Estimation of ground heat flux and its impact on the surface energy budget for a semi-arid grassland

Three approaches, i.e., the harmonic analysis （HA） technique, the thermal diffusion equation and correction （TDEC） method, and the calorimetric method used to estimate ground heat flux, are evaluated by using observations from the Semi-Arid Climate and Environment Observatory of Lanzhou University （SACOL） in July, 2008. The calorimetric method, which involves soil heat flux measurement with an HFP01SC self-calibrating heat flux plate buried at a depth of 5 cm and heat storage in the soil between the plate and the surface, is here called the ITHP approach. The results show good linear relationships between the soil heat fluxes measured with the HFP01SC heat flux plate and those calculated with the HA technique and the TDEC method, respectively, at a depth of 5 cm. The soil heat fluxes calculated with the latter two methods well follow the phase measured with the HFP01SC heat flux plate. The magnitudes of the soil heat flux calculated with the HA technique and the TDEC method are close to each other, and they are about 2 percent and 6 percent larger than the measured soil heat flux, respectively, which mainly occur during the nighttime. Moreover, the ground heat fluxes calculated with the TDEC method and the HA technique are highly correlated with each other （R2= 0.97）, and their difference is only about 1 percent. The TDEC-calculated ground heat flux also has a good linear relationship with the ITttP-calculated ground heat flux （R2 = 0.99）, but their difference is larger （about 9 percent）. Furthermore, compared to the HFP01SC direct measurements at a depth of 5 cm, the ground heat flux calculated with the HA technique, the TDEC method, and the ITHP approach can improve the surface energy budget closure by about 6 percent, 7 percent, and 6 percent at SACOL site, respectively. Therefore, the contribution of ground heat flux to the surface energy budget is very important for the semi-arid grassland over the Loess Plateau in China. Using turbulent heat fluxes with common corrections, soil heat storage between the surface and the heat flux plate can improve the surface energy budget closure by about 6 to 7 percent, resulting in a closure of 82 to 83 percent at the SACOL site.

Case Analyses and Numerical Simulation of Soil ThermalImpacts on Land Surface Energy Budget Based on anOff-Line Land Surface Model

The statistical relationship between soil thermal anomaly and short-term climate change is presented based on a typical case study. Furthermore, possible physical mechanisms behind the relationship are re-vealed through using an off-line land surface model with a reasonable soil thermal forcing at the bottom of the soil layer. In the first experiment, the given heat flux is 5 W m2 at the bottom of the soil layer (in depth of 6.3 m) for 3 months, while only a positive ground temperature anomaly of 0.06°C can be found compared to the control run. The anomaly, however, could reach 0.65°C if the soil thermal conductivity was one order of magnitude larger. It could be even as large as 0.81°C assuming the heat flux at bottom is 10 W m-2. Mean-while, an increase of about 10 W m−2 was detected both for heat flux in soil and sensible heat on land sur-face, which is not neglectable to the short-term climate change. The results show that considerable response in land surface energy budget could be expected when the soil thermal forcing reaches a certain spatial-tem-poral scale. Therefore, land surface models should not ignore the upward heat flux from the bottom of the soil layer. Moreover, integration for a longer period of time and coupled land-atmosphere model are also necessary for the better understanding of this issue.

Satellite Monitoring of the Surface Water and Energy Budget in the Central Tibetan Plateau

The water and energy cycle in the Tibetan Plateau is an important component of Monsoon Asia and the global energy and water cycle. Using data at a CEOP （Coordinated Enhanced Observing Period）-Tibet site, this study presents a first-order evaluation on the skill of weather forecasting from GCMs and satellites in producing precipitation and radiation estimates. The satellite data, together with the satellite leaf area index, are then integrated into a land data assimilation system （LDAS-UT） to estimate the soil moisture and surface energy budget on the Plateau. The system directly assimilates the satellite microwave brightness temperature, which is strongly affected by soil moisture but not by cloud layers, into a simple biosphere model. A major feature of this system is a dual-pass assimilation technique, which can auto-calibrate model parameters in one pass and estimate the soil moisture and energy budget in the other pass. The system outputs, including soil moisture, surface temperature, surface energy partition, and the Bowen ratio, are compared with observations, land surface models, the Global Land Data Assimilation System, and four general circulation models. The results show that this satellite data-based system has a high potential for a reliable estimation of the regional surface energy budget on the Plateau.

Simulation of arctic surface radiation and energy budget during the summertime using the single-column model

The surface heat budget of the Arctic Ocean （SHEBA） project has shown that the study of the surface heat budget characteristics is crucial to understanding the interface process and environmental change in the polar region. An arctic single - column model （ARCSCM） of Colorado University is used to simulate the arctic surface radiation and energy budget during the summertime. The simulation results are analyzed and compared with the SHEBA measurements. Sensitivity analyses are performed to test microphysical and radiative parameterizations in this model. The results show that the ARCSCM model is able to simulate the surface radiation and energy budget in the arctic during the summertime, and the different parameterizations have a significant influence on the results. The combination of cloud microphysics and RRTM parameterizations can fairly derive the surface solar shortwave radiation and downwelling longwave radiation flux. But this cloud microphysics parameterization scheme deviates notably from the simulation of surface sensible and latent heat flux. Further improvement for the parameterization scheme applied to the Arctic Regions is necessary.

Understanding the Surface Temperature Cold Bias in CMIP5 AGCMs over the Tibetan Plateau

The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(Tas) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(Ts) over the TP. The cold biases are larger in Tasthan in Ts, and are larger over the western TP. By decomposing the Tsbias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models.

Land Surface Albedo Variations in Sanjiang Plain from 1982 to 2015: Assessing with GLASS Data

As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth’s surface energy budget(SEB). Since the Sanjiang Plain has been severely affected by human activities(e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite(GLASS) broadband surface albedo product. The results showed that: 1) an increasing annual trend(+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend(+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.

Analysis of surface temperature bias over the Tibetan plateau in the CAS FGOALS-f3-L model

The Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System atmospheric component model(FGOALS-f3-L)participated in Phase 6 of the Coupled Model Intercomparison Project,but its reproducibility of surface temperature(T_(s))over the Tibetan Plateau(TP)as a key climatically sensitive region remains unclear.This study evaluates the capability of FGOALS-f3-L in reproducing the climatological T_(s)over the TP relative to the Climate Forecast System Reanalysis.The results show that FGOALS-f3-L can reasonably capture the spatial pattern of T_(s)but underestimates the annual mean T_(s)for the whole TP.The simulated T_(s)for the whole TP shows a cold bias in winter and spring and a warm bias in summer and autumn.Further quantitative analysis based on the surface energy budget equation shows that the surface albedo feedback(SAF)term strongly contributes to the annual,winter,and spring mean cold bias in the western TP and to the warm bias in the eastern TP.Compared with the SAF term,the surface sensible and latent heat flux terms make nearly opposite contributions to the T_(s)bias and considerably offset the bias due to the SAF term.The cloud radiative forcing term strongly contributes to the annual and seasonal mean weak cold bias in the eastern TP.The longwave radiation term associated with the overestimated water vapor content accounts for a large portion of the warm bias over the whole TP in summer and autumn.Improving land surface and cloud processes in FGOALS-f3-L is critical to reduce the T_(s)bias over the TP.

Evaluation and spatio-temporal analysis of surface energy flux in permafrost regions over the Qinghai-Tibet Plateau and Arctic using CMIP6 models

The surface energy budget over the Qinghai-Tibet Plateau(QTP)and the Arctic significantly influences the climate system with global consequences.The performances of 30 selected Coupled Model Intercomparison Project Phase 6(CMIP6)models were evaluated based on six sites in the QTP and Arctic.The simulation results for latent heat flux(LE)were more accurate in the QTP,where the correlation coefficient and root mean square error(RMSE)were 0.9 and 30 W m−2,respectively.The results for sensible heat flux(H)were more accurate in the Arctic,the correlation coefficient and RMSE were 0.8 and 24 W m−2,respectively.Furthermore,the multiple models mean results revealed that the surface energy flux had seasonal variation and regional differences over the QTP and the Arctic.In the QTP,H was the lowest in winter,increased in spring,and reached the maximum in summer.However,the transitional changes in spring and autumn were not apparent in the Arctic,mainly due to seasonal net radiation difference between the two places.LE was affected by precipitation and surface soil moisture content.This work is important for understanding land-atmosphere interactions and useful for improving the accuracy of land surface models simulations.

SOME NEW UNDERSTANDINGS OF LAND-SURFACE PROCESSES IN ARID AREA FROM THE HEIFE

The survey for the HEIFE(Atmosphere-Land Surface Processes Experiment at Heihe River Basin,Western China)is given in the paper.The following basic subjects for land-surface process- es in arid areas are studied:(1)the general characteristics of the energy budget on ground surface in arid areas;(2)the parameterization of the land surface processes;(3)the interaction between oasis and its desert circumstances,a special phenomenon in arid areas.The analysis shows that the sensible heat flux in the surface energy budget is in the majority,and the latent heat flux may be neglected.The influence of atmospheric stratification stability on the turbulent transfer of energy and substance must be considered in parameterization of land surface processes in arid areas.The “cold island effect”phenomenon in oasis and the“humidity inversion”phenomenon in desert near oasis are the result of the interaction between them.The results would improve the understanding of land surface processes in arid areas.

A novel spectral index for mapping blue colour-coated steel roofs(BCCSRs)in urban areas using Sentinel-2 data

Blue colour-coated steel roofs(BCCSRs)offer a lightweight and economical option to concrete and other cladding in buildings,but they are also controversial for altering the surface energy budget and water cycle.Obtaining spatial information about BCCSRs is crucial for exploring the environmental impacts of man-made landscapes.However,existing methods are not always effective due to the variety of BCCSR types and background conditions.To overcome these limitations,we proposed a new index(called BCCSI)based on Sentinel-2 multispectral images to map the commonly used BCCSRs.Five typical study areas were chosen worldwide to develop and validate the BCcSl.Based on spectral analysis,we constructed the BCCSl using the blue,red,green,and shortwave infrared 2(SWIR2)bands to highlight the BCCSR while suppressing the background condition.Compared with five existing indices,the BCCSl was effective in the visual evaluation,separability analysis and BCCSR mapping.Moreover,the BCCSI achieved similar accuracy to the supervised classifier while avoiding the time-consuming and laborious effort of sample collection.Furthermore,the BCCSl showed its applicability in medium-resolution satellite data,such as Landsat-8 imagery.Thus,the proposed BCCSI provides a viable scheme for global BCCSR mapping and analysis.

On the turbulent heat fluxes:A comparison among satellite-based estimates,atmospheric reanalyses,and in-situ observations during the winter climate over Arctic sea ice

The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric boundary layer.Satellite observations(e.g.CERES and APPX)and atmospheric reanalyses(e.g.,ERA5)are often used to represent components of the energy budget at regional and pan-Arctic scales.However,the uncertainties of the satellite-based turbulent heat fluxes are largely unknown,and cross-comparisons with reanalysis data and insitu observations are limited.In this study,satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station(north of Svalbard,JanuaryeJune 2015)and ERA5 reanalysis.The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes,surface atmospheric parameters from ERA5,and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes,while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error(RMSE).CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons(RMSE of 18 and 7 W m^(-2)for sensible and latent heat flux,respectively).The aireice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production(MEP)method,respectively.Furthermore,errors in the surface and near-surface temperature and humidity explain almost 50%of the uncertainties in the estimates based on the bulk-formula,whereas errors in the net radiative fluxes explain more than 50%of the uncertainties in the MEP-based results.

Air temperature feedback and its contribution to global warming

Air temperature feedback results from the thermal-radiative coupling between the atmosphere and the surface and plays an important role in surface energy balance. This paper reveals the contribution of air temperature feedback to the global warming from 1980 to 2000. The air temperature feedback kernel, evaluated using the ERA-Interim reanalysis data, is used to discuss the physical mechanism for air temperature feedback, the dependency of the strength of air temperature feedback on the climatological spatial distributions of air temperature, water vapor and cloud content, and the contributions of air temperature feedback to rapid global warming. The coupling between temperature feedback and each of the external forcings and individual feedback processes will amplify the anomaly of direct energy flux convergence at the surface induced by the external forcings and individual processes. The air temperature feedback amplifies the initial surface warming due to the increase in CO2 concentration, ice and snow melting, increase in water vapor, and change in ocean heat storage. It also amplifies the surface warming due to the longwave radiaitve forcing associated with the increase in cloud cover, which acts to suppress the cooling of the shortwave effect of cloud forcing. Overall, temperature feedback plays an important role in the global warming from 1980 to2000, as the net positive contribution to the perturbation of global mean energy flux at the surface from the air temperature feedback is larger than the net negative contribution from external forcing and all non-temperature feedbacks.