Satellite retrieval of hurricane wind speeds using the AMSR2 microwave radiometer

The AMSR2 microwave radiometer is the main payload of the GCOM-W1 satellite,launched by the Japan Aerospace Exploration Agency in 2012. Based on the pre-launch information extraction algorithm,the AMSR2 enables remote monitoring of geophysical parameters such as sea surface temperature,wind speed,water vapor,and liquid cloud water content. However,rain alters the properties of atmospheric scattering and absorption,which contaminates the brightness temperatures measured by the microwave radiometer. Therefore,it is difficult to retrieve AMSR2-derived sea surface wind speeds under rainfall conditions. Based on microwave radiative transfer theory,and using AMSR2 L1 brightness temperature data obtained in August 2012 and NCEP reanalysis data,we studied the sensitivity of AMSR2 brightness temperatures to rain and wind speed,from which a channel combination of brightness temperature was established that is insensitive to rainfall,but sensitive to wind speed. Using brightness temperatures obtained with the proposed channel combination as input parameters,in conjunction with HRD wind field data,and adopting multiple linear regression and BP neural network methods,we established an algorithm for hurricane wind speed retrieval under rainfall conditions. The results showed that the standard deviation and relative error of retrievals,obtained using the multiple linear regression algorithm,were 3.1 m/s and 13%,respectively. However,the standard deviation and relative error of retrievals obtained using the BP neural network algorithm were better(2.1 m/s and 8%,respectively). Thus,the results of this paper preliminarily verified the feasibility of using microwave radiometers to extract sea surface wind speeds under rainfall conditions.

Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite

HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China,which was launched on 16th August 2011.A scanning microwave radiometer（RM） is carried for sea surface temperature（SST）,sea surface wind speed,columnar water vapor and columnar cloud liquid water detection.In this paper,the initial SST product of RM was validated with in-situ data of National Data of Buoy Center（NDBC） mooring and Argo buoy.The validation results indicate the accuracy of RM SST is better than 1.7 C.The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed.Then,the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements.Based on the results of assessment and errors analysis,the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.

A preliminary assessment of the sea surface wind speed production of HY-2 scanning microwave radiometer

A scanning microwave radiometer（RM） was launched on August 16,2011,on board HY-2 satellite.The six-month long global sea surface wind speeds observed by the HY-2 scanning microwave radiometer are preliminarily validated using in-situ measurements and WindSat observations,respectively,from January to June 2012.The wind speed root-mean-square（RMS） difference of the comparisons with in-situ data is 1.89 m/s for the measurements of NDBC and 1.72 m/s for the recent four-month data measured by PY30-1 oil platform,respectively.On a global scale,the wind speeds of HY-2 RM are compared with the sea surface wind speeds derived from WindSat,the RMS difference of 1.85 m/s for HY-2 RM collocated observations data set is calculated in the same period as above.With analyzing the global map of a mean difference between HY-2 RM and WindSat,it appears that the bias of the sea surface wind speed is obviously higher in the inshore regions.In the open sea,there is a relatively higher positive bias in the mid-latitude regions due to the overestimation of wind speed observations,while the wind speeds are underestimated in the Southern Ocean by HY-2 RM relative to WindSat observations.

Comparison of CloudSat Cloud Liquid Water Paths in Arctic Summer Using Ground-Based Microwave Radiometer

Arctic clouds strongly influence the regional radiation balance, temperature, melting of sea ice, and freezing of sea water. Despite their importance, there is a lack of systematic and reliabie observations of Arctic clouds. The CloudSat satellite launched in 2006 with a 94GHz Cloud Profiling Radar （CPR） may contribute to close this gap. Here we compare one of the key parameters, the cloud liquid water path （LWP） retrieved from CloudSat observations and from microwave radiometer （MWR） data taken during the ASCOS （Arctic Summer Cloud Ocean Study） cruise of the research vessel Oden from August to September 2008. Over the 45 days of the ASCOS cruise, collocations closer than 3 h and 100 km were found in only 9 d, and collocations closer than 1 h and 30 km in only 2 d. The poor correlations in the scatter plots of the two LWP retrievals can be explained by the patchiness of the cloud cover in these two days （August 5th and September 7th）, as confirmed by coincident MODIS （Moderate-resolution Imaging Spectroradiome- ter） images. The averages of Oden-observed LWP values are systematically higher （40-70 g m-2） than the corresponding CloudSat observations （0-50 g m2）. These are cases of generally low LWP with presumably small droplets, and may be explained by the little sensitivity of the CPR to small droplets or by the surface clutter.

Influence of assimilating ground-based microwave radiometer data into the WRF model on precipitation

Ground-based microwave radiometers profilers(MWRPs)have been used in numerical weather prediction(NWP)systems and show different impacts on forecasts.Currently,there are around hundreds of ground-based MWPRs used in weather stations over China;however,the application of MWPRs in NWP systems is rather limited.In this work,two MWRP retrieved profiles were assimilated into the Weather Research and Forecasting(WRF)model for a rainstorm event that occurred in Beijing,China.The quality of temperature and humidity profiles retrieved from the MWRP was evaluated against radiosonde observations and showed the reliability of the two MWRP products.Then,comparisons between the measurements of ground-based rain gauges and the corresponding forecasted precipitation in different periods of the rainstorm were investigated.The results showed that assimilating the two MWRPs affected the distribution and intensity of rainfall,especially in the early stage of the rainstorm.With the development of the rainstorm,adding MWRP data showed only a slight influence on the precipitation during the stable and mature period of the rainstorm,since the two MWRP observations were too limited to affect the large area of heavy rainfall.

0-10 KM TEMPERATURE AND HUMIDITY PROFILES RETRIEVAL FROM GROUND-BASED MICROWAVE RADIOMETER

Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.

Research on sea surface temperature retrieval by the one-dimensional synthetic aperture microwave radiometer, 1D-SAMR

Due to the low spatial resolution of sea surface temperature(T_S)retrieval by real aperture microwave radiometers,in this study,an iterative retrieval method that minimizes the differences between brightness temperature(T_B)measured and modeled was used to retrieve sea surface temperature with a one-dimensional synthetic aperture microwave radiometer,temporarily named 1 D-SAMR.Regarding the configuration of the radiometer,an angular resolution of 0.43°was reached by theoretical calculation.Experiments on sea surface temperature retrieval were carried out with ideal parameters;the results show that the main factors affecting the retrieval accuracy of sea surface temperature are the accuracy of radiometer calibration and the precision of auxiliary geophysical parameters.In the case of no auxiliary parameter errors,the greatest error in retrieved sea surface temperature is obtained at low T_S scene(i.e.,0.7106 K for the incidence angle of 35°under the radiometer calibration accuracy of0.5 K).While errors on auxiliary parameters are assumed to follow a Gaussian distribution,the greatest error on retrieved sea surface temperature was 1.3305 K at an incidence angle of 65°in poorly known sea surface wind speed(W)(the error on W of 1.0 m/s)over high W scene,for the radiometer calibration accuracy of 0.5 K.

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.

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.

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.

Retrieval of Sea Surface Wind Speed by One-Dimensional Synthetic Aperture Microwave Radiometer

One-dimensional synthetic aperture microwave radiometers have higher spatial resolution and record measurements at multiple incidence angles.In this paper,we propose a multiple linear regression method to retrieve sea surface wind speed at an incidence angle between 0°65°.We assume that a one-dimensional synthetic aperture microwave radiometer operates at frequencies of 6.9,10.65,18.7,23.8 and 36.5 GHz.Then,the microwave radiative transfer forward model is used to simulate the measured brightness temperatures.The sensitivity of the brightness temperatures at 0°65°to the sea surface wind speed is calculated.Then,vertical polarization channels(VR),horizontal polarization channels(HR)and all channels(AR)are used to retrieve the sea surface wind speed via a multiple linear regression algorithm at 0°65°,and the relationship between the retrieval error and incidence angle is obtained.The results are as follows:(1)The sensitivity of the vertical polarization brightness temperature to the sea surface wind speed is smaller than that of the horizontal polarization.(2)The retrieval error increases with Gaussian noise.The retrieval error of VR first increases and then decreases with increasing incidence angle,the retrieval error of HR gradually decreases with increasing incidence angle,and the retrieval error of AR first decreases and then increases with increasing incidence angle.(3)The retrieval error of AR is the lowest and it is necessary to retrieve the sea surface wind speed at a larger incidence angle for AR.

MICROWAVE RADIOMETER AND ITS APPLICATION TO SNOW MEASUREMENT

The microwave radiactivproperty of snow is studied using self-developed three band microwave radiometers. Experiments were carried out repeatedly from 1986 to 1989 in Northeast China The relation between brightness temperature and observation angle was obtained with both vertical and horizontal polarizations. The curves corresponding brightness temperature and snow depth were also drawn out for different frequency bands. The results demonstrate the application potential of the multifrequency microwave radiometer in this area.

Primary Analysis of Sounding Data from a Multi-channel Parallel Ground-based Microwave Radiometer

The sounding data of a multi-channel parallel ground-based microwave radiometer （MWR） in Fuzhou station in July and August in 2016 were compared with the sounding data of a radiosonde in the same position in the same period. The results showed that the correlations between the two types of temperature or humidity detected by the microwave radiometer and the radiosonde were significant at 0.05 level, indicating that the overall changing trends of temperature or humidity detected by the two devices were similar. The temperature detected by the microwave radiometer and the radiosonde decreased with the increase of height. The difference between the changes in the height of the zero layer detected by the micro- wave radiometer and the radiosonde was not significant, and their trends were basically the same.

Data processing and error analysis for the CE-1 Lunar microwave radiometer

The microwave radiometer （MRM） onboard the Chang＇ E-1 （CE-I） lu- nar orbiter is a 4-frequency microwave radiometer, and it is mainly used to obtain the brightness temperature （TB） of the lunar surface, from which the thickness, temperature, dielectric constant and other related properties of the lunar regolith can be derived. The working mode of the CE-1 MRM, the ground calibration （including the official calibration coefficients）, as well as the acquisition and processing of the raw data are introduced. Our data analysis shows that TB increases with increasing frequency, decreases towards the lunar poles and is significantly affected by solar illumination. Our analysis also reveals that the main uncertainty in TB comes from ground calibration.

A Thorough Evaluation of the Passive Microwave Radiometer Measurements onboard Three Fengyun-3 Satellites

Microwave Radiometer Imager(MWRI) is a key payload of China’s second generation polar meteorological satellite, i.e., Fengyun-3 series(FY-3). Up to now, 5 satellites including FY-3A(2008), FY-3B(2010), FY-3C(2013), FY-3D(2018), and FY-3E(2021) have been launched successfully to provide multiwavelength, all-weather, and global data for decades. Much progress has been made on the calibration of MWRI and a recalibrated MWRI brightness temperature(BT) product(V2) was recently released. This study thoroughly evaluates the accuracy of this new product from FY-3B, 3C, and 3D by using the simultaneous collocated Global Precipitation Measurement(GPM)Microwave Imager(GMI) measurements as a reference. The results show that the mean biases(MBEs) of the BT between MWRI and GMI are generally less than 0.5 K and the root mean squares(RMSs) between them are less than1.5 K. The previous notable ascending and descending difference of the MWRI has disappeared. This indicates that the new MWRI recalibration procedure is very effective in removing potential errors associated with the emission of the hot-load reflector. Analysis of the dependence of MBE on the latitude and earth scene temperature shows that MBE decreases with decreasing latitude over ocean. Furthermore, MBE over ocean decreases linearly with increasing scene temperature for almost all channels, whereas this does not occur over land. A linear regression fitting is then used to modify MWRI, which can reduce the MBE over ocean to be within 0.2 K. The standard deviation of error of GMI, FY-3B, and FY-3D MWRI BT data derived by using the three-cornered hat method(TCH) shows that GMI has the best overall performance over ocean except at 10.65 GHz where its standard deviation of error is slightly larger than that of FY-3D. Over land, the standard deviation of error of FY-3D is the lowest at almost all channels except at 89V. MWRI onboard FY-3 series satellites would serve as an important passive microwave radiometer member of the constellation to monitor key surface and atmospheric properties.

MEASUREMENT OF WATER VAPOR AND CLOUD LIQUID WATER CONTENT BY A DUAL-CHANNEL GROUND-BASED MICROWAVE RADIOMETER

The design principle and structural features of a new type dual-channel ground-based microwave radiometer for measurement of water vapor and liquid water in troposphere are discussed. A method independent of radiosonde data is used for system absolute calibrations. A statistical method for retrieving the total water vapor and cloud liquid water content and a nonlinear iterative algorithm for retrieving the water vapor profiles in the troposphere are discussed. Comparison is conducted between the measurement of the integrated amounts of the water vapor and the tropospheric vapor profiles by the radiometer and the radiosonde data.

Spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River during the period 2002–2011 based on the Advanced Microwave Scanning Radiometer for the Earth Observing System(AMSR-E) data

Detecting near-surface soil freeze-thaw cycles in high-altitude cold regions is important for understanding the Earth＇s surface system, but such studies are rare. In this study, we detected the spatial-temporal variations in near-surface soil freeze-thaw cycles in the source region of the Yellow River（SRYR） during the period 2002–2011 based on data from the Advanced Microwave Scanning Radiometer for the Earth Observing System（AMSR-E）. Moreover, the trends of onset dates and durations of the soil freeze-thaw cycles under different stages were also analyzed. Results showed that the thresholds of daytime and nighttime brightness temperatures of the freeze-thaw algorithm for the SRYR were 257.59 and 261.28 K, respectively. At the spatial scale, the daily frozen surface（DFS） area and the daily surface freeze-thaw cycle surface（DFTS） area decreased by 0.08% and 0.25%, respectively, and the daily thawed surface（DTS） area increased by 0.36%. At the temporal scale, the dates of the onset of thawing and complete thawing advanced by 3.10（±1.4） and 2.46（±1.4） days, respectively; and the dates of the onset of freezing and complete freezing were delayed by 0.9（±1.4） and 1.6（±1.1） days, respectively. The duration of thawing increased by 0.72（±0.21） day/a and the duration of freezing decreased by 0.52（±0.26） day/a. In conclusion, increases in the annual minimum temperature and winter air temperature are the main factors for the advanced thawing and delayed freezing and for the increase in the duration of thawing and the decrease in the duration of freezing in the SRYR.

TP-PROFILE: Monitoring the Thermodynamic Structure of the Troposphere over the Third Pole

Ground-based microwave radiometers(MWRs)operating in the K-and V-bands(20–60 GHz)can help us obtain temperature and humidity profiles in the troposphere.Aside from some soundings from local meteorological observatories,the tropospheric atmosphere over the Tibetan Plateau(TP)has never been continuously observed.As part of the Chinese Second Tibetan Plateau Scientific Expedition and Research Program(STEP),the Tibetan Plateau Atmospheric Profile(TPPROFILE)project aims to construct a comprehensive MWR troposphere observation network to study the synoptic processes and environmental changes on the TP.This initiative has collected three years of data from the MWR network.This paper introduces the data information,the data quality,and data downloading.Some applications of the data obtained from these MWRs were also demonstrated.Our comparisons of MWR against the nearest radiosonde observation demonstrate that the TP-PROFILE MWR system is adequate for monitoring the thermal and moisture variability of the troposphere over the TP.The continuous temperature and moisture profiles derived from the MWR data provide a unique perspective on the evolution of the thermodynamic structure associated with the heating of the TP.The TP-PROFILE project reveals that the low-temporal resolution instruments are prone to large uncertainties in their vapor estimation in the mountain valleys on the TP.

An assessment of arctic sea ice concentration retrieval based on “HY-2” scanning radiometer data using field observations during CHINARE-2012 and other satellite instruments

A retrieval algorithm of arctic sea ice concentration （SIC） based on the brightness temperature data of “HY-2” scanning microwave radiometer has been constructed. The tie points of the brightness temperature were selected based on the statistical analysis of a polarization gradient ratio and a spectral gradient ratio over open water （OW）, first-year ice （FYI）, and multiyear ice （MYI） in arctic. The thresholds from two weather filters were used to reduce atmospheric effects over the open ocean. SIC retrievals from the “HY-2” radiom-eter data for idealized OW, FYI, and MYI agreed well with theoretical values. The 2012 annual SIC was calcu-lated and compared with two reference operational products from the National Snow and Ice Data Center （NSIDC） and the University of Bremen. The total ice-covered area yielded by the “HY-2” SIC was consistent with the results from the reference products. The assessment of SIC with the aerial photography from the fifth Chinese national arctic research expedition （CHINARE） and six synthetic aperture radar （SAR） images from the National Ice Service was carried out. The “HY-2” SIC product was 16% higher than the values de-rived from the aerial photography in the central arctic. The root-mean-square （RMS） values of SIC between “HY-2” and SAR were comparable with those between the reference products and SAR, varying from 8.57% to 12.34%. The “HY-2” SIC is a promising product that can be used for operational services.

A new algorithm for sea-surface wind-speed retrieval based on the L-band radiometer onboard Aquarius

Aquarius is the second satellite mission to focus on the remote sensing of sea-surface salinity from space and it has mapped global sea-surface salinity for nearly 3 years since its launch in 2011. However,benefiting from the high atmospheric transparency and moderate sensitivity to wind speed of the L-band brightness temperature(TB),the Aquarius L-band radiometer can actually provide a new technique for the remote sensing of wind speed. In this article,the sea-surface wind speeds derived from TBs measured by Aquarius' L-band radiometer are presented,the algorithm for which is developed and validated using multisource wind speed data,including Wind Sat microwave radiometer and National Data Buoy Center buoy data,and the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory wind field product. The error analysis indicates that the performance of retrieval algorithm is good. The RMSE of the Aquarius wind-speed algorithm is about 1 and 1.5 m/s for global oceans and areas of tropical hurricanes,respectively. Consequently,the applicability of using the Aquarius L-band radiometer as a near all-weather wind-speed measuring method is verified.