Latent heat flux estimation using trapezoidal relationship between MODIS land surface temperature and fraction of vegetation – application and validation in a humid tropical region

2014 ◽  
Vol 5 (11) ◽  
pp. 981-990 ◽  
Author(s):  
Keerthi Laxmi ◽  
Lakshman Nandagiri
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Tropical Region ◽  
Modis Land Surface Temperature ◽  
Heat Flux Estimation ◽  
Flux Estimation

scholarly journals Simulation of Land Surface Climate over China with RegCM4.5: Verification and Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Minghao Yang ◽  
Ruiting Zuo ◽  
Liqiong Wang ◽  
Xiong Chen
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface Temperature ◽  
South China ◽  
Land Surface ◽  
Reanalysis Data ◽  
Surface Evaporation

The ability of RegCM4.5 using land surface scheme CLM4.5 to simulate the physical variables related to land surface state was investigated. The NCEP-NCAR reanalysis data for the period 1964–2003 were used to drive RegCM4.5 to simulate the land surface temperature, precipitation, soil moisture, latent heat flux, and surface evaporation. Based on observations and reanalysis data, a few land surface variables were analyzed over China. The results showed that some seasonal features of land surface temperature in summer and winter as well as its magnitude could be simulated well. The simulation of precipitation was sensitive to region and season. The model could, to a certain degree, simulate the seasonal migration of rainband in East China. The overall spatial distribution of the simulated soil moisture was better in winter than in summer. The simulation of latent heat flux was also better in winter. In summer, the latent heat flux bias mainly arose from surface evaporation bias in Northwest China, and it primarily arose from vegetation evapotranspiration bias in South China. In addition, the large latent heat flux bias in South China during summer was probably due to less precipitation generated in the model and poor representation of vegetation cover in this region.

scholarly journals Evaluation of functional properties of various types of vegetation cover using remotely sensed data analysis

2010 ◽  
Vol 4 (Special Issue 2) ◽  
pp. S49-S58 ◽  
Author(s):  
J. Brom ◽  
J. Procházka ◽  
A. Rejšková
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Remotely Sensed Data ◽  
Mean Values

The dissipation of solar energy and consequently the formation of the hydrological cycle are largely dependent on the structural and optical characteristics of the land surface. In our study, we selected seven units with different types of vegetation in the Mlýnský and Horský catchments (South-Eastern part of the Šumava Mountains, Czech Republic) for the assessment of the differences in their functioning expressed through the surface temperature, humidity, and energy dissipation. For our analyses, we used Landsat 5 TM satellite data from June 25<SUP>th</SUP>, 2008. The results showed that the microclimatic characteristics and energy fluxes varied in different units according to their vegetation characteristics. A cluster analysis of the mean values was used to divide the vegetation units into groups according to their functional characteristics. The mown meadows were characterised by the highest surface temperature and sensible heat flux and the lowest humidity and latent heat flux. On the contrary, the lowest surface temperature and sensible heat flux and the highest humidity and latent heat flux were found in the forest. Our results showed that the climatic and energetic features of the land surface are related to the type of vegetation. We state that the spatial distribution of different vegetation units and the amount of biomass are crucial variables influencing the functioning of the landscape.

Latent heat flux estimation in clear sky days over Indian agroecosystems using noontime satellite remote sensing data

2009 ◽  
Vol 149 (10) ◽  
pp. 1646-1665 ◽  
Author(s):  
Kaniska Mallick ◽  
Bimal K. Bhattacharya ◽  
V.U.M. Rao ◽  
D. Raji Reddy ◽  
Saon Banerjee ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Clear Sky ◽  
Heat Flux Estimation ◽  
Flux Estimation

The Lagrangian Stochastic Model for fetch and latent heat flux estimation above uniform and nonuniform terrain

1997 ◽  
Vol 33 (3) ◽  
pp. 427-438 ◽  
Author(s):  
Cheng-I Hsieh ◽  
Gabriel G. Katul ◽  
John Schieldge ◽  
John T. Sigmon ◽  
Kenneth K. Knoerr
Keyword(s):  
Heat Flux ◽  
Stochastic Model ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Lagrangian Stochastic Model ◽  
Heat Flux Estimation ◽  
Flux Estimation

The Impact of Vertical Measurement Depth on the Information Content of Soil Moisture for Latent Heat Flux Estimation

2016 ◽  
Vol 17 (9) ◽  
pp. 2419-2430 ◽  
Author(s):  
Jianxiu Qiu ◽  
Wade T. Crow ◽  
Grey S. Nearing
Keyword(s):  
Heat Flux ◽  
Time Series ◽  
Soil Moisture ◽  
Information Content ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Heat Flux Estimation ◽  
Vertical Support ◽  
Flux Estimation ◽  
The Impact

Abstract This study aims to identify the impact of vertical support on the information content of soil moisture (SM) for latent heat flux estimation. This objective is achieved via calculation of the mutual information (MI) content between multiple soil moisture variables (with different vertical supports) and current/future evaporative fraction (EF) using ground-based soil moisture and latent/sensible heat flux observations acquired from the AmeriFlux network within the contiguous United States. Through the intercomparison of MI results from different SM–EF pairs, the general value (for latent heat flux estimation) of superficial soil moisture observations , vertically integrated soil moisture observations , and vertically extrapolated soil moisture time series [soil wetness index (SWI) from a simple low-pass transformation of ] are examined. Results suggest that, contrary to expectations, 2-day averages of and have comparable mutual information with regards to EF. That is, there is no clear evidence that the information content for flux estimation is enhanced via deepening the vertical support of superficial soil moisture observations. In addition, the utility of SWI in monitoring and forecasting EF is partially dependent on the adopted parameterization of time-scale parameter T in the exponential filter. Similar results are obtained when analyses are conducted at the monthly time scale, only with larger error bars. The contrast between the results of this paper and past work focusing on utilizing soil moisture to predict vegetation condition demonstrates that the particular application should be considered when characterizing the information content of soil moisture time series measurements.

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