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Passive microwave satellite observations provide critical information for global forecast models, particularly in cloudy and/or precipitating conditions. The limited temporal sampling provided by current operational polar orbiters cannot capture rapidly changing conditions such as the development of convective storms. This is a significant issue for open-ocean weather systems such as tropical cyclones and hurricanes that can only be effectively monitored from satellites. The recent development and demonstration of miniaturized microwave radiometers on-board low-cost CubeSat satellites has the potential to dramatically improve the temporal and spatial sampling of all-sky microwave observations by deploying a substantial constellation of satellites in low Earth orbit. Two constellations of 60 CubeSats in 550 km orbits are compared to the current operational microwave sensors. One approach employs all polar orbiters, while the other approach uses multiple inclination orbits for increased sampling over convective storm regions. Both approaches reduce average revisit times to approximately 20–30 min globally, and the multi-inclination approach also provides irregular 5–10 min sampling over selected latitudes. Improved global temporal sampling would provide all-sky observations to global forecast models over rapidly changing environments, while millimeter-wave observations over convective storm regions would be valuable for both forecasting and studying the development of convective storms. This article demonstrated that a constellation of low-cost CubeSats with microwave radiometers has the potential to provide equivalent temporal resolution to that observed from sensors on geostationary orbit .

Observing system assessments were made for the Earth Observing Nanosatellite-Microwave (EON-MW), a 12U CubeSat analog of the Advanced Technology Microwave Sounder (ATMS). Since the EON-MW channels and sensor specifications closely follow those of ATMS, the sensor characteristics and geophysical capabilities assessments indicate that the value of information for humidity (temperature) of EON-MW observations will be similar (very similar) to that of ATMS. Eight global observing system simulation experiments (OSSEs) were carried out to evaluate several different EON-MW constellations for data gap mitigation and/or replacement of existing sensors. In these OSSEs, adding 2 EON-MW sensors in different orbits, compared to adding a single EON-MW sensor, improves forecasts generally, and improves the analysis of at least wind and humidity. In terms of the overall OSSE impacts in the scenarios considered, a single EON-MW sensor is a close substitute for ATMS and two EON-MW sensors are a close substitute for the Special Sensor Microwave Imager Sounder (SSMIS). The analysis and forecast impacts indicate that EON-MW provides improved humidity profiles compared to SSMIS and ATMS.

As one of the calibration reference targets used to calibrate the cross-track infrared sounder (CrIS) earth scene (ES) measurements, the stable deep space (DS) reference spectrum in the 30-scan DS calibration moving window is very important for the accuracy of the calibrated ES radiances. The DS view changes when the lunar radiation intrudes into the observation field of view (FOV). In the original CrIS lunar intrusion (LI) detection algorithm implemented in the operational ground processing system, the contaminated DS spectra were not effectively removed from the DS moving window due to large threshold values and the assumption that the first DS spectrum in the moving window was not contaminated. As a result, inaccurate, degraded, or invalid ES radiances were produced in the operational CrIS sensor data record (SDR) during LI events. In this article, an improved LI detection algorithm is developed and implemented into the operational system. First, the new algorithm efficiently finds a contamination-free DS spectrum in the DS 30-scan calibration moving window to use as the reference spectrum. Second, based on the phase characteristics of the complex raw DS spectra during LI events, the LI band-dependent thresholds were derived to effectively reject the contaminated DS spectra and to make the valid DS window size consistent among the three CrIS bands. The new LI algorithm implemented in the operational system shows a successful detection and removal of all the lunar-contaminated DS spectra in the DS moving window, resulting in an improved calibration of ES radiances during LI events.

The Cross-track Infrared Sounder (CrIS) [1] is currently undergoing Thermal Vacuum Testing (TVAC) before integration with the Joint Polar Satellite System-2 (JPSS-2) satellite prior to the planned launch in 2022. During these tests, the NOAA/CrIS Sensor Data Record (SDR) team aims to independently evaluate the performance of the new CrIS instrument. Here, we will present our work assessing the instrument noise and the brightness temperature measurement from external calibration targets (ECTs) as a function of its stepped temperature. The latter test will be used to calculate the radiometric nonlinearity correction applied to the complex spectra. Additional tests that will take place during TVAC include the evaluation of noise during vibration testing, analyzing slit scan data to determine the Field-Of-View (FOV) crosstalk, processing gas cell data to derive the spectral calibration coefficients, and measuring ECTs to validate the radiometric calibration of CrIS.

The Cross-track Infrared Sounder (CrIS) on board the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite, NOAA-20, and future Joint Polar Satellite System (JPSS) satellites J2 to J4 provide the hyperspectral infrared observations for profiling atmospheric temperature, moisture and greenhouse gases globally. In this study, the J2 CrIS prelaunch spectral calibration parameters including detector focal plane geometry (FOV size and offset angles, referred to as instrument line shape (ILS)) and Neon lamp effective wavelength are derived from the thermal vacuum (TVAC) gas cell test data. These derived parameters are evaluated using the spectral cross-correlation method by comparing with the simulated spectral lines from the line-by-line radiative transfer model (LBLRTM).

The launch of the National Oceanic and Atmospheric Administration (NOAA)/ National Aeronautics and Space Administration (NASA) Suomi National Polar-orbiting Partnership (S-NPP) and its follow-on NOAA Joint Polar Satellite Systems (JPSS) satellites marks the beginning of a new era of operational satellite observations of the Earth and atmosphere for environmental applications with high spatial resolution and sampling rate. The S-NPP and JPSS are equipped with five instruments, each with advanced design in Earth sampling, including the Advanced Technology Microwave Sounder (ATMS), the Cross-track Infrared Sounder (CrIS), the Ozone Mapping and Profiler Suite (OMPS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Clouds and the Earth’s Radiant Energy System (CERES). Among them, the ATMS is the new generation of microwave sounder measuring temperature profiles from the surface to the upper stratosphere and moisture profiles from the surface to the upper troposphere, while CrIS is the first of a series of advanced operational hyperspectral sounders providing more accurate atmospheric and moisture sounding observations with higher vertical resolution for weather and climate applications. The OMPS instrument measures solar backscattered ultraviolet to provide information on the concentrations of ozone in the Earth’s atmosphere, and VIIRS provides global observations of a variety of essential environmental variables over the land, atmosphere, cryosphere, and ocean with visible and infrared imagery. The CERES instrument measures the solar energy reflected by the Earth, the longwave radiative emission from the Earth, and the role of cloud processes in the Earth’s energy balance. Presently, observations from several instruments on S-NPP and JPSS-1 (re-named NOAA-20 after launch) provide near real-time monitoring of the environmental changes and improve weather forecasting by assimilation into numerical weather prediction models. Envisioning the need for consistencies in satellite retrievals, improving climate reanalyses, development of climate data records, and improving numerical weather forecasting, the NOAA/Center for Satellite Applications and Research (STAR) has been reprocessing the S-NPP observations for ATMS, CrIS, OMPS, and VIIRS through their life cycle. This article provides a summary of the instrument observing principles, data characteristics, reprocessing approaches, calibration algorithms, and validation results of the reprocessed sensor data records. The reprocessing generated consistent Level-1 sensor data records using unified and consistent calibration algorithms for each instrument that removed artificial jumps in data owing to operational changes, instrument anomalies, contaminations by anomaly views of the environment or spacecraft, and other causes. The reprocessed sensor data records were compared with and validated against other observations for a consistency check whenever such data were available. The reprocessed data will be archived in the NOAA data center with the same format as the operational data and technical support for data requests. Such a reprocessing is expected to improve the efficiency of the use of the S-NPP and JPSS satellite data and the accuracy of the observed essential environmental variables through either consistent satellite retrievals or use of the reprocessed data in numerical data assimilations.

Atmospheric soundings from radiosondes are critical for the weather forecasting, particularly for the diagnostic of atmospheric stability conditions that can lead to thunderstorm development. However, radiosonde observations (RAOBs) are temporally and spatially limited throughout the globe, promoting the use of satellite measurements. This paper assesses the applicability to the operational short-term weather forecasting of atmospheric stability indices and parameters (SIPs) derived from thermodynamic profiles retrieved from the National Oceanic and Atmospheric Administration Unique Combined Atmospheric Processing System (NUCAPS) using the Suomi National Polar-orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) radiances. For this purpose, we validated NUCAPS SIPs against SIPs derived from conventional and dedicated/reference RAOBs collocated with NUCAPS retrievals within a maximum radius of 50 km and ±1-h time difference, over midlatitudes (60°N–30°N) and tropics (30°N–30°S). Stability parameters evaluated include total precipitable water (TPW), lifted index, K-index, total-totals index, and Galvez–Davison index. NUCAPS TPW exhibited the highest level of statistical agreement with RAOBs, with the remaining NUCAPS SIPs exhibiting favorable results (linear correlations ranging between 0.65 and 0.85). Case studies over the Texas/Oklahoma region and the Northern Coast of Brazil demonstrate NUCAPS capability of generating reliable fields of atmospheric stability, as well as capturing synoptic-scale convective signatures, not feasible with RAOBs. Considering also the benefit of SNPP NUCAPS hyperspectral-infrared (IR) and microwave soundings available for both regions during critical early afternoon periods, our analysis supports the use of NUCAPS CrIS/ATMS SIPs as complementary nowcasting tools for the analysis of preconvective environments.

This paper continues an overview of the validation of operational profile retrievals from the Suomi National Polar-Orbiting Partnership (SNPP), with focus here given to the infrared (IR) ozone profile environmental data record (EDR) product. The SNPP IR ozone profile EDR is retrieved using the cross-track IR sounder (CrIS), a Fourier transform spectrometer that measures high-resolution IR earth radiance spectra containing atmospheric state information, namely, vertical profiles of temperature, moisture, and trace gas constituents. The SNPP CrIS serves as the U.S. low earth orbit (LEO) satellite IR sounding system and will be featured on future Joint Polar Satellite System (JPSS) LEO satellites. The operational sounding algorithm is the National Oceanic and Atmospheric Administration-Unique Combined Atmospheric Processing System (NUCAPS), a legacy sounder science team algorithm that retrieves atmospheric profile EDR products, including ozone and carbon trace gases, with optimal vertical resolution under nonprecipitating (clear to partly cloudy) conditions. The NUCAPS ozone profile product is assessed in this paper using extensive global $in\;situ$ truth data sets, namely, ozonesonde observations launched from ground-based networks and from ocean-based intensive field campaigns, along with numerical weather prediction model output. Based upon rigorous statistical analyses using these data sets, the NUCAPS ozone profile EDRs are determined to meet the JPSS Level 1 global performance requirements.

This paper provides an overview of the validation of the operational atmospheric vertical temperature profile (AVTP) and atmospheric vertical moisture profile (AVMP) environmental data record (EDR) products retrieved from the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS), two passive sounding systems onboard the Suomi National Polar-Orbiting Partnership (SNPP) satellite. The CrIS/ATMS suite serves as the U.S. low earth orbit (LEO) satellite sounding system and will span the future Joint Polar Satellite System (JPSS) LEO satellites. The operational sounding algorithm is the National Oceanic and Atmospheric Administration-Unique Combined Atmospheric Processing System (NUCAPS), a legacy sounder science team algorithm capable of retrieving atmospheric profile EDR products with optimal vertical resolution under nonprecipitating (clear to partly cloudy) conditions. The SNPP NUCAPS AVTP and AVMP EDR products are validated using extensive global in situ baseline data sets, namely, radiosonde observations launched from ground-based networks and ocean-based intensive field campaigns, along with numerical weather prediction model output. Based upon statistical analyses using these data sets, the SNPP AVTP and AVMP EDRs are determined to meet the JPSS Level 1 global performance requirements.

The Microwave Integrated Retrieval System (MiRS) has been the NOAA official operational microwave retrieval algorithm since 2007 and is run operationally on multiple microwave satellite/sensor systems. The algorithm is based on a 1-dimensional variational (1-DVAR) methodology, in which the fundamental physical attributes affecting the microwave observations are retrieved physically, including the profile of atmospheric temperature, water vapor, hydrometeors, as well as surface emissivity and temperature. A description of the mathematical basis and algorithm components are presented here, followed by examples of retrieved hydrometeorological parameters. Examples presented show that global estimates of surface rain rate from different satellites are generally consistent, and that the explicit treatment of both surface (e.g., emissivity) and atmospheric parameters in the forward radiative transfer model allows for accurate and consistent estimates over a variety of surfaces (e.g., ocean, land with different vegetation types, coastal regions). Validation and performance metrics using independent reference data indicate that the rainfall rates meet most NOAA operational requirements. Suggested avenues for future development and enhancements are also presented including an example of one planned operational enhancement that has led to improved light rain detection over land.

In this work, the current performance of the calibrated Joint Polar Satellite System (JPSS) Cross-track Infrared Sensor (CrIS) observations is reported. The CrIS instrument is currently on-board the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 spacecraft, and planned for the JPSS-2, -3 and -4 satellites. Presently, calibrated and validated CrIS observations, in the form of sensor data record (SDR) products, are being assimilated by operational NWP models and atmospheric retrieval systems. CrIS measurements from SNPP and NOAA-20 are expected to improve our understanding of the dynamics of the atmosphere due to the higher temporal and spatial coverage resulting from optimally blending the hyperspectral Earth observations. This work also reports recent improvements performed on the CrIS SDR products, including: 1) the implementation of the polarization correction, 2) the optimization of the spike detection and correction algorithm, and 3) the optimization of the lunar intrusion algorithm.

This work presents an analysis of the vertical resolution of the temperature and water vapor retrieved by the National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS) using averaging kernels as a diagnostic tool. One of the goals of an atmospheric profile retrieval system is to estimate the state of the atmosphere using an optimal set of observations containing independent information content in order to simultaneously minimize the retrieval error and maximize the vertical resolution. The averaging kernels are also used to compute the number of degrees of freedom of retrieved temperature and water vapor in order to estimate the number of useful independent observations contained in the infrared and microwave observations. Our work uses data obtained from the Suomi National Polar-orbiting Partnership (S-NPP) Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) to diagnose the vertical resolution of NUCAPS retrieved sounding products over different latitudes and seasons, and to support comparisons of retrievals against correlative radiosonde measurements. This work is expected to be extended to other NUCAPS products, since the generation of the averaging kernels is a functionality embedded as part of NUCAPS.

The Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) instruments aboard the Suomi National Polar-orbiting Partnership satellite provide high-quality hyperspectral infrared and microwave observations to retrieve atmospheric vertical temperature and moisture profiles (AVTP and AVMP) and many other environmental data records (EDRs). The official CrIS and ATMS EDR algorithm, together called the Cross-track Infrared and Microwave Sounding Suite (CrIMSS), produces EDR products on an operational basis through the interface data processing segment. The CrIMSS algorithm group is to assess and ensure that operational EDRs meet beta and provisional maturity requirements and are ready for stages 1–3 validations. This paper presents a summary of algorithm optimization efforts, as well as characterization and validation of the AVTP and AVMP products using the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis, the Atmospheric Infrared Sounder (AIRS) retrievals, and conventional and dedicated radiosonde observations. The global root-mean-square (RMS) differences between the CrIMSS products and the ECMWF show that the AVTP is meeting the requirements for layers 30–300 hPa (1.53 K versus 1.5 K) and 300–700 hPa (1.28 K versus 1.5 K). Slightly higher RMS difference for the 700 hPa-surface layer (1.78 K versus 1.6 K) is attributable to land and polar profiles. The AVMP product is within the requirements for 300–600 hPa (26.8% versus 35%) and is close in meeting the requirements for 600 hPa-surface (25.3% versus 20%). After just one year of maturity, the CrIMSS EDR products are quite comparable to the AIRS heritage algorithm products and show readiness for stages 1–3 validations.

In this work, an ultra-wideband planar inverted-F antenna is presented, fed by a convex-shaped structure. The antenna shows a measured ultra-wide bandwidth starting at 2.7 GHz and ending at 13 GHz, for a VSWR less than 2. The antenna shows an omnidirectional pattern at the X–Y plane with a very low out-of-roundness all over the bandwidth. The group delay of the antenna is very stable, obtaining a variation less than 1 ns. As a result, very low dispersion over the entire bandwidth is presented, as well as low cross-polarization level.

The CubeSat Infrared Atmospheric Sounder (CIRAS) is a proposed small satellite IR sounder developed in response to the challenges of high cost and possible data gaps for currently operational hyperspectral IR sounders, such as Atmospheric Infrared Sounder, Infrared Atmospheric Sounding Interferometer, and Crosstrack Infrared Sounder. A key objective of CIRAS is to demonstrate the technologies required for a low cost-to-orbit, operational IR sounder. CIRAS was designed by National Aeronautics and Space Administration’s Jet Propulsion Laboratory, with 625 channels measuring upwelling IR radiation of the Earth in the mid-wavelength IR spectrum region. Through observational system simulation experiments, the impact of assimilating CIRAS on global numerical weather prediction was assessed. CIRAS was simulated by applying the Community Radiative Transfer Model to profiles extracted from the Goddard Earth Observing System Model, Version 5 nature run for an afternoon polar orbiting sensor, and then assimilated by the National Centers for Environmental Prediction Global Data Assimilation System. Assimilating CIRAS improved global analysis and forecasts, when added to the currently operational observing configuration and to a data gap scenario.

[1] We present in this study the results obtained when applying a physical algorithm based on a variational methodology to data from the Advanced Technology Microwave Sounder (ATMS) onboard the Suomi National Polar-Orbiting Partnership (SNPP) for a consistent retrieval of geophysical data in all weather conditions. The algorithm, which runs operationally at the U.S. National Oceanic and Atmospheric Administration, is applied routinely to a number of sounders from the Polar-Orbiting Operational Environmental Satellites, the Defense Meteorological Satellite Program, and the European Meteorological Operational satellite constellations. The one-dimension variational (1DVAR) methodology, which relies on a forward operator, the Community Radiative Transfer Model, allows for solving the inversion of the radiometric measurements into geophysical parameters which have a direct impact on the brightness temperatures. The parameters that are produced by this Microwave Integrated Retrieval System algorithm include the atmospheric temperature T(p), moisture Q(p), and vertically integrated total precipitable water; and the surface skin temperature and emissivity as well as the hydrometeor products of nonprecipitating cloud liquid water and rain- and ice-water paths. In this algorithm, a simple postprocessing is applied to the 1DVAR-generated emissivity to derive cryospheric products (snow water equivalent and sea-ice concentration) when the data are measured over these surfaces. The postprocessing is also applied to the hydrometeors products to generate a surface rainfall rate. This comprehensive set of sounding, surface, hydrometeor, and cryospheric products generated from SNPP/ATMS is therefore radiometrically consistent, meaning that when input to the forward operator, it will allow the simulation of the actual brightness temperatures measurements within noise levels. The geophysical consistency between the products, also critical, is satisfied due to the physical approach adopted and the geophysical constraints introduced through the correlation matrix used in the variational system. The results shown in this paper confirm that the performances of all products are within the expected accuracy and precision figures and comparable to performances usually obtained with single-parameter-dedicated algorithms, with the added value that the inverted products are both radiometrically and geophysically consistent.

There remains large disagreement between ice-water path (IWP) in observational data sets, largely because the sensors observe different parts of the ice particle size distribution. A detailed comparison of retrieved IWP from satellite observations in the Tropics (+/- 30 degrees latitude) in 2007 was made using collocated measurements. The radio detection and ranging(radar)/light detection and ranging (lidar) (DARDAR) IWP data set, based on combined radar/lidar measurements, is used as a reference because it provides arguably the best estimate of the total column IWP. For each data set, usable IWP dynamic ranges are inferred from this comparison. IWP retrievals based on solar reflectance measurements, in the moderate resolution imaging spectroradiometer (MODIS), advanced very high resolution radiometer-based Climate Monitoring Satellite Applications Facility (CMSAF), and Pathfinder Atmospheres-Extended (PATMOS-x) datasets, were found to be correlated with DARDAR over a lar!

NUCAPS (NOAA Unique CrIS/ATMS Processing System) uses the same scientific foundation as AIRS team science algorithm. The NUCAPS is being run operationally at NOAA for Suomi-NPP CrIS/ATMS, Metop-A/B IASI/AMSUA/MHS and provides atmospheric profiles of temperature, moisture, ozone, carbon oxide, carbon monoxide, and Methane. The sounding team at NASA developed a retrieval system using principal component radiative transfer model (PCRTM). The NASA retrieval system can be applied under all weather conditions at single field of view (FOV). In this presentation, we will present the trace gaseous environmental data record from hyperspectral sounders.