Temporal and Spatial Variation of Surface Albedo in Tibetan Plateau during 1982-2000

[Objective] Temporal and spatial variation of surface albedo in Tibetan Plateau were studied in our paper.[Method] Based on NOAA/AVHRR data,different algorithms were used to retrieve surface albedo in Tibetan Plateau,and it showed that the result of Stroeve was mostly close to observed data.Based on retrieval algorithm from Stroeve,the spatial distribution of surface albedo in Tibetan Plateau was obtained by means of NOAA/AVHRR data in 1982-2000.[Result] The distribution of annual mean surface albedo in Tibetan Plateau was identical with that of geographical zone in plateau area;annual mean surface albedo in plateau area showed slight decrease trend which was different in various regions;monthly surface albedo in plateau area had obviously zonal distribution and changed with time evidently.[Conclusion] Our study will be helpful to improving the parameterization scheme of surface albedo in climate model,revealing the internal mechanism of local and regional climate change and enhancing the level of long-term climate forecast.

Study on the Remote Sensing of Surface Albedo in the Horqin Sand Land

The surface albedo which is affected by the earth surface coverage or other surface characteristics is one of the important factors impacting remote sensing image information and therefore it can be calculated by integrating land coverage types with information of remote sensing images.Horqin sand land which was taken as an experimental area for study on Landsat-TM topography and atmospheric correction,then the Landsat-TM data inversion formula established by Liang was used to calculate the experimental zone albedo map;correlation analysis was performed to the surface albedo map and the land-use maps which was acquired by supervision and classification.The results revealed significant relations between land-use types and the surface albedo of study area.Additionally,the surface albedo and NDVI of the study area were statistically analyzed to obtain the study area's surface albedo and NDVI dependent equation.

Spatial Variation in CO_(2) Concentration Improves the Simulated Surface Air Temperature Increase in the Northern Hemisphere

The increasing concentration of atmospheric CO_(2) since the Industrial Revolution has affected surface air temperature.However,the impact of the spatial distribution of atmospheric CO_(2) concentration on surface air temperature biases remains highly unclear.By incorporating the spatial distribution of satellite-derived atmospheric CO_(2) concentration in the Beijing Normal University Earth System Model,this study investigated the increase in surface air temperature since the Industrial Revolution in the Northern Hemisphere(NH) under historical conditions from 1976-2005.In comparison with the increase in surface temperature simulated using a uniform distribution of CO_(2),simulation with a nonuniform distribution of CO_(2)produced better agreement with the Climatic Research Unit(CRU) data in the NH under the historical condition relative to the baseline over the period 1901-30.Hemispheric June-July-August(JJA) surface air temperature increased by 1.28℃ ±0.29℃ in simulations with a uniform distribution of CO_(2),by 1.00℃±0.24℃ in simulations with a non-uniform distribution of CO_(2),and by 0.24℃ in the CRU data.The decrease in downward shortwave radiation in the non-uniform CO_(2) simulation was primarily attributable to reduced warming in Eurasia,combined with feedbacks resulting from increased leaf area index(LAI) and latent heat fluxes.These effects were more pronounced in the non-uniform CO_(2)simulation compared to the uniform CO_(2) simulation.Results indicate that consideration of the spatial distribution of CO_(2)concentration can reduce the overestimated increase in surface air temperature simulated by Earth system models.

Relationships Between Surface Albedo,Soil Thermal Parameters and Soil Moisture in the Semi-arid Area of Tongyu,Northeastern China

Continuous observation data collected over the whole year of 2004 on a cropland surtace m Tongyu, a senti-arid area of northeastern China （44°25＇N, 122°52＇E）, have been used to investigate the variations of surface albedo and soil thermal parameters, including heat capacity, thermal conductivity and thermal diffusivity, and their relationships to soil moisture. The diurnal variation of surface albedo appears as a U shape curve on sunny days. Surface albedo decreases with the increase of solar elevation angle, and it tends to be a constant when solar elevation angle is larger than 40°. So the daily average surface albedo was computed using the data when solar elevation angle is larger than 40° Mean daily surface albedo is found to decrease with the increase of soil moisture, showing an exponential dependence on soil moisture. The variations of soil heat capacity are small during Julian days 90 300. Compared with the heat capacity, soil thermal conductivity has very gentle variations during this period, but the soil thermal diffusivity has wide variations during the same period. The soil thermal conductivity is found to increase as a power function of soil moisture. The soil thermal diffusivity increases firstly and then decreases with the increase of soil moisture.

Variability of Soil Moisture and Its Relationship with Surface Albedo and Soil Thermal Parameters over the Loess Plateau

Data from July 2006 to June 2008 observed at SACOL （Semi-Arid Climate and Environment Observatory of Lanzhou University, 35.946°N, 104.137°E, elev. 1961 m）, a semi-arid site in Northwest China, are used to study seasonal variability of soil moisture, along with surface albedo and other soil thermal parameters, such as heat capacity, thermal conductivity and thermal diffusivity, and their relationships to soil moisture content. The results indicate that surface albedo decreases with increases in soil moisture content, showing a typical exponential relation between the surface albedo and the soil moisture. The heat capacity, the soil thermal diffusivity, and soil thermal conductivity show large variations between Julian day 90-212 and 450-578. The soil thermal conductivity is found to increase as a power function of soil moisture. Soil heat capacity and soil thermal diffusivity increase with increases in soil moisture. The SACOL observed soil moisture are also used to validate the AMSR-E/AQUA retrieved soil moisture and there is good agreement between them. The analysis of the relationship between satellite retrieved soil moisture and precipitation suggests that the variability of soil moisture depends on the variation of precipitation over the Loess Plateau.

A Study on Parameterization of Surface Albedo over Grassland Surface in the Northern Tibetan Plateau

The relationship of surface albedo with the solar altitude angle and soil moisture is analyzed based on two-year （January 2002 to December 2003） observational data from the AWS （Automatic Weather Station） at MS3478 in the northern Tibetan Plateau during the experimental period of CEOP/CAMP-Tibet （Coordinated Enhanced Observing Period Asia-Australia Monsoon Project on the Tibetan Plateau）. As a double-variable （solar altitude angle and soil moisture） function, surface albedo varies inconspicuously with any single factor. By using the method of approximately separating the double-variable function into two, one-factor functions （product and addition）, the relationship of albedo with these two factors presents much better. The product and additional empirical formulae of albedo are then preliminarily fitted based on long-term experimental data. By comparison with observed values, it is found that the parameterization formulae fitted by using observational data are mostly reliable and their correlation coefficients are both over 0.6. The empirical formulae of albedo though, for the northern Tibetan Plateau, need to be tested by much more representative observational data with the help of numerical models and the retrieval of remote sensing data. It is practical until it is changed into effective parameterization formulae representing a grid scale in models.

Comprehensive Study on the Influence of Evapotranspiration and Albedo on Surface Temperature Related to Changes in the Leaf Area Index

Many studies have investigated the influence of evapotranspiration and albedo and emphasize their separate effects but ignore their interactive influences by changing vegetation status in large amplitudes. This paper focuses on the comprehensive influence of evapotranspiration and albedo on surface temperature by changing the leaf area index （LAD between 30^-90~N. Two LAI datasets with seasonally different amplitudes of vegetation change between 30^-90~N were used in the simulations. Seasonal differences between the results of the simulations are compared, and the major findings are as follows. （1） The interactive effects of evapotranspiration and albedo on surface temperature were different over different regions during three seasons [March-April-May （MAM）, June-July-August （JJA）, and September-October-November （SON）], i.e., they were always the same over the southeastern United States during these three seasons but were opposite over most regions between 30°-90°N during JJA. （2） Either evapotranspiration or albedo tended to be dominant over different areas and during different seasons. For example, evapotranspiration dominated almost all regions between 30^-90~N during JJA, whereas albedo played a dominant role over northwestern Eurasia during MAM and over central Eurasia during SON. （3） The response of evapotranspiration and albedo to an increase in LAI with different ranges showed different paces and signals. With relatively small amplitudes of increased LAI, the rate of the relative increase in evapotranspiration was quick, and positive changes happened in albedo. But both relative changes in evapotranspiration and albedo tended to be gentle, and the ratio of negative changes of albedo increased with relatively large increased amplitudes of LAI.

Agriculture Development-induced Surface Albedo Changes and Climatic Implications Across Northeastern China

To improve the understandings on regional climatic effects of past human-induced land cover changes,the surface albedo changes caused by conversions from natural vegetation to cropland were estimated across northeastern China over the last 300 years,and its climatic effects were simulated by using the Weather Research and Forecasting (WRF) model.Essential natural vegetation records compiled from historical documents and regional optimal surface albedo dataset were used.The results show that the surface albedo decreased by 0.01-0.03 due to conversions from grassland to cropland in the Northeast China Plain and it increased by 0.005-0.015 due to conversions from forests to cropland in the surrounding mountains.As a consequence,in the Northeast China Plain,the surface net radiation increased by 4-8 W/m 2,2-5 W/m 2,and 1-3 W/m 2,and the climate was therefore warmed by 0.1℃-0.2℃、0.1℃-0.2℃、 0.1℃-0.3 ℃ in the spring,autumn and winter,respectively.In the surrounding mountain area,the net radiation decreased by less than 1.5 W/m 2,and the climate was therefore cooled too slight to be detected.In summer,effects of surface albedo changes on climate were closely associated with moisture dynamics,such as evapotranspiration and cloud,instead of being merely determined by surface radiation budget.The simulated summer climatic effects have large uncertainties.These findings demonstrate that surface albedo changes resulted in warming climate effects in the non-rainy seasons in Northeast China Plain through surface radiation processes while the climatic effects in summer could hardly be concluded so far.

Improvement of Surface Albedo Simulations over Arid Regions

To improve the simulation of the surface radiation budget and related thermal processes in arid regions, three sophisticated surface albedo schemes designed for such regions were incorporated into the Biosphere- Atmosphere Transfer Scheme （BATS）. Two of these schemes are functions of the solar zenith angle （SZA）, where the first one has one adjustable parameter defined as SZA1 scheme, and the second one has two empirical parameters defined as SZA2 scheme. The third albedo scheme is a function of solar angle and soil water that were developed based on arid-region observations from the Dunhuang field experiment （DHEX） （defined as DH scheme）. We evaluated the performance of the original and newly-incorporated albedo schemes within BATS using the in-situ data from the Oasis System Energy and Water Cycle Field Experiment that was carried out in JinTa, Gansu arid area （JTEX）. The results indicate that a control run by the original version of the BATS generates a constant albedo, while the SZA1 and SZA2 schemes basically can reproduce the observed diurnal cycle of surface albedo, although these two schemes still underestimate the albedo when SZA is high in the early morning and late afternoon, and overestimate it when SZA is low during noontime. The SZA2 scheme has a better overall performance than the SZA1 scheme. In addition, BATS with the DH scheme slightly improves the albedo simulation in magnitude as compared to that from the control run, but a diurnal cycle of albedo is not produced by this scheme. The SZA1 and SZA2 schemes significantly increase the surface absorbed solar radiation by nearly 70 W m^-2, which further raises the ground temperature by 6 K and the sensible heat flux by 35 W m^-2. The increased solar radiation, heat flux, and temperature are more consistent with the observations that those from the control run. However, a significant improvement in these three variables is not found in BATS with the DH scheme due to the neglect of the diurnal cycle of albedo. Further analysis indicates that during cloudy days the solar radiation simulations of BATS with these three schemes are not in a good agreement with the observations, which implies that a more realistic partitioning of diffuse and direct radiation is needed in future land surface process simulations.

Land Surface Albedo Variations in Sanjiang Plain from 1982 to 2015: Assessing with GLASS Data

As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth’s surface energy budget(SEB). Since the Sanjiang Plain has been severely affected by human activities(e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite(GLASS) broadband surface albedo product. The results showed that: 1) an increasing annual trend(+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend(+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.

Significant Variations of Surface Albedo during a Snowy Period at Xianghe Observatory,China

Surface albedo over typical types of surfaces in the North China Plain was observed using a Multi-field Albedo Observation System before and after several snowfalls from 13 to 27 February 2005. Dramatic variations of the surface albedos of bare land, a frozen pond, and withered grassland during that period were analyzed. Under cloudy sky, the mean surface albedo of bare land was about 0.23, but it immediately rose to 0.85 when the surface was covered by fresh snow. The albedo decreased gradually to normal levels afterwards. The melting processes were different depending on the characteristics of the underlying surfaces. For example, over grassland the surface albedo was relatively lower after snowfall, and as a result, more solar energy could be absorbed and consequently the snow melting process was accelerated. Significant variations of surface albedo cannot be easily captured by satellite observations; therefore, detailed measurements of surface albedo and related parameters are essential for determining the impact of snow on the energy budget of the Earth.

Spatiotemporal variation of surface albedo and its influencing factors in northern Xinjiang, China

Surface albedo is a quantitative indicator for land surface processes and climate modeling,and plays an important role in surface radiation balance and climate change.In this study,by means of the MCD43A3 surface albedo product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS),we analyzed the spatiotemporal variation,persistence status,land cover type differences,and annual and seasonal differences of surface albedo,as well as the relationship between surface albedo and various influencing factors(including Normalized Difference Snow Index(NDSI),precipitation,Normalized Difference Vegetation Index(NDVI),land surface temperature,soil moisture,air temperature,and digital elevation model(DEM))in the north of Xinjiang Uygur Autonomous Region(northern Xinjiang)of Northwest China from 2010 to 2020 based on the unary linear regression,Hurst index,and Pearson's correlation coefficient analyses.Combined with the random forest(RF)model and geographical detector(Geodetector),the importance of the above-mentioned influencing factors as well as their interactions on surface albedo were quantitatively evaluated.The results showed that the seasonal average surface albedo in northern Xinjiang was the highest in winter and the lowest in summer.The annual average surface albedo from 2010 to 2020 was high in the west and north and low in the east and south,showing a weak decreasing trend and a small and stable overall variation.Land cover types had a significant impact on the variation of surface albedo.The annual average surface albedo in most regions of northern Xinjiang was positively correlated with NDSI and precipitation,and negatively correlated with NDVI,land surface temperature,soil moisture,and air temperature.In addition,the correlations between surface albedo and various influencing factors showed significant differences for different land cover types and in different seasons.To be specific,NDSI had the largest influence on surface albedo,followed by precipitation,land surface temperature,and soil moisture;whereas NDVI,air temperature,and DEM showed relatively weak influences.However,the interactions of any two influencing factors on surface albedo were enhanced,especially the interaction of air temperature and DEM.NDVI showed a nonlinear enhancement of influence on surface albedo when interacted with land surface temperature or precipitation,with an explanatory power greater than 92.00%.This study has a guiding significance in correctly understanding the land-atmosphere interactions in northern Xinjiang and improving the regional land-surface process simulation and climate prediction.

ESTIMATION OF VEGETATIVE SURFACE ALBEDO IN THE KUSHIRO MIRE WITH LANDSAT TM DATA──A New Approach to Atmospheric and Spectral Corrections

A method has been developed for estimating the filtered narrow band surface albedo with Landsat/TM date. In this method, the surface albedo from fitered range of Landsat/TM is converted to the surface albedo with unfiltered spcectral range. The atmospheric effects on each channel are systematically different, because of the different spectral behavior of atmospheric parameters.As a result, in this study, atmospheric correction has ho done respectively in different parameters for visible and infrared channels. The surface albedos of the Kushiro Mire gotten with this method were compared with the observed date there. The results show that the satellite inferred albedos have a good agreement tO the diurnal mean of ground observed albedos with 3% systematic error. There is a seasonal variation of albedo in high and low mires, the albedo decreased gradually from April to July and reached its minimum in July, further it rose gradually from August to October. It is also clear that there is a characteristic pattern of surface distribution according to the vegetation types of this area. The average surface albedos of each type of community are 0.164 for Sphagnum, 0.175 for Carex, 0.179 for Pragmites and 0.166 for Alnus. In the other words, the albedo in high mire (mainly covered by Sphagnum) is lower than that in low mire (mainly covered by phragmites and Carex).

SOME IMPORTANT CHARACTERISTICS OFSURFACE ALBEDO OF CHINA IN RECENT YEARS

Based on the radiation data from 14 representive stations from 1986 to 1990 and the distribution situations of vegetetion and soil, come new characteristics of surface albedo in China are analysed. In different regions, surface albedo is different due to difference of surface features. Even though in the same region, surface albedo varies with seasonal variation. However, in the seasons and regions without snow cover, the long-term and interannual variation of surface albedo is not obvious.On the viewpoint of climate, the values of surface albedo mainly depend on whether there is snow cover or not. The interannual variation of surface albedo is greater to the north of 50°N, with a variation range of 5%. The influences of geographical conditions, such as latitude, elevation and air pollution, are also analysed.

ON THE ESTIMATION OF SURFACE ALBEDO USING SATELLITE DATE

The method to determine the surface albedo using satellite date hasbeen developed and discussed. The relatons betwam the planetary albedo andsurfoce albedo in clear skies are derived with the help of the radiative transfermodelling. To improve the accuracy of the denved surfoce albedo, theparameter X0, i.e., the ratio of the reflected to the total extinction radiation isintroduced into this model. The influences of the model paramenters on thesurfoce albedo have been analyzed. It is found that the error in the derivedsurfoce albedo due to the paramaters together is less than that caused by oulyone parameter because of the complementarity of the parameters. Test resultsin 22 stations over China have been given using the Geostationary SatelliteGMS. The results are generally agreeable except for the case of snow/ice cover.

Estimating Monthly Surface Air Temperature Using MODIS LST Data and an Artificial Neural Network in the Loess Plateau, China

Air temperature(Ta)datasets with high spatial and temporal resolutions are needed in a wide range of applications,such as hydrology,ecology,agriculture,and climate change studies.Nonetheless,the density of weather station networks is insufficient,especially in sparsely populated regions,greatly limiting the accuracy of estimates of spatially distributed Ta.Due to their continuous spatial coverage,remotely sensed land surface temperature(LST)data provide the possibility of exploring spatial estimates of Ta.However,because of the complex interaction of land and climate,retrieval of Ta from the LST is still far from straightforward.The estimation accuracy varies greatly depending on the model,particularly for maximum Ta.This study estimated monthly average daily minimum temperature(Tmin),average daily maximum temperature(Tmax)and average daily mean temperature(Tmean)over the Loess Plateau in China based on Moderate Resolution Imaging Spectroradiometer(MODIS)LST data(MYD11A2)and some auxiliary data using an artificial neural network(ANN)model.The data from 2003 to 2010 were used to train the ANN models,while 2011 to 2012 weather station temperatures were used to test the trained model.The results showed that the nighttime LST and mean LST provide good estimates of Tmin and Tmean,with root mean square errors(RMSEs)of 1.04℃ and 1.01℃,respectively.Moreover,the best RMSE of Tmax estimation was 1.27℃.Compared with the other two published Ta gridded datasets,the produced 1 km×1 km dataset accurately captured both the temporal and spatial patterns of Ta.The RMSE of Tmin estimation was more sensitive to elevation,while that of Tmax was more sensitive to month.Except for land cover type as the input variable,which reduced the RMSE by approximately 0.01℃,the other vegetation-related variables did not improve the performance of the model.The results of this study indicated that ANN,a type of machine learning method,is effective for long-term and large-scale Ta estimation.

沙尘源区LST/Albedo时序变化与TSP的对比分析——以2001年春季中国北方强沙尘过程为例

20 0 1年春季 ,中国北方多次受到沙尘天气的影响 ,给人们的生产、生活带来严重的威胁 ,引起了亚洲国家的广泛重视。利用卫星监测数据采集沙尘云图变化、运移路径、地表覆盖和沙尘过程中的地面反照率、温度、湿度、粗糙度等物理参数反演实验结果 ,可以弥补地面观测站点稀少、数据不连续的缺陷。本文以 2 0 0 1年 3月到 5月的几次沙尘天气为例 ,介绍基于地表覆盖的AVHRR的LST/Albedo反演结果与TSP (沙尘干量 )对比分析 ,发现它们具有较好的相关性。从而反映了沙尘暴发生前后地表能量的变化状况 ,能为预测预警沙尘天气的危害提供及时客观的空间信息。

Observation and Study of Land Surface Parameters over Gobi in Typical Arid Region

According to the need of popular land surface process models, characteristics and rules of some key land surface process and soil parameters over Gobi in typical arid region of Northwest China are analyzed by using the data observed during the intensive observation period of the Dunhuang Land–Surface Process Field Experiment (DLSPFE) (May–June 2000). Using the relative reflection as weighting factor, the weighted mean of the surface albedo over Dunhuang Gobi in typical arid region is calculated and its values are 0.255 ± 0.021. After canceling the interference of the buildings, the mean values of the roughness length averaged with logarithm is 0.0019 ± 0.00071 m. After removing the influence of the oasis, the soil wetness factor computed with data under condition of no precipitation is 0.0045. After removing the influence of the precipitation , the mean values of the soil heat capacity over Dunhuang Gobi in typical arid region is 1.12 × 106 J m−3K−1, a bit smaller than the values observed in HEIFE. But the soil heat diffusivity and conductivity are about one of those observed in HEIFE. The soil water content over Dunhuang Gobi in typical synoptic condition is very little and does not exceed 1% basically.

Evaluating the impacts of land use and land cover changes on surface air temperature using the WRF-mosaic approach

Satellite-derived land surface data in 1980 and 2010 were used to represent land use and land cover（LULC） changes caused by the rapid economic development and human activities that have occurred over the past few decades in East Asia and China. The effects of LULC changes on the radiation budget and 2-m surface air temperature（SAT） were explored for the period using the Weather Research and Forecasting（WRF） model. The mosaic approach, which considers the N-most abundant land use types within a model grid cell（here, N = 3） and precisely describes the subgridscale LULC changes, was adopted in the integrations. The impacts of LULC changes based on two 36-year integrations showed that SAT generally decreased, with the sole exception being over eastern China, resulting in decreased SAT in China（-0.062 °C） and East Asian land areas（EAL,-0.061 °C）. The LULC changes induced changes in albedo, which influenced the radiation budget. The radiative forcings at the top of the atmosphere were-0.56 W m-2 across the whole of China, and-0.50 W m-2 over EAL. Meanwhile, the altered roughness length mainly influenced near-surface wind speeds, large-scale and upward moisture fluxes, latent heat fluxes, and cloud fractions at different altitudes. Though the impacts caused by the LULC changes were generally smaller at regional scales, the values at local scales were much stronger.

Land surface temperature and spectral indices: A seasonal study of Raipur City

This case study evaluates the seasonal variability of the Pearson's linear correlation coefficient of land surface temperature(LST)with some spectral indices like NDVI,NDWI,NDBI,and NDBaI by using a series of Landsat images for 1991-92,1995-96,1999-00,2004-05,2009-10,2014-15,and 2018-19.The results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI(0.71)and NDBaI(0.52)while it builds a negative correlation with NDVI(-0.44).The LST-NDWI correlation is insignificant.The best correlation is noticed in the post-monsoon period,while the least correlation is observed in the winter season.This study can support the environmental planning to build a sustainable city under a similar environment.