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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.

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.

The Physikalisch-Technische Bundesanstalt (PTB) has set up an additional measurement approach for the absolute calibration of the spectral responsivity of detectors in the near-infrared (NIR) and mid-infrared (MIR) spectral range. This alternative method uses the radiation of a blackbody operating at about 1200 K with a precision aperture. The blackbody radiation can be calculated by Planck's law and is additionally spectrally selected by accurately characterized optical bandpass filters. Thus, a calibration of the spectral responsivity of a detector with respect to irradiance can be achieved at the bandpass wavelength of the applied transmission filters. If the aperture of the detector is known, the spectral responsivity can also be calculated with respect to radiant power. Thermopile detectors with known aperture size were calibrated in terms of their spectral responsivity with several bandpass filters in the spectral range between 1.5 µm up to 14 µm with relative standard measurement uncertainties between 5 % and 19 %. The obtained results are consistent with previous calibrations at PTB's national primary detector standard. Therefore, this additional measurement approach is a further validation of the existing primary method which is based on a cryogenic radiometer and extends the usable wavelength range.

The amount of radiation given from the phototherapy lamp (Blue Light) who not right for neonates with hyperbilirubin is feared to cause the bilirubin levels in not decrease accordance with the calculated dose. The purpose of this study is to make a Blue Light calibration device with a stable measurement. The contribution of this research is by determine a sensor who able to measure the irradiation value more accurately between TCS3200 and AS7262 sensor. TCS3200 sensor measures the wavelengths of 470nm, 524nm and 640nm and AS7262 sensor can measure wavelengths of 430-670nm. The results of both sensors are stored in the Electrically Erasable Programmable Read-Only Memory, with the amount of data and the length of measurement can be adjusted according to user needs. Measurement the irradiation value of two sensors is done simultaneously using 3 Watt Light Emitting Diode lamp as a Blue Light simulation where the lamp is placed directly above the sensor and distance of the lamp to the sensor is 10cm, 20cm, 30cm, and 40cm. The average uncertainty value with TCS3200 sensor is 14.65 and the average uncertainty value with AS7262 sensor is 2.17. Type A uncertainty value is based on results of repeated measurements that show how close the measurement results are to the actual value (stable measurement results). The results showed that the average uncertainty value on AS7262 sensor is relatively small, so its mean the measurement results of AS7262 sensor are stable. The author suggests using sensors who capable of reading the value of light radiation without conversion. The results of this study can be implemented to measure the intensity of the lamp and be used as a reference to determining the time of lamp replacement.

Microwave remote sensing can be used to monitor the time evolution of some key parameters over land, such as land surface temperature or surface water extent. Observations are made with instruments, such as the Scanning Microwave Multichannel Radiometer (SMMR) before 1987, the Special Sensor Microwave/Imager (SSM/I) and the subsequent Special Sensor Microwave Imager/Sounder (SSMIS) from 1987 and still operating, and the more recent Global Precipitation Measurement Microwave Imager (GMI). As these instruments differ on some of their characteristics and use different calibration schemes, they need to be inter-calibrated before long-time-series products can be derived from the observations. Here an inter-calibration method is designed to remove major inconsistencies between the SMMR and other microwave radiometers for the 18 and 37 GHz channels over continental surfaces. Because of a small overlap in observations and a ∼6 h difference in overpassing times between SMMR and SSM/I, GMI was chosen as a reference despite the lack of a common observing period. The diurnal cycles from 3 years of GMI brightness temperatures are first calculated and then used to evaluate SMMR differences. Based on a statistical analysis of the differences, a simple linear correction is implemented to calibrate SMMR on GMI. This correction is shown to also reduce the biases between SMMR and SSM/I, and can then be applied to SMMR observations to make them more coherent with existing data records of microwave brightness temperatures over continental surfaces.

The advanced microwave radiometer-climate quality (AMR-C) is a part of the European Sentinel-6A/B series, a collaboration between ESA and NASA, of two Earth-observing satellites, which will be launched in 2020 and 2025. Compared to its predecessor, Jason-3, the two AMR-C radiometer instruments have an external calibration system which enables higher radiometric stability accomplished by moving the secondary mirror between well-defined targets. Sentinel-6 allows continuing the study of the ocean circulation, climate change, and sea-level rise for at least another decade. Besides the external calibration for the AMR heritage radiometer (18.7, 23.8, and 34 GHz channels), the AMR-C contains a high-resolution microwave radiometer (HRMR) with radiometer channels at 90, 130, and 168 GHz. This subsystem allows for a factor of 5× higher spatial resolution at coastal transitions. This article presents a brief description of the instrument and the measured performance of the completed AMR-C-A and AMR-C-B instruments.

Recently, polarimetry has been used to enhance classical photometry to infer aerosol optical properties, as polarized radiation contains additional information about the particles. Therefore, we have equipped the Sun–sky automatic radiometer (SSARA) with polarizer filters to measure linearly polarized light at 501.5 nm. We describe an improved radiometric and polarimetric calibration method, which allows us to simultaneously determine the linear polarizers' diattenuation and relative orientation with high accuracy (0.002 and 0.1∘, respectively). Furthermore, we employed a new calibration method for the alt-azimuthal mount capable of correcting the instrument's pointing to within 32 arcmin. So far, this is limited by the accuracy of the Sun tracker. Both these methods are applicable to other Sun and sky radiometers, such as the Cimel CE318-DP instruments used in the AErosol RObotic NETwork (AERONET). During the A-LIFE (Absorbing aerosol layers in a changing climate: aging, LIFEtime and dynamics) field campaign in April 2017, SSARA collected 22 d of data. Here, we present two case studies. The first demonstrates the performance of an aerosol retrieval from SSARA observations under partially cloudy conditions. In the other case, a high aerosol load due to a Saharan dust layer was present during otherwise clear-sky conditions.

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).

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.

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.

The first five years of operation of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange one point have produced results that uniquely complement the data from currently operating low orbit Earth-observing instruments. In this paper we describe an updated unified approach to EPIC calibration. In this approach, calibration coefficients and their trends were obtained by comparing EPIC observations to the measurements from polar orbiting radiometers. In this study L1B reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua and Terra satellites, Multi-angle Imaging Spectroradiometer (MISR) onboard Terra and Visible Infrared Imaging Radiometer (VIIRS) onboard the Suomi National Polar-orbiting Partnership (Suomi NPP) spacecraft were used to infer calibration coefficients for four EPIC visible and near-infrared channels: 443 nm, 551 nm, 680 nm, and 780 nm. EPIC Version three measurements made between June 2015 and August 2020 were used for comparison. The calibration procedure identifies the most homogeneous low Earth orbit radiometer scenes matching scattering angles that are temporarily and spatially collocated with EPIC observations. These scenes are used to determine reflectance to count (R/C) ratios in spectrally analogous channels. Seasonal average R/C ratios were analyzed to obtain EPIC calibration gains and trends. The trends for the full dataset period are not statistically significant except in the 443 nm channel. No significant changes in calibration were found after the instrument’s exit from safe hold in March 2020. The R/C ratios were also used to determine the differences in EPIC gains resulting from separate calibrations: against MODIS Aqua or Terra, as well as against forward or aftward MISR cameras. Statistical tests indicate that the differences between the two datasets are not significant except in the 780 nm channels where Aqua-derived coefficients may be around 2% lower compared to Terra. The dependence of EPIC calibration gains on the instrument scattering angle and on DSCOVR-Earth distance were investigated. Lastly, model Low Earth Orbit (LEO) reflectances calculated to match the EPIC viewing geometry were employed to study how EPIC calibration coefficients depend on EPIC-LEO viewing geometry differences. The effect of LEO and EPIC angular mismatch on calibration was shown to be small.

The expediency of using a compensation radiometer (CR) with periodic absolute calibration as a sensor for preprocessing the information of correlation-extreme navigation systems (CENS) of unmanned aerial vehicles (UAV) was shown. This is determined by the possibility of obtaining and using the estimates of gain fluctuations obtained in previous frames which will provide an increase in the radiometer sensitivity. In addition, due to the accumulation of information, an increase in accuracy of measurement of the elements of the current image formed by the CENS will be provided. The algorithm of processing the obtained calibration estimates during linear processing corresponds to a certain digital filter (DF). By defining a set of the DF weight coefficients, it is possible to improve the CR fluctuation sensitivity by reducing the gain fluctuations. Up to 1.8-time gain in sensitivity can be reached for typical frequency and time parameters of the compensation radiometer of UAV CENS. The problem of synthesis of a digital filter was set. A solution to the problem of synthesizing an optimal digital filter was proposed. Its use in a CR will improve the fluctuation sensitivity. In its turn, this will make it possible to improve the quality of a current image generated by the system when siting by means of sighting surfaces with low-contrast objects taking into account fluctuations in radio-brightness temperature. It was found that the gain in sensitivity when using the optimal digital filter increases with an increase in the operating period of the radiometer and an increase in the digital filter order. Improvement of fluctuation sensitivity of the CENS data preprocessing system is important for UAV location in low-contrast areas

A comprehensive comparison of more than 70 000 synchronous 1 min aerosol optical depth (AOD) data from three Global Atmosphere Watch precision-filter radiometers (GAW-PFR), traceable to the World AOD reference, and 15 Aerosol Robotic Network Cimel radiometers (AERONET-Cimel), calibrated individually with the Langley plot technique, was performed for four common or “near” wavelengths, 380, 440, 500 and 870 nm, in the period 2005–2015. The goal of this study is to assess whether, despite the marked technical differences between both networks (AERONET, GAW-PFR) and the number of instruments used, their long-term AOD data are comparable and consistent. The percentage of data meeting the World Meteorological Organization (WMO) traceability requirements (95 % of the AOD differences of an instrument compared to the WMO standards lie within specific limits) is >92 % at 380 nm, >95 % at 440 nm and 500 nm, and 98 % at 870 nm, with the results being quite similar for both AERONET version 2 (V2) and version 3 (V3). For the data outside these limits, the contribution of calibration and differences in the calculation of the optical depth contribution due to Rayleigh scattering and O3 and NO2 absorption have a negligible impact. For AOD >0.1, a small but non-negligible percentage (∼1.9 %) of the AOD data outside the WMO limits at 380 nm can be partly assigned to the impact of dust aerosol forward scattering on the AOD calculation due to the different field of view of the instruments. Due to this effect the GAW-PFR provides AOD values, which are ∼3 % lower at 380 nm and ∼2 % lower at 500 nm compared with AERONET-Cimel. The comparison of the Ångström exponent (AE) shows that under non-pristine conditions (AOD >0.03 and AE ) the AE differences remain . This long-term comparison shows an excellent traceability of AERONET-Cimel AOD with the World AOD reference at 440, 500 and 870 nm channels and a fairly good agreement at 380 nm, although AOD should be improved in the UV range.

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for $\sigma _{\mathrm{ HH}}^{o} $ , $\sigma _{\mathrm{ VV}}^{o} $ , $T_{\mathrm {BH}}$ , and $T_{\mathrm {BV}}$ , respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data.

Extraterrestrial spectral response calibration of a multi-filter rotating shadow band radiometer (MFRSR) under pristine Amazonian Forest atmosphere conditions was performed using the Langley plot method. The MFRSR is installed in central Amazonia as part of a long-term monitoring site, which was used in the context of the GoAmazon2014/5 experiment. It has been operating continuously since 2011 without regular extraterrestrial calibration, preventing its application to accurate monitoring of aerosol particles. Once calibrated, the MFRSR measurements were applied to retrieve aerosol particle columnar optical properties, specifically aerosol optical depth (AODλ) and Ångström exponent (AE), which were evaluated against retrievals from a collocated Cimel Sun photometer belonging to the AErosol RObotic NETwork (AERONET). Results obtained revealed that pristine Amazonian conditions are able to provide MFRSR extraterrestrial spectral response with relative uncertainty lower than 1.0 % in visible channels. The worst estimate (air mass =1) for absolute uncertainty in AODλ retrieval varied from ≈0.02 to ≈0.03, depending on the assumption regarding uncertainty for MFRSR direct normal irradiance measured at the surface. The obtained root mean square error (RMSE ≈0.025) from the evaluation of MFRSR retrievals against AERONET AODλ was, in general, lower than estimated MFRSR AODλ uncertainty, and close to the uncertainty of AERONET field Sun photometers (≈0.02).

The calibration strategy for synthetic aperture interferometric radiometers based on noise injection has been successfully demonstrated in the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument onboard the Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA). With the emerging demands of increasing both array size and frequency bands, the internal calibration hardware becomes more difficult to implement. Although several external calibration methods have been proposed, the so-called phase ambiguity problem was not carefully considered. In this article, a novel calibration strategy for both phase and amplitude calibrations based on redundant space calibration is proposed, which utilizes the unique structure of equispaced circular array and rotational sampling strategy. The original irregular phase ambiguity degenerates to the fixed p-ambiguity, where only two possible solutions to phases are introduced. Both phase and amplitude of visibility can be simultaneously calibrated by the proposed strategy, and no cooperative calibration target is needed. NSSC’s contribution was supported by the National Natural Science Foundation of China under Grant 41675035, the special Fund for Chinese Meteorological Research in the Public Interest under Grant GYHY201506023, and Beijing Science Project under Grant Z161100002616033. UPC’s contri-bution was supported by the Spanish Ministry of Science, Innovation and Universities, “SPOT: Sensing with Pioneering Opportunistic Techniques”, Grant RTI2018-099008-B-C21/AEI/10.13039/501100011033.

We have constructed, calibrated, and tested a cryogenic low-background infrared radiometer for both spectral radiance and irradiance measurements over the 4 μm to 20 μm wavelength range. The primary purpose of the Missile Defense Transfer Radiometer (MDXR) is to measure absolute irradiance or radiance from cryogenic infrared test chamber sources using a photoconductive Si:As Blocked Impurity Band (BIB) detector and a set of spectral filters. The MDXR also includes an absolute cryogenic radiometer (ACR) and a Fourier transform spectrometer (FTS). For irradiance measurements, the ACR is used to provide the primary power scale for the BIB detector in conjunction with spectral filters, while the FTS/BIB configuration derives its scale from an internal blackbody source. The two measurement scales show agreement for the irradiance of highly collimated (< 1 mrad) infrared beams from 10(−13) W/μm/cm(2) to 10(−8) W/μm/cm(2) within the combined relative uncertainties of 2.6 % (coverage factor k = 1.) We have also calibrated the radiometer for radiance measurements by using a large cavity fluid bath blackbody that overfills the spatial and angular extent of the radiometer entrance pupil. The radiometric calibration uncertainty analysis of the radiometer as well as its maintenance and stability are discussed.

The absolute radiometric accuracy of the Fengyun 3D advanced Medium Resolution Spectral Imager (FY3D MERSI-II) thermal infrared bands was evaluated using the collected field measurements and atmospheric transfer simulations during 16–22 August 2019 at Lake Qinghai. A thermal infrared radiometer equipped on an unmanned surface vehicle was used to continuously collect the water temperature. Atmospheric conditions, surface emissivity, and aerosol optical depth measured near the field experiment site were adopted by the atmospheric transfer code to calculate the parameters about the influence of atmosphere on long-wave radiation, including the path radiance and the transmittance propagated from land surface to the satellite. The radiometric calibration accuracy analysis suggests that the differences between the simulated brightness temperature and satellite-based brightness temperature are −0.346 K and −0.722 K for channel 24 on 18 and 20 August, respectively, while it reaches −0.460 K and −1.036 K for channel 25 on 18 and 20 August, respectively. The vicarious calibration coefficients were found to be in good agreement with the internal onboard calibration coefficient in channel 24 and 25 of the FY3D MERSI-II according to the validation analysis in selected regions. The thermal infrared bands of the FY3D have a good in-orbit operational status according to our vicarious calibration experiments.

Low uncertainty and long-term stability remote data are urgently needed for researching climate and meteorology variability and trends. Meeting these requirements is difficult with in-orbit calibration accuracy due to the lack of radiometric satellite benchmark. The radiometric benchmark on the reflected solar band has been under development since 2015 to overcome the on-board traceability problem of hyperspectral remote sensing satellites. This paper introduces the development progress of the Chinese radiometric benchmark of the reflected solar band based on the Space Cryogenic Absolute Radiometer (SCAR). The goal of the SCAR is to calibrate the Earth–Moon Imaging Spectrometer (EMIS) on-satellite using the benchmark transfer chain (BTC) and to transfer the traceable radiometric scale to other remote sensors via cross-calibration. The SCAR, which is an electrical substitution absolute radiometer and works at 20 K, is used to realize highly accurate radiometry with an uncertainty level that is lower than 0.03%. The EMIS, which is used to measure the spectrum radiance on the reflected solar band, is designed to optimize the signal-to-noise ratio and polarization. The radiometric scale of the SCAR is converted and transferred to the EMIS by the BTC to improve the measurement accuracy and long-term stability. The payload of the radiometric benchmark on the reflected solar band has been under development since 2018. The investigation results provide the theoretical and experimental basis for the development of the reflected solar band benchmark payload. It is important to improve the measurement accuracy and long-term stability of space remote sensing and provide key data for climate change and earth radiation studies.

Infrared (IR) radiometers from geostationary (GEO) satellites have an advantage over low-earth orbiting (LEO) satellites as they provide continuous observations to monitor the diurnal variations in the sea surface temperature (SST), typically better than 30-minute interval. However, GEO satellite observations suffer from significant diurnal and seasonal biases arising due to varying sun-earth-satellite geometry, leading to biases in SST estimates from conventional non-linear regression-based algorithms (NLSST). The midnight calibration issue occurring in GEO sensors poses a different challenge altogether. To mitigate these issues, we propose SST estimation from split-window IR observations of INSAT-3D and 3DR Imagers using One-Dimensional Variational (1DVAR) scheme. Prior to SST estimation, the bias correction in Imager observations is carried out using cumulative density function (CDF) matching. Then NLSST and 1DVAR algorithms were applied on six months of INSAT-3D/3DR observations to retrieve the SST. For the assessment of the developed algorithms, the retrieved SST was validated against in-situ SST measurements available from in-situ SST Quality Monitor (iQuam) for the study period. The quantitative assessment confirms the superiority of the 1DVAR technique over the NLSST algorithm. However, both the schemes under-estimate the SST as compared to in-situ SST, which may be primarily due to the differences in the retrieved skin SST versus bulk in-situ SST. The 1DVAR scheme gives similar accuracy of SST for both INSAT-3D and 3DR with a bias of −0.36 K and standard deviation (Std) of 0.63 K. However, the NLSST algorithm provides slightly less accurate SST with bias (Std) of −0.18 K (0.87 K) for INSAT-3DR and −0.27 K (0.95 K) for INSAT-3D. Both the NLSST and 1DVAR algorithms are capable of producing the accurate thermal gradients from the retrieved SST as compared to the gradients calculated from daily Multiscale Ultrahigh Resolution (MUR) level-4 analysis SST acquired from Group for High-Resolution Sea Surface Temperature (GHRSST). Based on these spatial gradients, thermal fronts can be generated that are very useful for predicting potential fishery zones (PFZ), which is available from GEO satellites, INSAT-3D/3DR, in near real-time at 15-minute intervals. Results from the proposed 1DVAR and NLSST algorithms suggest a marked improvement in the SST estimates with reduced diurnal/seasonal biases as compared to the operational NLSST algorithm.

The first two models of the Sea and Land Surface Temperature Radiometers (SLSTR) for the European Copernicus Sentinel-3 missions were tested prior to launch at the Rutherford Appleton Laboratory space instrument calibration facility. The pre-launch tests provide an essential reference that ensures that the flight data of SLSTR are calibrated to the same standards needed for surface temperature measurements and to those used by shipborne radiometers for Fiducial Reference Measurement (FRM). The radiometric calibrations of the thermal infrared channels were validated against accurate and traceable reference BB sources under flight representative thermal vacuum environment. Measurements were performed in both earth views for source temperatures covering the main operating range, for different instrument configurations and for the full field-of-view of the instruments. The data were used to derive non-linearity curves to be used in the level-1 processing. All results showed that the measured brightness temperatures and radiometric noise agreed within the requirements for the mission. An inconsistency that particularly affected SLSTR-A was observed which has been attributed to an internal stray light error. A correction for the stray light has been proposed to reduce the error. The internal stray light error was reduced for SLSTR-B by replacing the coating on the main aperture stop. We present a description of the test methodology and the key results.

We present the results from Verification of Reference Irradiance and Radiance Sources Laboratory Calibration Experiment Campaign. Ten international laboratories took part in the measurements. The spectral irradiance comparison included the measurements of the 1000 W tungsten halogen filament lamps in the spectral range of 350 nm&ndash, 900 nm in the pilot laboratory. The radiance comparison took a form of round robin where each participant in turn received two transfer radiometers and did the radiance calibration in their own laboratory. The transfer radiometers have seven spectral bands covering the wavelength range from 400 nm&ndash, 700 nm. The irradiance comparison results showed an agreement between all lamps within &plusmn, 1.5%. The radiance comparison results presented higher than expected discrepancies at the level of &plusmn, 4%. Additional investigation to determine the causes for these discrepancies identified them as a combination of the size-of-source effect and instrument effective field of view that affected some of the results.

International audience; The Sentinel-3 Mission Performance Centre (S3MPC) is tasked by the European Space Agency (ESA) to monitor the health of the Copernicus Sentinel-3 satellites and ensure a high data quality to the users. This paper deals exclusively with the effort devoted to the altimeter and microwave radiometer, both components of the Surface Topography Mission (STM). The altimeters on Sentinel-3A and -3B are the first to operate in delay-Doppler or SAR mode over all Earth surfaces, which enables better spatial resolution of the signal in the along-track direction and improved noise reduction through multi-looking, whilst the radiometer is a two-channel nadir-viewing system. There are regular routine assessments of the instruments through investigation of telemetered housekeeping data, calibrations over selected sites and comparisons of geophysical retrievals with models, in situ data and other satellite systems. These are performed both to monitor the daily production, assessing the uncertainties and errors on the estimates, and also to characterize the long-term performance for climate science applications. This is critical because an undetected drift in performance could be misconstrued as a climate variation. As the data are used by the Copernicus Services (e.g., CMEMS, Global Land Monitoring Services) and by the research community over open ocean, coastal waters, sea ice, land ice, rivers and lakes, the validation activities encompass all these domains, with regular reports openly available. The S3MPC is also in charge of preparing improvements to the processing, and of the development and tuning of algorithms to improve their accuracy. This paper is thus the first refereed publication to bring together the analysis of SAR altimetry across all these different domains to highlight the benefits and existing challenges.

We propose a space benchmark sensor with onboard SI (Syst&egrave, me International) traceability by means of quantum optical radiometry. Correlated photon pairs generated by spontaneous parametric down-conversion (SPDC) in nonlinear crystals are used to calibrate the absolute responsivity of a solar observing radiometer. The calibration is systematic, insensitive to degradation and independent of external radiometric standards. Solar spectral irradiance at 380&ndash, 2500 nm is traceable to the photon rate and Planck&rsquo, s constant with an expected uncertainty of about 0.35%. The principle of SPDC calibration and a prototype design of the solar radiometer are introduced. The uncertainty budget is analyzed in consideration of errors arising from calibration and observation modes.

This paper overviews the progress in the sky radiometer technology and development of the network called SKYNET. It is found that the technology has produced useful on-site calibration methods, retrieval algorithms, and data analyses from the sky radiometer observation of aerosol, cloud, water vapor and ozone. Increasing collaborations of users in the SKYNET community are becoming a useful platform for research and operation. The paper also presents issues of the technology for future development.

Climate on Earth is determined by the Earth Radiation Budget (ERB), which quantifies the incoming and outgoing radiative energy fluxes. The ERB can be monitored by non-scanning wide field-of-view radiometers, or by scanning narrow field-of-view radiometers. We propose an enhanced design for the wide field-of-view radiometer, with as key features the use of a near-spherical cavity to obtain a uniform angular sensitivity and the integration of the shuttered electrical substitution principle, eliminating long term drifts of the radiometer and improving its time response. The target absolute accuracy is 1 W/m 2 and the target stability is 0.1 W/m 2 per decade for the measurement of the total outgoing Earth’s radiation. In order to increase the spatial resolution and to separate the total outgoing radiation into reflected Solar and emitted thermal radiation, we propose the joint use of the radiometer with wide field-of-view Shortwave (400−900 nm) and Longwave (8−14 μm) cameras. This paper presents the concept and design of the novel wide field-of-view radiometer, including simulations and analyses of its expected performance. We focus on mechanical design and the measurement characteristics based on optical and thermal analyses. In combination with the cameras, we obtain an estimated accuracy of 0.44 W/m 2 .

The THz atmospheric limb sounder (TALIS) is a microwave radiometer developed by the National Space Science Center of the Chinese Academy of Sciences for the detection of atmospheric trace gases. The observation range of the instrument mainly focuses on the middle and upper atmosphere (10&ndash, 100 km above the earth&rsquo, s surface). The detection targets include the temperature, pressure, and more than 10 kinds of atmospheric components. Its scientific goal is to improve our comprehension of atmospheric chemical composition and dynamics, and to monitor environmental pollution and sources in the atmosphere. The TALIS instrument is composed of an antenna, superheterodyne radiometers, and digital fast Fourier transform (FFT) spectrometers. By measuring the atmospheric thermal radiance in the wide frequency band with 118, 190, 240, and 643 GHz as the center frequency, the required volume mixing ratio (VMR) of atmospheric chemical species can be obtained. This paper introduces the characteristics of the TALIS instrument, and establishes a simulation model for the TALIS spectrometer. Through a joint simulation with an atmosphere radiative transfer simulator (ARTS), the TALIS instrument performance is evaluated from the aspects of calibration, the imbalance of two sidebands, the spectrum resolution, and quantization. The simulation results show that the two-point calibration can well-restore the radiance spectrum of the scene target and remove the influence of the spectral response function (SRF), the double side band (DSB) receiver with a 2 MHz resolution can meet the sensitivity and spectrum resolution requirements. Finally, the sensitivity errors of different quantization bits are given by the simulation and the results show that at 8-bit, the sensitivity and its degradation ratio are 1.251 K and 1.036 at a 2 MHz spectrum resolution and 100 ms integration time, respectively.

3 pages, 4 figures, A method for internally calibrating microwave total power radiometers by using only one level of noise injection is presented. It is based on having a previous accurate characterization of the receiver noise temperature, which used de facto as a second calibration standard. The method proves to be at least equivalent to the classical two level, as demonstrated through their intercomparison using the data provided by the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) on board the European Space Agency Soil Moisture and Ocean Salinity (SMOS) Satellite. The long-term stability in terms of retrieved brightness temperature using both methods has similar trends with a small advantage for the one-point approach proposed her, With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

Providing uncertainties in satellite datasets used for Earth observation can be a daunting prospect because of the many processing stages and input data required to convert raw detector counts to calibrated radiances. The Sea and Land Surface Temperature Radiometer (SLSTR) was designed to provide measurements of the Earth’s surface for operational and climate applications. In this paper the authors describe the traceability chain and derivation of uncertainty estimates for the thermal infrared channel radiometry. Starting from the instrument model, the contributing input quantities are identified to build up an uncertainty effects tree. The characterisation of each input effect is described, and uncertainty estimates provided which are used to derive the combined uncertainties as a function of scene temperature. The SLSTR Level-1 data products provide uncertainty estimates for fully random effects (noise) and systematic effects that can be mapped for each image pixel, examples of which are shown.

We directly quantify the effect of infrequent calibration on the stability of microwave radiometer temperature measurements (where a power measurement for the unknown source is acquired at a fixed time, but calibration data are acquired at variable earlier times) with robust and nonrobust implementations of a new metric. Based on our new metric, we also determine a component of uncertainty in a single measurement due to infrequent calibration effects. We apply our metric to experimental data acquired from experimental ground-based calibration data acquired from a NASA millimeter-wave imaging radiometer and a NIST radiometer (Noise Figure Radiometer-NFRad). Based on a stochastic model for the NFRad, we determine the random uncertainty of an empirical prediction model of our stability metric by a Monte Carlo method. For comparison purposes, we also present a secondary metric that quantifies stability for the case where calibration data are acquired at a fixed time, but power measurements for the unknown source are acquired at variable later times.

The fourth and fifth Soil Moisture Active Passive Experiments (SMAPEx-4 and -5) were conducted at the beginning of the SMAP operational phase, May and September 2015, to: 1) evaluate the SMAP microwave observations and derived soil moisture (SM) products and 2) intercompare with the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions over the Murrumbidgee River Catchment in the southeast of Australia. Airborne radar and radiometer observations at the same microwave frequencies as SMAP were collected over SMAP footprints/grids concurrent with its overpass. In addition, intensive ground sampling of SM, vegetation water content, and surface roughness was carried out, primarily for validation of airborne SM retrieval over six $\sim 3\,\,\text {km} \times 3$ km focus areas. In this study, the SMAPEx-4 and -5 data sets were used as independent reference for extensively evaluating the brightness temperature and SM products of SMAP, and intercompared with SMOS and Aquarius under a wide range of SM and vegetation conditions. Importantly, this is the only extensive airborne field campaign that collected data while the SMAP radar was still operational. The SMAP radar, radiometer, and derived SM showed a high agreement with the SMAPEx-4 and -5 data set, with a root-mean-squared error (RMSE) of ~3 K for radiometer brightness temperature, and an RMSE of $\sim 0.05~\text{m}^{3}/\text{m}^{3}$ for the radiometer-only SM product. The SMAP radar backscatter had an RMSE of 3.4 dB, while the retrieved SM had an RMSE of 0.11 m3/m3 when compared with the SMAPEx-4 data set.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard Terra platform, which was launched in 1999, has three separate subsystems: a visible and near-infrared (VNIR) radiometer, a shortwave-infrared radiometer, and a thermal-infrared radiometer. The ASTER VNIR bands have been radiometrically corrected for approximately 14 years by the sensor degradation curves estimated from the onboard calibrator according to the original calibration plan. However, this calibration by the onboard calibrator encountered a problem; specifically, it is inconsistent with the results of vicarious calibration and cross calibration. Therefore, the ASTER VNIR processing was applied by the radiometric degradation curves calculated from the results of three calibration approaches, i.e., the onboard calibrator, the vicarious calibration, and the cross calibration since February 2014. Even though the current degradation curves were revised, the inter-band and lunar calibrations show some inconsistencies owing to the different traceability in the bands by different calibration approaches. In this study, the current degradation curves and their problems are explained, and the new curves that are derived from the vicarious calibration with lunar calibration are discussed. The new degradation curves that have the same traceability in the bands will be used for future ASTER VNIR processing.

The Second Generation Global Imager (SGLI) on Global Change Observation Mission−Climate (GCOM-C) satellite empowers surface and atmospheric measurements related to the carbon cycle and radiation budget, with two radiometers of Visible and Near Infrared Radiometer (SGLI-VNR) and Infrared Scanning Radiometer (SGLI-IRS) that perform a wide-band (380 nm−12 µm) optical observation not only with as wide as a 1150−1400 km field of view (FOV), but also with as high as 0.25−0.5 km resolution. Additionally, polarization and along-track slant view observations are quite characteristic of SGLI. It is important to calibrate radiometers to provide the sensor data records for more than 28 standard products and 23 research products including clouds, aerosols, ocean color, vegetation, snow and ice, and other applications. In this paper, the radiometric model and the first results of on-board calibrations on the SGLI-VNR, which include weekly solar and light-emitting diode (LED) calibration and monthly lunar calibration, will be described. Each calibration data was obtained with corrections, where beta angle correction and avoidance of reflection from multilayer insulation (MLI) were applied for solar calibration; LED temperature correction was performed for LED calibration; and the GIRO (GSICS (Global Space-based Inter-Calibration System) Implementation of the ROLO (RObotic Lunar Observatory) model) model was used for lunar calibration. Results show that the inter-comparison of the relative degradation amount between these three calibrations agreed to within 1% or less.