This paper describes the Altay 2024 airborne field campaign in support of snow observation retrieved from spaceborne InSAR measurements from the Chinese LuTan-1 (a spaceborne L-band SAR constellation launched in 2022). The airborne and field measurements that are synchronized with LuTan-1 InSAR acquisitions will be conducted in January-February 2024 (snow on) and May-July 2024 (snow off). The remote sensing and in-situ measurements include various in-situ observations and drone-based lidar measurements. We first provide the overview of the Altay 2024 campaign including the choice of the in-situ measurement locations and flight tracks of the drone-based lidar. Then, historical InSAR dataset from all the available L/C-band SAR’s (e.g. JAXA’s ALOS, ESA’s Sentinel-1, China’s LuTan-1) over the study area are used to generate SWE change products, which are further compared against the in-situ measurements when available. This synergetic spaceborne airborne field campaign will directly validate the LuTan-1 derived snow products using the acquired airborne and field dataset, which can also support the design of future spaceborne mission concepts for snow retrieval.

The Scanning Microwave Radiometer (SMR) onboard the Haiyang-2B satellite (HY-2B) can provide valuable observation data for various research fields. Resampling enables consistent spatial characteristics of SMR brightness temperature (BT) data from different channels, which is essential for the multi-channel collaborative retrieval of geophysical parameters. However, as the satellite moves, the relative position between the fields of view (FOVs) of different channels changes, and the error resulting from this factor is ignored by the traditional resampling method. Therefore, in this paper, the traditional resampling effect of SMR data at different orbital positions is analyzed in detail. Additionally, an improved resampling method based on multiple scan rows is proposed to reduce resampling errors while maintaining real-time resampling. In the long-term data experiment, compared with the traditional method, the mean Fit Error and Fit Error variation range obtained by the proposed method can be reduced by 57.92% and 54.07%, respectively. In the BT error analysis experiment, the differences in spatial resolution and geolocation between different channels can be eliminated more accurately by the proposed method, and the maximum and average BT errors on the selected long-term data are reduced by 3.80 K and 1.82 K, respectively.

The derivation of ice water path (IWP) from microwave radiometer measurements is challenging. This study presents a deep learning framework for global retrieval of IWP using observations from the Microwave Humidity Sounder-II (MWHS-II) aboard the FengYun-3D (FY-3D) satellites. Two deep learning models, Deep Forest (DF21) and Quantile Regression Neural Network (QRNN) are constructed to detect ice cloud flags and retrieve IWP. By collocating MWHS-II observations with 2C-ICE, a joint product of CloudSat and CALIPSO, deep learning models learn the characteristics of IWP from MWHS-II brightness temperatures. The test results show that the MWHS-II channels provide more information on IWP than the MWHS channels, particularly the 89 GHz channel and the 118 GHz channels with an offset of ≥ 0.8 GHz. Combining the QRNN and DF21 models, the IWP retrieval results in an RMSE of 707.346 g/m2, MAPE of 65.122%, MBE of -104 g/m2, determination coefficient (R2) of 0.683, and Pearson correlation coefficient (PCC) of 0.831. Application of the models to MWHS-II observations of Tropical Cyclone CILIDA shows better agreement with 2C-ICE. All datasets exhibit a similar feature on the monthly mean scale, but the magnitudes of IWP differ. Compared to GMI-GPROF, MODIS, and ERA5 IWP products, MWHS-II results are closest to 2C-ICE. Similar results are also shown for the zonal mean data. These results show that deep learning methods efficiently and probabilistically retrieve IWP from long-term observation data of MWHS/MWHS-II.

The thermal infrared (TIR) emissivity and physical temperature of snow together determine the thermal radiation of snow. The modeling of snow and ice TIR emissivity is important for climate models and remote sensing. Previous snow and ice TIR emissivity models fail in predicting the sensitivity of emissivity to snow type and snow microstructure, which was measured in experiments. Empirical models were proposed to simulate such sensitivity but not in a unified theoretical framework. In this study, we propose a snow and ice TIR emissivity model based on photon tracking by assuming that the geometric optics approximation is still valid in TIR spectral region. It is proved that the proposed model can predict both the TIR emissivity’s sensitivity to grain size for small grain sizes and the TIR emissivity’s sensitivity to snow density. These features can fully explain the experiment observed features. Moreover, the proposed model simulates snow and ice TIR emissivity in a unified theoretical framework. We also explain that the observed emissivity’s sensitivity to snow type is actually caused by the sensitivity to snow density, not grain size. This proposed model can be further used in climate models and remote sensing.

Basic radiative transfer theory reveals that the physical temperature gradients related to heat flow (HF) within the lunar regolith below the diurnal varying layer can be constrained by measurements of brightness temperature (TB) variations over a selected wavelength range, coupled with knowledge of the regolith electrical loss properties. We present a methodology illustrating the processing using recalibrated data from the Chang’E-2 (CE2) 10 and 3.85 cm wavelength microwave radiometer (MRM) data (channels 1 and 2). The utilized data are contained in latitude bins of 1 degree width centered at latitudes of 0, 5,..., 60, north and south. Results, presented as retrieved HF gradients (dT/dz in K/m) vs longitude for each of the 25 latitude bins, provide useful constraints on the overall variability of the heat flow gradient within the 60S-60N latitude range. In particular, no evidence is found that HF variations exceeding twice the Apollo value occur widely in the extensive highland regions of low electrical loss. Limitations related primarily to signal-to-noise (SNR) issues in regions of elevated electrical loss severely reduce thermal gradient retrieval accuracy needed for correlation with enhanced thorium concentrations observed in the frontside mare. Analyses of the CE2 data reveals a noise uncertainty of ~ 0.5 K in the TB10-TB3.85 measurements, equivalent to ~ 0.7 - 1.4 (loss tangent dependent) times the Apollo measured mean HF value of 1.8e-6w/cm2. The limitations preclude meaningful identification of regional variations within a precision less than one Apollo heat flow unit. An analyses is presented demonstrating that a threefold increase in SNR would be attained by addition of a 30 cm wavelength channel to the CE2 MRM’s design, providing sufficient resolution to map regional HF variations to ~ 0.5e-6w/cm2precision, ~ 30% of the averaged Apollo sites’ measured HF value.

The weight function (WF) of the microwave radiometer channel plays an important role in the development of the theory of microwave remote sensing and the design of microwave remote sensing instruments. A deep neural network (DNN) is used to describe the relationship between the atmospheric parameters and the channel WF for Microwave Humidity and Temperature Sounder (MWHTS) onboard Fengyun-3D (FY-3D) satellite, and a DNN-based WF calculation model is developed. The experimental results show that the calculated results of WF for MWHTS from the DNN-based WF calculation model are almost equal to those of the traditional radiative transfer model, and the accuracy of the distribution of the peak WF height is high. In addition, the DNN-based WF calculation model has higher computational efficiency compared with the traditional radiative transfer model.

Ice cloud parameters have an important influence on global climate research and weather forecast. According to the atmospheric radiation theory, sub-millimeter wave is the best frequency band for ice cloud remote sensing. In this paper, the principle and research status of ice cloud remote sensing is analyzed. The detection capabilities of different ice cloud sounders are compared, and a sub-millimeter wave ice cloud sounder for the next generation meteorological satellite is designed. The ice cloud sounder covers five detection frequencies of 183GHz, 243GHz, 325GHz, 448GHz and 664GHz, and uses cone scanning mode, with the spatial resolution better than 10km, noise temperature better than 3000K.

In the field of satellite-based microwave remote sensing, the classification of microwave observation data according to weather conditions is an important data preprocessing step in both dealing with the forward and inverse problems, which directly affects the application of observation data and the development of microwave remote sensing theory. This study designed to use the microwave radiative transfer model to classify the simulation accuracy of the observed data for the data classification preprocessing in the forward problem. And the corresponding clear-sky thresholds under clear-sky conditions are established. The experimental results show that the clear-sky data selection method for microwave remote sensing data based on the radiative transfer model has higher classification accuracy than the classification method using third-party data sources, and the operation is easy and promising for the operational meteorological application.

The Chang’E-1 and E-2 (CE-1 and CE-2) orbital sounders provided high-resolution global maps of lunar microwave brightness temperatures (TBs) at wavelengths of 0.8, 1.55, 3.85, and 10 cm covering approximately two years of data over the 2007–2010 time frame. The four-channel microwave radiometers (MRMs) effectively sampled the upper ~2 m of the lunar regolith and are diagnostic of thermal and electrical properties, including mineralogy, rock abundance, and, potentially, interior heat flow. Early comparisons of colocated data between the two instruments revealed ~10–20 K offsets between the CE-1 and CE-2 measurements that required in- flight recalibration efforts. These have included comparisons with model predictions at Apollo sites as well as adjustments of the cold sky horn reference temperatures to include contamination from lunar surface emissions. This article proposes an in- flight recalibration methodology that focuses on correction of the preflight transfer coefficients that determine the relative importance of component losses along the radiometer hardware paths connecting the antennas to the detectors. It is shown that for each channel, a single parameter, representing the ratio of the cold sky and main antenna transfer coefficients, can be constrained by knowledge of the stable regolith physical temperatures below the diurnal-varying layer and is sufficient to establish values for the complete set of hardware transfer coefficients. The in- flight comparisons proposed for recalibration are based on backside highland models of regolith thermal properties. Potential remaining offsets of the recalibrated MRM data are evaluated in terms of parameter uncertainties of our chosen nominal thermal model.

Haiyang-2B (HY-2B) is the second marine dynamic environment satellite of China. Sea surface temperature (SST) products from the scanning microwave radiometer (SMR) onboard HY-2B satellite are evaluated against in situ measurements. Approximately, ten months of data are used for the initial evaluation, from January 15, 2019 to November 15, 2019. The temporal and spatial windows for collocation are 30 min and 25 km, respectively, which produce 450 416 matchup pairs between HY-2B/SMR and in situ SSTs. The statistical comparison of the entire data set shows that the mean bias is -0.13 °C (SMR minus buoy), and the corresponding root-mean-square error (RMSE) is 1.06 °C. Time series of collocations for the SST difference shows that a good agreement is found between HY-2B/SMR and in situ SSTs after June 15, revealing a mean bias and an RMSE of only 0.09 °C and 0.72 °C, respectively. A three-way error analysis is conducted between the SMR, Global Precipitation Measurement Microwave Imager (GMI), and in situ SSTs. Individual standard deviations are found to be 0.41 °C for the GMI SST, 0.15 °C for the in situ SST, and 1.03 °C for the SMR SST. The results indicate that the HY2B/SMR SST products need to be improved during the period from January 15, 2019 to June 15, 2019.

Wind is a major factor in the formation of sea surface foam. Foam layer parameters, such as thickness and coverage are functions of wind speed. Microwave emissivity of sea surface is sensitive to thickness of its foam cover. Foam thickness plays a vital role in emissivity from sea surface with foam cover. The average thickness of foam layer is can be estimated from sea surface wind speed. In this study, the foam layer emissivity is simulated using the incoherent multiple scattering model at different wind speeds and observation frequencies. Model predictions show that emissivities at different frequencies are sensitive to average foam thickness (and wind speed) at different ranges. Model Comparisons with AMSR2 measurements show good agreement on how foam emissivity varies with wind speed; they also show better correlation for V-polarized emissivity at 36.5GHz and 6.9GHz at wind speed of 5 m/s to 30 m/s.

An advanced terahertz atmospheric profiling sounder for Chinese next generation meteorological satellite (FY-5 satellite) is introduced in this paper, driven by recent advances in microwave device technology that now permit broad frequency bands and higher frequencies into more sounding channels in order to not only improve both the vertical and horizontal resolutions of the retrieved atmospheric profile, but also enhance sounding capability of atmospheric hydrometeor parameters, like water cloud, ice, snow, rain and gaupel. Global simulation studies over ocean and land in clear and cloudy atmospheres using WMO radiosonde datesets and NWP reanalysis are presented that assess the temperature, moisture, and precipitation sounding capability with channels sampled near the 89, 118.75, 183.31, 380 and 425GHz absorption lines. Channel specification and configuration are presented after channel correlation and retrieval demonstration, and the distribution of subsystem units are determined based on previous design experience and requirements of satellite platform.

A newly designed thermal/vacuum (T/V) prelaunch multiangle calibration test is proposed for Microwave Humidity and Temperature Sounder (MWHTS) onboard the Feng Yun 3D satellite. Compared with other existing prelaunch calibration tests designed at fix scan angle, this test is first proposed to analyze the measurements of MWHTS from multiscan angles. A set of comprehensive calibration method is established and used for calibration data processing. The high-quality data preprocessing methods are performed. Essential calibration coefficients such as cold bias, hot bias, and nonlinearity coefficients, and calibration results such as calibration residual error, sensitivity, and calibration accuracy of MWHTS are all obtained and analyzed in MWHTS's six observing positions. The measured sensitivity value of channel 2 is 1.5 K while the measured sensitivities of the others range from 0.18 to 0.57 K. The calibration accuracy of channel 2 is 1.5 K while the calibration accuracies of the others range from 0.32 to 0.7 K. According to the discrepancy of multiangle calibration test results, the radiation leakage and the response lag for special channels are discovered for the first time in T/V test, and the reasons of these two special phenomena are fully analyzed. Moreover, the measurements of the T/V test with fast changing instrument temperatures are analyzed and the applicability of nonlinearity coefficients obtained in T/V test for in-orbit calibration is verified. In conclusion, MWHTS meets the basic design requirements of sensitivity and calibration accuracy, the changing of the MWHTS observing positions does not impact the calibration coefficients and results, and the nonlinearity coefficients obtained in T/V test are valid when instrument temperature experiences some fast changing.

The paper introduces the design and development of MWHTS system and quantitatively evaluates the stability of its post-launch performance (3 years and 3 months). The on-orbit assessment of MWHTS demonstrates that the MWHTS onboard FY-3C has been improved compared to it on FY-3A and FY-3B. Furthermore, using the observing data from MTHTS shows that the instrument plays an important role in monitor extreme climate, especially for typhoon between June to Sept in 2016, including the procedure of generating, evolution, strengthen and die out, and also including the heavy rainfall caused by typhoon, which is compared against ground-based observations (gauge) and products blended by sensors onboard TRMM and GPM.

This paper presents a rain rate retrieval algorithm for tropical cyclones (TCs) using passive microwave Fengyun-3B (FY-3B) MWRI brightness temperature (TB). Channel 18.7 and 36.5GHz of FY-3B/MWRI are used to implement retrieval algorithm. Two databases are constructed: one is 15,153 matchups of MWRI TB and NSIDC global swath ocean products for rain rate retrieving and another databset of 5,093 matchups retrieved rain rates and NSIDC rain rate products is used for error estimation of the retrievals. The retrieved rain rates show good agreement with the NSIDC surface rain rates in rain structures. Although there are slightly overestimated at heavy rain rates, the total bias is only 0.8467 mm/h and the total rms is 4.3475 mm/h even in the intensive TCs. This is submitted for the special session of “New Developments of Chinese Oceanographic and Meteorological Satellites”.

The Microwave Imager Combined Active/Passive (MICAP) is a suit of active/passive instrument package, which has been proposed for demonstrating the capability of remote sensing the sea surface salinity (SSS), sea surface temperature (SST) and wind speed (WS). In this paper, a nonlinear optimization algorithm for simultaneous retrieval of the above parameters is described. The sensitivity of active/passive microwave observations to SSS is analyzed using the nonlinear optimization algorithm. The results show that the root mean square (RMS) error on the retrieved SSS estimated by using the nonlinear optimization algorithm is enough to meet the requirement of Ocean Salinity Satellite. This is submitted for the special session of “New Developments of Chinese Oceanographic and Meteorological Satellites”.

Brightness temperature data in Amazon Rainforest, Sahara Desert, and Greenland Plateau are compared between HY-2A Atmospheric Correction Microwave Radiometer (ACMR) and Jason2 Advanced Microwave Radiometer (AMR). The brightness temperature data of the HY-2A ACMR are recalibrated. The brightness temperature recalibration results of the HY-2A ACMR agree well with those of Jason2 AMR. This is submitted for the special session of “New Developments of Chinese Oceanographic and Meteorological Satellites”.

Earth observation satellites play a critical role in providing information for understanding the global water cycle, which dominates the Earth-climate system. However, limitations in observations will restrict our current ability to reduce the uncertainties in the information used to make decisions regarding to water use and management. Under the support of “Strategic Priority Research Program for Space Sciences” of the Chinese Academy of Sciences, a new satellite concept of global Water Cycle Observation Mission (WCOM) is proposed, aiming to provide higher accuracy and consistent measurements of key elements of water cycle from space, including soil moisture, ocean salinity, freeze-thaw, snow water equivalent and etc. The expected more consistent and accurate datasets would be used to refine existing long-time series of satellite measurements, to constrain hydrological model projections and to detect the trends necessary for global change studies. The WCOM is expected to be implemented during the 13thfive-year-plan period (2016–2020).

Water Cycle Observation Mission (WCOM) is a mission dedicated to synergetic observations of global water cycle parameters, with emphasis on soil moisture, ocean surface salinity, snow water equivalent and frozen/thaw. WCOM implements its observation requirements by measurement of microwave emission/scattering of both the frequencies sensitive to the key parameters and also the auxiliary frequencies providing necessary atmospheric and surface roughness corrections. In order to satisfy this measurement requirements, WCOM is equipped with payloads with combination of active and passive microwave sounding capabilities of frequency from L-band to W-band. In addition to the multiple frequency requirement, the requirement for spatial resolutions and swath width leads to large aperture antennas and scanning of antenna beams, the accommodation of the three payloads becomes the major challenge for the design of the WCOM satellite. In order to satisfy the temporal resolution requirement, the design of data downlink and ground segment are also discussed. In this presentation, a preliminary design for WCOM satellite is provided, some technical issues need further investigation are also discussed.

An one-dimensional variational retrieval system was developed to retrieve the clear sky atmospheric temperature and humidity profiles over land using the measurements of microwave humidity-temperature sounder (MWHTS) on Chinese FY-3C satellite. The system parameters are configured by analyzing the MWHTS channel properties and the climate condition over land. The retrieval results are evaluated by root mean square error (rmse) with respect to European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The validated results show that the maximum root mean square error of temperature and humidity are 2.59K and 11.87%, respectively. The retrieval results, compared with National Centers for Environmental Prediction (NCEP) 6 hour forecast profiles, show that the background profiles can affect the accuracy of retrieval profiles and FY-3C/MWHTS measurements can improve forecast precision of humidity.

The new generation Microwave Humidity Sounder (MWHSII) is a fifteen-channel microwave radiometer working at central frequency of 89, 118.75, 150 and 183.31GHz onboard FengYun 3C satellite (FY-3C). This paper provides an extensive evaluation of the measurements of MWHS-II with the radiances simulated by atmospheric radiative transfer model RTTOV-11 using ECMWF ERA data in 0.75° grid at 37 vertical levels during 1, Feb 2014 and 31, Dec 2014. Because the brightness temperature over ocean surface is more stable than that over land surface and the emissivity of ocean surface is more accurate than land surface's, only the clear sky data over ocean surface is used for analysis. The analysis was conducted by two part. One is a global comparison of the TB products [1] of MWHS-II with the simulations by RTTOV-11, and the other is analyzing the effects of in-orbit calibration method on TB combined pre-launch thermal vacuum calibration[1]. The results shows that the monthly STD of TB products minor simulations by RTTOV-11 (TB differences) kept stable during the period calculated. And the monthly STD of TB differences are very close to the calibration sensitivity. The monthly means of TB differences is more stable in the channel of 1~5 and 10~12. However in the channel of 7~9 and 13~15, the monthly means of TB differences is more stable in cases corrected by hot bias. The antenna pattern correction contributes to decrease variety range of monthly means of TB differences in the channel of 5~6 and 11~13. A further evaluation on the measurements is progressing.

Polarimetric Microwave Imager (PMI) is planning as one of the main payload on WCOM satellite with the purposes of collecting the radiation from the Earth surface to retrieve the geophysical parameters of the land, ocean and atmosphere. PMI is passive microwave radiometer with frequencies of 6.8, 10.7, 18.7, 23.8, 37 .0 and 89GHz. The radiometers at 10.7, 18.7 and 37.0 GHz are full-polarized to measure four Stokes of the surface, whether from the ocean or the land. The other frequencies are traditional radiometer with vertical and horizontal channels. Since the third and the fourth Stokes parameter are sensitive to the orientation feature of the surface, they can be used to retrieve the wind vector, rain, snow cover, forest distribution and polar icecaps. Furthermore, with the higher resolutions at 37.0 and 89.0 GHz, the freeze-thaw on the land and rain on the ocean can be more accurately evaluated. In the paper, some primacy consideration and design on PMI are given for the application fulfilling the requirements of WCOM.

Microwave remote sensing provides an opportunity to retrieve wind speed (WS) inside tropical cyclones (TCs) due to the high atmospheric transmissivity through clouds and under rain conditions. A WS retrieval algorithm for WS above 20m/s in TCs using brightness temperature at 6.8- and 10.7-GHz has been developed and a new set of parameters has been optimized from 6.9GHz and 10.7GHz TB and the HWind analysis matches. This algorithm is estimated to have an encouraging degree of accuracy for retrieving WS in TCs. Then the retrieved wind speeds of TCs are used to study wave heights in TCs in the South China Sea.

There are three retrieval algorithms developed for the HY-2A Atmospheric Correction Microwave Radiometer (ACMR). The validation Results of these retrieval algorithms and corresponding products (the wet tropospheric path delays) are presented. Comparisons are made between HY-2A ACMR and various sources including Jason2 Advanced Microwave Radiometer (AMR), global climatological model (ECMWF).

Water vapor and cloud liquid water can influence the accuracy of sea surface height that spaceborne altimeter measures. Atmospheric correction microwave radiometer (ACMR) can be used to retrieve the amount of water vapor and cloud liquid water by measuring radiation from atmosphere and earth's surface. HY-2 satellite is a Chinese satellite for ocean dynamic environmental monitoring. ACMR is one payload of HY-2 satellite. Up to now, ACMR has been in operation for more than three years. In-orbit system stability of three years is assessed. The data of ACMR brightness temperature are matched to that of ECMWF wet tropospheric path delay in same space and time. The water vapor and cloud liquid water retrieval algorithm is derived The wet tropospheric path delay deviations are less than 1.5cm. Brightness temperatures and path delay of ACMR were compared with that of AMR. The average and standard deviations of wet tropospheric path delay are 1.27mm and 0.68mm.

The Advanced Microwave Atmospheric Sounder (AMAS) is the new generation of Microwave Humidity Sounder (MWHS) onboard the Feng Yun 3 C/D (FY-3C/D) satellite and follows the heritage and development of MWHS onboard the FY-3(A/B) satellite. AMAS onboard the FY-3C satellite is a 15-channel total power microwave radiometer in the range of 89-191 GHz scheduled to be launched on September 23, 2013. Compared to MWHS onboard FY-3A/B, AMAS improves channel characteristics by adding eight horizontal polarized channels near 118.75 GHz, which is the first operational polar-orbiting satellite-based sensor to observe the atmosphere in Earth-scanning mode in the 118-GHz oxygen band. Also, AMAS has more channels at 183 GHz than MWHS. This paper analyzes the channel capability and radiometric characteristics of AMAS at 118.75 GHz. Before the launch of FY-3C, the intensive thermal vacuum (T/V) tests for AMAS were carried out in a 2-m T/V chamber, and the basic parameters were obtained, such as the receiver nonlinearity and sensitivity of each channel for AMAS. Furthermore, system nonlinear error correction and bias correction of warm and cold targets are derived after the T/V data analysis and will be used for calibration processing, playing an important role in level 1 and 2 data processing. Accuracies of calibrated channels in AMAS range from 0.48 K to 2.7 K.

WCOM, the Water Cycle Observation Mission, is proposed to improve the capability of synergetic observation of key water cycle variables. By developing innovative active-passive and multi-frequency combined sensors and retrieval models and techniques, the scientific objectives of this mission is to deepen the understanding on global water distribution, transportation and phase conversion by synergistic observations; and based on the improved model and data, to rebuilt long-term data series for revealing of the responses and feedbacks of water cycle to global changes.

Earth observation satellites play a critical role in providing information for understanding the global water cycle, which dominates the Earth-climate system. However, limitations in observations will restrict our current ability to reduce the uncertainties in the information used to make decisions regarding to water use and management. Under the support of “Strategic Priority Research Program for Space Sciences” of the Chinese Academy of Sciences, a new satellite concept of global Water Cycle Observation Mission (WCOM) is proposed, aiming to provide higher accuracy and consistent measurements of key elements of water cycle from space, including soil moisture, ocean salinity, freeze-thaw, snow water equivalent and etc. The expected more consistent and accurate datasets would be used to refine existing long-time series of satellite measurements, to constrain hydrological model projections and to detect the trends necessary for global change studies.

In this paper, we give a method of calibrating Tbon HY-2 satellite by cross comparing them with those from WindSat satellite. The results show that the re-calibrated Tbwere obviously closer to the simulated Tbby using ECWMF data. We will further investigate the accuracies with newly launched microwave radiometer AMSR2.

Water vapor and cloud liquid water influence the accuracy of altimeter measurements by delaying the time that altimeter's signals travel from satellite to the ocean surface and back. Atmospheric correction microwave radiometer (ACMR) can be used to measure radiation from atmosphere and earth's surface so as to retrieve the amount of water vapor and cloud liquid water. HY-2 satellite is a Chinese satellite for ocean dynamic environmental monitoring. It launched on Aug.16, 2011. ACMR is one of HY-2 satellite payloads. The other payloads are an altimeter, a scatterometer and a scanning microwave radiometer. ACMR started to work on Sep.1, 2011. Since then, it has been in normal operation. In this paper, instrument description, pre-launch calibration and in-orbit performance assessment of ACMR are briefly presented.

Since the first polarimetric radiometer satellite WindSat was launched on January 6, 2003 [1] and has been working normally until now, microwave polarimetry has demonstrated its ability on retrieving global wind vector [2].The first digital correlation microwave polarimeter was designed in 2001 [3], and digital technology has made a great progress during the last decade. We describe design of a digital-correlation full-polarimetric microwave radiometer system (DPMR), which operates at the same frequencies as WindSat, i.e. 6.8, 10.7, 18.7, 23.8 and 37.0 GHz. A direct digital cross-cerrelation technique is used in the system to produce four Stokes parameters at each frequency simultaneously. The main specifications are list in TABLE 1.

Design and Technical specification parameters of MWHS-II (MicroWaves Humidity Sounder) of FY-3 satellite are presented, which include much improvements compared to MWHS onboard FY-3A/B satellite launched in 2008 and 2010. Especially MWHS-II adds 8 channels at 118.75GHz to sound temperature information for the first time internationally. The simulation results show that MWHS-II will play an important role in the meteorological sounding system for measuring global atmospheric temperature and water vapour profiles.

The Microwave Humidity Sounder (MWHS) is a five-channel microwave radiometer in the range of 150-191 GHz onboard FengYun 3 (FY-3). Before the launch of FY-3A, the intensive thermal vacuum (TVAC) tests for MWHS had been carried out in a 2-m TVAC chamber, and the basic parameters such as receiver nonlinearity were obtained. Four-year operation shows that the performance of FY-3A MWHS remains stabile. The variations among space views and warm target views in the interval of scan lines were generally within 20 counts. In addition, the temperature fluctuation of the warm target in a single pass is within 0.5 K. Primarily, due to the nonlinearity correction obtained from the TVAC test, radiance measurements of MWHS agree well with NOAA-17 AMSU-B and NOAA-18 Microwave Humidity Sounder (MHS) data. Averaged brightness temperature differences between FY-3 MWHS and NOAA-17 AMSU-B, at simultaneous cross-overpass points, are less than 1.08 K for the channels at 183 ± 1 GHz. In the observation-minus-background comparison, the observed and simulated brightness temperature biases of FY-3 MWHS and NOAA-18 MHS exhibit similar performance in the 183.31 ± 1 GHz channel; but in the 183.31 ± 7 GHz channel, MWHS agrees better with background. It is anticipated that FY-3 MWHS data will contribute to numerical weather prediction.

China's Feng Yun-3A (FY-3A) meteorological satellite is a second-generation polar-orbiting meteorological satellite launched in May 2008. The Microwave Humidity Sounder (MWHS) is the main payload, designed for atmospheric humidity sounding. Before the launch of MWHS, a series of experiments was conducted in a thermal/vacuum (T/V) chamber. This letter describes the MWHS T/V calibration, in which the flight model currently operating on FY-3A was tested. The calibration procedure and data-processing methods are presented. Calibration results, such as radiometric resolution, receiver nonlinearity, and calibration bias, were obtained. The results meet the specifications on bias and sensitivity of MWHS. Since the instrument temperatures will be approximately 10°C-20°C on orbit, the calibration errors of MWHS over the range of 100-300 K would be less than 0.3 K using the nonlinearity coefficients derived in the T/V test.

Chang'e-1 Microwave Sounder (CELMS) is a main payload of Chang'e-1 Moon Orbit Satellite in the first stage of China Lunar Probe. CELMS is a four-frequency microwave radiometer with frequencies 3GHz, 7.8GHz, 19.35GHz and 37GHz. During the one year and four months' working in lunar orbit, it got huge scientific data covering full moon surface and obtained the world first global lunar microwave emission measurements. Moreover, we obtained the world first the microwave brightness temperature map in global scale and established the Microwave Moon (MicM). MicM consists of global microwave brightness temperature maps, lunar pole microwave anomalies feature maps, microwave emission feature maps for some special areas of the lunar surface.

This paper presents a detailed analysis of a simplified Two-Scale Model for ocean surface polarimetric microwave emission, and investigates the extent to which varying ocean surface length scales contribute to brightness temperature zeroth and second azimuth harmonics. The Two-Scale Model can be expressed as a weighting function M0,2multiply ocean surface curvature spectrum C0,2. This implies a simple way to investigate the effect of curvature spectrum on ocean emission. It is found that ocean waves with wavelengths both comparable to and much greater than the electromagnetic wavelength can contribute to these harmonics, depending on the value of the ocean surface spectrum in these length scales. An ocean wave spectrum was derived from polarimetric microwave radiometer data according to constrained linear least-squares method.

We analysed the performances of multi-channel microwave radiometer (RAD) on-aboard SZ-4 spacecraft launched at the end of 2002. Because RAD lacks of on-orbit external calibration, we put forward a vicarious external calibration scheme, i.e., we re-calibrated all RAD channels using the typical microwave emission targets on the surface of the Earth, the global open ocean and Amazon Rain Forest. We compared the re-calibrated brightness temperatures of RAD with in situ measurements obtained during the ground experiment carried in February, 2003.