Literature DB >> 32020986

The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP).

Gregory S Elsaesser1, Christopher W O'Dell2, Matthew D Lebsock3, Ralf Bennartz4, Thomas J Greenwald5, Frank J Wentz6.   

Abstract

The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988 - 2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) inter-calibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2 and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and monthly-mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, a correction for a CLWP bias (based on matchups to clear-sky MODIS scenes), and the construction of a total (cloud+rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e. CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from -15% (e.g. global oceanic stratocumulus decks) to +5-10% (e.g. portions of the higher-latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Science Data and Information Services Center (http://disc.sci.gsfc.nasa.gov).

Entities:  

Year:  2017        PMID: 32020986      PMCID: PMC6999728          DOI: 10.1175/jcli-d-16-0902.1

Source DB:  PubMed          Journal:  J Clim        ISSN: 0894-8755            Impact factor:   5.148


  2 in total

1.  Evidence for climate change in the satellite cloud record.

Authors:  Joel R Norris; Robert J Allen; Amato T Evan; Mark D Zelinka; Christopher W O'Dell; Stephen A Klein
Journal:  Nature       Date:  2016-07-11       Impact factor: 49.962

2.  View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds.

Authors:  Ákos Horváth; Chellappan Seethala; Hartwig Deneke
Journal:  J Geophys Res Atmos       Date:  2014-07-12       Impact factor: 4.261

  2 in total
  4 in total

Review 1.  Earth's water reservoirs in a changing climate.

Authors:  Graeme L Stephens; Julia M Slingo; Eric Rignot; John T Reager; Maria Z Hakuba; Paul J Durack; John Worden; Remy Rocca
Journal:  Proc Math Phys Eng Sci       Date:  2020-04-01       Impact factor: 2.704

2.  Evaluation of Cloud Liquid Water Path Trends Using a Multi-Decadal Record of Passive Microwave Observations.

Authors:  Andrew Manaster; Christopher W O'Dell; Gregory Elsaesser
Journal:  J Clim       Date:  2017-07-03       Impact factor: 5.148

3.  Opportunistic experiments to constrain aerosol effective radiative forcing.

Authors:  Matthew W Christensen; Andrew Gettelman; Jan Cermak; Guy Dagan; Michael Diamond; Alyson Douglas; Graham Feingold; Franziska Glassmeier; Tom Goren; Daniel P Grosvenor; Edward Gryspeerdt; Ralph Kahn; Zhanqing Li; Po-Lun Ma; Florent Malavelle; Isabel L McCoy; Daniel T McCoy; Greg McFarquhar; Johannes Mülmenstädt; Sandip Pal; Anna Possner; Adam Povey; Johannes Quaas; Daniel Rosenfeld; Anja Schmidt; Roland Schrödner; Armin Sorooshian; Philip Stier; Velle Toll; Duncan Watson-Parris; Robert Wood; Mingxi Yang; Tianle Yuan
Journal:  Atmos Chem Phys       Date:  2022-01-17       Impact factor: 6.133

4.  The Global Atmosphere-aerosol Model ICON-A-HAM2.3-Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness.

Authors:  M Salzmann; S Ferrachat; C Tully; S Münch; D Watson-Parris; D Neubauer; C Siegenthaler-Le Drian; S Rast; B Heinold; T Crueger; R Brokopf; J Mülmenstädt; J Quaas; H Wan; K Zhang; U Lohmann; P Stier; I Tegen
Journal:  J Adv Model Earth Syst       Date:  2022-04-02       Impact factor: 8.469

  4 in total

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