Accurate satellite data assimilation under all-sky conditions requires enhanced parameterization of scattering properties for frozen hydrometeors in clouds.This study aims to develop a nonspherical scattering look-up ...Accurate satellite data assimilation under all-sky conditions requires enhanced parameterization of scattering properties for frozen hydrometeors in clouds.This study aims to develop a nonspherical scattering look-up table that contains the optical properties of five hydrometeor types—rain,cloud water,cloud ice,graupel,and snow—for the Advanced Radiative Transfer Modeling System(ARMS)at frequencies below 220 GHz.The discrete dipole approximation(DDA)method is employed to compute the single-scattering properties of solid cloud particles,modeling these particles as aggregated roughened bullet rosettes.The bulk optical properties of the cloud layer are derived by integrating the singlescattering properties with a modified Gamma size distribution,specifically for distributions with 18 effective radii.The bulk phase function is then projected onto a series of generalized spherical functions,applying the delta-M method for truncation.The results indicate that simulations using the newly developed nonspherical scattering look-up table exhibit significant consistency with observations under deep convection conditions.In contrast,assuming spherical solid cloud particles leads to excessive scattering at mid-frequency channels and insufficient scattering at high-frequency channels.This improvement in radiative transfer simulation accuracy for cloudy conditions will better support the assimilation of allsky microwave observations into numerical weather prediction models.·Frozen cloud particles were modeled as aggregates of bullet rosettes and the optical properties at microwave range were computed by DDA.·A complete process and technical details for constructing a look-up table of ARMS are provided.·The ARMS simulations generally show agreement with observations of MWTS and MWHS under typhoon conditions using the new look-up table.展开更多
In this paper, firstly, a simplified version （SGRTM） of the generalized layered radiative transfer model （GRTM） within the canopy, developed by us, is presented. It reduces the information requirement of inputted ...In this paper, firstly, a simplified version （SGRTM） of the generalized layered radiative transfer model （GRTM） within the canopy, developed by us, is presented. It reduces the information requirement of inputted sky diffuse radiation, as well as of canopy morphology, and in turn saves computer resources. Results from the SGRTM agree perfectly with those of the GRTM. Secondly, by applying the linear superposition principle of the optics and by using the basic solutions of the GRTM for radiative transfer within the canopy under the condition of assumed zero soil reflectance, two sets of explicit analytical solutions of radiative transfer within the canopy with any soil reflectance magnitude are derived： one for incident diffuse, and the other for direct beam radiation. The explicit analytical solutions need two sets of basic solutions of canopy reflectance and transmittance under zero soil reflectance, run by the model for both diffuse and direct beam radiation. One set of basic solutions is the canopy reflectance αf （written as α1 for direct beam radiation） and transmittance βf （written as β1 for direction beam radiation） with zero soil reflectance for the downward radiation from above the canopy （i.e. sky）, and the other set is the canopy reflectance （αb） and transmittance βb for the upward radiation from below the canopy （i.e., ground）. Under the condition of the same plant architecture in the vertical layers, and the same leaf adaxial and abaxial optical properties in the canopies for the uniform diffuse radiation, the explicit solutions need only one set of basic solutions, because under this condition the two basic solutions are equal, i.e., αf = αb and βf = βb. Using the explicit analytical solutions, the fractions of any kind of incident solar radiation reflected from （defined as surface albedo, or canopy reflectance）, transmitted through （defined as canopy transmittance）, and absorbed by （defined as canopy absorptance） the canopy and other properties pertinent to the radiative transfer within the canopy can be estimated easily on the ground surface below the canopy （soil or snow surface） with any reflectance magnitudes. The simplified transfer model is proven to have a similar accuracy compared to the detailed model, as well as very efficient computing.展开更多
Forward radiative transfer(RT)models are essential for atmospheric applications such as remote sensing and weather and climate models,where computational efficiency becomes equally as important as accuracy for high-re...Forward radiative transfer(RT)models are essential for atmospheric applications such as remote sensing and weather and climate models,where computational efficiency becomes equally as important as accuracy for high-resolution hyperspectral measurements that need rigorous RT simulations for thousands of channels.This study introduces a fast and accurate RT model for the hyperspectral infrared(HIR)sounder based on principal component analysis(PCA)or machine learning(i.e.,neural network,NN).The Geosynchronous Interferometric Infrared Sounder(GIIRS),the first HIR sounder onboard the geostationary Fengyun-4 satellites,is considered to be a candidate example for model development and validation.Our method uses either PCA or NN(PCA/NN)twice for the atmospheric transmittance and radiance,respectively,to reduce the number of independent but similar simulations to accelerate RT simulations;thereby,it is referred to as a multi-domain compression model.The first PCA/NN gives monochromatic gas transmittance in both spectral and atmospheric pressure domains for each gas independently.The second PCA/NN is performed in the traditional spectral radiance domain.Meanwhile,a new method is introduced to choose representative variables for the PCA/NN scheme developments.The model is three orders of magnitude faster than the standard line-by-line-based simulations with averaged brightness temperature difference(BTD)less than 0.1 K,and the compressions based on PCA or NN methods result in comparable efficiency and accuracy.Our fast model not only avoids an excessively complicated transmittance scheme by using PCA/NN but is also highly flexible for hyperspectral instruments with similar spectral ranges simply by updating the corresponding spectral response functions.展开更多
The radiative transfer is one of the significant theories that describe the processes of scattering, emission, and absorption of electromagnetic radiant intensity through scattering medium. It is the basis of the stud...The radiative transfer is one of the significant theories that describe the processes of scattering, emission, and absorption of electromagnetic radiant intensity through scattering medium. It is the basis of the study on the quan-titative remote sensing. In this paper, the radiative characteristics of soil, vegetation, and atmosphere were described respectively. The numerical solution of radiative transfer was accomplished by Successive Orders of Scattering (SOS). A radiative transfer model for simulating microwave brightness temperature over land surfaces was constructed, de-signed, and implemented. Analyzing the database generated from soil-vegetation-atmosphere radiative transfer model under Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) configuration showed that the atmospheric effects on microwave brightness temperature should not be neglected, particularly for higher frequency, and can be parameterized. At the same time, the relationship between the emissivities of the different channels was developed. The study results will promote the development of algorithm to retrieve geophysical parameters from mi-crowave remotely sensed data.展开更多
Two microwave radiative transfer models of precipitating cloud are used to simulate the microwave upwelling radiances emerging from precipitating clouds. Comparison of the simulation results shows that significant dif...Two microwave radiative transfer models of precipitating cloud are used to simulate the microwave upwelling radiances emerging from precipitating clouds. Comparison of the simulation results shows that significant difference of microwave upwelling radiances exists between these two radiative transfer models. Analysis of these differences in different cloud and precipitation conditions shows that it is complicated but has certain trend for different microwave frequencies. The results may be useful to quantitative rainfall rate retrieval of real precipitating clouds.展开更多
As a typical physical retrieval algorithm for retrieving atmospheric parameters,one-dimensional variational(1 DVAR)algorithm is widely used in various climate and meteorological communities and enjoys an important pos...As a typical physical retrieval algorithm for retrieving atmospheric parameters,one-dimensional variational(1 DVAR)algorithm is widely used in various climate and meteorological communities and enjoys an important position in the field of microwave remote sensing.Among algorithm parameters affecting the performance of the 1 DVAR algorithm,the accuracy of the microwave radiative transfer model for calculating the simulated brightness temperature is the fundamental constraint on the retrieval accuracies of the 1 DVAR algorithm for retrieving atmospheric parameters.In this study,a deep neural network(DNN)is used to describe the nonlinear relationship between atmospheric parameters and satellite-based microwave radiometer observations,and a DNN-based radiative transfer model is developed and applied to the 1 DVAR algorithm to carry out retrieval experiments of the atmospheric temperature and humidity profiles.The retrieval results of the temperature and humidity profiles from the Microwave Humidity and Temperature Sounder(MWHTS)onboard the Feng-Yun-3(FY-3)satellite show that the DNN-based radiative transfer model can obtain higher accuracy for simulating MWHTS observations than that of the operational radiative transfer model RTTOV,and also enables the 1 DVAR algorithm to obtain higher retrieval accuracies of the temperature and humidity profiles.In this study,the DNN-based radiative transfer model applied to the 1 DVAR algorithm can fundamentally improve the retrieval accuracies of atmospheric parameters,which may provide important reference for various applied studies in atmospheric sciences.展开更多
Water stress is a crucial environmental factor that impacts the growth and yield of rice.Complex field micro-climates and fluctuating water conditions pose a considerable challenge in accurately evaluating water stres...Water stress is a crucial environmental factor that impacts the growth and yield of rice.Complex field micro-climates and fluctuating water conditions pose a considerable challenge in accurately evaluating water stress.Measurement of a particular crop trait is not sufficient for accurate evaluation of the effects of complex water stress.Four comprehensive indicators were introduced in this research,including canopy chlorophyll content(CCC)and canopy equivalent water(CEW).The response of the canopy-specific traits to different types of water stress was identified through individual plant experiments.A hybrid method integrating the PROSAIL radiative transfer model and multidimensional imaging data to retrieve these traits.The synthetic dataset generated by PROSAIL was utilized as prior knowledge for developing a pre-trained machine learning model.Subsequently,reflectance separated from hyperspectral images and phenotypic indicators extracted from front-view images were innovatively united to retrieve water stress-related traits.The results demonstrated that the hybrid method exhibited improved stability and accuracy of CCC(R=0.7920,RMSE=24.971μg cm^(-2))and CEW(R=0.8250,RMSE=0.0075 cm)compared to both data-driven and physical inversion modeling methods.Overall,a robust and accurate method is proposed for assessing water stress in rice using a combination of radiative transfer modeling and multidimensional image-based data.展开更多
Accurate monitoring and spatial distribution of the leaf chlorophyll content(LCC)and canopy chlorophyll content(CCC)of individual apple trees are highly important for the effective management of individual plants and ...Accurate monitoring and spatial distribution of the leaf chlorophyll content(LCC)and canopy chlorophyll content(CCC)of individual apple trees are highly important for the effective management of individual plants and the promotion of the construction of modern smart orchards.However,the estimation of LCC and CCC is affected by shadows caused by canopy structure and observation geometry.In this study,we resolved the response rela-tionship between individual apple tree crown spectra and shadows through a three-dimensional radiative transfer model(3D RTM)and unmanned aerial vehicle(UAV)multispectral images,assessed the resistance of a series of vegetation indices(VIs)to shadows and developed a hybrid inversion model that is resistant to shadow inter-ference.The results revealed that(1)the proportion of individual tree canopy shadows exhibited a parabolic trend with time,with a minimum occurring at noon.Correspondingly,the reflectance in the visible band decreased with increasing canopy shadow ratio and reached a maximum value at noon,whereas the pattern of change in the reflectance in the near-infrared band was opposite that in the visible band.(2)The accuracy of chlorophyll content estimation varies among different VIs at different canopy shadow ratios.The top five VIs that are most resistant to changes in canopy shadow ratios are the NDVI-RE,Cire,Cigreen,TVI,and GNDVI.(3)For the con-structed 3D RTM+GPR hybrid inversion model,only four VIs,namely,NDVI-RE,Cire,Cigreen,and TVI,need to be input to achieve the best inversion accuracy.(4)Both the LCC and the CCC of individual trees had good validation accuracy(LCC:R^(2)=0.775,RMSE=6.86μg/cm^(2),nRMSE=12.24%;CCC:R^(2)=0.784,RMSE=32.33μg/cm^(2),and nRMSE=14.49%),and their distributions at orchard scales were characterized by considerable spatial heterogeneity.This study provides ideas for investigating the response between individual tree canopy shadows and spectra and offers a new strategy for minimizing the influence of shadow effects on the accurate estimation of chlorophyll content in individual apple trees.展开更多
Accurate and real-time monitoring true leaf area index(LAI)is an essential for assessing crop growth status and predicting yields.Conventional LAI inversion approaches have been constrained by insufficient data repres...Accurate and real-time monitoring true leaf area index(LAI)is an essential for assessing crop growth status and predicting yields.Conventional LAI inversion approaches have been constrained by insufficient data represen-tativeness and environmental variability,particularly when applied across interannual variations and different phenological stages.This study presented a novel methodology integrating three-dimensional radiative transfer modeling(3D RTM)with knowledge-guided deep learning to address these limitations.We developed a knowledge-guided convolutional neural network(KGCNN)architecture incorporating 3D canopy structural physics,enhanced through transfer learning(TL)techniques for cross-temporal adaptation.The KGCNN model was initially pre-trained on synthetic datasets generated by the large-scale remote sensing scattering model(LESS),followed by domain-specific fine-tuning using 2021 field measurements,and culminating in cross-year validation with 2022-2023 datasets.Our results demonstrated significant improvements over conventional ap-proaches,with the 3D RTM-based KGCNN achieving superior performance compared to 1D RTM implementations(PROSAIL+CNN+TL).Specially,for the 2022 dataset,the overall R^(2) increased by 0.27 and RMSE decreased by 2.46;for the 2023 dataset,the overall RMSE decreased by 1.62,compared to the PROSAIL+TL method.Our method(3D RTM+KGCNN+TL)delivered superior LAI retrieval accuracy on the two-year datasets compared to LSTM+TL,RNN+TL,and 3D RTM+RF models.This study also introduced an effective 3D scene modeling strategy that integrates scenarios representing the measured data range with additional synthetic scenes gener-ated through random combinations of structural parameters.By incorporating detailed 3D crop structural in-formation into the KGCNN network and fine-tuning the model with measured data,the approach significantly enhanced the model's adaptability to varying data distributions across different years and growth stages.This approach thus improved both the accuracy and stability of true LAI retrieval.展开更多
Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies.Here,we compared a radiative transfer model(RTM)inversion by m...Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies.Here,we compared a radiative transfer model(RTM)inversion by merit function and five machine learning algorithms trained on an RTM simulated dataset predicting the three plant traits leaf chlorophyll content(LCC),canopy chlorophyll content(CCC),and leaf area index(LAI),in a mixed temperate forest.The accuracy of the retrieval methods in predicting these three plant traits with spectral data from Sentinel-2 acquired on 13 July 2017 over Bavarian Forest National Park,Germany,was evaluated using in situ measurements collected contemporaneously.The RTM inversion using merit function resulted in estimations of LCC(R^(2)=0.26,RMSE=3.9µg/cm^(2)),CCC(R^(2)=0.65,RMSE=0.33 g/m^(2)),and LAI(R^(2)=0.47,RMSE=0.73 m^(2)/m^(2)),comparable to the estimations based on the machine learning method Random forest regression of LCC(R^(2)=0.34,RMSE=4.06µg/cm^(2)),CCC(R^(2)=0.65,RMSE=0.34 g/m^(2)),and LAI(R^(2)=0.47,RMSE=0.75 m^(2)/m^(2)).Several of the machine learning algorithms also yielded accuracies and robustness similar to the RTM inversion using merit function.The performance of regression methods trained on synthetic datasets showed promise for fast and accurate mapping of plant traits accross different plant functional types from remote sensing data.展开更多
Forward radiative transfer models(RTM)are an indispensable tool for quantitative applications of satellite radiometers,e.g.,for data calibration,instrument development,retrieval,and so on.In this study,we develop an a...Forward radiative transfer models(RTM)are an indispensable tool for quantitative applications of satellite radiometers,e.g.,for data calibration,instrument development,retrieval,and so on.In this study,we develop an accurate and efficient RTM for radiometers onboard Fengyun satellites,namely FYRTM(RTM for Fengyun Radiometers).Correlated k-distribution models are developed to improve the computational efficiency for gas absorption,and the effects of cloud and aerosol multiple scattering and emission are accelerated with pre-computed look-up tables.FYRTM is evaluated with a rigorous simulation based on discrete ordinate radiative transfer model(DISORT)as well as a popular fast forward model,i.e.,the Community Radiative Transfer Model(CRTM).Results indicate that FYRTM-based simulations are two to three orders of magnitudes faster than the DISORT-based simulations.Compared to the rigorous model,FYRTM relative errors are within 2%at solar channels,and brightness temperatures(BT)differences are within 1 K at infrared channels.Compared with CRTM,FYRTM is computationally similar at solar channels,but three times faster at infrared channels.Furthermore,simulated reflectances/BTs using FYRTM are in a good agreement with the satellite observations.Overall,FYRTM is capable to simulate satellite observations under different atmospheric conditions,and can be extended to other radiometers onboard the Fengyun satellites(both geostationary and polarorbiting satellites).It is expected to play important roles in future applications with Fengyun observations.展开更多
A fractional vegetation cover(FVC)estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed,which was suitable for FVC estimation in homogeneous areas because th...A fractional vegetation cover(FVC)estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed,which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarseresolution FVC pixel were all assumed to have the same vegetation growth model.However,this assumption does not hold over heterogeneous areas,meaning that the method cannot be applied to large regions.Therefore,this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite(GLASS)FVC product.The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data.Then,independent dynamic vegetation models were built for each finer-resolution pixel.Finally,the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale.Validation results indicated that the proposed method(R^(2)=0.7757,RMSE=0.0881)performed better than either the previous method(R^(2)=0.7038,RMSE=0.1125)or a commonly used method involving look-up table inversions of the PROSAIL model(R^(2)=0.7457,RMSE=0.1249).展开更多
Tree height composition describes the relative abundance of trees in different height levels and performs as a critical characteristic for community ecology.The recent launched full-waveform spaceborne LiDAR(Light Det...Tree height composition describes the relative abundance of trees in different height levels and performs as a critical characteristic for community ecology.The recent launched full-waveform spaceborne LiDAR(Light Detection and Ranging),i.e.,Global Ecosystem Dynamics Investigation(GEDI),can map canopy height,but whether this observation reflects tree height composition remains untested.In this study,we firstly conduct numerical simulations to explore to what extent tree height composition can be obtained from GEDI waveform signals.We simulate waveforms for diverse forest scenarios using GEDI simulator coupled with LESS(LargE-Scale remote sensing data and image Simulation),a state-of-the-art radiative transfer model.We devise a minimalistic model,Tree generation based on Asymmetric generalized Gaussian(TAG),for customizing tree objects to accelerate forest scene creation.The results demonstrate that tree objects generated by TAG perform similarly in LiDAR simulation with objects from commercial 3-dimensional software.Results of simulated GEDI waveforms reasonably respond to the variation of crown architectures in even-aged forests.GEDI waveforms have an acceptable ability to identify different height layers within multi-layer forests,except for fir forests with a cone-shaped crown.The shape metric of waveforms reflects the height of each layer,while retrieval accuracy decreases with the increases in height variations within each layer.A 5-m interval between layers is the minimum requirement so that the different height layers can be separated.A mixture of different tree species reduces the retrieval accuracy of tree height layers.We also utilize real GEDI observations to retrieve tree heights in multi-height-layer forests.The findings indicate that GEDI waveforms are also efficient in identifying tree height composition in practical forest scenarios.Overall,results from this study demonstrate that GEDI waveforms can reflect the height composition within typical forest stands.展开更多
A high-resolution dual-band terahertz(THz) radiometer was designed to measure vertical distributions of chemical elements in the middle atmosphere of the Tibetan Plateau. A forward simulation, which always should be c...A high-resolution dual-band terahertz(THz) radiometer was designed to measure vertical distributions of chemical elements in the middle atmosphere of the Tibetan Plateau. A forward simulation, which always should be conducted firstly for the development of a matching retrieval algorithm, has not been done before. We use two radiative transfer models, ARTS and AM, to simulate the water vapor, ozone and carbon monoxide spectra on the plateau based on the spectral design of the THz radiometer. The emission line characteristics of the three gases in this spectral band are identified. Reasons for the differences in the spectral simulations between the two models are analyzed for individual gases. The impact of several different spectral parameter settings on the simulations are evaluated through a series of sensitivity experiments. This study suggests that the ARTS is more suitable for the development of the THz radiometer retrieval algorithm. An optimal parameter setting of the ARTS for the three elements are given.展开更多
An overall vector radiative transfer theory was developed for numerical modeling, in both active and passive microwave remote sensing. The Theory and approaches are briefly summerized.To quantitatively understand scat...An overall vector radiative transfer theory was developed for numerical modeling, in both active and passive microwave remote sensing. The Theory and approaches are briefly summerized.To quantitatively understand scattering and thermal emission from targets in active and passive remote sensing, we have developed an overall vector radiative transfer theory for a set of theoretical models of discrete scatterer and continuous random media for the earth terrain (wet soil, vegetation, snow, sea-ice, etc.) and atmosphere, and numerical approaches for simulation, data analysis, and parameter sensitivity test. Our numerical results favorably agreed with experimental data in microwave re mote sensing of various earth surfaces. Main approaches are briefly summerized herewith.展开更多
This paper compares the predictions by two radiative transfer models-the two-stream approximation model and the generalized layered model （developed by the authors） in land surface processes -for different canopies ...This paper compares the predictions by two radiative transfer models-the two-stream approximation model and the generalized layered model （developed by the authors） in land surface processes -for different canopies under direct or diffuse radiation conditions. The comparison indicates that there are significant differences between the two models, especially in the near infrared （NIR） band. Results of canopy reflectance from the two-stream model are larger than those from the generalized model. However, results of canopy absorptance from the two-stream model are larger in some cases and smaller in others compared to those from the generalized model, depending on the cases involved. In the visible （VIS） band, canopy reflectance is smaller and canopy absorptance larger from the two-stream model compared to the generalized model when the Leaf Area Index （LAI） is low and soil reflectance is high. In cases of canopies with vertical leaf angles, the differences of reflectance and absorptance in the VIS and NIR bands between the two models are especially large. Two commonly occurring cases, with which the two-stream model cannot deal accurately, are also investigated. One is for a canopy with different adaxial and abaxial leaf optical properties; and the other is for incident sky diffuse radiation with a non-uniform distribution. Comparison of the generalized model within the same canopy for both uniform and non-uniform incident diffuse radiation inputs shows smaller differences in general. However, there is a measurable difference between these radiation inputs for a canopy with high leaf angle. This indicates that the application of the two-stream model to a canopy with different adaxial and abaxial leaf optical properties will introduce non-negligible errors.展开更多
The radiance leaving the earth-atmosphere system which can be sensed by a satellite borne radiometer is the sum of radiation emission from the earth surface and each atmospheric level that are transmitted to the top o...The radiance leaving the earth-atmosphere system which can be sensed by a satellite borne radiometer is the sum of radiation emission from the earth surface and each atmospheric level that are transmitted to the top of the atmosphere. The radiation emission from the earth surface and the radiance of each atmospheric level can be separated from the radiance at the top the atmospheric level measured by a satellite borne radiometer. However, it is very difficult to measure the atmospheric radiance, especially the synchronous measurement with the satellite. Thus some atmospheric radiative transfer models have been developed to provide many options for modeling atmospheric radiation transport, such as LOWTRAN, MODTRAN, 6S, FASCODE, LBLRTM, SHARC, and SAMM. Meanwhile, these models can support the detailed detector system design, the optimization and evaluation of satellite mission parameters, and the data processing procedures. As an example, the newly atmospheric radiative transfer models, MODTRAN will be compared with other models after the atmospheric radiative transfer is described. And the atmospheric radiative transfer simulation procedures and their applications to atmospheric transmittance, retrieval of atmospheric elements, and surface parameters, will also be presented.展开更多
This research investigates a numerical simulation of swirling turbulent non-premixed combustion.The effects on the combustion characteristics are examined with three turbulence models:namely as the Reynolds stress mod...This research investigates a numerical simulation of swirling turbulent non-premixed combustion.The effects on the combustion characteristics are examined with three turbulence models:namely as the Reynolds stress model,spectral turbulence analysis and Re-Normalization Group.In addition,the P-1 and discrete ordinate(DO)models are used to simulate the radiative heat transfer in this model.The governing equations associated with the required boundary conditions are solved using the numerical model.The accuracy of this model is validated with the published experimental data and the comparison elucidates that there is a reasonable agreement between the obtained values from this model and the corresponding experimental quantities.Among different models proposed in this research,the Reynolds stress model with the Probability Density Function(PDF)approach is more accurate(nearly up to 50%)than other turbulent models for a swirling flow field.Regarding the effect of radiative heat transfer model,it is observed that the discrete ordinate model is more precise than the P-1 model in anticipating the experimental behavior.This model is able to simulate the subcritical nature of the isothermal flow as well as the size and shape of the internal recirculation induced by the swirl due to combustion.展开更多
Accurate estimates of albedos are required in climate modeling. Accurate and simple schemes for radiative transfer within canopy are required for these estimates, but severe limitations exist. This paper developed a f...Accurate estimates of albedos are required in climate modeling. Accurate and simple schemes for radiative transfer within canopy are required for these estimates, but severe limitations exist. This paper developed a four-stream solar radiative transfer model and coupled it with a land surface process model. The radiative model uses a four-stream approximation method as in the atmosphere to obtain analytic solutions of the basic equation of canopy radiative transfer. As an analytical model, the four-stream radiative transfer model can be easily applied efficiently to improve the parameterization of land surface radiation in climate models. Our four-stream solar radiative transfer model is based on a two-stream short wave radiative transfer model. It can simulate short wave solar radiative transfer within canopy according to the relevant theory in the atmosphere. Each parameter of the basic radiative transfer equation of canopy has special geometry and optical characters of leaves or canopy. The upward or downward radiative fluxes are related to the diffuse phase function, the G-function, leaf reflectivity and transmission, leaf area index, and the solar angle of the incident beam. The four-stream simulation is compared with that of the two-stream model. The four-stream model is proved successful through its consistent modeling of canopy albedo at any solar incident angle. In order to compare and find differences between the results predicted by the four- and two-stream models, a number of numerical experiments are performed through examining the effects of different leaf area indices, leaf angle distributions, optical properties of leaves, and ground surface conditions on the canopy albedo. Parallel experiments show that the canopy albedos predicted by the two models differ significantly when the leaf angle distribution is spherical and vertical. The results also show that the difference is particularly great for different incident solar beams. One additional experiment is carried out to evaluate the simulations of the BATS land surface model coupled with the two- and four-stream radiative transfer models. Station observations in 1998 are used for comparison. The results indicate that the simulation of BATS coupled with the four-stream model is the best because the surface absorbed solar radiation from the four-stream model is the closest to the observation.展开更多
Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely appli...Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests,due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales.Fortunately,some of important tree structure parameters such as canopy height and tree density distribution have been available globally.This enables to run the intermediate complexities of the 3-D MCRT models.We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density.It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms.The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA,respectively.Results demonstrated that the simulations of bidirectional reflectance factor(BRF)based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error(RMSE)and relative RMSE(rRMSE)ranging from 0.002 to 0.006 and from 0.7%to 19.8%,respectively.Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%,respectively.Although the results from the current study are limited in two boreal forest stands,our approach has the potential to generate stand structures for different forest biomes.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2021YFB3900400)the National Natural Science Foundation of China(Grant Nos.U2142212 and 42361074)。
文摘Accurate satellite data assimilation under all-sky conditions requires enhanced parameterization of scattering properties for frozen hydrometeors in clouds.This study aims to develop a nonspherical scattering look-up table that contains the optical properties of five hydrometeor types—rain,cloud water,cloud ice,graupel,and snow—for the Advanced Radiative Transfer Modeling System(ARMS)at frequencies below 220 GHz.The discrete dipole approximation(DDA)method is employed to compute the single-scattering properties of solid cloud particles,modeling these particles as aggregated roughened bullet rosettes.The bulk optical properties of the cloud layer are derived by integrating the singlescattering properties with a modified Gamma size distribution,specifically for distributions with 18 effective radii.The bulk phase function is then projected onto a series of generalized spherical functions,applying the delta-M method for truncation.The results indicate that simulations using the newly developed nonspherical scattering look-up table exhibit significant consistency with observations under deep convection conditions.In contrast,assuming spherical solid cloud particles leads to excessive scattering at mid-frequency channels and insufficient scattering at high-frequency channels.This improvement in radiative transfer simulation accuracy for cloudy conditions will better support the assimilation of allsky microwave observations into numerical weather prediction models.·Frozen cloud particles were modeled as aggregates of bullet rosettes and the optical properties at microwave range were computed by DDA.·A complete process and technical details for constructing a look-up table of ARMS are provided.·The ARMS simulations generally show agreement with observations of MWTS and MWHS under typhoon conditions using the new look-up table.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos. 40233034, 40575043the Chinese Academy of Sciences （KZCX3_SW_229）.
文摘In this paper, firstly, a simplified version （SGRTM） of the generalized layered radiative transfer model （GRTM） within the canopy, developed by us, is presented. It reduces the information requirement of inputted sky diffuse radiation, as well as of canopy morphology, and in turn saves computer resources. Results from the SGRTM agree perfectly with those of the GRTM. Secondly, by applying the linear superposition principle of the optics and by using the basic solutions of the GRTM for radiative transfer within the canopy under the condition of assumed zero soil reflectance, two sets of explicit analytical solutions of radiative transfer within the canopy with any soil reflectance magnitude are derived： one for incident diffuse, and the other for direct beam radiation. The explicit analytical solutions need two sets of basic solutions of canopy reflectance and transmittance under zero soil reflectance, run by the model for both diffuse and direct beam radiation. One set of basic solutions is the canopy reflectance αf （written as α1 for direct beam radiation） and transmittance βf （written as β1 for direction beam radiation） with zero soil reflectance for the downward radiation from above the canopy （i.e. sky）, and the other set is the canopy reflectance （αb） and transmittance βb for the upward radiation from below the canopy （i.e., ground）. Under the condition of the same plant architecture in the vertical layers, and the same leaf adaxial and abaxial optical properties in the canopies for the uniform diffuse radiation, the explicit solutions need only one set of basic solutions, because under this condition the two basic solutions are equal, i.e., αf = αb and βf = βb. Using the explicit analytical solutions, the fractions of any kind of incident solar radiation reflected from （defined as surface albedo, or canopy reflectance）, transmitted through （defined as canopy transmittance）, and absorbed by （defined as canopy absorptance） the canopy and other properties pertinent to the radiative transfer within the canopy can be estimated easily on the ground surface below the canopy （soil or snow surface） with any reflectance magnitudes. The simplified transfer model is proven to have a similar accuracy compared to the detailed model, as well as very efficient computing.
基金supported by the National Natural Science Foundation of China(Grant No.42122038)。
文摘Forward radiative transfer(RT)models are essential for atmospheric applications such as remote sensing and weather and climate models,where computational efficiency becomes equally as important as accuracy for high-resolution hyperspectral measurements that need rigorous RT simulations for thousands of channels.This study introduces a fast and accurate RT model for the hyperspectral infrared(HIR)sounder based on principal component analysis(PCA)or machine learning(i.e.,neural network,NN).The Geosynchronous Interferometric Infrared Sounder(GIIRS),the first HIR sounder onboard the geostationary Fengyun-4 satellites,is considered to be a candidate example for model development and validation.Our method uses either PCA or NN(PCA/NN)twice for the atmospheric transmittance and radiance,respectively,to reduce the number of independent but similar simulations to accelerate RT simulations;thereby,it is referred to as a multi-domain compression model.The first PCA/NN gives monochromatic gas transmittance in both spectral and atmospheric pressure domains for each gas independently.The second PCA/NN is performed in the traditional spectral radiance domain.Meanwhile,a new method is introduced to choose representative variables for the PCA/NN scheme developments.The model is three orders of magnitude faster than the standard line-by-line-based simulations with averaged brightness temperature difference(BTD)less than 0.1 K,and the compressions based on PCA or NN methods result in comparable efficiency and accuracy.Our fast model not only avoids an excessively complicated transmittance scheme by using PCA/NN but is also highly flexible for hyperspectral instruments with similar spectral ranges simply by updating the corresponding spectral response functions.
基金Under the auspices of National Natural Science Foundation of China (No. 40425012)"Hundred Talent" Program of Chinese Academy of Sciences
文摘The radiative transfer is one of the significant theories that describe the processes of scattering, emission, and absorption of electromagnetic radiant intensity through scattering medium. It is the basis of the study on the quan-titative remote sensing. In this paper, the radiative characteristics of soil, vegetation, and atmosphere were described respectively. The numerical solution of radiative transfer was accomplished by Successive Orders of Scattering (SOS). A radiative transfer model for simulating microwave brightness temperature over land surfaces was constructed, de-signed, and implemented. Analyzing the database generated from soil-vegetation-atmosphere radiative transfer model under Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) configuration showed that the atmospheric effects on microwave brightness temperature should not be neglected, particularly for higher frequency, and can be parameterized. At the same time, the relationship between the emissivities of the different channels was developed. The study results will promote the development of algorithm to retrieve geophysical parameters from mi-crowave remotely sensed data.
基金This work is supported by the National Natural Science Foundation of China.
文摘Two microwave radiative transfer models of precipitating cloud are used to simulate the microwave upwelling radiances emerging from precipitating clouds. Comparison of the simulation results shows that significant difference of microwave upwelling radiances exists between these two radiative transfer models. Analysis of these differences in different cloud and precipitation conditions shows that it is complicated but has certain trend for different microwave frequencies. The results may be useful to quantitative rainfall rate retrieval of real precipitating clouds.
基金National Natural Science Foundation of China(41901297,41806209)Science and Technology Key Project of Henan Province(202102310017)+1 种基金Key Research Projects for the Universities of Henan Province(20A170013)China Postdoctoral Science Foundation(2021M693201)。
文摘As a typical physical retrieval algorithm for retrieving atmospheric parameters,one-dimensional variational(1 DVAR)algorithm is widely used in various climate and meteorological communities and enjoys an important position in the field of microwave remote sensing.Among algorithm parameters affecting the performance of the 1 DVAR algorithm,the accuracy of the microwave radiative transfer model for calculating the simulated brightness temperature is the fundamental constraint on the retrieval accuracies of the 1 DVAR algorithm for retrieving atmospheric parameters.In this study,a deep neural network(DNN)is used to describe the nonlinear relationship between atmospheric parameters and satellite-based microwave radiometer observations,and a DNN-based radiative transfer model is developed and applied to the 1 DVAR algorithm to carry out retrieval experiments of the atmospheric temperature and humidity profiles.The retrieval results of the temperature and humidity profiles from the Microwave Humidity and Temperature Sounder(MWHTS)onboard the Feng-Yun-3(FY-3)satellite show that the DNN-based radiative transfer model can obtain higher accuracy for simulating MWHTS observations than that of the operational radiative transfer model RTTOV,and also enables the 1 DVAR algorithm to obtain higher retrieval accuracies of the temperature and humidity profiles.In this study,the DNN-based radiative transfer model applied to the 1 DVAR algorithm can fundamentally improve the retrieval accuracies of atmospheric parameters,which may provide important reference for various applied studies in atmospheric sciences.
基金funded by the National Natural Science Foundation of China,China(52279042)the National Key Research and Development program of China,China(2021YFC3201204)the Key Research and Development Program in Guangxi,China(AB23026021).
文摘Water stress is a crucial environmental factor that impacts the growth and yield of rice.Complex field micro-climates and fluctuating water conditions pose a considerable challenge in accurately evaluating water stress.Measurement of a particular crop trait is not sufficient for accurate evaluation of the effects of complex water stress.Four comprehensive indicators were introduced in this research,including canopy chlorophyll content(CCC)and canopy equivalent water(CEW).The response of the canopy-specific traits to different types of water stress was identified through individual plant experiments.A hybrid method integrating the PROSAIL radiative transfer model and multidimensional imaging data to retrieve these traits.The synthetic dataset generated by PROSAIL was utilized as prior knowledge for developing a pre-trained machine learning model.Subsequently,reflectance separated from hyperspectral images and phenotypic indicators extracted from front-view images were innovatively united to retrieve water stress-related traits.The results demonstrated that the hybrid method exhibited improved stability and accuracy of CCC(R=0.7920,RMSE=24.971μg cm^(-2))and CEW(R=0.8250,RMSE=0.0075 cm)compared to both data-driven and physical inversion modeling methods.Overall,a robust and accurate method is proposed for assessing water stress in rice using a combination of radiative transfer modeling and multidimensional image-based data.
基金funded by the Natural Science Foundation of China(42171303,42371373)the Special Fund for Construction of Scientific and Technological Innovation Ability of Beijing Academy of Agriculture and Forestry Sciences(KJCX20230434).
文摘Accurate monitoring and spatial distribution of the leaf chlorophyll content(LCC)and canopy chlorophyll content(CCC)of individual apple trees are highly important for the effective management of individual plants and the promotion of the construction of modern smart orchards.However,the estimation of LCC and CCC is affected by shadows caused by canopy structure and observation geometry.In this study,we resolved the response rela-tionship between individual apple tree crown spectra and shadows through a three-dimensional radiative transfer model(3D RTM)and unmanned aerial vehicle(UAV)multispectral images,assessed the resistance of a series of vegetation indices(VIs)to shadows and developed a hybrid inversion model that is resistant to shadow inter-ference.The results revealed that(1)the proportion of individual tree canopy shadows exhibited a parabolic trend with time,with a minimum occurring at noon.Correspondingly,the reflectance in the visible band decreased with increasing canopy shadow ratio and reached a maximum value at noon,whereas the pattern of change in the reflectance in the near-infrared band was opposite that in the visible band.(2)The accuracy of chlorophyll content estimation varies among different VIs at different canopy shadow ratios.The top five VIs that are most resistant to changes in canopy shadow ratios are the NDVI-RE,Cire,Cigreen,TVI,and GNDVI.(3)For the con-structed 3D RTM+GPR hybrid inversion model,only four VIs,namely,NDVI-RE,Cire,Cigreen,and TVI,need to be input to achieve the best inversion accuracy.(4)Both the LCC and the CCC of individual trees had good validation accuracy(LCC:R^(2)=0.775,RMSE=6.86μg/cm^(2),nRMSE=12.24%;CCC:R^(2)=0.784,RMSE=32.33μg/cm^(2),and nRMSE=14.49%),and their distributions at orchard scales were characterized by considerable spatial heterogeneity.This study provides ideas for investigating the response between individual tree canopy shadows and spectra and offers a new strategy for minimizing the influence of shadow effects on the accurate estimation of chlorophyll content in individual apple trees.
基金supported by the National Key Research and Development Program of China(2021YFD2000102)the Natural Science Foundation of China(42371373)the Special Fund for Construction of Scientific and Technological Innovation Ability of Beijing Academy of Agriculture and Forestry Sciences(KJCX20230434).
文摘Accurate and real-time monitoring true leaf area index(LAI)is an essential for assessing crop growth status and predicting yields.Conventional LAI inversion approaches have been constrained by insufficient data represen-tativeness and environmental variability,particularly when applied across interannual variations and different phenological stages.This study presented a novel methodology integrating three-dimensional radiative transfer modeling(3D RTM)with knowledge-guided deep learning to address these limitations.We developed a knowledge-guided convolutional neural network(KGCNN)architecture incorporating 3D canopy structural physics,enhanced through transfer learning(TL)techniques for cross-temporal adaptation.The KGCNN model was initially pre-trained on synthetic datasets generated by the large-scale remote sensing scattering model(LESS),followed by domain-specific fine-tuning using 2021 field measurements,and culminating in cross-year validation with 2022-2023 datasets.Our results demonstrated significant improvements over conventional ap-proaches,with the 3D RTM-based KGCNN achieving superior performance compared to 1D RTM implementations(PROSAIL+CNN+TL).Specially,for the 2022 dataset,the overall R^(2) increased by 0.27 and RMSE decreased by 2.46;for the 2023 dataset,the overall RMSE decreased by 1.62,compared to the PROSAIL+TL method.Our method(3D RTM+KGCNN+TL)delivered superior LAI retrieval accuracy on the two-year datasets compared to LSTM+TL,RNN+TL,and 3D RTM+RF models.This study also introduced an effective 3D scene modeling strategy that integrates scenarios representing the measured data range with additional synthetic scenes gener-ated through random combinations of structural parameters.By incorporating detailed 3D crop structural in-formation into the KGCNN network and fine-tuning the model with measured data,the approach significantly enhanced the model's adaptability to varying data distributions across different years and growth stages.This approach thus improved both the accuracy and stability of true LAI retrieval.
文摘Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies.Here,we compared a radiative transfer model(RTM)inversion by merit function and five machine learning algorithms trained on an RTM simulated dataset predicting the three plant traits leaf chlorophyll content(LCC),canopy chlorophyll content(CCC),and leaf area index(LAI),in a mixed temperate forest.The accuracy of the retrieval methods in predicting these three plant traits with spectral data from Sentinel-2 acquired on 13 July 2017 over Bavarian Forest National Park,Germany,was evaluated using in situ measurements collected contemporaneously.The RTM inversion using merit function resulted in estimations of LCC(R^(2)=0.26,RMSE=3.9µg/cm^(2)),CCC(R^(2)=0.65,RMSE=0.33 g/m^(2)),and LAI(R^(2)=0.47,RMSE=0.73 m^(2)/m^(2)),comparable to the estimations based on the machine learning method Random forest regression of LCC(R^(2)=0.34,RMSE=4.06µg/cm^(2)),CCC(R^(2)=0.65,RMSE=0.34 g/m^(2)),and LAI(R^(2)=0.47,RMSE=0.75 m^(2)/m^(2)).Several of the machine learning algorithms also yielded accuracies and robustness similar to the RTM inversion using merit function.The performance of regression methods trained on synthetic datasets showed promise for fast and accurate mapping of plant traits accross different plant functional types from remote sensing data.
基金supported by the National Natural Science Foundation of China(Grant No.41975025)the Natural Science Foundation of Jiangsu Province(Grant No.BK20190093)+1 种基金the Young Elite Scientists Sponsorship Program by CAST(Grant No.2017QNRC001)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX18_1004)。
文摘Forward radiative transfer models(RTM)are an indispensable tool for quantitative applications of satellite radiometers,e.g.,for data calibration,instrument development,retrieval,and so on.In this study,we develop an accurate and efficient RTM for radiometers onboard Fengyun satellites,namely FYRTM(RTM for Fengyun Radiometers).Correlated k-distribution models are developed to improve the computational efficiency for gas absorption,and the effects of cloud and aerosol multiple scattering and emission are accelerated with pre-computed look-up tables.FYRTM is evaluated with a rigorous simulation based on discrete ordinate radiative transfer model(DISORT)as well as a popular fast forward model,i.e.,the Community Radiative Transfer Model(CRTM).Results indicate that FYRTM-based simulations are two to three orders of magnitudes faster than the DISORT-based simulations.Compared to the rigorous model,FYRTM relative errors are within 2%at solar channels,and brightness temperatures(BT)differences are within 1 K at infrared channels.Compared with CRTM,FYRTM is computationally similar at solar channels,but three times faster at infrared channels.Furthermore,simulated reflectances/BTs using FYRTM are in a good agreement with the satellite observations.Overall,FYRTM is capable to simulate satellite observations under different atmospheric conditions,and can be extended to other radiometers onboard the Fengyun satellites(both geostationary and polarorbiting satellites).It is expected to play important roles in future applications with Fengyun observations.
基金This work was supported by the National Natural Science Foundation of China under[Grant 41671332 and Grant 41571422]in part by the National Key Research and Development Program of China under[Grant 2016YFA0600103].
文摘A fractional vegetation cover(FVC)estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed,which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarseresolution FVC pixel were all assumed to have the same vegetation growth model.However,this assumption does not hold over heterogeneous areas,meaning that the method cannot be applied to large regions.Therefore,this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite(GLASS)FVC product.The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data.Then,independent dynamic vegetation models were built for each finer-resolution pixel.Finally,the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale.Validation results indicated that the proposed method(R^(2)=0.7757,RMSE=0.0881)performed better than either the previous method(R^(2)=0.7038,RMSE=0.1125)or a commonly used method involving look-up table inversions of the PROSAIL model(R^(2)=0.7457,RMSE=0.1249).
基金supported by the National Science Foun-dation of China(42141005)supported by the High-performance Computing Platform of Peking University.
文摘Tree height composition describes the relative abundance of trees in different height levels and performs as a critical characteristic for community ecology.The recent launched full-waveform spaceborne LiDAR(Light Detection and Ranging),i.e.,Global Ecosystem Dynamics Investigation(GEDI),can map canopy height,but whether this observation reflects tree height composition remains untested.In this study,we firstly conduct numerical simulations to explore to what extent tree height composition can be obtained from GEDI waveform signals.We simulate waveforms for diverse forest scenarios using GEDI simulator coupled with LESS(LargE-Scale remote sensing data and image Simulation),a state-of-the-art radiative transfer model.We devise a minimalistic model,Tree generation based on Asymmetric generalized Gaussian(TAG),for customizing tree objects to accelerate forest scene creation.The results demonstrate that tree objects generated by TAG perform similarly in LiDAR simulation with objects from commercial 3-dimensional software.Results of simulated GEDI waveforms reasonably respond to the variation of crown architectures in even-aged forests.GEDI waveforms have an acceptable ability to identify different height layers within multi-layer forests,except for fir forests with a cone-shaped crown.The shape metric of waveforms reflects the height of each layer,while retrieval accuracy decreases with the increases in height variations within each layer.A 5-m interval between layers is the minimum requirement so that the different height layers can be separated.A mixture of different tree species reduces the retrieval accuracy of tree height layers.We also utilize real GEDI observations to retrieve tree heights in multi-height-layer forests.The findings indicate that GEDI waveforms are also efficient in identifying tree height composition in practical forest scenarios.Overall,results from this study demonstrate that GEDI waveforms can reflect the height composition within typical forest stands.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41505024 & 41127901)
文摘A high-resolution dual-band terahertz(THz) radiometer was designed to measure vertical distributions of chemical elements in the middle atmosphere of the Tibetan Plateau. A forward simulation, which always should be conducted firstly for the development of a matching retrieval algorithm, has not been done before. We use two radiative transfer models, ARTS and AM, to simulate the water vapor, ozone and carbon monoxide spectra on the plateau based on the spectral design of the THz radiometer. The emission line characteristics of the three gases in this spectral band are identified. Reasons for the differences in the spectral simulations between the two models are analyzed for individual gases. The impact of several different spectral parameter settings on the simulations are evaluated through a series of sensitivity experiments. This study suggests that the ARTS is more suitable for the development of the THz radiometer retrieval algorithm. An optimal parameter setting of the ARTS for the three elements are given.
基金The Project supported by National National Science FoundationYing Tung Education Foundation
文摘An overall vector radiative transfer theory was developed for numerical modeling, in both active and passive microwave remote sensing. The Theory and approaches are briefly summerized.To quantitatively understand scattering and thermal emission from targets in active and passive remote sensing, we have developed an overall vector radiative transfer theory for a set of theoretical models of discrete scatterer and continuous random media for the earth terrain (wet soil, vegetation, snow, sea-ice, etc.) and atmosphere, and numerical approaches for simulation, data analysis, and parameter sensitivity test. Our numerical results favorably agreed with experimental data in microwave re mote sensing of various earth surfaces. Main approaches are briefly summerized herewith.
基金supported by the National Natural Science Foundation of China under Grant Nos.40233034,40605024,40575043,and 40305011.
文摘This paper compares the predictions by two radiative transfer models-the two-stream approximation model and the generalized layered model （developed by the authors） in land surface processes -for different canopies under direct or diffuse radiation conditions. The comparison indicates that there are significant differences between the two models, especially in the near infrared （NIR） band. Results of canopy reflectance from the two-stream model are larger than those from the generalized model. However, results of canopy absorptance from the two-stream model are larger in some cases and smaller in others compared to those from the generalized model, depending on the cases involved. In the visible （VIS） band, canopy reflectance is smaller and canopy absorptance larger from the two-stream model compared to the generalized model when the Leaf Area Index （LAI） is low and soil reflectance is high. In cases of canopies with vertical leaf angles, the differences of reflectance and absorptance in the VIS and NIR bands between the two models are especially large. Two commonly occurring cases, with which the two-stream model cannot deal accurately, are also investigated. One is for a canopy with different adaxial and abaxial leaf optical properties; and the other is for incident sky diffuse radiation with a non-uniform distribution. Comparison of the generalized model within the same canopy for both uniform and non-uniform incident diffuse radiation inputs shows smaller differences in general. However, there is a measurable difference between these radiation inputs for a canopy with high leaf angle. This indicates that the application of the two-stream model to a canopy with different adaxial and abaxial leaf optical properties will introduce non-negligible errors.
文摘The radiance leaving the earth-atmosphere system which can be sensed by a satellite borne radiometer is the sum of radiation emission from the earth surface and each atmospheric level that are transmitted to the top of the atmosphere. The radiation emission from the earth surface and the radiance of each atmospheric level can be separated from the radiance at the top the atmospheric level measured by a satellite borne radiometer. However, it is very difficult to measure the atmospheric radiance, especially the synchronous measurement with the satellite. Thus some atmospheric radiative transfer models have been developed to provide many options for modeling atmospheric radiation transport, such as LOWTRAN, MODTRAN, 6S, FASCODE, LBLRTM, SHARC, and SAMM. Meanwhile, these models can support the detailed detector system design, the optimization and evaluation of satellite mission parameters, and the data processing procedures. As an example, the newly atmospheric radiative transfer models, MODTRAN will be compared with other models after the atmospheric radiative transfer is described. And the atmospheric radiative transfer simulation procedures and their applications to atmospheric transmittance, retrieval of atmospheric elements, and surface parameters, will also be presented.
基金the provided funding resources by Mohsen Saffari Pour from the National Elites Foundation of IranStiftelsen Axel Hultgerns of Sweden for supporting this research。
文摘This research investigates a numerical simulation of swirling turbulent non-premixed combustion.The effects on the combustion characteristics are examined with three turbulence models:namely as the Reynolds stress model,spectral turbulence analysis and Re-Normalization Group.In addition,the P-1 and discrete ordinate(DO)models are used to simulate the radiative heat transfer in this model.The governing equations associated with the required boundary conditions are solved using the numerical model.The accuracy of this model is validated with the published experimental data and the comparison elucidates that there is a reasonable agreement between the obtained values from this model and the corresponding experimental quantities.Among different models proposed in this research,the Reynolds stress model with the Probability Density Function(PDF)approach is more accurate(nearly up to 50%)than other turbulent models for a swirling flow field.Regarding the effect of radiative heat transfer model,it is observed that the discrete ordinate model is more precise than the P-1 model in anticipating the experimental behavior.This model is able to simulate the subcritical nature of the isothermal flow as well as the size and shape of the internal recirculation induced by the swirl due to combustion.
基金Supported by the National Natural Science Foundation of China under Grant Nos.40375026 and 40233034.
文摘Accurate estimates of albedos are required in climate modeling. Accurate and simple schemes for radiative transfer within canopy are required for these estimates, but severe limitations exist. This paper developed a four-stream solar radiative transfer model and coupled it with a land surface process model. The radiative model uses a four-stream approximation method as in the atmosphere to obtain analytic solutions of the basic equation of canopy radiative transfer. As an analytical model, the four-stream radiative transfer model can be easily applied efficiently to improve the parameterization of land surface radiation in climate models. Our four-stream solar radiative transfer model is based on a two-stream short wave radiative transfer model. It can simulate short wave solar radiative transfer within canopy according to the relevant theory in the atmosphere. Each parameter of the basic radiative transfer equation of canopy has special geometry and optical characters of leaves or canopy. The upward or downward radiative fluxes are related to the diffuse phase function, the G-function, leaf reflectivity and transmission, leaf area index, and the solar angle of the incident beam. The four-stream simulation is compared with that of the two-stream model. The four-stream model is proved successful through its consistent modeling of canopy albedo at any solar incident angle. In order to compare and find differences between the results predicted by the four- and two-stream models, a number of numerical experiments are performed through examining the effects of different leaf area indices, leaf angle distributions, optical properties of leaves, and ground surface conditions on the canopy albedo. Parallel experiments show that the canopy albedos predicted by the two models differ significantly when the leaf angle distribution is spherical and vertical. The results also show that the difference is particularly great for different incident solar beams. One additional experiment is carried out to evaluate the simulations of the BATS land surface model coupled with the two- and four-stream radiative transfer models. Station observations in 1998 are used for comparison. The results indicate that the simulation of BATS coupled with the four-stream model is the best because the surface absorbed solar radiation from the four-stream model is the closest to the observation.
文摘Three-dimensional(3-D)Monte Carlo-based radiative transfer(MCRT)models are usually used for benchmarking in intercomparisons of the canopy radiative transfer(RT)simulations.However,the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests,due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales.Fortunately,some of important tree structure parameters such as canopy height and tree density distribution have been available globally.This enables to run the intermediate complexities of the 3-D MCRT models.We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density.It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms.The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA,respectively.Results demonstrated that the simulations of bidirectional reflectance factor(BRF)based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error(RMSE)and relative RMSE(rRMSE)ranging from 0.002 to 0.006 and from 0.7%to 19.8%,respectively.Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%,respectively.Although the results from the current study are limited in two boreal forest stands,our approach has the potential to generate stand structures for different forest biomes.
