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Статті в журналах з теми "Emissivities"

Автор: Grafiati

Опубліковано: 13 липня 2022

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1

Prigent, Catherine, Frédéric Chevallier, Fatima Karbou, Peter Bauer, and Graeme Kelly. "AMSU-A Land Surface Emissivity Estimation for Numerical Weather Prediction Assimilation Schemes." Journal of Applied Meteorology 44, no. 4 (April 1, 2005): 416–26. http://dx.doi.org/10.1175/jam2218.1.

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Abstract This study describes the work performed at the European Centre for Medium-Range Weather Forecasts (ECMWF) to estimate the microwave land surface emissivities at Advanced Microwave Sounding Unit (AMSU)-A frequencies within the specific context and constraint of operational assimilation. The emissivities are directly calculated from the satellite observations in clear-sky conditions using the surface skin temperature derived from ECMWF and the Radiative Transfer for the Television and Infrared Observation Satellite Operational Vertical Sounder (RTTOVS) model, along with the forecast model variables to estimate the atmospheric contributions. The results are analyzed, with special emphasis on the evaluation of the frequency and angular dependencies of the emissivities with respect to the surface characteristics. Possible extrapolation of the Special Sensor Microwave Imager (SSM/I) emissivities to those of the AMSU is considered. Direct calculation results are also compared with emissivity model outputs.

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2

Birman, Camille, Fatima Karbou, and Jean-François Mahfouf. "Daily Rainfall Detection and Estimation over Land Using Microwave Surface Emissivities." Journal of Applied Meteorology and Climatology 54, no. 4 (April 2015): 880–95. http://dx.doi.org/10.1175/jamc-d-14-0192.1.

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AbstractSurface emissivities computed at 89 GHz from AMSU-A, AMSU-B, and SSMI/S instruments are used to detect rain events and to estimate a daily precipitation rate over land surfaces. This new retrieval algorithm, called the emissivity rainfall retrieval (EMIRR) algorithm, is evaluated over France and compared with several other precipitation products. The precipitation detection is performed using temporal changes in daily surface emissivities. A statistical fit, derived from a rainfall analysis product using rain gauge and radar data, is devised to estimate a daily precipitation rate from surface emissivities. Rain retrievals are evaluated over a 1-yr period in 2010 against other precipitation products, including rain gauge measurements. The EMIRR algorithm allows a reasonable detection of rainy events from daily surface emissivities. The number of rainy days and the daily rainfall rates compare well to estimates from other precipitation products. However, the algorithm tends to overestimate low precipitation amounts and to underestimate higher ones, with reduced performances in the presence of snow. Despite such limitations, this new method is very promising and provides a demonstration of the potential use of the 89-GHz surface emissivities to infer relevant information (occurrence and amounts) related to daily precipitation over land surfaces.

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3

Prigent, Catherine, Filipe Aires, and William B. Rossow. "Land Surface Microwave Emissivities over the Globe for a Decade." Bulletin of the American Meteorological Society 87, no. 11 (November 1, 2006): 1573–84. http://dx.doi.org/10.1175/bams-87-11-1573.

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Microwave land surface emissivities have been calculated over the globe for ~10 yr between 19 and 85 GHz at 53° incidence angle for both orthogonal polarizations, using satellite observations from the Special Sensor Microwave Imager (SSM/I). Ancillary data (IR satellite observations and meteorological reanalysis) help remove the contribution from the atmosphere, clouds, and rain from the measured satellite signal and separate surface temperature from emissivity variations. The method to calculate the emissivity is general and can be applied to other sensors. The monthly mean emissivities are available for the community, with a 0.25° × 0.25° spatial resolution. The emissivities are sensitive to variations of the vegetation density, the soil moisture, the presence of standing water at the surface, or the snow behavior, and can help characterize the land surface properties. These emissivities (not illustrated in this paper) also allow for improved atmospheric retrieval over land and can help evaluate land surface emissivity models at global scales.

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4

Prigent, C., J. P. Wigneron, W. B. Rossow, and J. R. Pardo-Carrion. "Frequency and angular variations of land surface microwave emissivities: can we estimate SSM/T and AMSU emissivities from SSM/I emissivities?" IEEE Transactions on Geoscience and Remote Sensing 38, no. 5 (2000): 2373–86. http://dx.doi.org/10.1109/36.868893.

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5

Malone, C. G., B. I. Choi, M. I. Flik, and E. G. Cravalho. "Spectral Emissivity of Optically Anisotropic Solid Media." Journal of Heat Transfer 115, no. 4 (November 1, 1993): 1021–28. http://dx.doi.org/10.1115/1.2911356.

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This work determines the spectral emissivity of a semi-infinite uniaxial medium in vacuum. If the optic axis is normal to the surface, then, for many materials and wavelengths, such as rutile between 10 and 25 μm, the directional and hemispherical spectral emissivities of the medium can be approximated, with an error of less than 10 percent, as those of an isotropic medium possessing the ordinary optical constants. In contrast, if the optic axis is parallel to the surface, the directional and hemispherical spectral emissivities can be predicted only by accounting for the optical anisotropy of the medium. Measurements of the directional emissivities of rutile crystals conform to the theoretical predictions.

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6

Langsdale, Mary F., Thomas P. F. Dowling, Martin Wooster, James Johnson, Mark J. Grosvenor, Mark C. de Jong, William R. Johnson, Simon J. Hook, and Gerardo Rivera. "Inter-Comparison of Field- and Laboratory-Derived Surface Emissivities of Natural and Manmade Materials in Support of Land Surface Temperature (LST) Remote Sensing." Remote Sensing 12, no. 24 (December 17, 2020): 4127. http://dx.doi.org/10.3390/rs12244127.

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Correct specification of a target’s longwave infrared (LWIR) surface emissivity has been identified as one of the greatest sources of uncertainty in the remote sensing of land surface temperature (LST). Field and laboratory emissivity measurements are essential for improving and validating LST retrievals, but there are differing approaches to making such measurements and the conditions that they are made under can affect their performance. To better understand these impacts we made measurements of fourteen manmade and natural samples under different environmental conditions, both in situ and in the laboratory. We used Fourier transform infrared (FTIR) spectrometers to deliver spectral emissivities and an emissivity box to deliver broadband emissivities. Field- and laboratory-measured spectral emissivities were generally within 1–2% in the key 8–12 micron region of the LWIR atmospheric window for most samples, though greater variability was observed for vegetation and inhomogeneous samples. Differences between laboratory and field spectral measurements highlighted the importance of field methods for these samples, with the laboratory setup unable to capture sample structure or inhomogeneity. The emissivity box delivered broadband emissivities with a consistent negative bias compared to the FTIR-based approaches, with differences of up to 5%. The emissivities retrieved using the different approaches result in LST retrieval differences of between 1 and 4 °C, stressing the importance of correct emissivity specification.

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7

ZHANG, JIE, SHAO-FENG WANG, and MEN-QUAN LIU. "PROTON BRANCH OF MODIFIED URCA PROCESS IN STRONG MAGNETIC FIELD AND SUPERFLUIDITY OF NEUTRON STAR CORES." International Journal of Modern Physics E 19, no. 03 (March 2010): 437–47. http://dx.doi.org/10.1142/s0218301310014856.

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The modified URCA process produces efficient neutrino energy losses in neutron star cores, and has been shown to go via neutron and proton branches. Based on the improved electron chemical potential and critical temperature of superfluidity, the effects of strong magnetic field and superfluidity on the proton branch of modified URCA process are investigated simultaneously in this paper. The results show that strong magnetic field enhances the neutrino emissivities compared to the case in zero magnetic field, and superfluidity reduces the emissivities significantly. For the total neutrino emissivities, the magnetic field is dominant at the initial stage of neutron star cooling, but the superfluidity becomes crucial as the temperature drops below the critical temperature.

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8

Bowen, C., F. Wagon, D. Galmiche, P. Loiseau, E. Dattolo, and D. Babonneau. "Gold emissivities for hydrocode applications." Physics of Plasmas 11, no. 10 (October 2004): 4641–48. http://dx.doi.org/10.1063/1.1777615.

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9

Ficker, Tomáš. "Virtual emissivities of infrared thermometers." Infrared Physics & Technology 114 (May 2021): 103656. http://dx.doi.org/10.1016/j.infrared.2021.103656.

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10

Bowen, C. "NLTE emissivities via an ionisation temperature." Journal of Quantitative Spectroscopy and Radiative Transfer 71, no. 2-6 (October 2001): 201–14. http://dx.doi.org/10.1016/s0022-4073(01)00068-1.

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11

Berger, X., and J. Bathiebo. "Directional spectral emissivities of clear skies." Renewable Energy 28, no. 12 (October 2003): 1925–33. http://dx.doi.org/10.1016/s0960-1481(03)00059-4.

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12

Yoshida, Masashi, Noah Utsumi, Ryuta Ichiki, Jung Hyun Kong, and Masahiro Okumiya. "Surface Structure and Emissivity of Aluminum Nitride Films." Advanced Materials Research 1110 (June 2015): 163–68. http://dx.doi.org/10.4028/www.scientific.net/amr.1110.163.

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In this study, aluminum nitride films were formed on aluminum substrates by gas nitriding in order to improve their low emissivities. To accomplish this, aluminum alloys were subjected to nitriding conditions at 773 and 823 K for 0–5 h, using alumina and magnesium powders. The resulting aluminum nitride films were several micrometers thick and the films were dark brown or black. The surface structures of the aluminum nitride films were investigated using a scanning electron microscope, which showed fine acicular aluminum nitride nodules with diameters on the order of several micrometers. Emissivities were evaluated at 298 K using Fourier transform infrared spectroscopy, in a wavelength range of 2–14 μm. Total emissivities at temperatures between 323 and 383 K were estimated from emissivity results obtained at 298 K. It was subsequently found that emissivity decreases with increasing wavelength and an emissivity of 0.80 was observed at a wavelength of 2 μm. Total emissivity was 0.49 % at 298 K and was in excess of 0.50 between 323 and 383 K.

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13

Du, Kaikai, Lu Cai, Hao Luo, Yue Lu, Jingyi Tian, Yurui Qu, Pintu Ghosh, et al. "Wavelength-tunable mid-infrared thermal emitters with a non-volatile phase changing material." Nanoscale 10, no. 9 (2018): 4415–20. http://dx.doi.org/10.1039/c7nr09672k.

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14

Wang, D., C. Prigent, L. Kilic, S. Fox, C. Harlow, C. Jimenez, F. Aires, C. Grassotti, and F. Karbou. "Surface Emissivity at Microwaves to Millimeter Waves over Polar Regions: Parameterization and Evaluation with Aircraft Experiments." Journal of Atmospheric and Oceanic Technology 34, no. 5 (May 2017): 1039–59. http://dx.doi.org/10.1175/jtech-d-16-0188.1.

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AbstractThe Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2) is linked to a climatology of monthly emissivity estimates and provides a parameterization of the surface emissivity up to 700 GHz, in the framework of the preparation for the Ice Cloud Imager (ICI) on board the Meteorological Operational Satellite Second Generation (MetOp-SG). It is an updated version of the Tool to Estimate Land Surface Emissivities at Microwave Frequencies (TELSEM; Aires et al. 2011). This study presents the parameterization of continental snow and ice and sea ice emissivities in TELSEM2. It relies upon satellite-derived emissivities up to 200 GHz, and it is anchored to the Special Sensor Microwave Imager (SSM/I) TELSEM monthly climatology dataset (19–85 GHz). Emissivities from Météo-France and the National Oceanic and Atmospheric Administration (NOAA) at frequencies up to 190 GHz were used, calculated from the Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Sounding Unit-B (AMSU-B) observations. TELSEM2 has been evaluated up to 325 GHz with the observations of the International Submillimeter Airborne Radiometer (ISMAR) and the Microwave Airborne Radiometer Scanning System (MARSS), which were operated on board the Facility for Airborne Atmospheric Measurements (FAAM) aircraft during the Cold-Air Outbreak and Submillimeter Ice Cloud Study (COSMICS) campaign over Greenland. Above continental snow and ice, TELSEM2 is very consistent with the aircraft estimates in spatially homogeneous regions, especially at 89 and 157 GHz. Over sea ice, the aircraft estimates are very variable spatially and temporally, and the comparisons with the TELSEM2 were not conclusive. TELSEM2 will be distributed in the new version of the RTTOV radiative transfer community code, to be available in 2017.

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15

Crnomarković, Nenad, Srđan Belošević, Stevan Nemoda, Ivan Tomanović, and Aleksandar Milićević. "DETERMINATION OF THE WALL VARIABLES WITHIN THE ZONAL MODEL OF RADIATION INSIDE A PULVERIZED COAL-FIRED FURNACE." Facta Universitatis, Series: Mechanical Engineering 16, no. 2 (August 1, 2018): 219. http://dx.doi.org/10.22190/fume180227021c.

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Determination of the wall variables (wall emissivities, wall temperatures, and heat fluxes) when the zonal model of radiation is used in numerical simulations of processes inside a pulverized coal-fired furnaces is described. Two methods for determination of the wall variables, i.e., a repeated run of numerical simulation (RRNS) and a temporary correction of the total exchange areas (TCTEA) are compared. Investigation was carried out for three values of the flame total extinction coefficient and four values of the initial wall emissivities. Differences of the wall variables were determined using the arithmetic means (AMs) of the relative differences. The AMs of the relative differences of the wall variables increased with an increase in the flame total extinction coefficient and changed a little with an increase in the initial values of the wall emissivities. For the selected furnace, the smallest differences of the wall variables were obtained for Kt=0.3 m-1 and ew,in=0.7. Although both methods can be used for determination of the wall variables, the RRNS method was recommended because the manipulation with files was easier for it. mmended because the manipulation with files was easier for it.

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16

Kamiuto, Kouichi. "Total Emissivities of Temperature Fluctuating Molecular Gases." Journal of Thermophysics and Heat Transfer 11, no. 3 (July 1997): 482–83. http://dx.doi.org/10.2514/2.6268.

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17

Fuller, Raymond P., Pei-Kuan Wu, Kevin A. Kirkendall, Abdollah S. Nejad, and Kouichi Kamiuto. "Total emissivities of temperature-fluctuating molecular gases." Journal of Thermophysics and Heat Transfer 11 (January 1997): 482–84. http://dx.doi.org/10.2514/3.923.

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18

Del Zanna, G., P. J. Storey, N. R. Badnell, and V. Andretta. "Helium Line Emissivities in the Solar Corona." Astrophysical Journal 898, no. 1 (July 24, 2020): 72. http://dx.doi.org/10.3847/1538-4357/ab9d84.

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19

REES, W. G. "Infrared emissivities of Arctic land cover types." International Journal of Remote Sensing 14, no. 5 (March 1993): 1013–17. http://dx.doi.org/10.1080/01431169308904392.

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20

Patton, Kelly M., Cecilia Lunardini, and Robert J. Farmer. "Presupernova Neutrinos: Realistic Emissivities from Stellar Evolution." Astrophysical Journal 840, no. 1 (April 26, 2017): 2. http://dx.doi.org/10.3847/1538-4357/aa6ba8.

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21

Aver, Erik, Keith A. Olive, R. L. Porter, and Evan D. Skillman. "The primordial helium abundance from updated emissivities." Journal of Cosmology and Astroparticle Physics 2013, no. 11 (November 7, 2013): 017. http://dx.doi.org/10.1088/1475-7516/2013/11/017.

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22

Elgarøy, Ø., L. Engvik, E. Osnes, F. V. De Blasio, M. Hjorth-Jensen, and G. Lazzari. "Emissivities of Neutrinos in Neutron Star Cores." Physical Review Letters 76, no. 12 (March 18, 1996): 1994–97. http://dx.doi.org/10.1103/physrevlett.76.1994.

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23

Fan, Chongxing, and Xianglei Huang. "Direct impact of solar farm deployment on surface longwave radiation." Environmental Research Communications 3, no. 12 (December 1, 2021): 125006. http://dx.doi.org/10.1088/2515-7620/ac40f1.

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Abstract Motivated by a previous study of using the Moderate Resolution Imaging Spectroradiometers (MODIS) observations to quantify changes in surface shortwave spectral reflectances caused by six solar farms in the southwest United States, here we used a similar method to study the longwave effects of the same six solar farms, with emphases on surface emissivities and land surface temperature (LST). Two MODIS surface products were examined: one relying on generalized split-window algorithm while assuming emissivities from land cover classifications (MYD11A2), the other based on Temperature Emissivity Separation algorithm capable of dynamically retrieving emissivities (MYD21A2). Both products suggest that, compared to adjacent regions without changes before and after solar farm constructions, the solar farm sites have reduced outgoing radiances in three MODIS infrared window channels. Such reduction in upward longwave radiation is consistent with previous in situ measurements. The MYD11A2 results show constant emissivities before and after solar farm constructions because its land type classification algorithm is not aware of the presence of solar farms. The estimated daytime and nighttime LST reduction due to solar farm deployment are ∼1–4K and ∼0.2–0.9K, respectively. The MYD21A2 results indicate a decrease in Band 31 (10.78–11.28 μm) emissivity up to −0.01 and little change in Band 32 (11.77–12.27 μm) emissivity. The LST decreases in the MYD21A2 is slightly smaller than its counterpart in the MYD11A2. Laboratory and in situ measurements indicate the longwave emissivity of solar panels can be as low as 0.83, considerably smaller than MODIS retrieved surface emissivity over the solar farm sites. The contribution of exposed and shaded ground within the solar farm to the upward longwave radiation needs to be considered to fully explain the results. A synthesis of MODIS observations and published in situ measurements is presented. Implication for parameterizing such solar farm longwave effect in the climate models is also discussed.

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24

MOMENI, M., and M. SARADJIAN. "Evaluating NDVI-based emissivities of MODIS bands 31 and 32 using emissivities derived by Day/Night LST algorithm." Remote Sensing of Environment 106, no. 2 (January 30, 2007): 190–98. http://dx.doi.org/10.1016/j.rse.2006.08.005.

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25

Liu, L., and K. Shang. "MINERAL INFORMATION EXTRACTION BASED ON GAOFEN-5’S THERMAL INFRARED DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1157–60. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1157-2018.

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Gaofen-5 carries six instruments aimed at various land and atmosphere applications, and it’s an important unit of China High-resolution Earth Observation System. As Gaofen-5’s thermal infrared payload is similar to that of ASTER, which is widely used in mineral exploration, application of Gaofen-5’s thermal infrared data is discussed regarding its capability in mineral classification and silica content estimation. First, spectra of silicate, carbonate, sulfate minerals from a spectral library are used to conduct spectral feature analysis on Gaofen-5’s thermal infrared emissivities. Spectral indices of band emissivities are proposed, and by setting thresholds of these spectral indices, it can classify three types of minerals mentioned above. This classification method is tested on a simulated Gaofen-5 emissivity image. With samples acquired from the study area, this method is proven to be feasible. Second, with band emissivities of silicate and their silica content from the same spectral library, correlation models have been tried to be built for silica content inversion. However, the highest correlation coefficient is merely 0.592, which is much lower than that of correlation model built on ASTER thermal infrared emissivity. It can be concluded that GF-5’s thermal infrared data can be utilized in mineral classification but not in silica content inversion.

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26

Li, Xiangning, and William Strieder. "Fiber Bed Effective Emissivities from Multiple-Scattering Calculations." Industrial & Engineering Chemistry Research 43, no. 12 (June 2004): 3041–48. http://dx.doi.org/10.1021/ie030598u.

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27

Tang, Bo-Hui, Hua Wu, Chuanrong Li, and Zhao-Liang Li. "Estimation of broadband surface emissivity from narrowband emissivities." Optics Express 19, no. 1 (December 22, 2010): 185. http://dx.doi.org/10.1364/oe.19.000185.

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28

Berdermann, J. "Neutrino emissivities in 2SC color-superconducting quark matter." Physics of Particles and Nuclei 39, no. 7 (November 23, 2008): 1163–66. http://dx.doi.org/10.1134/s1063779608070320.

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29

Thelen, Jean-Claude, Stephan Havemann, Stuart M. Newman, and Jonathan P. Taylor. "Hyperspectral retrieval of land surface emissivities using ARIES." Quarterly Journal of the Royal Meteorological Society 135, no. 645 (October 2009): 2110–24. http://dx.doi.org/10.1002/qj.520.

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30

Tian, Jiemo, W. R. Zhu, and H. D. Li. "Infrared radiant emissivities of ceramics with spinel structure." International Journal of Infrared and Millimeter Waves 14, no. 9 (September 1993): 1855–63. http://dx.doi.org/10.1007/bf02101337.

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31

Sinn, Christoph, Felix Kranz, Jonas Wentrup, Jorg Thöming, Gregor D. Wehinger, and Georg R. Pesch. "CFD Simulations of Radiative Heat Transport in Open-Cell Foam Catalytic Reactors." Catalysts 10, no. 6 (June 26, 2020): 716. http://dx.doi.org/10.3390/catal10060716.

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The heat transport management in catalytic reactors is crucial for the overall reactor performance. For small-scale dynamically-operated reactors, open-cell foams have shown advantageous heat transport characteristics over conventional pellet catalyst carriers. To design efficient and safe foam reactors as well as to deploy reliable engineering models, a thorough understanding of the three heat transport mechanisms, i.e., conduction, convection, and thermal radiation, is needed. Whereas conduction and convection have been studied extensively, the contribution of thermal radiation to the overall heat transport in open-cell foam reactors requires further investigation. In this study, we simulated a conjugate heat transfer case of a µCT based foam reactor using OpenFOAM and verified the model against a commercial computational fluid dynamics (CFD) code (STAR-CCM+). We further explicitly quantified the deviation made when radiation is not considered. We studied the effect of the solid thermal conductivity, the superficial velocity and surface emissivities in ranges that are relevant for heterogeneous catalysis applications (solid thermal conductivities 1–200 W m−1 K−1; superficial velocities 0.1–0.5 m s−1; surface emissivities 0.1–1). Moreover, the temperature levels correspond to a range of exo- and endothermal reactions, such as CO2 methanation, dry reforming of methane, and methane steam reforming. We found a significant influence of radiation on heat flows (deviations up to 24%) and temperature increases (deviations up to 400 K) for elevated temperature levels, low superficial velocities, low solid thermal conductivities and high surface emissivities.

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32

He, Wenying, Hongbin Chen, Yuejian Xuan, Jun Li, Minzheng Duan, and Weidong Nan. "Ground mobile observation system for measuring multisurface microwave emissivity." Atmospheric Measurement Techniques 14, no. 11 (November 11, 2021): 7069–78. http://dx.doi.org/10.5194/amt-14-7069-2021.

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Abstract. Large microwave surface emissivities with a highly heterogeneous distribution and the relatively small hydrometeor signal over land make it challenging to use satellite microwave data to retrieve precipitation and to be assimilated into numerical models. To better understand the microwave emissivity over land surfaces, we designed and established a ground observation system for the in situ observation of microwave emissivities over several typical surfaces. The major components of the system include a dual-frequency polarized ground microwave radiometer, a mobile observation platform, and auxiliary sensors to measure the surface temperature and soil temperature and moisture; moreover, observation fields are designed comprising five different land surfaces. Based on the observed data from the mobile system, we preliminarily investigated the variations in the surface microwave emissivity over different land surfaces. The results show that the horizontally polarized emissivity is more sensitive to land surface variability than the vertically polarized emissivity is: the former decreases to 0.75 over cement and increases to 0.90 over sand and bare soil and up to 0.97 over grass. The corresponding emissivity polarization difference is obvious over water (>0.3) and cement (approximately 0.25) but reduces to 0.1 over sand and 0.05 over bare soil and almost 0.01 or close to zero over grass; this trend is similar to that of the Tb polarization difference. At different elevation angles, the horizontally/vertically polarized emissivities over land surfaces obviously increase/slightly decrease with increasing elevation angles but exhibit the opposite trend over water.

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33

Bennartz, Ralf, Katja Paape, Jürgen Fischer, and Tim J. Hewison. "Comparison of observed and simulated microwave land surface emissivities over bare soil." Meteorologische Zeitschrift 11, no. 1 (March 5, 2002): 5–12. http://dx.doi.org/10.1127/0941-2948/2002/0011-0005.

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34

Harlow, R. Chawn. "Airborne Retrievals of Snow Microwave Emissivity at AMSU Frequencies Using ARTS/SCEM-UA." Journal of Applied Meteorology and Climatology 46, no. 1 (January 1, 2007): 23–35. http://dx.doi.org/10.1175/jam2440.1.

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Abstract The remote sounding, by satellite, of atmospheric temperature and humidity is an important source of data for assimilation into operational weather forecasting routines. For retrievals of these variables near the surface, wavebands with low optical depths are monitored to allow penetration through the overlying atmosphere. Brightness temperatures in these relatively transparent bands are also sensitive to the land surface emissivity and effective temperature. Inadequate understanding of these land surface emissivities is a major issue when assimilating Advanced Microwave Sounding Unit data for the land-covered portion of the globe. One approach for estimating the emissivity of snow-covered surfaces is an empirical model derived from satellite-based and land-based retrievals of emissivity for a variety of snow types. The Met Office’s Hercules C-130 aircraft flew over snow-covered Arctic terrain of northern Finland during the Polar Experiment (POLEX) of March 2001. On these flights, microwave radiometers provided microwave brightness temperatures at 23.8, 50.3, 89.0, 157, and 183 GHz. The work presented here uses these data along with a robust multiparameter optimization routine [Shuffled Complex Evolution Metropolis (SCEM-UA)] coupled to the Atmospheric Radiative Transfer Simulator (ARTS) to retrieve emissivities at the measured frequencies. These results are then used to validate an empirical model. This latter model predicts 23.8–157-GHz emissivities with an RMSE of less than 0.02 and bias of less than 0.01 when compared with data at an incidence angle of 40°. Nonmonotonic behavior in the emissivity spectrum for this campaign, reported in earlier work, is confirmed by the retrievals presented here.

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35

Kalman, Joseph, Nick Glumac, and Herman Krier. "High-Temperature Metal Oxide Spectral Emissivities for Pyrometry Applications." Journal of Thermophysics and Heat Transfer 29, no. 4 (October 2015): 874–79. http://dx.doi.org/10.2514/1.t4565.

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36

Bowen, C., A. Decoster, C. J. Fontes, K. B. Fournier, O. Peyrusse, and Yu V. Ralchenko. "Review of the NLTE emissivities code comparison virtual workshop." Journal of Quantitative Spectroscopy and Radiative Transfer 81, no. 1-4 (September 2003): 71–84. http://dx.doi.org/10.1016/s0022-4073(03)00061-x.

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37

Porter, R. L., R. P. Bauman, G. J. Ferland, and K. B. MacAdam. "Theoretical He i Emissivities in the Case B Approximation." Astrophysical Journal 622, no. 1 (February 28, 2005): L73—L75. http://dx.doi.org/10.1086/429370.

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38

Alberti, Michael, Roman Weber, and Marco Mancini. "Gray gas emissivities for H2O-CO2-CO-N2 mixtures." Journal of Quantitative Spectroscopy and Radiative Transfer 219 (November 2018): 274–91. http://dx.doi.org/10.1016/j.jqsrt.2018.08.008.

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39

Ballico, Mark J., and Trebor P. Jones. "Novel Experimental Technique for Measuring High-Temperature Spectral Emissivities." Applied Spectroscopy 49, no. 3 (March 1995): 335–40. http://dx.doi.org/10.1366/0003702953963607.

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A novel experimental technique for the measurement of spectral emissivities in the temperature range 500 to 1000°C of materials that are both poorly thermally conducting and have a high level of transparency is presented. A Fourier transform infrared spectrometer (FT-IR) is used to compare the spectral radiance from a nearly isothermal, but rapidly cooling, sample to that of a reference blackbody. Experimental results obtained from metal metaborate samples and a theoretical analysis of the technique show the effectiveness of this method, particularly for the case of molten samples.

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40

Nakamura, Satoshi X. "Neutrino Emissivities from Deuteron-Breakup and Formation in Supernovae." Journal of Physics: Conference Series 569 (December 8, 2014): 012057. http://dx.doi.org/10.1088/1742-6596/569/1/012057.

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41

Yao, Yin-Hua, and Quan-Xi Cao. "Infrared emissivities of Mn, Co co-doped ZnO powders." Chinese Physics B 21, no. 12 (December 2012): 124205. http://dx.doi.org/10.1088/1674-1056/21/12/124205.

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42

Prigent, Catherine, William B. Rossow, and Elaine Matthews. "Microwave land surface emissivities estimated from SSM/I observations." Journal of Geophysical Research: Atmospheres 102, no. D18 (September 1, 1997): 21867–90. http://dx.doi.org/10.1029/97jd01360.

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43

Felde, Gerald W., and John D. Pickle. "Retrieval of 91 and 150 GHz Earth surface emissivities." Journal of Geophysical Research 100, no. D10 (1995): 20855. http://dx.doi.org/10.1029/95jd02221.

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44

Porter, R. L., G. J. Ferland, P. J. Storey, and M. J. Detisch. "Improved He i emissivities in the case B approximation." Monthly Notices of the Royal Astronomical Society: Letters 425, no. 1 (July 9, 2012): L28—L31. http://dx.doi.org/10.1111/j.1745-3933.2012.01300.x.

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45

Luo, Gang, Xijian Lin та James A. Coakley. "11-μm emissivities and droplet radii for marine stratocumulus". Journal of Geophysical Research 99, № D2 (1994): 3685. http://dx.doi.org/10.1029/93jd02462.

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46

Mizuno, Masashi, and Mitsuo Utsuno. "Emissivities of metals for the purpose of radiation thermometry." DENKI-SEIKO[ELECTRIC FURNACE STEEL] 57, no. 2 (1986): 95–103. http://dx.doi.org/10.4262/denkiseiko.57.95.

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47

DeWitt, David P., and Roger E. Rondeau. "Measurement of surface temperatures and spectral emissivities duringlaser irradiation." Journal of Thermophysics and Heat Transfer 3, no. 2 (April 1989): 153–59. http://dx.doi.org/10.2514/3.142.

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48

Rosenkranz, P. W. "Rough-sea microwave emissivities measured with the SSM/I." IEEE Transactions on Geoscience and Remote Sensing 30, no. 5 (1992): 1081–85. http://dx.doi.org/10.1109/36.175345.

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49

Nasu, S., S. X. Nakamura, K. Sumiyoshi, T. Sato, F. Myhrer, and K. Kubodera. "NEUTRINO EMISSIVITIES FROM DEUTERON BREAKUP AND FORMATION IN SUPERNOVAE." Astrophysical Journal 801, no. 2 (March 5, 2015): 78. http://dx.doi.org/10.1088/0004-637x/801/2/78.

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50

Ishii, J., M. Kobayashi, and F. Sakuma. "Effective emissivities of black-body cavities with grooved cylinders." Metrologia 35, no. 3 (June 1998): 175–80. http://dx.doi.org/10.1088/0026-1394/35/3/5.

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