Sea surface temperature retrieval based on simulated microwave polarimetric measurements of a one-dimensional synthetic aperture microwave radiometer

Compared with traditional real aperture microwave radiometers,one-dimensional synthetic aperture microwave radiometers have higher spatial resolution.In this paper,we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz,10.65 GHz,18.7 GHz and 23.8 GHz at multiple incidence angles.We used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness temperature.The brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness temperature.Then,a backpropagation(BP)neural network algorithm,a random forest(RF)algorithm and two multiple linear regression algorithms(RE1 and RE2)were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°-65°.The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian noise.The BP achieves the lowest retrieval errors at all incidence angles.The retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.

A Neural Network Based Single Footprint Temperature Retrieval for Atmospheric Infrared Sounder Measurements and Its Application to Study on Stratospheric Gravity Wave

Satellite hyperspectral infrared sounder measurements have better horizontal resolution than other sounding techniques as it boasts the stratospheric gravity wave(GW)analysis.To accurately and efficiently derive the three-dimensional structure of the stratospheric GWs from the single-field-of-view(SFOV)Atmospheric Infra Red Sounder(AIRS)observations,this paper firstly focuses on the retrieval of the atmospheric temperature profiles in the altitude range of 20-60 km with an artificial neural network approach(ANN).The simulation experiments show that the retrieval bias is less than 0.5 K,and the root mean square error(RMSE)ranges from 1.8 to 4 K.Moreover,the retrieval results from 20 granules of the AIRS observations with the trained neural network(AIRS_SFOV)and the corresponding operational AIRS products(AIRS_L2)as well as the dual-regression results from the Cooperative Institute for Meteorological Satellite Studies(CIMSS)(AIRS_DR)are compared respectively with ECMWF T799 data.The comparison indicates that the standard deviation of the ANN retrieval errors is significantly less than that of the AIRS_DR.Furthermore,the analysis of the typical GW events induced by the mountain Andes and the typhoon"Soulik"using different data indicates that the AIRS_SFOV results capture more details of the stratospheric gravity waves in the perturbation amplitude and pattern than the operational AIRS products do.

Performance of the Large Field of View Airborne Infrared Scanner and its application potential in land surface temperature retrieval

The Large Field of View Airborne Infrared Scanner is a newly developed multi-spectral instrument that collects images from the near-infrared to long-wave infrared channels.Its data can be used for land surface temperature(LST)retrieval and environmental monitoring.Before data application,quality assessment is an essential procedure for a new instrument.In this paper,based on the data collected by the scanner near the Yellow River in Henan Province,the geometric and radiometric qualities of the images are first evaluated.The absolute geolocation accuracy of the ten bands of the scanner is approximately 5.1 m.The ground sampling distance is found to be varied with the whisk angles of the scanner and the spatial resolution of the images.The band-to-band registration accuracy between band one and the other nine bands is approximately 0.25 m.The length and angle deformations of the ten bands are approximately 0.67%and 0.3°,respectively.The signal-to-noise ratio(SNR)and relative radiometric calibration accuracy of bands 4,9,and 10 are relatively better than those of the other bands.Secondly,the radiative transfer equation(RTE)method is used to retrieve the LST from the data of the scanner.Measurements of in situ samples are collected to evaluate the retrieved LST.Neglecting the samples with unreasonable retrieved LST,the bias and RMSE between in situ LST measured by CE312 radiometer and retrieved LST are−0.22 K and 0.94 K,and the bias and RMSE are 0.27 K and 1.59 K for the InfReC R500-D thermal imager,respectively.Overall,the images of the Large Field of View Airborne Infrared Scanner yield a relatively satisfactory accuracy for both LST retrieval and geometric and radiometric qualities.

The Study of In-Orbit Calibration Accuracy of NOAA Satellite Infrared Sounder and Its Effect on Temperature Profile Retrievals

The calibration accuracy of High Resolution Infrared Radiation Sounder Mod. 2 (HIRS / 2) on NOAA-10 satellite is analyzed in this paper. The non-linear effect in the linear calibration curve induces a deviation of 1.5 degrees (k) of brightness temperature in the tenth channel (8.3 um, water vapor absorption) of the HIRS/2 and the non-linear effect affects the other channels to a different extent. Based on analyzing non- linearity in two-point calibration curve, a tri-point calibration equation is given. A numerical test of effects of the linear and non-linear calibration models on the accuracy of atmospheric temperature retrievals is carried out.

Spatio-temporal Evolution Characteristics and Driving Forces of Winter Urban Heat Island:A Case Study of Rapid Urbanization Area of Fuzhou City,China

Under the influence of anthropogenic and climate change,the problems caused by urban heat island(UHI)has become increasingly prominent.In order to promote urban sustainable development and improve the quality of human settlements,it is significant for exploring the evolution characteristics of urban thermal environment and analyzing its driving forces.Taking the Landsat series images as the basic data sources,the winter land surface temperature(LST)of the rapid urbanization area of Fuzhou City in China was quantitatively retrieved from 2001 to 2021.Combing comprehensively the standard deviation ellipse model,profile analysis and GeoDetector model,the spatio-temporal evolution characteristics and influencing factors of the winter urban thermal environment were systematically analyzed.The results showed that the winter LST presented an increasing trend in the study area during 2001–2021,and the winter LST of the central urban regions was significantly higher than the suburbs.There was a strong UHI effect from 2001 to 2021with an expansion trend from the central urban regions to the suburbs and coastal areas in space scale.The LST of green lands and wetlands are significantly lower than croplands,artificial surface and unvegetated lands.Vegetation and water bodies had a significant mitigation effect on UHI,especially in the micro-scale.The winter UHI had been jointly driven by the underlying surface and socio-economic factors in a nonlinear or two-factor interactive enhancement mode,and socio-economic factors had played a leading role.This research could provide data support and decision-making references for rationally planning urban layout and promoting sustainable urban development.

Simultaneous reconstruction of temperature distribution and radiative properties in participating media using a hybrid LSQR-PSO algorithm

A hybrid least-square QR decomposition （LSQR）-particle swarm optimization （LSQR-PSO） algorithm was devel- oped to estimate the three-dimensional （3D） temperature distributions and absorption coefficients simultaneously. The outgoing radiative intensities at the boundary surface of the absorbing media were simulated by the line-of-sight （LOS） method, which served as the input for the inverse analysis. The retrieval results showed that the 3D temperature distribu- tions of the participating media with known radiative properties could be retrieved accurately using the LSQR algorithm, even with noisy data. For the participating media with unknown radiative properties, the 3D temperature distributions and absorption coefficients could be retrieved accurately using the LSQR-PSO algorithm even with measurement errors. It was also found that the temperature field could be estimated more accurately than the absorption coefficients. In order to gain insight into the effects on the accuracy of temperature distribution reconstruction, the selection of the detection direction and the angle between two detection directions was also analyzed.

Sea surface wind speed retrieval under rain with the HY-2 microwave radiometer

As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer（RM） loaded on HY-2 satellite, the sensitivity of some brightness temperature（TB）channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with Wind Sat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.

Temperature field reconstruction of 3D luminous flames based on light field tomography theory

Standard plenoptic camera can be used to capture multi-dimensional radiation information of high temperature luminous flame to reconstruct the temperature distribution. In this study, a novel method for reconstructing three-dimensional temperature field is proposed. This method is based on the optical tomography combined with standard plenoptic camera. The flame projection information from different planes is contained in one radiation image. In this model, we introduced the effective concept of the nearest neighbor method in the frequency domain to strip the interference of redundant information in the projection and to realize three-dimensional deconvolution. The flame emission intensity received by the pixels on the charge-coupled device sensor can be obtained according to the optical tomographic model. The temperature distributions of the axisymmetric and nonaxisymmetric flames can be reconstructed by solving the mathematical model with the nearest neighbor method. The numerical results show that three-dimensional temperature fields of high temperature luminous flames can be retrieved, proving the validity of the proposed method.

PMODTRAN:a parallel implementation based on MODTRAN for massive remote sensing data processing

MODerate resolution atmospheric TRANsmission(MODTRAN)is a commercial remote sensing(RS)software package that has been widely used to simulate radiative transfer of electromagnetic radiation through the Earth’s atmosphere and the radiation observed by a remote sensor.However,when very large RS datasets must be processed in simulation applications at a global scale,it is extremely time-consuming to operate MODTRAN on a modern workstation.Under this circumstance,the use of parallel cluster computing to speed up the process becomes vital to this time-consuming task.This paper presents PMODTRAN,an implementation of a parallel task-scheduling algorithm based on MODTRAN.PMODTRAN was able to reduce the processing time of the test cases used here from over 4.4 months on a workstation to less than a week on a local computer cluster.In addition,PMODTRAN can distribute tasks with different levels of granularity and has some extra features,such as dynamic load balancing and parameter checking.