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Observing and Detecting Atmospheric Rivers

From Satellites to Aircraft, Radars, AR Observatories, Regional Mesonets, Reanalyses, and AR Detection Methods

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Atmospheric Rivers

Abstract

How do we observe and detect ARs? Observing systems provide ground truth of the main AR ingredients, such as water vapor and wind, and process information on AR mechanisms and effects. Gridded atmospheric reanalysis products allow us to study ARs from historical, regional, and global perspectives. Detection methods are also critical to identifying ARs in regional and global models in order to evaluate their performance in simulating and predicting ARs, as well as to determine how ARs will behave in the future, based on global climate projections. The first three sections of this chapter describe some of the observing technologies used to monitor ARs, such as (1) satellite data, which help to provide a global context; (2) AR observatories: land-based collections of instruments that help track ARs as they make landfall; (3) other ground-based observations that track ARs as they penetrate inland; (4) airborne and other measurements from major research field experiments devoted to understanding ARs, as well as AR Reconnaissance (Recon) airborne efforts to better predict ARs; (5) the representation of ARs in reanalyses; and (6) the evolution of methods used to identify ARs and describes some of the AR climatologies that have been created using these techniques.

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Notes

  1. 1.

    Marty Ralph (NOAA) and Mike Dettinger (Scripps Institution of Oceanography and USGS) originally developed the vision for this proposal, with input from many others. It was managed by a Program Management Council consisting of Gary Bardini (DWR; sponsor), Marty Ralph (NOAA; Proposal/Contract PI), and David Cayan (Scripps and USGS; Partner). The Program Management Council oversaw execution by the Project Management Team, which was led by Allen White (NOAA), and included Michael Anderson (DWR) and Mike Dettinger (Scripps and USGS).

References

  • Alishouse JC, Snyder SA, Vongsathorn J et al (1990) Determination of oceanic total precipitable water from the SSM/I. IEEE Trans Geosci Remote Sens 28:811–816

    ADS  Google Scholar 

  • Anthes RA, Bernhardt PA, Chen Y et al (2008) The COSMIC/FORMOSAT-3 Mission: early results. Bull Am Meteorol Soc 89:313–333

    Google Scholar 

  • Ault AP, Williams CR, White AB et al (2011) Detection of Asian dust in California orographic precipitation. J Geophys Res 116:D16205

    ADS  Google Scholar 

  • Baker WE, Atlas R, Cardinali C et al (2014) Lidar-measured wind profiles. The missing link in the global observing system. Bull Am Meteorol Soc 95:543–564

    Google Scholar 

  • Bergeron T (1965) On the low-level redistribution of atmospheric water caused by orography. In: Proc Int Conf on Cloud Physics, Tokyo, Japan. IAMAP/WMO, pp 96–100

    Google Scholar 

  • Bevis M, Businger S, Herring TA et al (1992) GPS meteorology: remote sensing of the atmospheric water vapor using the global positioning system. J Geophys Res 97(D14):15787–15801

    ADS  Google Scholar 

  • Blamey RC, Ramos AM, Trigo RM et al (2018) The influence of atmospheric rivers over the South Atlantic on winter rainfall in South Africa. J Hydrometeorol 19:127–142. https://doi.org/10.1175/JHM-D-17-0111.1

    Article  ADS  Google Scholar 

  • Boukabara S–A, Garrett K (2018) Tropospheric moisture sounding using microwave imaging channels: application to GCOM-W1/AMSR2. IEEE Trans Geosci Remote Sens 56(9):5537–5549

    ADS  Google Scholar 

  • Boukabara S–A, Garrett K, Chen W et al (2011) MiRS: an all-weather 1DVAR satellite data assimilation and retrieval system. IEEE Trans Geosci Remote Sens 49:3249–3883

    ADS  Google Scholar 

  • Browning KA, Pardoe CW (1973) Structure of low-level jet streams ahead of mid-latitude cold fronts. Q J R Meteorol Soc 99(422):619–638. https://doi.org/10.1002/qj.4970994330

  • Cannon F, Ralph FM, Wilson AM et al (2017) GPM satellite radar measurements of precipitation and freezing level in atmospheric rivers: comparison with ground-based radars and reanalyses. J Geophys Res-Atmos 122:12747–12764. https://doi.org/10.1002/2017JD027355

    Article  ADS  Google Scholar 

  • Cannon F, Hecht CW, Cordeira JM et al (2018) Synoptic and mesoscale forcing of Southern California extreme precipitation. J Geophys Res-Atmos 123(24):13714–13730. https://doi.org/10.1029/2018JD029045

    Article  ADS  Google Scholar 

  • Carter DA, Gage KS, Ecklund WL et al (1995) Developments in UHF lower tropospheric wind profiling at NOAA’s aeronomy laboratory. Radio Sci 30:977–1001

    ADS  Google Scholar 

  • Chen XM, Chen SH, Haase JS et al (2018) The impact of airborne radio occultation observations on the simulation of Hurricane Karl (2010). Mon Wea Rev 146:329–350

    ADS  Google Scholar 

  • Compo GP et al (2011) The twentieth century reanalysis project. Q J Roy Meteorol Soc 137:1–28. https://doi.org/10.1002/qj.776

    Article  ADS  Google Scholar 

  • Cordeira JM, Ralph FM, Moore BJ (2013) The development and evolution of two atmospheric rivers in proximity to western North Pacific tropical cyclones in October 2010. Mon Wea Rev 141:4234–4255

    ADS  Google Scholar 

  • Cordeira JM, Ralph FM, Martin A, Natalie G, Ryan Spackman J, Neiman PJ, Rutz JJ, Pierce R (2017) Forecasting atmospheric rivers during CalWater 2015. Bull Am Meteorol Soc 98(3):449–459

    Google Scholar 

  • Creamean JM, Suski DJ, Rosenfeld D et al (2013) Dust and biological aerosols from the Sahara and Asia influence precipitation in the Western U.S. Science 339:1572–1578

    ADS  Google Scholar 

  • Creamean JM, Lee C, Hill TC et al (2014) Chemical properties of insoluble precipitation residue particles. J Aerosol Sci 76:13–27

    ADS  Google Scholar 

  • Creamean JM, Ault AP, White AB (2015) Impact of interannual variations in sources of insoluble aerosol species on orographic precipitation over California’s Central Sierra Nevada. Atmos Chem Phys 15:6535–6548

    ADS  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. https://doi.org/10.1002/qj.828

    Article  ADS  Google Scholar 

  • DeFlorio MJ, Waliser DE, Guan B et al (2018) Global assessment of atmospheric river prediction skill. J Hydrometeorol 19, 409–426. https://doi.org/10.1175/JHM-D-17-0135.1

  • DeFlorio M, Waliser DE, Guan B et al (2019) Global Evaluation of Atmospheric River Subseasonal Prediction Skill. Clim Dyn 52, 3039–3060. https://doi.org/10.1007/s00382-018-4309-x

  • Dettinger M (2011) Climate change, atmospheric rivers, and floods in California – a multimodel analysis of storm frequency and magnitude changes. J Am Water Resour Assoc 47(3):514–523

    Google Scholar 

  • Dettinger MD, Ralph FM, Das T et al (2011) Atmospheric rivers, floods and the water resources of California. Water 3(2):445–478. http://www.mdpi.com/2073-4441/3/2/445/

  • Dole RM, Spackman JR, Newman M et al (2018) Advancing science and services during the 2015-16 El Niño: the NOAA El Niño rapid response field campaign. Bull Am Meteorol Soc 99:975–1001. https://doi.org/10.1175/BAMS-D-16-0219.1

    Article  Google Scholar 

  • Doyle JD, Reynolds CA, Amerault C et al (2012) Adjoint Sensitivity and Predictability of Tropical Cyclogenesis. J Atmos Sci 69:3535–3557. https://doi.org/10.1175/JAS-D-12-0110.1

  • Doyle JD, Amerault C, Reynolds CA et al (2014) Initial condition sensitivity and predictability of a severe extratropical cyclone using a moist adjoint. Mon Wea Rev 142:320–342. https://doi.org/10.1175/MWR-D-13-00201.1

    Article  ADS  Google Scholar 

  • Duan J, Bevis M, Fang P et al (1996) GPS meteorology: direct estimation of the absolute value of precipitable water. J Appl MeteoroI 35:830–838

    Google Scholar 

  • Dunne T, Black RD (1970) An experimental investigation of runoff production in permeable soil. Water Resour Res 6:478–490

    ADS  Google Scholar 

  • Espinoza V, Waliser DE, Guan B et al (2018) Global Analysis of Climate Change Projection Effects on Atmospheric Rivers. Geophys Res Lett. https://doi.org/10.1029/2017GL076968

  • Fan J, Leung LR, DeMott PJ et al (2014) Aerosol impacts on California winter clouds and precipitation during CalWater 2011: local pollution versus long-range transported dust. Atmos Chem Phys 14(1):81

    ADS  Google Scholar 

  • Garreaud R (2013) Warm winter storms in Central Chile. J Hydrometeorol 14:1515–1534

    ADS  Google Scholar 

  • Gelaro R, Langland RH, Pellerin S et al (2010) The THORPEX observation impact intercomparison experiment. Mon Wea Rev 138:4009–4025

    ADS  Google Scholar 

  • Gelaro R, McCarty W, Suárez MJ et al (2017) The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). J Clim 30:5419–5454

    Google Scholar 

  • Gershunov A, Shulgina R, Ralph FM et al (2017) Assessing the climate-scale variability of atmospheric rivers affecting western North America. Geophys Res Lett 44:7900–7908. https://doi.org/10.1002/2017GL074175

    Article  ADS  Google Scholar 

  • Ghebrebrhan O (1990) Full decoding of truncated ranges for ST/MST radar applications. IEEE Trans Geosci Remote Sens 28:14–18

    ADS  Google Scholar 

  • Gorodetskaya IV, Tsukernik M, Claes K et al (2014) The role of atmospheric rivers in anomalous snow accumulation in East Antarctica. Geophys Res Lett 41:6199–6206

    ADS  Google Scholar 

  • Guan B, Waliser DE (2015) Detection of atmospheric rivers: evaluation and application of an algorithm for global studies. J Geophys Res Atmos 120:12514–12535. https://doi.org/10.1002/2015JD024257

    Article  ADS  Google Scholar 

  • Guan B, Waliser DE (2017) Atmospheric rivers in 20 year weather and climate simulations: a multimodel, global evaluation. J Geophys Res Atmos 122:5556–5581. https://doi.org/10.1002/2016JD026174

    Article  ADS  Google Scholar 

  • Guan B, Molotch NP, Waliser DE et al (2010) Extreme snowfall events linked to atmospheric rivers and surface air temperature via satellite measurements. Geophys Res Lett 37:L20401. https://doi.org/10.1029/2010GL044696

    Article  ADS  Google Scholar 

  • Guan B, Waliser DE, Ralph FM (2018) An inter-comparison between reanalysis and dropsonde observations of the total water vapor transport in individual atmospheric rivers. J Hydrometeorol 19:321–337. https://doi.org/10.1175/JHM-D-17-0114.1

    Article  ADS  Google Scholar 

  • Guttman SI, Sahm SR, Benjamin SG et al (2004) Rapid retrieval and assimilation of ground based GPS precipitable water observations at the NOAA forecast systems laboratory: impact on weather forecasts. J Meteorol Soc Japan 82:351–360. https://doi.org/10.2151/jmsj.2004.351

  • Haase JS, Murphy BJ, Muradyan P et al (2014) First results from an airborne GPS radio occultation system for atmospheric profiling. Geophys Res Lett 41:1759–1765

    ADS  Google Scholar 

  • Han M, Braun SA, Persson PO et al (2009) Alongfront variability of precipitation associated with a midlatitude frontal zone: TRMM observations and MM5 simulation. Mon Wea Rev 137:1008–1028

    ADS  Google Scholar 

  • Hollinger JP, Peirce JL, Poe GA (1990) SSM/I instrument evaluation. IEEE Trans Geosci Remote Sens 28:781–790

    ADS  Google Scholar 

  • Huning LS, Margulis SA, Guan B et al (2017) Implications of detection methods on characterizing atmospheric river contribution to seasonal snowfall across Sierra Nevada, USA. Geophysical Res Lett 44:10445–10453. https://doi.org/10.1002/2017GL075201

  • Jackson DL, Hughes H, Wick GA (2016) Evaluation of landfalling atmospheric rivers along the U.S. West Coast in reanalysis data sets. J Geophys Res Atmos 121:2705–2718. https://doi.org/10.1002/2015JD024412

    Article  ADS  Google Scholar 

  • Johnston PE, Jordan JR, White AB (2017) The NOAA FM-CW snow-level radar. J Atmos Ocean Technol 34:249–267

    Google Scholar 

  • Jorgensen DP, Pu Z, Persson PO et al (2003) Variations associated with cores and gaps of a Pacific narrow cold frontal rainband. Mon Wea Rev 131:2705–2729

    ADS  Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R et al (1996) The NMC/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471. https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2

    Article  Google Scholar 

  • Kidder SQ, Jones AS (2007) A blended satellite total precipitable water product for operational forecasting. J Atmos Ocean Technol 24:74–81

    Google Scholar 

  • Kingsmill DE, Neiman PJ, Ralph FM et al (2006) Synoptic and topographic variability of northern California precipitation characteristics in landfalling winter storms observed during CALJET. Mon Wea Rev 134:2072–2094

    ADS  Google Scholar 

  • Kingsmill DE, Neiman PJ, Moore BJ et al (2013) Kinematic and thermodynamic structures of Sierra barrier jets and overrunning atmospheric rivers during a landfalling winter storm in northern California. Mon Wea Rev 141:2015–2036. https://doi.org/10.1175/MWR-D-12-00277.1

    Article  ADS  Google Scholar 

  • Kingsmill DE, Neiman PJ, White AB (2016) Microphysics regime impacts on the relationship between orographic rain and orographic forcing in the coastal mountains of northern California. J Hydrometeorol 17:2905–2922

    ADS  Google Scholar 

  • Kingston DG, Lavers DA, Hannah DM (2016) Floods in the Southern Alps of New Zealand: the importance of atmospheric rivers. Hydrol Process 30:5063–5070. https://doi.org/10.1002/hyp.10982

    Article  ADS  Google Scholar 

  • Kren AC, Cucurull L, Wang H (2018) Impact of UAS Global Hawk dropsonde data on tropical and extratropical cyclone forecasts in 2016. Weather Forecast 33:1121–1141

    ADS  Google Scholar 

  • Kunkee DB, Poe GA, Boucher DJ et al (2008) Design and evaluation of the first special sensor microwave imager/sounder. IEEE Trans Geosci Remote Sens 46:863–883

    ADS  Google Scholar 

  • Lavers DA, Villarini G, Allan RP et al (2012) The detection of atmospheric rivers in atmospheric reanalyses and their links to British winter floods and the large-scale climatic circulation. J Geophys Res 117:D20106. https://doi.org/10.1029/2012JD018027

    Article  ADS  Google Scholar 

  • Lim S, Cifelli R, Chandrasekar V et al (2013) Precipitation classification and quantification using X-band dual-polarization weather radar: application in the hydrometeorology Testbed. J Atmos Ocean Technol 30:2108–2120

    Google Scholar 

  • Lojou J–Y, Benard R, Eymard L (1994) A simple method for testing brightness temperatures from satellite microwave radiometers. J Atmos Ocean Technol 11:387–400

    Google Scholar 

  • Ma Z, Kuo Y-H, Ralph FM et al (2011) Assimilation of GPS radio occultation data for an intense atmospheric river with the NCEP regional GSI system. Mon Wea Rev 139:2170–2183

    ADS  Google Scholar 

  • Mahoney K, Jackson DL, Neiman P (2016) Understanding the role of atmospheric rivers in heavy precipitation in the Southeast United States. Mon Wea Rev 144:1617–1632

    ADS  Google Scholar 

  • Martin AC, Cornwell GC, Atwood SA et al (2017) Transport of pollution to a remote coastal site during gap flow from California’s interior: impacts on aerosol composition, clouds, and radiative balance. Atmos Chem Phys 17:1491–1509

    ADS  Google Scholar 

  • Martin A, Ralph FM, Demirdjian R et al (2018) Evaluation of atmospheric river predictions by the WRF model using aircraft and regional Mesonet observations of orographic precipitation and its forcing. J Hydrometeorol 19:1097–1113. https://doi.org/10.1175/JHM-D-17-0098

    Article  ADS  Google Scholar 

  • Martner BE, Yuter SE, White AB et al (2008) Raindrop size distributions and rain characteristics in California coastal rainfall for periods with and without a radar bright band. J Hydrometeorol 9:408–425

    ADS  Google Scholar 

  • Matrosov SY (2013) Characteristics of landfalling atmospheric rivers inferred from satellite observations over the eastern North Pacific Ocean. Mon Wea Rev 141(11):3757–3768. https://doi.org/10.1175/MWR-D-12-00324.1

    Article  ADS  Google Scholar 

  • Matrosov SY, Clark KA, Kingsmill DE (2007) A polarimetric radar approach to identify rain, melting-layer, and snow regions for applying corrections to vertical profiles of reflectivity. J Appl Meteorol Climatol 46:154–166

    ADS  Google Scholar 

  • Morss RE, Ralph FM (2007) Use of information by National Weather Service forecasters and emergency managers during CALJET and PACJET-2001. Wea Forecast 22:539–555

    ADS  Google Scholar 

  • Mundhenk B, Barnes EA, Maloney ED (2016) All-season climatology and variability of atmospheric rivers over the North Pacific. J Clim. https://doi.org/10.1175/JCLI-D-15-0655.1

  • Neff W, Compo GP, Ralph FM et al (2014) Continental heat anomalies and the extreme melting of the Greenland ice surface in 2012 and 1889. J Geophys Res Atmos 119:6520–6536

    ADS  Google Scholar 

  • Neiman PJ, Ralph FM, White AB et al (2002) The statistical relationship between upslope flow and rainfall in California’s coastal mountains: observations during CALJET. Mon Wea Rev 130:1468–1492

    ADS  Google Scholar 

  • Neiman PJ, Ralph FM, Persson PO et al (2004) Modification of fronts and precipitation by coastal blocking during an intense landfalling winter storm in Southern California: observations during CALJET. Mon Wea Rev 132:242–273

    ADS  Google Scholar 

  • Neiman PJ, Wick GA, Ralph FM et al (2005) Wintertime nonbrightband rain in California and Oregon during CALJET and PACJET: geographic, interannual, and synoptic variability. Mon Wea Rev 133:1199–1223

    ADS  Google Scholar 

  • Neiman PJ, Ralph FM, White AB et al (2006) A multiwinter analysis of channeled flow through a prominent gap along the Northern California coast during CALJET and PACJET. Mon Wea Rev 134:1815–1841

    ADS  Google Scholar 

  • Neiman PJ, Ralph FM, Wick GA et al (2008a) Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West Coast of North America based on eight years of SSM/I satellite observations. J Hydrometeorol 9:22–47

    ADS  Google Scholar 

  • Neiman PJ, Ralph FM, Wick GA et al (2008b) Diagnosis of an intense atmospheric river impacting the Pacific Northwest: storm summary and offshore vertical structure observed with COSMIC satellite retrievals. Mon Weather Rev 136:4398–4420

    ADS  Google Scholar 

  • Neiman PJ, White AB, Ralph FM et al (2009) A water vapour flux tool for precipitation forecasting. Proc Inst Civil Eng Water Manag 162:83–94

    Google Scholar 

  • Neiman PJ, Schick LJ, Ralph FM et al (2011) Flooding in Western Washington: the connection to atmospheric rivers. J Hydrometeorol 12:1337–1358

    ADS  Google Scholar 

  • Neiman PJ, Ralph FM, Moore BJ et al (2013a) The landfall and inland penetration of a flood-producing atmospheric river in Arizona. Part 1: observed synoptic-scale, orographic, and hydrometeorological characteristics. J Hydrometeorol 14:460–484

    ADS  Google Scholar 

  • Neiman PJ, Hughes M, Moore BJ et al (2013b) Sierra barrier jets, atmospheric rivers, and precipitation characteristics in Northern California: a composite perspective based on a network of wind profilers. Mon Wea Rev 141:4211–4233

    ADS  Google Scholar 

  • Neiman PJ, Wick GA, Moore BJ et al (2014) An airborne study of an atmospheric river over the subtropical Pacific during WISPAR: Dropsonde budget-box diagnostics, and precipitation impacts in Hawaii. Mon Wea Rev 142:3199–3223

    ADS  Google Scholar 

  • Neiman PJ, Moore BJ, White AB et al (2016) An airborne and ground-based study of a long-lived and intense atmospheric river with mesoscale frontal waves impacting California during CalWater-2014. Mon Wea Rev 144:1115–1144

    ADS  Google Scholar 

  • Neiman PJ, Gaggini N, Fairall CW et al (2017) An analysis of coordinated observations from NOAA’s Ronald H. Brown ship and G-IV aircraft in a landfalling atmospheric river over the North Pacific during CalWater-2015. Mon Wea Rev 145:3647–3669

    ADS  Google Scholar 

  • Newell RE, Newell NE, Zhu Y et al (1992) Tropospheric rivers? – a pilot study. Geophys Res Lett 19:2401–2404

    ADS  Google Scholar 

  • Nieman SJ, Menzel WP, Hayden CM et al (1997) Fully automated cloud-drift winds in NESDIS operations. Bull Am Meteorol Soc 78:1121–1133

    Google Scholar 

  • Payne AE, Magnusdottir G (2014) Dynamics of landfalling atmospheric rivers over the North Pacific in 30 years of MERRA reanalysis. J Clim 27(18):7133–7150. https://doi.org/10.1175/JCLI-D-14-00034.1

    Article  ADS  Google Scholar 

  • Persson PO, Neiman PJ, Walter B et al (2005) Contributions from California coastal-zone surface fluxes to heavy coastal precipitation: a CALJET case study during the strong El Niño of 1998. Mon Wea Rev 133:1175–1198

    ADS  Google Scholar 

  • Petty GW (1994) Physical retrievals of over-ocean rain rate from multi-channel microwave imaging. Part II: algorithm implementation. Meteorog Atmos Phys 54:101–122

    ADS  Google Scholar 

  • Poli P et al (2016) ERA–20C: an atmospheric reanalysis of the 20th century. J Clim 29(11):4083–4097. https://doi.org/10.1175/JCLI-D-15-0556.1

    Article  ADS  Google Scholar 

  • Ralph FM, Persson POG, Reynolds D et al (1999) The California Land-falling Jets Experiment (CALJET): Objectives and design of a coastal atmosphere–ocean observing system deployed during a strong El Niño. In: Preprints, Third Symp. on Integrated Observing Systems, Dallas, TX. Amer Meteor Soc, pp 78–81

    Google Scholar 

  • Ralph FM, Neiman PJ, Kingsmill DE et al (2003) The impact of a prominent rain shadow on flooding in California’s Santa Cruz Mountains: a CALJET case study and sensitivity to the ENSO cycle. J Hydrometeor 4:1243–1264

    Google Scholar 

  • Ralph FM, Neiman PJ, Wick GA (2004) Satellite and CALJET aircraft observations of atmospheric rivers over the eastern North Pacific Ocean during the winter of 1997/98. Mon Wea Rev 132:1721–1745

    ADS  Google Scholar 

  • Ralph FM, Neiman PJ, Rotunno R (2005a) Dropsonde observations in low-level jets over the northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: mean vertical-profile and atmospheric-river characteristics. Mon Wea Rev 133:889–910

    ADS  Google Scholar 

  • Ralph FM, Rauber RM, Jewett BF et al (2005b) Improving short-term (0–48 h) cool-season quantitative precipitation forecasting: recommendations from a USWRP Workshop. Bull Am Meteorol Soc 86:1619–1632

    Google Scholar 

  • Ralph FM, Neiman PJ, Wick GA et al (2006) Flooding on California’s Russian River: the role of atmospheric rivers. Geophys Res Lett 33:L13801. https://doi.org/10.1029/2006GL026689

    Article  ADS  Google Scholar 

  • Ralph FM, Sukovich E, Reynolds D et al (2010) Assessment of extreme quantitative precipitation forecasts and development of regional extreme event thresholds using data from HMT-2006 and COOP observers. J Hydrometeorol 11:1288–1306

    Google Scholar 

  • Ralph FM, Neiman PJ, Kiladis GN et al (2011) A multi-scale observational case study of a Pacific atmospheric river exhibiting tropical-extratropical connections and a mesoscale frontal wave. Mon Wea Rev 139:1169–1189. https://doi.org/10.1175/2010MWR3596.1

    Article  ADS  Google Scholar 

  • Ralph FM, Wick GA, Neiman PJ et al (2012) Atmospheric rivers in reanalysis products: a six-event comparison with aircraft observations of water vapor transport, WCRP Reanalysis Conf., Silver Spring, MD, 1 p. https://www.wcrp-climate.org/ICR4/posters/Hughes_AT-20.pdf

  • Ralph FM, Intrieri J, Andra D Jr et al (2013a) The emergence of weather-focused testbeds linking research and forecasting operations. Bull Am Meteorol Soc 94:1187–1210

    Google Scholar 

  • Ralph FM, Coleman T, Neiman PJ et al (2013b) Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal Northern California. J Hydrometeorol 14:443–459

    ADS  Google Scholar 

  • Ralph FM, Dettinger MD, White A (2014) A vision for future observations for Western U.S. extreme precipitation and flooding. J Contemp Water Resour Res Educ 153:16–32

    Google Scholar 

  • Ralph FM, Prather KA, Cayan D et al (2016) CalWater field studies designed to quantify the roles of atmospheric rivers and aerosols in modulating U.S. West Coast precipitation in a changing climate. Bull Am Meteorol Soc 97:1209–1228. https://doi.org/10.1175/BAMS-D-14-00043.1

    Article  Google Scholar 

  • Ralph FM, Iacobellis SF, Neiman PJ et al (2017) Dropsonde observations of total integrated water vapor transport within North Pacific atmospheric rivers. J Hydrometeorol 18(9):2577–2596. https://doi.org/10.1175/JHM-D-17-0036.1

    Article  ADS  Google Scholar 

  • Ralph FM, Dettinger MD, Cairns MM et al (2018a) Defining “atmospheric river” how the glossary of meteorology helped resolve a debate. Bull Am Meteorol Soc 99:837–839

    Google Scholar 

  • Ralph FM, Wilson AM, Shulgina T et al (2018b) Comparison of Atmospheric River Detection Tools: How Many Atmospheric Rivers Hit Northern California’s Russian River Watershed? Climate Dynamics. 10.1007/s00382-018-4427-5

    Google Scholar 

  • Ralph FM, Rutz JJ, Cordeira JM et al (2019) A scale to characterize the strength and impacts of atmospheric rivers. Bull Am Meteorol Soc 100:269–289. https://doi.org/10.1175/BAMS-D-18-0023.1

    Article  Google Scholar 

  • Ramos AM, Trigo RM, Liberato ML et al (2015) Daily precipitation extreme events in the Iberian Peninsula and Its association with atmospheric rivers. J Hydrometeorol 16:579–597. https://doi.org/10.1175/JHM-D-14-0103.1

    Article  ADS  Google Scholar 

  • Richiardone R, Manfrin M (2009) Neutral saturated lapse rate: an experimental check from CALJET-1998 and PACJET-2001. Mon Wea Rev 137:4382–4385

    ADS  Google Scholar 

  • Rienecker MM et al (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24:3624–3648. https://doi.org/10.1175/JCLI-D-11-00015.1

    Article  ADS  Google Scholar 

  • Rosenfeld D, Chemke R, Prather K et al (2014) Polluting of winter convective clouds upon transition from ocean inland over Central California: contrasting case studies. Atmos Res 135–136:112–127

    Google Scholar 

  • Rutz JJ, Steenburgh WJ (2012) Quantifying the role of atmospheric rivers in the interior western United States. Atmos Sci Lett 13:257–261

    ADS  Google Scholar 

  • Rutz JJ, Steenburgh WJ, Ralph FM (2014) Climatological characteristics of atmospheric rivers and their inland penetration over the western United States. Mon Wea Rev 142:905–921. https://doi.org/10.1175/MWR-D-13-00168.1

    Article  ADS  Google Scholar 

  • Saha S, Moorthi S, Pan H–L et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91:1015–1057. https://doi.org/10.1175/2010BAMS3001.1

  • Schäfler A, Craig G, Wernli H et al (2018) The North Atlantic Waveguide and Downstream Impact Experiment Bull Amer Meteor Soc 99:1607–1637. https://doi.org/10.1175/BAMS-D-17-0003.1

  • Schlüssel P, Emery WJ (1990) Atmospheric water vapour over oceans from SSM/I measurements. Int J Remote Sens 11:753–766

    Google Scholar 

  • Shields CA, Rutz JJ, Leung L–Y et al (2018) Atmospheric River Tracking Method Intercomparison Project (ARTMIP); project goals and experimental design. Geosci. Model Dev 11:2455–2474

    ADS  Google Scholar 

  • Viale M, Valenzuela R, Garreaud RD et al (2018) Impacts of atmospheric rivers on precipitation in southern South America. J Hydrometeorol 19:1671–1687. https://doi.org/10.1175/JHM-D-18-0006.1

    Article  ADS  Google Scholar 

  • Waliser D, Guan B (2017) Extreme winds and precipitation during landfall of atmospheric rivers. Nat Geosci 10:179–183. https://doi.org/10.1038/NGEO2894

  • Waliser DE, Moncrieff MW, Burridge D et al (2012) The “year” of tropical convection (May 2008 – April 2010): climate variability and weather highlights. Bull Am Meteorol Soc 93:1189–1218

    Google Scholar 

  • Weng F, Zhao L, Poe G et al (2003) AMSU cloud and precipitation algorithms. Radio Sci 38:8068–8079

    ADS  Google Scholar 

  • Wentz FJ (1995) The intercomparison of 53 SSM/I water vapor algorithms. Technical report, Remote Sens Syst, Santa Rosa, CA. 19 pp

    Google Scholar 

  • Wentz FJ (1997) A well-calibrated ocean algorithm for special sensor microwave/imager. J Geophys Res 102:8703–8718

    ADS  Google Scholar 

  • Wentz FJ, Ricciardulli L, Hilburn KA et al (2007) How much more rain will global warming bring? Science 317:233–235

    ADS  Google Scholar 

  • White AB, Jordan RJ, Martner BE et al (2000) Extending the dynamic range of an S-band radar for cloud and precipitation studies. J Atmos Ocean Technol 17:1226–1234

    Google Scholar 

  • White AB, Gottas DJ, Strem ET et al (2002) An automated brightband height detection algorithm for use with Doppler radar spectral moments. J Atmos Ocean Technol 19:687–697

    Google Scholar 

  • White AB, Neiman PJ, Ralph FM et al (2003) Coastal orographic rainfall processes observed by radar during the California land-falling jets experiment. J Hydrometeorol 4:264–282

    ADS  Google Scholar 

  • White AB, Gottas DJ, Henkel AF et al (2010) Developing a performance measure for snow-level forecasts. J Hydrometeorol 11:739–753

    ADS  Google Scholar 

  • White AB, Anderson ML, Dettinger MD et al (2013) A twenty-first-century California observing network for monitoring extreme weather events. J Atmos Ocean Technol 30:1585–1603

    Google Scholar 

  • White AB, Mahoney KM, Cifelli R et al (2015a) Wind profilers to aid with monitoring and forecasting of high-impact weather in the Southeastern and Western United States. Bull Am Meteorol Soc 96:2039–2043

    Google Scholar 

  • White AB, Neiman PJ, Creamean JM et al (2015b) The impacts of California’s San Francisco Bay Area gap on precipitation observed in the Sierra Nevada during HMT and CalWater. J Hydrometeorol 16:1048–1069

    ADS  Google Scholar 

  • Wick GA, Kuo Y, Ralph FM et al (2008) Intercomparison of integrated water vapor retrievals from SSM/I and COSMIC. Geophys Res Lett 35:L21805. https://doi.org/10.1029/2008GL035126

    Article  ADS  Google Scholar 

  • Wick GA, Neiman PJ, Ralph FM (2013a) Description and validation of an automated objective technique for identification and characterization of the integrated water vapor signature of atmospheric rivers. IEEE Trans Geosci Remote Sens 51:2166–2176

    ADS  Google Scholar 

  • Wick GA, Neiman PJ, Ralph FM et al (2013b) Evaluation of forecasts of the water vapor signature of atmospheric rivers in operational numerical weather prediction models. Weather Forecast 28:1337–1352

    ADS  Google Scholar 

  • Wick GA, Dunion JP, Walker J (2018a) Sensing Hazards with Operational Unmanned Technology: Impact study of Global Hawk unmanned aircraft system observations for hurricane forecasting, Final Report. NOAA Tech Memo. OAR-UAS-002, 94 pp

    Google Scholar 

  • Wick GA, Hock TF, Neiman PJ et al (2018b) The NCAR/NOAA Global Hawk dropsonde system. J Atmos Ocean Technol 35:1585–1604. https://doi.org/10.1175/JTECH-D-17-0225.1

    Article  Google Scholar 

  • Wimmers AJ, Velden CSA (2011) Seamless advective blending of total precipitable water retrievals from polar-orbiting satellites. J Appl Meteorol Climatol 50:1024–1036

    ADS  Google Scholar 

  • Zamora RJ, Ralph FM, Clark E et al (2011) The NOAA hydrometeorology testbed soil moisture observing networks: design, instrumentation, and preliminary results. J Atmos Ocean Technol 28:1129–1140

    Google Scholar 

  • Zhu Y, Newell RE (1998) A proposed algorithm for moisture fluxes from atmospheric rivers. Mon Wea Rev 126(3):725–735. https://doi.org/10.1175/1520-0493(1998)126<0725:APAFMF>2.0.CO;2

    Article  ADS  Google Scholar 

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Ralph, F.M., White, A.B., Wick, G.A., Anderson, M.L., Rutz, J.J. (2020). Observing and Detecting Atmospheric Rivers. In: Ralph, F., Dettinger, M., Rutz, J., Waliser, D. (eds) Atmospheric Rivers. Springer, Cham. https://doi.org/10.1007/978-3-030-28906-5_3

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