses on soil parameters estimation by comparing three different scenarios with the inclusion of roughness data and selects the most appropriate one. The difference between the resulted accuracies of scenarios is due to the roughness calculation approach.The analysis on the retrieval model shows a meaningful and acceptable accuracy on soil moisture estimation according to the three scenarios.The SLPRM method has shown better performance when the SAR (Synthetic Aperture RADAR) data are used for roughness calculation.  相似文献   

14.
This survey considers those studies conducted into estimating errors in satellite derived large scale space-time means (of the order of 250 km by 250 km by a month) for rainfall, cloud cover, sea surface processes and the Earth's radiation budget, resulting from their incomplete coverage of the space-time volume over which the mean is evaluated. Many of these studies have focused on estimating the errors in space-time means post satellite launch and compare mean data derived from such satellites with that from an independent data set. Pre-launch studies tend to involve computer simulations of a satellite overflying and sampling from an existing data set and hence the two approaches give values for sampling errors for specific cases. However, more generic sampling papers exist that allow the exact evaluation of sampling errors for any instrument or combination of instruments if their sampling characteristics and the auto-correlation of the parameter field are known. These generic and simulation techniques have been used together on the same data sets and are found to give very similar values for the sampling error and are presented. Also considered are studies in which data from several satellites, or satellite and ground based measurements are combined to improve estimates in the above means. This improvement being brought about not only by increased spatial and temporal coverage but also by a reduction in retrieval error.  相似文献   

15.
Used to test the Milankovitch theory over the last glacial-interglacial cycles, the Louvain-la-Neuve two-dimension Northern Hemisphere climate model shows that orbital and CO2 variations induce, in the climate system, feedbacks sufficient to generate the low frequency part of the climatic variations over the last 200 kyr. Initiation and termination of glacial cycles cannot indeed be explained without invoking both the fast feedbacks associated with atmospheric processes (water vapor, cloud, snow and sea ice) and the slower feedbacks associated with coupling to other parts of the climate system, in particular the land ice-sheet buildup and disintegration. This model shows that long-term changes in the Earth's orbital parameters lead to variations in the amount of solar radiation received at the top of the atmosphere, which in turn act as a pacemaker for climatic variations at the astronomical frequencies, through induced albedo-temperature and greenhouse gases-temperature feedbacks. Spectral analysis of the Northern Hemisphere global ice volume variations simulated under both insolation and CO2 forcings reproduces correctly the relative intensity of the peaks at the orbital frequencies as seen in SPECMAP data. Except for variations with time scales shorter than 5 kyr, the simulated long-term variations of total ice volume are comparable to that reconstructed from deep-sea cores. For example, the model simulates glacial maxima of similar amplitudes at 134 kyr BP and 15 kyr BP, followed by abrupt deglaciations.  相似文献   

16.
The Noah model is a land surface model of the National Centers for Environmental Prediction. It has been widely used in regional coupled weather and climate models (i.e. Weather Research and Forecasting Model, Eta Mesoscale Model) and global coupled weather and climate models (i.e. National Centers for Environmental Prediction Global Forecast System, Climate Forecast System). Therefore, its continued improvement and development are keys to enhancing our weather and climate forecast ability and water and energy flux simulation accuracy. North American Land Data Assimilation System phase 1 (NLDAS‐1) experiments indicated that the Noah model exhibited substantial bias in latent heat flux, total runoff and land skin temperature during the warm season, and such bias can significantly affect coupled weather and climate models. This paper presents a study to improve the Noah model by adding model parameterization processes such as including seasonal factor on leaf area index and root distribution and selecting optimal model parameters. We compared simulated latent heat flux, mean annual runoff and land skin temperature from the Noah control and test versions with measured latent heat flux, land surface skin temperature, mean annual runoff and satellite‐retrieved land surface skin temperature. The results show that the test version significantly reduces biases in latent heat, total runoff and land skin temperature simulation. The test version has been used for the NLDAS phase 2 (NLDAS‐2) to produce 30‐year water flux, energy flux and state variable products to support the US drought monitor of National Integrated Drought Information System. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

17.
Variations in the Earth's climate have had considerable impact on society sectors such as energy, agriculture, fisheries, water resources, and environmental quality. This natural climate variability must be documented and understood in order to assess its potential impacts, its predictability and relationships with human-induced changes. Understanding the mechanisms responsible for natural variability proceeds through a strategy based on the use of a hierarchy of climate models and careful data analysis. In this paper, we examine primarily climate fluctuations on interannual-to-decadal time scales and their climate signature in terms of precipitation and temperature. First, space and time characteristics of two of the major variability modes, the Southern Oscillation (and its associated teleconnection patterns) and the North Atlantic Oscillation, are documented with a focus onto the midlatitudes of the Northern Hemisphere. Then, the current hypothesis regarding the nature of these modes (forced, coupled or internal) are reviewed based on both simulation results and statistical data analyses. Next, we address the potential predictability of seasonal surface temperature and land precipitation using an ensemble of atmospheric model simulations forced by observed sea surface temperatures. Finally, we review the relationships between the atmospheric variability modes and the recent low-frequency trends and suggest a possible influence of anthropogenic effects on these low-frequency variations.  相似文献   

18.
Coarse-resolution satellite albedo products are important for climate change and energy balance research because of their capability to characterize the spatiotemporal patterns of land surface parameters at both the regional and global scales. The accuracy of coarse-resolution products is usually assessed via comparison with in situ measurements. The key issue in the comparison of remote sensing observations with in situ measurements is scaling and uncertainty. This paper presents a strategy for validating 1-km-resolution remote sensing albedo products using field measurements and high-resolution remote sensing observations. Field measurements were collected to calibrate the high-resolution(30 m) albedo products derived from HJ-1a/b images. Then, the calibrated high-resolution albedo maps were resampled(i.e., upscaled) to assess the accuracy of the coarse-resolution albedo products. The samples of field measurements and high-resolution pixels are based on an uncertainty analysis. Two types of coarse-resolution albedo datasets, from global land surface satellite(GLASS) and moderate-resolution imaging spectroradiometer(MODIS), are validated over the middle reaches of the Heihe River in China. The results indicate that the upscaled HJ(Huan Jing means environment in Chinese and this refers to a satellite constellation designed for environment and disaster monitoring by China) albedo, which was calibrated using field measurements, can provide accurate reference values for validating coarse-resolution satellite albedo products. However, the uncertainties in the upscaled HJ albedo should be estimated, and pixels with large uncertainties should be excluded from the validation process.  相似文献   

19.
由于ENVISAT/AATSR资料不同角度热辐射亮度值之间存在较高的相关性从而导致较大误差的产生,本文尝试避开这种误差源,只选取天底观测数据对黄土高原陇东地区整层大气水汽含量及地表温度进行反演.与MODIS整层大气水汽含量产品对比验证表明,本文结果与MODIS产品有一定差异,但是可以直接用于大气透过率的估算.结合野外观测数据对地表温度反演结果的检验表明,最大绝对误差为4.0 ℃,平均相对误差为5.0％,因此,该算法在黄土高原陇东地区应用比较成功.  相似文献   

20.
Aerosol particles over land mainly come from man- made source such as biomass burning, industrial de-bris and natural source such as soil dust, sea salt parti-cles, etc. More and more research results show that, aerosols impact global and regional energy radiative budget; aerosol particles also modify the cloud mi-crophysics, as a result, aerosol particles may change the cloud radiative properties. Aerosol particles also play an important role in many biogeochemical cycles. All the above-menti…  相似文献   

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