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A new cost-effective radiometer has been designed, built, and tested to measure direct normal solar irradiance (DNI). The proposed instrument for solar irradiance measurement is based on an optical fiber as the light beam collector, a semiconductor photodiode to measure the optical power, and a calibration algorithm to convert the optical power into solar irradiance. The proposed radiometer offers the advantage of separating the measurement point, where the optical fiber collects the solar irradiation, from the place where the optical power is measured. A calibration factor is mandatory because the semiconductor photodiode is only spectrally responsive to a limited part of the spectral irradiance. Experimental tests have been conducted under different conditions to evaluate the performance of the proposed device. The measurements confirm that the proposed instrument performs similarly to the expensive high-accuracy pyrheliometer used as a reference. [ABSTRACT FROM AUTHOR]

Objectives: Since there is only nadir radiometer onboard for the wide-swath altimetry, the wet tropospheric delay can only be corrected by models inside the cross-swath or substituted by the nadir radiometer measured data, which lead to the lower accuracy.Methods: In order to improve the accuracy of wet tropospheric correction (WTC) inside the cross-swath, an optimum interpolation method to fuse the nadir radiometer WTC is proposed, and it is verified by taken the SWOT (surface water and ocean topography) wide-swath altimeter as example. Results: Inside the cross-swath, when the ERA5 (ECMWF reanalysis 5th generation) data are used, the residual of WTC after correction by optimum interpolation method can be reduced by 40% compared with the nadir radiometer WTC substituted. When the simulated WTCs from the spectrum of radiometer measured WTCs are used, the residual of WTC after correction by optimum in⁃ terpolation method can be reduced by 80% in all latitude areas compared with the nadir radiometer WTC substituted.Conclusions: The optimum interpolation method has much better accuracy than the nadir radiometer WTC substituted in the case of high water vapor variability. [ABSTRACT FROM AUTHOR]

Accurate information on tropical cyclone position, intensity, and structure is critical for storm surge prediction. Atmospheric reanalysis datasets can provide gridded, full coverage, long-term and multi-parameter atmospheric fields for the research on the impact of tropical cyclones on the upper ocean, which effectively makes up for the uneven temporal and spatial distribution of satellite remote sensing and in situ data. However, the reanalysis data cannot accurately describe characteristic parameters of tropical cyclones, especially in high wind conditions. In this paper, the performance of the tropical cyclone representation in ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation) is investigated and analyzed with respect to IBTrACS (International Best Track Archive for Climate Stewardship) during the period 2018–2020. Comparisons demonstrate that ERA5 winds significantly underestimate the maximum wind speed during the tropical cyclones (>30 m/s) compared to those provided by IBTrACS. An effective wind reconstruction method is examined to enhance tropical cyclone intensity representation in reanalysis data in 94 cases of 31 tropical cyclones 2018–2020. The reconstructed wind speeds are in good agreement with the SFMR (Stepped Frequency Microwave Radiometer) measured data and SMAP (Soil Moisture Active Passive) L-band radiometer remotely sensed measurements. The proposed wind reconstruction method can effectively improve the accuracy of the tropical cyclone representation in ERA5, and will benefit from the establishment of remote sensing satellite retrieval model and the forcing fields of the ocean model. [ABSTRACT FROM AUTHOR]

• Normal concentrations of ionized calcium in children differ from adults. • Radiometer instruments record lab results for all analytes independent of the order(s) placed. • Radiometer data can be used to apply exclusion criteria and calculate reference intervals. Measurement of ionized calcium (iCa) reflects bioavailable calcium and has significant utility in children. However, robust pediatric iCa reference intervals (RI) have not been well-established. In this study, we retrospectively calculated RI for iCa in a pediatric population by accessing archived data acquired on Radiometer instruments and applying stringent exclusion criteria. Data saved on 4 Radiometer ABL800 FLEX blood gas analyzers were queried. Exclusion criteria were applied based on information available from these instruments. iCa results were plotted and inflection points were visually identified. Following outlier removal and partition verification, age-specific RI were calculated using a nonparametric rank order approach from > 5,000 individuals. Finally, the stringency of the exclusion criteria was assessed by calculating RI from additional results in the dataset and comparing to existing in-house ranges. Six age-specific iCa partitions were established from 0 to 19 years. Relative to adults, wider ranges for the central 95th percentile were observed early in life that progressively narrowed with increasing age and approached adult concentrations by 2.5 years. Analysis of concurrent data for sodium and creatinine in the dataset suggest the applied exclusion criteria reduced the likelihood of including results from acutely-ill children. Normal concentrations of iCa in children are more variable than adults. Observed differences may reflect the transition from maternally supplied calcium to nutritional sources, the maturation of calcium homeostatic mechanisms, and/or the need for calcium for growth/development. This study also demonstrates the feasibility and advantages of using data archived on Radiometer analyzers to establish pediatric RI. This approach enables rapid, cost-effective evaluation of large datasets and may be a feasible option when prospective or detailed retrospective analyses are not possible. [ABSTRACT FROM AUTHOR]

This paper presents measurements using a dual-polarised radiometer operating at 93 GHz to detect ice or water on asphalt in laboratory conditions. The brightness temperatures of both H and V polarizations were measured for a dry surface, liquid water, and ice on asphalt at observation angles of 50° and 56°. The results presented in this paper demonstrate that the studied road conditions can be identified by the radiometer. The measurements are compared with a model and surface parameters, such as dielectric constant and roughness are fitted and compared to reference values. The experiments and results, described in this article, are the first steps towards the future installation of a polarimetric sensor on a moving vehicle for traffic safety. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched in 1997, and the observations continued for more than 17 years. The features of TRMM observation were as follows: (a) it followed a non-sun synchronized orbit that enabled the diurnal variation of precipitation to be investigated; (b) it carried a precipitation radar and microwave and infrared radiometers, along with two instruments of opportunity in the form of a lighting sensor and a radiation budget sensor; and (c) it worked as a standard reference for precipitation measurements for other spaceborne microwave radiometers, which enabled global rain maps to be developed. For science, TRMM provided precise and accurate rain distributions over tropical and subtropical regions. The rainfall results are primarily essential for the study of precipitation climatologies, whereas the three-dimensional images of precipitation systems enabled the study of the global characteristics of precipitation systems. Technologically, the spaceborne rain radar onboard TRMM demonstrated the effectiveness of radars in space, whereas the combination with other rain observation instruments showed its effectiveness as a calibration source. Multi-satellite rain maps in which TRMM was the reference standard have been developed, and they became prototypes of the multi-satellite Earth observation systems. On the basis of the great success of TRMM, the Global Precipitation Measurement (GPM) was designed to expand TRMM's coverage to higher latitudes. The core satellite of GPM is equipped with a dual-frequency precipitation radar (DPR) and a microwave radiometer. DPR comprises a Kuband radar (KuPR) and a Ka-band radar (KaPR) and can discriminate solid from liquid precipitation. The period of the precipitation measurement with spaceborne radars extended to more than 23 years, which may make it possible to detect the change of precipitation climatology related to change in the global environment. Although TRMM's and GPM's accomplishments are very broad, this paper attempts to highlight Japan's contributions to the science of these missions. [ABSTRACT FROM AUTHOR]

With the help of Ground Based seven channel K-Band humidity profiling radiometer, humidity at different height levels from 0 to 10 Km from ground has been obtained for two years from 2016 to 2017. Radiometer based zenith attenuation has been retrieved for the 20-30 GHz band which have been compared with ITU-R proposed attenuation estimation due to absorption by gases. ITU-R estimation has been found to underestimate zenith attenuation for tropical high rainfall region like Umiam. The Mean Atmospheric Temperature has been estimated from ground observations and Zenith Radiometer Attenuation through linear regression equations. Additionally, water vapour scale height has been estimated from zenith attenuation and surface meteorological parameters. Total water vapour has been also obtained from this and compared with Total water vapour estimated from IWV retrievals by radiometer. A regression relation has been found between IWV and 22.24 GHz brightness temperature obtained from Radiometer. [ABSTRACT FROM AUTHOR]

Temporal and spatial variation of sea ice type in the Arctic is an indicator of regional and global change. Arctic sea ice can be classified into two major categories: multiyear ice (MYI) and first-year ice. In this paper, classification method based on machine learning is established and applied to produce daily sea ice classification data set during the winter (November–April) from 2002 to 2017 using active microwave data from QuikSCAT and Advanced Scatterometer as well as passive microwave data from Advanced Microwave Scanning Radiometer for EOS, Special Sensor Microwave Imager/Sounder, and Advanced Microwave Scanning Radiometer 2 radiometer. First, the open water area is flagged out using brightness temperature (Tb) from the passive microwave sensor. Then, K-means algorithm is applied to identify the clusters of the two ice types in the Tb/backscatter parameter space and finally assign pixels to each class. Two optimization methods based on the movement of MYI and marginal ice zone are used to correct the misclassification of MYI. The results have shown a decrease of MYI in winter from 2002 to 2017, especially in 2008 and 2013 with a remarkable recovery in 2014. The classifications are consistent with results by visual interpretation from synthetic aperture radar images in the Canadian Arctic Archipelago with overall classification accuracy over 93%. Comparison with classifications from previous studies and products shows that our method could reflect more differences in MYI declining trend interannually and less anomalous fluctuations in certain years. [ABSTRACT FROM AUTHOR]

Collocated observations from microwave radiometer and wind profiler are used in a pilot study during the monsoon period to derive information on the thermodynamics and winds and association with rainfall characteristics. These instruments were operated throughout the monsoon season of 2015. Continuous vertical profiles of winds, temperature and humidity show significant promise for understanding the low-level jet, its periodicity and its association with moisture transport, clouds and precipitation embedded within the monsoon large-scale convection. Observations showed mutually beneficial in explaining variability that are part of the low frequency oscillations and the diurnal variability during monsoon. These observations highlight the importance of locally driven convective systems, in the presence of weak moisture transport over the area. The episodic moisture convergence showed a periodicity of 9 days which matches with the subsequent convection and precipitation and thermodynamic regimes. Inferences from the diurnal cycle of moisture transport and the convective activity, relationship with the low-level jet characteristics and thermodynamics are also illustrated. [ABSTRACT FROM AUTHOR]

The L-band passive microwave data from the Soil Moisture Active Passive (SMAP) observatory are investigated for remote sensing of ocean surface winds during severe storms. The surface winds of Joaquin derived from the real-time analysis of the Center for Advanced Data Assimilation and Predictability Techniques at Penn State support the linear extrapolation of the Aquarius and SMAP geophysical model functions (GMFs) to hurricane force winds. We apply the SMAP and Aquarius GMFs to the retrieval of ocean surface wind vectors from the SMAP radiometer data to take advantage of SMAP's two-look geometry. The SMAP radiometer winds are compared with the winds from other satellites and numerical weather models for validation. The root-mean-square difference (RMSD) with WindSat or Special Sensor Microwave Imager/Sounder is 1.7 m/s below 20-m/s wind speeds. The RMSD with the European Center for Medium-Range Weather Forecasts direction is 18° for wind speeds between 12 and 30 m/s. We find that the correlation is sufficiently high between the maximum wind speeds retrieved by SMAP with a 60-km resolution and the best track peak winds estimated by the National Hurricane Center and the Joint Typhoon Warning Center to allow them to be estimated by SMAP with a correlation coefficient of 0.8 and an underestimation by 8%–18% on average, which is likely due to the effects of spatial averaging. There is also a good agreement with the airborne Stepped-Frequency Radiometer wind speeds with an RMSD of 4.6 m/s for wind speeds in the range of 20–40 m/s. [ABSTRACT FROM PUBLISHER]

In the present paper, permittivity maps of equatorial lunar surface are generated using brightness temperature ( T B ) data obtained from Microwave Radiometer (MRM) of Chang'e-1 and physical temperature ( T P ) data obtained from Diviner of Lunar Reconnaissance Orbiter (LRO). Here, permittivity mapping is not carried out above 60° latitudes towards the lunar poles due to large anomaly in the physical temperature obtained from the Diviner. Microwave frequencies, which are used to generate these maps are 3 GHz, 7.8 GHz, 19.35 GHz and 37 GHz. Permittivity values are simulated using T B values at these four frequencies. Here, weighted average of physical temperature obtained from Diviner are used to compute permittivity at each microwave frequencies. Longer wavelengths of microwave signals give information of more deeper layers of the lunar surface as compared to smaller wavelength. Initially, microwave emissivity is estimated using T B values from MRM and physical temperature ( T P ) from Diviner. From estimated emissivity the real part of permittivity ( ε ), is calculated using Fresnel equations. The permittivity maps of equatorial lunar surface is generated. The simulated permittivity values are normalized with respect to density for easy comparison of simulated permittivity values with the permittivity values of Apollo samples as well as with the permittivity values of Terrestrial Analogue of Lunar Soil (TALS) JSC-1A. Lower value of dielectric constant ( ε ′) indicates that the corresponding lunar surface is smooth and doesn't have rough rocky terrain. Thus a future lunar astronaut can use these data to decide proper landing site for future lunar missions. The results of this paper will serve as input to future exploration of lunar surface. [ABSTRACT FROM AUTHOR]

L-band brightness temperature (TB) has been shown to provide the best sensitivity to soil moisture (SM) although C- and X-band based products offer a longer time-series from satellite-based measurements. Currently, global coverage SM is routinely produced from spaceborne measurements using all three frequency bands, but despite continued validation efforts of the products, the relative characteristics and performance of these observations have not been fully established. Therefore, this study focused on the parametrization of SM retrieval algorithms at L-, C- and X-bands using TB observations from the L-band radiometer on NASA's SM Active Passive (SMAP) mission and the C- and X-band channels of JAXA's Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W satellite. These can be applied in global SM retrieval algorithms using either one of the frequencies or a combination of them. The reference in situ SM data was obtained from 12 core validation sites across various land cover types around the world. The investigation highlighted the known challenges of retrieving SM from C- and X-band data compared to the higher sensitivity of the L-band data. Even with a site-specific retrieval algorithm parameterization, the mean correlation of the C- and X-band retrievals for the core validation site SM measurement were much lower than that for L-band, being 0.52 (0.54) and 0.45 (0.47) for vertical (horizontal) polarization, respectively, while for the L-band retrieval the corresponding values were 0.81 (0.77). The parameterization exercise showed that matching the C- and X-band TB measurements with an emission model was not difficult; the problem was relating the observations to SM under the influence of large roughness and vegetation effects. As a result, parameter optimization produced values for some sites that were not realistic or did not allow any practical sensitivity to SM at C- and X-band. Considering the L-band observations, the parameter optimization resulted in superior bias performance as compared to the operational SMAP product parameterization, but the sensitivity to SM changes (R and unbiased root mean square difference) did not improve markedly, or in some cases degraded at the expense of a smaller bias. • Spaceborne radiometer observation at L/C/X-band over 12 soil moisture core sites. • Calibration of soil moisture retrieval algorithm for L/C/X-band using the core sites. • L-band retrieval achieves correlation of 0.8 while C/X-band achieves only 0.5. • Retrieval capability of C/X-band questionable over some of the sites. • Calibration of L-band improves bias and RMSD over SMAP product but not sensitivity. [ABSTRACT FROM AUTHOR]

We present a method to retrieve wind speeds in hurricanes from spaceborne passive microwave radiometer data. Brightness temperature (TB) observations acquired at the 6.9-GHz horizontal polarization channel by the AMSR-E and AMSR2 onboard the Earth Observing System Aqua and Global Change Observation Mission-Water 1 satellites are selected for wind retrieval due to the fact that the signal at this frequency is sensitive to high wind speeds but less sensitive to rain scatter than those acquired at other higher frequency channels. The AMSR-E and AMSR2 observations of 53 hurricanes between 2002 and 2014 are collected and collocated with stepped-frequency microwave radiometer (SFMR) measurements. Based on the small slope approximation/small perturbation method model and an ocean surface roughness spectrum, the wind speeds are retrieved from the TB data and validated against the SFMR measurements. The statistical comparison of the entire data set shows that the bias and root-mean-square error (RMSE) of the retrieved wind speeds are 1.11 and 4.34 m/s, respectively, which suggests that the proposed method can obtain high wind speeds under hurricane conditions. Two case studies show that the wind speed retrieval bias and RMSE are 1.08 and 3.93 m/s for Hurricane Earl and 0.09 and 3.23 m/s for Hurricane Edouard, respectively. The retrieved wind speeds from the AMSR-E and AMSR2 continuous three-day observations clearly show the process of hurricane intensification and weakening. [ABSTRACT FROM PUBLISHER]

Snow on sea ice is a sensitive indicator of climate change, it plays an essential role in regulating surface and near surface air temperatures. Given the high albedo and low thermal conductivity, snow is regarded as one of the key reasons for the amplification of the warming in polar regions. The distributions of sea ice and snow depth are essential to the whole thermal conduction in the Arctic. This study focused on the retrieval of snow depth on sea ice from brightness temperatures of the MicroWave Radiometer Imager (MWRI) onboard the FengYun (FY)-3B satellite during the period from December 1, 2010 to April 30, 2011. After cross calibrated to the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) Level 2A data, the MWRI brightness temperatures were applied to calculate the sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice (ASI) algorithm. According to the proportional relationship between the snow depth and the surface scattering in 18.7 and 36.5 GHz, the snow depths were derived. In order to eliminate the influence of uncertainties in grain sizes of snow as well as sporadic weather effects, the seven-day averaged snow depths were calculated. Then the results were compared with the snow depths from the AMSR-E Level 3 Sea Ice products. The bias of differences between the MWRI and the AMSR-E Level 3 products are ranged between -1.09 and -0.32 cm,while the standard deviations and the correlation coefficients are ranged from 2.47 to 2.88 cm and from 0.78 to 0.90 for different months. As a result, it could be summarized that FY3B/MWRI showed a promising prospect in retrieving snow depth on sea ice. [ABSTRACT FROM AUTHOR]

Microwave radiometers are instruments for resolving blackbody radiation of heated matter above absolute zero, with many applications including breast cancer diagnosis. In this work a prototype microwave radiometer including a controllable noise reference generator was designed. The design of this noise source is based on the NC303 noise diode that delivers symmetrical white Gaussian noise and flat output power versus frequency (10MHz - 10GHz). An embedded PID control scheme is responsible for temperature stabilization of this sub-unit. The PID controller is designed to cope with disturbance rejection and set-point tracking problems. The first step in PID tuning involved extraction of the system's open loop transfer function. Then the internal model control (IMC) method was used for tuning the controller and the resulting control scheme was successfully applied to the real system. [ABSTRACT FROM AUTHOR]

This paper considers some of the issues of radiometer brightness image formation and reconstruction for use in the NASA-sponsored Calibrated Passive Microwave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature Earth System Data Record project, which generates a multisensor multidecadal time series of high-resolution radiometer products designed to support climate studies. Two primary reconstruction algorithms are considered: the Backus–Gilbert approach and the radiometer form of the scatterometer image reconstruction (SIR) algorithm. These are compared with the conventional drop-in-the-bucket (DIB) gridded image formation approach. Tradeoff study results for the various algorithm options are presented to select optimum values for the grid resolution, the number of SIR iterations, and the BG gamma parameter. We find that although both approaches are effective in improving the spatial resolution of the surface brightness temperature estimates compared to DIB, SIR requires significantly less computation. The sensitivity of the reconstruction to the accuracy of the measurement spatial response function (MRF) is explored. The partial reconstruction of the methods can tolerate errors in the description of the sensor measurement response function, which simplifies the processing of historic sensor data for which the MRF is not known as well as modern sensors. Simulation tradeoff results are confirmed using actual data. [ABSTRACT FROM AUTHOR]

On 5 February 2012 an episode of freezing precipitation took place in the Guadarrama Mountains, at the center of the Iberian Peninsula. This precipitation affected high elevations, where temperatures remained below freezing because of snow cover that had accumulated from snowfall during the previous days. The case study was recorded by surface synoptic observations (SYNOP) at Navacerrada Pass meteorological observatory (belonging to the National Weather Service of Spain). To study winter cloud systems during the TEcoAgua project, a multichannel ground-based microwave radiometer (MMWR), Micro Rain Radar (MRR-2), and isothermal cloud chamber were installed in the study area, thus permitting the monitoring of the freezing precipitation event. Analysis using Meteosat Second Generation (MSG) satellite data and observations permitted the determination of factors that triggered the freezing precipitation event. Freezing drizzle was interspersed with the passage of a warm and cold front. During frontal passage, mid-level clouds inhibited the generation of freezing drizzle, with snowfall recorded in the study area. However, during the period between the two fronts, an absence of mid-level clouds permitted low-level orographic clouds to persist upwind of the mountain system, producing freezing drizzle at the surface. The decisive factors for the generation of freezing drizzle were high humidity at low levels, weak mesoscale updrafts caused by the topography, stability at mid levels, cloud-top temperatures warmer than − 15 °C, and low concentrations of ice nuclei. [ABSTRACT FROM AUTHOR]

Tipping calibration is an important technique for the absolute calibration of ground-based microwave radiometers. The standard tipping calibration is usually used in clear atmosphere. The spatial variations of liquid water in cloudy atmosphere may lead to great calibration errors in the process of standard tipping calibration. A new method of tipping calibration for ground-based microwave radiometers is proposed, which uses an accurate channel to calibrate another inaccurate channel in cloudy atmosphere. The simulation and measurements show that the method proposed here can eliminate the radiation of cloud liquid water and calibrate the radiometer under cloudy-sky conditions effectively. A relative tipping calibration is also introduced to retrieve the parameters in cloudy atmosphere. It has been proven that the relative tipping calibration can reduce the retrieval error significantly in cloudy atmosphere even though neither of the two channels is accurate. [ABSTRACT FROM PUBLISHER]

The sea surface temperature (SST) is a crucial parameter system in climate monitoring. Satellite remote sensing is currently the most common approach for measuring long-term and large-area sea surface temperatures. The SST data measured by the satellite radiometer include the sea surface skin temperature (SSTskin) at a depth of approximately 10 μm. Satellite remote sensing measurement data must be compared and validated with on-site measured data. There are various solutions for on-site measuring instruments; the essential components are usually infrared radiation sensors with radiation output. This paper uses an ordinary integrated infrared thermometer without a radiation output function to remotely measure the sea surface temperature to achieve a high-precision measurement. The scheme of integrating infrared thermometers to measure the sea surface temperature is investigated in this paper. Based on Planck's formula, the bidirectional conversion relationship between temperature and radiation in a certain band is established. The experimental system introduced in this paper uses an integrated infrared thermometer to measure the small blackbody and the target in a cyclic measurement system. We combine it with the sea surface emissivity characteristics and eliminate the influence of sky background radiation on the sea surface to obtain the actual amount of radiation on the sea surface, from which we obtain the actual radiation amount on the sea surface. Accurate SST can be calculated from the actual amount of radiation at the sea surface. The temperature measurement accuracy can reach 0.1 K, allowing it to meet on-site temperature measurement requirements, as well as the comparison measurement requirements confirmed by satellite remote sensing on-site data. There are relatively few products available for sensors with a temperature measurement accuracy of 0.1 K on the market, and temperature measurement equipment with a temperature measurement accuracy of 0.1 K is relatively expensive. Cost is one of the important factors to consider when using in bulk, especially as global warming increases the need for ocean monitoring. The scheme proposed in this paper is beneficial to reduce the volume and weight of measuring instruments, reduce the cost, and promote the large-scale combined application of sea surface temperature change monitoring. [ABSTRACT FROM AUTHOR]

The reliability of the data products from the European Centre for Medium-range Weather Forecasts fields mapped to CloudSat profiles (ECMWF-aux) and the Cloud Geometrical Profile from combined Cloud Profiling Radar (CPR) and Cloud Aerosol and Lidar Infrared Pathfinder Satellite Observations (CALIPSO) (GeoProf-lidar) was determined in a polar marine environment by comparing the satellite products with data from ship-based instrumentation. Simultaneous microwave radiometer profiler (MWRP) measurements were compared with CloudSat's ECMWF-aux temperature and absolute humidity profiles from the surface to 10 km. Cloud-base heights from the ceilometer and radiometer were compared with the GeoProf-lidar cloud-base heights which are derived from a combination of CloudSat and CALIPSO data. Temperatures from ECMWF-aux were generally warmer than those measured by the MWRP during all seasons (negative bias). The root mean square (RMS) differences for temperature were greater than one standard deviation of the MWRP and thus greater than the expected range of the climate. The ECMWF-aux absolute humidity profiles had relatively large RMS differences from the surface to 2 km when compared with the MWRP data during spring and summer. The correlation coefficients between both ECMWF-aux and MWRP temperature and absolute humidity were generally greater than 0.8, indicating a strong agreement between the profile lapse rates. However, negative biases indicated systematic differences in the actual values at all levels. The GeoProf-lidar cloud-base height was compared with the MWRP and ceilometer cloud-base heights. There were fifteen occurrences when both ship-based instruments indicated clear skies but the GeoProf-lidar product indicated clouds. For six of these occurrences no clouds were detectable by visual observation of the radar's reflectivity profile or from the lidar's backscatter profile; five of the occurrences were over mixed ice conditions. This is an indication that the constraints used by the GeoProf-lidar product for cloud detection need to be refined for the Arctic, specifically over mixed ice conditions. Further investigations should include comparisons of GeoProf-lidar cloud heights with the backscatter and reflectivity profiles and with optical depth over mixed ice conditions to help determine the sources of these issues. RÉSUMÉ [Traduit par la rédaction] Nous avons déterminé la fiabilité des produits de données établis à partir des champs du Centre européen pour les prévisions météorologiques à moyen terme présentés sous forme de profils CloudSat (ECMWF-aux) et de Profil géométrique des nuages établis d'après les observations combinées du Radar profileur de nuages (CPR) et du CALIPSO (Cloud Aerosol and Lidar Infrared Pathfinder Satellite Observations) (GeoProf-lidar) dans un environnement marin polaire en comparant les produits satellitaires aux données d'instruments embarqués sur des navires. Nous avons comparé les mesures simultanées d'un radiomètre micro-onde profileur (MWRP) avec les profils de température et d'humidité absolue CloudSat de ECMWF-aux entre la surface et 10 km. Nous avons comparé les hauteurs des bases de nuages mesurées par le célomètre et le radiomètre avec les hauteurs GeoProf-lidar, lesquelles sont dérivées d'une combinaison de données CloudSat et CALIPSO. Les températures selon ECMWF-aux étaient généralement plus élevées que celles mesurées par le MWRP quelle que soit la saison (biais négatif). Les différences quadratiques moyennes pour la température étaient plus grandes que l’écart-type des données MWRP et donc plus grandes que l'intervalle climatologique attendu. Les profils d'humidité absolue ECMWF-aux affichaient des différences RMS relativement grandes de la surface à 2 km par rapport aux données MWRP au printemps et en été. Les coefficients de corrélation de la température et de l'humidité absolue entre ECMWF-aux et MWRP étaient généralement supérieurs à 0,8, ce qui indique une forte concordance des gradients thermiques des profils. Cependant, les biais négatifs indiquaient des différences systématiques dans les valeurs réelles à tous les niveaux. Nous avons comparé la hauteur GeoProf-lidar de la base des nuages avec les hauteurs mesurées par le MWRP et le célomètre. Dans 15 cas, les deux instruments embarqués indiquaient des ciels clairs alors que le produit GeoProf-lidar indiquait des nuages. Dans six de ces cas, aucun nuage n’était détectable par l'observation visuelle du profil de réflectivité du radar ou du profil de rétrodiffusion du lidar; cinq des cas sont survenus lors de conditions de glace mixtes. Cela indique que les contraintes utilisées par le produit GeoProf-lidar pour la détection des nuages doivent être raffinées pour l'Arctique, en particulier au-dessus de conditions de glace mixtes. D'autres études devraient inclure des comparaisons des hauteurs GeoProf-lidar des bases de nuages avec les profils de rétrodiffusion et de réflectivité et avec l’épaisseur optique au-dessus de conditions de glace mixte pour aider à déterminer les sources de ces problèmes. [ABSTRACT FROM AUTHOR]

A prerequisite for the successful retrieval of geophysical parameters from remote sensing measurements is the development of an accurate forward model. The European Space Agency Soil Moisture and Ocean Salinity (SMOS), carrying onboard an L-band interferometric radiometer (Microwave Interferometric Radiometer using Aperture Synthesis), was launched on November 2009. Due to the lack of L-band passive ocean measurements from space, several prelaunch forward models were developed and initially used in the SMOS ocean salinity operational processor. In this paper, an update of the prelaunch semi-empirical forward model is presented, using for the first time, real SMOS data. In particular, the ocean surface emissivity modulation at L-band due to rough sea surface is reviewed and reanalyzed. A new model definition is provided with the help of a simple neural network. The improvement is quantified in terms of retrieved salinity accuracy compared with the climatology and concerns essentially the range of wind speeds higher than 12 m·s-1. [ABSTRACT FROM AUTHOR]

This paper presents a built-in calibration procedure of a 10-to-20 GHz polarimeter aimed at measuring the I, Q, U Stokes parameters of cosmic microwave background (CMB) radiation. A full-band square waveguide double directional coupler, mounted in the antenna-feed system, is used to inject differently polarized reference waves. A brief description of the polarimetric microwave radiometer and the system calibration injector is also reported. A fully polarimetric calibration is also possible using the designed double directional coupler, although the presented calibration method in this paper is proposed to obtain three of the four Stokes parameters with the introduced microwave receiver, since V parameter is expected to be zero for the CMB radiation. Experimental results are presented for linearly polarized input waves in order to validate the built-in calibration system. [ABSTRACT FROM AUTHOR]

Offshore of many coastal regions, the ocean surface wind varies in speed and direction throughout the day, owing to forcing from land/sea temperature differences and orographic effects. Far offshore, both diurnal and semidiurnal wind vector variability has been noted in the Tropical Atmosphere Ocean-TRIangle Trans-Ocean buoy Network (TAO-TRITON) mooring data in the tropical Pacific Ocean. In this manuscript, the tropical diurnal wind variability is examined with microwave radiometer-derived winds from the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM), merged with RapidScat and other scatterometer data. Since the relationship between wind speed and its zonal and meridional components is nonlinear, this manuscript describes an observationally based methodology to merge the radiometer and scatterometer-based wind estimates as a function of observation time, to generate a multi-year dataset of diurnal wind variability. Compared to TAO-TRITON mooring array data, the merged satellite-derived wind components fairly well replicate the semidiurnal zonal wind variability over the tropical Pacific but generally show more variability in the meridional wind components. The meridional component agrees with the associated mooring location data in some locations better than others, or it shows no clear dominant diurnal or semidiurnal mode. Similar discrepancies are noted between two forecast model reanalysis products. It is hypothesized that the discrepancies amongst the meridional winds are due to interactions between surface convergence and convective precipitation over tropical ocean basins. [ABSTRACT FROM AUTHOR]

Sun, W.; Zhang, J.; Meng, J.; Li, Y., and Cao, K., 2020. An arctic gridded sea surface temperature product constructed from spaceborne radiometer data. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 280-286. Coconut Creek (Florida), ISSN 0749-0208. A sea surface temperature (SST) record with a grid size of 0.1° for the Arctic region is presented by fusing satellite-derived SST products from three passive-microwave (WindSat, AMSR-E and ASMR2) and four infrared (AVHRR, MODIS onboard Terra and Aqua, and VIIRS) radiometers (RMs). In this study, optimum interpolation (OI) is used to construct the dataset. The fused SST data of Arctic covering the regime north of 60°N span from 2010 to 2018, available with the format of NetcDF. The accuracy of the gridded Arctic SST product was assessed with the drifting buoy measurements. Comparisons with the measurements from Argo buoys show that the Root Mean Squared Errors (RMSE) of the fusion SST data obtained in this study is relatively stable with values ranging from 0.54 to 0.75 °C. This gridded SST data set is characterized with a high spatiotemporal resolution and an assured accuracy. [ABSTRACT FROM AUTHOR]

Operated since the end of 2009, the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite mission is the first orbiting radiometer that collects regular and global observations from space of two Essential Climate Variables of the Global Climate Observing System: Sea Surface Salinity (SSS) and Soil Moisture. The National Aeronautics and Space Administration (NASA) Aquarius mission, with the primary objective to provide global SSS measurements from space operated from mid-2011 to mid-2015. NASA's Soil Moisture Active-Passive (SMAP) mission, primarily dedicated to soil moisture measurements, but also monitoring SSS, has been operating since early 2015. The primary sensors onboard these three missions are passive microwave radiometers operating at 1.4 GHz (L-band). SSS is retrieved from radiometer measurements of the sea surface brightness temperature (T B). In this paper, we first provide a historical review of SSS remote sensing with passive L-band radiometry beginning with the discussions of measurement principles, technology, sensing characteristics and complementarities of the three aforementioned missions. The assessment of satellite SSS products is then presented in terms of individual mission characteristics, common algorithms, and measurement uncertainties, including the validation versus in situ data, and, the consideration of sampling differences between satellite SSS and in situ salinity measurements. We next review the major scientific achievements of the combined first 10 years of satellite SSS data, including the insights enabled by these measurements regarding the linkages of SSS with the global water cycle, climate variability, and ocean biochemistry. We also highlight the new ability provided by satellites to monitor mesoscale and synoptic-scale SSS features and to advance our understanding of SSS' role in air-sea interactions, constraining ocean models, and improving seasonal predictions. An overview of satellite SSS observation highlights during this first decade and upcoming challenges are then presented. • Historical review of sea surface salinity estimates with passive L-band radiometry • SMOS, Aquarius, and SMAP sensor characteristics and algorithms are presented. • Quality assessment of latest satellite SSS products is provided. • The major scientific achievements of the first decade of satellite SSS are reviewed. [ABSTRACT FROM AUTHOR]

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 . [ABSTRACT FROM AUTHOR]

Land Surface Temperature (ST) represents the radiative temperature of the Earth's surface and is used as input to hydrological, agricultural, and meteorological science applications. Due to the synoptic nature of satellite imaging systems, ST products derived from space-borne platforms are invaluable for estimating ST at the local, regional, and global scale. In the past two decades, an emphasis has been placed on the need to develop algorithms necessary to deliver accurate surface temperature products to support the needs of science users. However, corresponding efforts to validate these products are hindered by the availability of quality ground-based reference measurements. The NOAA Surface Radiation Budget (SURFRAD) network is commonly used to support ST validation efforts, but their instrumentation is broadband (4–50 μ m) and several of their sites lack spatial uniformity. To address the apparent deficiencies within existing validation networks, this work discusses a prototype radiometer that was developed to provide surface temperature estimates to support validation efforts for spaceborne thermal instruments. Specifically, a prototype radiometer was designed, built, and calibrated to acquire ground reference data to be used to validate ST product(s) derived from Landsat 8 image data. Lab-based efforts indicate that these prototype instruments are accurate to within 1.28 K and initial field measurements demonstrate agreement to Landsat-derived ST products to within 1.37 K. [ABSTRACT FROM AUTHOR]

Accurate prediction of sea surface emission is the key for sea surface salinity retrieval from satellite microwave radiometer. In order to retrieve salinity from satellite observation, several sea surface microwave emission models have been developed based on theoretical or empirical methods and validated by in-situ measurements in different regions. However, their performances are still unclear in the Chinese coastal waters. In this study, based on two cruises measurements in the East China Sea (ECS), including the brightness temperature measured by a shipborne microwave radiometer and other auxiliary data (sea surface salinity, sea surface temperature and wind speed), the performances of different sea surface emission models are tested. The results showed that the developed models provide fairly good accuracy in predicting brightness temperature; for example, the accuracy of small perturbance/small scale approximation model (SPM/SSA), two-scale model (TSM) and empirical model is in the range from 0.6 K to 3 K. Moreover, the TSM and empirical models are further improved by optimizing the model parameters in the ECS. Finally, the sea surface salinity were retrieved from shipborne measured data based on the improved models, and the results show that the root mean square (rms) differences between retrieved and in-situ sea surface salinity is about 0.4 psu, indicating the significant improvement by the regional model parameters. [ABSTRACT FROM AUTHOR]