{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T16:29:17Z","timestamp":1764174557085,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,6,28]],"date-time":"2018-06-28T00:00:00Z","timestamp":1530144000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Infrared surface emissivity is needed for the calculation of net longwave radiation, a critical parameter in weather and climate models and Earth\u2019s radiation budget. Due to a prior lack of spatially and temporally variant global broadband emissivity (BBE) measurements of the surface, it is common practice in land surface and climate models to set BBE to a single constant over the globe. This can lead to systematic biases in the estimated net and longwave radiation for any particular location and time of year. Under the National Aeronautics and Space Administration\u2019s (NASA) Making Earth System Data Records for Use in Research Environments (MEaSUREs) project, a new global, high spectral resolution land surface emissivity dataset has recently been made available at monthly at 0.05 degree resolution since 2000. Called the Combined ASTER MODIS Emissivity over Land (CAMEL), this dataset is created by the merging of the MODIS baseline-fit emissivity database developed at the University of Wisconsin-Madison and the ASTER Global Emissivity Dataset (GED) produced at the Jet Propulsion Laboratory. CAMEL has 13 hinge points between 3.6\u201314.3 \u00b5m which are expanded to cover 417 infrared spectral channels within the same wavelength region using a principal component regression approach. This work presents the method for calculating BBE using the new CAMEL dataset. BBE is computed via numerical integration over the CAMEL High Spectral Resolution product for two different wavelength ranges\u20143.6\u201314.3 \u00b5m which takes advantage of the full, available CAMEL spectra and 8.0\u201313.5 \u00b5m which has been determined to be an optimal range for computing the most representative all wavelength, longwave net radiation. CAMEL BBE uncertainty estimates are computed, and comparisons are made to BBE computed from lab validation data for selected case sites. Variations of BBE over time and land cover classification schemes are investigated and converted into flux to demonstrate the equivalent error in longwave radiation which would be made by the use of a single, constant BBE value. Misrepresentations in BBE by 0.05 at 310 K corresponds to potential errors in longwave radiation of over 25 W\/m2.<\/jats:p>","DOI":"10.3390\/rs10071027","type":"journal-article","created":{"date-parts":[[2018,6,28]],"date-time":"2018-06-28T10:53:33Z","timestamp":1530183213000},"page":"1027","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["The Combined ASTER and MODIS Emissivity over Land (CAMEL) Global Broadband Infrared Emissivity Product"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5871-0353","authenticated-orcid":false,"given":"Michelle","family":"Feltz","sequence":"first","affiliation":[{"name":"Space Science and Engineering Center, University of Wisconsin\u2014Madison, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eva","family":"Borbas","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center, University of Wisconsin\u2014Madison, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Knuteson","sequence":"additional","affiliation":[{"name":"Space Science and Engineering Center, University of Wisconsin\u2014Madison, Madison, WI 53706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3266-179X","authenticated-orcid":false,"given":"Glynn","family":"Hulley","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Hook","sequence":"additional","affiliation":[{"name":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4075","DOI":"10.1029\/JD092iD04p04075","article-title":"The Role of Earth Radiation Budget Studies in Climate and General Circulation Research","volume":"92","author":"Ramanathan","year":"1987","journal-title":"J. Geophys. Res."},{"key":"ref_2","unstructured":"WMO (World Meteorological Organization) (2016). The Global Observing System for Climate: Implementation Needs GCOS-200, WMO."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1029\/JC081i021p03719","article-title":"Remote sensing of the surface emissivity at 9 micron over the globe","volume":"81","author":"Prabhakara","year":"1976","journal-title":"J. Geophys. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/0034-4257(92)90092-X","article-title":"Emissivity of terrestrial materials in the 3\u20135 \u03bcm atmospheric window","volume":"42","author":"Salisbury","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/0034-4257(94)00072-U","article-title":"Algorithms for extracting information from remote thermal-IR observations of the earth\u2019s surface","volume":"51","author":"Norman","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1853","DOI":"10.1175\/JAM2175.1","article-title":"Background Error Correlation between Surface Skin and Air Temperatures: Estimation and Impact on the Assimilation of Infrared Window Radiances","volume":"43","author":"Garand","year":"2004","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1175\/JAMC-D-15-0208.1","article-title":"Assimilation of Infrared Radiance Observations with Sensitivity to Land Surfaces in the Canadian Ensemble\u2013Variational System","volume":"55","author":"Dutta","year":"2016","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2001","DOI":"10.1175\/MWR-D-16-0349.1","article-title":"Sensitivity of Convection-Allowing Forecasts to Land-Surface Model Perturbations and Implications for Ensemble Design","volume":"145","author":"Duda","year":"2017","journal-title":"Mon. Weather Rev."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Niu, G.Y., Yang, Z.L., Mitchell, K.E., Chen, F., Ek, M.B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., and Rosero, E. (2011). The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res. Atmos., 116.","DOI":"10.1029\/2010JD015139"},{"key":"ref_10","first-page":"2867","article-title":"An Improved Land Surface Emissivity Parameter for Land Surface Models Using","volume":"19","author":"Jin","year":"2006","journal-title":"Am. Meterol. Soc."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Zhou, L., Dickinson, R.E., Tian, Y., Jin, M., Ogawa, K., Yu, H., and Schmugge, T. (2003). A sensitivity study of climate and energy balance simulations with use of satellite-derived emissivity data over Northern Africa and the Arabian Peninsula. J. Geophys. Res., 108.","DOI":"10.1029\/2003JD004083"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"D11109","DOI":"10.1029\/2004JD005566","article-title":"Estimation of surface long wave radiation and broadband emissivity using moderate resolution imaging spectroradiometer (MODIS) land surface temperature\/emissivity products","volume":"110","author":"Wang","year":"2005","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1364\/OE.19.000185","article-title":"Estimation of broadband surface emissivity from narrowband emissivities","volume":"19","author":"Tang","year":"2010","journal-title":"Opt. Express"},{"key":"ref_14","first-page":"695","article-title":"Estimation of broadband land surface emissivity from multi-spectral thermal infrared remote sensing","volume":"22","author":"Ogawa","year":"2002","journal-title":"Agron. EDP Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1109\/TGRS.2007.913213","article-title":"Estimating broadband emissivity of arid regions and its seasonal variations using thermal infrared remote sensing","volume":"46","author":"Ogawa","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1080\/17538947.2013.805262","article-title":"A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies","volume":"6","author":"Liang","year":"2013","journal-title":"Int. J. Digit. Earth"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2619","DOI":"10.1109\/TGRS.2012.2216887","article-title":"Empirical algorithms to map global broadband emissivities over vegetated surfaces","volume":"51","author":"Ren","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1109\/LGRS.2012.2206367","article-title":"Estimating the optimal broadband emissivity spectral range for calculating surface longwave net radiation","volume":"10","author":"Cheng","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3390\/rs6010111","article-title":"A comparative study of three land surface broadband emissivity datasets from satellite data","volume":"6","author":"Cheng","year":"2014","journal-title":"Remote Sens."},{"key":"ref_20","unstructured":"Wilber, A.C., Kratz, D.P., and Gupta, S.K. (1999). Surface Emissivity Maps for Use in Retrievals of Longwave Radiation Satellite."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/1087-3562(2004)008<0001:MSBEOT>2.0.CO;2","article-title":"Mapping Surface Broadband Emissivity of the Sahara Desert Using ASTER and MODIS Data","volume":"8","author":"Ogawa","year":"2004","journal-title":"Earth Interact."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Borbas, E., Hulley, G., Feltz, M., Knuteson, R., and Hook, S. (2018). The Combined ASTER MODIS Emissivity over Land (CAMEL) Part 1: Methodology and High Spectral Resolution Application. Remote Sens., 10.","DOI":"10.3390\/rs10040643"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Feltz, M., Borbas, E., Knuteson, R., Hulley, G., and Hook, S. (2018). The Combined ASTER MODIS Emissivity over Land (CAMEL) Part 2: Uncertainty and Validation. Remote Sens., 10.","DOI":"10.3390\/rs10050664"},{"key":"ref_24","unstructured":"Hook, S. (2018, June 15). Combined ASTER and MODIS Emissivity for Land (CAMEL) Uncertainty Monthly Global 0.05Deg. V001, Available online: https:\/\/lpdaac.usgs.gov\/dataset_discovery\/measures\/measures_products_table\/cam5k30uc_v001."},{"key":"ref_25","unstructured":"Borbas, E.E., Hulley, G.C., Knuteson, R.O., and Feltz, M.L. (2018, May 07). MEaSUREs Unified and Coherent Land Surface Temperature and Emissivity (LST&E) Earth System Data Record (ESDR): The Combined ASTER and MODIS Emissivity Database over Land (CAMEL) Users\u2019 Guide. Available online: https:\/\/lpdaac.usgs.gov\/sites\/default\/files\/public\/product_documentation\/cam5k30_v1_user_guide_atbd.pdf."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1175\/2007JAMC1590.1","article-title":"Development of a global infrared land surface emissivity database for application to clear sky sounding retrievals from multispectral satellite radiance measurements","volume":"47","author":"Seemann","year":"2007","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"7966","DOI":"10.1002\/2015GL065564","article-title":"The ASTER Global Emissivity Dataset (ASTER GED): Mapping Earth\u2019s emissivity at 100 meter spatial scale","volume":"42","author":"Hulley","year":"2015","journal-title":"Geophys. Res. Lett."},{"key":"ref_28","unstructured":"Borbas, E.E., and Seemann, S.W. (2018, June 15). Global Infrared Land Surface Emissivity: UW-Madison Baseline Fit Emissivity Database V2.0. Available online: http:\/\/cimss.ssec.wisc.edu\/iremis\/."},{"key":"ref_29","unstructured":"Hulley, G., and Hook, S. (2018, June 15). AG5KMMOH: ASTER Global Emissivity Dataset, Monthly, 0.05 Degree, HDF5 V041, Available online: https:\/\/lpdaac.usgs.gov\/node\/1123."},{"key":"ref_30","unstructured":"Borbas, E.E., and Ruston, B.C. (2010). The RTTOV UWiremis IR Land Surface Emissivity Module, EUMETSAT. EUMETAT NWP SAF, NWPSAF-MO-VS-042."},{"key":"ref_31","unstructured":"Wan, Z. (2018, June 15). MOD11C3 MODIS\/Terra Land Surface Temperature\/Emissivity Monthly L3 Global 0.05Deg CMG. V006, Available online: https:\/\/lpdaac.usgs.gov\/dataset_discovery\/modis\/modis_products_table\/mod11c3_v006."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_33","unstructured":"Channan, S., Collins, K., and Emanuel, W.R. (2014). Global Mosaics of the Standard MODIS Land Cover Type Data, University of Maryland and the Pacific Northwest National Laboratory."},{"key":"ref_34","unstructured":"Borbas, E.E., Feltz, M.L., and Knuteson, R.O. (2018, June 15). Broad Band Emissivity derived from the MEaSUREs CAMEL V001 Database. UW-Madison Space Science and Engineering Center. Dataset. Available online: https:\/\/ezid.lib.purdue.edu\/id\/doi:10.21231\/S2PP8H."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/7\/1027\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:10:31Z","timestamp":1760195431000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/7\/1027"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,28]]},"references-count":34,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2018,7]]}},"alternative-id":["rs10071027"],"URL":"https:\/\/doi.org\/10.3390\/rs10071027","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,6,28]]}}}