scholarly journals Modelling surface temperature and radiation budget of snow-covered complex terrain

2021 ◽  
Author(s):  
Alvaro Robledano ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Fanny Larue ◽  
Inès Ollivier
Keyword(s):  
Surface Temperature ◽  
Energy Budget ◽  
Complex Terrain ◽  
Spatial Variations ◽  
Monte Carlo Algorithm ◽  
Absorption Enhancement ◽  
Atmospheric Effects ◽  
Landsat 8 ◽  
Topographic Effects ◽  
Radiative Processes

Abstract. The surface temperature controls the temporal evolution of the snowpack playing a key role in many physical processes such as metamorphism, snowmelt, etc. It shows large spatial variations in mountainous areas because the surface energy budget is affected by specific radiative processes that occur due to the topography, such as the modulation of the irradiance by the local slope, the shadows and the re-illumination of the surface from surrounding slopes. These topographic effects are often neglected in large scale models considering the surface as flat and smooth. Here we aim at estimating the surface temperature and the energy budget of snow-covered complex terrains, in order to evaluate the relative importance of the different processes that control the spatial variations. For this, a modelling chain is implemented to derive surface temperature in a kilometre-wide area from local radiometric and meteorological measurements at a single station. The main component is the Rough Surface Ray-Tracing (RSRT) model, based on a photon transport Monte Carlo algorithm to quantify the incident and reflected radiation on every facet of a mesh, describing the snow-covered surface. RSRT is coupled to a surface scheme in order to estimate the complete energy budget from which the surface temperature is solved. To assess the modelling chain performance, we use in situ measurements of surface temperature and satellite thermal observations (TIRS sensor aboard Landsat-8) in the Col du Lautaret area, in the French Alps. The satellite images are corrected from atmospheric effects with a single-channel algorithm. The results of the simulation show (i) an agreement between the simulated and observed surface temperature at the station for a diurnal cycle in winter within 0.3 °C; (ii) the spatial variations of surface temperature are on the order of 5 to 10 °C between opposed slope orientations and are well represented by the model; (iii) the importance of the considered topographic effects is up to 1 °C, the most important being the modulation of solar irradiance by the topography, followed by altitudinal variations in air temperature, long-wave thermal emission from surrounding terrain, spectral dependence of snow albedo, and absorption enhancement due to multiple bounces of photons in steep terrain. These results show the necessity of considering the topography to correctly assess the energy budget and the surface temperature of snow-covered complex terrain.

Surface temperature and radiation budget of snow-covered complex terrains

2021 ◽  
Author(s):  
Alvaro Robledano ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Fanny Larue ◽  
Inès Ollivier
Keyword(s):  
Surface Temperature ◽  
Single Channel ◽  
Spatial Variations ◽  
In Situ Measurements ◽  
Surface Energy Budget ◽  
Radiation Budget ◽  
Atmospheric Effects ◽  
Landsat 8 ◽  
The Impact

<p>The temporal evolution of the snowpack is controlled by the surface temperature, which plays a key role in physical processes such as snowmelt. It shows large spatial variations in mountainous areas, where the illumination conditions are variable and depend on the topography. The surface energy budget is affected by the particular processes that occur in these areas, such as the modulation of the illumination by local slope and the re-illumination of the surface from surrounding slopes. These topography effects are often neglected in models, considering the surface as flat and smooth. Here we aim at estimating the surface temperature and the radiation budget of snow-covered complex terrains, in order to evaluate the role of the different processes that control their spatial variations. For this, a modelling chain is implemented to derive surface temperature from in-situ measurements. The main component is the Rough Surface Ray-Tracing (RSRT) model, based on a photon transport algorithm to quantify the impact of surface roughness in snow-covered areas. It is coupled to a surface scheme in order to estimate the radiation budget. To validate the model, we use in-situ measurements and satellite thermal observations (TIRS sensor aboard Landsat-8) in the Col du Lautaret area, in the French Alps. The satellite images are corrected from atmospheric effects with a single-channel algorithm. The results of the simulations show (i) an agreement between the simulated and observed surface temperature for a diurnal cycle in winter; (ii) the spatial variations of surface temperature are on the order of 5 to 10°C between opposed slope orientations; (iii) the agreement with satellite observations is improved when considering topography effects. It is therefore necessary to account for these effects to estimate the spatial variations of the radiation budget and surface temperature over snow-covered complex terrain. </p>

scholarly journals First Comparisons of Surface Temperature Estimations between ECOSTRESS, ASTER and Landsat 8 over Italian Volcanic and Geothermal Areas

2020 ◽  
Vol 12 (1) ◽  
pp. 184 ◽  
Author(s):  
Malvina Silvestri ◽  
Vito Romaniello ◽  
Simon Hook ◽  
Massimo Musacchio ◽  
Sergio Teggi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Heat Waves ◽  
Space Station ◽  
Volcanic Eruptions ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Effects ◽  
Landsat 8 ◽  
Surface Temperatures

The ECO System Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a new space mission developed by NASA-JPL which launched on July 2018. It includes a multispectral thermal infrared radiometer that measures the radiances in five spectral channels between 8 and 12 μm. The primary goal of the mission is to study how plants use water by measuring their temperature from the vantage point of the International Space Station. However, as ECOSTRESS retrieves the surface temperature, the data can be used to measure other heat-related phenomena, such as heat waves, volcanic eruptions, and fires. We have cross-compared the temperatures obtained by ECOSTRESS, the Advanced Spaceborne Thermal Emission and Reflectance radiometer (ASTER) and the Landsat 8 Thermal InfraRed Sensor (TIRS) in areas where thermal anomalies are present. The use of ECOSTRESS for temperature analysis as well as ASTER and Landsat 8 offers the possibility of expanding the availability of satellite thermal data with very high spatial and temporal resolutions. The Temperature and Emissivity Separation (TES) algorithm was used to retrieve surface temperatures from the ECOSTRESS and ASTER data, while the single-channel algorithm was used to retrieve surface temperatures from the Landsat 8 data. Atmospheric effects in the data were removed using the moderate resolution atmospheric transmission (MODTRAN) radiative transfer model driven with vertical atmospheric profiles collected by the University of Wyoming. The test sites used in this study are the active Italian volcanoes and the Parco delle Biancane geothermal area (Italy). In order to test and quantify the difference between the temperatures retrieved by the three spaceborne sensors, a set of coincident imagery was acquired and used for cross comparison. Preliminary statistical analyses show a very good agreement in terms of correlation and mean values among sensors over the test areas.

scholarly journals The Atmospheric Compensation Component of a Landsat Land Surface Temperature (LST) Product: Assessment of Errors Expected for a North American Test Product

2014 ◽  
Vol XL-1 ◽  
pp. 73-79
Author(s):  
M. J. Cook ◽  
J. R. Schott
Keyword(s):  
Surface Temperature ◽  
North American ◽  
Land Surface ◽  
Quality Data ◽  
Initial Assessment ◽  
Atmospheric Effects ◽  
Landsat 8 ◽  
Atmospheric Compensation ◽  
Compensation Approach ◽  
Emissivity Compensation

The Landsat archive of thermal data (Landsats 4, 5 and 7) has gone through a rigorous calibration assessment and update. However, in order to be useful to most users the calibrated sensor reaching radiance must be corrected to surface temperatures by first compensating for atmospheric effects and then emissivity variations. The USGS is exploring the possibility of producing a LST product through a joint program with RIT (the atmospheric compensation component) and JPL (the emissivity compensation component). This paper addresses the atmospheric compensation component for an initial North American pilot study. In particular, the results of a comparison of retrieved water surface temperature (where emissivity is well known) and truth temperatures for over 800 sites are presented. The errors are broken down by cloud conditions with extremely good results for cloud-free conditions (errors less than 1 K). The results of the error assessment for North America by cloud class are presented along with a discussion of potential quality data for a LST product. An initial assessment of the LST errors observed for Landsat 8 bands 10 and 11 are also presented. The next steps on this effort include testing of a global atmospheric compensation approach and full integration of the atmospheric and emissivity compensation tools into an operational LST product.

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals The Challenge of the Urban Compact Form: Three-Dimensional Index Construction and Urban Land Surface Temperature Impacts

2021 ◽  
Vol 13 (6) ◽  
pp. 1067
Author(s):  
Han Yan ◽  
Kai Wang ◽  
Tao Lin ◽  
Guoqin Zhang ◽  
Caige Sun ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Form ◽  
Three Dimensional ◽  
Compact Form ◽  
Landsat 8 ◽  
Driving Mechanism ◽  
Building Density ◽  
Building Height

Cities are growing higher and denser, and understanding and constructing the compact city form is of great importance to optimize sustainable urbanization. The two-dimensional (2D) urban compact form has been widely studied by previous researchers, while the driving mechanism of three-dimensional (3D) compact morphology, which reflects the reality of the urban environment has seldom been developed. In this study, land surface temperature (LST) was retrieved by using the mono-window algorithm method based on Landsat 8 images of Xiamen in South China, which were acquired respectively on 14 April, 15 August, 2 October, and 21 December in 2017, and 11 March in 2018. We then aimed to explore the driving mechanism of the 3D compact form on the urban heat environment (UHE) based on our developed 3D Compactness Index (VCI) and remote sensing, as well as Geo-Detector techniques. The results show that the 3D compact form can positively effect UHE better than individual urban form construction elements, as can the combination of the 2D compact form with building height. Individually, building density had a greater effect on UHE than that of building height. At the same time, an integration of building density and height showed an enhanced inter-effect on UHE. Moreover, we explore the temporal and spatial UHE heterogeneity with regards to 3D compact form across different seasons. We also investigate the UHE impacts discrepancy caused by different 3D compactness categories. This shows that increasing the 3D compactness of an urban community from 0.016 to 0.323 would increase the heat accumulation, which was, in terms of satellite derived LST, by 1.35 °C, suggesting that higher compact forms strengthen UHE. This study highlights the challenge of the urban 3D compact form in respect of its UHE impact. The related evaluation in this study would help shed light on urban form optimization.

Earth's balanced climates in view of their energy budgets

2021 ◽  
Author(s):  
Thomas Anderl
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Energy Budget ◽  
Energy Budgets ◽  
Temperature Dependency ◽  
Energy Balancing ◽  
Atmospheric Water ◽  
Atmospheric Absorption ◽  
Rainfall Events ◽  
Characteristic Concentration

Abstract Earth’s well-known energy budget scheme is subjected to variations representing changes of insolation and atmospheric absorption. The Charney Report variability cases of doubled atmospheric CO2 concentration and insolation increase by 2 % are found reproducible. The planetary emissivity is revealed linear to surface temperature, conformant with measurements. Atmospheric water vapor with its characteristic concentration-temperature dependency appears as a major component in Earth’s energy balancing mechanisms. From this, shift towards fewer and stronger rainfall events is prescribed for rising temperatures.

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