Estimation of Turbulent Heat Fluxes by Assimilation of Land Surface Temperature Observations From GOES Satellites Into an Ensemble Kalman Smoother Framework

2018 ◽  
Vol 123 (5) ◽  
pp. 2409-2423 ◽  
Author(s):  
Tongren Xu ◽  
S. M. Bateni ◽  
C. M. U. Neale ◽  
T. Auligne ◽  
Shaomin Liu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Kalman Smoother ◽  
Turbulent Heat Fluxes ◽  
Temperature Observations

scholarly journals Improving Soil Moisture and Surface Turbulent Heat Flux Estimates by Assimilation of SMAP Brightness Temperatures or Soil Moisture Retrievals and GOES Land Surface Temperature Retrievals

2020 ◽  
Vol 21 (2) ◽  
pp. 183-203 ◽  
Author(s):  
Yang Lu ◽  
Susan C. Steele-Dunne ◽  
Gabriëlle J. M. De Lannoy
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Surface Heat Flux ◽  
Surface Heat ◽  
Heat Fluxes ◽  
Transfer Model ◽  
Turbulent Heat

AbstractSurface heat fluxes are vital to hydrological and environmental studies, but mapping them accurately over a large area remains a problem. In this study, brightness temperature (TB) observations or soil moisture retrievals from the NASA Soil Moisture Active Passive (SMAP) mission and land surface temperature (LST) product from the Geostationary Operational Environmental Satellite (GOES) are assimilated together into a coupled water and heat transfer model to improve surface heat flux estimates. A particle filter is used to assimilate SMAP data, while a particle smoothing method is adopted to assimilate GOES LST time series, correcting for both systematic biases via parameter updating and for short-term error via state updating. One experiment assimilates SMAP TB at horizontal polarization and GOES LST, a second experiment assimilates SMAP TB at vertical polarization and GOES LST, and a third experiment assimilates SMAP soil moisture retrievals along with GOES LST. The aim is to examine if the assimilation of physically consistent TB and LST observations could yield improved surface heat flux estimates. It is demonstrated that all three assimilation experiments improved flux estimates compared to a no-assimilation case. Assimilating TB data tends to produce smaller bias in soil moisture estimates compared to assimilating soil moisture retrievals, but the estimates are influenced by the respective bias correction approaches. Despite the differences in soil moisture estimates, the flux estimates from different assimilation experiments are in general very similar.

A General Framework of Kernel-driven Modeling in the Thermal Infrared Band for Land Surface Temperature Normalization

2020 ◽  
Author(s):  
Biao Cao ◽  
Qinhuo Liu ◽  
Yongming Du ◽  
Hua Li ◽  
Zunjian Bian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
General Framework ◽  
Thermal Infrared ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Modeling Framework ◽  
New Models

<p>Land surface temperature (LST) is the direct driving force of turbulent heat fluxes at the surface and atmosphere interface and is widely used in the fields of evapotranspiration estimation (Su et al., 2002) and energy budget (Liang et al., 2019). Remote sensing products offer the only possibility for measuring LST with completely spatially averaged values. The thermal radiation directionality (TRD) effect has been widely concerned in the area of thermal infrared (TIR) remote sensing over 50 years which can lead to the directional brightness temperature (DBT) difference between different viewing directions up to 10 K (Cao et al., 2019). Many models have been proposed to simulate the DBT patterns over different underlying surfaces aimed to achieve the TRD effect correction for the satellite LST products. In practice, it is advised to handle only TRD models having a limited number of input parameters for operational normalization of LST products. The use of TIR kernel-driven models appears a good tradeoff between physical accuracy and operationality. It remains that the existing 4 TIR kernel-driven models (Ross-Li, LSF-Li, Vinnikov, RL) underestimate the hotspot effect, especially for continuous canopies. In this study, a new general framework of TIR kernel-driven modeling is proposed to overcome such issue. It is a linear combination of three kernels (including a base shape kernel, a hotspot kernel and an isotropic kernel) with the ability to simulate the bowl, dome and bell shapes in the solar principal plane. 4 specific models (Vinnikov-RL, LSF-RL, Vinnikov-Chen, LSF-Chen) within the new framework were further developed to assess their fitting abilities for both continuous and discrete vegetation canopies. To evaluate 4 existing models and 4 new models comprehensively, it was prepared 102 groups of 4SAIL/DART generated multi-angle datasets considering 6 different canopy architectures and 17 component temperatures. Results show that the 4 new models behave slightly better than the 4 existing models over discrete canopies (R2 increases from 0.791~0.989 to 0.976~0.996) whereas they significantly improved the fitting accuracy over continuous canopies (R2 increases from 0.661~0.970 to 0.940~0.997). The innovative new general framework with three kernels and four parameters improve the fitting ability significantly since the addition of one more degree of freedom. This new kernel-driven modeling framework is a potential tool to achieve angular correction of LST products.</p>

The Effect of Soil on the Summertime Surface Energy Budget of a Humid Subarctic Tundra in Northern Quebec, Canada

2021 ◽  
Vol 22 (10) ◽  
pp. 2547-2564
Author(s):  
Georg Lackner ◽  
Daniel F. Nadeau ◽  
Florent Domine ◽  
Annie-Claude Parent ◽  
Gonzalo Leonardini ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Arctic Region ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

AbstractRising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux.

Contribution of lakes in the ORCHIDEE land surface model

2020 ◽  
Author(s):  
Anthony Bernus ◽  
Catherine Ottle ◽  
Nina Raoult
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Energy Budget ◽  
Land Surface ◽  
Land Surface Model ◽  
Global Scale ◽  
Heat Fluxes ◽  
Energy Budgets ◽  
Surface Model ◽  
Local Climate

<p>Lakes play a major role on local climate and boundary layer stratification. At global scale, they have been shown to have an impact on the energy budget, (see for example Le Moigne et al., 2016 or Bonan, 1995 ) . To represent the energy budget of lakes at a global scale, the FLake (Mironov et al, 2008) lake model has been coupled to the ORCHIDEE land surface model - the continental part of the IPSL earth system model. By including Flake in ORCHIDEE, we aim to improve the representation of land surface temperature and heat fluxes. Using the standard CMIP6 configuration of ORCHIDEE,  two 40-year simulations were generated (one coupled with FLake and one without) using the CRUJRA meteorological forcing data at a spatial resolution of 0.5°. We compare land surface temperatures and heat fluxes from the two ORCHIDEE simulations and assess the impacts of lakes on surface energy budgets. MODIS satellite land surface temperature products will be used to validate the simulations. We expect a better fit between the simulated land surface temperature and the MODIS data when the FLake configuration is used. The preliminary results of the comparison will be presented.</p>

Estimation of land surface key parameters for the study of energy and water cycle over the Tibetan Plateau based on geostationary and polar orbiting satellites

2021 ◽  
Author(s):  
Lei Zhong ◽  
Yaoming Ma ◽  
Zhongbo Su ◽  
Weiqiang Ma ◽  
Zeyong Hu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Water Cycle ◽  
Surface Characteristic ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
The Tibetan Plateau ◽  
Characteristic Parameters ◽  
Turbulent Heat Fluxes ◽  
Land Surface Parameters

<p>Estimation of land surface characteristic parameters and turbulent heat fluxes is important for energy and water cycle studies, especially on the Tibetan Plateau (TP), where the topography is unique and the land-atmosphere interactions are strong. The land surface heating conditions also directly influence the movement of atmospheric circulation. However, high temporal resolution information on the plateau-scale land surface parameters has lacked for a long time, which significantly limits the understanding of diurnal variations in land-atmosphere interactions. On the other hand, how to remove cloud effects for optical satellite images is another important research issue. Based on Chinese FY geostationary satellite data and other polar orbiting satellite data, the hourly land surface characteristic parameters and turbulent heat fluxes were estimated. A new cloud‐free time series of vegetation index data sets was reconstructed, and the vegetation density showed a general increasing trend along with a warming trend in the TP. The regions showing significant increases accounted for 7.63% of the total Tibetan territory. Downwelling shortwave and longwave radiation parameterization schemes were improved to derive all-sky radiation over the TP. The diurnal and seasonal cycles of the land surface parameters were clearly identified, and their spatial distribution was found to be consistent with the heterogeneous land surface conditions and the general hydrometeorological conditions of the TP.</p>

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