Comparison between Infrared and Microwave Radiometers for Retrieving Sea Surface Temperature

The basic principles of sea surface temperature （SST） remote sensing using infrared and microwave radiometers are introduced, and the differences between two sensors for retrieving sea surface temperature are investigated. The ground resolution, atmospheric effect, sea surface wind, skin depth and so on have important influence on precision of sea surface temperature retrieved by two sensors. The better understanding of the advantage and disadvantage of sea surface temperature detected by infrared and microwave radiometers would help us to imply SST remote sensing data more effectively and correctly.

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.

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.

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.

Application of Spectral Angle Mapper Classification to Discriminate Hydrothermal Alteration in Southwest Birjand, Iran, Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Image Processing

The purpose of this study is to evaluate the Spectral Angle Mapper （SAM） classification method for determining the optimum threshold （maximum spectral angle） to unveil the hydrothermal mineral assemblages related to mineral deposits. The study area indicates good potential for Cu-Au porphyry, epithermal gold deposits and hydrothermal alteration well developed in arid and semiarid climates, which makes this region significant for Advanced Spaceborne Thermal Emission and Reflection Radiometer （ASTER） image processing analysis. Given that achieving an acceptable mineral mapping requires knowing the alteration patterns, petrochemistry and petrogenesis of the igneous rocks while considering the effect of weathering, overprinting of supergene alteration, overprinting of hypogene alteration and host rock spectral mixing, SAM classification was implemented for argillic, sericitic, propylitic, alunitization, silicification and iron oxide zones of six previously known mineral deposits： Maherabad, a Cu-Au porphyry system; Sheikhabad, an upper part of Cu-Au porphyry system; Khoonik, an Intrusion related Au system; Barmazid, a low sulfidation epithermal system; Khopik, a Cu-Au porphyry system; and Hanish, an epithermal Au system. Thus, the investigation showed that although the whole alteration zones are affected by mixing, it is also possible to produce a favorable hydrothermal mineral map by such complementary data as petrology, petrochemistry and alteration patterns.

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.

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.

Verification and recalibration of HY-2A microwave radiometer brightness temperature

HY-2A is the first one of the Chinese HY-2 ocean satellite series carrying a microwave radiometer(RM)to measure sea surface temperature,sea surface wind speed,atmospheric water vapor,cloud liquid water content,and rain rate.We verified the RM level 1B brightness temperature(T B)to retrieve environmental parameters.In the verification,TB that simulated using the ocean-atmosphere radiative transfer model(RTM)was used as a reference.The total bias and total standard deviation(SD)of the RM level 1B TB,with reference to the RTM simulation,ranged-20.6-4.38 K and 0.7-2.93 K,respectively.We found that both the total bias and the total SD depend on the frequency and polarization,although the values for ascending and descending passes are different.In addition,substantial seasonal variation of the bias was found at all channels.The verification results indicate the RM has some problems regarding calibration,e.g.,correction of antenna spillover and antenna physical emission,especially for the 18.7-GHz channel.Based on error analyses,a statistical recalibration algorithm was designed and recalibration was performed for the RM level 1B TB.Validation of the recalibrated TB indicated that the quality of the recalibrated RM level 1B TB was improved significantly.The bias of the recalibrated T B at all channels was reduced to<0.4 K,seasonal variation was almost eradicated,and SD was diminished(i.e.,the SD of the 18.7-GHz channel was reduced by more than 0.5K).

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%.

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.

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.

A new global gridded sea surface temperature product constructed from infrared and microwave radiometer data using the optimum interpolation method

A new 0.1° gridded daily sea surface temperature（SST） data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave（Wind Sat, AMSR-E, ASMR2 and HY-2 A RM）and two infrared（MODIS and AVHRR） radiometers（RMs） based on the optimum interpolation（OI） method. The effect of including HY-2 A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error（RMSE） of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52–0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.

Calibration chain design based on integrating sphere transfer radiometer for SI-traceable on-orbit spectral radiometric calibration and its uncertainty analysis

In order to satisfy the requirement of SI-traceable on-orbit absolute radiation calibration transfer with high accuracy for satellite remote sensors,a transfer chain consisting of a fiber coupling monochromator（FBM） and an integrating sphere transfer radiometer（ISTR） was designed in this paper.Depending on the Sun,this chain based on detectors provides precise spectral radiometric calibration and measurement to spectrometers in the reflective solar band（RSB） covering 300–2500 nm with a spectral bandwidth of 0.5–6 nm.It shortens the traditional chain based on lamp source and reduces the calibration uncertainty from 5% to 0.5% by using the cryogenic radiometer in space as a radiometric benchmark and trap detectors as secondary standard.This paper also gives a detailed uncertainty budget with reasonable distribution of each impact factor,including the weak spectral signal measurement with uncertainty of 0.28%.According to the peculiar design and comprehensive uncertainty analysis,it illustrates that the spectral radiance measurement uncertainty of the ISTR system can reach to 0.48%.The result satisfies the requirements of SI-traceable on-orbit calibration and has wider significance for expanding the application of the remote sensing data with high-quality.

Sensitivity Investigation and Optimization for Solar Irradiance Absolute Radiometer

Since the calibration accuracy decreases with the reduction of irradiance power,the nonlinearity of sensitivity is experimentally investigated and corrected in order to improve the precision of calibration for Solar Irradiance Absolute Radiometer( SIAR). The optimization method is proposed based on the interpolation approximation principle. The real-time correction sensitivities are repeatedly measured at each radiant power.The relative system error of sensitivity nonlinearity is 2.2%. The impact of sensitivity nonlinearity is analyzed.The radiant powers are measured by the optimization method and the traditional method. The comparison experiment results illustrate that the optimization method improves the measure accuracy to 0. 1%. The sensitivity nonlinearity is compensated by the real-time correction. Thus,the optimization method significantly improves the calibration precision of ground-based comparison experiment. The investigation of sensitivity nonlinearity also provides the theoretical and experimental basis for optimizing the on-orbit calibration precision of Total Solar Irradiance Monitor( TSIM).

TWO NEW TYPES OF MICROWAVE RADIOMETER: A COMPUTER GAIN COMPENSATIVE DESIGN AND A REAL-TIME CALIBRATED DESIGN

Long term stability is the main factor that influences the minimum detectable signal of microwave radiometers. Two new types of microwave radiometer were studied: a computer gain compensative microwave radiometer and a real-time calibrated microwave radiometer. The long term stability of both designs was optimal because they were insensitive to system gain fluctuations. The continuous calibrated microwave radiometer was also insensitive to system noise fluctuations. The minimum detectable signals were 0.13 and 0.19K respectively under an integration time of 0.6s.

Retrieval of Tropospheric CO Profiles Using Correlation Radiometer:I.Retrieval Experiments for a Clear Atmosphere

This paper discusses the retrieval scheme associated with the gas correlated radiometer MOPITT which will be on board of EOS-AM1 to measure the global vertical profiles of carbon monoxide. The vertical resolution and retrieval errors caused by errors in the temperature profiles and in the surface temperature have been assessed. The main results are: a. Assuming the noise equivalent radiance (NER) of 1.8 × 105 W m-2 sr-1, the surface temperature can be deduced from the wide band signals with uncertainty less than 1 K, and the atmospheric term of the modulated signal can be deduced with errors almost equal to the NER which does not significantly increase errors in the retrieved CO profiles. b. With typical uncertainty in temperature profiles, errors in the retrieved profiles at latitudes lower than 70? are generally less than 20% with the first guess of 100 ppbv. (If a better first guess was used, the errors may decrease). c. By incorporating the total column CO amount derived from the reflected solar radiation in 2.3 Μm spectral region into the retrieval, the accuracy of the retrieved CO profile below 6 km may be greatly improved. d. In the retrieval experiment with 10 CO profiles representing the typical CO profiles, the r.m.s. relative/ absolute errors of the retrieved CO profiles are about 10% / 15-20 ppbv.