Articles | Volume 15, issue 3
https://doi.org/10.5194/amt-15-605-2022
© Author(s) 2022. 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-15-605-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Feb 2022
Research article |
| 04 Feb 2022
| 04 Feb 2022
Differential absorption lidar measurements of water vapor by the High Altitude Lidar Observatory (HALO): retrieval framework and first results
Brian J. Carroll
CORRESPONDING AUTHOR
NASA Postdoctoral Program, NASA Langley Research Center,
Hampton, VA, United States
NASA Langley Research Center, Hampton, VA, United States
Susan A. Kooi
Science Systems and Applications, Inc., Hampton, VA, United States
James E. Collins
Science Systems and Applications, Inc., Hampton, VA, United States
Rory A. Barton-Grimley
NASA Langley Research Center, Hampton, VA, United States
Anthony Notari
NASA Langley Research Center, Hampton, VA, United States
David B. Harper
NASA Langley Research Center, Hampton, VA, United States
Joseph Lee
NASA Langley Research Center, Hampton, VA, United States
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Cited articles
Abshire, J. B., Riris, H., Weaver, C. J., Mao, J., Allan, G. R.,
Hasselbrack, W. E., and Browell, E. V.: Airborne measurements of CO2
column absorption and range using a pulsed direct-detection integrated path
differential absorption lidar, Appl. Optics, 52, 4446–4461, 2013.
Amediek, A., Ehret, G., Fix, A., Wirth, M., Büdenbender, C.,
Quatrevalet, M., Kiemle, C., and Gerbig, C.: CHARM-F–a new airborne
integrated-path differential-absorption lidar for carbon dioxide and methane
observations: measurement performance and quantification of strong point
source emissions, Appl. Optics, 56, 5182–5197, 2017.
Ansmann, A.: Errors in ground-based water-vapor DIAL measurements due to
Doppler-broadened Rayleigh backscattering, Appl. Optics, 24, 3476–3480, 1985.
Ansmann, A. and Bosenberg, J.: Correction scheme for spectral broadening by
Rayleigh scattering in differential absorption lidar measurements of water
vapor in the troposphere, Appl. Optics, 26, 3026–3032, 1987.
Bedka, K. M., Nehrir, A. R., Kavaya, M., Barton-Grimley, R., Beaubien, M., Carroll, B., Collins, J., Cooney, J., Emmitt, G. D., Greco, S., Kooi, S., Lee, T., Liu, Z., Rodier, S., and Skofronick-Jackson, G.: Airborne lidar observations of wind, water vapor, and aerosol profiles during the NASA Aeolus calibration and validation (Cal/Val) test flight campaign, Atmos. Meas. Tech., 14, 4305–4334, https://doi.org/10.5194/amt-14-4305-2021, 2021.
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.
Behrendt, A., Wulfmeyer, V., Schaberl, T., Bauer, H. S., Kiemle, C., Ehret,
G., Flamant, C., Kooi, S., Ismail, S., Ferrare, R., and Browell, E. V.:
Intercomparison of water vapor data measured with lidar during
IHOP_2002. Part II: Airborne-to-airborne systems, J. Atmos. Ocean. Tech., 24, 22–39, 2007.
Birk, M., Wagner, G., Loos, J., Lodi, L., Polyansky, O. L., Kyuberis, A. A., Zobov, N. F., and Tennyson, J.: Accurate line intensities for water transitions in the infrared: comparison of theory and experiment, J. Quant. Spectrosc. Ra., 203, 88–102, 2017.
Black, P., Harrison, L., Beaubien, M., Bluth, R., Woods, R., Penny, A.,
Smith, R. W., and Doyle, J. D.: High-definition Sounding System (HDSS) for
atmospheric profiling, J. Atmos. Ocean. Tech., 34, 777–796, 2017.
Bony, S., Colman, R., Kattsov, V. M., Allan, R. P., Bretherton, C. S.,
Dufresne, J. L., Hall, A., Hallegatte, S., Holland, M. M., Ingram, W., and
Randall, D. A.: How well do we understand and evaluate climate change
feedback processes?, J. Climate, 19, 3445–3482, 2006.
Bony, S., Stevens, B., Frierson, D. M., Jakob, C., Kageyama, M., Pincus, R.,
Shepherd, T. G., Sherwood, S. C., Siebesma, A. P., Sobel, A. H. and Watanabe,
M.: Clouds, circulation and climate sensitivity, Nat. Geosci., 8, 261–268, 2015.
Bösenberg, J.: Ground-based differential absorption lidar for
water-vapor and temperature profiling: methodology, Appl. Optics, 37, 3845–3860, 1998.
Browell, E. V.: Remote sensing of tropospheric gases and aerosols with an
airborne DIAL system, in: Optical and Laser Remote Sensing, edited by: Killinger, D. K. and Mooradian A., Springer, Berlin, Heidelberg, Germany, 138–147, https://doi.org/10.1007/978-3-540-39552-2_18, 1983.
Browell, E. V., Ismail, S., and Grant, W. B.: Differential absorption lidar
(DIAL) measurements from air and space, Appl. Phys. B, 67, 399–410, 1998.
Burton, S. P., Ferrare, R. A., Hostetler, C. A., Hair, J. W., Rogers, R. R., Obland, M. D., Butler, C. F., Cook, A. L., Harper, D. B., and Froyd, K. D.: Aerosol classification using airborne High Spectral Resolution Lidar measurements – methodology and examples, Atmos. Meas. Tech., 5, 73–98, https://doi.org/10.5194/amt-5-73-2012, 2012.
Carroll, B. J., Demoz, B. B., Turner, D. D., and Delgado, R.: Lidar observations of a mesoscale moisture transport event impacting convection and comparison to Rapid Refresh model analysis, Mon. Weather Rev., 149, 463–477,
2021.
Chahine, M. T., Pagano, T. S., Aumann, H. H., Atlas, R., Barnet, C., Blaisdell, J., Chen, L., Fetzer, E. J., Goldberg, M., Gautier, C., and Granger, S.: AIRS: Improving weather forecasting and providing new data on greenhouse gases, B. Am. Meteorol. Soc., 87, 911–926, 2006.
Chazette, P., Marnas, F., Totems, J., and Shang, X.: Comparison of IASI water vapor retrieval with H2O-Raman lidar in the framework of the Mediterranean HyMeX and ChArMEx programs, Atmos. Chem. Phys., 14, 9583–9596, https://doi.org/10.5194/acp-14-9583-2014, 2014.
Clerbaux, C., Boynard, A., Clarisse, L., George, M., Hadji-Lazaro, J., Herbin, H., Hurtmans, D., Pommier, M., Razavi, A., Turquety, S., Wespes, C., and Coheur, P.-F.: Monitoring of atmospheric composition using the thermal infrared IASI/MetOp sounder, Atmos. Chem. Phys., 9, 6041–6054, https://doi.org/10.5194/acp-9-6041-2009, 2009.
Cooney, J.: Remote measurements of atmospheric water vapor profiles using
the Raman component of laser backscatter, J. Appl. Meteorol., 9, 182–184, 1970.
Davis, K. J., Browell, E. V., Feng, S., Lauvaux, T., Obland, M. D., Pal, S.,
Baier, B. C., Baker, D. F., Baker, I. T., Barkley, Z. R., and Bowman, K. W.: The Atmospheric Carbon and Transport (ACT)-America Mission, B. Am. Meteorol. Soc., 102, E1714–E1734, 2021.
Diao, M., Jumbam, L., Sheffield, J., Wood, E. F., and Zondlo, M. A.: Validation of AIRS/AMSU-A water vapor and temperature data with in situ aircraft observations from the surface to UT/LS from 87∘N–67∘S, J. Geophys. Res.-Atmos., 118, 6816–6836, 2013.
Diskin, G. S., Podolske, J. R., Sachse, G. W., and Slate, T. A.: Open-path
airborne tunable diode laser hygrometer, Diode Lasers and Applications in
Atmospheric Sensing, Proc. SPIE, 4817, 9 pp., https://doi.org/10.1117/12.453736, 2002.
Dobler, J. T., Harrison, F. W., Browell, E. V., Lin, B., McGregor, D., Kooi,
S., Choi, Y., and Ismail, S.: Atmospheric CO2 column measurements with an
airborne intensity-modulated continuous wave 1.57 µm fiber laser
lidar, Appl. Optics, 52, 2874–2892, 2013.
Doyle, J. D., Moskaitis, J. R., Feldmeier, J. W., Ferek, R. J., Beaubien,
M., Bell, M. M., Cecil, D. L., Creasey, R. L., Duran, P., Elsberry, R. L.,
Komaromi, W. A., Molinari, J., Ryglicki, D. R., Stern, D. P., Velden, C. S.,
Wang, X., Allen, T., Barrett, B. S., Black, P. G., Dunion, J. P., Emanuel,
K. A., Harr, P. A., Harrison, L., Hendricks, E. A., Herndon, D., Jeffries,
W. Q., Majumdar, S. J., Moore, J. A., Pu, Z., Rogers, R. F., Sanabia, E. R.,
Tripoli, G. J., and Zhang, D.: A View of Tropical Cyclones from Above: The
Tropical Cyclone Intensity Experiment, B. Am. Meteorol. Soc., 98,
2113–2134, https://doi.org/10.1175/BAMSD-16-0055.1, 2017.
Ehret, G., Kiemle, C., Renger, W., and Simmet, G.: Airborne remote sensing of
tropospheric water vapor with a near–infrared differential absorption lidar
system, Appl. Optics, 32, 4534–4551, 1993.
Eichinger, W. E., Cooper, D. I., Forman, P. R., Griegos, J., Osborn, M. A.,
Richter, D., Tellier, L. L., and Thornton, R.: The development of a scanning
Raman water vapor lidar for boundary layer and tropospheric observations, J. Atmos. Ocean. Tech., 16, 1753–1766, 1999.
Fan, L., Zhang, Y., Chen, S., Guo, P., and Chen, H.: Rayleigh-backscattering doppler broadening correction for differential absorption lidar, in: Selected Papers of the Photoelectronic Technology Committee Conferences, June–July 2015, International Society for Optics and Photonics, Proc. SPIE, 9795, p. 979517, 2015.
Ferrare, R. A., Browell, E. V., Ismail, S., Kooi, S. A., Brasseur, L. H.,
Brackett, V. G., Clayton, M. B., Barrick, J. D. W., Diskin, G. S., Goldsmith,
J. E. M., and Lesht, B. M.: Characterization of upper-troposphere water vapor
measurements during AFWEX using LASE, J. Atmos. Ocean. Tech., 21, 1790–1808, 2004.
Ferreira, A. P., Nieto, R., and Gimeno, L.: Completeness of radiosonde humidity observations based on the Integrated Global Radiosonde Archive, Earth Syst. Sci. Data, 11, 603–627, https://doi.org/10.5194/essd-11-603-2019, 2019.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., and Wargan,
K.: The modern-era retrospective analysis for research and applications,
version 2 (MERRA-2), J. Climate, 30, 5419–5454, 2017.
Gettelman, A., Weinstock, E. M., Fetzer, E. J., Irion, F. W., Eldering, A.,
Richard, E. C., Rosenlof, K. H., Thompson, T. L., Pittman, J. V., Webster, C. R., and Herman, R. L.: Validation of Aqua satellite data in the upper troposphere and lower stratosphere with in situ aircraft instruments, Geophys. Res. Lett., 31, L22107, https://doi.org/10.1029/2004GL020730, 2004.
Goldsmith, J. E. M., Blair, F. H., Bisson, S. E., and Turner, D. D.: Turn-key
Raman lidar for profiling atmospheric water vapor, clouds, and aerosols, Appl. Optics, 37, 4979–4990, 1998.
Gordon, I. E., Rothman, L. S., Hill, C., Kochanov, R. V., Tan, Y., Bernath,
P. F., Birk, M., Boudon, V., Campargue, A., Chance, K. V., and Drouin, B. J.:
The HITRAN2016 molecular spectroscopic database, J. Quant. Spectrosc. Ra., 203, 3–69, 2017.
Hair, J. W., Hostetler, C. A., Cook, A. L., Harper, D. B., Ferrare, R. A., Mack, T. L., Welch, W., Izquierdo, L. R., and Hovis, F. E.: Airborne high spectral resolution lidar for profiling aerosol optical properties, Appl. Optics, 47, 6734–6752, 2008.
Hastings, D. A., Dunbar, P. K., Elphingstone, G. M., Bootz, M., Murakami, H.,
Maruyama, H., Masaharu, H., Holland, P., Payne, J., Bryant, N. A., and Logan,
T. L.: The global land one-kilometer base elevation (GLOBE) digital elevation
model, version 1.0, National Oceanic and Atmospheric Administration,
National Geophysical Data Center, https://www.ngdc.noaa.gov/mgg/topo/globe.html (last access: 1 August 2007), 1999.
Higdon, N. S., Browell, E. V., Ponsardin, P., Grossmann, B. E., Butler, C. F., Chyba, T. H., Mayo, M. N., Allen, R. J., Heuser, A. W., Grant, W. B., and Ismail, S.: Airborne differential absorption lidar system for measurements of
atmospheric water vapor and aerosols, Appl. Optics, 33, 6422–6438, 1994.
Hilton, F., Atkinson, N. C., English, S. J., and Eyre, J. R.: Assimilation of
IASI at the Met Office and assessment of its impact through observing system
experiments, Q. J. Roy. Meteor. Soc., 135, 495–505, 2009.
Hilton, F., Armante, R., August, T., Barnet, C., Bouchard, A., Camy-Peyret,
C., Capelle, V., Clarisse, L., Clerbaux, C., Coheur, P. F., and Collard, A.:
Hyperspectral Earth observation from IASI: Five years of accomplishments, B. Am. Meteorol. Soc., 93, 347–370, 2012.
Hodges, J. T., Lisak, D., Lavrentieva, N., Bykov, A., Sinitsa, L., Tennyson,
J., Barber, R. J., and Tolchenov, R. N.: Comparison between theoretical calculations and high-resolution measurements of pressure broadening for near-infrared water spectra, J. Mol. Spectrosc., 249, 86–94, 2008.
Ismail, S. and Browell, E. V.: Airborne and spaceborne lidar measurements of
water vapor profiles: a sensitivity analysis, Appl. Optics, 28, 3603–3615, 1989.
Ismail, S., Ferrare, R. A., Browell, E. V., Chen, G., Anderson, B., Kooi,
S. A., Notari, A., Butler, C. F., Burton, S., Fenn, M., and Dunion, J. P.: LASE measurements of water vapor, aerosol, and cloud distributions in Saharan air layers and tropical disturbances, J. Atmos. Sci., 67, 1026–1047, 2010.
Kavaya, M. J., Beyon, J. Y., Koch, G. J., Petros, M., Petzar, P. J., Singh,
U. N., Trieu, B. C., and Yu, J.: The Doppler Aerosol Wind (DAWN) Airborne,
Wind-Profiling Coherent-Detection Lidar System: Overview and Preliminary
Flight Results, J. Atmos. Ocean. Tech., 31, 826–842,
https://doi.org/10.1175/JTECH-D-12-00274.1, 2014.
Kiemle, C., Groß, S., Wirth, M., and Bugliaro, L.: Airborne lidar
observations of water vapor variability in tropical shallow convective
environment, in: Shallow Clouds, Water Vapor, Circulation, and Climate
Sensitivity, Springer International Publishing, 253–271, 2017.
Klaes, K. D., Cohen, M., Buhler, Y., Schlüssel, P., Munro, R., Luntama,
J. P., von Engeln, A., Clérigh, E. Ó., Bonekamp, H., Ackermann, J., and Schmetz, J.: An introduction to the EUMETSAT polar system, B. Am. Meteorol. Soc., 88, 1085–1096, https://doi.org/10.1175/BAMS-88-7-1085, 2007.
Leblanc, T., McDermid, I. S., and Walsh, T. D.: Ground-based water vapor raman lidar measurements up to the upper troposphere and lower stratosphere for long-term monitoring, Atmos. Meas. Tech., 5, 17–36, https://doi.org/10.5194/amt-5-17-2012, 2012.
Le Marshall, J., Jung, J., Derber, J., Chahine, M., Treadon, R., Lord, S. J.,
Goldberg, M., Wolf, W., Liu, H. C., Joiner, J., and Woollen, J.: Improving
global analysis and forecasting with AIRS, B. Am. Meteorol. Soc., 87, 891–894, 2006.
Liu, Z., Hunt, W., Vaughan, M., Hostetler, C., McGill, M., Powell, K.,
Winker, D., and Hu, Y.: Estimating random errors due to shot noise in
backscatter lidar observations, Appl. Optics, 45, 4437–4447, 2006.
Martins, J. P., Teixeira, J., Soares, P. M., Miranda, P. M., Kahn, B. H., Dang, V. T., Irion, F. W., Fetzer, E. J., and Fishbein, E.: Infrared sounding of the trade-wind boundary layer: AIRS and the RICO experiment, Geophys. Res. Lett., 37, L24806, https://doi.org/10.1029/2010GL045902, 2010.
Moore, A. S., Brown, K. E., Hall, W. M., Barnes, J. C., Edwards, W. C., Petway, L. B., Little, A. D., Luck, W. S., Jones, I. W., Antill, C.W., and Browell, E. V.: Development of the Lidar Atmospheric Sensing Experiment (LASE) – an advanced airborne DIAL instrument, in: Advances in Atmospheric Remote Sensing with Lidar, Springer, Berlin, Germany, 281–288, 1997.
NASA/LARC/SD/ASDC: Aeolus CalVal HALO Aerosol and Water Vapor Profiles and
Images, NASA Langley Atmospheric Science Data Center DAAC [data set],
https://doi.org//10.5067/SUBORBITAL/AEOLUSCALVAL2019/DATA001, 2020.
Nehrir, A. R., Repasky, K. S., Carlsten, J. L., Obland, M. D., and Shaw, J.
A.: Water Vapor Profiling Using a Widely Tunable, Amplified
Diode-Laser-Based Differential Absorption Lidar (DIAL), J. Atmos. Ocean. Tech., 26, 733–745, 2009.
Nehrir, A. R., Repasky, K. S., and Carlsten, J. L.: Eye-safe
diode-laser-based micropulse differential absorption lidar (DIAL) for water
vapor profiling in the lower troposphere, J. Atmos. Ocean. Tech., 28, 131–147, 2011.
Nehrir, A. R., Repasky, K. S., and Carlsten, J. L.: Micropulse water vapor
differential absorption lidar: transmitter design and performance, Opt.
Express, 20, 25137–25151, 2012.
Nehrir, A. R., Kiemle, C., Lebsock, M. D., Kirchengast, G., Buehler, S. A.,
Löhnert, U., Liu, C. L., Hargrave, P. C., Barrera-Verdejo, M., and Winker, D. M.: Emerging technologies and synergies for airborne and space-based measurements of water vapor profiles, Surv. Geophys., 38, 1445–1482, 2017.
Philbrick, C. R.: Raman lidar measurements of atmospheric properties, in:
Atmospheric Propagation and Remote Sensing III, edited by: Flood, W. A. and Miller, W. B., SPIE, 2222, 922–931, 1994.
Podolske, J. R., Sachse, G. W., and Diskin, G. S.: Calibration and data
retrieval algorithms for the NASA Langley/Ames Diode Laser Hygrometer for
the NASA transport and chemical evolution over the pacific (TRACE-P)
mission, J. Geophys. Res., 108, 8792, https://doi.org/10.1029/2002JD003156, 2003.
Remsberg, E. E. and Gordley, L. L.: Analysis of differential absorption lidar
from the Space Shuttle, Appl. Optics, 17, 624–630, 1978.
Richardson, M. T., Thompson, D. R., Kurowski, M. J., and Lebsock, M. D.: Boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy, Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021, 2021.
Roman, J., Knuteson, R., August, T., Hultberg, T., Ackerman, S., and
Revercomb, H.: A global assessment of NASA AIRS v6 and EUMETSAT IASI v6
precipitable water vapor using ground-based GPS SuomiNet stations, J. Geophys. Res.-Atmos., 121, 8925–8948, 2016.
Schäfler, A., Fix, A., and Wirth, M.: Mixing at the extratropical tropopause as characterized by collocated airborne H2O and O3 lidar observations, Atmos. Chem. Phys., 21, 5217–5234, https://doi.org/10.5194/acp-21-5217-2021, 2021.
Schotland, R. M.: Errors in the lidar measurement of atmospheric gases by
differential absorption, J. Appl. Meteorol., 13, 71–77, 1974.
Sherwood, S. C., Roca, R., Weckwerth, T. M., and Andronova, N. G.: Tropospheric water vapor, convection, and climate, Rev. Geophys., 48, RG2001, https://doi.org/10.1029/2009RG000301, 2010.
Späth, F., Behrendt, A., Muppa, S. K., Metzendorf, S., Riede, A., and Wulfmeyer, V.: 3-D water vapor field in the atmospheric boundary layer observed with scanning differential absorption lidar, Atmos. Meas. Tech., 9, 1701–1720, https://doi.org/10.5194/amt-9-1701-2016, 2016.
Späth, F., Behrendt, A., and Wulfmeyer, V.: Minimization of the
Rayleigh-Doppler error of differential absorption lidar by frequency tuning:
a simulation study, Opt. Express, 28, 30324–30339, 2020.
Spuler, S. M., Repasky, K. S., Morley, B., Moen, D., Hayman, M., and Nehrir, A. R.: Field-deployable diode-laser-based differential absorption lidar (DIAL) for profiling water vapor, Atmos. Meas. Tech., 8, 1073–1087, https://doi.org/10.5194/amt-8-1073-2015, 2015.
Spuler, S. M., Hayman, M., Stillwell, R. A., Carnes, J., Bernatsky, T., and Repasky, K. S.: MicroPulse DIAL (MPD) – a diode-laser-based lidar architecture for quantitative atmospheric profiling, Atmos. Meas. Tech., 14, 4593–4616, https://doi.org/10.5194/amt-14-4593-2021, 2021.
Stoffelen, A., Pailleux, J., Källén, E., Vaughan, J. M., Isaksen, L.,
Flamant, P., Wergen, W., Andersson, E., Schyberg, H., Culoma, A., and
Meynart, R.: The atmospheric dynamics mission for global wind field
measurement, B. Am. Meteorol. Soc., 86, 73–88, 2005.
Teixeira, J., Piepmeier, J. R., Nehrir, A. R., Ao, C. O., Chen, S. S.,
Clayson, C. A., Fridlind, A. M., Lebsock, M., McCarty, W., Salmun, H.,
Santanello, J. A., Turner, D. D., Wang, Z., and Zeng, X.: Toward a Global
Planetary Boundary Layer Observing System, The NASA PBL Incubation Study
Team Report, 134 pp., 2021.
Thrastarson, H. T., Manning, E., Kahn, B., Fetzer, E., Yue, Q., Wong, S.,
Kalmus, P., Payne, V., Wang, T., Olsen, E. T., Wilson, R. C., Blaisdell, J., Iredell, L., Susskind, J., Warner, J., and Cady-Pereira, K.: AIRS/AMSU/HSB Version 7 Level 2 Product User Guide, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA, 2020.
Thompson, D. R., Kahn, B. H., Brodrick, P. G., Lebsock, M. D., Richardson, M., and Green, R. O.: Spectroscopic imaging of sub-kilometer spatial structure in lower-tropospheric water vapor, Atmos. Meas. Tech., 14, 2827–2840, https://doi.org/10.5194/amt-14-2827-2021, 2021.
Trenberth, K. E., Jones, P. D., Ambenje, P., Bojariu, R., Easterling, D.,
Klein Tank, A., Parker, D., Rahimzadeh, F., Renwick, J. A., Rusticucci, M.,
Soden, B., and Zhai, P.: Observations: Surface and atmospheric climate change, chap. 3, in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 236–336, 2007.
Turner, D. D. and Löhnert, U.: Ground-based temperature and humidity profiling: combining active and passive remote sensors, Atmos. Meas. Tech., 14, 3033–3048, https://doi.org/10.5194/amt-14-3033-2021, 2021.
Wakimoto, R. M., Murphey, H. V., Browell, E. V., and Ismail, S.: The “triple
point” on 24 May 2002 during IHOP. Part I: Airborne Doppler and LASE
analyses of the frontal boundaries and convection initiation, Mon. Weather Rev., 134, 231–250, 2006.
Whiteman, D. N., Melfi, S. H., and Ferrare, R. A.: Raman lidar system for the
measurement of water vapor and aerosols in the Earth's atmosphere, Appl. Optics, 31, 3068–3082, 1992.
Wirth, M., Fix, A., Mahnke, P., Schwarzer, H., Schrandt, F., and Ehret, G.:
The airborne multi-wavelength water vapor differential absorption lidar
WALES: system design and performance, Appl. Phys. B, 96, 201–213, 2009.
Wong, S., Fetzer, E. J., Schreier, M., Manipon, G., Fishbein, E. F., Kahn,
B. H., Yue, Q., and Irion, F. W.: Cloud-induced uncertainties in AIRS and ECMWF temperature and specific humidity, J. Geophys. Res.-Atmos., 120, 1880–1901, 2015.
Wu, Y., Nehrir, A. R., Ren, X., Dickerson, R. R., Huang, J., Stratton, P. R.,
Gronoff, G., Kooi, S. A., Collins, J. E., Berkoff, T. A., and Lei, L.:
Synergistic aircraft and ground observations of transported wildfire smoke
and its impact on air quality in New York City during the summer 2018 LISTOS
campaign, Sci. Total Environ., 773, 145030, https://doi.org/10.1016/j.scitotenv.2021.145030, 2021.
Wulfmeyer, V.: Ground-based differential absorption lidar for water-vapor
and temperature profiling: development and specifications of a
high-performance laser transmitter, Appl. Optics, 37, 3804–3824, 1998.
Wulfmeyer, V. and Bösenberg, J.: Ground-based differential absorption
lidar for water-vapor profiling: assessment of accuracy, resolution, and
meteorological applications, Appl. Optics, 37, 3825–3844, 1998.
Wulfmeyer, V., Bauer, H. S., Grzeschik, M., Behrendt, A., Vandenberghe, F.,
Browell, E. V., Ismail, S., and Ferrare, R. A.: Four-dimensional variational
assimilation of water vapor differential absorption lidar data: The first
case study within IHOP_2002, Mon. Weather Rev., 134, 209–230, 2006.
Wulfmeyer, V., Hardesty, R. M., Turner, D. D., Behrendt, A., Cadeddu, M. P., Di Girolamo, P., Schlüssel, P., Van Baelen, J., and Zus, F.: A review of the remote sensing of lower tropospheric thermodynamic profiles and its
indispensable role for the understanding and the simulation of water and
energy cycles, Rev. Geophys., 53, 819–895, 2015.
Short summary
HALO is a recently developed lidar system that demonstrates new technologies and advanced algorithms for profiling water vapor as well as aerosol and cloud properties. The high-resolution, high-accuracy measurements have unique advantages within the suite of atmospheric instrumentation, such as directly trading water vapor measurement resolution for precision. This paper provides the methodology and first water vapor results, showing agreement with in situ and spaceborne sounder measurements.
HALO is a recently developed lidar system that demonstrates new technologies and advanced...
