scholarly journals Land-surface water vapor and sensible heat flux: Spatial variability, homogeneity, and measurement scales

1998 ◽  
Vol 34 (10) ◽  
pp. 2433-2442 ◽  
Author(s):  
Wilfried Brutsaert
2010 ◽  
Vol 4 (Special Issue 2) ◽  
pp. S49-S58 ◽  
Author(s):  
J. Brom ◽  
J. Procházka ◽  
A. Rejšková

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.


2020 ◽  
Author(s):  
Yaoming Ma

&lt;p&gt;The exchange of heat and water vapor between land surface and atmosphere over the Third Pole region (Tibetan Plateau and nearby surrounding region) plays an important role in Asian monsoon, westerlies and the northern hemisphere weather and climate systems. Supported by various agencies in the People&amp;#8217;s Republic of China, a Third Pole Environment (TPE) observation and research Platform (TPEORP) is now implementing over the Third Pole region. The background of the establishment of the TPEORP, the establishing and monitoring plan of long-term scale (5-10 years) of it will be shown firstly. Then the preliminary observational analysis results, such as the characteristics of land surface energy fluxes partitioning and the turbulent characteristics will also been shown in this study. Then, the parameterization methodology based on satellite data and the atmospheric boundary layer (ABL) observations has been proposed and tested for deriving regional distribution of net radiation flux, soil heat flux, sensible heat flux and latent heat flux (evapotranspiration (ET)) and their variation trends over the heterogeneous landscape of the Tibetan Plateau (TP) area. To validate the proposed methodology, the ground measured net radiation flux, soil heat flux, sensible heat flux and latent heat flux of the TPEORP are compared to the derived values. The results showed that the derived land surface heat fluxes over the study areas are in good accordance with the land surface status. These parameters show a wide range due to the strong contrast of surface feature. And the estimated land surface heat fluxes are in good agreement with ground measurements, and all the absolute percent difference in less than 10% in the validation sites. The sensible heat flux has increased slightly and the latent heat flux has decreased from 2001 to 2016 over the TP. It is therefore conclude that the proposed methodology is successful for the retrieval of land surface heat fluxes and ET over heterogeneous landscape of the TP area. Further improvement of the methodology and its applying field over the whole Third Pole region and Pan-Third Pole region were also discussed.&lt;/p&gt;


2017 ◽  
Vol 34 (9) ◽  
pp. 2103-2112 ◽  
Author(s):  
Temple R. Lee ◽  
Michael Buban ◽  
Edward Dumas ◽  
C. Bruce Baker

AbstractUpscaling point measurements from micrometeorological towers is a challenging task that is important for a variety of applications, for example, in process studies of convection initiation, carbon and energy budget studies, and the improvement of model parameterizations. In the present study, a technique was developed to determine the horizontal variability in sensible heat flux H surrounding micrometeorological towers. The technique was evaluated using 15-min flux observations, as well as measurements of land surface temperature and air temperature obtained from small unmanned aircraft systems (sUAS) conducted during a one-day measurement campaign. The computed H was found to be comparable to the micrometeorological measurements to within 5–10 W m−2. Furthermore, when comparing H computed using this technique with H determined using large-eddy simulations (LES), differences of <10 W m−2 were typically found. Thus, implementing this technique using observations from sUAS will help determine sensible heat flux variability at horizontal spatial scales larger than can be provided from flux tower measurements alone.


2016 ◽  
Vol 29 (14) ◽  
pp. 5123-5139 ◽  
Author(s):  
Anna L. Merrifield ◽  
Shang-Ping Xie

Abstract This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental United States in the Atmospheric Model Intercomparison Project (AMIP) experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-yr period (1979–2008). Regions of high SAT variability are closely associated with midtropospheric highs, subsidence, and radiative heating accompanying clear-sky conditions. The land surface exerts a spatially variable influence on SAT through the sensible heat flux and is a second-order effect in the high-variability centers of action (COAs) in observational estimates. The majority of the AMIP models feature high SAT variability over the central United States, displaced south and/or west of observed COAs. SAT COAs in models tend to be concomitant and strongly coupled with regions of high sensible heat flux variability, suggesting that excessive land–atmosphere interaction in these models modulates U.S. summer SAT. In the central United States, models with climatological warm biases also feature less evapotranspiration than ERA-Interim but reasonably reproduce observed SAT variability in the region. Models that overestimate SAT variability tend to reproduce ERA-Interim SAT and evapotranspiration climatology. In light of potential model biases, this analysis calls for careful evaluation of the land–atmosphere interaction hot spot region identified in the central United States. Additionally, tropical sea surface temperatures play a role in forcing the leading EOF mode for summer SAT in models. This relationship is not apparent in observations.


2019 ◽  
Vol 11 (24) ◽  
pp. 2899
Author(s):  
Nan Ge ◽  
Lei Zhong ◽  
Yaoming Ma ◽  
Meilin Cheng ◽  
Xian Wang ◽  
...  

Land surface heat fluxes consist of the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. The estimation of these fluxes is essential to the study of energy transfer in land–atmosphere systems. In this paper, Landsat 7 ETM+ SLC-on data were applied to estimate the land surface heat fluxes on the northern Tibetan Plateau using the SEBS (surface energy balance system) model, in combination with the calculation of field measurements at CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project on the Tibetan Plateau) automatic weather stations based on the combinatory method (CM) for comparison. The root mean square errors between the satellite estimations and the CM calculations for the net radiation flux, soil heat flux, sensible heat flux, and latent heat flux were 49.2 W/m2, 46.3 W/m2, 68.2 W/m2, and 54.9 W/m2, respectively. The results reveal that land surface heat fluxes all present significant seasonal variability. Apart from the sensible heat flux, the satellite-estimated net radiation flux, soil heat flux, and latent heat flux exhibited a trend of summer > spring > autumn > winter. In summer, spring, autumn, and winter, respectively, the median values of the net radiation flux (631.8 W/m2, 583.0 W/m2, 404.4 W/m2, 314.3 W/m2), soil heat flux (40.9 W/m2, 37.9 W/m2, 26.1 W/m2, 20.5 W/m2), sensible heat flux (252.7 W/m2, 219.5 W/m2, 221.4 W/m2, 204.8 W/m2), and latent heat flux (320.1 W/m2, 298.3 W/m2, 142.3 W/m2, 75.5 W/m2) exhibited distinct seasonal diversity. From November to April, the in situ sensible heat flux is higher than the latent heat flux; the opposite is true between June and September, leaving May and October as transitional months. For water bodies, alpine meadows and other main underlying surface types, sensible and latent heat flux generally present contrasting and complementary spatial distributions. Due to the 15–60 m resolution of the Landsat 7 ETM+ data, the distribution of land surface heat fluxes can be used as an indicator of complex underlying surface types over the northern Tibetan Plateau.


2021 ◽  
Vol 9 ◽  
Author(s):  
Wenzong Dong ◽  
Hua Yuan ◽  
Ruqing Zhang ◽  
Hongmei Li ◽  
Lina Huang ◽  
...  

Leaf optical properties (LOPs, i.e., leaf reflectance and transmittance), as a fundamental property of vegetation, are a key parameter in the canopy radiative transfer process. LOPs have a direct impact on the surface solar radiation partition and further affect surface flux exchanges. Recent works have provided reliable LOP data and mentioned that notable differences exist between the prescribed LOP values in current land surface models and measured LOP values, especially in the near-infrared (NIR) band. To evaluate the effects of different LOP values in land surface modeling, we ran two land surface models (the Community Land Model and the Common Land Model) with their default prescribed and measured values to examine the differences in simulated surface radiation partitions and fluxes. Our analyses show that differences in LOP values can lead to a large discrepancy in albedo, radiation partition, sensible heat flux and net radiation simulations. By using the measured LOP values, in the boreal forest zone, Southeast China, and the eastern United States, both models have a significantly increased surface albedo in the NIR band, with the difference exceeding 10% during JJA. Thus, the measured LOP values can improve the negative albedo bias in the boreal forest zone during summertime. Moreover, both models simulate less net radiation with a maximum reduction of 11 W/m2 when incorporating the measured LOP values. Therefore, the total sensible heat flux can be reduced by as much as 11 W/m2. The results of this study emphasize that different LOP values can have a considerable effect on the surface radiation budget and sensible heat flux simulations which need attention in land surface model development. However, in current offline simulations, the measured LOP values cause slight changes in land surface temperatures and gross primary productivity (GPP).


2021 ◽  
Author(s):  
Lian Liu ◽  
Yaoming Ma ◽  
Massimo Menenti ◽  
Rongmingzhu Su ◽  
Nan Yao ◽  
...  

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land-atmosphere interactions estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the WRF and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates, by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged RMSE relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %) respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.


2021 ◽  
Vol 25 (9) ◽  
pp. 4967-4981
Author(s):  
Lian Liu ◽  
Yaoming Ma ◽  
Massimo Menenti ◽  
Rongmingzhu Su ◽  
Nan Yao ◽  
...  

Abstract. Snow albedo is important to the land surface energy balance and to the water cycle. During snowfall and subsequent snowmelt, snow albedo is usually parameterized as functions of snow-related variables in land surface models. However, the default snow albedo scheme in the widely used Noah land surface model shows evident shortcomings in land–atmosphere interaction estimates during snow events on the Tibetan Plateau. Here, we demonstrate that our improved snow albedo scheme performs well after including snow depth as an additional factor. By coupling the Weather Research and Forecasting (WRF) and Noah models, this study comprehensively evaluates the performance of the improved snow albedo scheme in simulating eight snow events on the Tibetan Plateau. The modeling results are compared with WRF run with the default Noah scheme and in situ observations. The improved snow albedo scheme significantly outperforms the default Noah scheme in relation to air temperature, albedo and sensible heat flux estimates by alleviating cold bias estimates, albedo overestimates and sensible heat flux underestimates, respectively. This in turn contributes to more accurate reproductions of snow event evolution. The averaged root mean square error (RMSE) relative reductions (and relative increase in correlation coefficients) for air temperature, albedo, sensible heat flux and snow depth reach 27 % (5 %), 32 % (69 %), 13 % (17 %) and 21 % (108 %), respectively. These results demonstrate the strong potential of our improved snow albedo parameterization scheme for snow event simulations on the Tibetan Plateau. Our study provides a theoretical reference for researchers committed to further improving the snow albedo parameterization scheme.


2020 ◽  
Author(s):  
E. Hugo Berbery ◽  
Eli Dennis

&lt;p&gt;The land surface is inextricably linked to the atmospheric circulation as it dictates the location and strength of land surface-atmosphere (LA) coupling mechanisms. In this context, soil hydraulic properties are critical to estimate sub-surface processes and fluxes at the surface. &amp;#160;In most numerical weather and climate models, those properties are assigned through maps of soil texture complemented with look-up tables.&amp;#160; Then, the hydraulic properties are used in a large variety of process parameterizations within the models.&amp;#160; In this study, we investigate the sensitivity of the simulated regional climate to changes in the prescribed soil maps in the WRF/CLM4 modeling suite. &amp;#160;Comparison of two widely used soil texture databases, the USGS State Soil Geographic Database (STATSGO) and Beijing Normal University&amp;#8217;s soil texture database (GSDE), over the United States and Central America reveals that only 32% of soil texture classifications are in common. Further, the differences are not random but tend to depict small-to-large spatial patterns with a preponderance of either finer or coarser grains. Over North America, the US Great Plains have finer grains in GSDE than in STATSGO, while the opposite is true over Central Mexico.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Seasonal simulations were carried out to assess the changes in the soil-water system that result from changing the soil types (GSDE vs. STATSGO) and their corresponding hydraulic properties. Wherever GSDE has finer grains than STATSGO (e.g., over the US Great Plains), the soil will retain water more strongly as evidenced by smaller latent heat fluxes and larger sensible heat flux. On the other hand, areas of coarser grains in GSDE (e.g., over central Mexico) exhibit an increase in latent heat fluxes and a corresponding decrease in sensible heat flux. Regions with an increase/decrease in latent heat flux have a corresponding increase/decrease in the 2-m moisture content. Similar relations are obtained between sensible heat flux and 2-m temperature. These changes also affect the atmospheric column, which responds with an increase/decrease of temperature and height of the planetary boundary layer. Changes in the vertical structure induce changes in the vertical instability and winds. Interestingly, the chain of modifications resulting from soil texture changes impact the moisture fluxes, and more generally, the atmospheric water budget.&lt;/p&gt;


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