Articles | Volume 13, issue 10
https://doi.org/10.5194/amt-13-5193-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-5193-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Oct 2020
Research article |
| 02 Oct 2020
| 02 Oct 2020
Assessment of global total column water vapor sounding using a spaceborne differential absorption radar
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Richard Roy
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Matthew Lebsock
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
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Laura N. Saunders, Kaley A. Walker, Gabriele P. Stiller, Piera Raspollini, Luis F. Millán, Marco Gai, Chris D. Boone, John Gille, Norbert Glatthor, Armin Kleinboehl, Anne Kleinert, Alyn Lambert, Donal Murtaugh, Patrick E. Sheese, Geoffrey C. Toon, and Gerald Wetzel
EGUsphere, https://doi.org/10.5194/egusphere-2026-4651, https://doi.org/10.5194/egusphere-2026-4651, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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We present a comprehensive evaluation of nitrous oxide (N2O) measurements taken during the 2002–2024 period from five limb-viewing satellite instruments: ACE-FTS, HIRDLS, MIPAS, Aura-MLS, and SMR. Coincident measurements are compared between satellite instruments and with independent reference data from balloon-borne instruments. We show that ACE-FTS, MIPAS, and SMR constitute an excellent 23-year record of N2O measurements that could be used to create an ESA-funded merged dataset in future.
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This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.
Luis F. Millán, Peter Hoor, Michaela I. Hegglin, Gloria L. Manney, Harald Boenisch, Paul Jeffery, Daniel Kunkel, Irina Petropavlovskikh, Hao Ye, Thierry Leblanc, and Kaley Walker
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In the Observed Composition Trends And Variability in the UTLS (OCTAV-UTLS) Stratosphere-troposphere Processes And their Role in Climate (SPARC) activity, we have mapped multiplatform ozone datasets into coordinate systems to systematically evaluate the influence of these coordinates on binned climatological variability. This effort unifies the work of studies that focused on individual coordinate system variability. Our goal was to create the most comprehensive assessment of this topic.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
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In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
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The 2022 Hunga Tonga eruption injected a large amount of water into the stratosphere. Ozone depletion was observed inside the volcanic plume. Chlorine and water vapor injected by this eruption exceeded the normal range, which made the ozone chemistry during this event occur at a higher temperature than polar ozone depletion. Unlike polar ozone chemistry where chlorine nitrate is more important, hypochlorous acid plays a large role in the in-plume chlorine balance and heterogeneous processes.
Luis F. Millán, Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, Irina Petropavlovskikh, Kaley Walker, Krzysztof Wargan, and Andreas Zahn
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Paul S. Jeffery, Kaley A. Walker, Chris E. Sioris, Chris D. Boone, Doug Degenstein, Gloria L. Manney, C. Thomas McElroy, Luis Millán, David A. Plummer, Niall J. Ryan, Patrick E. Sheese, and Jiansheng Zou
Atmos. Chem. Phys., 22, 14709–14734, https://doi.org/10.5194/acp-22-14709-2022, https://doi.org/10.5194/acp-22-14709-2022, 2022
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We analyze satellite-derived distributions of chlorine monoxide (ClO) and hypochlorous acid (HOCl) in the upper atmosphere. For 2005–2020, from 50°S to 50°N and over ~30 to 45 km, ClO and HOCl decreased by −0.7 % and −0.4 % per year, respectively. A detailed model of chemistry and dynamics agrees with the results. These decreases confirm the effectiveness of the 1987 Montreal Protocol, which limited emissions of chlorine- and bromine-containing source gases, in order to protect the ozone layer.
Nathaniel J. Livesey, William G. Read, Lucien Froidevaux, Alyn Lambert, Michelle L. Santee, Michael J. Schwartz, Luis F. Millán, Robert F. Jarnot, Paul A. Wagner, Dale F. Hurst, Kaley A. Walker, Patrick E. Sheese, and Gerald E. Nedoluha
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Preprint archived
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Using simulated airborne and spaceborne W-band (94 GHz) and G-band (239 GHz) radar observations, this article presents an optimal estimation framework that includes dual-frequency reflectivity and differential absorption measurements to obtain more accurate drizzle retrievals. We demonstrate that an improvement of more than one order of magnitude in the retrieval of the drizzle mixing ratio, droplet concentration, and mass-weighted diameter can be achieved compared to W-band only results.
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This study explores the potential of a hypothetical spaceborne radar to observe water vapor within clouds.
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This article presents a novel technique to estimate liquid water content (LWC) profiles in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Luis F. Millán, Peter Hoor, Michaela I. Hegglin, Gloria L. Manney, Harald Boenisch, Paul Jeffery, Daniel Kunkel, Irina Petropavlovskikh, Hao Ye, Thierry Leblanc, and Kaley Walker
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In the Observed Composition Trends And Variability in the UTLS (OCTAV-UTLS) Stratosphere-troposphere Processes And their Role in Climate (SPARC) activity, we have mapped multiplatform ozone datasets into coordinate systems to systematically evaluate the influence of these coordinates on binned climatological variability. This effort unifies the work of studies that focused on individual coordinate system variability. Our goal was to create the most comprehensive assessment of this topic.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, Robert M. Beauchamp, and Arturo Umeyama
Earth Syst. Sci. Data, 16, 2701–2715, https://doi.org/10.5194/essd-16-2701-2024, https://doi.org/10.5194/essd-16-2701-2024, 2024
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This paper describes multifrequency radar observations of clouds and precipitation during the EPCAPE campaign. The data sets were obtained from CloudCube, a Ka-, W-, and G-band atmospheric profiling radar, to demonstrate synergies between multifrequency retrievals. This data collection provides a unique opportunity to study hydrometeors with diameters in the millimeter and submillimeter size range that can be used to better understand the drop size distribution within clouds and precipitation.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
Short summary
Short summary
In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
Matthew D. Lebsock and Mikael Witte
Atmos. Chem. Phys., 23, 14293–14305, https://doi.org/10.5194/acp-23-14293-2023, https://doi.org/10.5194/acp-23-14293-2023, 2023
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This paper evaluates measurements of cloud drop size distributions made from airplanes. We find that as the number of cloud drops increases the distribution of the cloud drop sizes narrows. The data are used to develop a simple equation that relates the drop number to the width of the drop sizes. We then use this equation to demonstrate that existing approaches to observe the drop number from satellites contain errors that can be corrected by including the new relationship.
Yunqian Zhu, Robert W. Portmann, Douglas Kinnison, Owen Brian Toon, Luis Millán, Jun Zhang, Holger Vömel, Simone Tilmes, Charles G. Bardeen, Xinyue Wang, Stephanie Evan, William J. Randel, and Karen H. Rosenlof
Atmos. Chem. Phys., 23, 13355–13367, https://doi.org/10.5194/acp-23-13355-2023, https://doi.org/10.5194/acp-23-13355-2023, 2023
Short summary
Short summary
The 2022 Hunga Tonga eruption injected a large amount of water into the stratosphere. Ozone depletion was observed inside the volcanic plume. Chlorine and water vapor injected by this eruption exceeded the normal range, which made the ozone chemistry during this event occur at a higher temperature than polar ozone depletion. Unlike polar ozone chemistry where chlorine nitrate is more important, hypochlorous acid plays a large role in the in-plume chlorine balance and heterogeneous processes.
Richard M. Schulte, Matthew D. Lebsock, and John M. Haynes
Atmos. Meas. Tech., 16, 3531–3546, https://doi.org/10.5194/amt-16-3531-2023, https://doi.org/10.5194/amt-16-3531-2023, 2023
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In order to constrain climate models and better understand how clouds might change in future climates, accurate satellite estimates of cloud liquid water content are important. The satellite currently best suited to this purpose, CloudSat, is not sensitive enough to detect some non-raining low clouds. In this study we show that information from two other satellite instruments, MODIS and CALIOP, can be combined to provide cloud water estimates for many of the clouds that are missed by CloudSat.
Luis F. Millán, Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, Irina Petropavlovskikh, Kaley Walker, Krzysztof Wargan, and Andreas Zahn
Atmos. Meas. Tech., 16, 2957–2988, https://doi.org/10.5194/amt-16-2957-2023, https://doi.org/10.5194/amt-16-2957-2023, 2023
Short summary
Short summary
The determination of atmospheric composition trends in the upper troposphere and lower stratosphere (UTLS) is still highly uncertain. We present the creation of dynamical diagnostics to map several ozone datasets (ozonesondes, lidars, aircraft, and satellite measurements) in geophysically based coordinate systems. The diagnostics can also be used to analyze other greenhouse gases relevant to surface climate and UTLS chemistry.
Frank Werner, Nathaniel J. Livesey, Luis F. Millán, William G. Read, Michael J. Schwartz, Paul A. Wagner, William H. Daffer, Alyn Lambert, Sasha N. Tolstoff, and Michelle L. Santee
Atmos. Meas. Tech., 16, 2733–2751, https://doi.org/10.5194/amt-16-2733-2023, https://doi.org/10.5194/amt-16-2733-2023, 2023
Short summary
Short summary
The algorithm that produces the near-real-time data products of the Aura Microwave Limb Sounder has been updated. The new algorithm is based on machine learning techniques and yields data products with much improved accuracy. It is shown that the new algorithm outperforms the previous versions, even when it is trained on only a few years of satellite observations. This confirms the potential of applying machine learning to the near-real-time efforts of other current and future mission concepts.
Paul S. Jeffery, Kaley A. Walker, Chris E. Sioris, Chris D. Boone, Doug Degenstein, Gloria L. Manney, C. Thomas McElroy, Luis Millán, David A. Plummer, Niall J. Ryan, Patrick E. Sheese, and Jiansheng Zou
Atmos. Chem. Phys., 22, 14709–14734, https://doi.org/10.5194/acp-22-14709-2022, https://doi.org/10.5194/acp-22-14709-2022, 2022
Short summary
Short summary
The upper troposphere–lower stratosphere is one of the most variable regions in the atmosphere. To improve our understanding of water vapour and ozone concentrations in this region, climatologies have been developed from 14 years of measurements from three Canadian satellite instruments. Horizontal and vertical coordinates have been chosen to minimize the effects of variability. To aid in analysis, model simulations have been used to characterize differences between instrument climatologies.
Kevin M. Smalley, Matthew D. Lebsock, Ryan Eastman, Mark Smalley, and Mikael K. Witte
Atmos. Chem. Phys., 22, 8197–8219, https://doi.org/10.5194/acp-22-8197-2022, https://doi.org/10.5194/acp-22-8197-2022, 2022
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We use geostationary satellite observations to track pockets of open-cell (POC) stratocumulus and analyze how precipitation, cloud microphysics, and the environment change. Precipitation becomes more intense, corresponding to increasing effective radius and decreasing number concentrations, while the environment remains relatively unchanged. This implies that changes in cloud microphysics are more important than the environment to POC development.
Lucien Froidevaux, Douglas E. Kinnison, Michelle L. Santee, Luis F. Millán, Nathaniel J. Livesey, William G. Read, Charles G. Bardeen, John J. Orlando, and Ryan A. Fuller
Atmos. Chem. Phys., 22, 4779–4799, https://doi.org/10.5194/acp-22-4779-2022, https://doi.org/10.5194/acp-22-4779-2022, 2022
Short summary
Short summary
We analyze satellite-derived distributions of chlorine monoxide (ClO) and hypochlorous acid (HOCl) in the upper atmosphere. For 2005–2020, from 50°S to 50°N and over ~30 to 45 km, ClO and HOCl decreased by −0.7 % and −0.4 % per year, respectively. A detailed model of chemistry and dynamics agrees with the results. These decreases confirm the effectiveness of the 1987 Montreal Protocol, which limited emissions of chlorine- and bromine-containing source gases, in order to protect the ozone layer.
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 15, 117–129, https://doi.org/10.5194/amt-15-117-2022, https://doi.org/10.5194/amt-15-117-2022, 2022
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Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that
smears2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is
towardsor
away fromthe Sun, so calculating
across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.
Nathaniel J. Livesey, William G. Read, Lucien Froidevaux, Alyn Lambert, Michelle L. Santee, Michael J. Schwartz, Luis F. Millán, Robert F. Jarnot, Paul A. Wagner, Dale F. Hurst, Kaley A. Walker, Patrick E. Sheese, and Gerald E. Nedoluha
Atmos. Chem. Phys., 21, 15409–15430, https://doi.org/10.5194/acp-21-15409-2021, https://doi.org/10.5194/acp-21-15409-2021, 2021
Short summary
Short summary
The Microwave Limb Sounder (MLS), an instrument on NASA's Aura mission launched in 2004, measures vertical profiles of the temperature and composition of Earth's "middle atmosphere" (the region from ~12 to ~100 km altitude). We describe how, among the 16 trace gases measured by MLS, the measurements of water vapor (H2O) and nitrous oxide (N2O) have started to drift since ~2010. The paper also discusses the origins of this drift and work to ameliorate it in a new version of the MLS dataset.
Richard J. Roy, Matthew Lebsock, and Marcin J. Kurowski
Atmos. Meas. Tech., 14, 6443–6468, https://doi.org/10.5194/amt-14-6443-2021, https://doi.org/10.5194/amt-14-6443-2021, 2021
Short summary
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This study describes the potential capabilities of a hypothetical spaceborne radar to observe water vapor within clouds.
Cited articles
Abel, S. J. and Boutle, I. A.: An improved representation of the raindrop size
distribution for single-moment microphysics schemes, Q. J.
Roy. Meteor. Soc., 138, 2151–2162, https://doi.org/10.1002/qj.1949,
2012. a
Austin, R. T. and Stephens, G. L.: Retrieval of stratus cloud microphysical
parameters using millimeter-wave radar and visible optical depth in
preparation for CloudSat: 1. Algorithm formulation, J. Geophys.
Res.-Atmos., 106, 28233–28242, https://doi.org/10.1029/2000JD000293,
2001. a
Austin, R. T., Heymsfield, A. J., and Stephens, G. L.: Retrieval of ice cloud
microphysical parameters using the CloudSat millimeter-wave radar and
temperature, J. Geophys. Res.-Atmos., 114, d00A23,
https://doi.org/10.1029/2008JD010049, 2009. a
Battaglia, A. and Kollias, P.: Evaluation of differential absorption radars in
the 183 GHz band for profiling water vapour in ice clouds, Atmos. Meas. Tech., 12, 3335–3349, https://doi.org/10.5194/amt-12-3335-2019, 2019. a
Battaglia, A., Haynes, J. M., L'Ecuyer, T., and Simmer, C.:
Identifying multiple-scattering-affected profiles in CloudSat observations
over the oceans, J. Geophys. Res., 113, D00A17,
https://doi.org/10.1029/2008jd009960, 2008. a
Bauer, A., Godon, M., Kheddar, M., and Hartmann, J.: Temperature and perturber
dependences of water vapor line-broadening. Experiments at 183 GHz;
calculations below 1000 GHz, J. Quant. Spectrosc.
Ra., 41, 49–54, https://doi.org/10.1016/0022-4073(89)90020-4, 1989. a
Bedka, S., Knuteson, R., Revercomb, H., Tobin, D., and Turner, D.: An
assessment of the absolute accuracy of the Atmospheric Infrared Sounder v5
precipitable water vapor product at tropical, midlatitude, and arctic
ground-truth sites: September 2002 through August 2008, J. Geophys. Res., 115, D17310, https://doi.org/10.1029/2009jd013139, 2010. a
Browell, E. V., Wilkerson, T. D., and Mcilrath, T. J.: Water vapor
differential absorption lidar development and evaluation, Appl. Optics, 18,
3474–3483, https://doi.org/10.1364/AO.18.003474, 1979. a
CloudSat DPC: CloudSat Data Processing Center, 2C-RAINPROFILE. 2B-CWCRO R05, ECMWF-aux, available at: http://www.cloudsat.cira.colostate.edu/order-data, last access: 1 March 2020. a
Cooper, K. B., Monje, R. R., Millán, L., Lebsock, M., Tanelli, S., Siles, J. V., Lee, C., and Brown, A.: Atmospheric Humidity Sounding Using
Differential Absorption Radar Near 183 GHz, IEEE Geosci. Remote
S., 15, 163–167, https://doi.org/10.1109/lgrs.2017.2776078, 2018. a
Cronk, H. and Partain, P.: CloudSat ECMWF-AUX Auxillary Data Product Process
Description and Interface Control Document, Product Version: P_R05,
available at: http://www.cloudsat.cira.colostate.edu/sites/default/files/products/files/ECMWF-AUX_PDICD.P_R05.rev0_.pdf (last access: 1 March 2020),
2017. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J.,
Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N.,
and Vitart, F.: The ERA-Interim reanalysis: configuration and performance
of the data assimilation system, Q. J. Roy.
Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Diedrich, H., Preusker, R., Lindstrot, R., and Fischer, J.: Retrieval of daytime total columnar water vapour from MODIS measurements over land surfaces, Atmos. Meas. Tech., 8, 823–836, https://doi.org/10.5194/amt-8-823-2015, 2015. a
Ellis, S. M. and Vivekanandan, J.: Water vapor estimates using simultaneous
dual-wavelength radar observations, Radio Sci., 45,
RS5002, https://doi.org/10.1029/2009rs004280, 2010. a
GCOS-ECV: Global Climate Observing System – Essential Climate Variable,
available at:
https://www.ncdc.noaa.gov/gosic/gcos-essential-climate-variable-ecv-data-access-matrix/gcos-atmosphere-upper-air-ecv-water-vapour,
last access: 11 March 2020. a
Goyette, T. M. and Lucia, F. C. D.: The pressure broadening of the 31, 3-22, 0
transition of water between 80 and 600 K, J. Mol. Spectrosc.,
143, 346–358, https://doi.org/10.1016/0022-2852(91)90099-v, 1990. a
Haynes, J. M., L'Ecuyer, T. S., Stephens, G. L., Miller, S. D., Mitrescu, C., Wood, N. B., and Tanelli, S.: Rainfall retrieval over
the ocean with spaceborne W-band radar, J. Geophys. Res., 114,
D00A22, https://doi.org/10.1029/2008jd009973, 2009. a
Hogan, R. J.: Multiscatter: a fast, approximate multiple scattering
algorithm, University of Reading, Reading, UK, 2013. a
Hogan, R. J. and Battaglia, A.: Fast Lidar and Radar Multiple-Scattering
Models. Part II: Wide-Angle Scattering Using the Time-Dependent Two-Stream
Approximation, J. Atmos. Sci., 65, 3636–3651,
https://doi.org/10.1175/2008jas2643.1, 2008. a, b
Hufford, G.: A model for the complex permittivity of ice at frequencies below 1 THz, Int. J. Infrared Milli., 12, 677–682,
https://doi.org/10.1007/bf01008898, 1991. a
Kawanishi, T., Sezai, T., Ito, Y., Imaoka, K., Takeshima, T., Ishido, Y.,
Shibata, A., Miura, M., Inahata, H., and Spencer, R.: The advanced microwave
scanning radiometer for the earth observing system (AMSR-E),
NASDA's contribution to the EOS for global energy and
water cycle studies, IEEE T. Geosci. Remote,
41, 184–194, https://doi.org/10.1109/tgrs.2002.808331, 2003. a
Lang, R., Casadio, S., Maurellis, A. N., and Lawrence, M. G.: Evaluation of the
GOME Water Vapor Climatology 1995–2002, J. Geophys.
Res., 112, D17110, https://doi.org/10.1029/2006jd008246, 2007. a
Lebsock, M. D. and L'Ecuyer, T. S.: The retrieval of warm rain from CloudSat,
J. Geophys. Res.-Atmos., 116, d20209,
https://doi.org/10.1029/2011JD016076, 2011. a
Lebsock, M. D., Suzuki, K., Millán, L. F., and Kalmus, P. M.: The feasibility of water vapor sounding of the cloudy boundary layer using a differential absorption radar technique, Atmos. Meas. Tech., 8, 3631–3645, https://doi.org/10.5194/amt-8-3631-2015, 2015. a, b, c
L'Ecuyer, T. S. and Stephens, G. L.: An Estimation-Based
Precipitation Retrieval Algorithm for Attenuating Radars, J. Appl.
Meteorol., 41, 272–285,
https://doi.org/10.1175/1520-0450(2002)041<0272:aebpra>2.0.co;2,
2002. a
Li, L., Heymsfield, G. M., Tian, L., and Racette, P. E.: Measurements of Ocean
Surface Backscattering Using an Airborne 94-GHz Cloud Radar Implication for
Calibration of Airborne and Spaceborne W-Band Radars, J. Atmos.
Ocean. Tech., 22, 1033–1045, https://doi.org/10.1175/jtech1722.1, 2005. a, b, c, d
Liebe, H. J., Hufford, G. A., and Manabe, T.: A model for the complex
permittivity of water at frequencies below 1 THz, Int. J. Infrared Milli., 12, 659–675, https://doi.org/10.1007/BF01008897, 1991. a
Lindstrot, R., Preusker, R., Diedrich, H., Doppler, L., Bennartz, R., and Fischer, J.: 1D-Var retrieval of daytime total columnar water vapour from MERIS measurements, Atmos. Meas. Tech., 5, 631–646, https://doi.org/10.5194/amt-5-631-2012, 2012. a
McFarquhar, G. M. and Heymsfield, A. J.: Parameterization of Tropical Cirrus
Ice Crystal Size Distributions and Implications for Radiative Transfer:
Results from CEPEX, J. Atmos. Sci., 54, 2187–2200,
https://doi.org/10.1175/1520-0469(1997)054<2187:POTCIC>2.0.CO;2, 1997. a
Meneghini, R., Liao, L., and Tian, L.: A Feasibility Study for Simultaneous
Estimates of Water Vapor and Precipitation Parameters Using a Three-Frequency
Radar, J. Appl. Meteorol., 44, 1511–1525,
https://doi.org/10.1175/jam2302.1, 2005. a
Meshkov, A. I. and De Lucia, F. C.: Broadband absolute absorption measurements
of atmospheric continua with millimeter wave cavity ringdown spectroscopy,
Rev. Sci. Instrum., 76, 083103, https://doi.org/10.1063/1.1988027, 2005. a, b
Millán, L., Lebsock, M., Livesey, N., Tanelli, S., and Stephens, G.: Differential absorption radar techniques: surface pressure, Atmos. Meas. Tech., 7, 3959–3970, https://doi.org/10.5194/amt-7-3959-2014, 2014. a
Millán, L., Lebsock, M., Livesey, N., and Tanelli, S.: Differential absorption radar techniques: water vapor retrievals, Atmos. Meas. Tech., 9, 2633–2646, https://doi.org/10.5194/amt-9-2633-2016, 2016. a, b, c, d
Nelson, R. R., Crisp, D., Ott, L. E., and O'Dell, C. W.: High-accuracy
measurements of total column water vapor from the Orbiting Carbon
Observatory-2, Geophys. Res. Lett., 43, 12261–12269,
https://doi.org/10.1002/2016GL071200, 2016. a
NTIA: National Telecommunications and Information Administration: Manual of
Regulations and Procedures for Federal Radio Frequency Management,
available at:
https://www.ntia.doc.gov/page/2011/ (last access: 3 March 2020),
2015. a
Pearson, J. C., Cooper, K., and Drouin, B. J.: Spectroscopic detection,
fundamental limits and system considerations, in: 2008 33rd International
Conference on Infrared, Millimeter and Terahertz Waves, IEEE,
https://doi.org/10.1109/icimw.2008.4665839, 2008. a
Peral, E., Tanelli, S., Statham, S., Joshi, S., Imken, T., Price, D., Sauder, J., Chahat, N., and Williams, A.: RainCube: the first ever radar
measurements from a CubeSat in space, J. Appl. Remote Sens.,
13, 1, https://doi.org/10.1117/1.jrs.13.032504, 2019. a
Pickett, H., Poynter, R., Cohen, E., Delitsky, M., Pearson, J., and Müller, H.: SUBMILLIMETER, MILLIMETER, AND MICROWAVE SPECTRAL LINE
CATALOG, J. Quant. Spectrosc. Ra., 60,
883–890, https://doi.org/10.1016/s0022-4073(98)00091-0, 1998. a
Pougatchev, N., August, T., Calbet, X., Hultberg, T., Oduleye, O., Schlüssel,
P., Stiller, B., Germain, K. St., and Bingham, G.: IASI temperature and water
vapor retrievals – error assessment and validation, Atmos. Chem. Phys., 9, 6453–6458, https://doi.org/10.5194/acp-9-6453-2009, 2009. a
Roy, R. J., Lebsock, M., Millán, L., and Cooper, K. B.: Validation of a G-Band Differential Absorption Cloud Radar for Humidity Remote Sensing. J. Atmos. Ocean. Technol., 37, 1085–1102, https://doi.org/10.1175/JTECH-D-19-0122.1, 2020. a, b, c
Roy, R. J., Lebsock, M., Millán, L., Dengler, R., Rodriguez Monje, R., Siles, J. V., and Cooper, K. B.: Boundary-layer water vapor profiling using differential absorption radar, Atmos. Meas. Tech., 11, 6511–6523, https://doi.org/10.5194/amt-11-6511-2018, 2018. a, b
Sassen, K. and Wang, Z.: Classifying clouds around the globe with the
CloudSat radar: 1-year of results, Geophys. Res. Lett., 35,
L04805, https://doi.org/10.1029/2007gl032591, 2008. a
Schluessel, P. and Emery, W. J.: Atmospheric water vapour over oceans from
SSM/I measurements, Int. J. Remote Sens., 11, 753–766,
https://doi.org/10.1080/01431169008955055, 1990. a
Schotland, R. M.: Some observations of the vertical profile of water vapor by
means of a ground based optical radar, Proceedings of the Fourth Symposium
on Remote Sensing of the Environment, Environmental Research Institute of
Michigan, Ann Arbor, MI, USA, 273–283, 1966. a
Sekhon, R. S. and Sirvastava, R. C.: Snow size spectra and radar
reflectivity,, J. Atmos. Sci., 37, 299–370,
https://doi.org/10.1175/1520-0469(1970)027<0299:SSSARR>2.0.CO;2, 1970. a
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z.,
Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., Mitrescu, C., and Team, T. C. S.: THE CLOUDSAT MISSION AND THE A-TRAIN: A New Dimension
of Space-Based Observations of Clouds and Precipitation, B.
Am. Meteorol. Soc., 83, 1771–1790,
https://doi.org/10.1175/bams-83-12-1771, 2002. a, b
Tian, L., Heymsfield, G. M., Li, L., and Srivastava, R. C.: Properties of
light stratiform rain derived from 10- and 94-GHz airborne Doppler radars
measurements, J. Geophys. Res., 112, D11211,
https://doi.org/10.1029/2006jd008144, 2007. a
Townes, C. H. and Geschwind, S.: Limiting Sensitivity of a Microwave
Spectrometer, J. Appl. Phys., 19, 795–796,
https://doi.org/10.1063/1.1698206, 1948. a
Walsh, E. J.: Pulse-to-pulse correlation in satellite radar altimeters, Radio
Sci., 17, 786–800, https://doi.org/10.1029/rs017i004p00786, 1982. a
Wang, H., Liu, X., Chance, K., González Abad, G., and Chan Miller, C.: Water vapor retrieval from OMI visible spectra, Atmos. Meas. Tech., 7, 1901–1913, https://doi.org/10.5194/amt-7-1901-2014, 2014. a
Wentz, F. J.: A well-calibrated ocean algorithm for special sensor microwave/imager, J. Geophys. Res.-Oceans, 102, 8703–8718,
https://doi.org/10.1029/96jc01751, 1997.
a
Wentz, F. J. and Meissner, T.: AMSR ocean algorithm, version 2, Remote
Sensing Systems Tech. Rep. 121599A-1, 66 pp.,
available at: http://eospso.gsfc.nasa.gov/sites/default/files/atbd/atbd-amsr-ocean.pdf
(last access: 1 March 2020),
2000. a
Wulfmeyer, V. and Walther, C.: Future performance of ground-based and airborne
water-vapor differential absorption lidar. II. Simulations of the precision
of a near-infrared, high-power system, Appl. Opt., 40, 5321–5336,
https://doi.org/10.1364/AO.40.005321, 2001. a
Short summary
This paper describes the feasibility of using a differential absorption radar technique for the remote sensing of total column water vapor from a spaceborne platform.
This paper describes the feasibility of using a differential absorption radar technique for the...
