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Accurate measurements of ice hydrometeors are required to improve the representation of clouds and precipitation in weather and climate models. In this study, a newly developed, synergistic retrieval algorithm that combines radar with passive millimeter and sub-millimeter observations is applied to observations of three frontally generated, mid-latitude cloud systems in order to validate the retrieval and assess its capabilities to constrain the properties of ice hydrometeors. To account for uncertainty in the assumed shapes of ice particles, the retrieval is run multiple times while the shape is varied. Good agreement with in situ measurements of ice water content and particle concentrations for particle maximum diameters larger than 200 µm is found for one of the flights for the large plate aggregate and the six-bullet rosette shapes. The variational retrieval fits the observations well, although small systematic deviations are observed for some of the sub-millimeter channels pointing towards issues with the sensor calibration or the modeling of gas absorption. For one of the flights the quality of the fit to the observations exhibits a weak dependency on the assumed ice particle shape, indicating that the employed combination of observations may provide limited information on the shape of ice particles in the observed clouds. Compared to a radar-only retrieval, the results show an improved sensitivity of the synergistic retrieval to the microphysical properties of ice hydrometeors at the base of the cloud. Our findings indicate that the synergy between active and passive microwave observations may improve remote-sensing measurements of ice hydrometeors and thus help to reduce uncertainties that affect currently available data products. Due to the increased sensitivity to their microphysical properties, the retrieval may also be a valuable tool to study ice hydrometeors in field campaigns. The good fits obtained to the observations increase confidence in the modeling of clouds in the Atmospheric Radiative Transfer Simulator and the corresponding single scattering database, which were used to implement the retrieval forward model. Our results demonstrate the suitability of these tools to produce realistic simulations for upcoming sub-millimeter sensors such as the Ice Cloud Image or the Arctic Weather Satellite.

In order to cover the warm end of Earth-scene brightness temperature (TB) range of passive microwave radiometers, intercalibration over warm scenes is necessary. This article presents a methodology to intercalibrate the microwave radiation imager (MWRI) on the Chinese second-generation meteorological satellite Fengyun 3C (FY-3C) with the Global Precipitation Measurement (GPM) Microwave Imager (GMI) over the warm scenes of dense forests using the double-difference (DD) method. Based on the microwave radiative transfer model (RTM), an intercalibration method is developed, in which a modified land surface emissivity (LSE) model for dense forests is proposed. The forests with optically thick canopy are identified in terms of polarization TB differences and normalized difference vegetation index (NDVI) extracted from the latest vegetation product of Moderate-Resolution Imaging Spectroradiometer (MODIS). The matching TBs between FY-3C MWRI and GMI over dense forest warm scenes are collected and analyzed together with the TBs over ocean surfaces obtained by Zeng and Jiang (2020). The results show that: 1) FY-3C MWRI's observations are generally underestimated, and the intercalibration biases are polynomial functions of observations; 2) the intercalibration biases at the warm end are relatively smaller than those at the cold end; and 3) the calibration in the ascending orbits (MWRIA) is relatively better than that in the descending orbits (MWRID). At the tropical rain forest scene TBs defined in this work, the intercalibration biases (mean ± standard deviation at the mean) in the FY-3C MWRI channels of 10 V, 10 H, 18 V, 18 H, 23 V, 36 V, 36 H, 89 V, and 89 H are, respectively, -1.3 ± 0.7, -1.9 ± 1.1, 1.6 ± 0.6, 2.5 ± 0.8, -0.2 ± 0.5, -2.0 ± 0.6, -2.4 ± 0.7, -0.2 ± 0.6, and -0.1 ± 0.6 K for the ascending orbits, while they are, respectively, -4.0 ± 0.8, -5.4 ± 1.2, -1.4 ± 0.7, -1.2 ± 0.8, -2.9 ± 0.5, -4.9 ± 0.7, -5.5 ± 0.7, -2.7 ± 0.8, and -2.3 ± 0.7 K for the descending orbits. The in-orbit calibration coefficients of GMI are successfully transferred to FY-3C MWRI.

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station (ISS) on June 29, 2018, and currently provides the highest spatial resolution thermal infrared (TIR) data (38 m x 69 m) available from space. In this study, we validated the ECOSTRESS level-2 Land Surface Temperature (LST) and emissivity product at fourteen global sites to Stage-1 status. Two primary methods are recommended for the validation of LST data: Temperature-based (T-based) and Radiance-based (R-based) methods. The T-based method requires calibrated measurements of the ground leaving radiance concurrent with the satellite overpass. In contrast, the R-based method uses a radiative closure simulation with external atmospheric profiles and an a priori knowledge of surface emissivity. Using these standard methods, we validated 1139 ECOSTRESS clear-sky observations between August 1, 2018, and March 31, 2020. For LST, the results show good agreement with ground-based measurements with an average root mean square error (RMSE) of 1.07 K, mean absolute error (MAE) of 0.40 K, and r²>0.988 at all sites. However, a cold bias of ~0.75 K was identified for temperatures below 295 K linked to calibration issues that will be addressed in future reprocessing of the data. Retrieved emissivity comparisons with laboratory spectra had an RMSE of 0.023 (2.3%) for all bands on average. With the decommissioning of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on Terra in 2023, the multispectral and high-spatial-resolution characteristics of ECOSTRESS data serve as a pathfinder to the National Aeronautics and Space Administration's (NASA) Surface Biology and Geology (SBG) designated observable with an expected launch in 2026.

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.

FengYun-3C (FY-3C) is the second-generation polar-orbiting meteorological satellite in China. As one of the most important microwave payloads deployed onboard FY-3C, microwave radiation imager (MWRI) has been continuously observing radiance originating from land and sea surface and supports numerical weather predictions at regional and global scales. With a long-term monitoring of the cold-end reference, MWRI onboard FY-3C was found suffering from discontinuous observations due to its temporary power-OFF/power-ON in the years of 2015 and 2018, resulting in anomalous brightness temperature (TB) jump up to 2–3 K in magnitude at some channels. Analysis of the operating status of FY-3C MWRI indicated that deviation of the receiver system from its optimal operating status affects the nonlinearity characteristics significantly. A correction algorithm, which relates nonlinearity to the autogain control (AGC) operating voltage of the sensor, is thus proposed on the basis of on-ground thermal/vacuum (T/V) test results in the prelaunch phase in order to mitigate the calibration anomalies of FY-3C MWRI. Nonlinearity correction of FY-3C MWRI is further corroborated by comparisons of simultaneously overlapping observations of global precipitation measurement (GPM) microwave imager (GMI). The results demonstrated that after nonlinearity correction the performance of FY-3C MWRI has been improved at all channels except for the 36-V channel where technical failures have been detected since October 2016.

The absolute radiometric accuracy of thermal infrared channels of the Advanced Geosynchronous Radiation Imager (AGRI) onboard the FengYun-4A (FY4A) satellite was assessed with field experiment data in a vicarious calibration on 18, 2019, and August 20, 2019, in Lake Qinghai. Continuous water temperature records were collected by an unmanned surface vehicle equipped with a radiometer during the experimental period. We proposed a spectral matching method based on atmospheric transfer code to create consistent equivalent spectral radiance, and the results predicted by atmospheric transfer simulation were convolved with instrument response functions to obtain predicted brightness temperature for comparison with satellite-derived temperature. Our results indicated that AGRI had an average temperature bias of 0.12 K with an RMSE of 0.17 and 0.61 K with an RMSE of 0.22 K in band 12 and band 13 on August 18, while these biases decreased to −0.01 K with an RMSE of 0.13 and −0.48 K with an RMSE of 0.17 K on August 20, respectively. This radiometric accuracy indicated that AGRI TIR bands are well functional compared with their preflight requirement of less than 1 K. The uncertainty analysis also suggested that atmospheric conditions would alter the calibration accuracy by influencing the transmittance and path thermal radiance. Meanwhile, cloud cover also requires more attention to select the appropriate concurrent satellite pixels to reduce the possible cloud edge effects. It is important and necessary for FY4A AGRI to conduct more intense automatic observations and obtain more data to improve the accuracy of radiometric calibration and monitor the operational status of satellite instruments.

International audience; The electrical-substitution cryogenic detector BOLometer for Use in the range of X-rays (BOLUX), which was developed some years ago at CEA/DAM, has been set up and restarted now at LNHB. It has been used for the primary measurement of the intensity (total energy per unit time) of monochromatic synchrotron beams in the energy range from 3 to 30 keV. These well-determined photon beams have been employed for the efficiency calibration of two photodiodes in terms of current induced per unit optical power at different photon energies. In a final step, we explored the possibility to use these primary calibrated photodiodes to determine the efficiency curve of an energy dispersive spectrometer based on a semiconductor detector (Silicon Drift Detector) using less intense monochromatic photon fluxes. The characteristics of the radiometer BOLUX and its principle of operation are described, and the measurements carried out at the synchrotron beamline are presented, including the determination of the beams' intensities, the direct calibration of photodiodes with respect to BOLUX and the use of one of those photodiodes as a standard transfer for the calibration of the SDD.

International audience; Traditional efficiency calibration of spectrometers is based on the measurement of sources of radionuclides calibrated in activity and whose emission probabilities are known beforehand. However, there are regions of the spectrum where there is a lack of reliable tabulated emission probabilities. Furthermore, if one aims to improve the measurement of emission probabilities, this approach implies the use of the same parameters that one intends to measure. The solution to these limitations is the use of photon fluxes whose intensity has been measured in an absolute way by another technique. Photodiodes constitute a very suitable choice for measuring the intensity of these fluxes, but they need to be previously calibrated in terms of amount of current generated per unit power. In this work, we present the calibration of several photodiodes with a monochromatic photon beam whose intensity is previously measured in an absolute way by a cryogenic electrical-substitution radiometer.Cryogenic detectors are based on the measurement of the temperature rise experienced by an absorber when the radiation interacts with it. In electrical-substitution radiometers, the amount of incident energy is determined by finding the electrical power that must be dissipated in the material to get the same temperature rise obtained during the photonic heating. In order to monitor temperature, a thermistor is polarized by a constant current, so the diminution of resistance induced by the temperature rise implies a decrease of its potential.In this work, the intensity of monochromatic beams is measured by means of the radiometer BOLUX (BOLometer for Use in the field of X-rays). This measurement is corrected by transmission, escape and scattering in BOLUX's absorber. Afterwards the current generated in the photodiode is measured when the same beam impinges on it, in order to obtain its efficiency at that photon energy. Measurements were performed at two different beamlines (Métrologie and PUMA) at synchrotron SOLEIL, covering an energy range from 3 keV to 60 keV. Absolute calibration of photodiodes also plays an important role in all those applications that rely on well-characterized photon fluxes, such as reference-free X-ray spectrometry.

In this paper, we present the design and implementation tests of a water vapor radiometer (WVR) suitable for very long baseline interferometry (VLBI) observation. We describe the calibration method with an analysis of the sources of measurement errors. The experimental results show that the long-term measurement accuracy of the brightness temperature of the water vapor radiometer can reach 0.2 K under arbitrary ambient conditions by absolute calibration, receiver gain error calibration, and antenna feeder system temperature noise error calibration. Furthermore, we present a method for measurements of the calibration error of the oblique path measurement. This results in an oblique path wet delay measurement accuracy of the water vapor radiometer reaching 20 mm (within one month).

International audience; Vegetation optical depth (VOD) retrieved from microwave remote sensing techniques has been used as an important proxy for monitoring the vegetation dynamics at large scales. In a first study we developed a new X-VOD indice from inversion of the X-MEB model from the Microwave Scanning Radiometer 2 (AMSR2, 2012-present) observations. The Advanced Microwave Scanning Radiometer for EOS (AMSR-E, 2002–2011) and AMSR2 share many characteristics, such as local crossing time, incidence angle, frequency at X-band, etc, which makes it possible to produce a consistent long-term X-VOD product over a long period spanning from 2002 to present. The objective of this study was to merge the AMSR-E and AMSR2 observations in order, in a second step, to produce a consistent long-term X-VOD product spanning over the combined periods of AMSR-E and AMSR2.The main challenges in retrieving a consistent X-VOD data set from AMSR-E and AMSR2 are that (i) there is a bias between observations from the two sensors; and (ii) the lack of overlapping observations between the two sensors makes it impossible to achieve a direct inter-calibration. Here, to overcome this problem, we used AMSR-E slow rotation data (AMSR-E L1S), which has similar characteristics as AMSR-E and provided observations concurrently with AMSR2, as a bridge to calibrate the AMSR-E brightness temperature (TB) observations with AMSR2 TB.As our main objective in this TB calibration study was to produce a consistent long-term AMSR-E/AMSR2 X-VOD product, we evaluated the retrieved X-VOD product based on different inter-calibration, either global-based or pixel-based, methods. Both AMSR-E and AMSR2 X-VOD were evaluated against the Aboveground Biomass (AGB), Leaf Area Index (LAI) and the Normalized Difference Vegetation Index (NDVI). The results suggest that global-based inter-calibration methods using homogeneous and temporally stable land covers (Evergreen Broadleaf Forests and Snow and Ice) as reference calibration data sets provided the best results. For instance, the spatial relationships between X-VOD and AGB/LAI/NDVI are highly consistent over the AMSR-E and AMSR2 periods after the calibration work. This study laid a solid foundation for monitoring the dynamics of X-VOD, as a proxy of AGB, over the combined periods of AMSR-E and AMSR2 sensors (almost 20 years).

The Multi-View, Multi-Channel, Multi-Polarisation Imaging (3MI) instrument is a passive scanning radiometer dedicated to aerosol characterisation, air quality and numerical weather prediction, as well as climate monitoring and more generally characterisation of the microphysical properties of the atmosphere, including clouds. The 3MI mission has heritage from the POLarization and Directionality of the Earth's Reflectances (POLDER) on-board the ADEOS and PARASOL satellites. Compared to POLDER, 3MI has improved spatial coverage, higher spatial resolution, and an expanded spectral range with more spectral bands in the reflective part of the spectrum, all bands being polarised (except absorption bands). It is scheduled for launch on the EPS-SG platform in 2024. 3MI’s mission is to provide images of the Earth Top-Of-Atmosphere outgoing radiance for 12 different spectral bands (from 410nm to 2130nm), with 3 different polarisers (-60°, 0° and +60°), and 14 angles. The design consists of two optical heads (SWIR and VNIR) composed by a detector along with a filter and polariser rotating wheel and a wide field-of-view optics. The multi-view is achieved by several successive overlapping acquisitions of the same Earth-Atmosphere target under different angles thanks to the instrument large field of view. Using the experience acquired for the POLDER missions, CNES is cooperating with EUMETSAT and is providing the necessary analysis and expertise for the in-flight calibration and/or validation of several key parameters, both for geometric and radiometric aspects. Here we present the different methodologies that will be used to achieve that goal.

Clouds and the Earth’s Radiant Energy System (CERES) instruments are scanning radiometers on board the Terra, Aqua, NPP and NOAA20 satellites that use thermistor bolometers as detectors, with a sampling rate of 0.01s. During calibration testing a slow mode of detectors was found which had a magnitude of about three percent of the signal, and a characteristic time of 0.3 sec. To reduce the effect of this mode, a numerical filter was introduced. However, an analysis of the data from the CERES instruments aboard the Terra and Aqua satellites showed a difference of radiances in the forward scan compared to radiances from the backward scan. This difference was due to the fact that parameters of the digital filtered derived based on calibration data were not characterized correctly. A focus of this work is to show results of setting slow mode filter parameters based on in-flight data. A gradient-based minimization strategy is employed to effectively find the filter parameters for each instrument to meet the performance goal, namely the divergence of 0.15% for viewing zenith angles

Continuous observation and quantitative retrieval of aerosol backscatter coefficients are important in the study of air quality and climate in metropolitan areas such as New York City. Ceilometers are ideal for this application, but aerosol backscatter coefficient retrievals from ceilometers are challenging and require proper calibration. In this study, we calibrate the ceilometer (Lufft CHM15k, 1064 nm) system constant with the molecular backscatter coefficient and evaluate the calibrated profiles with other independent methods, including the water-phase cloud method and comparison with the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) attenuated backscatter coefficient profile. Multiple-day calibration results show a stable system constant with a relative uncertainty of about 7%. We also evaluate the overlap correction for the CHM15k ceilometer (provided by Lufft) with a Vaisala CL-31 ceilometer, and the results show good consistency between two ceilometers’ range-corrected signal (RCS) profiles above 200 m. Next, we implement a forward iterative method to retrieve aerosol backscatter coefficients from continuous ceilometer measurements. In the retrieval, the lidar ratio is constrained by the co-located NASA AERONET radiometer aerosol optical depth (AOD) retrieval and agrees with the AERONET lidar-ratio products, derived from aerosol microphysical parameters. The aerosol backscatter coefficient retrievals are validated with co-located elastic-Raman lidar retrievals and indicate a good correlation (R2≥0.95) in the planetary boundary layer (PBL). Furthermore, a case study shows that the ceilometer retrieved aerosol extinction coefficient profiles can be used to estimate the AOD of the PBL and the aloft plumes. Finally, simulations of the uncertainty of aerosol backscatter coefficient retrieval show that a calibration error of 10% results in 10–20% of relative error in the aerosol backscatter coefficient retrievals, while relative error caused by a lidar-ratio error of 10% is less than 4% in the PBL.

Detecting signals from the Cosmic Dawn using “global” experiments requires an unprecedented level of instrumental calibration, especially to remove possible systematics which arise from the interaction between the antenna and receiving systems. In this paper we describe the calibration methods which can be applied to a range of experiments including the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH) which is an instrument being designed to detect such signals. We use the functions described by noise wave parameters in a fast Bayesian pipeline to determine physical calibration coefficients which can describe the systematics. This approach when used in the field and on the fly could calibrate the absolute temperature measured by the antenna down to sub-kelvin levels. In this paper we present the Bayesian framework and simulated results of our pipeline using models derived from early laboratory measurements. A major advantage of this approach is that we can properly model the uncertainties in our measurement system.

In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg–Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C.

Solar radiation-based calibration (SRBC) has been used to assess radiometric calibration of earth remote sensing sensors using a source with the same spectral source that is expected during the instrument's operation. The approach has been shown capable of providing high-accuracy radiance calibration, the merits of which have been proven for laboratory and field instruments, as well as serving as a preflight calibration option for airborne and spaceborne imagers. The current work presents multiple SRBC results for a small portable transfer radiometer that was developed as part of an effort to ensure the quality of upwelling radiance at automated test sites used for vicarious calibration in the solar reflective. The results are used to develop an updated absolute uncertainty budget for the SRBC method. Comparisons of the SRBC method to standard source-based laboratory calibrations and a detector-based method recently developed for the CLARREO Pathfinder mission.

The Joint Polar Satellite System 3 (JPSS-3) is the follow-on to the Suomi-National Polar-orbiting Partnership (S-NPP), National Oceanic and Atmospheric Administration 20 (NOAA-20) and JPSS-2 satellites. A primary sensor on the S-NPP, NOAA-20 and JPSS satellites, the Visible-Infrared Imaging Radiometer Suite (VIIRS) has 22 bands covering a spectral range of 0.412-12.0 µmwith spatial resolutions of 742mand 371m for the moderate and imaging bands, respectively. VIIRS provides radiometrically calibrated Sensor Data Records (SDRs) using a combination of pre -launch characterization and on-orbit calibration sources, such as the Solar Diffuser (SD) for the Reflective Solar Bands (RSBs) and an On-Board Calibrator BlackBody (OBCBB) for the Thermal Emissive Bands (TEBs), for gain correction. Each VIIRS sensor build goes through extensive pre-launch characterization at vendor’s testing facility. This includes ambient, vibration, electro-magnetic interference and thermal vacuum (TVAC) environments. Each test environment is used to characterize different performance parameters for sensor functionality and on-orbit applications. This paper will focus on the JPSS-3 VIIRS pre-launch TEB calibration measured during the sensor level TVAC testing in late 2020. This will include the dynamic range, noise equivalent delta temperature, gain characterization and radiometric retrievals as well as a brief comparison with heritage VIIRS sensor TVAC results.

The Visible-Infrared Imaging Radiometer Suite (VIIRS) is a primary sensor on-board the Suomi-National Polar-orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration 20 (NOAA-20) spacecrafts, launched in October 2011 and November 2017, respectively. VIIRS has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). Both the RSBs and TEBs use a combination of pre-launch and on-orbit calibration information to provide accurate radiance, reflectance, and brightness temperature Sensor Data Records (SDRs). An on-orbit comparison of the S-NPP and NOAA-20 RSB SDR radiances, using ground calibration sites and vicarious methods such as deep convective clouds, show that there is a ~2% bias between the two sensors for all the reflective solar bands. Additionally, the M5 (0.672 μm) and M7 (0.865 μm) bands of Suomi NPP VIIRS have larger biases. An investigation of each sensor’s pre-launch and on-orbit calibrations was performed to ascertain the root cause of the sensor-to-sensor bias. This paper will discuss the VIIRS methodologies for both pre-launch and on-orbit calibration and how they affect the SDR product performance, as well as the most likely cause for the bias . In particular, the characterization of the reflectance of the Solar Diffuser and its reflectance variation versus view geometry was performed with different methodologies for S-NPP and NOAA-20 VIIRS. It is anticipated that J2, J3 and J4 VIIRS sensors will behave more similarly to NOAA-20 than S-NPP VIIRS due to the methodology for the SD characterization being consistent with NOAA-20.

The MErcury Radiometer and Thermal Infrared Spectrometer (MERTIS) is an instrument to study the mineralogy and temperature distribution of Mercury’s surface in unprecedented detail. MERTIS was proposed in 2003 as payload of the Mercury Planetary Orbiter spacecraft of ESA-JAXA BepiColombo mission and will reach Mercury in 2025. MERTIS will map the whole surface at 500 m scale, combining a push-broom IR grating spectrometer (TIS) with a radiometer (TIR) sharing the same optics, instrument electronics and in-flight calibration components for the whole wavelength range of 7- 14μm (TIS) and 7-40μm (TIR). MERTIS successfully completed its planned tests of the Near-Earth Commissioning Phase (NECP) between 13 and 14 November, collecting thousands of measurements of its internal calibration bodies and deep space. The data collected during NECP, are being used to verify the operational performances of onboard sub-modules, in particular the spectrometer and radiometer sensor sensitivity. A preliminary look at calibrated data shows a performance comparable with ground-based measurements and no appreciable performance loss or misalignment. The next important dates for MERTIS are the Earth/Moon flyby on 6 April 2020 and the first Venus flyby on 12 October 2020. Both those encounters will be important both for further instrument calibration refinement and for possible unprecedented measurement in the thermal infrared of the Moon and Venus.

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a twosided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudoinvariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

A system for calibrating single photon detector efficiency that is traceable to the SI through a state-of-the-art classical optical fibre radiometer has been developed and is in the process of being vetted as a calibration service at the National Institute of Standards and Technology (NIST). The method of calibration is direct substitution to power meters relative to NIST's optical fibre cryogenic primary standard and builds on the existing measurement infrastructure for the calibration of optical fibre power meters. Recent improvements to the optical fibre cryogenic radiometer make it more robust and deployable. The traceability of the single photon detector calibration service under development to these classical measurements is discussed, along with a description of the technique used in this calibration service to calibrate the detection efficiency of single photon detectors. Finally, we discuss work on the development of these technologies so that in the future they may be deployable to the point-of- use.

A digital-correlation full-polarized microwave radiometer is an important passive remote sensor, as it can obtain the amplitude and phase information of an electromagnetic wave at the same time. It is widely used in the measurement of sea surface wind speed and direction. Its configuration is complicated, so the error analysis of the instrument is often difficult. This paper presents a full-polarized radiometer system model that can be used to analyze various errors, which include input signal models and a full-polarized radiometer (receiver) model. The input signal models are generated by WGN (white Gaussian noise), and the full-polarized radiometer model consists of an RF front-end model and digital back-end model. The calibration matrix is obtained by solving the overdetermined equations, and the output voltage is converted into Stokes brightness temperature through the calibration matrix. Then, we use the four Stokes parameters to analyze the sensitivity, linearity, and calibration residuals, from which the simulation model is validated. Finally, two examples of error analysis, including gain imbalance and quantization error, are given through a simulation model. In general, the simulation model proposed in this paper has good accuracy and can play an important role in the error analysis and pre-development of the fully polarized radiometer.