An Intercomparison of Techniques to Determine the Area-Averaged Latent Heat Flux from Individual in Situ Observations: A remote Sensing Approach Using the European Field Experiment in a Desertification-Threatened Area Data

1996 ◽  
Vol 32 (9) ◽  
pp. 2775-2786 ◽  
Author(s):  
H. Pelgrum ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Field Experiment ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
In Situ Observations ◽  
Area Data

scholarly journals Numerical simulation of extreme snow melt observed at the SIGMA-A site, northwest Greenland, during summer 2012

2015 ◽  
Vol 9 (1) ◽  
pp. 495-539
Author(s):  
M. Niwano ◽  
T. Aoki ◽  
S. Matoba ◽  
S. Yamaguchi ◽  
T. Tanikawa ◽  
...  
Keyword(s):  
Heat Flux ◽  
Grain Size ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
In Situ Measurements ◽  
The Arctic ◽  
Snow Surface ◽  
Near Surface ◽  
Surface Snow

Abstract. The surface energy balance (SEB) from 30 June to 14 July 2012 at site SIGMA (Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic)-A, (78°03' N, 67°38' W; 1490 m a.s.l.) on the northwest Greenland Ice Sheet (GrIS) was investigated by using in situ atmospheric and snow measurements, as well as numerical modeling with a one-dimensional, multi-layered, physical snowpack model called SMAP (Snow Metamorphism and Albedo Process). At SIGMA-A, remarkable near-surface snowmelt and continuous heavy rainfall (accumulated precipitation between 10 and 14 July was estimated to be 100 mm) were observed after 10 July 2012. Application of the SMAP model to the GrIS snowpack was evaluated based on the snow temperature profile, snow surface temperature, surface snow grain size, and shortwave albedo, all of which the model simulated reasonably well. However, comparison of the SMAP-calculated surface snow grain size with in situ measurements during the period when surface hoar with small grain size was observed on-site revealed that it was necessary to input air temperature, relative humidity, and wind speed data from two heights to simulate the latent heat flux into the snow surface and subsequent surface hoar formation. The calculated latent heat flux was always directed away from the surface if data from only one height were input to the SMAP model, even if the value for roughness length of momentum was perturbed between the possible maximum and minimum values in numerical sensitivity tests. This result highlights the need to use two-level atmospheric profiles to obtain realistic latent heat flux. Using such profiles, we calculated the SEB at SIGMA-A from 30 June to 14 July 2012. Radiation-related fluxes were obtained from in situ measurements, whereas other fluxes were calculated with the SMAP model. By examining the components of the SEB, we determined that low-level clouds accompanied by a significant temperature increase played an important role in the melt event observed at SIGMA-A. These conditions induced a remarkable surface heating via cloud radiative forcing in the polar region.

Upscaling latent heat flux for thermal remote sensing studies: Comparison of alternative approaches and correction of bias

2012 ◽  
Vol 468-469 ◽  
pp. 35-46 ◽  
Author(s):  
Thomas G. Van Niel ◽  
Tim R. McVicar ◽  
Michael L. Roderick ◽  
Albert I.J.M. van Dijk ◽  
Jason Beringer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Thermal Remote Sensing ◽  
Alternative Approaches

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

scholarly journals Quantifying the uncertainty in estimates of surface–atmosphere fluxes through joint evaluation of the SEBS and SCOPE models

2013 ◽  
Vol 17 (4) ◽  
pp. 1561-1573 ◽  
Author(s):  
J. Timmermans ◽  
Z. Su ◽  
C. van der Tol ◽  
A. Verhoef ◽  
W. Verhoef
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Estimation Error ◽  
Accurate Estimation ◽  
Area Index ◽  
Ground Heat Flux ◽  
Scope Model

Abstract. Accurate estimation of global evapotranspiration is considered to be of great importance due to its key role in the terrestrial and atmospheric water budget. Global estimation of evapotranspiration on the basis of observational data can only be achieved by using remote sensing. Several algorithms have been developed that are capable of estimating the daily evapotranspiration from remote sensing data. Evaluation of remote sensing algorithms in general is problematic because of differences in spatial and temporal resolutions between remote sensing observations and field measurements. This problem can be solved in part by using soil-vegetation-atmosphere transfer (SVAT) models, because on the one hand these models provide evapotranspiration estimations also under cloudy conditions and on the other hand can scale between different temporal resolutions. In this paper, the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model is used for the evaluation of the Surface Energy Balance System (SEBS) model. The calibrated SCOPE model was employed to simulate remote sensing observations and to act as a validation tool. The advantages of the SCOPE model in this validation are (a) the temporal continuity of the data, and (b) the possibility of comparing different components of the energy balance. The SCOPE model was run using data from a whole growth season of a maize crop. It is shown that the original SEBS algorithm produces large uncertainties in the turbulent flux estimations caused by parameterizations of the ground heat flux and sensible heat flux. In the original SEBS formulation the fractional vegetation cover is used to calculate the ground heat flux. As this variable saturates very fast for increasing leaf area index (LAI), the ground heat flux is underestimated. It is shown that a parameterization based on LAI reduces the estimation error over the season from RMSE = 25 W m−2 to RMSE = 18 W m−2. In the original SEBS formulation the roughness height for heat is only valid for short vegetation. An improved parameterization was implemented in the SEBS algorithm for tall vegetation. This improved the correlation between the latent heat flux predicted by the SEBS and the SCOPE algorithm from −0.05 to 0.69, and led to a decrease in difference from 123 to 94 W m−2 for the latent heat flux, with SEBS latent heat being consistently lower than the SCOPE reference. Lastly the diurnal stability of the evaporative fraction was investigated.

scholarly journals Are Soil Moisture and Latent Heat Overcoupled in Land Models?

Eos ◽  
2019 ◽  
Vol 100 ◽  
Author(s):  
Aaron Sidder
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Soil Moisture ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Coupling Strength ◽  
Statistical Approach ◽  
Flux Coupling ◽  
The Relationship

A novel statistical approach demonstrates how to reduce bias in remote sensing estimates of soil moisture and latent heat flux coupling strength and clarifies the relationship between the variables.

scholarly journals Estimation of Terrestrial Latent Heat Flux Based on Chinese GaoFen-1 Remote Sensing Data

2021 ◽  
Author(s):  
Ruiyang Yu ◽  
Yunjun Yao ◽  
Ke Shang ◽  
Junming Yang ◽  
Xiaozheng Guo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals A Satellite-Based Model for Estimating Latent Heat Flux From Urban Vegetation

2021 ◽  
Vol 9 ◽  
Author(s):  
Ian A. Smith ◽  
Joy B. Winbourne ◽  
Koen F. Tieskens ◽  
Taylor S. Jones ◽  
Fern L. Bromley ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Extreme Heat ◽  
Extreme Heat Events ◽  
Resolution Model ◽  
Complex Landscape ◽  
High Resolution Model ◽  
Heat Events

The impacts of extreme heat events are amplified in cities due to unique urban thermal properties. Urban greenspace mitigates high temperatures through evapotranspiration and shading; however, quantification of vegetative cooling potential in cities is often limited to simple remote sensing greenness indices or sparse, in situ measurements. Here, we develop a spatially explicit, high-resolution model of urban latent heat flux from vegetation. The model iterates through three core equations that consider urban climatological and physiological characteristics, producing estimates of latent heat flux at 30-m spatial resolution and hourly temporal resolution. We find strong agreement between field observations and model estimates of latent heat flux across a range of ecosystem types, including cities. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetation cooling benefits across the complex landscape of cities at an adequate resolution to inform policies addressing the effects of extreme heat events.

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