Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method

2018 ◽  
Vol 39 (19) ◽  
pp. 6300-6315
Author(s):  
Verónica Barraza Bernadas ◽  
Francisco Grings ◽  
Natalia Restrepo-Coupe ◽  
Alfredo Huete
Keyword(s):  
Heat Flux ◽  
Collocation Method ◽  
Southern Hemisphere ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Forest Ecosystems ◽  
In Situ Measurements ◽  
Error Structure

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.

scholarly journals Estimation of Vegetation Latent Heat Flux over Three Forest Sites in ChinaFLUX using Satellite Microwave Vegetation Water Content Index

2019 ◽  
Vol 11 (11) ◽  
pp. 1359 ◽  
Author(s):  
Yipu Wang ◽  
Rui Li ◽  
Qilong Min ◽  
Leiming Zhang ◽  
Guirui Yu ◽  
...  
Keyword(s):  
Heat Flux ◽  
Water Content ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
In Situ Measurements ◽  
Vegetation Water Content ◽  
Forest Sites ◽  
Content Index ◽  
Vegetation Water

Latent heat flux (LE) and the corresponding water vapor lost from the Earth’s surface to the atmosphere, which is called Evapotranspiration (ET), is one of the key processes in the water cycle and energy balance of the global climate system. Satellite remote sensing is the only feasible technique to estimate LE over a large-scale region. While most of the previous satellite LE methods are based on the optical vegetation index (VI), here we propose a microwave-VI (EDVI) based LE algorithm which can work for both day and night time, and under clear or non-raining conditions. This algorithm is totally driven by multiple-sensor satellite products of vegetation water content index, solar radiation, and cloud properties, with some aid from a reanalysis dataset. The satellite inputs and the performance of this algorithm are validated with in situ measurements at three ChinaFLUX forest sites. Our results show that the selected satellite observations can indeed serve as the inputs for the purpose of estimating ET. The instantaneous estimations of LE (LEcal) from this algorithm show strong positive temporal correlations with the in situ measured LE (LEobs) with the correlation coefficients (R) of 0.56–0.88 in the study years. The mean bias is kept within 16.0% (23.0 W/m2) across the three sites. At the monthly scale, the correlations between the retrieval and the in situ measurements are further improved to an R of 0.84–0.95 and the bias is less than 14.3%. The validation results also indicate that EDVI-based LE method can produce stable LEcal under different cloudy skies with good accuracy. Being independent of any in situ measurements as inputs, this algorithm shows great potential for estimating ET under both clear and cloudy skies on a global scale for climate study.

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.

scholarly journals Uncertainty characterization of HOAPS 3.3 latent heat-flux-related parameters

2018 ◽  
Vol 11 (3) ◽  
pp. 1793-1815 ◽  
Author(s):  
Julian Liman ◽  
Marc Schröder ◽  
Karsten Fennig ◽  
Axel Andersson ◽  
Rainer Hollmann
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Quality Data ◽  
Boreal Winter ◽  
Western Boundary ◽  
Decomposition Approach ◽  
In Situ Data ◽  
Global Mean

Abstract. Latent heat flux (LHF) is one of the main contributors to the global energy budget. As the density of in situ LHF measurements over the global oceans is generally poor, the potential of remotely sensed LHF for meteorological applications is enormous. However, to date none of the available satellite products have included estimates of systematic, random, and sampling uncertainties, all of which are essential for assessing their quality. Here, the challenge is taken on by matching LHF-related pixel-level data of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS) climatology (version 3.3) to in situ measurements originating from a high-quality data archive of buoys and selected ships. Assuming the ground reference to be bias-free, this allows for deriving instantaneous systematic uncertainties as a function of four atmospheric predictor variables. The approach is regionally independent and therefore overcomes the issue of sparse in situ data densities over large oceanic areas. Likewise, random uncertainties are derived, which include not only a retrieval component but also contributions from in situ measurement noise and the collocation procedure. A recently published random uncertainty decomposition approach is applied to isolate the random retrieval uncertainty of all LHF-related HOAPS parameters. It makes use of two combinations of independent data triplets of both satellite and in situ data, which are analysed in terms of their pairwise variances of differences. Instantaneous uncertainties are finally aggregated, allowing for uncertainty characterizations on monthly to multi-annual timescales. Results show that systematic LHF uncertainties range between 15 and 50 W m−2 with a global mean of 25 W m−2. Local maxima are mainly found over the subtropical ocean basins as well as along the western boundary currents. Investigations indicate that contributions from qa (U) to the overall LHF uncertainty are on the order of 60 % (25 %). From an instantaneous point of view, random retrieval uncertainties are specifically large over the subtropics with a global average of 37 W m−2. In a climatological sense, their magnitudes become negligible, as do respective sampling uncertainties. Regional and seasonal analyses suggest that largest total LHF uncertainties are seen over the Gulf Stream and the Indian monsoon region during boreal winter. In light of the uncertainty measures, the observed continuous global mean LHF increase up to 2009 needs to be treated with caution. The demonstrated approach can easily be transferred to other satellite retrievals, which increases the significance of the present work.

scholarly journals Impacts of wildfire aerosols on global energy budget and climate: The role of climate feedbacks

2020 ◽  
Author(s):  
Yiquan Jiang ◽  
Xiu-Qun Yang ◽  
Xiaohong Liu
Keyword(s):  
Heat Flux ◽  
Southern Hemisphere ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Global Climate ◽  
The Arctic ◽  
Global Ocean ◽  
Climate Feedbacks ◽  
Surface Latent Heat Flux

<p>Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols’ impacts on global climate with emphasizing the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be -0.78±0.29 W m<sup>-2</sup>, which is mostly from shortwave RE due to aerosol-cloud interactions (REaci, -0.70±0.20 W m<sup>-2</sup>). The associated global-annual mean surface air temperature (SAT) change (∆T) is -0.64±0.16K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to re-amplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ∆T) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ∆T) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N), but increases in Southern Hemisphere tropical ocean, which is associated with the southward shift of the Inter-Tropical Convergence Zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal-forest fire aerosol indirect effect, through intensifying the cross-equator atmospheric heat transport.</p>

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