scholarly journals A parameterization of sub-grid topographical effects on solar radiation in the E3SM Land Model (version 1.0): implementation and evaluation over the Tibetan Plateau

2021 ◽  
Vol 14 (10) ◽  
pp. 6273-6289
Author(s):  
Dalei Hao ◽  
Gautam Bisht ◽  
Yu Gu ◽  
Wei-Liang Lee ◽  
Kuo-Nan Liou ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Surface Energy ◽  
Surface Temperature ◽  
Snow Cover ◽  
Land Surface ◽  
Spatial Scales ◽  
The Tibetan Plateau ◽  
Topographic Effects ◽  
Earth System

Abstract. Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth system models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes that the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to compare with the ELM simulations. The results show that topography has non-negligible effects on surface energy budget, snow cover, snow depth, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20, 10, and 5 W m−2, respectively. The differences in land surface albedo, snow cover fraction, snow depth, and surface temperature between TOP and PP exceed 0.1, 0.1, 10 cm, and 1 K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are larger with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover, and surface temperature, especially in the high-elevation and snow-covered regions over the TP. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.

scholarly journals A Parameterization of Sub-grid Topographical Effects on Solar Radiation in the E3SM Land Model (Version 1.0): Implementation and Evaluation Over the Tibetan Plateau

2021 ◽  
Author(s):  
Dalei Hao ◽  
Gautam Bisht ◽  
Yu Gu ◽  
Wei‐Liang Lee ◽  
Kuo-Nan Liou ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Surface Energy ◽  
Surface Temperature ◽  
Snow Cover ◽  
Land Surface ◽  
Spatial Scales ◽  
The Tibetan Plateau ◽  
Topographic Effects ◽  
Earth System

Abstract. Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth System Models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to evaluate the performance of ELM. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover and surface temperature especially in the high-elevation and snow-cover regions over the TP. Topography has non-negligible effects on surface energy budget, snow cover, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20 W/m2, 10 W/m2, and 5 W/m2, respectively. The differences in land surface albedo, snow cover fraction, and surface temperature between TOP and PP exceed 0.1, 20%, and 1K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations, and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are more significant with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.

scholarly journals Estimation of surface energy fluxes under complex terrain of Mt. Qomolangma over the Tibetan Plateau

2012 ◽  
Vol 9 (9) ◽  
pp. 10411-10445 ◽  
Author(s):  
X. Chen ◽  
Z. Su ◽  
Y. Ma ◽  
K. Yang ◽  
B. Wang
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Solar Radiation ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Sensible Heat Flux ◽  
The Tibetan Plateau ◽  
Surface Solar Radiation ◽  
Ground Heat Flux

Abstract. Surface solar radiation is an important parameter in surface energy balance models and in estimation of evapotranspiration. This study developed a DEM based radiation model to estimate instantaneous clear sky solar radiation for surface energy balance system to obtain accurate energy absorbed by the mountain surface. Efforts to improve spatial accuracy of satellite based surface energy budget in mountainous regions were made in this work. Based on 8 scenes of Landsat TM/ETM+ (Thematic Mapper/Enhanced Thematic Mapper+) data and observations around Qomolangma region of the Tibetan Plateau, the topographical enhanced surface energy balance system (TESEBS) was tested for deriving net radiation, ground heat flux, sensible heat flux and latent heat flux distributions over the heterogeneous land surface. The land surface energy fluxes over the study area showed a wide range in accordance with the surface features and their thermodynamic states. The model was validated by observations at QOMS/CAS site in the research area with a reasonable accuracy. The mean bias of net radiation, sensible heat flux, ground heat flux and latent heat flux is lower than 23.6 W m−2. The surface solar radiation estimated by the DEM based radiation model developed by this study has a mean bias as low as −9.6 W m−2.

scholarly journals A Review of Reconstructing Remotely Sensed Land Surface Temperature under Cloudy Conditions

2021 ◽  
Vol 13 (14) ◽  
pp. 2838
Author(s):  
Yaping Mo ◽  
Yongming Xu ◽  
Huijuan Chen ◽  
Shanyou Zhu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatial Scales ◽  
Remotely Sensed ◽  
Urban Heat Islands ◽  
Reconstruction Algorithms ◽  
Gap Filling ◽  
Practical Applications ◽  
Data Gaps

Land surface temperature (LST) is an important environmental parameter in climate change, urban heat islands, drought, public health, and other fields. Thermal infrared (TIR) remote sensing is the main method used to obtain LST information over large spatial scales. However, cloud cover results in many data gaps in remotely sensed LST datasets, greatly limiting their practical applications. Many studies have sought to fill these data gaps and reconstruct cloud-free LST datasets over the last few decades. This paper reviews the progress of LST reconstruction research. A bibliometric analysis is conducted to provide a brief overview of the papers published in this field. The existing reconstruction algorithms can be grouped into five categories: spatial gap-filling methods, temporal gap-filling methods, spatiotemporal gap-filling methods, multi-source fusion-based gap-filling methods, and surface energy balance-based gap-filling methods. The principles, advantages, and limitations of these methods are described and discussed. The applications of these methods are also outlined. In addition, the validation of filled LST values’ cloudy pixels is an important concern in LST reconstruction. The different validation methods applied for reconstructed LST datasets are also reviewed herein. Finally, prospects for future developments in LST reconstruction are provided.

scholarly journals Clarifying the role of radiative mechanisms in the spatio-temporal changes of land surface temperature across the Horn of Africa

2019 ◽  
Vol 221 ◽  
pp. 210-224 ◽  
Author(s):  
Temesgen Alemayehu Abera ◽  
Janne Heiskanen ◽  
Petri Pellikka ◽  
Miina Rautiainen ◽  
Eduardo Eiji Maeda
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temporal Changes ◽  
Horn Of Africa ◽  
Spatio Temporal

scholarly journals Mapping urban greenery to create the optimal cooling effect model against solar radiation under the conditions of a smart city

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Vladimír Sedlák ◽  
Katarína Onačillová ◽  
Michal Gallay ◽  
Jaroslav Hofierka ◽  
Ján Kaňuk ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Surface Temperature ◽  
Urban Environment ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Smart City ◽  
Research Study ◽  
Cooling Effect ◽  
Urban Greenery ◽  
Sentinel 2

<p><strong>Abstract.</strong> Current climate changes on a global scale require an optimal estimate of heat transfer in a complex urban environment as a part of the requirements for optimal urban planning in the conditions of a smart city. Urban greenery has a considerable impact on the cooling of the urban environment during thermal waves. Sentinel-2 as an Earth observation mission developed by the European Space Agency as part of the Copernicus Programme to perform terrestrial observations in support of various services could become a potential means also for quantified assessment of different urban scenarios where vegetation plays an essential role. The Sentinel-2 data provide higher spatial and temporal resolution than other similar missions allow.</p><p>The presented research study is aimed at exploiting the potential of Sentinel-2 in simulating the cooling effect of urban greenery as part of smart city mapping in assessing the quality of life of its inhabitants. The main objective of the research study is to define a methodical approach for spatial surface temperature modelling in selected urban areas based on the solar radiation modelling and parameterization of the land cover properties from the Sentinel-2 data. While solar irradiation can be accurately calculated at a fine scale using virtual 3D city models, it is difficult to find other important parameters for ground surface modelling such as surface thermal emissivity, broadband albedo and evapotranspiration. The research study was tested and verified in 4&amp;thinsp;sq.&amp;thinsp;km urban area in the selected central parts of the city of Košice in Slovakia (Figure 1). For a detailed survey, four sites (site 1 &amp;ndash; Moyzesova Street, site 2 &amp;ndash; Historical centre, site 3 &amp;ndash; City park, site 4 &amp;ndash; Hvozdíkov park) were chosen in the central city area. The virtual 3D urban model was created from the airborne LiDAR (Light Detection And Ranging, hereinafter referred to as the lidar) and photogrammetric data obtained in a single mission.</p><p>The aim of the research study was to assess the feasibility of using virtual 3D city models and multispectral satellite images to approximate surface temperature dynamics by modelling of the spatial distribution of solar radiation and land surface characteristics in a complex urban environment. A time-series of the Sentinel-2 data was collected for comparison with the reference time series of the terrestrial lidar (TLS &amp;ndash; Terrestrial Laser Scanning) data on urban greenery on four selected urban areas of the city of Košice. Between the vegetation metrics, the statistical linear relationship derived from the Sentinel-2 and TLS data was defined. Based on terrain mapping, a geobotanic database of urban trees was created. The algorithmic structure of a toolbox for the land surface temperature modelling in the open-source GRASS GIS was developed based on the Stefan-Boltzmann law and Kirchhoff rule.</p><p>This research study has highlighted how the Sentinel-2 data can be used to estimate of the broad-band albedo, surface emission, and solar transmittance to the vegetation of urban greenery. The main benefit of the research study is the developed algorithm for estimation of the land surface temperature in a GIS environment that provides a unique platform for integrating different types of data-sets to become usable in urban planning and for exploitation of the Sentinel-2 data in mitigation of a negative impact of the urban extreme heat islands on the quality of life of inhabitants. The resulting LST (Land Surface Temperature) was calculated for four scenarios using the detail of the study area of the site 1 (Figure 2) and whole study are (Figure 3) demonstrate. These figures also show the cooling effect of urban trees and shrubs.</p>

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

&lt;p&gt;Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.&lt;/p&gt;

scholarly journals Towards a more objective evaluation of modelled land-carbon trends using atmospheric CO<sub>2</sub> and satellite-based vegetation activity observations

2013 ◽  
Vol 10 (6) ◽  
pp. 4189-4210 ◽  
Author(s):  
D. Dalmonech ◽  
S. Zaehle
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Spatial Scales ◽  
Evaluation Framework ◽  
Atmospheric Co2 ◽  
Evaluation Methodology ◽  
Surface Model ◽  
System Modelling ◽  
Earth System ◽  
Vegetation Activity

Abstract. Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular the net land–atmosphere carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to better understand the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely sensed vegetation activity to provide a novel set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits) specifically considers the robustness of information given that the uncertainty of both data and evaluation methodology is largely unknown or difficult to quantify. Based on these considerations, we introduce a baseline benchmark – a minimum test that any model has to pass – to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI Earth System Model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite-based vegetation activity data allows pinpointing of specific model deficiencies that would not be possible by the sole use of atmospheric CO2 observations.

scholarly journals Investigating Seasonal Effects of Dominant Driving Factors on Urban Land Surface Temperature in a Snow-Climate City in China

2020 ◽  
Vol 12 (18) ◽  
pp. 3006
Author(s):  
Chaobin Yang ◽  
Fengqin Yan ◽  
Xuelei Lei ◽  
Xiuli Ding ◽  
Yue Zheng ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Snow Cover ◽  
Spatial Patterns ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Driving Factors ◽  
Seasonal Effects ◽  
Landsat 8 ◽  
Crop Species

Land surface temperature (LST) is a crucial parameter in surface urban heat island (SUHI) studies. A better understanding of the driving mechanisms, influencing variations in LST dynamics, is required for the sustainable development of a city. This study used Changchun, a city in northeast China, as an example, to investigate the seasonal effects of different dominant driving factors on the spatial patterns of LST. Twelve Landsat 8 images were used to retrieve monthly LST, to characterize the urban thermal environment, and spectral mixture analysis was employed to estimate the effect of the driving factors, and correlation and linear regression analyses were used to explore their relationships. Results indicate that, (1) the spatial pattern of LST has dramatic monthly and seasonal changes. August has the highest mean LST of 38.11 °C, whereas December has the lowest (−19.12 °C). The ranking of SUHI intensity is as follows: summer (4.89 °C) > winter with snow cover (1.94 °C) > spring (1.16 °C) > autumn (0.89 °C) > winter without snow cover (−1.24 °C). (2) The effects of driving factors also have seasonal variations. The proportion of impervious surface area (ISA) in summer (49.01%) is slightly lower than those in spring (56.64%) and autumn (50.85%). Almost half of the area is covered with snow (43.48%) in winter. (3) The dominant factors are quite different for different seasons. LST possesses a positive relationship with ISA for all seasons and has the highest Pearson coefficient for summer (r = 0.89). For winter, the effect of vegetation on LST is not obvious, and snow becomes the dominant driving factor. Despite its small area proportion, water has the strongest cooling effect from spring to autumn, and has a warming effect in winter. (4) Human activities, such as agricultural burning, harvest, and different choices of crop species, could also affect the spatial patterns of LST.

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