Normalized Difference Latent Heat Index for Remote Sensing of Land Surface Energy Fluxes

2019 ◽  
Vol 57 (3) ◽  
pp. 1423-1433 ◽  
Author(s):  
Yuei-An Liou ◽  
Mai Son Le ◽  
Hwa Chien
Keyword(s):  
Remote Sensing ◽  
Surface Energy ◽  
Latent Heat ◽  
Land Surface ◽  
Heat Index ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

scholarly journals Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

2018 ◽  
Author(s):  
Andrei Serafimovich ◽  
Stefan Metzger ◽  
Jörg Hartmann ◽  
Katrin Kohnert ◽  
Donatella Zona ◽  
...  
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Land Surface ◽  
Response Functions ◽  
Sensible Heat ◽  
Environmental Response ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Eddy Covariance Measurements

Abstract. The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high resolution flux maps. In order to support the evaluation of coupled atmospheric/land–surface models we investigated spatial patterns of energy fluxes in relation to land–surface properties. We used airborne eddy-covariance measurements acquired by the POLAR 5 research aircraft in June–July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modelled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modelled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

scholarly journals Distinguishing between early- and late-covering crops in the land surface model Noah-MP: impact on simulated surface energy fluxes and temperature

2020 ◽  
Vol 17 (10) ◽  
pp. 2791-2805
Author(s):  
Kristina Bohm ◽  
Joachim Ingwersen ◽  
Josipa Milovac ◽  
Thilo Streck
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Surface Energy ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

Abstract. Land surface models are essential parts of climate and weather models. The widely used Noah-MP land surface model requires information on the leaf area index (LAI) and green vegetation fraction (GVF) as key inputs of its evapotranspiration scheme. The model aggregates all agricultural areas into a land use class termed “cropland and pasture”. In a previous study we showed that, on a regional scale, the GVF has a bimodal distribution formed by two crop groups differing in phenology and growth dynamics: early-covering crops (ECC; e.g., winter wheat, winter rapeseed, winter barley) and late-covering crops (LCC; e.g., corn, silage maize, sugar beet). That result can be generalized for central Europe. The present study quantifies the effect of splitting the land use class cropland and pasture of Noah-MP into ECC and LCC on surface energy fluxes and temperature. We further studied the influence of increasing the LCC share, which in the study area (the Kraichgau region, southwest Germany) is mainly the result of heavily subsidized biomass production, on energy partitioning at the land surface. We used the GVF dynamics derived from high-resolution (5 m × 5 m) RapidEye satellite data and measured LAI data for the simulations. Our results confirm that the GVF and LAI strongly influence the partitioning of surface energy fluxes, resulting in pronounced differences between simulations of ECC and LCC. Splitting up the generic crop into ECC and LCC had the strongest effect on land surface exchange processes in July–August. During this period, ECC are at the senescence growth stage or already harvested, while LCC have a well-developed ground-covering canopy. The generic crop resulted in humid bias, i.e., an increase in evapotranspiration by +0.5 mm d−1 (latent heat flux is 1.3 MJ m−2 d−1), decrease in sensible heat flux (H) by 1.2 MJ m−2  d−1 and decrease in surface temperature by −1 ∘C. The bias increased as the shares of ECC and LCC became similar. The observed differences will impact the simulations of processes in the planetary boundary layer. Increasing the LCC share from 28 % to 38 % in the Kraichgau region led to a decrease in latent heat flux (LE) and a heating up of the land surface in the early growing season. Over the second part of the season, LE increased and the land surface cooled down by up to 1 ∘C.

scholarly journals Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

2018 ◽  
Vol 18 (13) ◽  
pp. 10007-10023 ◽  
Author(s):  
Andrei Serafimovich ◽  
Stefan Metzger ◽  
Jörg Hartmann ◽  
Katrin Kohnert ◽  
Donatella Zona ◽  
...  
Keyword(s):  
Surface Energy ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Land Surface ◽  
Response Functions ◽  
Sensible Heat ◽  
Environmental Response ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Eddy Covariance Measurements

Abstract. The objective of this study was to upscale airborne flux measurements of sensible heat and latent heat and to develop high-resolution flux maps. In order to support the evaluation of coupled atmospheric–land-surface models we investigated spatial patterns of energy fluxes in relation to land-surface properties. We used airborne eddy-covariance measurements acquired by the Polar 5 research aircraft in June–July 2012 to analyze surface fluxes. Footprint-weighted surface properties were then related to 21 529 sensible heat flux observations and 25 608 latent heat flux observations using both remote sensing and modeled data. A boosted regression tree technique was used to estimate environmental response functions between spatially and temporally resolved flux observations and corresponding biophysical and meteorological drivers. In order to improve the spatial coverage and spatial representativeness of energy fluxes we used relationships extracted across heterogeneous Arctic landscapes to infer high-resolution surface energy flux maps, thus directly upscaling the observational data. These maps of projected sensible heat and latent heat fluxes were used to assess energy partitioning in northern ecosystems and to determine the dominant energy exchange processes in permafrost areas. This allowed us to estimate energy fluxes for specific types of land cover, taking into account meteorological conditions. Airborne and modeled fluxes were then compared with measurements from an eddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependent quantification of surface energy fluxes and they provide new insights into the processes affecting these fluxes for the main vegetation types in high-latitude permafrost areas.

A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture

2009 ◽  
Vol 33 (2) ◽  
pp. 224-250 ◽  
Author(s):  
G. Petropoulos ◽  
T.N. Carlson ◽  
M.J. Wooster ◽  
S. Islam
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Energy ◽  
Land Surface ◽  
Vegetation Index ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Wide Range

Imagery from remote sensing systems, often combined with ancillary ground information, is able to provide repetitive, synoptic views of key parameters characterizing land surface interactions, including surface energy fluxes and surface soil moisture. Differing methodologies using a wide range of remote sensing data have been developed for this purpose. Approaches vary from purely empirical to more complex ones, including residual methods and those that have their basis in the biophysical properties characterizing a two-dimensional Ts/VI (surface temperature/ vegetation index) scatterplot domain derived from remote sensing observations. The present article aims to offer a comprehensive and systematic review of this latter group of methods, which differ in terms of the complexity and assumptions they entail as well as their requirement for field-based and other ancillary data. Prior to the review, the biophysical meanings and properties encapsulated in the Ts/VI feature space is elucidated, since these represent the building block upon which all the Ts/VI methods described herein are based. The overview of the Ts/VI methods is also very timely, as one such method is being scheduled in the operational retrieval of surface soil moisture content by the National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms due to be launched in the next 12 years starting from 2016.

scholarly journals Remotely sensed land-surface energy fluxes at sub-field scale in heterogeneous agricultural landscape and coniferous plantation

2014 ◽  
Vol 11 (18) ◽  
pp. 5021-5046 ◽  
Author(s):  
R. Guzinski ◽  
H. Nieto ◽  
R. Jensen ◽  
G. Mendiguren
Keyword(s):  
Surface Energy ◽  
Spatial Resolution ◽  
Land Surface ◽  
Agricultural Landscape ◽  
Remotely Sensed ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Coniferous Plantation ◽  
Polar Orbiting Satellite ◽  
Agricultural Site

Abstract. In this study we evaluate a methodology for disaggregating land surface energy fluxes estimated with the Two-Source Energy Balance (TSEB)-based Dual-Temperature Difference (DTD) model which uses day and night polar orbiting satellite observations of land surface temperature (LST) as a remotely sensed input. The DTD model is run with MODIS input data at a spatial resolution of around 1 km while the disaggregation uses Landsat observations to produce fluxes at a nominal spatial resolution of 30 m. The higher-resolution modelled fluxes can be directly compared against eddy covariance (EC)-based flux tower measurements to ensure more accurate model validation and also provide a better visualization of the fluxes' spatial patterns in heterogeneous areas allowing for development of, for example, more efficient irrigation practices. The disaggregation technique is evaluated in an area covered by the Danish Hydrological Observatory (HOBE), in the west of the Jutland peninsula, and the modelled fluxes are compared against measurements from two flux towers: the first one in a heterogeneous agricultural landscape and the second one in a homogeneous conifer plantation. The results indicate that the coarse-resolution DTD fluxes disaggregated at Landsat scale have greatly improved accuracy as compared to high-resolution fluxes derived directly with Landsat data without the disaggregation. At the agricultural site the disaggregated fluxes display small bias and very high correlation (r ≈ 0.95) with EC-based measurements, while at the plantation site the results are encouraging but still with significant errors. In addition, we introduce a~modification to the DTD model by replacing the "parallel" configuration of the resistances to sensible heat exchange by the "series" configuration. The latter takes into account the in-canopy air temperature and substantially improves the accuracy of the DTD model.

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