Brightness temperature simulation of subarctic lake-ice evolution by HIGHTSI and SMRT model

Microwave brightness temperature(TB)can be used to retrieve lake ice thickness in the Arctic and subarctic regions.However,the accuracy of the retrieval is affected by the physical properties of lake ice.To improve the understanding of how lake ice affects TB,numerical modeling was applied.This study combined a physical thermodynamic ice model HIGHTSI with a microwave radiation transfer model SMRT to simulate the TB and lake ice evolution in 2002-2011 in Hulun Lake,China.The reanalyzed meteorological data were used as atmospheric forcing.The ice season was divided into the growth period,the slow growth period,and the ablation period.The simulations revealed that TB was highly sensitive to ice thickness during the ice season,especially vertical polarization measurement at 18.7 GHz.The quadratic polynomial fit for ice thickness to TB outperformed the linear fit,regardless of whether lake ice contained bubbles or not.A comparison of the simulated TB with space-borne TB showed that the simulated TB had the best accuracy during the slow growth period,with a minimum RMSE of 4.6 K.The results were influenced by the bubble radius and salinity.These findings enhance comprehension of the interaction between lake ice properties(including ice thickness,bubbles,and salinity)and TB during ice seasons,offering insights to sea ice in the Arctic and subarctic freshwater observations.

Comparative Analysis of Microwave Brightness Temperature Data in Northeast China Using AMSR-E and MWRI Products

With such significant advantages as all-day observation, penetrability and all-weather coverage, passive mi-crowave remote sensing technique has been widely applied in the research of global environmental change. As the sat-ellite-based passive microwave remote sensor, the Advanced Microwave Scanning Radiometer-Earth Observing Sys-tem (AMSR-E) loaded on NASA's (National Aeronautics and Space Administration of USA) Aqua satellite has been popularly used in the field of microwave observation. The Microwave Radiation Imager (MWRI) loaded on the Chi-nese FengYun-3A (FY-3A) satellite is an AMSR-E-like conical scanning microwave sensor, but there are few reports about MWRI data. This paper firstly proposed an optimal spatial position matching algorithm from rough to exact for the position matching between AMSR-E and MWRI data, then taking Northeast China as an example, comparatively analyzed the microwave brightness temperature data derived from AMSR-E and MWRI. The results show that when the antenna footprints of the two sensors are filled with either full water, or full land, or mixed land and water with ap-proximate proportion, the errors of brightness temperature between AMSR-E and MWRI are usually in the range from -10 K to +10 K. In general, the residual values of brightness temperature between the two microwave sensors with the same spatial resolution are in the range of ±3 K. Because the spatial resolution of AMSR-E is three times as high as that of MWRI, the results indicate that the quality of MWRI data is better. The research can provide useful information for the MWRI data application and microwave unmixing method in the future.

MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS: METHODS AND IDEAL TESTS

Clouds have important effects on the infi＇ared radiances transmission in that the inclusion of cloud effects in data assimilation can not only improve the quality of the assimilated atmospheric parameters greatly, but also minimize the initial error of cloud parameters by adjusting part of the infrared radiances data. On the basis of the Grapes-3D-var （Global and Regional Assimilation and Prediction Enhanced System）, cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation. Under the conditions of clear sky, partly cloudy cover and totally cloudy cover, the brightness temperature of 16 MODIS channels are assimilated respectively in ideal tests. Results show that when the simulated background brightness temperatures are lower than the observation, the analyzed field will increase the simulated brightness temperature by increasing its temperature and reducing its moisture, cloud liquid water, cloud ice water, and cloud cover. The simulated brightness temperature can be reduced if adjustment is made in the contrary direction. The adjustment of the temperature and specific humidity under the clear sky conditions conforms well to the design of MODIS channels, but it is weakened for levels under cloud layers. The ideal tests demonstrate that by simultaneously adding both cloud parameters and atmospheric parameters as governing variables during the assimilation of infrared radiances, both the cloud parameters and atmospheric parameters can be adjusted using the observed infrared radiances and conventional meteorological elements to make full use of the infrared observations.

Cross-calibration of brightness temperature obtained by FY-3B/MWRI using Aqua/AMSR-E data for snow depth retrieval in the Arctic

This study cross-calibrated the brightness temperatures observed in the Arctic by using the FY-3B/MWRI L1 and the Aqua/AMSR-E L2A.The monthly parameters of the cross-calibration were determined and evaluated using robust linear regression.The snow depth in case of seasonal ice was calculated by using parameters of the crosscalibration of data from the MWRI Tb.The correlation coefficients of the H/V polarization among all channels Tb of the two sensors were higher than 0.97.The parameters of the monthly cross-calibration were useful for the snow depth retrieval using the MWRI.Data from the MWRI Tb were cross-calibrated to the AMSR-E baseline.Biases in the data of the two sensors were optimized to approximately 0 K through the cross-calibration,the standard deviations decreased significantly in the range of 1.32 K to 2.57 K,and the correlation coefficients were as high as 99%.An analysis of the statistical distributions of the histograms before and after cross-calibration indicated that the FY-3B/MWRI Tb data had been well calibrated.Furthermore,the results of the cross-calibration were evaluated by data on the daily average Tb at 18.7 GHz,23.8 GHz,and 36.5 GHz(V polarization),and at 89 GHz(H/V polarization),and were applied to the snow depths retrieval in the Arctic.The parameters of monthly cross-calibration were found to be effective in terms of correcting the daily average Tb.The results of the snow depths were compared with those of the calibrated MWRI and AMSR-E products.Biases of 0.18 cm to 0.38 cm were observed in the monthly snow depths,with the standard deviations ranging from 4.19 cm to 4.80 cm.

MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS Ⅱ: IMPACTS ON RAINSTORM FORECASTING

Satellite observations provide large amount of information of clouds and precipitation and play an important role in the forecast of heavy rainfall.However,we have not fully taken advantage of satellite observations in the data assimilation of numerical weather predictions,especially those in infrared channels. It is common to only assimilate radiances under clear-sky conditions since it is extremely difficult to simulate infrared transmittance in cloudy sky.On the basis of the Global and Regional Assimilation and Prediction Enhanced System 3-dimensional variance(GRAPES-3DVar),cloud liquid water content, ice-water content and cloud cover are employed as governing variables in the assimilation system.This scheme can improve the simulation of infrared transmittance by a fast radiative transfer model for TOVS (RTTOV)and adjust the atmospheric and cloud parameters based on infrared radiance observations.In this paper,we investigate a heavy rainfall over Guangdong province on May 26,2007,which is right after the onset of a South China Sea monsoon.In this case,channels of the Moderate Resolution Imaging Spectroradiometer(MODIS)for observing water vapor(Channel 27)and cloud top altitude(Channel 36)are selected for the assimilation.The process of heavy rainfall is simulated by the Weather Research and Forecasting(WRF)model.Our results show that the assimilated MODIS data can improve the distribution of water vapor and temperature in the first guess field and indirectly adjust the upper-level wind field.The tendency of adjustment agrees well with the satellite observations.The assimilation scheme has positive impacts on the short-range forecasting of rainstorm.

Surface Brightness Temperature Variation of Different Land Use Types

[Objective] The aim of this study is to investigate the surface brightness temperature variation of different land use types.[Method] Based on MODIS data in 2008 and IGBP land classification system,the surface brightness temperature in the Yangtze River Delta area was calculated,and its rules and reasons were also discussed in this study.[Result] Different land use types had its own special brightness temperature variation.During the day,the brightness temperature was as follows：grassland or urban and built-up landcropland,forest land and barrenwetland and water.During the night,the brightness temperature was as follows：water,wetland and barrengrassland or urban and built-up landforest land and cropland.Brightness temperature showed the trend of high in summer and low in winter or increasing in spring and decreasing in fall.The characteristics of surface thermal radiation could be reflected better by brightness temperature at night.Solar radiation,mixed pixel,heat capacity,water content were the main reasons for the difference of brightness temperature in different land types.[Conclusion] The brightness temperature variation of different land use types has significance for water content analysis in soil and dynamic monitoring of land use.

Seasonal and Interannual Variations of Upper Tropospheric Water Vapor Band Brightness Temperature over the Global Monsoon Regions

The upper-troposphere water vapor (UTWV) band brightness temperature (BT) dataset derived from the High-resolution Infrared Radiation Sounder (HIRS) channel 12 of the National Oceanic and Atmospheric Administration (NOAA) polar satellites from 1979 to 1995 is used to analyze the seasonal and interannual variations for the global monsoon regions. Results show that (i) there are three major regions where the UTWV band BT varies significantly with season, i.e., South Asia, the western coastal South-North America tropical region and the low-latitude African region; (ii) UTWV band BT clearly reveals the water vapor temporal/spatial features as well as the atmospheric circulation structure over the low-latitude during the monsoon onset; and (iii) there is a remarkable relationship between the interannual variation of the UTWV band BT over the monsoon regions and the sea surface temperature anomaly in the eastern equatorial Pacific.

The deconvolution of lunar brightness temperature based on the maximum entropy method using Chang'e-2 microwave data

A passive and multi-channel microwave sounder onboard the Chang＇e-2 orbiter has successfully acquired microwave observations of the lunar surface and subsurface structure. Compared with the Chang＇e-1 orbiter, the Chang＇e-2 orbiter obtained more accurate and comprehensive microwave brightness temperature data, which are helpful for further research. Since there is a close relationship between mi- crowave brightness temperature data and some related properties of the lunar regolith, such as the thickness, temperature and dielectric constant, precise and high resolution brightness temperature data are necessary for such research. However, through the detection mechanism of the microwave sounder, the brightness temperature data ac- quired from the microwave sounder are weighted by the antenna radiation pattern, so the data are the convolution of the antenna radiation pattern with the lunar brightness temperature. In order to obtain the real lunar brightness temperature, a deconvolution method is needed. The aim of this paper is to solve the problem associated with per- forming deconvolution of the lunar brightness temperature. In this study, we introduce the maximum entropy method （MEM） to process the brightness temperature data and achieve excellent results. The paper mainly includes the following aspects： first, we introduce the principle of the MEM; second, through a series of simulations, the MEM has been verified as an efficient deconvolution method; and third, the MEM is used to process the Chang＇e-2 microwave data and the results are significant.

Utilizing a new soil effective temperature scheme and archived satellite microwave brightness temperature data to estimate surface soil moisture in the Nagqu region, Tibetan Plateau of China

Since the early 2000s, many satellite passive microwave brightness temperature （BT） archives, such as the Advanced Microwave Scanning Radiometer for the Earth Observing System （AMSR-E） BTs, have become the useful resources for assessing the changes in the surface and deep soil moistures over both arid and semi-arid regions. In this study, we used a new soil effective temperature （T scheme and the archived AMSR-E BTs to estimate surface soil moisture （SM） over the Nagqu region in the central Tibetan Plateau, China. The surface and deep soil temperatures required for the calculation of regional-scale T were obtained from outputs of the Community Land Model version 4.5 （CLM4.5）. In situ SM measurements at the CEOP-CAMP/Tibet （Coordinated Enhanced Observing Period Asia-Australia Monsoon Project on the Tibetan Plateau） experimental sites were used to validate the AMSR-E-based SM estimations at regional and single-site scales. Furthermore, the spatial distribution of monthly mean surface SM over the Nagqu region was obtained from 16 daytime AMSR-E BT observations in July 2004 over the Nagqu region. Results revealed that the AMSR-E-based surface SM estimations agreed well with the in situ-based surface SM measurements, with the root mean square error （RMSE） ranging from 0.042 to 0.066 m3/m3 and the coefficient of determination （R2） ranging from 0.71 to 0.92 during the nighttime and daytime. The regional surface soil water state map showed a clear spatial pattern related to the terrain. It indicated that the lower surface SM values occurred in the mountainous areas of the northern, mid-western and southeastern parts of Nagqu region, while the higher surface SM values appeared in the low elevation areas such as the Tongtian River Basin, Namco Lake and bog meadows in the central part of Nagqu region. Our analysis also showed that the new T^scheme does not require special fitting parameters or additional assumptions, which simplifies the data requirements for regional-scale applications. This scheme combined with the archived satellite passive microwave BT observations can be used to estimate the historical surface SM for hydrological process studies over the Tibetan Plateau regions.

Improving microwave brightness temperature predictions based on Bayesian model averaging ensemble approach

The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.

Possible Thermal Brightness Temperature Anomalies Associated with the Yutian (China) M_S7.3 Earthquake on February 12,2014

In order to analyze the seismic brightness temperature anomalies associated with the Yutian earthquake which occurred at Yutian County, Xinjiang on February 12,2014, daily brightness temperature data was collected from the China Geostationary Meteorological Satellite FY-2E,for the period from May 1,2012 to April 30,2014 and the geographical extent of 30°- 45°N latitude and 70°- 95°E longitude. The continuous wavelet transform method was used to analyze the relative wavelet power spectrum( RWPS) of brightness temperature data for each pixel. And the RWPS time-spatial evolution within the analysis area was obtained. The results showed that the anomaly started to appear at the vicinity of epicentre since October 2013, and anomalous areas gradually enlarged and stretched towards to Altun fault zone and the eastern part of West Kunlun fault zone. Anomalies began to appear at fault zones at Middle Tianshan Mountains, Southern Tianshan Mountains and the western part of the West Kunlun Mountains area which is located at the western margin of Tarim basin,since November 2013. Then anomalous area further enlarged and gathered along fault zones,and eventually,anomalous belts were developed along fault zones around the Tarim basin. The anomaly area and amplitude reached their maximum in late December 2013 and early January 2014. With the impending earthquake,the anomaly area and amplitude dwindled. Anomalies at the vicinity of epicentre disappeared days before the occurrence of the main shock. However, the anomaly at Altun and Middle Tianshan areas still remained. After the main shock,the anomaly attenuated quickly and the whole anomaly disappeared in late February 2014.

Cross-calibration between MWRI and AMSR2 to improve consistency of snow depth products

The Microwave Radiation Imager (MWRI), boarded on the FY-3 series satellites: FY-3B, FY-3C, and FY-3D, is thefirst satellite-based microwave radiometer in China, commencing passive microwave brightness temperature dataacquisition since 2010. The Advanced Microwave Scanning Radiometer 2 (AMSR2) boarded on the Global ChangeObservation Mission 1st-Water (GCOM-W1), has been operational since 2012. Despite the FY-3 series satellitesare equipped with the same MWRI and all MWRIs sharing comparable parameters and configurations as AMSR2,disparities in observation times and satellite platforms result in inconsistencies in the data obtained by differentsatellites, which further impacting the consistency of retrieved geophysical parameters. To improve the consistency of brightness temperatures from FY-3B, FY-3C, FY-3D/MWRI, and GCOM-W1/AMSR2, cross-calibrationswere conducted among brightness temperatures at ten-channel from above four platforms. The consistency ofderived snow depth from MWRIs and AMSR2 in China before and after the calibration were also analyzed. Theresults show that the correlation coefficients of brightness temperatures at all channels between sensors exceed0.98. After cross-calibration, the RMSEs and biases of brightness temperatures at all frequencies and snow depthin China derived from them reduce to varying degrees. The consistencies in both brightness temperatures andsnow depth of FY-3B/MWRI, FY-3D/MWRI, and AMSR2 are higher than those of FY-3C and others. These findingsadvocate for the utilization of cross-calibrated brightness temperatures from FY-3B/MWRI, FY-3D/MWRI, andAMSR2, which share similar satellite overpass time, to derived a long-term snow depth dataset.

GOES-16 ABI Brightness Temperature Observations Capturing Vortex Rossby Wave Signals during Rapid Intensification of Hurricane Irma(2017)

Geostationary Operational Environmental Satellite-16(GOES-16) Advanced Baseline Imager(ABI) observations of brightness temperature(TB) are used to examine the temporal evolutions of convection-affected structures of Hurricane Irma(2017) during its rapid intensification(RI) period from 0600 to 1800 UTC 4 September 2017.The ABI observations reveal that both an elliptical eye and a spiral rainband that originated from Irma's eyewall obviously exhibit wavenumber-2 TB asymmetries.The elliptical eye underwent a counterclockwise rotation at a mean speed of a wavenumber-2 vortex Rossby edge wave from 0815 to 1005 UTC 4 September.In the following about 2 hours(1025–1255 UTC 4 September),an inner spiral rainband originated from the eyewall and propagated at a phase speed that approximates the vortex Rossby wave(VRW) phase speed calculated from the aircraft reconnaissance data.During the RI period of Irma,ABI TB observations show an on–off occurrence of low TB intrusions into the eye,accompanying a phase lock of eyewall TB asymmetries of wavenumbers 1 and 2 and an outward propagation of VRW-like inner spiral rainbands from the eyewall.The phase lock leads to an energy growth of Irma's eyewall asymmetries.Although the eye remained clear from 1415 to 1725 UTC 4 September,an inner spiral rainband that originated from a large convective area also had a VRW-like outward propagation,which is probably due to a vertical tilt of Irma.This study suggests a potential link between convection sensitive GOES imager observations and hurricane dynamics.

Evaluation of the Long-term Performance of Microwave Radiation Imager Onboard Chinese Fengyun Satellites

Accurate brightness temperature(BT)is a top priority for retrievals of atmospheric and surface parameters.Microwave Radiation Imagers(MWRIs)on Chinese Fengyun-3(FY-3)serial polar-orbiting satellites have been providing abundant BT data since 2008.Much work has been done to evaluate short-term MWRI observations,but the long-term performance of MWRIs remains unclear.In this study,operational MWRI BTs from 2012–19 were carefully examined by using simultaneous Advanced Microwave Scanning Radiometer 2(AMSR2)BTs as the reference.The BT difference between MWRI/FY3B and AMSR2 during 2012–19 increased gradually over time.As compared with MWRI/FY3B BTs over land,those of MWRI/FY3D were much closer to those of AMSR2.The ascending and descending orbit difference for MWRI/FY3D is also much smaller than that for MWRI/FY3B.These results suggested the improvement of MWRI/FY3D over MWRI/FY3B.A substantial BT difference between AMSR2 and MWRI was found over water,especially at the vertical polarization channels.A similar BT difference was found over polar water based on the simultaneous conical overpassing(SCO)method.Radiative transfer model simulations suggested that the substantial BT differences at the vertical polarization channels of MWRI and AMSR2 over water were partly contributed by their difference in the incident angle;however,the underestimation of the operational MWRI BT over water remained a very important issue.Preliminary assessment of the operational and recalibrated MWRI BT demonstrated that MWRI BTs were substantially improved after the recalibration,including the obvious underestimation of the operational MWRI BT at the vertical polarization channels over water was corrected,and the time-dependent biases were reduced.

Two-step method to extract seismic microwave radiation anomaly:Case study of M_s8.0 Wenchuan earthquake

The satellite remote sensing has become a promising technique for detecting earthquake and fault activities. But it is still very difficult to exactly extract the earthquake anomaly from the complicated remote sensing information. This paper presented a two-step method to extract the seismic microwave radiation anomaly related with earthquake, which could eliminate the stable influence of geography, terrain, coversphere and seasons, as well as the random influence of weather. Furthermore the two-step method was applied to analyze the anomaly of Wenchuan earthquake based on the data of AMSR-E. Microwave radiation anomalies were effectively detected related to the main shock and aftershocks. The extracted microwave radiation variation showed general features of three-stage： the positive radiation anomaly appeared around the epicenter in the first stage, quiet variation in the second stage, and abnormal area gradually moved to the epicenter in the third stage. After the main shock the microwave radiation anomalies distributed along the Longmenshan faults, and the epicenters of aftershocks were coincident with the anomaly area in space.

Geochemical Indications of Possible Gas Hydrates in the Northeastern South China Sea

Gas hydrate, mainly composed of hydrocarbon gas and water, is considered to be a clean energy in the 21st century. Many indicators such as BSRs （Bottom-Simulating Reflections）, which are thought to be related to gas hydrate, are found in the South China Sea （SCS） in recent years. The northeastern part of the SCS is taken as one of the most potentials in the area by many scientists. It is situated in the conjunction of the northern divergent continental margin and the eastern convergent island margin, whose geological settings are much preferable for gas hydrate to occur. Through this study, brightness temperature anomalies recorded by satellite-based thermal infrared remotely sensed images before or within the imminent earthquake, the high content of hydrocarbon gas acid-degassed from subsurface sediment and the high radioactive thermoluminescence value of subsurface sediment were found in the region. Sometimes brightness temperature anomalies alone exist in the surrounding of the Dongsha Islands. The highest content of hydrocarbon gas amounts to 393 μL methane per kilogram sediment and the highest radioactive thermoluminescence value is 31752 unit; their geometric averages are 60.5 μL/kg and 2688.9 unit respectively. What is more inspiring is that there are three sites where the methane contents are up to 243, 268 and 359μL/kg and their radioactive thermoluminescence values are 8430, 9537 and 20826 unit respectively. These three locations are just in the vicinity of one of the highest confident BSRs identified by predecessors. Meanwhile, the anomalies are generally coincident with other results such as headspace gas anomaly in the sediment and chloride anomaly in the interstitial water in the site 1146 of Leg 184. The above-mentioned anomalies are most possibly to indicate the occurrence of gas hydrate in the northeastern SCS.

A Scheme for Estimating Tropical Cyclone Intensity Using AMSU-A Data

Brightness temperature anomalies measured by the Advanced Microwave Sounding Unit （AMSU） on the National Oceanic and Atmospheric Administration （NOAA） polar-orbiting series are suited to estimate tropical cyclone （TC） intensity by virtue of their ability to assess changes in tropospheric warm core struc-ture in the presence of clouds. Analysis of the measurements from different satellites shows that the variable horizontal resolution of the instrument has significant effects on the observed brightness temperature anoma-lies. With the aim to decrease these effects on TC intensity estimation more easily and effectively, a new simple correction algorithm, which is related to the product of the brightness temperature gradient near the TC center and the size of the field-of-view （FOV） observing the TC center, is proposed to modify the observed anomalies. Without other measurements, the comparison shows that the performance of the new algorithm is better than that of the traditional, physically-based algorithm. Furthermore, based on the correction algorithm, a new scheme, in which the brightness temperature anomalies at 31.4 GHz and 89 GHz accounting for precipitation effects are directly used as the predictors with those at 54.94 GHz and 55.5 GHz, is developed to estimate TC intensity in the western North Pacific basin. The collocated AMSU-A observations from NOAA-16 with the best track （BT） intensity data from the Japan Meteorological Agency （JMA） in 2002-2003 and in 2004 are used respectively to develop and validate regression coefficients. For the independent validation dataset, the scheme yields 8.4 hPa of the root mean square error and 6.6 hPa of the mean absolute error. For the 81 collocated cases in the western North Pacific basin and for the 24 collocated cases in the Atlantic basin, compared to the BT data, the standard deviations of the estimation differences of the results are 15% and 11% less than those of the CIMSS （Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison） TC intensity AMSU estimation products.

Retrieval Snow Depth by Artificial Neural Network Methodology from Integrated AMSR-E and In-situ Data——A Case Study in Qinghai-Tibet Plateau

On the basis of artificial neural network (ANN) model, this paper presents an algorithm for inversing snow depth with use of AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System (EOS)) dataset, i.e., brightness temperature at 18.7 and 36.5GHz in Qinghai-Tibet Plateau during the snow season of 2002-2003. In order to overcome the overfitting problem in ANN modeling, this methodology adopts a Bayesian regularization approach. The experiments are performed to compare the results obtained from the ANN-based algorithm with those obtained from other existing algorithms, i.e., Chang algorithm, spectral polarization difference (SPD) algorithm, and temperature gradient (TG) algorithm. The experimental results show that the presented algorithm has the highest accuracy in estimating snow depth. In addition, the effects of the noises in datasets on model fitting can be decreased due to adopting the Bayesian regularization approach.

Validation of the “HY-2” altimeter wet tropospheric path delay correction based on radiosonde data

Wet tropospheric path delay （PD） is a highly variable term for the altimeter measurement of a sea surface height, caused by the refraction effect of atmospheric water vapor and cloud liquid water. In order to esti- mate PD values, the ＂HY-2＂ system includes a calibration microwave radiometer （CMR） operating at 18.7, 23.8 and 37 GHz. The PD data of the CMR were compared and validated by coincident radiosonde profiles from ten globally distributed radiosonde stations during October 2011 to August 2012. The temporal interval was 1 h. In order to avoid land contamination, different spatial intervals between these two data sets were tested. The empirical fit function of PD uncertainty and spatial interval was found and extrapolated to the ideal situation that the data of CMR and radiosonde were totally coincident. The stability of the brightness temperature of the CMR and its impact on the PD correction was also studied. Consequently, the uncertainty of the PD algorithm of the CMR was estimated to be 2.1 cm.

EXPERIMENTAL STUDY ON SOIL MOISTURE USING DUAL-FREQUENCY MICROWAVE RADIOMETER

An experiment of measuring soil moisture was carried out by using dual-frequency microwave radiometer designed by the authors. The measured data were analyzed by using statistical regression method and the empirical regression model of retrieving soil moisture in L-band and C-band was developed. The soil moisture in a rainfall event was retrieved using the experiential regression model, which is consistent well with the field sampling value. The results show that when soil moisture is lower than 75%, the brightness temperature is linear with soil moisture. However, when soil moisture is higher than 75%, the brightness temperature is not linear with soil moisture, so it is difficult for microwave radiometer to measure the changes of soil moisture. The experiment verifies the effectiveness and feasibility of microwave remote sensing soil moisture. Although this method for linear regression based on the data measured with the radiometer is simple, and has strong adaptability, generally it has only local application value, and lacks universal applicability for different areas and different conditions.