Cross-track Scanning Research Articles

Initial evaluation of humidity profiles retrieved by the EOS-07 millimetre-wave humidity sounder

ABSTRACT The vertical profiles of specific humidity in the troposphere measured by the millimetre-wave humidity sounder (MHS) onboard of the Earth Observation Satellite (EOS)-07 (Microsoft 2B) are validated using ground-based radiosonde observations during July-August 2023. MHS onboard EOS-07 (hereafter referred as EOS-07/MHS) is a 6-channel cross-track scanning radiometer operating in the 183.31 ± 16.25 GHz band. The EOS-07 observations are used to retrieve three-dimensional specific humidity profiling from 1000 hPa (surface) to 100 hPa (16 km) atmospheric pressure levels with a spatial resolution of 10 km at nadir. The EOS-07/MHS measurements over India have a high correlation coefficient of 0.98 with the radiosonde observations. The mean relative bias is found to be 0.44 ± 0.55 g kg−1 below 350hPa and 2.8 ± 2.3 g kg−1 above 350 hPa. It is also found that above the 350 hPa level, MHS seems to be systematically overestimating the radiosonde measurements. After that, the EOS-07/MHS measurements are used to construct the diurnal variation of humidity during the active phases of the Indian summer monsoon. The observations are consistent with the present understanding of the Indian summer monsoon system. The present results are very encouraging and demonstrate the great potential of EOS-07/MHS observations of humidity for meteorological application, especially in understanding the hydrological cycle.

Evaluating and Improving TROPICS Millimeter‐Wave Sounder's Precipitation Estimate Over Ocean

AbstractThis paper examines precipitation retrievals from Kidd et al. (2022, https://doi.org/10.3390/rs14132992) by applying the Precipitation Retrieval and Profiling Scheme to data observed by the NASA Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter‐wave Sounder (TMS) onboard the TROPICS Pathfinder satellite, a precursor to the TROPICS mission. We first compare the TMS precipitation retrieval performance over ocean with those from seven current operational passive microwave radiometers, including four conical scanning sensors [Special Sensor Microwave Imager/Sounders (SSMISs) onboard F16/F17/F18 satellites, and Advanced Microwave Scanning Radiometer 2 (AMSR2)] and three cross track scanning sensors [Microwave Humidity Sounders onboard NOAA19 and MetOpB satellites, and the Advanced Technology Microwave Sounder onboard the National Polar‐orbiting Partnership satellite], using precipitation estimates from Global Precipitation Measurement Mission Microwave Imager (GMI) as the reference. We show that TMS performs similarly to the current operational cross track scanning sensors, while worse than conical scanning sensors largely due to the lack of low frequency channels (e.g., 19 GHz). Second, we create an adjusted TMS precipitation retrievals by combining the original TMS precipitation and the precipitation propagated from AMSR2 and SSMISs to the time/location of the TMS overpass, using our previously developed microwave‐to‐microwave propagation technique. Results show that the adjusted TMS precipitation performs better than the original TMS estimates. For example, the correlation of the original TMS and GMI estimates is 0.35 but increases to 0.49 when the adjusted TMS result is compared to GMI. The propagation technique lays the foundation to improve TMS precipitation when incorporating them into level‐3 merged products.

Evaluation of Snowfall Retrieval Performance of GPM Constellation Radiometers Relative to Spaceborne Radars

Abstract This study assesses the level-2 snowfall retrieval results from 11 passive microwave radiometers generated by the version 5 Goddard profiling algorithm (GPROF) relative to two spaceborne radars: CloudSat Cloud Profiling Radar (CPR) and Global Precipitation Measurement (GPM) Ku-band Precipitation Radar (KuPR). These 11 radiometers include six conical scanning radiometers [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), its successor sensor AMSR2, GPM Microwave Imager (GMI), and three Special Sensor Microwave Imager/Sounders (SSMIS)] and five cross-track scanning radiometers [Advanced Technology Microwave Sounder (ATMS) and four Microwave Humidity Sounders (MHS)]. Results show that over ocean conical scanning radiometers have better detection and intensity estimation skills than cross-track sensors, likely due to the availability and usage of the low-frequency channels (e.g., 19 and 37 GHz). Over land, AMSR-E and AMSR2 have noticeably worse performance than other sensors, primarily due to the lack of higher than 89-GHz channels (e.g., 150, 166, and 183 GHz). Over both land and ocean, all 11 sensors severely underestimate the snowfall intensity, which propagates to the widely used level 3 precipitation product [i.e., Integrated Multi-satelliteE Retrievals for GPM (IMERG)]. These conclusions hold regardless of using either KuPR or CPR as the reference, though the statistical metrics vary quantitatively. The conclusions drawn from these comparisons apply solely to the GPROF version 5 algorithm.

Simulations of sea surface reflection for V-band O2 differential absorption radar barometry

This study simulates V-band sea surface reflectance and normalized radar cross-section (NRCS) for sea surface air pressure barometry using a differential absorption radar operating at three spectrally even spaced close frequency bands (65.5, 67.75 and 70.0 GHz) with ± 15° cross-track scanning angle. The reflectance ratios of two neighboring frequency pairs and the ratio of the two ratios or three-channel approach are the focus of this study. Impacts of major sea surface geophysical variables such as sea surface temperature, wind, salinity, whitecap, and incidence angle on these reflection properties are analyzed. The reflection simulation is essentially based on geometric optics of rough sea surface. Simulation shows that NRCS values are sufficiently strong within the scanning angle and sea surface salinity would only introduce minimal variations in the surface reflection. The impact of sea surface reflection variations with sea surface temperature, wind, and whitecaps on sea surface barometry are mitigated when the ratios of frequency-paired radar signals are used. Furthermore, the ratios of a three-channel approach are very close to unity and calibration or compensation for the reflectance ratios may not be needed for sea level pressure retrievals. These results improve our understanding of sea surface reflection variations and would help the system design and development.

Low-Cost Millimeter Wave Frequency Scanning Based Synthesis Aperture Imaging System for Concealed Weapon Detection

In this article, a novel low-cost frequency scanning-based synthetic aperture radar (F-SAR) system is proposed for high-resolution imaging. F-SAR scheme is demonstrated for personal screening for the first time. A hybrid scanning model is presented to illuminate the human body, namely, frequency control beam steering in cross-track and mechanical scanning in along-track. A frequency scanning-based tomographic SAR focusing algorithm is proposed. Accordingly, a power spectrum estimation algorithm in cross-track and synthetical aperture processing in along-track are compounded in the signal processing framework. Unlike a variety of multiple input multiple output (MIMO) array imaging which illuminates the object by switching different channels sequentially over separate time intervals, the F-SAR concept sweeps across all swaths over each chirp by employing a frequency scanned beam. Herein imaging time and hardware cost can be significantly cut down by dimensionality reduction from the MIMO system to a single input single output (SISO) system. Furthermore, to fulfill the particular scheme of the F-SAR system, a novel combo antenna module, leaky-wave slotted waveguide combined with a cylindrical lens, is proposed and achieved at 78–92-GHz band, by which a steering fan-beam focused at the object under test (OUT) plane is radiated. The radiation beam is focalized by the cylindrical lens accompanied by frequency sweeping, while is diffused in along-track. The frequency-controlled beam-steering concept and the fan-beam focusing mechanism are verified by the chamber measurements. The measured scanning range is 23°. Beamwidth of 11–16 mm is obtained at the focal plane. Beam steering in cross-track together with mechanical scanning in along-track can attain a field of view (FoV) of 0.54 2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{2}$ </tex-math></inline-formula> . Through-clothes imaging of person-borne concealed objects and the real-time capability are demonstrated by experiments. Resolutions in both along-track and cross-track can reach 5 mm.

Precipitation Estimation from the NASA TROPICS Mission: Initial Retrievals and Validation

This paper describes the initial results of precipitation estimates from the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) Millimeter-wave Sounder (TMS) using the Precipitation Retrieval and Profiling Scheme (PRPS). The TROPICS mission consists of a Pathfinder CubeSat and a constellation of six CubeSats, providing a low-cost solution to the frequent sampling of precipitation systems across the Tropics. The TMS instrument is a 12-channel cross-track scanning radiometer operating at frequencies of 91.655 to 204.8 GHz, providing similar resolutions to current passive microwave sounding instruments. These retrievals showcase the potential of the TMS instrument for precipitation retrievals. The PRPS has been modified for use with the TMS using a database based upon observations from current sounding sensors. The results shown here represent the initial postlaunch version of the retrieval scheme, as analyzed for the Pathfinder CubeSat launched on 30 June 2021. In terms of monthly precipitation estimates, the results fall within the mission specifications and are similar in performance to retrievals from other sounding instruments. At the instantaneous scale, the results are very promising.

Angular-Dependent Polarized Characteristics of Surface Emissivity at 150 GHz Over Saharan and Taklimakan Deserts

This study characterizes the marginally-known angular-dependent polarization difference of the land surface emissivity (LSE), using the microwave humidity sounder (MWHS) onboard China&#x2019;s sun-synchronous satellite FengYun-3B (FY-3B). The instrument has two quasi-polarization channels at 150 GHz in addition to the three water-vapor absorption channels in the vicinity of 183 GHz, allowing observations at quasi vertical and horizontal polarizations with its cross-track scanning geometry. The Saharan and Taklimakan deserts are taken as examples due to the relatively homogeneous surface conditions. In the two 150 GHz channels of MWHS, the polarization bias is corrected according to the measurements at the Earth incidence angle (EIA) of 0&#x00B0;. The monthly-mean quasi-polarization difference (QPD) at 150 GHz is found to be varying with the EIA and exhibits seasonal variations over deserts. The QPD reaches a maximum value at the EIA of &#x007E;35&#x00B0;, while the zero value appears near the EIA of &#x007E;53&#x00B0; (equal to the satellite viewing angle of 45&#x00B0;) as expected. In contrast to the relatively stable and low QPD over Sahara, the QPD, quasi polarized emissivity difference and pure polarized emissivity difference are generally larger in the Taklimakan Desert, where the maximum monthly QPD is &#x007E;4 K and the polarized emissivity difference increases monotonously to &#x007E;0.2 at the EIA of 50&#x00B0;. The complex surface parameters and temporal variabilities impinge on the uncertainties of the land polarization. The increasing soil moisture due to precipitation damps the dichroic ability of the land surface, while the frozen surface due to snowfalls in cold seasons enhances the polarization.

Geolocation Error Estimation Method for the Wide Swath Polarized Scanning Atmospheric Corrector Onboard HJ-2 A/B Satellites

Polarized Scanning Atmospheric Corrector (PSAC) onboard the Huanjing Jianzai (HJ)-2 A/B satellites is a cross-track scanning polarimetric remote sensor that measures the intensity and direction of light reflected by the Earth and its atmosphere by 9 full polarized spectral bands from near-ultraviolet (near-UV) to shortwave infrared (SWIR). In particular, geolocation accuracy is an important factor for polarization observations. An automatic coastline inflection method (CIM) is implemented for PSAC geolocation error estimation. Over five months of globally middle or low latitude coastline area measurements are used to obtain statistical result. The results of the comparison with the Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG) show PSAC geolocation error is smaller than 0.38 ground sample distance (GSD) or 3.25 km in 95% confidence level. In cross-track direction, the geolocation error estimation is affected by the instrument sampling characteristics like spatial response function (SRF). Thus, the correction method is proposed by establishing relationship between measurement radiance in CIM and offset proportion of PSAC GSD. The biases are obviously reduced after correction.

Orbit Simulator for Satellite and Near-Space Platforms Supporting Observing System Simulation Experiments

Abstract Developed at the National Oceanic and Atmospheric Administration (NOAA) and the Joint Center for Satellite Data Assimilation (JCSDA), the Community Global Observing System Simulation Experiment (OSSE) Package (CGOP) provides a vehicle to quantitatively evaluate the impacts of emerging environmental observing systems or emerging in situ or remote sensing instruments on NOAA numerical weather prediction (NWP) forecast skill. The typical first step for the OSSE is to simulate observations from the so-called nature run. Therefore, the observation spatial, temporal, and view geometry are needed to extract the atmospheric and surface variables from the nature run, which are then input to the observation forward operator (e.g., radiative transfer models) to simulate the new observations. This is a challenge for newly proposed systems for which instruments are not yet built or platforms are not yet deployed. To address this need, this study introduces an orbit simulator to compute these parameters based on the specific hosting platform and onboard instrument characteristics, which has been recently developed by the NOAA Center for Satellite Applications and Research (STAR) and added to the GCOP framework. In addition to simulating existing polar-orbiting and geostationary orbits, it is also applicable to emerging near-space platforms (e.g., stratospheric balloons), cube satellite constellations, and Tundra orbits. The observation geometry simulator includes not only passive microwave and infrared sounders but also global navigation satellite system/radio occultation (GNSS/RO) instruments. For passive atmospheric sounders, it calculates the geometric parameters of proposed instruments on different platforms, such as time varying location (latitude and longitude), scan geometry (satellite zenith and azimuth angles), and ground instantaneous field of view (GIFOV) parameters for either cross-track or conical scanning mechanisms. For RO observations, it determines the geometry of the transmitters and receivers either on satellites or stratospheric balloons and computes their slant paths. The simulator has been successfully applied for recent OSSE studies (e.g., evaluating the impacts of future geostationary hyperspectral infrared sounders and RO observations from stratospheric balloons). Significance Statement An orbit simulator for satellite and near-space platforms for supporting observing system simulation experiments (OSSE) is developed in this study. It can compute spatial, temporal, and view geometry parameters of the new observations based on the specific hosting platform and onboard instrument characteristics. These parameters are important for the OSSE to extract atmospheric profiles and surface properties from nature run data and simulate new observations. In addition to simulating existing polar-orbiting and geostationary orbits, it is applicable to emerging near-space platforms (e.g., stratospheric balloons), cube satellite constellations, and Tundra orbits. The observation geometry simulator includes not only passive microwave and infrared sounders but also radio occultation instruments.

Spaceborne differential absorption radar water vapor retrieval capabilities in tropical and subtropical boundary layer cloud regimes

Abstract. Differential absorption radar (DAR) near the 183 GHz water vapor absorption line is an emerging measurement technique for humidity profiling inside of clouds and precipitation with high vertical resolution, as well as for measuring integrated water vapor (IWV) in clear-air regions. For radar transmit frequencies on the water line flank away from the highly attenuating line center, the DAR system becomes most sensitive to water vapor in the planetary boundary layer (PBL), which is a region of the atmosphere that is poorly resolved in the vertical by existing spaceborne humidity and temperature profiling instruments. In this work, we present a high-fidelity, end-to-end simulation framework for notional spaceborne DAR instruments that feature realistically achievable radar performance metrics and apply this simulator to assess DAR's PBL humidity observation capabilities. Both the assumed instrument parameters and radar retrieval algorithm leverage recent technology and algorithm development for an existing airborne DAR instrument. To showcase the capabilities of DAR for humidity observations in a variety of relevant PBL settings, we implement the instrument simulator in the context of large eddy simulations (LESs) of five different cloud regimes throughout the trade-wind subtropical-to-tropical cloud transition. Three distinct DAR humidity observations are investigated: IWV between the top of the atmosphere and the first detected cloud bin or Earth's surface; in-cloud water vapor profiles with 200 meter vertical resolution; and IWV between the last detected cloud bin and the Earth's surface, which can provide a precise measurement of the sub-cloud humidity. We provide a thorough assessment of the systematic and random errors for all three measurement products for each LES case and analyze the humidity precision scaling with along-track measurement integration. While retrieval performance depends greatly on the specific cloud regime, we find generally that for a radar with cross-track scanning capability, in-cloud profiles with 200 m vertical resolution and 10 %–20 % uncertainty can be retrieved for horizontal integration distances of 100–200 km. Furthermore, column IWV can be retrieved with 10 % uncertainty for 10–20 km of horizontal integration. Finally, we provide some example science applications of the simulated DAR observations, including estimating near-surface relative humidity using the cloud-to-surface column IWV and inferring in-cloud temperature profiles from the DAR water vapor profiles by assuming a fully saturated environment.

Improving Cross-track Scanning Radiometers’ Precipitation Retrieval over Ocean by Morphing

AbstractPrevious studies showed that conical scanning radiometers greatly outperform cross-track scanning radiometers for precipitation retrieval over ocean. This study demonstrates a novel approach to improve precipitation rates at the cross-track scanning radiometers’ observation time by propagating the conical scanning radiometers’ retrievals to the cross-track scanning radiometers’ observation time. The improved precipitation rate is a weighted average of original cross-track radiometers’ retrievals and retrievals propagated from a conical scanning radiometer. The cross-track scanning radiometers include the Advanced Technology Microwave Sounder (ATMS) onboard the NPP satellite and four Microwave Humidity Sounders (MHSs). The conical scanning radiometers include the Advanced Microwave Scanning Radiometer 2 (AMSR2) and three Special Sensor Microwave Imager/Sounders (SSMISs), while the precipitation retrievals from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) are taken as the reference. Results show that the morphed precipitation rates agree much better with the reference. The degree of improvement depends on several factors, including the propagated precipitation source, the time interval between the cross-track scanning radiometer and the conical scanning radiometer, the precipitation type (convective vs. stratiform), the precipitation events’ size, and the geolocation. The study has potential to greatly improve high-impact weather systems monitoring (e.g., hurricanes) and multi-satellite precipitation products. It may also enhance the usefulness of future satellite missions with cross-track scanning radiometers onboard.

The Passive Microwave Neural Network Precipitation Retrieval Algorithm for Climate Applications (PNPR-CLIM): Design and Verification

This paper describes the Passive microwave Neural network Precipitation Retrieval algorithm for climate applications (PNPR-CLIM), developed with funding from the Copernicus Climate Change Service (C3S), implemented by ECMWF on behalf of the European Union. The algorithm has been designed and developed to exploit the two cross-track scanning microwave radiometers, AMSU-B and MHS, towards the creation of a long-term (2000–2017) global precipitation climate data record (CDR) for the ECMWF Climate Data Store (CDS). The algorithm has been trained on an observational dataset built from one year of MHS and GPM-CO Dual-frequency Precipitation Radar (DPR) coincident observations. The dataset includes the Fundamental Climate Data Record (FCDR) of AMSU-B and MHS brightness temperatures, provided by the Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO) project, and the DPR-based surface precipitation rate estimates used as reference. The combined use of high quality, calibrated and harmonized long-term input data (provided by the FIDUCEO microwave brightness temperature Fundamental Climate Data Record) with the exploitation of the potential of neural networks (ability to learn and generalize) has made it possible to limit the use of ancillary model-derived environmental variables, thus reducing the model uncertainties’ influence on the PNPR-CLIM, which could compromise the accuracy of the estimates. The PNPR-CLIM estimated precipitation distribution is in good agreement with independent DPR-based estimates. A multiscale assessment of the algorithm’s performance is presented against high quality regional ground-based radar products and global precipitation datasets. The regional and global three-year (2015–2017) verification analysis shows that, despite the simplicity of the algorithm in terms of input variables and processing performance, the quality of PNPR-CLIM outperforms NASA GPROF in terms of rainfall detection, while in terms of rainfall quantification they are comparable. The global analysis evidences weaknesses at higher latitudes and in the winter at mid latitudes, mainly linked to the poorer quality of the precipitation retrieval in cold/dry conditions.

The Passive microwave Empirical cold Surface Classification Algorithm (PESCA): application to GMI and ATMS

AbstractThis paper describes a new Passive microwave Empirical cold Surface Classification Algorithm (PESCA) developed for snow cover detection and characterization by using passive microwave satellite measurements. The main goal of PESCA is to support the retrieval of falling snow, as several studies have highlighted the influence of snow cover radiative properties on the falling snow passive microwave signature. The developed methodology is based on the exploitation of the lower frequency channels (&lt; 90 GHz), common to most microwave radiometers. The methodology applied to the conically scanning GMI and the cross-track scanning ATMS is described in this paper. PESCA is based on a decision tree developed using an empirical method and verified using the AutoSnow product built from satellite measurements. The algorithm performance appears to be robust for both sensors in dry conditions (TPW &lt; 10 mm), and for mean surface elevation &lt; 2500 m, independently of the cloud cover. The algorithm shows very good performance for cold temperatures (2 m temperature below 270 K) with a rapid decrease of the detection capabilities between 270 K and 280 K, where 280 K is assumed as the maximum temperature limit for PESCA [overall detection statistics: POD=0.98(0.92), FAR=0.01(0.08), HSS=0.72(0.69) for ATMS(GMI)]. Some inconsistencies found between the snow categories identified with the two radiometers are related to their different viewing geometry, spatial resolution, and temporal sampling. The spectral signatures of the different snow classes appear to be different also at high frequency (&gt;90GHz), indicating potential impact for snowfall retrieval. This method can be applied to other conically and cross track scanning radiometers including the future operational EPS-SG mission microwave radiometers.

Preliminary Development and Testing of an EPS-SG Microwave Sounder Proxy Data Generator Using the NOAA Microwave Integrated Retrieval System

The European Organisation for the Exploitation of Meteorological Satellites currently plans to launch Meteorological Operational Satellite Second Generation A1 (Metop-SG A1) with the microwave Sounder (MWS) instrument in 2023. MWS is a cross-track scanning passive microwave radiometer measuring in the range from 23.8 to 229 GHz, which is similar to the Advanced Technology Microwave Sounder (ATMS) on board the satellites in the Joint Polar Satellite System (JPSS) program. To confirm the capability of operational retrieval systems with MWS before its operational deployment, the prerequisites are to have the MWS simulated brightness temperatures and to apply them to a proper testbed. In this study, a preliminary version of MWS proxy data generator has been developed to provide the MWS simulated brightness temperature datasets and the Microwave Integrated Retrieval System (MiRS) is used as a testbed for an operational retrieval system. ATMS simulated brightness temperature datasets are also generated in the same way in which the MWS simulated brightness temperature datasets are generated in order to have a consistent comparison between MWS and ATMS results. MiRS was run with the MWS simulated inputs and the results are comparable to those of the MiRS ATMS experiments. MiRS MWS total precipitable water accuracy and precision are within most JPSS requirements. The change in channel characteristics from ATMS to MWS including the addition of temperature sounding channels at 53.2 and 53.9 GHz and the polarization change in channels 1 and 2 appear to slightly improve performance of MWS over land temperature and water vapor retrievals,respectively.

TEMPEST-D Radiometer: Instrument Description and Prelaunch Calibration

The Temporal Experiment for Storms and Tropical Systems Technology Demonstration (TEMPEST-D) instrument is a five-frequency millimeter-wave radiometer operating from 87 to 181 GHz. The cross-track scanning radiometer has been operating on a 6U CubeSat in low Earth orbit since September 5, 2018. The direct-detection architecture of the radiometer reduces its mass and power consumption by eliminating the need for a local oscillator and mixer, also reducing system complexity. The instrument includes a scanning reflector and ambient calibration target. The reflector rotates continuously to scan the antenna beams in the cross-track direction, first across the blackbody calibration target, then toward the Earth over the full range of incidence angles, and finally to cosmic microwave background radiation at 2.73 K. This enables precision end-to-end calibration of the millimeter-wave receivers during every 2-s scan period. The TEMPEST-D millimeter-wave radiometers are based on 35-nm indium phosphide (InP) high-electron-mobility transistor (HEMT) low-noise amplifiers. This article describes the instrument and its characterization prior to launch.

Calibration and Validation of the TEMPEST-D CubeSat Radiometer

Temporal Experiment for Storms and Tropical Systems-Demonstration (TEMPEST-D) is a 6U CubeSat satellite with a cross-track scanning millimeter-wave radiometer measuring at five frequencies from 87 to 181 GHz. It employs a direct-detection architecture with InP HEMT monolithic microwave integrated circuit (MMIC) low-noise amplifiers and related new technologies. An end-to-end two-point external calibration is performed every 2-s rotation of the scanning mirror, based on observations of the cosmic microwave background and an internal blackbody calibration target, with three thermistors to monitor the target physical temperature. Corrections for antenna pattern effects and cross-scan biases based on prelaunch measured values were updated using data from an on-orbit calibration pitch maneuver. Validation of the observed brightness temperatures ( T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> ) is performed by comparing to coincident nonprecipitating ocean observations from five well-calibrated on-orbit instruments, including Global Precipitation Measurement (GPM) mission Microwave Imager (GMI) and four Microwave Humidity Sounder (MHS) sensors on board NOAA-19, MetOp-A, MetOp-B, and MetOp-C satellites. Absolute calibration accuracy is within 1 K for all channels, well within the 4-K requirement. Calibration precision, or stability over time, is within 0.6 K for all channels, also well within the 2-K requirement. The intrinsic noise of TEMPEST-D is lower than MHS, resulting in similar on-orbit noise equivalent differential temperatures (NEDTs), even though TEMPEST-D has a much shorter integration time of 5 ms as compared to 18 ms for MHS. As a result, although the TEMPEST-D radiometer is substantially smaller, lower power, and lower cost than similar current operational radiometers, it has comparable or better performance in terms of instrument noise, calibration accuracy, and calibration stability or precision.

A tie-point zone group compaction schema for the geolocation data of S-NPP and NOAA-20 VIIRS SDRs to reduce file sizes in memory-sensitive environments

The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) disseminates weather and climate-related satellite data to its users via satellite broadcast. As part of this, the EUMETSAT Advanced Retransmission Service (EARS) provides Sensor Data Records (SDR) from the United States satellites Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20. Due to bandwidth constraints and for cost-reduction reasons for the upload to the disseminating satellite, a near-lossless compaction method has been developed for the geolocation data of the data capturing satellites’ Visible Infrared Imager Radiometer Suite (VIIRS) instrument. The geolocation data are compacted by storing only the data representation for so called tie-points which form tie-point zones and are grouped in tie-point zone groups. Compression factors of 120 for M-Band, 479 for I-Band, and 154 for Day/Night Band, not using HDF5 internal compression on neither the input nor the output, and 56 for M-Band, 210 for I-Band, and 89 for Day/Night Band, using HDF5 internal compression on both the input and output, respectively, are reached. The compaction process introduces an error of about 1 ​m RMSE for the position in latitude/longitude and of about 0.001° RMSE for the angular data. The concept of the tie-point zones and the quadratic interpolation schema with coefficients analytically derived from the scanning geometry forms the main elements of the method presented. The full algorithm and mathematical background needed are presented, and the algorithm can be highly parallelized. The method can likely be applied to any cross-track scanning sensor.

Instrument Design and Performance of the High-Frequency Airborne Microwave and Millimeter-Wave Radiometer

The high-frequency airborne microwave and millimeter-wave radiometer (HAMMR) is a cross-track scanning airborne radiometer instrument with 25 channels from 18.7 to 183.3 GHz. HAMMR includes: low-frequency microwave channels at 18.7, 23.8, and 34.0 GHz at two linear-orthogonal polarizations; high-frequency millimeter-wave channels at 90, 130 and 168 GHz; and millimeter-wave sounding channels consisting of eight channels near the 118.75 GHz oxygen absorption line for temperature profiling and eight additional channels near the 183.31 GHz water vapor absorption line for water vapor profiling. HAMMR was deployed on a twin otter aircraft for a west coast flight campaign (WCFC) from November 4–17, 2014. During the WCFC, HAMMR collected radiometric observations for more than 53.5 h under diverse atmospheric conditions, including clear sky, scattered and dense clouds, as well as over a variety of surface types, including coastal ocean areas, inland water and land. These measurements provide a comprehensive dataset to validate the instrument.

Bias characterization of ATMS low-level channels under clear-sky and cloudy conditions

The Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-Orbiting Partnership satellite is a cross-track scanning instrument containing 22 sounding channels in total. In this study, the bias characteristics of channels 1–6, which could have significant cloud contamination in heavy precipitation, are first analyzed based on the differences between ATMS observations (O) and model simulations (B) under clear-sky conditions over oceans. Latitudinal dependencies of the biases of window channels 1–3 are greater than those of channels 4–6. Biases of all nadir-only observations examined in different latitudinal bands [μ1(φ)] are positive and no more than 7.0 K. Biases at higher latitudes are larger. Channels 1–5 have a generally symmetric scan bias pattern [μ2(α)]. The global distributions of brightness temperature differences after subtracting the biases, i.e., O-B-μ1(φ)-μ2(α), for channels 3–6 spatially match the liquid water path distributions. Excluding ice-affected observations, channel 3–6 O-B differences systematically increase as the liquid water path increases under cloudy conditions. Further investigation is needed to apply these findings for ATMS data assimilation under both clear-sky and cloudy conditions.

An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-Launch Testing

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022 and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011 and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 μm: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB) and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Our analysis results confirmed the good performance of J2 VIIRS, in general as good as previous VIIRS instruments and all non-compliances are expected to have low impact on data quality. Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS) and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.