The samples of brazed diamond grits with NiCr brazing alloy are prepared in vacuum and argon gas. The microstructures are analyzed with scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDS...The samples of brazed diamond grits with NiCr brazing alloy are prepared in vacuum and argon gas. The microstructures are analyzed with scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction(XRD). The effects of brazing atmospheres on the as-brazed NiCr brazing alloy composite structures and interracial microstructure are studied between diamond grits and brazing alloy. Results show that: (1) There are different composite structures of as-brazed NiCr brazing alloy under different oxygen partial pressures in vacuum and argon gas. B203 exists on the surface of the brazed samples under argon gas furnace brazing. It indicates that oxygen plays an important role in the resultants of as-brazed NiCr brazing alloy during the brazing process. (2) There are different interfacial microstructures in different brazing atmospheres, but the main reaction product is chromium carbides. The chromium carbides in argon gas furnace brazing grow in a disordered form, but those in vacuum furnace brazing grow radiated. And the scale of grains in argon gas is smaller than those in vacuum.展开更多
This paper uses a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to study the interaction between land surface and atmospheric boundary layer processes. The scheme is composed of two main parts: atmospheric boundary la...This paper uses a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to study the interaction between land surface and atmospheric boundary layer processes. The scheme is composed of two main parts: atmospheric boundary layer processes and land surface processes. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feasibility of the model is well proved in this paper. The numerical simulation results from MSPAS show good agreement with reality. The scheme is used to obtain reasonable simulations for diurnal variations of heat balance, potential temperature of boundary layer, and wind field, and spatial distributions of temperature, specific humidity, vertical velocity, turbulence kinetic energy, and turbulence exchange coefficient over desert and oasis. In addition, MSPAS is used to simulate the interaction between desert and oasis at night, and again it obtains reasonable results. This indicates that MSPAS can be used to study the interaction between land surface processes and the atmospheric boundary layer over various underlying surfaces and can be extended for regional climate and numerical weather prediction study.展开更多
Land-atmosphere coupling is a key process of the climate system, and various coupling mechanisms have been proposed before based on observational and numerical analyses. The impact of soil moisture(SM) on evapotrans...Land-atmosphere coupling is a key process of the climate system, and various coupling mechanisms have been proposed before based on observational and numerical analyses. The impact of soil moisture(SM) on evapotranspiration(ET) and further surface temperature(ST) is an important aspect of such coupling. Using ERA-Interim data and CLM4.0 offline simulation results, this study further explores the relationships between SM/ST and ET to better understand the complex nature of the land-atmosphere coupling(i.e., spatial and seasonal variations) in eastern China, a typical monsoon area. It is found that two diagnostics of land-atmosphere coupling(i.e., SM-ET correlation and ST-ET correlation) are highly dependent on the climatology of SM and ST. By combining the SM-ET and ST-ET relationships, two "hot spots" of land-atmosphere coupling over eastern China are identified: Southwest China and North China. In Southwest China, ST is relatively high throughout the year, but SM is lowest in spring, resulting in a strong coupling in spring. However, in North China, SM is relatively low throughout the year, but ST is highest in summer, which leads to the strongest coupling in summer. Our results emphasize the dependence of land-atmosphere coupling on the seasonal evolution of climatic conditions and have implications for future studies related to land surface feedbacks.展开更多
Atmosphere–land interactions simulated by an LES model are evaluated from the perspective of heterogeneity propagation by comparison with airborne measurements. It is found that the footprints of surface heterogeneit...Atmosphere–land interactions simulated by an LES model are evaluated from the perspective of heterogeneity propagation by comparison with airborne measurements. It is found that the footprints of surface heterogeneity, though as 2D patterns can be dissipated quickly due to turbulent mixing, as 1D projections can persist and propagate to the top of the atmospheric boundary layer. Direct comparison and length scale analysis show that the simulated heterogeneity patterns are comparable to the observation. The results highlight the model's capability in simulating the complex effects of surface heterogeneity on atmosphere–land interactions.展开更多
A new two-way land-atmosphere interaction model (R42_AVIM) is fulfilled by coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences...A new two-way land-atmosphere interaction model (R42_AVIM) is fulfilled by coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM). In this coupled model, physical and biological components of AVIM are both included. Climate base state and land surface physical fluxes simulated by R42_AVIM are analyzed and compared with the results of R42_SSIB [which is coupled by SAMIL_R42L9 and Simplified Simple Biosphere (SSIB) models]. The results show the performance of the new model is closer to the observations. It can basically guarantee that the land surface energy budget is balanced, and can simulate June-July-August (JJA) and December-January- February (DJF) land surface air temperature, sensible heat flux, latent heat flux, precipitation, sea level pressure and other variables reasonably well. Compared with R42_SSIB, there are obvious improvements in the JJA simulations of surface air temperature and surface fluxes. Thus, this land-atmosphere coupled model will offer a good experiment platform for land-atmosphere interaction research.展开更多
Energy used for industrial production, buildings and transport will be accumulated in Atmosphere and Earth land. Global use of energy is known and documented for a long period of time and proportion of fossil and rene...Energy used for industrial production, buildings and transport will be accumulated in Atmosphere and Earth land. Global use of energy is known and documented for a long period of time and proportion of fossil and renewable energy is also known. Calculated accumulated energy in Earth land from 1971 to 2018 corresponds to 40% of IPCC Global Energy Inventory and calculated Atmosphere temperature increase from 1971 to 2018 corresponds to 100% of actual measurements.展开更多
The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospect...The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospecting the latest research progress in the simulation of land-surface processes(LSPs) over the past 20 years, this study discusses both the simulation ability of land-surface models(LSMs) and the modification of parameterization schemes from two perspectives, the models' applicability and improved parameterization schemes. Our review suggests that different LSMs can well capture the spatiotemporal variations of the physical quantities of LSPs; but none of them can be fully applied to the plateau, meaning that all need to be revised according to the characteristics specific to the TP. Avoiding the unstable iterative computation and determining the freeze-thaw critical temperature according to the thermodynamic equilibrium equation, the unreasonable freeze-thaw parameterization scheme can be improved. Due to the complex underlying surface of the TP, no parameterization scheme of roughness length can well simulate the various characteristics of the turbulent flux over the TP at different temporal scales. The uniform soil thermodynamic and hydraulic parameterization scheme is unreasonable when it is applied to the plateau, as a result of the strong soil heterogeneity. There is little research on the snow-cover process so far,and the improved scheme has no advantage over the original one due to the lack of some related physical processes. The constant interaction among subprocesses of LSPs makes the improvement of a multiparameterization scheme yield better simulation results. According to the review of existing research, adding high-quality observation stations, developing a parameterization scheme suitable for the special LSPs of the TP, and adjusting the model structures can be helpful to the simulation of LSPs on the TP.展开更多
As part of a joint effort to construct an atmospheric forcing dataset for China's Mainland with high spatiotemporal reso- lution, a new approach is proposed to construct gridded near-surface temperature, relative ...As part of a joint effort to construct an atmospheric forcing dataset for China's Mainland with high spatiotemporal reso- lution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km× 1 km. The approach comprises two steps: (1) fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; (2) apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over China's Mainland. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Predic- tion (NCEP) Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.展开更多
In theory, land subsidence measurement results with high accuracy can be obtained by using the Differential Interferometry Synthetic Aperture Radar(D-InSAR) at X-band. In practice, however, the measuring accuracy of D...In theory, land subsidence measurement results with high accuracy can be obtained by using the Differential Interferometry Synthetic Aperture Radar(D-InSAR) at X-band. In practice, however, the measuring accuracy of D-InSAR at X-band has been seriously affected by some factors, e.g., decorrelation and high deformation gradient. In this work, the monitoring capability of D-InSAR for coal-mining subsidence is evaluated by using SAR data acquired by TerrraSAR-X system. The SAR image registration method for low coherence image pairs, the denoising phase filter for high noise level interferogram and atmospheric effects mitigation method are the key technical aspects which directly influence the measurement results of D-InSAR at X-band. Thus, a robust image registration method, an improved phase filter method and an atmospheric effects mitigation method are proposed in this paper. The proposed image registration method successfully achieves InSAR coregistration, while the amplitude cross-correlation cannot properly coregister low coherence SAR image pairs. Moreover, the time complexity of the proposed image registration method is obviously slighter than that of the Singular Value Decomposition(SVD) method. The comparing experiment results and the unwrapping phase results show that the improved Goldstein filter is more effective than the original Goldstein filter in noise elimination. The atmospheric influence correction experiment results show that the land subsidence areas with atmospheric influence correction are more clarified than that of without atmospheric influence correction. In summary, the presented methods directly improved the measurement results of D-InSAR at X-band.展开更多
Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(C...Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(CR)takes advantage of the inherent dynamic feedback mechanisms found in the soil−vegetation−atmosphere interface for its estimation of ET rates without the need of such biogeophysical data.ET estimates over the conterminous United States by a new,globally calibrated,static scaling(GCR-stat)of the generalized complementary relationship(GCR)of evaporation were compared to similar estimates of an existing,calibration-free version(GCR-dyn)of the GCR that employs a temporally varying dynamic scaling.Simplified annual water balances of 327 medium and 18 large watersheds served as ground-truth ET values.With long-term monthly mean forcing,GCR-stat(also utilizing precipitation measurements)outperforms GCR-dyn as the latter cannot fully take advantage of its dynamic scaling with such data of reduced temporal variability.However,in a continuous monthly simulation,GCR-dyn is on a par with GCR-stat,and especially excels in reproducing long-term tendencies in annual catchment ET rates even though it does not require precipitation information.The same GCR-dyn estimates were also compared to similar estimates of eight other popular ET products and they generally outperform all of them.For this reason,a dynamic scaling of the GCR is recommended over a static one for modeling long-term behavior of terrestrial ET.展开更多
This paper examines the performance of an atmospheric general circulation model (AGCM) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of ...This paper examines the performance of an atmospheric general circulation model (AGCM) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). It is a spectral model truncated at R42(2.8125°long×1.66°lat) resolution and with nine vertical levels, and referred to as R42L9/LASG hereafter. It is also the new version of atmospheric component model R15L9 of the global ocean-atmosphere-land system (GOALS/LASG). A 40-year simulation in which the model is forced with the climatological monthly mean sea surface temperature is compared with the 40-year (1958-97) U.S. National Center for Environmental Prediction (NGEP) global reanalysis and the 22-year (1979-2000) Xie-Arkin monthly precipitation climatology. The mean DJF and JJA geographical distributions of precipitation, sea level pressure, 500-hPa geopotential height, 850-hPa and 200-hPa zonal wind, and other fields averaged for the last 30-year integration of the R42L9 model are analyzed. Results show that the model reproduces well the observed basic patterns, particularly precipitation over the East Asian region. Comparing the new model with R15L9/LASG, the old version with coarse resolution (nearly 7.5°long×4.5°lat), shows an obvious improvement in the simulation of regional climate, especially precipitation. The weaknesses in simulation and future improvements of the model are also discussed.展开更多
This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 mill...This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software w<span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">ere</span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"> used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands </span><i><span style="font-family:Verdana;">i.e</span></i></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">.</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985</span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to 46.1314</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;">, and, 18.3437</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to 30.9693</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> respectively. Results of Kumasi also show a higher range of temperatures from 32.6986</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to 19.1077<span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span></span><span style="font-family:Verdana;">C</span><span style="font-family:Verdana;"> during the dry season. In the wet season, temperatures ranged from 26.4142</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to </span><span style="font-family:Verdana;">-</span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">0</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">.898728</span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;">. Among the reasons for the cities of Accra and Kumasi recorded higher than corresponding rural areas’ values can be attributed to the urban heat islands’ phenomenon.</span></span></span></span>展开更多
Alpine wetland is one of the typical underlying surfaces on the Qinghai–Tibet Plateau.It plays a crucial role in runoff regulation.Investigations on the mechanisms of water and heat exchanges are necessary to underst...Alpine wetland is one of the typical underlying surfaces on the Qinghai–Tibet Plateau.It plays a crucial role in runoff regulation.Investigations on the mechanisms of water and heat exchanges are necessary to understand the land surface processes over the alpine wetland.This study explores the characteristics of hydro-meteorological factors with in situ observations and uses the Community Land Model 5 to identify the main factors controlling water and heat exchanges.Latent heat flux and thermal roughness length were found to be greater in the warm season(June–August)than in the cold season(December–February),with a frozen depth of 20–40 cm over the alpine wetland.The transfers of heat fluxes were mainly controlled by longwave radiation and air temperature and affected by root distribution.Air pressure and stomatal conductance were also important to latent heat flux,and soil solid water content was important to sensible heat flux.Soil temperature was dominated by longwave radiation and air temperature,with crucial surface parameters of initial soil liquid water content and total water content.The atmospheric control factors transitioned to precipitation and air temperature for soil moisture,especially at the shallow layer(5 cm).Meanwhile,the more influential surface parameters were root distribution and stomatal conductance in the warm season and initial soil liquid water content and total water content in the cold season.This work contributes to the research on the land surface processes over the alpine wetland and is helpful to wetland protection.展开更多
基金supported by the National Key Technologies R&D Program of China[grant number 2022YFC3002803]the National Science Fund for Distinguished Young Scholars[grant number 41925021].
基金Supported by the National Natural Science Foundation of China(50475040)the Aeronautical Science Foundation of China(2005ZH52060)the Natural Science Foundation of Jiangsu Province(BK2006723)~~
文摘The samples of brazed diamond grits with NiCr brazing alloy are prepared in vacuum and argon gas. The microstructures are analyzed with scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction(XRD). The effects of brazing atmospheres on the as-brazed NiCr brazing alloy composite structures and interracial microstructure are studied between diamond grits and brazing alloy. Results show that: (1) There are different composite structures of as-brazed NiCr brazing alloy under different oxygen partial pressures in vacuum and argon gas. B203 exists on the surface of the brazed samples under argon gas furnace brazing. It indicates that oxygen plays an important role in the resultants of as-brazed NiCr brazing alloy during the brazing process. (2) There are different interfacial microstructures in different brazing atmospheres, but the main reaction product is chromium carbides. The chromium carbides in argon gas furnace brazing grow in a disordered form, but those in vacuum furnace brazing grow radiated. And the scale of grains in argon gas is smaller than those in vacuum.
基金supported by the National Natural Science Foundation of China (Grant No.40275004)the State Key Laboratory of Atmosphere Physics and Chemistry,and the City University of Hong Kong(Grant No.8780046)the City University of Hong Kong Strategic Research(Grant No.7001038)
文摘This paper uses a Modified Soil-Plant-Atmosphere Scheme (MSPAS) to study the interaction between land surface and atmospheric boundary layer processes. The scheme is composed of two main parts: atmospheric boundary layer processes and land surface processes. Compared with SiB and BATS, which are famous for their detailed parameterizations of physical variables, this simplified model is more convenient and saves much more computation time. Though simple, the feasibility of the model is well proved in this paper. The numerical simulation results from MSPAS show good agreement with reality. The scheme is used to obtain reasonable simulations for diurnal variations of heat balance, potential temperature of boundary layer, and wind field, and spatial distributions of temperature, specific humidity, vertical velocity, turbulence kinetic energy, and turbulence exchange coefficient over desert and oasis. In addition, MSPAS is used to simulate the interaction between desert and oasis at night, and again it obtains reasonable results. This indicates that MSPAS can be used to study the interaction between land surface processes and the atmospheric boundary layer over various underlying surfaces and can be extended for regional climate and numerical weather prediction study.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.41625019 and 41605042)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20151525)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘Land-atmosphere coupling is a key process of the climate system, and various coupling mechanisms have been proposed before based on observational and numerical analyses. The impact of soil moisture(SM) on evapotranspiration(ET) and further surface temperature(ST) is an important aspect of such coupling. Using ERA-Interim data and CLM4.0 offline simulation results, this study further explores the relationships between SM/ST and ET to better understand the complex nature of the land-atmosphere coupling(i.e., spatial and seasonal variations) in eastern China, a typical monsoon area. It is found that two diagnostics of land-atmosphere coupling(i.e., SM-ET correlation and ST-ET correlation) are highly dependent on the climatology of SM and ST. By combining the SM-ET and ST-ET relationships, two "hot spots" of land-atmosphere coupling over eastern China are identified: Southwest China and North China. In Southwest China, ST is relatively high throughout the year, but SM is lowest in spring, resulting in a strong coupling in spring. However, in North China, SM is relatively low throughout the year, but ST is highest in summer, which leads to the strongest coupling in summer. Our results emphasize the dependence of land-atmosphere coupling on the seasonal evolution of climatic conditions and have implications for future studies related to land surface feedbacks.
基金supported by the DFG Transregional Cooperative Research Centre 32 "Patterns in Soil-Vegetation-Atmosphere-Systems: Monitoring, Modelling and Data Assimilation"
文摘Atmosphere–land interactions simulated by an LES model are evaluated from the perspective of heterogeneity propagation by comparison with airborne measurements. It is found that the footprints of surface heterogeneity, though as 2D patterns can be dissipated quickly due to turbulent mixing, as 1D projections can persist and propagate to the top of the atmospheric boundary layer. Direct comparison and length scale analysis show that the simulated heterogeneity patterns are comparable to the observation. The results highlight the model's capability in simulating the complex effects of surface heterogeneity on atmosphere–land interactions.
基金This study is jointly supported by the National Key Basic Research 2006CB403607the Chinese Academy of Sciences(CAS)International Partnership Creative Group"The climate system model development and application studies"and the National Natural Science Foundation of China under Grant Nos.40221503,40475027 and 40523001.
文摘A new two-way land-atmosphere interaction model (R42_AVIM) is fulfilled by coupling the spectral atmospheric model (SAMIL_R42L9) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences (LASG/IAP/CAS) with the land surface model, Atmosphere-Vegetation-Interaction-Model (AVIM). In this coupled model, physical and biological components of AVIM are both included. Climate base state and land surface physical fluxes simulated by R42_AVIM are analyzed and compared with the results of R42_SSIB [which is coupled by SAMIL_R42L9 and Simplified Simple Biosphere (SSIB) models]. The results show the performance of the new model is closer to the observations. It can basically guarantee that the land surface energy budget is balanced, and can simulate June-July-August (JJA) and December-January- February (DJF) land surface air temperature, sensible heat flux, latent heat flux, precipitation, sea level pressure and other variables reasonably well. Compared with R42_SSIB, there are obvious improvements in the JJA simulations of surface air temperature and surface fluxes. Thus, this land-atmosphere coupled model will offer a good experiment platform for land-atmosphere interaction research.
文摘Energy used for industrial production, buildings and transport will be accumulated in Atmosphere and Earth land. Global use of energy is known and documented for a long period of time and proportion of fossil and renewable energy is also known. Calculated accumulated energy in Earth land from 1971 to 2018 corresponds to 40% of IPCC Global Energy Inventory and calculated Atmosphere temperature increase from 1971 to 2018 corresponds to 100% of actual measurements.
基金funded by the National Natural Science Foundation of China (41571066, 41601077, and 41771068)the Strategic Priority Research Pro gram of the Chinese Academy of Sciences (CAS) (XDA20100102, XDA19070204)+2 种基金the CAS "Light of West China" Programthe Youth Innovation Promo tion Association CAS (2018460)the Program of China Scholarship Council (201804910129)
文摘The Tibetan Plateau(TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospecting the latest research progress in the simulation of land-surface processes(LSPs) over the past 20 years, this study discusses both the simulation ability of land-surface models(LSMs) and the modification of parameterization schemes from two perspectives, the models' applicability and improved parameterization schemes. Our review suggests that different LSMs can well capture the spatiotemporal variations of the physical quantities of LSPs; but none of them can be fully applied to the plateau, meaning that all need to be revised according to the characteristics specific to the TP. Avoiding the unstable iterative computation and determining the freeze-thaw critical temperature according to the thermodynamic equilibrium equation, the unreasonable freeze-thaw parameterization scheme can be improved. Due to the complex underlying surface of the TP, no parameterization scheme of roughness length can well simulate the various characteristics of the turbulent flux over the TP at different temporal scales. The uniform soil thermodynamic and hydraulic parameterization scheme is unreasonable when it is applied to the plateau, as a result of the strong soil heterogeneity. There is little research on the snow-cover process so far,and the improved scheme has no advantage over the original one due to the lack of some related physical processes. The constant interaction among subprocesses of LSPs makes the improvement of a multiparameterization scheme yield better simulation results. According to the review of existing research, adding high-quality observation stations, developing a parameterization scheme suitable for the special LSPs of the TP, and adjusting the model structures can be helpful to the simulation of LSPs on the TP.
基金supported by the National Program on Key Basic Research Project of China (Grant Nos.2010CB951604 and 2010CB950703)the National Natural Science Foundation of China General Program (Grant Nos.40975062 and 40875062)+2 种基金R&D Special Fund for Nonprofit Industry (Grant No.Meteorology GYHY201206008)the Key Technologies Research and Development Program of China (Grant No.2013BAC05B04)the Fundamental Research Funds for the Central Universities (Grant No.2012LYB42)
文摘As part of a joint effort to construct an atmospheric forcing dataset for China's Mainland with high spatiotemporal reso- lution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km× 1 km. The approach comprises two steps: (1) fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; (2) apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over China's Mainland. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Predic- tion (NCEP) Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.
文摘In theory, land subsidence measurement results with high accuracy can be obtained by using the Differential Interferometry Synthetic Aperture Radar(D-InSAR) at X-band. In practice, however, the measuring accuracy of D-InSAR at X-band has been seriously affected by some factors, e.g., decorrelation and high deformation gradient. In this work, the monitoring capability of D-InSAR for coal-mining subsidence is evaluated by using SAR data acquired by TerrraSAR-X system. The SAR image registration method for low coherence image pairs, the denoising phase filter for high noise level interferogram and atmospheric effects mitigation method are the key technical aspects which directly influence the measurement results of D-InSAR at X-band. Thus, a robust image registration method, an improved phase filter method and an atmospheric effects mitigation method are proposed in this paper. The proposed image registration method successfully achieves InSAR coregistration, while the amplitude cross-correlation cannot properly coregister low coherence SAR image pairs. Moreover, the time complexity of the proposed image registration method is obviously slighter than that of the Singular Value Decomposition(SVD) method. The comparing experiment results and the unwrapping phase results show that the improved Goldstein filter is more effective than the original Goldstein filter in noise elimination. The atmospheric influence correction experiment results show that the land subsidence areas with atmospheric influence correction are more clarified than that of without atmospheric influence correction. In summary, the presented methods directly improved the measurement results of D-InSAR at X-band.
基金supported by a BMEWater Sciences and Disaster Prevention FIKP grant of EMMI(BME FIKP-VIZ).
文摘Most large-scale evapotranspiration(ET)estimation methods require detailed information of land use,land cover,and/or soil type on top of various atmospheric measurements.The complementary relationship of evaporation(CR)takes advantage of the inherent dynamic feedback mechanisms found in the soil−vegetation−atmosphere interface for its estimation of ET rates without the need of such biogeophysical data.ET estimates over the conterminous United States by a new,globally calibrated,static scaling(GCR-stat)of the generalized complementary relationship(GCR)of evaporation were compared to similar estimates of an existing,calibration-free version(GCR-dyn)of the GCR that employs a temporally varying dynamic scaling.Simplified annual water balances of 327 medium and 18 large watersheds served as ground-truth ET values.With long-term monthly mean forcing,GCR-stat(also utilizing precipitation measurements)outperforms GCR-dyn as the latter cannot fully take advantage of its dynamic scaling with such data of reduced temporal variability.However,in a continuous monthly simulation,GCR-dyn is on a par with GCR-stat,and especially excels in reproducing long-term tendencies in annual catchment ET rates even though it does not require precipitation information.The same GCR-dyn estimates were also compared to similar estimates of eight other popular ET products and they generally outperform all of them.For this reason,a dynamic scaling of the GCR is recommended over a static one for modeling long-term behavior of terrestrial ET.
文摘This paper examines the performance of an atmospheric general circulation model (AGCM) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). It is a spectral model truncated at R42(2.8125°long×1.66°lat) resolution and with nine vertical levels, and referred to as R42L9/LASG hereafter. It is also the new version of atmospheric component model R15L9 of the global ocean-atmosphere-land system (GOALS/LASG). A 40-year simulation in which the model is forced with the climatological monthly mean sea surface temperature is compared with the 40-year (1958-97) U.S. National Center for Environmental Prediction (NGEP) global reanalysis and the 22-year (1979-2000) Xie-Arkin monthly precipitation climatology. The mean DJF and JJA geographical distributions of precipitation, sea level pressure, 500-hPa geopotential height, 850-hPa and 200-hPa zonal wind, and other fields averaged for the last 30-year integration of the R42L9 model are analyzed. Results show that the model reproduces well the observed basic patterns, particularly precipitation over the East Asian region. Comparing the new model with R15L9/LASG, the old version with coarse resolution (nearly 7.5°long×4.5°lat), shows an obvious improvement in the simulation of regional climate, especially precipitation. The weaknesses in simulation and future improvements of the model are also discussed.
文摘This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software w<span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">ere</span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"> used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands </span><i><span style="font-family:Verdana;">i.e</span></i></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">.</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985</span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to 46.1314</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;">, and, 18.3437</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to 30.9693</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> respectively. Results of Kumasi also show a higher range of temperatures from 32.6986</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to 19.1077<span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span></span><span style="font-family:Verdana;">C</span><span style="font-family:Verdana;"> during the dry season. In the wet season, temperatures ranged from 26.4142</span><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;"> to </span><span style="font-family:Verdana;">-</span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">0</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">.898728</span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;"><span style="color:#4F4F4F;font-family:Simsun;font-size:14px;white-space:normal;background-color:#FFFFFF;">o</span></span></span>C</span><span style="font-family:Verdana;">. Among the reasons for the cities of Accra and Kumasi recorded higher than corresponding rural areas’ values can be attributed to the urban heat islands’ phenomenon.</span></span></span></span>
基金supported by the National Natural Science Foundation of China(Grant Nos.42005075,41975130)Natural Science Foundation of Gansu Province(Grant No.21JR7RA047)+1 种基金Open Research Fund Program of Plateau Atmosphere and Environment Key Laboratory of Sichuan Province(Grant No.PAEKL-2022-K03)the State Key Laboratory of Cryospheric Science(Grant No.SKLCS-ZZ-2023,SKLCS-ZZ-2022).
文摘Alpine wetland is one of the typical underlying surfaces on the Qinghai–Tibet Plateau.It plays a crucial role in runoff regulation.Investigations on the mechanisms of water and heat exchanges are necessary to understand the land surface processes over the alpine wetland.This study explores the characteristics of hydro-meteorological factors with in situ observations and uses the Community Land Model 5 to identify the main factors controlling water and heat exchanges.Latent heat flux and thermal roughness length were found to be greater in the warm season(June–August)than in the cold season(December–February),with a frozen depth of 20–40 cm over the alpine wetland.The transfers of heat fluxes were mainly controlled by longwave radiation and air temperature and affected by root distribution.Air pressure and stomatal conductance were also important to latent heat flux,and soil solid water content was important to sensible heat flux.Soil temperature was dominated by longwave radiation and air temperature,with crucial surface parameters of initial soil liquid water content and total water content.The atmospheric control factors transitioned to precipitation and air temperature for soil moisture,especially at the shallow layer(5 cm).Meanwhile,the more influential surface parameters were root distribution and stomatal conductance in the warm season and initial soil liquid water content and total water content in the cold season.This work contributes to the research on the land surface processes over the alpine wetland and is helpful to wetland protection.