Multichannel Microwave Radiometer Research Articles

Global evaluation of fast radiative transfer model coefficients for early meteorological satellite sensors

Abstract. RTTOV (the Radiative Transfer for TOVS code, where TOVS is the TIROS Operational Vertical Sounder) coefficients are evaluated using a large, independent dataset of 25 000 atmospheric model profiles as a robust test of the diverse 83 training profiles typically used. The study is carried out for nine historical satellite instruments: the InfraRed Interferometer Spectrometer D (IRIS-D), Satellite Infrared Spectrometer B (SIRS-B), Medium Resolution Infrared Radiometer (MRIR) and High Resolution Infrared Radiometer (HRIR) for the infrared part of the spectrum, and the Microwave Sounding Unit (MSU), Special Sensor Microwave Imager (SSM/I), Special Sensor Microwave – Humidity (SSM/T-2), Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager/Sounder (SSMI/S) for the microwave. Simulated channel brightness temperatures show similar statistics for both the independent and the 83-profile datasets, confirming that it is acceptable to validate the RTTOV coefficients with the same profiles used to generate the coefficients. Differences between the RTTOV and the line-by-line models are highest in water vapour channels, where mean values can reach up to 0.4 ± 0.2 K for the infrared and 0.04 ± 0.13 K for the microwave. Examination of the latitudinal dependence of the bias reveals different patterns of variability for similar channels on different instruments, such as the channel centred at 679 cm−1 on both IRIS-D and SIRS-B, showing the importance of the specification of the instrumental spectral response functions (ISRFs). Maximum differences of up to several kelvin are associated with extremely non-typical profiles, such as those in polar or very hot regions.

Radiance Simulations in Support of Climate Services

AbstractClimate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates how the development and the uptake of F(C)DR benefit from radiance simulations, using reanalyses and radiative transfer models. We identify three classes of applications, with examples for each application class. The first application is to validate assumptions during F(C)DR development. Hereto we show the value of applying advanced quality controls to geostationary European (Meteosat) images. We also show the value of a cloud mask to study the spatio‐temporal coherence of the impact of the Mount Pinatubo volcanic eruption between Advanced Very High Resolution Radiometer (AVHRR) and the High‐resolution Infrared Radiation Sounder (HIRS) data. The second application is to assess the coherence between reanalyses and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI‐1) flown on a Soviet satellite in 1979. We also present a first attempt to estimate the random uncertainties from this instrument. Finally, we investigate how advanced bias correction can help to improve the coherence between reanalysis and Nimbus‐3 Medium‐Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform F(C)DR users about particular quality aspects. We show how simulations can help to make a better‐informed use of the corresponding F(C)DR, taking as examples the Nimbus‐7 Scanning Multichannel Microwave Radiometer (SMMR), the Meteosat Second Generation (MSG) imager, and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Water Vapor Profiler (SSM/T‐2).

Spectral Linear Mixing Model application in passive microwave data to analyze Antarctic surface melting dynamics (1978-2018).

Several studies have utilized passive microwave imagery for monitoring snowmelt in Antarctica. However, due to the low spatial resolution of these images (25 km), the quantification of snowmelt is not precise. To enhance the accuracy of these estimations, this study proposed a subpixel analysis approach based on a Spectral Linear Mixing Model. This approach was applied to images obtained from channels 18/19 GHz and 37 GHz, both horizontally and vertically polarized, acquired from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSM/IS) instruments, spanning the period 1978-2018. The spatiotemporal analysis of the estimated snowmelt fraction images indicated that the most persistent and intensive melt was observed on the Antarctic Peninsula, particularly on the Larsen, Wilkins, George VI, and Wordie ice shelves. The melting period in the Antarctic Peninsula began in late October, with a peak in early January, and ended in late March. Other regions with persistent and intensive snowmelt were Mary Bird Land and Wilkes Land, followed by Dronning Maud Land, Amery Ice Shelf, Filchner-Ronne Ice Shelf, and Ross Ice Shelf. These snowmelt data are valuable for modeling the impacts of snowmelt on glacial systems, local coastal environments, and sea-level rise.

Characteristics Analysis of the Multi-Channel Ground-Based Microwave Radiometer Observations during Various Weather Conditions

Ground-based multi-channel microwave radiometers (MWRs) can continuously detect atmospheric profiles in the tropospheric atmosphere. This makes MWR an ideal tool to supplement radiosonde and satellite observations in monitoring the thermodynamic evolution of the atmosphere and improving numerical weather prediction (NWP) through data assimilation. The analysis of product characteristics of MWR is the basis for applying its data to real-time monitoring and assimilation. In this paper, observations from the latest generation of ground-based multi-channel MWR RPG-HATPRO-G5 installed in Shanghai, China, are compared with the radiosonde observations (RAOB) observed in the same location. The detection performance, characteristics of various channels, and the accuracy of the retrieval profile products of the MWR RPG are comprehensively evaluated during various weather conditions. The results show that the brightness temperatures (BTs) observed by the ground-based MWR RPG during precipitation conditions were high, which affected its detection performance. The bias and the standard deviation (SD) between the BT observed by MWR RPG and the simulated BT during clear and cloudy sky conditions were slight and large, respectively, and the coefficient of determination (R2) was high and low, respectively. However, when the cloud liquid water (CLW) information was added when simulating BT, the bias and the SD of the observed BT and the simulated BT during cloudy days were reduced and the R2 value improved, which indicated that CLW information should be taken into account when simulating BT during cloudy conditions. The temperature profiles of the MWR retrieval had the same accuracy of RMSEs (root-mean-square error) with heights during both clear-sky and cloudy sky conditions, where the RMSEs were below 2 K when the heights were below 4 km. In addition, the MWR RPG has the potential ability to retrieve the temperature inversion in the boundary layer, which has important application value for fog and air pollution monitoring.

A 41-year (1979–2019) passive-microwave-derived lake ice phenology data record of the Northern Hemisphere

Abstract. Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude regions. The annual freeze-up and breakup dates as well as the duration of ice cover (i.e., lake ice phenology) are sensitive to the weather and climate; hence, they can be used as an indicator of climate variability and change. In addition to optical, active microwave, and raw passive microwave data that can provide daily observations, the Calibrated Enhanced-Resolution Brightness Temperature (CETB) dataset available from the National Snow and Ice Data Center (NSIDC) provides an alternate source of passive microwave brightness temperature (TB) measurements for the determination of lake ice phenology on a 3.125 km grid. This study used Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSMIS) data from the CETB dataset to extract the ice phenology for 56 lakes across the Northern Hemisphere from 1979 to 2019. According to the differences in TB between lake ice and open water, a threshold algorithm based on the moving t test method was applied to determine the lake ice status for grids located at least 6.25 km away from the lake shore, and the ice phenology dates for each lake were then extracted. When ice phenology could be extracted from more than one satellite over overlapping periods, results from the satellite offering the largest number of observations were prioritized. The lake ice phenology results showed strong agreement with an existing product derived from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) data (2002 to 2015), with mean absolute errors of ice dates ranging from 2 to 4 d. Compared with near-shore in situ observations, the lake ice results, while different in terms of spatial coverage, still showed overall consistency. The produced lake ice record also displayed significant consistency when compared to a historical record of annual maximum ice cover of the Laurentian Great Lakes of North America. From 1979 to 2019, the average complete freezing duration and ice cover duration for lakes forming a complete ice cover on an annual basis were 153 and 161 d, respectively. The lake ice phenology dataset – a new climate data record (CDR) – will provide valuable information to the user community about the changing ice cover of lakes over the last 4 decades. The dataset is available at https://doi.org/10.1594/PANGAEA.937904 (Cai et al., 2021).

Observing the Microwave Radiation of the Sun during a Solar Eclipse with a Ground-Based Multichannel Microwave Radiometer

A ground-based multichannel microwave radiometer (GMR) is commonly used to observe the atmospheric radiation brightness temperature (TB) in order to retrieve atmospheric temperature and humidity profiles. At present, GMRs are used only in meteorology and climate monitoring. However, theoretical analysis showed that GMRs can be also used to observe the solar radiation. Therefore, we tried to improve the antenna servo control system of a GMR so that it could track and observe the sun, and the results showed that the GMR could respond to the variation of solar radiation. A further question was: can a GMR observe the variation of the sun during a solar eclipse? Fortunately, two solar eclipse events were captured by the GMR on 26 December 2019 and 21 June 2020 in Xi’an, China. We used the upgraded GMR to observe the variation of solar radiation during the two solar eclipses. The observation and analysis results showed that (1) the GMR could accurately track the sun and respond to the variation of solar radiation during the solar eclipse. We analyzed the variation features of the solar radiation by combining the solar phase during the two solar eclipses. (2) We found that the GMR could respond to the variation of the solar radiation arising from the Earth–Sun distance, and we further propose a novel method to measure the eccentricity of earth orbit with the GMR by using the passive solar observation. The results show that the eccentricity measured was 0.0169, which agreed quite well with the value of 0.0167 in the literature. (3) The average variation percentages of both the Earth–Sun distance and the intensity of the incident solar radiation throughout the year were estimated to be 3.44% and 6.6%, respectively. According to these results, the solar observation techniques can broaden the field usage of GMR.

Measurement of Solar Absolute Brightness Temperature Using a Ground-Based Multichannel Microwave Radiometer

Ground-based multichannel microwave radiometers (GMRs) can observe the atmospheric microwave radiation brightness temperature at K-bands and V-bands and provide atmospheric temperature and humidity profiles with a relatively high temporal resolution. Currently, microwave radiometers are operated in many countries to observe the atmospheric temperature and humidity profiles. However, a theoretical analysis showed that a radiometer can be used to observe solar radiation. In this work, we improved the control algorithm and software of the antenna servo control system of the GMR so that it could track and observe the sun and we use this upgraded GMR to observe solar microwave radiation. During the observation, the GMR accurately tracked the sun and responded to the variation in solar radiation. Furthermore, we studied the feasibility for application of the GMR to measure the absolute brightness temperature (TB) of the sun. The results from the solar observation data at 22.235, 26.235, and 30.000 GHz showed that the GMR could accurately measure the TB of the sun. The derived solar TB measurements were 9950 ± 334, 10,351 ± 370, and 9217 ± 375 K at three frequencies. In a comparison with previous studies, we obtained average percentage deviations of 9.1%, 5.3%, and 4.5% at 22.235, 26.235, and 30.0 GHz, respectively. The results demonstrated that the TB of the sun retrieved from the GMR agreed well with the previous results in the literature. In addition, we also found that the GMR responded to the variation in sunspots and a positive relationship existed between the solar TB and the sunspot number. According to these results, it was demonstrated that the solar observation technique can broaden the field usage of GMR.

Estimation of Arctic Basin-Scale Sea Ice Thickness From Satellite Passive Microwave Measurements

Retrievals of sea ice thickness from passive microwave measurements have been limited to thin ice because microwaves penetrate at most the upper 50 cm of sea ice. To overcome such a limitation, a method of retrieving Arctic basin-scale ice thickness is developed. The physical background of this method is that the scattering optical thickness at microwave frequencies within the freeboard layer is linearly proportional to the physical thickness of the ice freeboard. In this study, we relate the optical thickness estimated from the Advanced Microwave Scanning Radiometer 2 (AMSR2) with ice freeboard estimated from the CryoSat-2 (CS2) by employing a piecewise linear fit. The results show a strong linear relationship between the AMSR2-estimated and CS2-measured ice freeboards with a correlation coefficient of 0.85 and bias and RMSE of 0.0001 and 0.04 m, respectively; this evidence suggests that the method can provide Arctic basin-scale ice freeboard with a comparable accuracy level of CS2. The method is also applied to estimate ice freeboard for the periods of the Scanning Multichannel Microwave Radiometer (SMMR) (1978-1987) and AMSR-E (2002-2011). It is shown that the area-averaged ice freeboard has decreased significantly with the linear trends of 1.5 cm/decade. In addition, there seems to be a change of ice freeboard distributions over the Arctic. Furthermore, the algorithm is extended to the ice thickness retrieval by using the hydrostatic balance equation, showing that operational basin-scale ice thickness retrieval will be possible from satellite passive microwave measurements if a realistic snow depth on sea ice is employed.

Feasibility for Operationally Monitoring Ground-Based Multichannel Microwave Radiometer by Using Solar Observations

Ground-based multichannel microwave radiometers can observe the atmospheric microwave radiation brightness temperature and continuously provide temperature and humidity profiles of the troposphere. At present, microwave radiometers are operated in many countries for monitoring climate and meteorological phenomena, and there have been many microwave radiometers of this kind presently implemented in China, but they lack a unified monitor for their operational condition, which is necessary if they are taken as a network. For this reason, a real-time monitoring receiving system of radiometer is fundamental and important. In order to check the system stability and the antenna performances, this paper studied the feasibility of applying the solar signals to monitor the antenna alignment, antenna pattern and stability of a radiometer system in working for operational field applications. An experiment was performed and the results from the analysis of the annual variation features with long-term solar observation data at four frequencies, 22.235, 26.235, 30.000 and 51.250 GHz, show that an antenna pattern retrieved from solar observations agrees well with that retrieved from the traditional method. In addition, a daily analysis of the solar signals in online data of a radiometer can be used for monitoring the alignment of the antenna and the stability of the ground-based microwave radiometer system.

Statistical modeling of sea ice concentration in the northwest region of the Antarctic Peninsula

Sea ice is one of the main components of the cryosphere that modifies the exchange of heat and moisture between the ocean and atmosphere, regulating the global climate. In this sense, it is important to identify the concentration of sea ice in different regions of Antarctica in order to measure the impact of environmental changes on the region's ecosystem. The objective of this study was to evaluate the performance of the multiple linear regression and Box-Jenkins methods for predicting the concentration of sea ice along the northwest coast of the Antarctic Peninsula. Sea ice concentration data from May to November for the period 1979-2018 were extracted from passive remote sensors including a scanning multichannel microwave radiometer, special sensor microwave imager, and special sensor microwave imager/sounder. Meteorological variables from the atmospheric reanalysis model ERA5 of the European Center for Medium-Range Weather Forecasts were used as predictor variables, and the leave-one-out cross-validation technique was used to calibrate and validate the models. It was found that both statistical models have similar performance when analyzing residual analysis results, root mean square error of cross-validation, and final accuracy and residual standard deviation, these responses being related to the regionalization of the study area and to the Box-Jenkins presents strong, homogeneous, and stable correlations in the time series modeled for each pixel.

Спутниковая СВЧ-радиометрия для решения задач дистанционного зондирования Земли

The issues of development of the direction of satellite microwave radiometry in Russia in the interests of operational meteorology and oceanography are considered. The analysis of the current state of Russian and foreign radiometric ERS equipment in the microwave range is carried out. The technical characteristics of onboard multichannel microwave radiometers, combining the functions of a scanner and a sounder, are analyzed. The issues of metrological support of microwave measurements of equipment installed on Russian satellites of the Meteor-M series are considered. The original method of internal calibration of the MTVZA-GYA microwave scanner/sounding device is analyzed in detail in order to form the antenna temperature scale. The MTVZA-GYA calibration unit measures the radiation intensity of two matched loads with known brightness temperatures (“hot” and “cold”). An on-board calibrator is used as a “hot” load, it serves as an imitator of an absolutely black body, its brightness temperature of which is in the range of 240–300 K. Absolute (external) calibration is a transition from antenna to brightness temperatures and is performed using high-precision radiation calculations for specially selected natural testing sites. The issues of preliminary processing of MTVZA-GYA data are considered and examples of microwave images of the Earth in the scale of brightness temperatures are given.

Spectral linear mixing model applied to data from passive microwave radiometers for sea ice mapping in the Antarctic Peninsula

This study proposes the use of a Spectral Linear Mixing Model (SLMM) on passive microwave data for mapping the concentration and area of young and/or first-year ice in the oceanic region located in the northwest of the Antarctic Peninsula. Sentinel-1A Synthetic Aperture Radar (SAR) data were used to estimate fraction images needed for subpixel analysis of passive microwave data acquired by the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and the Special Sensor Microwave Imager/Sounder (SSMIS) in the 19H, 19 V, 37H, and 37 V channels and polarizations. Sea ice concentrations estimated by the SLMM approach had a difference of 1.4% (13.6% standard deviation, 15.3% root mean square error) when compared to sea ice concentrations mapped using Sentinel-1A SAR data. The evolution in the total area covered by young and/or first-year ice with concentrations ≥ 15% showed a negative linear trend for the studied region from 1979 to 2018.

A Printed Antenna with an Infrared Temperature Sensor for a Medical Multichannel Microwave Radiometer

The results of designing a printed ultra-wideband antenna intended for use as a part of a multichannel microwave radiometer are presented. The design of a ring-shaped antenna with a built-in infrared sensor for measuring skin temperature is proposed. The results of numerical simulation of the electromagnetic field of the antenna in tissues of a biological object are presented. The results of calculating the voltage standing wave ratio, measurement depth of the antenna, the resolution, and the distribution of radiation power over the tissue volume under study are presented.

Assessing the Potential of Enhanced Resolution Gridded Passive Microwave Brightness Temperatures for Retrieval of Sea Ice Parameters

A new enhanced resolution gridded passive microwave brightness temperature (TB) product is used to estimate sea ice concentration and motion. The effective resolution of the TBs is found to be roughly twice that of the standard 25 km resolution, though the gridded resolution of the distributed product is higher. Enhanced resolution sea ice concentrations from the Bootstrap algorithm show more detail in the sea ice, including relatively small open water regions within the ice pack. Sea ice motion estimates from the enhanced resolution TBs using a maximum cross-correlation method show a smoother motion circulation pattern; in comparison to buoys, RMS errors are 15–20% lower than motion estimates from the standard resolution fields and the magnitude of the bias is smaller as well. The enhanced resolution product includes other potentially beneficial characteristics, including twice-daily grids based on local time of day and a complete timeseries of data from nearly all multi-channel passive microwave radiometers since 1978. These enhanced resolution TBs are potential new source for long-term records of sea ice concentration, motion, age, melt, as well as salinity and ocean-atmosphere fluxes.

Comparison of HY-2B Passive Brightness Temperatures with SSMI/S, GMI, AMSR2 and MWRI in Land Surface

China launched a new marine satellite HaiYang (HY)-2B satellite on October 24, 2018 at 22:57 (UTC time), which provides full-time and all-weather observations with a design life of five years. It can cover 90% of the world’s oceans and obtain marine dynamic environment data. The Scanning Microwave Radiometer (SMR) is the main payload onboard the HY-2B, which can provide near-real-time observations. The instrument is a 5-frequency 9-channel microwave observing instrument with the central frequencies set to 6.925, 10.7, 18.7, 23.8, and 37 GHz. Except for 23.8 GHz, which is vertical polarization only, other four frequencies have both vertical and horizontal polarization detection channels. For the past forty years, passive microwave brightness temperature data from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I), Special Sensor Microwave Imager/Sounder (SSMI/S), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Microwave Scanning Radiometer 2 (AMSR2), Microwave Radiation Imager (MWRI) and the microwave imager of Global Precipitation Measurement mission (GMI) have provided considerable information on geophysical and climatic research. In order to expand the use of SMR observations on the earth’s land surface, in this study, SMR is compared with other on-orbit radiometers (SSMI/S, AMSR2, MWRI and GMI), and is conducted the cross-sensor calibration in land surface, which is critical foundation for the inversion of Earth surface geophysical parameters and climate researches in the near future.

A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures

Abstract. The Fundamental Climate Data Record (FCDR) of Microwave Imager Radiances from the Satellite Application Facility on Climate Monitoring (CM SAF) comprises inter-calibrated and homogenized brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I), and the Special Sensor Microwave Imager/Sounder SSMIS radiometers. It covers the time period from October 1978 to December 2015 including all available data from the SMMR radiometer aboard Nimbus-7 and all SSM/I and SSMIS radiometers aboard the Defense Meteorological Satellite Program (DMSP) platforms. SMMR, SSM/I, and SSMIS data are used for a variety of applications, such as analyses of the hydrological cycle, remote sensing of sea ice, or as input into reanalysis projects. The improved homogenization and inter-calibration procedure ensures the long-term stability of the FCDR for climate-related applications. All available raw data records from different sources have been reprocessed to a common standard, starting with the calibration of the raw Earth counts, to ensure a completely homogenized data record. The data processing accounts for several known issues with the instruments and corrects calibration anomalies due to along-scan inhomogeneity, moonlight intrusions, sunlight intrusions, and emissive reflector. Corrections for SMMR are limited because the SMMR raw data records were not available. Furthermore, the inter-calibration model incorporates a scene dependent inter-satellite bias correction and a non-linearity correction in the instrument calibration. The data files contain all available original sensor data (SMMR: Pathfinder level 1b) and metadata to provide a completely traceable climate data record. Inter-calibration and Earth incidence angle normalization offsets are available as additional layers within the data files in order to keep this information transparent to the users. The data record is complemented with noise-equivalent temperatures (NeΔT), quality flags, surface types, and Earth incidence angles. The FCDR together with its full documentation, including evaluation results, is freely available at: https://doi.org/10.5676/EUM_SAF_CM/FCDR_MWI/V003 (Fennig et al., 2017).

NCA-LDAS Land Analysis: Development and Performance of a Multisensor, Multivariate Land Data Assimilation System for the National Climate Assessment

Abstract This article describes one of the first successful examples of multisensor, multivariate land data assimilation, encompassing a large suite of soil moisture, snow depth, snow cover, and irrigation intensity environmental data records (EDRs) from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), Advanced Scatterometer (ASCAT), Moderate-Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Soil Moisture Ocean Salinity (SMOS) mission, and Soil Moisture Active Passive (SMAP) mission. The analysis is performed using the NASA Land Information System (LIS) as an enabling tool for the U.S. National Climate Assessment (NCA). The performance of the NCA Land Data Assimilation System (NCA-LDAS) is evaluated by comparing it to a number of hydrological reference data products. Results indicate that multivariate assimilation provides systematic improvements in simulated soil moisture and snow depth, with marginal effects on the accuracy of simulated streamflow and evapotranspiration. An important conclusion is that across all evaluated variables, assimilation of data from increasingly more modern sensors (e.g., SMOS, SMAP, AMSR2, ASCAT) produces more skillful results than assimilation of data from older sensors (e.g., SMMR, SSM/I, AMSR-E). The evaluation also indicates the high skill of NCA-LDAS when compared with other LSM products. Further, drought indicators based on NCA-LDAS output suggest a trend of longer and more severe droughts over parts of the western United States during 1979–2015, particularly in the southwestern United States, consistent with the trends from the U.S. Drought Monitor, albeit for a shorter 2000–15 time period.

Enhanced-Resolution SMAP Brightness Temperature Image Products

The NASA-sponsored Calibrated Passive Micro- wave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature (CETB) Earth System Data Record Project team has generated a multisensor, multidecadal time series of high-resolution radiometer products designed to support climate studies. This project uses image reconstruction techniques to generate conventional and enhanced-resolution daily brightness temperature images on a standard set of map projections. Sensors included in CETB are the Aqua Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E), Scanning Multichannel Microwave Radiometer, and all Special Sensor Microwave/Imager and Special Sensor Microwave Imager/Sounder radiometers. These span frequencies between 6 and 89 GHz. This paper considers the issues of adding the L-band (1.6 GHz) Soil Moisture Active Passive (SMAP) radiometer measurements to the CETB climate record, with emphasis on optimizing the reconstruction to provide the highest possible spatial resolution at the lowest noise level. SMAP radiometer reconstruction on SMAP-standard grids is also considered. Simulation is used to optimize the reconstruction, and the results confirmed using actual data. A comparison of the performance of the Backus–Gilbert approach and the radiometer form of the Scatterometer Image Reconstruction algorithm is provided. These are compared to the conventional drop-in-the-bucket gridded imaging.

Passive Microwave Melt Onset Retrieval Based on a Variable Threshold: Assessment in the Canadian Arctic Archipelago

The Canadian Arctic Archipelago (CAA) presents unique challenges to the determination of melt onset (MO) using remote sensing data. High spatial resolution data is required to discern melt onset among the islands and narrow waterways of the region. Current passive microwave retrievals use daily averaged 19 GHz and 37 GHz data from the multi-channel microwave radiometer (SMMR) and/or the special sensor microwave/imager (SSM/I). The development of a new passive microwave melt onset method capable of using higher resolution data is desirable. The new passive microwave melt onset method described here, named the Dynamic Threshold Variability Method (DTVM), uses higher resolution data from the 37 GHz vertically-polarized channel from the advanced microwave scanning radiometers (AMSR-E and AMSR-2). The DTVM MO detection methodology differs from previously presented passive microwave Arctic MO methods in that it does not use a fixed threshold of a brightness temperature parameter. Instead, the DTVM determines MO dates based on the distribution of dates corresponding to the exceedance of a range of brightness temperature variability thresholds. The method also uses swath data instead of daily averaged brightness temperatures, which is found to lead to improved melt detection. Two current passive microwave MO methods are compared and evaluated for applicability in the CAA alongside the DTVM. The DTVM provides MO dates at a higher spatial resolution than earlier methods in addition to higher correlation with MO dates from surface air temperature (SAT) reanalyses. It is found that, for some years, MO dates in the CAA exhibit a latitudinal dependence, while in other years the MO dates in the CAA are relatively uniform across the domain.

Sea Ice Sensing From GNSS-R Data Using Convolutional Neural Networks

In this letter, a scheme that uses convolutional neural networks (CNNs) is proposed for sea ice detection and sea ice concentration (SIC) prediction from TechDemoSat-1 Global Navigation Satellite System Reflectometry delay-Doppler maps (DDMs). Specifically, a classification-orientated CNN was designed for sea ice detection and a regression-based one for SIC estimation. Here, DDM images were used as input, and SIC data from Nimbus-7 Scanning Multi-Channel Microwave Radiometer and Defense Meteorological Satellite Program Special Sensor Microwave Imager-Special Sensor Microwave Imager/Sounder sensors were modified as targeted output. In the experimental phase, the CNN output resulted from inputting full-size DDM data (128-by-20 pixels) showed better accuracy than that of the existing NN-based method. Besides, both CNNs and NNs with further processed input data (40-by-20 pixels, and with a fixed position in each image) were evaluated and the performance of both networks was enhanced. It was found that when DDM data are adequately preprocessed, CNNs and NNs share similar accuracy; otherwise the former outperforms the latter. Further conclusion was thus drawn that CNNs were more tolerant to the data format changes than NNs.