Search

We present and discuss the details of the SMAP radiometer calibration that is used in the NASA/RSS ocean surface salinity algorithm. The values for antenna spillover, noise diode and reflector emissivity are fine-tuned to give accurate antenna and brightness temperature values for the global ocean and the Amazon rain forest. The calibration is dynamically adjusted to account for small calibration drifts over time. An adjustment of the thermal model for the reflector temperature is necessary in order to mitigate biases that occur when the SMAP spacecraft goes in and out of solar eclipse. An important test of the reflector emission is an analysis of SMAP brightness temperature differences between ascending and descending swaths. The radiometric calibration accuracy of the NASA/RSS SMAP salinity data set is better than 0.1 Kelvin, which is necessary for accurate ocean surface salinity retrievals.

The Moon is a good calibration source for the millimeter-wave radiometer onboard the Feng Yun-4 Millimeter (FY-4M) satellite. The temperature profiles of the lunar surface can be obtained by solving the one-dimensional heat conduction equation with the thermo-physical properties of regolith. Then, the loss tangent is fitting using the Chinese Chang’e-2 (CE-2) 37GHz brightness temperatures (TB) data against TiO2 abundances, which is derived from Clementine five-bands multispectral data. The calculated surface temperatures and the TBs are validated by Diviner infrared data and CE-2 37GHz TB data. With the theoretical analysis of the radiative transfer, the TBs at FY-4M frequencies of lunar center area is obtained for calibration. In addition, the abnormal thermal emission at "cold spots" should be excluded for calibration.

Miniaturized microwave radiometers deployed on nanosatellites in Low Earth Orbit (LEO) are now demonstrating the ability to provide science-quality weather measurements, such as the 3U Micro-sized Microwave Atmospheric Satellite-2A (MicroMAS-2A). The goal of having cost-effective miniature instruments distributed in LEO constellations is to improve temporal and geospatial coverage. The Time-Resolved Observations of Precipitations structure and storm Intensity with a Constellation of Smallsats (TROPICS) is a constellation of six 3U CubeSats, based on MicroMAS-2A, scheduled to launch no earlier than 2020. Each CubeSat hosts a scanning 12-channel passive microwave radiometer. TROPICS will improve temporal resolution to less than 60 minutes compared to larger satellites in polar orbit, such as NOAA-20 which hosts the Advanced Technology Microwave Sounder (ATMS) and has a revisit rate of 7.6 hours. [1] The improved refresh rate will provide high value observations of inner-core conditions for tropical cyclones [2]. In order to effectively use miniaturized microwave radiometers on small satellites such as MicroMAS-2A and TROPICS operationally, new approaches to calibration are needed to achieve state-of-the-art performance. Calibration on nanosatellite platforms present new challenges, as standard blackbody targets are too bulky to fit on 3U CubeSats. Instead, internal noise diodes are used for calibration, with long-term drifts measured on the order of 0.2% to 3.0% (approximately 0.4 K to 6.0 K) [4]. Blackbody calibration targets such as used on ATMS have 0.14 K error or better for warm calibration [3]. In order to provide state of the art calibration for CubeSats, methods must be developed to trend and correct noise diode drift. We develop a new way to continuously calibrate CubeSat constellations, such as TROPICS, by incorporating frequent and periodic solar and lunar intrusions as an additional source of information to counter noise diode drift. These solar and lunar intrusions also occur for existing satellites hosting microwave radiometers in polar orbits, but are much more infrequent than for the scanning payload on the TROPICS constellation, and are typically treated as an observational and calibration limiting constraint. The higher occurrence rate of intrusions for TROPICS motivates the novel idea of using the intrusions to support calibration. An algorithm is developed to compare expected effective brightness temperature from solar and lunar measurements to actual measured brightness temperatures. Future work includes developing a detailed error budget for the algorithm and testing the algorithm using actual sun and moon measurements taken by MicroMAS-2A and ATMS. In this paper we discuss background information, provide our approach, and show initial results.

Aquarius final product V5.0 has been released. The dataset includes close to four years of global radiometric measurements at L-band. The mission's objective was to monitor sea surface salinity, but other applications of its data over land and the cryosphere have been developed. For this reason, it is important to have accurate calibration over the full range of antenna temperatures from natural targets. It is also needed in order to combine Aquarius measurements with other L-band sensors. Aquarius calibration is strongly focused on the ocean. We present a research product which is part of the final release and aims at producing an accurate calibration from the low end (celestial sky) to the high end (land and ice) of the brightness temperature scale. We calibrate the Aquarius radiometers using measurements over the Sky and oceans and assess the new calibration using measurements over land.

Spaceborne microwave radiometers with high frequency channels (150 – 183 GHz) are important for retrieving many geophysical parameters such as snowfall, ice water path, and atmospheric water vapor profiles. In order to obtain accurate retrievals from the brightness temperature measurements, the radiometers must be properly calibrated. Several methods have been developed to analyze the on-orbit calibration, including comparisons with radiative transfer models, comparisons with radiosonde profiles, and cross-calibration with similar radiometers. This paper introduces a new method to calibrate high frequency channels that utilizes TB histograms. This new method gives an independent approach that can be used by itself to analyze radiometer calibration or in conjunction with other methods to corroborate results.

TabstractPDFeXpress. Due to redshift, the 21-cm signal is expected at frequencies 6. The Experiment to Detect the Global EoR Signature (EDGES) measures the sky-average, or global, brightness temperature spectrum in the frequency range 50–200 MHz, with the objective of characterizing the cosmological 21-cm signal. The EDGES instruments are single-antenna, absolutely-calibrated, total-power radiometers. They conduct observations from the Murchison Radio-astronomy Observatory in Western Australia.

Conventional satellite intercalibration for microwave imaging radiometers involves a linear two-point calibration approach, over cold ocean scenes and warm ends of the scene brightness temperatures, traditionally over tropical rain forest. Unfortunately, this approach ignores the possibility of non-linear radiometer transfer function, which is often important. This paper discusses a new tool developed to identify large-scale homogeneous desert scenes as possible third calibration targets with brightness temperatures that fall between the conventional cold and warm earth scenes. Previously a prototype “ShowMask” procedure was developed over continental Australia using 10, 18 and 37 GHz Vertical and Horizontal polarized brightness temperatures from GPM Microwave Imager (GMI) data. This paper focus on extending this tool to global scale and including 89 GHz channel in the analysis. Further, by applying the mask, we examine intercalibration results over selected desert targets using GMI-TMI and GMI-AMSR-2 match-ups. Initial results indicate a scene temperature dependence of calibration factor particularly for horizontally polarized channels.

High emissivity temperature-controlled microwave blackbodies, or calibration targets, are often used as brightness temperature reference sources for radiometer calibration. Calibration targets are, in practice, often viewed from a range of angles due to the scanning nature of operational radiometers (e.g. a conical scanning instrument). Ideally, the calibration target has view-angle-independent emissivity of unity, but any deviation from ideal can bias the brightness temperature radiating from the target. Microwave emissivity is not a directly-measurable quantity, and instead must be inferred through measurements of reflectivity. We measure reflections from calibration targets by quantifying the magnitude of the standing wave formed by the target as it is linearly stepped through space at sub-wavelength increments. We present monostatic reflectivity results over a range of incidence angles for two types of calibration targets; a periodic pyramidal absorber array and a conical cavity blackbody. Measurements are presented at 165.5 GHz and 183.3 GHz, two channels of interest for environmental remote sensing. We find that the pyramidal array has higher reflectivity than the conical cavity at both frequencies and across the range of incidence angles. Additionally, we find that the pyramidal array has a larger range of reflectivity across the range of incidence angles. The reflectivity magnitude decreases as a function of incidence angle for both geometries, with local maxima at normal incidence except for the pyramidal array at 165.5 GHz. The considerable angular variation in reflectivity observed for the pyramidal array could potentially cause significant calibration bias as large as 0.12 K.

The Tropical Rainfall Measurements Mission (TRMM) Microwave Imager (TMI), has served as the radiometric transfer standard for the TRMM constellation radiometers for over 17 years. The final legacy processing for the TMI is in progress for the TMI 1B11 Tb Version-8 (V8), which will be released in late 2017. This paper presents a radiometric evaluation of the Tb differences between the current TMI Version-7 (V7) and the newly derived V8 dataset. For this evaluation, we perform an inter-satellite radiometric calibration (XCAL) between the Global Precipitation Mission Microwave Imager (GMI) Tb product and TMI Tb products for both V7 and V8. The results of XCAL using different datasets are compared to assess the TMI V8 calibration biases relative to V7.

The Visible-Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft as a primary sensor was launched October 28, 2011. There are 22 VIIRS bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). An on-orbit On-Board Calibrator BlackBody (OBCBB) is used as the TEB calibration source that tracks the detector gain change on a scan-by-scan basis. A thermal model to account for internal sensor emission is used in both the OBCBB derived gain calibration and Earth View (EV) radiance and brightness temperature retrievals. This thermal model uses pre-launch calibration coefficients to convert detector response into radiance and internal VIIRS cavity thermistors to estimate the sensor's internal emission from various optical surfaces. The inputs to the thermal model have uncertainties which introduce errors in both the gain correction and the EV retrievals. This paper will discuss the impacts of the thermal model uncertainties on the VIIRS calibration.

The Thermal InfraRed Sensor (TIRS), an infrared (IR) radiometer developed at Centro de Astrobiología, is one the sensors that compose the Mars Environmental Dynamics Analyzer (MEDA) onboard NASA?s Mars 2020 mission. It will measure the net thermal infrared radiation, reflected solar radiation at the surface, atmosphere temperature and surface skin brightness temperature using five different channels. The present paper provides a brief description on TIRS design and channels requirements. Then, a detailed presentation of sensor model equations and a sensitivity analysis to model uncertainties are included. Finally, accuracy and resolution calculus for each channel versus operational temperature is presented. The calculus is performed based on sensitivity equations and the estimated values for different uncertainties source

In this work, it is present a method to convert atmospheric opacity from 350 μm tipper radiometers to precipitable water vapour (PWV). The dynamic range of these tippers is limited and therefore, their use is confined to sites with very low PWV such as the Chilean Altiplano, with altitudes higher than 5000 m. The main scientific drivers behind this procedure are long term climatological studies in the region and water vapour concentration for calibration of radio-astronomical data. The method presented here differs from a previous version in that the ground temperature at the time of the opacity measurement is now included as input to the procedure, as opposed to the use of long-term temperature averages. This new procedure solves the problem of induced false anomalies in the resultant PWV, allowing the results to be used for PWV studies at any timescale, e.g. from hours to decades. In addition, these improvements notably increase the accuracy of the conversion, when the results are compared with other independent measurements taken simultaneously and with the instruments physically co-located.

estimating the regolith depth from brightness temperature (TB) measured by a multi-channel radiometer at 3GHz, 7.8GHz, 19.35GHz and 37GHz. To establish the accurate microwave radiation or scattering model of lunar surface, firstly we need to determine an accurate model of dielectric constant of lunar regolith. However, until now there is no model of dielectric constant suitable for microwave band between 3GHz–37GHz.In this paper, we extract the normalized temperature deviation τ from CE-1 TB data, which filter out the diurnal variation and the impact of latitude. Then we established a new dielectric constant model for microwave band, through analyzing the different relationship that between τ and the content of iron and titanium. The parameters in the model are inverted by comparing the TB measured and the TB calculated. At last, we compared the proposed dielectric constant model with the measured results of lunar regolith samples.

The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) had been operated in special slow rotation mode to obtain continuous brightness temperatures for the inter-comparison with those of AMSR2 on the Global Change Observation Mission-Water (GCOM-W) for three years. Although its observation coverage is sparse and some calibration uncertainties exist, the data are still very useful for straightforward inter-comparison.

A robust XCAL double difference (DD) approach for radiometric calibration has been successfully applied between the TRMM Microwave Imager, TMI, (previous calibration transfer standard for NASA's Precipitation Measuring Mission) and a number of precipitation measuring radiometers in polar sun-synchronous orbits. Now that the TRMM Mission has ended (April 2015), the radiometric transfer standard was changed from TMI to the current GPM Microwave Imager (GMI). The use of an ocean radiative transfer model (RTM) is an integral part of our XCAL DD approach. Because the RTM physics is imperfect and because the environmental parameters are likewise only estimates of their true values, it is important to assess the sensitivity of the derived brightness temperature biases to these limitations. Therefore, in this paper, we conduct the inter-calibration between GMI and other constellation satellite microwave radiometers using the XCAL DD approach with two different ocean surface emissivity models. Results are presented that demonstrate the robustness of the XCAL DD approach for multiple instruments over a wide range of channel frequencies.

The method of two-point calibration of multi-band microwave radiometer is investigated in this paper. The radiometer calibration results are verified with synchronized measurements, compared between the thermometer and the calibrated radiometer for the 6.6GHz, 13.9GHz, 19.35GHz, 22.235GHz and 37GHz bands. Results show that the root-mean-square error is below 0.5K in each channel for both brightness temperature measured by radiometer and the temperature from thermometer. Therefore, assuming good radiometer receiver linearity, the calibration coefficient of radiometer obtained by two-point calibration is valid in the dynamic range of measurement. The error induced by parameter variation and the system error have been analyzed. Absolute calibration accuracy of brightness temperature is better than 1K within the radiometer measuring range.

MWS is a total power radiometer that has been selected by ESA as part of the MetOp-SG programme, with Airbus Defence and Space Ltd, chosen as the instrument prime contractor. MWS measures the brightness temperature at various altitudes and delivers calibrated and geo-located atmospheric temperature and water-vapour sounding data, in all weather and illumination conditions. MWS is thus an essential instrument for the provision of operational meteorology, offering significant improvements in measurement performance over MetOp First Generation and indeed all microwave sounders currently operating on meteorological satellites. This paper describes the MWS instrument key design features, predicted performance, development status of associated key technology developments, both at equipment and instrument level, and the current status of equipment procurement and instrument MAIT, including the MWS calibration plan. MWS data processing to level 1b is also described.

The Visible-Infrared Imaging Radiometer Suite (VIIRS) on-board the Suomi National Polar-orbiting Partnership (SNPP) spacecraft as a primary sensor was launched October 28, 2011. It has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). The TEBs are calibrated on-orbit using the On-Board Calibrator BlackBody (OBCBB) as a thermal source every scan to track the detector gain change. A thermal model is used in both the OBCBB derived gain calibration as well as in other corrections to the Earth View (EV) radiance and brightness temperature retrievals. This thermal model uses prelaunch calibration coefficients to convert detector response into radiance as well as VIIRS cavity thermistors to estimate the sensor's internal emission contributions. The inputs to the thermal model have uncertainties which introduce errors in both the gain correction and the EV retrievals. This paper will discuss the impacts of the thermal model uncertainties on the VIIRS calibration.

SMOS is the acronym for the Soil Moisture and Ocean Salinity mission by the European Space Agency (ESA) [1]. Its single payload, the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), was successfully launched in November 2009 to provide a continuous flow of fully polarimetric brightness temperature images. After more than five years of operation, SMOS has proven to be highly useful for a variety of scientific applications related to soil moisture over land, ocean salinity and winds over ocean, as well as specific studies over the ice covered surfaces [2][3]. Along these years of operation, SMOS calibration and imaging algorithms have undergone a continuous evolution to further improve the accuracy of the retrieved geophysical parameters. These improvements are particularly useful in Ocean Salinity applications where accuracy and stability requirements are very demanding and spatial and temporal averaging is required to achieve SMOS mission objectives. This paper analyzes the impact on ocean images of the so-called “floor error”, an image reconstruction artifact that, currently, is significant on the 3rd and 4th Stokes parameters. Error mitigation techniques are evaluated by computing spatial bias over the ocean and also by providing a 4th Stokes global error map over the ocean that takes into account SMOS full spatial and temporal averaging capabilities.

A constellation of disparate radiometers is inherent to the Global Precipitation Measurement (GPM) mission concept. The task of the Intersatellite Calibration Working group is to generate adjustments to make the measurements of all these radiometers physically consistent. A key role of the GPM Microwave Imager (GMI) on the GPM Core satellite is to serve as a transfer standard among the constellation radiometers. The TRMM Microwave Imager (TMI) has served this role during the development phase and for interim corrections early in the GPM mission. The stability of GMI appears to be very good and a physically based calibration has been generated that appears to be accurate at the 1K level or better.

We discuss work at NIST aimed at developing a passive microwave brightness temperature standard. By reducing uncertainty, we can provide better calibrations for future weather and climate-monitoring radiometers. We discuss the calibration procedure used, measured data, and various theoretical and simulated results that have led to an improved understanding of the various uncertainty contributions in the measurement. We overview a Monte Carlo simulation to determine the uncertainty in target brightness temperature as a function of measurement distance and target size. We also discuss other future improvements including an improved blackbody design. The achievable calibration source brightness temperature uncertainty is expected to be reduced from the current 0.7 to 1.0 K from 18 to 65 GHz to less than 0.3 K.