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This study presents an original approach on how to generate a radiator with an emissivity less than one by using a conventional blackbody and a screen with a defined area density of holes. This is needed for the calibration of infrared (IR) radiometry, which is a very useful form of temperature measurement in industrial, scientific, and medical applications. One of the major sources of errors in IR radiometry is the emissivity of the surface being measured. Emissivity is a physically well-defined parameter, but in real experiments, it may be influenced by many factors: surface texture, spectral properties, oxidation, and aging of surfaces. While commercial blackbodies are prevalent, the much-needed grey bodies with a known emissivity are unavailable. This work describes a methodology for how to calibrate radiometers in the lab or in the factory or FAB using the "screen approach" and a novel thermal sensor dubbed Digital TMOS. The fundamental physics required to appreciate the reported methodology is reviewed. The linearity in emissivity of the Digital TMOS is demonstrated. The study describes in detail how to obtain the perforated screen as well as how to do the calibration. [ABSTRACT FROM AUTHOR]

A method has been developed for the retrieval of the atmospheric boundary layer parameters in tropical cyclones, namely the dynamic speed, the wind speed at a 10 m height, and the roughness parameter. For the analysis, the wind speed profiles were obtained from NOAA GPS-dropsondes and collocated with the data from the Stepped-Frequency Microwave Radiometer (SFMR). The parameters of the atmospheric boundary layer from the GPS-dropsonde data were obtained by taking into account the self-similarity of the velocity defect profile. The emissivity, determined from the radiometric measurement data, was calibrated to the field data from the GPS-dropsondes. Empirical relations between the wind speed, dynamic wind speed, and aerodynamic drag coefficient with the surface emissivity have been proposed. Based on a comparison of the measured dynamic parameters and the surface emissivity, empirical formulas have also been proposed. From an analysis of cross-polarized Sentinel-1 SAR images and collocated SFMR measurements for hurricanes Irma (2017/09/07) and Maria (2017/09/21 and 2017/09/23), we have obtained the dependences of the NRCS on the ocean surface emissivity, surface wind speed, and friction velocity. These results could potentially be used to improve the algorithm for the retrieval of boundary layer parameters in tropical cyclones from remote sensing data. [ABSTRACT FROM AUTHOR]

This study presents an original approach on how to generate a radiator with an emissivity less than one by using a conventional blackbody and a screen with a defined area density of holes. This is needed for the calibration of infrared (IR) radiometry, which is a very useful form of temperature measurement in industrial, scientific, and medical applications. One of the major sources of errors in IR radiometry is the emissivity of the surface being measured. Emissivity is a physically well-defined parameter, but in real experiments, it may be influenced by many factors: surface texture, spectral properties, oxidation, and aging of surfaces. While commercial blackbodies are prevalent, the much-needed grey bodies with a known emissivity are unavailable. This work describes a methodology for how to calibrate radiometers in the lab or in the factory or FAB using the “screen approach” and a novel thermal sensor dubbed Digital TMOS. The fundamental physics required to appreciate the reported methodology is reviewed. The linearity in emissivity of the Digital TMOS is demonstrated. The study describes in detail how to obtain the perforated screen as well as how to do the calibration.

A method has been developed for the retrieval of the atmospheric boundary layer parameters in tropical cyclones, namely the dynamic speed, the wind speed at a 10 m height, and the roughness parameter. For the analysis, the wind speed profiles were obtained from NOAA GPS-dropsondes and collocated with the data from the Stepped-Frequency Microwave Radiometer (SFMR). The parameters of the atmospheric boundary layer from the GPS-dropsonde data were obtained by taking into account the self-similarity of the velocity defect profile. The emissivity, determined from the radiometric measurement data, was calibrated to the field data from the GPS-dropsondes. Empirical relations between the wind speed, dynamic wind speed, and aerodynamic drag coefficient with the surface emissivity have been proposed. Based on a comparison of the measured dynamic parameters and the surface emissivity, empirical formulas have also been proposed. From an analysis of cross-polarized Sentinel-1 SAR images and collocated SFMR measurements for hurricanes Irma (2017/09/07) and Maria (2017/09/21 and 2017/09/23), we have obtained the dependences of the NRCS on the ocean surface emissivity, surface wind speed, and friction velocity. These results could potentially be used to improve the algorithm for the retrieval of boundary layer parameters in tropical cyclones from remote sensing data.

To improve the thermal modelling of high power isotope separation on-line (ISOL) targets at TRIUMF, an optical technique is being developed that allows for direct off-line and on-line temperature measurements of targets for radioactive isotope production. In this setup the light coming from a hot target through the ionizer opening is collected via a set of optics and coupled into a spectrometer. Thus, from the emission spectrum and Planck's law, the target temperature can be deduced. Tantalum targets were heated to high temperatures and preliminary temperature measurements confirm the correlation between the spectrum of the radiation emitted from the target and the currents used to resistively heat the targets. The final goal is to apply this technique to on-line targets and correlate the isotope releases with the target temperatures for a better understanding of the diffusion and effusion processes happening in the target and for optimizing the delivery of short-lived species. [ABSTRACT FROM AUTHOR]

The joint National Aeronautics and Space Administration and Japanese Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) mission will provide considerably more observations over complex and dynamically changing land backgrounds. A physically based precipitation retrieval using GPM's satellite constellation of passive microwave (PMW) observations has to accommodate the spatially and temporally varying radiometric signature of the land surface to constrain the set of candidate rainfall solutions. The challenge for retrieval algorithms is to identify and isolate precipitation profiles whose simulated observations agree with the satellite observations and are also representative of the surface conditions. Microwave emissivity modeling results are presented from a physically based land algorithm that retrieves soil moisture, vegetation water content, and surface temperature, along with the emissivity using polarized 10, 18, and 37 GHz channel measurements from the WindSat sensor onboard the Coriolis satellite, and results from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The emissivity mean, coefficient of variation, covariance, and correlation slope are examined for the range of clear-scene surface properties observed by WindSat and TRMM between 2003-2012 and 2002-2011, respectively, under a range of seasons, time of day, rain events, etc. These joint data provide a means to examine the extent to which the surface geophysical properties control the microwave land surface emissivity covariability, to better utilize these lower frequency observations in overland PMW-based precipitation retrievals. [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]

Knowledge about the surface soil water content is essential because it controls the surface water dynamics and land-atmosphere interaction. In high mountain areas in particular, soil surface water content controls infiltration and flood events. Although satellite-derived surface soil moisture data from passive microwave sensors are readily available for most regions globally, mountainous areas are often excluded from these data (or at least flagged as biased) due to the strong topographic influence on the retrieved signal. Even though a substantial volume of literature is available dealing with topographic effects on spaceborne brightness temperature, no systematic analysis has been reported. Therefore, we present a comprehensive analysis of topographic effects on brightness temperature at C-band using a two-step approach. First, a well-controlled field experiment is carried out using a mobile truck-mounted C-band radiometer to analyze the impact of geometric and adjacent effects on the radiometer signal. Additionally, a comprehensive radiative transfer model is developed accounting for both effects and tested on the ground-based data. Second, recorded Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) data over the Tibetan Plateau were used to analyze the error due to the impact of topography using the developed model. The results of the field experiment clearly show that the geometric effect of a single hill has a much larger impact on brightness temperature compared to the adjacent effect of multiple hills, whereby, due to the geometric effect, the bias is up to +20 K for horizontal and -13 K for vertical polarization. For the adjacent effect, the bias is less than 3 K for both polarizations. Additionally, the developed radio transfer model was able to reproduce both effects with high accuracy. For the AMSR-E data, the model shows that the brightness temperature recorded is biased in the same way as the ground-based measurements and that uncertainties induced by the wide existence of atypical mountain regions in the Tibetan Plateau will have a great impact on the retrieving error (maximum 30%). The largest impact on the retrieval error, on the other hand, is calculated for the soil moisture with a maximum relative error of 44%. The negligible impact can be attributed to false parameterization of the soil texture, soil surface temperature, and sky temperature. Finally, the overall absolute error in the estimated water content is quantified on average with 4%, whereby single pixels indicate a maximum absolute error of up to 16%. In conclusion, we show that recorded spaceborne brightness temperatures are highly biased by topographic effects in mountainous regions using a comprehensive radiative transfer model. Additionally, we suggest using this model to invert the effective surface emissivity of mountain areas for standard processing of higher level data products such as surface soil water content. [ABSTRACT FROM AUTHOR]

Abstract: We analyze the surface emissivity and radar backscatter measured by the Aquarius L-band radiometer and scatterometer under rainy conditions. The residual signals due to rain are derived from measurements after accounting for roughness due to wind and flat surface emissivity. The wind roughness is accounted for by a geophysical model function (GMF) built using rain-free data. Using more than one year of Aquarius data collocated with SSMI/S, WindSAT rain rate and NCEP wind, our analysis reveals rain rate dependence in radar backscatter and surface emissivity, which become increasingly significant as the wind speed approaches zero and not significant above 15ms−1. The effect of rain on radar backscatter is dominated by raindrop splashing as indicated by the incidence angle dependence and polarization characteristics of the residuals. [Copyright &y& Elsevier]

Blackbody sources at near-ambient temperature are routinely used to calibrate infrared instruments used in remote sensing and thermal imaging applications to measure radiance and radiation temperature. The measured temperature of the blackbody and its calculated effective emissivity determine its radiance and radiation temperature according to Planck's law. The temperature measurement is generally accomplished with a contact thermometer which is calibrated against the international Temperature Scale (iTS-90). The ammonia heat-pipe blackbody of the Physikalisch-Technische Bundesanstalt (PTB) in Germany is a primary source standard working over a wide spectral range with low uncertainties, i.e. less than 33 mK at 10 µm in the temperature range from -60 °C to 50 °C. A more direct method of absolute radiance measurement is to use an absolutely calibrated radiometer, calibrated against a primary detector standard, the cryogenic radiometer. AMBER (Absolute Measurements of Blackbody Emitted Radiance) is an absolutely calibrated radiometer of the Optical Measurement Group of the National Physical Laboratory (NPL) in the UK which was specially designed to determine the radiance and hence the radiation temperature of near-ambient-temperature blackbodies. When AMBER is operated at short wavelengths, where photodetectors offering good long-term stability exist, it derives its traceability through the cryogenic radiometer. However, available photodetectors operating in the 8 µm to 12 im wavelength range offer poor long-term stability so when AMBER is used in this wavelength range, the NPL radiance temperature scale is based on a gallium fixed-point blackbody operating at 29.7646 °C (ITS-90). At other radiance temperatures, the NPL scale also relies on the gallium fixed-point blackbody but requires the calibration of the relative spectral irradiance responsivity of the AMBER radiometer (done against NPL spectral responsivity standards), measurement of the radiometric zero, as well as the use of Planck's equation. This paper gives the results of a comparison of the radiation temperature scale of the PTB with the radiation temperature scale of NPL in a temperature range from -57 °C to 50 °C for wavelengths around 10 µm. [ABSTRACT FROM AUTHOR]

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) (Ku- and Ka-band, or 14 and 35 GHz) provides the capability to resolve the precipitation structure under moderate to heavy precipitation conditions. In this manuscript, the use of near-coincident observations between GPM and the CloudSat Profiling Radar (CPR) (W-band, or 94 GHz) are demonstrated to extend the capability of representing light rain and cold-season precipitation from DPR and the GPM passive microwave constellation sensors. These unique triple-frequency data have opened up applications related to cold-season precipitation, ice microphysics, and light rainfall and surface emissivity effects. [ABSTRACT FROM AUTHOR]