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Global Datasets of Clouds and Precipitation

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Satellite Measurements of Clouds and Precipitation

Part of the book series: Springer Remote Sensing/Photogrammetry ((SPRINGERREMO))

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Abstract

Satellite measurements play crucial roles in the construction of global observation datasets of clouds and precipitation. Many of such datasets are open to public, but there are so many choices it is hard to decide which one best suits your needs. This chapter is meant to be a concise guidance for those in need of a little assistance. It is not attempted in this chapter to present a complete list of satellite-based cloud/precipitation products, since otherwise the reader would be inundated with excessive information. Instead, we will put focus on a limited number of datasets that are widely used in the science and commercial/industrial sectors. Following an introduction to the data processing levels, selected data products are summarized without going too much into technical details.

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Notes

  1. 1.

    Similar terms such as cloudiness, cloud cover, and cloud fraction are used interchangeably with cloud amount in most (although not all) cases.

  2. 2.

    The TMPA (TRMM 3B42) product (Huffman et al. 2007) now has been replaced by IMERG.

References

  • Andersson A, Fennig K, Klepp C, Bakan S, Graßl H, Schulz J (2010) The hamburg ocean atmosphere parameters and fluxes from satellite data - HOAPS-3. Earth Sys Sci Data 2:215–234. https://doi.org/10.5194/essd-2-215-2010

    Article  Google Scholar 

  • Arkin PA, Meisner BN (1987) The relationship between large-scale convective rainfall and cold cloud over the western hemisphere during 1982–84. Mon Wea Rev 115:51–74. https://doi.org/10.1175/1520-0493(1987)115<0051:TRBLSC>2.0.CO;2

  • Ashouri H, Hsu KL, Sorooshian S, Braithwaite DK, Knapp KR, Cecil LD, Nelson BR, Prat OP (2015) PERSIANN-CDR: daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bull Amer Meteor Soc 96:69–83. https://doi.org/10.1175/BAMS-D-13-00068.1

    Article  Google Scholar 

  • Beck HE, Wood EF, Pan M, Fisher CK, Miralles DG, van Dijk AIJM, McVicar TR, Adler RF (2019) MSWEP v2 global 3-hourly 0.1\(^\circ \) precipitation: methodology and quantitative assessment. Bull Amer Meteor Soc 100:473–500. https://doi.org/10.1175/BAMS-D-17-0138.1

    Article  Google Scholar 

  • Becker A, Finger P, Meyer-Christoffer A, Rudolf B, Schamm K, Schneider U, Ziese M (2013) A description of the global land-surface precipitation data products of the global precipitation climatology centre with sample applications including centennial (trend) analysis from 1901-present. Earth Sys Sci Data 5:71–99. https://doi.org/10.5194/essd-5-71-2013

    Article  Google Scholar 

  • Elsaesser GS, O’Dell CW, Lebsock MD, Bennartz R, Greenwald TJ, Wentz FJ (2017) The multisensor advanced climatology of liquid water path (MAC-LWP). J Climate 30:10,193-10,210. https://doi.org/10.1175/JCLI-D-16-0902.1

    Article  Google Scholar 

  • Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison L, Hoell A, Michaelsen J (2015) The climate hazards infrared precipitation with stations - a new environmental record for monitoring extremes. Sci Data 2(150):066. https://doi.org/10.1038/sdata.2015.66

  • Grecu M, Olson WS, Munchak SJ, Ringerud S, Liao L, Haddad Z, Kelley BL, McLaughlin SF (2016) The gpm combined algorithm. J Atmos Oceanic Technol 33:2225–2245. https://doi.org/10.1175/JTECH-D-16-0019.1

    Article  Google Scholar 

  • Heidinger AK, Foster MJ, Walther A, Zhao X (2014) The pathfinder atmospheres - extended AVHRR climate dataset. Bull Amer Meteor Soc 95:909–922. https://doi.org/10.1175/BAMS-D-12-00246.1

    Article  Google Scholar 

  • Hong Y, Hsu KL, Sorooshian S, Gao X (2004) Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. J Appl Meteor 43:1834–1853. https://doi.org/10.1175/JAM2173.1

    Article  Google Scholar 

  • Hsu K, Gao X, Sorooshian S, Gupta HV (1997) Precipitation estimation from remotely sensed information using artificial neural networks. J Appl Meteor 36:1176–1190. https://doi.org/10.1175/1520-0450(1997)036<1176:PEFRSI>2.0.CO;2

  • Huffman GJ, Adler RF, Morrissey MM, Bolvin DT, Curtis S, Joyce R, McGavock B, Susskind J (2001) Global precipitation at one-degree daily resolution from multisatellite observations. J Hydrometeor 2:36–50. https://doi.org/10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2

  • Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multi-satellite precipitation analysis: quasi-global, multi-year, combined-sensor precipitation estimates at fine scale. J Hydrometeor 8:38–55

    Article  Google Scholar 

  • Huffman GJ, Adler RF, Bolvin DT, Hsu K, Kidd C, Nelkin EJ, J T, Xie P (2019) Algorithm theoretical basis document (ATBD) for global precipitation climatology project version 3.0 precipitation data. NASA/Goddard Space Flight Center, Greenbelt, MD, USA

    Google Scholar 

  • Huffman GJ, Bolvin DT, Braithwaite D, Hsu KL, Joyce RJ, Kidd C, Nelkin EJ, Sorooshian S, Stocker EF, Tan J, Wolff DB, Xie P (2020) Integrated multi-satellite retrievals for the global precipitation measurement (GPM) mission (IMERG). In: Levizzani V, Kidd C, Kirschbaum DB, Kummerow CD, Nakamura K, Turk FJ (eds) Satellite precipitation measurement: volume 1. Springer International Publishing, pp 343–353. https://doi.org/10.1007/978-3-030-24568-9_19

  • Joyce RJ, Janowiak JE, Arkin PA, Xie P (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeor 5:487–503. https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2

  • Karlsson KG, Anttila K, Trentmann J, Stengel M, Fokke Meirink J, Devasthale A, Hanschmann T, Kothe S, Jääskeläinen E, Sedlar J, Benas N, van Zadelhoff GJ, Schlundt C, Stein D, Finkensieper S, Håkansson N, Hollmann R (2017) CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data. Atmos Chem Phys 17:5809–5828. https://doi.org/10.5194/acp-17-5809-2017

  • Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Climate 6:1587–1606

    Article  Google Scholar 

  • Kubota T, Aonashi K, Ushio T, Shige S, Takayabu YN, Kachi M, Arai Y, Tashima T, Masaki T, Kawamoto N, Mega T, Yamamoto MK, Hamada A, Yamaji M, Liu G, Oki R (2020) Global satellite mapping of precipitation (GSMaP) products in the GPM era. In: Levizzani V, Kidd C, Kirschbaum DB, Kummerow CD, Nakamura K, Turk FJ (eds) Satellite precipitation measurement: volume 1. Springer International Publishing, pp 355–373. https://doi.org/10.1007/978-3-030-24568-9_20

  • Luo Z, Rossow WB (2004) Characterizing tropical cirrus life cycle, evolution, and interaction with upper-tropospheric water vapor using Lagrangian trajectory analysis of satellite observations. J Climate 17:4541–4563

    Article  Google Scholar 

  • Randel DL, Kummerow CD, Ringerud S (2020) The Goddard profiling (GPROF) precipitation retrieval algorithm. In: Levizzani V, Kidd C, Kirschbaum DB, Kummerow CD, Nakamura K, Turk FJ (eds) Satellite Precipitation measurement: volume 1. Springer International Publishing, pp 141–152. https://doi.org/10.1007/978-3-030-24568-9_8

  • Roca R, Haddad ZS, Akimoto FF, Alexander L, Behrangi A, Huffman G, Kato S, Kidd C, Kirstetter PE, Kubota T, Kummerow C, L’Ecuyer TS, Levizzani V, Maggioni V, Massari C, Masunaga H, Schröder M, Tapiador FJ, Turk FJ, Utsumi N (2021) The joint IPWG/GEWEX precipitation assessment. WCRP report 2/2021. World Climate Research Programme (WCRP), Geneva, Switzerland. https://doi.org/10.13021/gewex.precip

  • Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Amer Meteor Soc 80:2261–2288

    Article  Google Scholar 

  • Skofronick-Jackson G, Petersen WA, Berg W, Kidd C, Stocker EF, Kirschbaum DB, Kakar R, Braun SA, Huffman GJ, Iguchi T, Kirstetter PE, Kummerow C, Meneghini R, Oki R, Olson WS, Takayabu YN, Furukawa K, Wilheit T (2017) The global precipitation measurement (GPM) mission for science and society. Bull Amer Meteor Soc 98(8):1679–1695. https://doi.org/10.1175/BAMS-D-15-00306.1

    Article  Google Scholar 

  • Stengel M, Stapelberg S, Sus O, Schlundt C, Poulsen C, Thomas G, Christensen M, Carbajal Henken C, Preusker R, Fischer J, Devasthale A, Willén U, Karlsson KG, McGarragh GR, Proud S, Povey AC, Grainger RG, Meirink JF, Feofilov A, Bennartz R, Bojanowski JS, Hollmann R (2017) Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the cloud_cci project. Earth Syst Sci Data 9:881–904. https://doi.org/10.5194/essd-9-881-2017

  • Stephens GL, Kummerow CD (2007) The remote sensing of clouds and precipitation from space: a review. J Atmos Sci 64:3742–3765. https://doi.org/10.1175/2006JAS2375.1

    Article  Google Scholar 

  • Stephens GL, Li J, Wild M, Clayson CA, Loeb N, Kato S, L’Ecuyer T, Stackhouse PW, Lebsock M, Andrews T (2012) An update on Earth’s energy balance in light of the latest global observations. Nat Geosci 5:691–696. https://doi.org/10.1038/ngeo1580

    Article  Google Scholar 

  • Stubenrauch CJ, Rossow WB, Kinne S, Ackerman S, Cesana G, Chepfer H, Girolamo LD, Getzewich B, Guignard A, Heidinger A, Maddux BC, Menzel WP, Minnis P, Pearl C, Platnick S, Poulsen C, Riedi J, Sun-Mack S, Walther A, Winker D, Zeng S, Zhao G (2013) Assessment of global cloud datasets from satellites: project and database initiated by the GEWEX radiation panel. Bull Amer Meteor Soc 94:1031–1049. https://doi.org/10.1175/BAMS-D-12-00117.1

  • Sun Q, Miao C, Duan Q, Ashouri H, Sorooshian S, Hsu KL (2018) A review of global precipitation data sets: data sources, estimation, and intercomparisons. Rev Geophys 56:79–107. https://doi.org/10.1002/2017RG000574

    Article  Google Scholar 

  • Ushio T, Sasashige K, Kubota T, Shige S, Okamoto K, Aanashi K, Inuoe T, Takahashi N, Iguchi T, Kachi M, Oki R, Morimoto T, Kawasaki ZI (2009) A Kalman filter approach to the global satellite mapping of precipitation (GSMaP) from combined passive microwave and infrared radiometric data. J Meteor Soc Japan 87A:137–151. https://doi.org/10.2151/jmsj.87A.137

    Article  Google Scholar 

  • Xie P, Arkin PA (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Amer Meteor Soc 78:2539–2558. https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2

  • Xie P, Chen M, Yang S, Yatagai A, Hayasaka T, Fukushima Y, Liu C (2007) A gauge-based analysis of daily precipitation over east asia. J Hydrometeorol 8:607–626. https://doi.org/10.1175/JHM583.1

    Article  Google Scholar 

  • Xie P, Joyce R, Wu S, Yoo SH, Yarosh Y, Sun F, Lin R (2017) Reprocessed, bias-corrected CMORPH global high-resolution precipitation estimates from 1998. J Hydrometeor 18:1617–1641. https://doi.org/10.1175/JHM-D-16-0168.1

    Article  Google Scholar 

  • Young AH, Knapp KR, Inamdar A, Hankins W, Rossow WB (2018) The international satellite cloud climatology project H-series climate data record product. Earth Syst Sci Data 10:583–593. https://doi.org/10.5194/essd-10-583-2018

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Aichi, Japan

    Hirohiko Masunaga

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  1. Hirohiko Masunaga
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Correspondence to Hirohiko Masunaga .

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Masunaga, H. (2022). Global Datasets of Clouds and Precipitation. In: Satellite Measurements of Clouds and Precipitation. Springer Remote Sensing/Photogrammetry. Springer, Singapore. https://doi.org/10.1007/978-981-19-2243-5_12

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