Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang,China

Land surface temperature(LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones(the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami(Tuha) Basin, and Pakakuna Mountain Group) using geographical detector(Geodetector) and geographically weighted regression(GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24℃/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09℃/10a in autumn, and showed a warming trend in other seasons. Digital elevation model(DEM), latitude, wind speed, precipitation, normalized difference vegetation index(NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover(LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas.

Spatiotemporal landscape pattern changes and their effects on land surface temperature in greenbelt with semi-arid climate:A case study of the Erbil City,Iraq

Urban expansion of cities has caused changes in land use and land cover(LULC)in addition to transformations in the spatial characteristics of landscape structure.These alterations have generated heat islands and rise of land surface temperature(LST),which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas.Greenbelts are employed as an urban planning containment policy to regulate urban expansion,safeguard natural open spaces,and serve adaptation and mitigation functions.And they are regarded as a powerful measure for enhancing urban environmental sustainability.Despite the fact that,the relation between landscape structure change and variation of LST has been examined thoroughly in many studies,but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well,with the lacking of comprehensive research combing both aspects.Accordingly,this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq.The study utilized remote sensing data to retrieve LST,classified LULC,and calculated landscape metrics for analyzing spatial changes during the study period.The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area.The Pearson's correlation showed the significant effect of Vegetation 1 type(VH),cultivated land(CU),and bare soil(BS)on LST,as increase of LST was related to the decrease of VH and the increases of CU and BS,while,neither Vegetation 2 type(VL)nor built-up(BU)had any effects.Additionally,the spatial distribution of LULC also exhibited significant effects on LST,as LST was strongly correlated with landscape indices for VH,CU,and BS.However,for BU,only aggregation index metric affected LST,while none of VL metrics had a relation.The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment,and further promote sustainable development and enhance well-being in the cities with semi-arid climate.

Spatiotemporal dynamics of land use/land cover(LULC)changes and its impact on land surface temperature:A case study in New Town Kolkata,eastern India

Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

Spatiotemporal detection of land use/land cover changes and land surface temperature using Landsat and MODIS data across the coastal Kanyakumari district, India

This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques. Landsat images are used to estimate the LULC changes and the MODIS data for LST.The Maximum Likelihood Classification(MLC) method is used, and the LULC is classified into six categories: Agriculture Land, Barren Land, Salt Pan, Sandy Beach, Settlement, and Waterbody. Within the two decades of the present change detection study, upheave in the Settlement area of 49.89% is noticed, and the Agriculture Land is exploited by 20.09%. Salt Pan emits a high LST of 31.57°C, and the Waterbodies are noticed with a low LST of 28.9°C. However, the overall rate of LST decreased by 0.56°C during this period. This study will help policymakers make appropriate planning and management to overcome the impact of LULC and LST in the forthcoming years.

Spatiotemporal Evolution Characteristics of Urban Land Surface Temperature Based on Local Climate Zones in Xi’an Metropolitan,China

Local climate zones(LCZs)are an effective nexus linking internal urban structures to the local climate and have been widely used to study urban thermal environment.However,few studies considered how much the temperature changed due to LCZs transformation and their synergy.This paper quantified the change of urban land surface temperature(LST)in LCZs transformation process by combining the land use transfer matrix with zonal statistics method during 2000–2019 in the Xi’an metropolitan.The results show that,firstly,both LCZs and LST had significant spatiotemporal variations and synchrony.The period when the most LCZs were converted was also the LST rose the fastest,and the spatial growth of the LST coincided with the spatial expansion of the built type LCZs.Secondly,the LST difference between land cover type LCZs and built type LCZs gradually widened.And LST rose more in both built type LCZs transferred in and out.Finally,the Xi’an-Xianyang profile showed that the maximum temperature difference between the peaks and valleys of the LST increased by 4.39℃,indicating that localized high temperature phenomena and fluctuations in the urban thermal environment became more pronounced from 2000 to 2019.

Statistical Downscaling Retrieval of Land Surface Temperature in an Area with Complex Landforms in the Eastern Qinling Mountains of China Based on Sentinel-2/3 Satellite Data

The study of land surface temperature(LST)is of great significance for ecosystem monitoring and ecological environmental protection in the Qinling Mountains of China.In view of the contradicting spatial and temporal resolutions in extracting LST from satellite remote sensing(RS)data,the areas with complex landforms of the Eastern Qinling Mountains were selected as the research targets to establish the correlation between the normalized difference vegetation index(NDVI)and LST.Detailed information on the surface features and temporal changes in the land surface was provided by Sentinel-2 and Sentinel-3,respectively.Based on the statistically downscaling method,the spatial scale could be decreased from 1000 m to 10 m,and LST with a Sentinel-3 temporal resolution and a 10 m spatial resolution could be retrieved.Comparing the 1 km resolution Sentinel-3 LST with the downscaling results,the 10 m LST downscaling data could accurately reflect the spatial distribution of the thermal characteristics of the original LST image.Moreover,the surface temperature data with a 10 m high spatial resolution had clear texture and obvious geomorphic features that could depict the detailed information of the ground features.The results showed that the average error was 5 K on April 16,2019 and 2.6 K on July 15,2019.The smaller error values indicated the higher vegetation coverage of summer downscaling result with the highest level on July 15.

Land Surface Temperature Change in Hangzhou Urban Area in Recent 20 Years Based on Landsat Image

Since the reform and opening-up in 1978, the urbanization level of our country has been continuously improved and the urban development has made great progress. However, with the rapid expansion of urban construction land, the population density and building density have been greatly increased, resulting in the urban heat island effect, which has negative impact on the urban thermal environment and restricts the high-quality development of urbanization. This paper focuses on how the urban surface thermal environment of Hangzhou changes in 20 years. In this paper, the characteristics of land surface temperature (LST) in Hangzhou urban area from 2000 to 2020 were studied by using Landsat images. The radiative transfer equation method is used to retrieve the land surface temperature, and the retrieval results are analyzed. The results show that: 1) the land surface temperature in Hangzhou city area has a slight upward trend in the past 20 years;2) the area of high temperature area is expanding;3) the land surface temperature in the city center area has decreased significantly in the past 20 years, while the ground temperature in other areas around the city center has increased significantly.

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.

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.

An overview of the spatial patterns of land surface processes over arid and semiarid regions

With data from the project Collaborative Observation of Semi-arid/Arid Regions in North China, collected during July and September 2008, the spatial patterns of land surface processes over arid and semiarid regions have been investigated based on the ordinary Kriging interpolation approach. Generally, for the radiation processes, downward and upward short-wave radiation have a uniformly increasing trend with latitude, but the spatial patterns of long-wave radiation present notable regional differences: both upward and downward long-wave radiation increase with latitude in the west of North China, while in the east they vary inversely with latitude, suggesting surface temperature and clouds respectively have feedbacks to the long-wave radiation in the west and east of North China. The surface net radiation basically has a negative latitudinal trend. Long-wave radiation budget plays an important role in the spatial pattern of surface net radiation, particularly in the east of North China, although short-wave radiation budget largely determines the magnitude of surface net radiation. For the energy processes, latent and sensible heat flux varies conversely with latitude: more available land surface energy is consumed by evaporating soil water at lower latitudes while more is used for heating the atmosphere at higher latitudes. A soil heat flux maximum and minimum are found in Loess Plateau and Qinghai Plateau respectively, and a maximum is seen in the northeast China.

Case Analyses and Numerical Simulation of Soil ThermalImpacts on Land Surface Energy Budget Based on anOff-Line Land Surface Model

The statistical relationship between soil thermal anomaly and short-term climate change is presented based on a typical case study. Furthermore, possible physical mechanisms behind the relationship are re-vealed through using an off-line land surface model with a reasonable soil thermal forcing at the bottom of the soil layer. In the first experiment, the given heat flux is 5 W m2 at the bottom of the soil layer (in depth of 6.3 m) for 3 months, while only a positive ground temperature anomaly of 0.06°C can be found compared to the control run. The anomaly, however, could reach 0.65°C if the soil thermal conductivity was one order of magnitude larger. It could be even as large as 0.81°C assuming the heat flux at bottom is 10 W m-2. Mean-while, an increase of about 10 W m−2 was detected both for heat flux in soil and sensible heat on land sur-face, which is not neglectable to the short-term climate change. The results show that considerable response in land surface energy budget could be expected when the soil thermal forcing reaches a certain spatial-tem-poral scale. Therefore, land surface models should not ignore the upward heat flux from the bottom of the soil layer. Moreover, integration for a longer period of time and coupled land-atmosphere model are also necessary for the better understanding of this issue.

Simulation Experiments of Land Surface Physical Processes and Ecological Effect over Different Underlying Surface

Based on the existing Land Surface Physical Process Models(Deardorff, Dickinson, LIU, Noilhan, Seller, ZHAO), a Comprehensive Land Surface Physical Process Model (CLSPPM) is developed by considering the different physical processes of the earth's surface-vegetation-atmosphere system more completely. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feas...

Estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985oC to 46.1314oC, and, 18.3437oC to 30.9693oC respectively. Results of Kumasi also show a higher range of temperatures from 32.6986oC to 19.1077oC during the dry season. In the wet season, temperatures ranged from 26.4142oC to -0.898728oC. Among the reasons for the cities of Accra and Kumasi recorded higher than corresponding rural areas’ values can be attributed to the urban heat islands’ phenomenon.

Relief degree of land surface and its influence on population distribution in China

The relief degree of land surface （RDLS） is an important factor for describing the landform at macro-scales. This study defines a concept for RDLS and applies the concept for population distribution study of the entire country. Based on the concept and macro-scale digital elevation model datum and ARC/INFO software, the RDLS at a 10 km×10 km grid size of China is extracted. This paper depicts systemically the spatial distributions of RDLS through analyzing the ratio structure and altitudinal characters of RDLS in China. The conclusions are drawn as follows： the RDLS in more than 63% of the area is less than one （1） （relative altitude is less than 500 m）, reflecting the fact that most of RDLS in China is low. In general, the RDLS in the west is larger than that in the east and so is the south than that of the north in China. The RDLS decreases with the increase of longitude and latitude and the change of RDLS at the latitudes of 28°N, 35°N, 42°N, as well as at the longitudes of 85°E, 102°E, 115°E could reflect the three major ladders of China. In the vertical direction, the RDLS increases with the increase of altitude. Analysis of the correlation between RDLS and population distribution in China and its regional difference shows that the R2 value between RDLS and population density is 0.91 and RDLS is an important factor influencing the spatial distribution of population. More than 85% of the people in China live in areas where the RDLS is less than one （1）, while the population in areas with RDLS greater than 3 accounts only for 0.57% of the total. The regional difference of correlation between RDLS and population within China is significant and such correlation is significant in Central China and South China and weak in Inner Mongolia and Tibet.

Impacts of Land Use and Cover Change on Land Surface Temperature in the Zhujiang Delta

Remote sensing and geographic information systems (GIS) technologies were used to detect land use/cover changes (LUCC) and to assess their impacts on land surface temperature (LST) in the Zhujiang Delta. Multi-temporal Landsat TM and Landsat ETM+ data were employed to identify patterns of LUCC as well as to quantify urban expansion and the associated decrease of vegetation cover. The thermal infrared bands of the data were used to retrieve LST. The results revealed a strong and uneven urban growth,which caused LST to raise 4.56℃in the newly urbanized part of the study area. Overall, remote sensing and GIS technologies were effective approaches for monitoring and analyzing urban growth patterns and evaluating their impacts on LST.

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.

Relief Degree of Land Surface and Population Distribution of Mountainous Areas in China

Evaluation on the population pressure in the mountainous areas is a necessary condition for the protection and good governance. The evaluation depends on accurate population density assessment. Traditional methods used to calculate population density often adopt the administrative region as a scale for statistical analysis. These methods did not consider the effects of the relief degree of land surface(RDLS) on the population distribution. Therefore they cannot accurately reflect the degree of population aggregation, especially in mountainous areas. To explore this issue further, we took the mountainous areas of China as the research area. China has A total area of 666 km2 can be classified as mountainous area,accounting for 69.4% of the country's total landmass. The data used in this research included the digital elevation model(DEM) of China at a scale of 1:1,000,000, National population density raster data, the DEM and the national population density raster data. First, we determined the relief degree of land surface(RDLS). Next, we conducted a correlation analysis between the population distribution and the RDLS using the Statistical Package for Social Science(SPSS). Based on the correlation analysis results and population distribution, this new method was used to revise the provincial population density of themountainous areas. The revised results were used to determine the population pressure of different mountainous areas. Overall, the following results were obtained:(1) The RDLS was low in most mountainous areas(with a value between 0 and 3.5) and exhibited a spatial pattern that followed the physiognomy of China;(2) The relationship between the RDLS and population density were logarithmic, with an R2 value up to 0.798(p<0.05), and the correlation decreased from east to west;(3) The difference between the revised population density(RPD) and the traditional population density(PD) was larger in the southeastern region of China than in the northwestern region;(4) In addition, compared with traditional results, the revised result indicated that the population pressure was larger. Based on these results, the following conclusions were made:(1) the revised method for estimating population density that incorporates the RDLS is reasonable and practical,(2) the potential population pressure in the southeastern mountainous areas is substantial,(3) the characteristics of the terrain in the high mountainous areas are important for the scattered distribution of the population, and(4) the population distribution of mountainous areas in China should be guided by local conditions, such as social, economic, and topographic conditions.

Improvement of Mono-window Algorithm for Retrieving Land Surface Temperature from HJ-1B Satellite Data

The thermal infrared channel (IRS4) of HJ-1B satellite obtains view zenith angles (VZA) up to ±33°. The view angle should be taken into account when retrieving land surface temperature (LST) from IRS4 data. This study aims at improving the mono-window algorithm for retrieving LST from IRS4 data. Based on atmospheric radiative transfer simulations,a model for correcting the VZA effects on atmospheric transmittance is proposed. In addition,a generalized model for calculating the effective mean atmospheric temperature is developed. Validation with the simulated dataset based on standard atmospheric profiles reveals that the improved mono-window algorithm for IRS4 obtains high accuracy for LST retrieval,with the mean absolute error (MAE) and root mean square error (RMSE) being 1.0 K and 1.1 K,respectively. Numerical experiment with the radiosonde profile acquired in Beijing in winter demonstrates that the improved mono-window algorithm exhibits excellent ability for LST retrieval,with MAE and RMSE being 0.6 K and 0.6 K,respectively. Further application in Qinghai Lake and comparison with the Moderate-Resolution Imaging Spectroradiometer (MODIS) LST product suggest that the improved mono-window algorithm is applicable and feasible in actual conditions.

A Modeling Study of Land Surface Process Impacts on Inland Behavior of Typhoon Rananim(2004)

On 12 August 2004, Typhoon Rananim （0414） moved inland over China and stagnated over the Poyang Lake area, resulting in torrential rainfall and severe geologic hazards. The Advanced Weather Research and Forecasting （ARW-WRF） model and its different land surface models （LSMs） were employed to study the impacts of land surface process on the inland behavior of Typhoon Rananim. Results show that simulations, coupled with LSMs or not, have no significant differences in predicting typhoon track, intensity, and largescale circulation. However, the simulations of mesoscale structure, rainfall rate, and rainfall distribution of typhoon are more reasonable with LSMs than without LSMs. Although differences are slight among LSMs, NOAH is better than the others. Based on outputs using the NOAH scheme, the interaction between land surtace and typhoon was explored in this study. Notably, typhoon rainfall and cloud cover can cool land surface, but rainfall expands the underlying saturated wetland area, which exacerbates the asymmetric distribution of surface heat fluxes. Accordingly, an energy frontal zone may form in the lower troposphere that enhances ascending motion and local convection, resulting in heavier rainfall. Moreover, the expanded underlying saturated wetlands provide plentiful moisture and unstable energy for the maintenance of Typhoon Rananim and increased rainfall in return.