scholarly journals Application of fractional calculus in ground heat flux estimation

2012 ◽  
Vol 16 (2) ◽  
pp. 373-384 ◽  
Author(s):  
Milan Protic ◽  
Miomir Stankovic ◽  
Dragan Mitic ◽  
Branimir Todorovic
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Land Surface ◽  
Ground Surface ◽  
Physical Factor ◽  
Soil Heat Flux ◽  
Analytic Solutions ◽  
Ground Heat Flux ◽  
Balance Analysis ◽  
Energy Balance Analysis

Ground (soil) heat flux is important physical factor primarily because of its role in surface energy balance, analysis of atmospheric boundary layer and land surface-atmosphere interaction. Direct measurement of this property is often associated with difficulties arising from need for adequate calibration of measuring devices, determination of proper depth for probes, upward water migration and accumulation below measuring plates to lack of understanding of the governing thermal processes occurring at the ground surface. In the following paper approach for inferring heat flux indirectly, from known ground surface temperature time-dependant functions, using previously developed fractional diffusion equation for ground heat conduction is elaborated. Fractional equation is solved for two, most frequently encountered harmonic surface temperature functions. Yielded results were compared with analytic solutions. Validation results indicate that solutions obtained with fractional approach closely correspond to analytic solutions with remark that former are more general, containing the term covering the transitional effect.

scholarly journals Estimating Surface Soil Heat Flux in Permafrost Regions Using Remote Sensing-Based Models on the Northern Qinghai-Tibetan Plateau under Clear-Sky Conditions

2019 ◽  
Vol 11 (4) ◽  
pp. 416 ◽  
Author(s):  
Cheng Yang ◽  
Tonghua Wu ◽  
Jiemin Wang ◽  
Jimin Yao ◽  
Ren Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Surface Soil ◽  
Ground Surface ◽  
Soil Heat Flux ◽  
Parameterization Scheme ◽  
Clear Sky ◽  
Sky Conditions ◽  
Permafrost Regions

The ground surface soil heat flux (G0) quantifies the energy transfer between the atmosphere and the ground through the land surface. However; it is difficult to obtain the spatial distribution of G0 in permafrost regions because of the limitation of in situ observation and complication of ground surface conditions. This study aims at developing an improved G0 parameterization scheme applicable to permafrost regions of the Qinghai-Tibet Plateau under clear-sky conditions. We validated several existing remote sensing-based models to estimate G0 by analyzing in situ measurement data. Based on the validation of previous models on G0; we added the solar time angle to the G0 parameterization scheme; which considered the phase difference problem. The maximum values of RMSE and MAE between “measured G0” and simulated G0 using the improved parameterization scheme and in situ data were calculated to be 6.102 W/m2 and 5.382 W/m2; respectively. When the error of the remotely sensed land surface temperature is less than 1 K and the surface albedo measured is less than 0.02; the accuracy of estimates based on remote sensing data for G0 will be less than 5%. MODIS data (surface reflectance; land surface temperature; and emissivity) were used to calculate G0 in a 10 x 10 km region around Tanggula site; which is located in the continuous permafrost region with long-term records of meteorological and permafrost parameters. The results obtained by the improved scheme and MODIS data were consistent with the observation. This study enhances our understanding of the impacts of climate change on the ground thermal regime of permafrost and the land surface processes between atmosphere and ground surface in cold regions.

scholarly journals Characteristic Variation of Ground Heat Flux and Net Radiation at Tropical Station in Ile-Ife, Osun State, Nigeria

2020 ◽  
pp. 35-42
Author(s):  
A. Usman ◽  
B. B. Ibrahim ◽  
L. A. Sunmonu
Keyword(s):  
Heat Flux ◽  
Research Work ◽  
Soil Heat Flux ◽  
Entire Period ◽  
Net Radiation ◽  
Sampled Data ◽  
Minimum Value ◽  
Maximum Value ◽  
Characteristic Variation ◽  
Ground Heat Flux

Characteristic variation of ground heat flux and net radiation enhances the understanding of the significance of indicated trends of variability to everyday life and factors that might be responsible for such variations. This research work critically analyses some specific days with field data over grass-covered surface at Ile-Ife, Nigeria between ground heat flux and net radiation. For the field observations, an instrumented meteorological mast was set up at an experimental site (7°33’N, 4°35’E) located at Obafemi Awolowo University campus, Ile-Ife, Nigeria for a period of two weeks (31st May-14th June, 2013). The soil heat flux, net radiation and soil temperature from the soil heat flux plate; an all-wave net radiometer, and soil thermometer were recorded every 10 seconds and averaged over 2 minutes interval. The sampled data was stored in the data logger (Campbell Scientific, Model CR10X) storage module. After the removal of spurious measurement values (Quality Assurance and Quality Control), the data stored was further reduced to 30 minutes averages using the Microcal Origin (version 7.0) data analysis software. The results showed that the measured ground heat flux, HGM during the daytime increases until 1400 hrs with maximum value of about 136.86 Wm-2 and minimum value of about -72.87 Wm-2 at 0830 hrs (DOY 156). The measured net radiation, Rn value of 649.65 Wm-2 observed at 1400 hrs (DOY 156), represented the maximum value for the entire period of the study. -10.75 Wm-2 value observed at1800 hrs (DOY 154), represented the minimum value for the entire period of the study due to the cloudy condition of the sky which reduces the amount of incoming solar radiation reaching the earth surface.

scholarly journals Simulation of Land Surface Climate over China with RegCM4.5: Verification and Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Minghao Yang ◽  
Ruiting Zuo ◽  
Liqiong Wang ◽  
Xiong Chen
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface Temperature ◽  
South China ◽  
Land Surface ◽  
Reanalysis Data ◽  
Surface Evaporation

The ability of RegCM4.5 using land surface scheme CLM4.5 to simulate the physical variables related to land surface state was investigated. The NCEP-NCAR reanalysis data for the period 1964–2003 were used to drive RegCM4.5 to simulate the land surface temperature, precipitation, soil moisture, latent heat flux, and surface evaporation. Based on observations and reanalysis data, a few land surface variables were analyzed over China. The results showed that some seasonal features of land surface temperature in summer and winter as well as its magnitude could be simulated well. The simulation of precipitation was sensitive to region and season. The model could, to a certain degree, simulate the seasonal migration of rainband in East China. The overall spatial distribution of the simulated soil moisture was better in winter than in summer. The simulation of latent heat flux was also better in winter. In summer, the latent heat flux bias mainly arose from surface evaporation bias in Northwest China, and it primarily arose from vegetation evapotranspiration bias in South China. In addition, the large latent heat flux bias in South China during summer was probably due to less precipitation generated in the model and poor representation of vegetation cover in this region.

scholarly journals Evaluation of functional properties of various types of vegetation cover using remotely sensed data analysis

2010 ◽  
Vol 4 (Special Issue 2) ◽  
pp. S49-S58 ◽  
Author(s):  
J. Brom ◽  
J. Procházka ◽  
A. Rejšková
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Remotely Sensed Data ◽  
Mean Values

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.

scholarly journals Evaluation of the ground heat flux simulated by a multi-layer land surface scheme using high-quality observations at grass land and bare soil

2016 ◽  
Vol 25 (5) ◽  
pp. 607-620 ◽  
Author(s):  
Jan-Peter Schulz ◽  
Gerd Vogel ◽  
Claudia Becker ◽  
Steffen Kothe ◽  
Udo Rummel ◽  
...  
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Bare Soil ◽  
High Quality ◽  
Land Surface Scheme ◽  
Grass Land ◽  
Ground Heat Flux ◽  
Surface Scheme

Intercomparison of Spatially Distributed Models for Predicting Surface Energy Flux Patterns during SMACEX

2005 ◽  
Vol 6 (6) ◽  
pp. 941-953 ◽  
Author(s):  
Wade T. Crow ◽  
Fuqin Li ◽  
William P. Kustas
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Energy Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Energy Fluxes ◽  
Spatially Distributed

Abstract The treatment of aerodynamic surface temperature in soil–vegetation–atmosphere transfer (SVAT) models can be used to classify approaches into two broad categories. The first category contains models utilizing remote sensing (RS) observations of surface radiometric temperature to estimate aerodynamic surface temperature and solve the terrestrial energy balance. The second category contains combined water and energy balance (WEB) approaches that simultaneously solve for surface temperature and energy fluxes based on observations of incoming radiation, precipitation, and micrometeorological variables. To date, few studies have focused on cross comparing model predictions from each category. Land surface and remote sensing datasets collected during the 2002 Soil Moisture–Atmosphere Coupling Experiment (SMACEX) provide an opportunity to evaluate and intercompare spatially distributed surface energy balance models. Intercomparison results presented here focus on the ability of a WEB-SVAT approach [the TOPmodel-based Land–Atmosphere Transfer Scheme (TOPLATS)] and an RS-SVAT approach [the Two-Source Energy Balance (TSEB) model] to accurately predict patterns of turbulent energy fluxes observed during SMACEX. During the experiment, TOPLATS and TSEB latent heat flux predictions match flux tower observations with root-mean-square (rms) accuracies of 67 and 63 W m−2, respectively. TSEB predictions of sensible heat flux are significantly more accurate with an rms accuracy of 22 versus 46 W m−2 for TOPLATS. The intercomparison of flux predictions from each model suggests that modeling errors for each approach are sufficiently independent and that opportunities exist for improving the performance of both models via data assimilation and model calibration techniques that integrate RS- and WEB-SVAT energy flux predictions.

scholarly journals Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models

2010 ◽  
Vol 11 (5) ◽  
pp. 1103-1122 ◽  
Author(s):  
Rolf H. Reichle ◽  
Sujay V. Kumar ◽  
Sarith P. P. Mahanama ◽  
Randal D. Koster ◽  
Q. Liu
Keyword(s):  
Heat Flux ◽  
Data Assimilation ◽  
Skin Temperature ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Open Loop ◽  
Surface Model ◽  
Ground Heat Flux ◽  
Assimilation System

Abstract Land surface (or “skin”) temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research LST retrievals from the International Satellite Cloud Climatology Project (ISCCP) are assimilated into the Noah land surface model and Catchment land surface model (CLSM) using an ensemble-based, offline land data assimilation system. LST is described very differently in the two models. A priori scaling and dynamic bias estimation approaches are applied because satellite and model LSTs typically exhibit different mean values and variabilities. Performance is measured against 27 months of in situ measurements from the Coordinated Energy and Water Cycle Observations Project at 48 stations. LST estimates from Noah and CLSM without data assimilation (“open loop”) are comparable to each other and superior to ISCCP retrievals. For LST, the RMSE values are 4.9 K (CLSM), 5.5 K (Noah), and 7.6 K (ISCCP), and the anomaly correlation coefficients (R) are 0.61 (CLSM), 0.63 (Noah), and 0.52 (ISCCP). Assimilation of ISCCP retrievals provides modest yet statistically significant improvements (over an open loop, as indicated by nonoverlapping 95% confidence intervals) of up to 0.7 K in RMSE and 0.05 in the anomaly R. The skill of the latent and sensible heat flux estimates from the assimilation integrations is essentially identical to the corresponding open loop skill. Noah assimilation estimates of ground heat flux, however, can be significantly worse than open loop estimates. Provided the assimilation system is properly adapted to each land model, the benefits from the assimilation of LST retrievals are comparable for both models.

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