The NOAA-21 ATMS, launched in November 2022, collected two-dimensional lunar scan data on March 10, 2023, during its commissioning phase at a Moon phase angle of 34°. The raw data were calibrated using MiCalPS, a microwave calibration and geolocation tool developed at the University of Maryland. Analysis showed that NOAA-21’s lunar antenna gain is generally lower than NOAA-20’s due to sampling rate differences. After correcting for beam pointing errors, disk-averaged lunar brightness temperatures (TDISKB,Moon) were derived for 23–183 GHz. These were compared to NOAA-20 data at 0° phase angle and predictions from the microwave lunar radiative transfer model (ML-RTM). The observed model differences were: −3.3 K (K band), 0.01 K (V), 2.0 K (W), −2.3 K (low-G), and 1.6 K (high-G), consistent with predicted phase delay trends. Further observations at varying Moon phases are recommended to enhance MLRTM validation.

Space-borne microwave sounding instruments have become vital data sources for weather prediction and climate change studies. Among the various radiometer configurations, the total power microwave radiometer is particularly appealing for current and future operational satellites due to its superior sensitivity and simple design. However, its performance is vulnerable to degradation caused by receiver gain fluctuations, electronic 1/f noise, and other time varying receiver characteristics. For Numerical Weather Prediction (NWP) users, 1/f noise introduces inter-channel correlations, complicating the assimilation of affected observations and reducing their accuracy. Addressing this noise issue in ground data processing system is essential to enhance the utility of microwave sounding data. This paper focuses on the characterization and mitigation of noise in current and future microwave sounding instruments, with particular emphasis on the impact of 1/f noise. Various methods are applied to quantitatively characterize noise features in both frequency and time domains. Additionally, the influence of calibration parameters on 1/f noise are analyzed. Based on these findings, we propose a mitigation algorithm for reducing noise during the on-orbit calibration of microwave sounding instruments, aiming to improve the quality of retrieved data for operational use.

The Advanced Technology Microwave Sounder (ATMS) sensor data records (SDRs) product are assimilated for weather forecasts and used to derive environment data records (EDRs) products. Meanwhile, ATMS imagery, derived from SDR product, offers snapshots of weather events, like the warm core of a hurricane. However, its coarse resolution and angular dependence have long been a challenge for improving image visualization. Given these challenges, we have proposed a method which combined limb-correction algorithm and AI resolution enhancement to improve ATMS imagery visualization for bands 16, 18 and 19 [1]. This study further optimized the method and aimed to apply it to most of ATMS bands.

CubeSats with miniaturized microwave radiometers are now demonstrating the potential to provide science-quality weather measurements. For example, the Micro-Sized Microwave Atmospheric Satellite-2A (MicroMAS-2A) and Temporal Experiment for Storms and Tropical Systems–Demonstration (TEMPEST-D) CubeSats are both launched in 2018 and have demonstrated microwave atmospheric sounder data from orbit. The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a follow-on constellation of six 3U CubeSats based on the MicroMAS-2 design that is scheduled for launch no sooner than 2021. The TROPICS sensors use internal noise diodes (NDs) for calibration. Although the NDs on TROPICS are similar to technology flown on GMI, they have not been tested on-orbit at TROPICS frequencies. In order to track and correct ND drift, we develop a novel method of calibration for CubeSat constellations, such as TROPICS, by incorporating periodic solar and lunar intrusions as an additional source of information to counter ND drift. These lunar intrusions also occur for existing satellites hosting microwave radiometers in sun-synchronous polar orbits but are much more infrequent than for the TROPICS constellation’s scanning payload. In this work, we develop a solar/lunar calibration correction algorithm and test it using advanced technology microwave sounder (ATMS) lunar intrusion data. The mean bias and standard deviation between the solar/lunar calibration correction algorithm and actual ATMS data fall within the expected ATMS error budget of 0.6–3.9 K, validating our model.

Passive microwave sounders provide the highest-impact observations ingested by major numerical weather prediction (NWP) forecast models. The Advanced Technology Microwave Sounder (ATMS), built by Northrop Grumman, Azusa, CA, USA, is the latest operational microwave sounder series being launched by the United States to provide both temperature and water vapor soundings of the atmosphere. The first ATMS was launched on the Suomi National Polar-orbiting Partnership (SNPP) satellite in 2011. This article focuses on the details of the on-orbit performance characterization of the second ATMS, which launched on November 18, 2017, on the Joint Polar Satellite System-1 (JPSS-1) satellite. After successful commissioning, JPSS-1 was renamed National Oceanic and Atmospheric Administration (NOAA)-20 (N-20). We present performance characterizations from prelaunch and postlaunch tests, including the thermal vacuum (TVAC) campaign, and postlaunch activities that contribute to the radiance data products. Significant improvements were found for reflector emissivity,$1/f$noise performance, antenna beam efficiency, interchannel noise correlation, and scan drive bearing design. New geolocation and pointing algorithms were evaluated. The N-20 ATMS has the same channel set, polarizations, scan geometry, and calibration approach as the SNPP ATMS. The N-20 ATMS meets all performance requirements with margin.

The Advanced Technology Microwave Sounder (ATMS) is a passive microwave radiometer for the current generation of polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA). The first two ATMS instruments are manifested onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. Several critical changes have been made to ATMS operational calibration algorithm since March 2017. The calibration processing has been revised from a Rayleigh–Jeans approximated algorithm to a full radiance algorithm in order to reduce the error introduced by the approximation over cold radiances in the higher frequency channels. In addition, based on the lessons learned from S-NPP and NOAA-20 postlaunch calibration/validation tests, some major improvements have been made in the updated operational algorithm. These include reflector emission and antenna pattern corrections. Details of the radiance-based ATMS on-orbit calibration are documented in this report, and results of prelaunch calibration error budget analysis and postlaunch calibration accuracy evaluation are also presented for reference.

The noise equivalent delta temperature (NEDT) determines the radiometric resolution of a radiometer. Determining NEDT is indispensable for assessing the in-orbit radiometer performance and quantifying uncertainty propagation from radiance to climate data records. Agencies of EUMETSAT, UK MetOffice, and National Oceanic and Atmospheric Administration (NOAA) have developed their own algorithms for calculating and monitoring NEDT of in-orbit microwave radiometers. These algorithms are an essential means for monitoring NEDT and hardware health. While remarkable accomplishments have been made, there appears to be room for improvement. The investigation is needed for the NEDT underestimate found at channels like G-band that has pronounced$1/f$noise. Also, it is necessary to explain the inconsistency in calculated NEDTs of different algorithms. We have reviewed the theoretical basis for determining NEDT and developed an improved algorithm of clear physics and mathematics. We have developed methods for handling error sources that can result in either negative or positive biases with an overall underestimate of NEDT. We have done comparison and validation with the prelaunch thermal vacuum chamber (TVAC) test, in-orbit data, and simulation. The new algorithm significantly improves the estimate of NEDT, including the G-band and advances the understanding of algorithm structures and physical foundations. It can accurately monitor in-orbit NEDT and facilitate quantifying the associated uncertainty propagation through science products.

One of the data fusion issues for observations from multiple space-borne microwave sensors is the non-uniform spatial resolution. Although the Backus-Gilbert Inversion (BGI) algorithm has long been used for the Advanced Technology Microwave Sounder (ATMS) antenna pattern matching, previous studies showed that it has difficulty in accurate remapping from the coarser to the finer observations. Since BGI tends to enhance the data’s high spatial frequency components including both information and noise, it is a challenge to increase the spatial resolution while maintaining an acceptable noise level. This study unveils that the main cause of this issue is the insufficiency of the information provided by the conventional fixed reconstruction window. An adaptive window method is applied to provide sufficient information for the reconstruction at each scan position. In addition, a new noise tuning method is proposed to eliminate the scan-angle-dependent features in the noise caused by the sensor’s cross-track scanning manner. Results from simulations and NOAA ATMS data show that compared to the fixed window, the new method can significantly reduce the bias stemming from the resolution difference. The issue of the deterioration of the resolution enhancement capability near the scan edge in the fixed window method has been largely ameliorated. The overall Root-Mean-Square error is declined by 30%. The new noise tuning method is capable of suppressing the noise level at around 0.6 K over scan.

One of the limitations in using spaceborne, microwave radiometer data for atmospheric remote sensing is the coarse spatial resolution at low frequencies. Backus-Gilbert inversion algorithm is widely used for spatial resolution enhancement. However, the enhancement in resolution is achieved at the expense of the increase in noise. To suppress the noise in the reconstructed data, a new adaptive window method is proposed. Compared to the fixed window method adopted in previous studies, the new method is capable of reducing the noise to 1/10 of the noise induced by the fixed window method while keeping the similar degree of spatial resolution enhancement.

Reported here are disk-integrated Moon surface microwave brightness temperature ($Tb$) retrievals covering the frequency range of 23–183 GHz. Full Moon observations obtained from the advanced technology microwave sounder (ATMS) onboard the NOAA-20 satellite during a special spacecraft pitch–maneuver operation forms the basis of the retrievals. Instrument nonlinearity, Earth sidelobe contamination, cosmic background radiation, and reflector thermal emission corrections are applied to the observations to obtain accurate values of the Moon’s$Tb$at all frequencies. The measured full Moon$Tb$ranges from ~240 to 293 K with frequency increases from 23 to 183 GHz. A clear frequency trend is detected when the brightness temperature increases.

The Advanced Technology Microwave Sounder (ATMS) is a satellite-based microwave radiometer that provides temperature and humidity sounding observations from low Earth orbit. The instrument utilizes 22 channels that cover a frequency range of 23 to 183 GHz. The first ATMS instrument was launched in 2011 on the Suomi National Polar-orbiting Partnership (S-NPP) satellite and the second ATMS was launched in 2017 on the Joint Polar Satellite System-1 (JPSS-1) satellite (now NOAA-20); both on-orbit ATMS instruments are currently operational. This paper will describe the pre-launch performance of the third ATMS instrument, designated for the JPSS-2 satellite, during ground testing and calibration.

For the on-orbit calibration of passive microwave radiometers, instrument non-linearity is a major error source, causing a scene-temperature-dependent error if not being properly corrected. non-linearity results from the intrinsic feature of the square-law detector and amplifiers used in total-power microwave radiometers, and can only be accurately characterized through the ground-based Thermal Vacuum Test (TVAC). The ground-based non-linearity characterization is then used in the calibration algorithm to attempt to remove this error source. Evaluation results for current operational microwave-sounding instruments show that the magnitude of the non-linearity error varies from channel to channel and from instrument to instrument, with maximum changes of several tenths of kelvins to several kelvins. While the different responses of the detector and amplifier may explain the non-linearity differences in different instruments, errors in TVAC tests could also increase the uncertainty in the non-linearity assessment. Therefore, accurate knowledge of error sources in the TVAC test and their corrections are important for a reliable and accurate non-linearity measurement. In this paper, major error sources in the TVAC test are studied and identified for the NOAA-20 Advanced Technology Microwave Sounder. Correction methods are developed by combining the pre-launch TVAC test and post-launch deep-space-scan test data sets. An on-orbit evaluation method is also proposed to validate the ground-measured instrument non-linearity.

NEDT is a critical metric for assessing the noise level and instrument performance of microwave radiometers. In the study, we have reviewed different algorithms of calculating NEDT including those of EUMESAT, UK Met Office, and NOAA. We found that these algorithms suffer from a number of issues resulting in an overall underestimate of NEDT. We develop an algorithm with solid physical and mathematical substance and apply it to ATMS. The algorithm provides unbiased estimate of NEDT and is validated against ground thermal vacuum chamber measurement and simulation.

For small and cubic microwave satellite on orbit calibration, there is no room for the bulky calibration targets that are normally used on larger satellites. Miniaturizing microwave radiometer instruments to fit on a Cube-Sat leads to the challenge of finding a vicarious calibration method that need not warm load. Radiation of the Moon is very stable in microwave spectrum, attribute to its stable geophysical property. The only factors that change the magnitude of lunar microwave radiation in satellite observations are its bulk temperature, which is determined by its phase angle and penetration depth of detection frequency. Therefore, there is potential to take the Moon as permanent reference target to carry out on-orbit absolute calibration for microwave CubeSat constellation, inter-satellite calibration, as well as assess the long-term calibration stability for each single instrument. In this study, microwave brightness temperature spectrum from 23 to 183 GHz was derived from well calibrated two-dimension lunar observations of NOAA-20 ATMS instrument. A two-dimension lunar microwave brightness temperature model was also established for future on-orbit calibration of small and cubic microwave radiometers.

The NOAA-20 satellite was successfully launched on 18 November 2017. It carries five key instruments including Advanced Technology Microwave Sounder (ATMS). On January 31, 2018, the NOAA-20 performed a pitch maneuver operation, during which the 2-Dimension lunar scan observations were also being collected. In this study, based on simulation for NOAA-20 orbit dynamics and lunar disk-integrated radiation flux, a physical model was being able to be established to evaluate the antenna beam pointing error in terms of Euler angles. The results were validated by comparing with those derived from coastline inflection point method. It shows that the Euler angles derived from these two different methods independently are very consistent.

The reanalysis data produced by numerical weather prediction (NWP) models and data assimilation have been widely used for radiometer calibration. They provide atmospheric profiles that are necessary for radiative transfer simulation against observation. However, there are biases and uncertainties in the reanalysis due to NWP model mechanism, parameterization, boundary conditions, and assimilation skills. As spaceborne radiometer data have been used in deriving reanalyses, reanalyses are not independent of these radiometers and should be used with caution when used as reference for radiometer calibration. In addition, these data often have coarse spatial (~100 km horizontally) and temporal resolution (~6 h). An independent data set with high resolution can be very useful to diagnose reanalyses and might improve calibration. The Global Precipitation Measurement (GPM) core observatory measures atmospheric water signatures with an onboard radar and radiometer. A GPM data set including atmospheric water vapor, cloud liquid water, and precipitation has been produced based on observational retrieval with high spatiotemporal resolution (~5 km horizontally and 250 m vertically). We have developed a scheme to ingest the high-resolution GPM profiles and perform rigorous simulation and calibration taking into account the radiometer spectral response function, footprint size variation, and antenna pattern. GPM data exhibit different water vapor profiles and weighting functions from reanalyses. It produces overall consistent results of calibration as reanalyses and outperforms them in some aspects. The GPM profiles and our scheme are very useful and will be routinely applied to monitor Advanced Technology Microwave Sounder inflight status.

For the quantitative applications of the Suomi National Polar-orbiting Partnership (SNPP) Advanced Technology Microwave Sounder (ATMS), the geolocation accuracy of its sensor data records must be quantified during its on-orbit operation. In this paper, a refined coastline inflection point method is used to evaluate the on-orbit geolocation accuracy of SNPP ATMS. It is disclosed that for SNPP ATMS, the static error term with scan-angle-dependent feature is a dominant part among all the geolocation error sources. A mathematical model is then developed to convert the in-track and cross-track geolocation errors to the beam pointing Euler angles defined in the spacecraft coordinate system, which can be further used to construct the correction matrix for on-orbit geolocation process. By using the correction matrix built in this paper, the geolocation error is obviously reduced both at nadir and at the edge of the scan. The total geolocation error at nadir before/after correction is 3.8/0.8 km at K-band, 5.6/0.8 km at Ka-band, 3.3/0.4 km at V-band, and 1.5/0.1 km at W-band. The geolocation bias at the edge of the scan line before/after correction is 4.6/1.3 km at K-band, 9.4/1.8 km at Ka-band, 4.4/2.4 km at V-band, and 3.2/0.8 km at W-band. After correction, the scan-angle-dependent feature in geolocation error is also largely reduced.

The second Advanced Technology Microwave Sounder (ATMS) recently launched November 2017 on the Joint Polar Satellite System-l satellite (JPSS-l), now re-named NOAA-20. It joins the first ATMS flight unit aboard the Suomi NPP (S-NPP) satellite, as well as older sounders-the Advanced Microwave Sounding Units A & B (AMSU-A/B) and Microwave Humidity Sounder (MHS)-on polar-orbiting operational weather satellites. Together, these sounders provide critical all-weather temperature and humidity profile information for Numerical Weather Prediction (NWP) models. This paper presents results from a number of special post-launch tests used to characterize the instrument and provide unique calibration information. These special tests-long stares, alternate techniques for lunar intrusion mitigation and geolocation, spacecraft maneuvers, special scan modes, comparisons with NWP models-require nonstandard modes of operation or data analysis, and can only be conducted during commissioning, prior to the start of regular forecast observations.

Accurate global observations from space are critical for global climate change study. However, atmospheric temperature trend derived from spaceborne microwave instruments remains a subject of debate, due mainly to the uncertainty in characterizing the long-term drift of instrument calibration. Thus, a highly stable target with a well-known microwave radiation is required to evaluate the long-term calibration stability. This paper develops a new model to simulate the lunar emission at microwave frequencies, and the model is then used for monitoring the stability of the Advanced Technology Microwave Sounder (ATMS) onboard Suomi NPP satellite. It is shown that the ATMS cold space view of lunar radiation agrees well with the model simulation during the past five years and this instrument is capable of serving the reference instrument for atmospheric temperature trending studies, and connecting the previous generation of microwave sounders from NOAA-15 to the future Joint Polar Satellite System Microwave Sounder onboard NOAA-20 satellite.

Accurate global observations from space are a critical part of the needed knowledge base for global climate change study. However, atmospheric temperature trends derived from space-borne microwave instruments remains a subject of debate, mainly due to uncertainty arise from calibration error and long-term drift and degradation of instrument. In this study, a new method was developed for assessing microwave radiometer long-term on-orbit calibration stability, by taking the lunar observation as a reference. This method was applied to 5 years of NPP ATMS lunar observations, results show that ATMS calibration accuracy and stability can be well assessed by using the Moon as a reference target.

Spaceborne radiometers have provided critical information of atmospheric water vapor and precipitation through sounding channels around 183 GHz. Understanding the performance and characteristics of these channels is important for hardware assessment, refining radiative transfer model, and improving science product. Whereas atmospheric water profiles from ancillary operational or reanalysis data are widely used for RTM simulation of 183 GHz, they cannot well represent the real atmospheric conditions due to the intrinsic nature of water/precipitation heterogeneity and variability. In addition, these ancillary data are with limited spatial (~100 km) and temporal (several hours) resolution. As a result, significant errors propagate into simulation. The combined radar and radiometer of GPM core observatory measure both vertical profile and total column radiance and therefore can well retrieve water profiles with fine spatial resolution and instaneous temporal resolution. We have developed a scheme using the combined retrieval product for simulating ATMS radiance. A rigorous simulation is performed with considering the field of view matchup, variation of beam size along cross-track scanning, radiometer spectral response, and antenna pattern convolution. It is shown that the simulated brightness temperature agree well with observation. The scheme can combine DPR/GMI product and different radiometers for instrument assessment and model refinement.

Recently, the advanced coastline inflection point method (CIPSD) was developed to retrieve the instrument boresight pointing error of Suomi National Polar-orbiting Partnership (SNPP) Advanced Technology Microwave Sounder (ATMS). Because of the use of mathematical model and separate-domain technique, this algorithm can retrieve the boresight pointing error in terms of Euler angles efficiently. But the retrieval uncertainty of yaw is larger than that of the other two angles due to the limitation in this method. This paper thoroughly investigates the phenomenon of asynchrony between the serial of space view counts and that of the simulated antenna response in lunar intrusion (LI) events. Sensitivity study shows that this asynchrony is mainly caused by the boresight pointing Euler angle yaw. A new retrieval algorithm for yaw is developed based on this relation. The yaw derived from the Lunar observations of space view 4 (SPV4) from 2011 to 2016 is 0.028° at K band, -0.012° at Ka band, -0.168° at V band, -0.005° at W band, and -0.054 at G band. This algorithm can serve as a supplement to CIPSD. The combined retrieval results, the roll and pitch from CIPSD and the yaw from lunar observations, are used to correct the ATMS SPV vectors when simulating the antenna response. The comparison between the corrected antenna response and the observed cold counts of ATMS channel 7 SPV4 at the LI event occurring on Jan 6-8, 2017 shows that, after correction, the simulated antenna response synchronizes very well with the actual observations.

A new constellation comprising of eight microwave small satellites is proposed in this study. This constellation is capable of covering the entire globe every two hours. With six more satellites added and properly arranged, a constellation is able to provide hourly observations of fast-evolving severe weather systems like hurricanes. Compared to current polar-orbiting satellite which normally carries one passive microwave instrument onboard, a small satellite constellation is more cost-effective, requires a shorter development cycle and has smaller failure impact. NOAA Center for Satellite Applications and Research (STAR) has built a full radiance transformation system (ARTS) that is applicable for small satellite calibration, validation and data processing. Hourly NWP forecast fields for tropical storm Debby (2012) will be produced and used as inputs to Community Radiative Transfer Model (CRTM) to simulate the designed microwave small satellite observations to demonstrate their values for monitoring and predicting hurricane and typhoon events.

The Earth-scene brightness temperature (TB) seen by satellite radiometers is generally cold over the ocean due to low emissivity, warm over land with high emissivity, and with a large dynamic range dependent on frequency and polarization. Calibration at either cold or warm end cannot fully characterize the calibration dependence on the full TB dynamic range. We have developed calibration methods using both warm and cold reference TB tie points and applied them to the Global Precipitation Measurement (GPM) mission particularly for the GPM Microwave Imager (GMI). The two-end method characterizes the GMI calibration dependence on TB and enables the development of TB-dependent intercalibration correction tables for GPM.

Accurate instrument mounting matrix information is significant for geolocation algorithm to reach a high on orbit geolocation accuracy. In this study, an integrated satellite-ground geolocation error model was proposed, based on which the instrument mounting matrix can be accurately rebuilt. This method has been successfully applied to SNPP ATMS on-orbit geolocation, results show that the geolocation error can be reduced by 34%.

Microwave Radiation Imager (MWRI) onboard the FengYun (FY)-3C satellite provides measurements of the Earth's atmosphere and surface at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with dual polarization. While FY MWRI data have been widely distributed to the user community, their geolocation accuracy has not been documented. In this paper, the coastline inflection method is used to estimate MWRI geolocation errors. Three coastal regions where MWRI brightness temperature exhibits a large contrast are selected for the geolocation analysis. A total of 720 MWRI data points are identified that cross the coastlines. The latitudes and longitudes at these data points are compared with the fine-resolution database of the Global Self-consistent, Hierarchical, High-resolution Shoreline (GSHHS). It is found that the mean geolocation errors in along- and cross-track directions are approximately 5-6 km at 89 GHz. This magnitude of errors is more than 30% of the field-of-view size at 89 GHz. Such a geolocation error must be corrected so that the MWRI data can be more useful for quantitative remote sensing. Thus, the mean geolocation errors are further utilized to adjust the satellite attitude angles (e.g., pitch, roll, and raw). After the attitude angle correction, the MWRI geolocation is very accurate at 89 GHz, and errors in other MWRI channels may be corrected through their co-registration relationships to the 89-GHz channel.

The cold calibration count from the Advanced Technology Microwave Sounder (ATMS) space view increases when the lunar radiation intrudes its antenna field of view (FOV). This increase is referred to as lunar contamination since the cold count is not matched with the specified brightness temperature of 2.73 K. For ATMS, it is found that the elapse time of lunar intrusion (LI) and the magnitude of the cold count increase are channel dependent. If the lunar-affected calibration counts are rejected in the processing, a data gap can be shown in brightness temperature at all channels. At ATMS channels 1 and 2, which have a large FOV, the LI can result in an increase of 40 counts in cold calibration. At higher frequency channels which have a smaller FOV size, the LI intensity is much stronger and can be as large as a few hundred counts. The LI becomes significant when its radiation appears in the ATMS antenna main beam. In the current ATMS operational calibration algorithm, the cold count anomaly is detected when the intensity of LI exceeds a certain threshold. The lunar radiation can be also corrected in the ATMS calibration. In doing so, a lunar radiation term is derived as a function of antenna gain, the solid angle of the Moon, and the brightness temperature of the Moon disk. This algorithm is applied in an ATMS calibration system developed at NOAA and shows a successful removal of all the lunar contamination on the earth-scene brightness temperature.

The Advanced Technology Microwave Sounder (ATMS) on board the Suomi National Polar-orbiting Partnership (NPP) satellite is a total power radiometer and scans across the track with a range of ±52.77° from nadir. It has 22 channels and measures the microwave radiation at either quasi-vertical or quasi-horizontal polarization from the Earth's atmosphere. The ATMS scanning reflector is made of beryllium coated with gold and can have an emission due to the surface roughness. During prelaunch phase, an estimate of the reflector emissivity was not explored. In this paper, a new methodology is developed to assess the antenna emission from the ATMS pitch-over observations. It is found that the antenna emission is significant and dominates the scan-angle-dependent features in the ATMS antenna temperatures. Retrieved emissivity from K- to G-bands ranges from 0.002 to 0.006. An error model was also developed to assess the impact of antenna emissivity to calibration accuracy of antenna temperature products. Simulation results show that the calibration error is scene temperature dependent and can be as large as 2.5 K for space view.

The Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (NPP) satellite is a total power radiometer and scans across the track within a range of ±52.77° from nadir. It has 22 channels and measures the microwave radiation at either quasi-vertical or quasi-horizontal polarization from the Earth's atmosphere. From the ATMS pitch-over deep space scan observations, it is found that the antenna reflector losses play an important role in calibration and dominates the scan angle dependent features in the ATMS antenna temperatures. Since the losses are small, they are difficult to measure by traditional means. However, they can be assessed directly from pitch over observations by using deep space radiation measured at different scan angle. This paper describes a physical model developed for the correction of reflector emissivity, which incorporates the angular dependent terms derived from the pitch-over maneuver data. Based on the pitch-maneuver data, the expected V/H polarization emissivity value is in the range of 0.002 to 0.0065. Considering the facts that ATMS is heritage of historical NOAA series microwave sounding instruments like MSU and AMSU, on which the reflector emissivity correction model can also be used to improve TDR/SDR data quality.

In recent years, drought occurs frequently in China. Soil moisture, as a key parameter in the drought monitoring, becomes especially concerned. The FY-3B/MWRI soil moisture product provides global observations of land surface soil moisture. This paper gives a basic introduction of FY-3B/MWRI soil moisture product including the retrieval method used. Then an example in the application for drought monitoring will be demonstrated and finally we will evaluate the utility of MWRI soil moisture for drought monitoring.1

The Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (NPP) satellite is a total power radiometer and scans across the track within a range of$\pm 52.77^{\circ}$from nadir. It has 22 channels and measures the microwave radiation at either quasi-vertical or quasi-horizontal polarization from the Earth's atmosphere. Without simultaneous measurements at both polarizations at the same frequency, the conversion from ATMS antenna temperature to sensor brightness temperature becomes nonunique if the antenna subsystem has a significant spillover from cross-polarization. In addition, the antenna temperature could be contributed from both the near- and far-field radiation through the sidelobes of the ATMS antenna subsystem. An analysis of the ATMS antenna gain measurements reveals that the efficiencies of both ATMS antenna sidelobes and cross-polarization are frequency dependent. From the ATMS pitchover maneuver data, it is found that the contributions of spacecraft radiation through the near-field sidelobes are significant and dominates the scan-angle-dependent features in the ATMS antenna temperatures. A theoretical model is developed for the conversion from antenna to sensor brightness temperatures, which incorporates the angular dependent terms derived from the pitchover maneuver data.

Land surface emissivity can be used for several purposes including land surface characterization and atmospheric retrieval over land. It is quite challengeable to simulate passive microwave radiances over land. This paper focuses on land surface emissivity retrieval and radiance simulation under snow-free conditions on a global scale for AMSR-E sensor configurations. A surface emission model (Qp) is coupled within Community Radiative Transfer Model (CRTM) which takes volumetric scattering of dense medium into consideration. The Qp model has been proved that it has higher accuracy and more suitable for the high-frequency and high-incidence AMSR-E data analysis. The results show that estimated radiances are comparable to passive microwave observations from satellite for different land surface vegetation types. The Root Mean Square Errors (RMSEs) are less than 20K and the mean errors are generally less than 10K.

Microwave Radiation Imager (MWRI) onboard the FengYun (FYJ-3A/B satellites observes the Earth atmosphere at 10.65, 18.7, 23.8, 36.5 and 89.0 GHz with each having dual polarization. Its calibration system is uniquely designed with a main reflector viewing both cold and hot calibration targets. Two quasi-optical reflectors are used to reflect the radiation from hot load and cold space to the main reflector. Soon after FY3b was successfully launched in November 2010, evaluation of on-orbit calibration accuracy of MWRI was carried out. In this paper, CRTM was used to simulate the MWRI observations over ocean, by using GDAS data as model inputs. "O-B" Results and "Double difference " results show that: 1). the on-orbit calibration status of MWRI is stable, 2). the brightness temperatures from MWRI observation are highly consistent with those derived from AMSR-E and model simulation.

The retrieval of land surface emissivity from satellite passive microwave measurements often requires the knowledge of various radiative components (e.g., atmospheric upwelling and downwelling radiation) contributed to the measurements. Under a cloud-free condition, atmospheric and surface radiative components can be derived from atmospheric temperature and water vapor, and surface temperature data. Thus, the quality of these auxiliary data sets directly affects the emissivity accuracy. From an emission-based radiative transfer equation, a set of relationships is derived to study the sensitivity of surface emissivity to the errors of brightness temperature, atmospheric transmittance, and surface temperature. As an example, the uncertainties in the Advanced Microwave Scanning Radiometer-Earth Observing System emissivity at 23 and 89 GHz may be much larger than the uncertainties of emissivity at lower frequencies due to the higher uncertainties in computing the water vapor absorption. The error in the land surface temperature is a main source of error in emissivity at the frequencies less than 19 GHz.

The Microwave Radiation Imager (MWRI) on board the FengYun-3A/B satellites observes the Earth atmosphere at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with each having dual polarization. Its calibration system is uniquely designed with a main reflector viewing both cold and hot calibration targets. Two quasi-optical reflectors are used to reflect the radiation from the hot load and cold space to the main reflector. In the MWRI calibration process, a radiation loss in the beam transmission path must be taken into account. The loss factor in the hot load transmission path is derived using the antenna pattern data measured on ground and satellite data observing over the Amazon forest where the scene temperature is steady and close to the hot load. The instrument nonlinearity factors at different channels are also evaluated over a wide range of brightness temperatures and compared with the results from the ground vacuum test. After a cross-calibration with Windsat data, atmospheric products are derived from MWRI brightness temperatures with the accuracy similar to those from the legacy sensors (e.g., the Special Sensor Microwave/Imager).

Snow depth (SD) is an important input parameter for snow cover hydrologic model and climate model. In China, the snow volume is affected by the plateau climate and different geographical situation, which shows specific rules and characteristics in space and time distribution. Consequently, it is very necessary to dynamically estimate the snow volume of China area. In this paper, we use passive microwave to estimate the snow depth in China, through the analysis on the characteristics of time, space and geographical environment of the snow zone in China, we added the impact of snow cover in pixel, high-frequency (89.0 GHz) on the accuracy of inversion and on the basis Chang's classical algorithm of inversion of snow water equivalent, considered that there were different responses to the microwave in different types of surface, improve the algorithm of inversion of snow water equivalent in China. The results show that new inversion algorithm can improve the precise of the inversion of snow depth in the area of China. However, the low spatial resolution of microwave, complex types of feature in the ground pixel and the changes of the snow status with time and space, which make it difficult to invert snow water equivalent, so need to further study.

In this paper, we present a simple but efficient algorithm to derive land surface temperature (LST). The major point of our algorithm is to build liner regress equations between brightness temperature of AMSR-E and LST product from MODIS. Each equation corresponds to a group of land surface cells, within which the emissivities are similar. We found that for a given land surface type and a given latitude range, land surface emissivities are comparatively steady within a period (one month for example). In this way, we can separate all of the AMSR-E brightness temperature and MODIS LST product data into groups by land surface type, latitude range and date range. In each group, the regress equation can be build. We used 2004 data to build the regress equations and validated those used 2004 and 2006 data. We found that: 1, in snow covered area the accuracy of retrieved LST is poor. 2, in desert, accuracy of retrieval LST is also poor. 3, in other most land cover, retrieved LST by AMSR-E fit well with the MODIS LST product.