Erzsebet Eva Borbas
@wisc.edu
Scopus Publications
- Evaluation of total column water vapour products from satellite observations and reanalyses within the GEWEX Water Vapor Assessment
Tim Trent, Marc Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, Thomas Wagner
Atmospheric Chemistry and Physics, 2024
Since 2011, the Global Energy and Water cycle Exchanges (GEWEX) Water Vapor Assessment (G-VAP) has provided performance analyses for state-of-the-art reanalysis and satellite water vapour products to the GEWEX Data and Analysis Panel (GDAP) and the user community in general. A significant component of the work undertaken by G-VAP is to characterise the quality and uncertainty of these water vapour records to (i) ensure full exploitation and (ii) avoid incorrect use or interpretation of results. This study presents results from the second phase of G-VAP, where we have extended and expanded our analysis of total column water vapour (TCWV) from phase 1, in conjunction with updating the G-VAP archive. For version 2 of the archive, we consider 28 freely available and mature satellite and reanalysis data products, remapped to a regular longitude–latitude grid of 2° × 2° and on monthly time steps between January 1979 and December 2019. We first analysed all records for a “common” short period of 5 years (2005–2009), focusing on variability (spatial and seasonal) and deviation from the ensemble mean. We observed that clear-sky daytime-only satellite products were generally drier than the ensemble mean, and seasonal variability/disparity in several regions up to 12 kg m−2 related to original spatial resolution and temporal sampling. For 11 of the 28 data records, further analysis was undertaken between 1988–2014. Within this “long period”, key results show (i) trends between −1.18 ± 0.68 to 3.82 ± 3.94 kg m−2 per decade and −0.39 ± 0.27 to 1.24 ± 0.85 kg m−2 per decade were found over ice-free global oceans and land surfaces, respectively, and (ii) regression coefficients of TCWV against surface temperatures of 6.17 ± 0.24 to 27.02 ± 0.51 % K−1 over oceans (using sea surface temperature) and 3.00 ± 0.17 to 7.77 ± 0.16 % K−1 over land (using surface air temperature). It is important to note that trends estimated within G-VAP are used to identify issues in the data records rather than analyse climate change. Additionally, breakpoints have been identified and characterised for both land and ocean surfaces within this period. Finally, we present a spatial analysis of correlations to six climate indices within the long period, highlighting regional areas of significant positive and negative correlation and the level of agreement among records. - Ground-Based Far Infrared Emissivity Measurements Using the Absolute Radiance Interferometer
M. Loveless, D. Adler, F. Best, E. Borbas, X. Huang, R. Knuteson, T. L'Ecuyer, N. R. Nalli, E. Olsen, H. Revercomb, J. K. Taylor
Earth and Space Science, 2024
Far infrared (FIR) emission from the Earth's polar regions has become an area of increasing scientific interest and value. FIR emission is important for understanding Earth's radiative balance and improving global climate models, especially in rapidly changing Arctic conditions. Far‐infrared emission from Earth is not currently being monitored from space, except as part of broadband emission channels of Earth radiation budget measurements like those from the CERES project, and only limited measurements in the FIR spectrum exist. The Absolute Radiance Interferometer (ARI), developed as a prototype of the infrared spectrometer for CLARREO at the University of Wisconsin‐Madison, Space Science and Engineering Center, measures absolute spectrally resolved infrared (IR) radiance from 200 to 2,000 cm−1 (or 5–50 μm) at 0.5 cm−1 resolution with high accuracy (<0.1 K 3‐sigma brightness temperature at scene temperature). This instrument was taken into the field in Madison, Wisconsin, USA, during the winters of 2021 and 2022, where the weather can reach polar‐like conditions to measure high spectral resolution radiances of various sample types. Sample materials included water, snow, ice, evergreen leaves, dry grass, and sand, all characteristic of high latitude regions. Radiances collected from both a sky view and the sample view in clear‐sky conditions were used to retrieve FIR emissivity. This paper describes the ARI instrument configuration and capability for ground‐based measurements in the FIR region, and documents retrieved emissivities of various analyzed samples. The retrieved emissivity results are publicly available, and comparisons are made to simulated emissivity estimates. - Physically Based Thermal Infrared Snow/Ice Surface Emissivity for Fast Radiative Transfer Models
Nicholas R. Nalli, Cheng Dang, James A. Jung, Robert O. Knuteson, E. Eva Borbas, Benjamin T. Johnson, Ken Pryor, Lihang Zhou
Remote Sensing, 2023
Accurate thermal infrared (TIR) fast-forward models are critical for weather forecasting via numerical weather prediction (NWP) satellite radiance assimilation and operational environmental data record (EDR) retrieval algorithms. The thermodynamic and compositional data about the surface and lower troposphere are derived from semi-transparent TIR window bands (i.e., surface-sensitive channels) that can span into the far-infrared (FIR) region under dry polar conditions. To model the satellite observed radiance within these bands, an accurate a priori emissivity is necessary for the surface in question, usually provided in the form of a physical or empirical model. To address the needs of hyperspectral TIR satellite radiance assimilation, this paper discusses the research, development, and preliminary validation of a physically based snow/ice emissivity model designed for practical implementation within operational fast-forward models such as the U.S. National Oceanic and Atmospheric Administration (NOAA) Community Radiative Transfer Model (CRTM). To accommodate the range of snow grain sizes, a hybrid modeling approach is adopted, combining a layer scattering model based on the Mie theory (viz., the Wiscombe–Warren 1980 snow albedo model, its complete derivation provided in the Appendices) with a specular facet model. The Mie-scattering model is valid for the smallest snow grain sizes typical of fresh snow and frost, whereas the specular facet model is better suited for the larger sizes and welded snow surfaces typical of aged snow. Comparisons of the model against the previously published spectral emissivity measurements show reasonable agreement across zenith observing angles and snow grain sizes, and preliminary observing system experiments (OSEs) have revealed notable improvements in snow/ice surface window channel calculations versus hyperspectral TIR satellite observations within the NOAA NWP radiance assimilation system. - Evaluation of CAMEL over the Taklimakan Desert Using Field Observations
Yufen Ma, Wei Han, Zhenglong Li, E. Eva Borbas, Ali Mamtimin, Yongqiang Liu
Land, 2023
Infrared (IR) land surface emissivity (LSE) plays an important role in numerical weather prediction (NWP) models through the satellite radiance assimilation. However, due to the large uncertainties in LSE over the desert, many land-surface sensitive channels of satellite IR sensors are not assimilated. This calls for further assessments of the quality of satellite-retrieved LSE in these desert regions. A set of LSE observations were made from field experiments conducted on 16–18 October 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference values to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL) data. Analysis of these data shows four main results. First, the CAMEL datasets appear to sufficiently capture the spatial variations in LSE from the oasis to the hinterland of the TD (this is especially the case in the quartz reststrahlen band). From site 1 at the southern edge of the Taklimakan Desert to site 10 at the northern edge, the measured LSE and the corresponding CAMEL observation in the quartz reststrahlen band first decrease and reach their minimum around sites 4–6 in the hinterland of the Taklimakan Desert. Then, the LSE increases gradually and finally reaches its maximum at site 10, which has a clay ground surface, showing that the LSE is higher at the edges of the desert and lower in the center. Second, the CAMEL values at 11.3 μm have a zonal distribution characterized by a northeast–southwest strike, though such an artifact might have been introduced by ASTER LSE data during the merging process that created the CAMEL dataset. Third, the unrealistic variation of the original EOBS can be filtered out with useful signals, as identified by the first six principal components of the PCA conducted on the laboratory-measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL results correlate well with the measured LSE at the 10 observation sites, with the observed LSE being slightly smaller than the CAMEL values in general. - PATMOS-x Version 6.0: 40 Years of Merged AVHRR and HIRS Global Cloud Data
Michael J. Foster, Coda Phillips, Andrew K. Heidinger, Eva E. Borbas, Yue Li, W. Paul Menzel, Andi Walther, Elisabeth Weisz
Journal of Climate, 2023
A new version of the PATMOS-x multidecadal cloud record, version 6.0, has been produced and is available from the NOAA National Centers for Environmental Information. A description of the processes and methods used for generating the dataset are presented, with a focus on the differences between version 6.0 and the previous version of PATMOS-x, version 5.3. The new version appears both to be more stable, with less intersatellite variability, and to have more consistent polar cloud detection, phase distribution, and cloud-top height distribution when compared against the MODIS EOS record. Improvements in consistency and performance are attributed to the addition of multidimensional variables for cloud detection, constraining cloud retrievals to radiometric bands available throughout the record, and the addition of data from the HIRS instrument. Significance Statement The PATMOS-x project produces multidecadal cloudiness records from polar-orbiting satellites. Version 6.0 combines imager and sounder data from 15 satellites and shows significant improvements in accuracy and stability. - Improvement in tropospheric moisture retrievals from VIIRS through the use of infrared absorption bands constructed from VIIRS and CrIS data fusion
E. Eva Borbas, Elisabeth Weisz, Chris Moeller, W. Paul Menzel, Bryan A. Baum
Atmospheric Measurement Techniques, 2021
An operational data product available for both the Suomi National Polar-orbiting Partnership (S-NPP) and National Oceanic and Atmospheric Administration-20 (NOAA-20) platforms provides high-spatial-resolution infrared (IR) absorption band radiances for Visible Infrared Imaging Radiometer Suite (VIIRS) based on a VIIRS and Crosstrack Infrared Sounder (CrIS) data fusion method. This study investigates the use of these IR radiances, centered at 4.5, 6.7, 7.3, 9.7, 13.3, 13.6, 13.9, and 14.2 µm, to construct atmospheric moisture products (e.g., total precipitable water and upper tropospheric humidity) and to evaluate their accuracy. Total precipitable water (TPW) and upper tropospheric humidity (UTH) retrieved from hyperspectral sounder CrIS measurements are provided at the associated VIIRS sensor's high spatial resolution (750 m) and are compared subsequently to collocated operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and S-NPP VIIRS moisture products. This study suggests that the use of VIIRS IR absorption band radiances will provide continuity with Aqua MODIS moisture products. - Observed hirs and aqua modis thermal infrared moisture determinations in the 2000s
Eva E. Borbas, Paul W. Menzel
Remote Sensing, 2021
This paper compares the tropospheric moisture data records derived from High-resolution Infrared Radiation Sounder (HIRS) and Moderate Resolution Imaging Spectro-radiometer (MODIS) measurements from the years 2003 through 2013. Total Precipitable Water Vapor (TPW) and Upper Tropospheric Precipitable Water Vapor (UTPW) are derived using the infrared spectral bands in the CO2 and H2O absorption bands as well as in the atmospheric windows. Retrieval of TPW and UTPW uses a statistical regression algorithm performed using clear sky radiances (and Brightness Temperatures) measured over land and ocean for both day and night. The TPW and UTPW seasonal cycles of HIRS and MODIS observations are found to be in synchronization with zonal mean values for one degree latitude bands within 2.0 mm and 0.07 mm, respectively. - Climatology of the combined aster modis emissivity over land (Camel) version 2
Michelle Loveless, E. Eva Borbas, Robert Knuteson, Kerry Cawse-Nicholson, Glynn Hulley, Simon Hook
Remote Sensing, 2021
The Combined ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) MODIS (Moderate Resolution Imaging Spectroradiometer) Emissivity over Land (CAMEL) Version 2 (V002) has been available since March 2019 from the NASA LP DAAC (Land Processes Distributed Active Archive Center) and provides global, monthly infrared land surface emissivity and uncertainty at 0.05 degrees (~5 km) resolution. A climatology of the CAMEL V002 product is now available at the same spatial, temporal, and spectral resolution, covering the CAMEL record from 2000 to 2016. Characterization of the climatology over case sites and IGBP (International Geosphere-Biosphere Programme) land cover categories shows the climatology is a stable representation of the monthly CAMEL emissivity. Time series of the monthly CAMEL V002 product show realistic seasonal changes but also reveal subtle artifacts known to be from calibration and processing errors in the MODIS MxD11 emissivity. The use of the CAMEL V002 climatology mitigates many of these time dependent errors by providing an emissivity estimate which represents the complete 16-year record. The CAMEL V002 climatology’s integration into RTTOV (Radiative Transfer for TOVS) v12 is demonstrated through the simulation of IASI (Infrared Atmospheric Sounding Interferometer) radiances. Improved stability in CAMEL Version 3 is expected in the future with the incorporation of the new MxD21 and VIIRS VNP21 emissivity products in MODIS Collection 6.1. - Land surface temperature from GOES-East and GOES-West
Wen Chen, Rachel T. Pinker, Yingtao Ma, Glynn Hulley, Eva Borbas, Tanvir Islam, Kerry-A. Cawse-Nicholson, Simon Hook, Chris Hain, Jeff Basara
Journal of Atmospheric and Oceanic Technology, 2021
Land surface temperature (LST) is an important climate parameter that controls the surface energy budget. For climate applications, information is needed at the global scale with representation of the diurnal cycle. To achieve global coverage there is a need to merge about five independent geostationary (GEO) satellites that have different observing capabilities. An issue of practical importance is the merging of independent satellite observations in areas of overlap. An optimal approach in such areas could eliminate the need for redundant computations by differently viewing satellites. We use a previously developed approach to derive information on LST from GOES-East (GOES-E), modify it for application to GOES-West (GOES-W) and implement it simultaneously across areas of overlap at 5-km spatial resolution. We evaluate the GOES-based LST against in situ observations and an independent MODIS product for the period of 2004–09. The methodology proposed minimizes differences between satellites in areas of overlap. The mean and median values of the differences in monthly mean LST retrieved from GOES-E and GOES-W at 0600 UTC for July are 0.01 and 0.11 K, respectively. Similarly, at 1800 UTC the respective mean and median value of the differences were 0.15 and 1.33 K. These findings can provide guidelines for potential users to decide whether the reported accuracy based on one satellite alone, meets their needs in area of overlap. Since the 6 yr record of LST was produced at hourly time scale, the data are well suited to address scientific issues that require the representation of LST diurnal cycle or the diurnal temperature range (DTR). - Characteristics of Satellite Sampling Errors in Total Precipitable Water from SSMIS, HIRS, and COSMIC Observations
Yunheng Xue, Jun Li, W. Paul Menzel, Eva Borbas, Shu‐Peng Ho, Zhenglong Li, Jinlong Li
Journal of Geophysical Research Atmospheres, 2019
This study quantifies the characteristics of different satellite sampling errors in the time series of total precipitable water (TPW) derived from Constellation System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation, Special Sensor Microwave Imager Sounder (SSMIS), and High‐resolution Infrared Radiation Sounder (HIRS) during the overlapping time period of January 2007 to December 2013. Gap‐free data from ERA5 reanalysis of the European Centre for Medium Range Weather Forecasts are used as reference values. All TPW data are first compared with microwave radiometer measurements from Atmospheric Radiation Measurement Program. In general, they are consistent, with all their regression coefficients being greater than 0.77. Discrepancies in global TPW time series can be mainly attributed to the inherent sampling errors of these three different satellite remote sensing systems. COSMIC has small sampling errors in higher latitudes. But it has scarce samples in tropical regions, which leads to a large sampling error of 3.00 mm in the estimation of global TPW. Sampling in SSMIS is more uniform with mean errors less than 0.5 mm. But the sampling is only over the ocean. Sampling errors in HIRS are larger in tropics and north subtropical areas due to clear sky biased sampling. Moreover, it is significantly correlated with the variability of TPW, whereas the sampling error in COSMIC is less influenced by TPW. Sampling errors will be reduced and more consistent global TPW time series will be derived by simply combining the multisensor samplings together. - Towards a unified and coherent land surface temperature earth system data record from geostationary satellites
Rachel T. Pinker, Yingtao Ma, Wen Chen, Glynn Hulley, Eva Borbas, Tanvir Islam, Chris Hain, Kerry Cawse-Nicholson, Simon Hook, Jeff Basara
Remote Sensing, 2019 - Global Validation of MODIS Near-Surface Air and Dew Point Temperatures
Caroline A. Famiglietti, Joshua B. Fisher, Gregory Halverson, Eva E. Borbas
Geophysical Research Letters, 2018 - The combined ASTER and MODIS emissivity over land (CAMEL) global broadband infrared emissivity product
Michelle Feltz, Eva Borbas, Robert Knuteson, Glynn Hulley, Simon Hook
Remote Sensing, 2018 - The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses
Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, Suranjana Saha
Earth System Science Data, 2018 - The Combined ASTER MODIS Emissivity over Land (CAMEL) Part 2: Uncertainty and validation
Michelle Feltz, Eva Borbas, Robert Knuteson, Glynn Hulley, Simon Hook
Remote Sensing, 2018 - The combined ASTER MODIS Emissivity over Land (CAMEL) part 1: Methodology and high spectral resolution application
E. Borbas, Glynn Hulley, Michelle Feltz, Robert Knuteson, Simon Hook
Remote Sensing, 2018 - Improvements to Terra MODIS L1B, L2, and L3 science products through using crosstalk corrected L1B radiances
Christopher C. Moeller, Richard A. Frey, Eva Borbas, W. Paul Menzel, Truman Wilson, Aisheng Wu, Xu Geng
Proceedings of SPIE the International Society for Optical Engineering, 2017 - Reprocessing of HIRS satellite measurements from 1980 to 2015: Development toward a consistent decadal cloud record
W. Paul Menzel, Richard A. Frey, Eva E. Borbas, Bryan A. Baum, Geoff Cureton, Nick Bearson
Journal of Applied Meteorology and Climatology, 2016 - Land surface VIS/NIR BRDF atlas for RTTOV-11: Model and validation against SEVIRI land SAF albedo product
Jérôme Vidot, Éva Borbás
Quarterly Journal of the Royal Meteorological Society, 2014 - Diurnal variation in sahara desert sand emissivity during the dry season from IASI observations
Guido Masiello, Carmine Serio, Sara Venafra, Italia DeFeis, Eva E. Borbas
Journal of Geophysical Research, 2014 - Dual-regression retrieval algorithm for real-time processing of satellite ultraspectral radiances
William L. Smith, Elisabeth Weisz, Stanislav V. Kireev, Daniel K. Zhou, Zhenglong Li, Eva E. Borbas
Journal of Applied Meteorology and Climatology, 2012 - An approach for improving cirrus cloud-top pressure/Height estimation by merging high-spatial-resolution infrared-window imager data with high-spectral-resolution sounder data
Elisabeth Weisz, W. Paul Menzel, Nadia Smith, Richard Frey, Eva E. Borbas, Bryan A. Baum
Journal of Applied Meteorology and Climatology, 2012 - Improvements to radiometric consistency between AVHRR, MODIS, and VIIRS in SST bands using MICROS online near-real time system
Xingming Liang, Alexander Ignatov, Quanhua Liu, Yong Chen, David Groff, Xiaoxiong Xiong, Changyong Cao, Eva Borbas, Simon Hook
Proceedings of SPIE the International Society for Optical Engineering, 2012 - An objective methodology for infrared land surface emissivity evaluation
Zhenglong Li, Jun Li, Xin Jin, Timothy J. Schmit, Eva E. Borbas, Mitchell D. Goldberg
Journal of Geophysical Research Atmospheres, 2010 - Combining AIRS and MODIS measurements to determine cloud characteristics
Elisabeth Weisz, Paul Menzel, Jun Li, Eva Borbas, Robert Holz
Optics Infobase Conference Papers, 2009 - Deriving atmospheric temperature of the tropopause region-upper troposphere by combining information from GPS radio occultation refractivity and high-spectral-resolution infrared radiance measurements
Eva E. Borbas, W. Paul Menzel, Elisabeth Weisz, Dezso Devenyi
Journal of Applied Meteorology and Climatology, 2008 - Analysis of multispectral fields of satellite IR measurements: Using statistics of second spatial differential of spectral fields for measurement characterization
Youri Plokhenko, W. Paul Menzel, Henry E. Revercomb, Eva Borbas, Paolo Antonelli, EliSabeth Weisz
International Journal of Remote Sensing, 2008 - Development of a global infrared land surface emissivity database for application to clear sky sounding retrievals from multispectral satellite radiance measurements
Suzanne W. Seemann, Eva E. Borbas, Robert O. Knuteson, Gordon R. Stephenson, Hung-Lung Huang
Journal of Applied Meteorology and Climatology, 2008 - Estimation of vertically integrated water vapor in Hungary using MODIS imagery
Anikó Kern, Judit Bartholy, Éva E. Borbás, Zoltán Barcza, Rita Pongrácz, Csaba Ferencz
Advances in Space Research, 2008 - A global infrared land surface emissivity database and its validation
87th Ams Annual Meeting, 2007 - Comparison of water vapor measurements by airborne Sun photometer and near-coincident in situ and satellite sensors during INTEX/ITCT 2004
J. Livingston, B. Schmid, J. Redemann, P. B. Russell, S. A. Ramirez, J. Eilers, W. Gore, S. Howard, J. Pommier, E. J. Fetzer, S. W. Seemann, E. Borbas, D. E. Wolfe, A. M. Thompson
Journal of Geophysical Research Atmospheres, 2007 - International MODIS and AIRS processing package: AIRS products and applications
Elisabeth Weisz
Journal of Applied Remote Sensing, 2007 - Erratum: International MODIS and AIRS processing package: AIRS products and applications (Journal of Applied Remote Sensing (2007) 1 (013519))
Elisabeth Weisz
Journal of Applied Remote Sensing, 2007 - Combining radio occultation refractivities and IR/MW radiances to derive temperature and moisture profiles: A simulation study plus early results using CHAMP and ATOVS
Éva Borbás, W. Paul Menzel, Jun Li, Harold M. Woolf
Journal of Geophysical Research Atmospheres, 2003 - A simulation study combining radio occultation data and IR/MW radiances to derive temperature and moisture profiles
Eva Borbas, W. Paul Menzel, Jun Li
Proceedings of SPIE the International Society for Optical Engineering, 2002
