• American Meteorological Society, 2017: Atmospheric river. Glossary of Meteorology, http://glossary.ametsoc.org/wiki/Atmospheric_river.

  • Biasutti, M., R. Seager, and D. B. Kirschbaum, 2016: Landslides in West Coast metropolitan areas: The role of extreme weather events. Wea. Climate Extremes, 14, 6779, https://doi.org/10.1016/j.wace.2016.11.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Campbell, R. H., 1975: Soil slips, debris flows, and rainstorms in the Santa Monica Mountains and vicinity, Southern California. USGS Professional Paper 851, 51 pp., https://pubs.usgs.gov/pp/0851/report.pdf.

    • Crossref
    • Export Citation
  • Campbell, R. H., R. L. Bernknopf, and D. R. Soller, 1998: Mapping time-dependent changes in soil slip-debris flow probability. USGS Miscellaneous Investigations Series Map I-2586, https://doi.org/10.3133/i2586.

    • Crossref
    • Export Citation
  • Cannon, S. H., and S. Ellen, 1985: Rainfall conditions for abundant debris avalanches, San Francisco Bay, California. Calif. Geol., 38 (12), 267272.

    • Search Google Scholar
    • Export Citation
  • Cannon, S. H., and J. E. Gartner, 2005: Debris-flow hazard analysis. Debris-Flow Hazards and Related Phenomena, M. Jakob and O. Hungr, Eds. Springer, 363374.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, X., L. R. Leung, Y. Gao, Y. Liu, M. Wigmosta, and M. Richmond, 2018: Predictability of extreme precipitation in western U.S. watersheds based on atmospheric river occurrence, intensity, and duration. Geophys. Res. Lett., 45, 11 69311 701, https://doi.org/10.1029/2018GL079831.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coe, J. A., J. W. Godt, R. L. Baum, R. C. Bucknam, and J. A. Michael, 2004: Landslide susceptibility from topography in Guatemala, Landslides: Evaluation and Stabilization, Proceedings of the 9th International Symposium on Landslides, Rio de Janeiro, Brazil, June 28-July 2, 2004, W. A. Lacerda et al., Eds., A. A. Balkema, 69–78.

    • Search Google Scholar
    • Export Citation
  • Compo, G. P., J. S. Whitaker, and P. D. Sardeshmukh, 2006: Feasibility of a 100-year reanalysis using only surface pressure data. Bull. Amer. Meteor. Soc., 87, 175190, https://doi.org/10.1175/BAMS-87-2-175.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Compo, G. P., and Coauthors, 2011: The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc., 137, 128, https://doi.org/10.1002/qj.776.

  • Cordeira, J. M., F. M. Ralph, A. Martin, N. Gaggini, J. R. Spackman, P. J. Neiman, J. Rutz, and R. Pierce, 2017: Forecasting atmospheric rivers during CalWater 2015. Bull. Amer. Meteor. Soc., 98, 449459, https://doi.org/10.1175/BAMS-D-15-00245.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Easterling, D. R., G. A. Meehl, C. Parmesan, S. A. Changnon, T. R. Karl, and L. O. Mearns, 2000: Climate extremes: Observations, modeling, and impacts. Science, 289, 20682074, https://doi.org/10.1126/science.289.5487.2068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ellen, S. D., and G. F. Wieczorek, 1988: Landslides, floods, and marine effects of the storm of January 3–5, 1982, in the San Francisco Bay Region, California. USGS Professional Paper 1434, 310 pp., https://pubs.usgs.gov/pp/1988/1434/pp1434.pdf.

    • Search Google Scholar
    • Export Citation
  • Ellen, S. D., R. K. Mark, G. F. Wieczorek, C. M. Wentworth, D. W. Ramsey, and T. E. May, 1997: Map showing principal debris-flow source areas in the San Francisco Bay region, California. USGS Open-File Rep. 97-745 E, 8 pp., https://doi.org/10.3133/ofr97745E.

    • Search Google Scholar
    • Export Citation
  • Florsheim, J. L., E. A. Keller, and D. W. Best, 1991: Fluvial sediment transport in response to moderate storm flows following chaparral wildfire, Ventura County, Southern California. Geol. Soc. Amer. Bull., 103, 504511, https://doi.org/10.1130/0016-7606(1991)103<0504:FSTIRT>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hatchett, B. J., S. Burak, J. J. Rutz, N. S. Oakley, E. H. Bair, and M. L. Kaplan, 2017: Avalanche fatalities during atmospheric river events in the western United States. J. Hydrometeor., 18, 13591374, https://doi.org/10.1175/JHM-D-16-0219.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Highland, L. M., 2004: Landslide types and processes. USGS Fact Sheet 2004-3072, 4 pp., https://doi.org/10.3133/fs20043072.

  • Hobbs, P. V., and P. O. G. Persson, 1982: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part V: the substructure of narrow cold-frontal rainbands. J. Atmos. Sci., 39, 280295, https://doi.org/10.1175/1520-0469(1982)039<0280:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iverson, R. M., 1997: The physics of debris flows. Rev. Geophys., 35, 245296.

  • Iverson, R. M., and Coauthors, 2015: Landslide mobility and hazards: Implications of the 2014 Oso disaster. Earth Planet. Sci. Lett., 412, 197208, https://doi.org/10.1016/j.epsl.2014.12.020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jibson, R. W., 2005: Landslide hazards at La Conchita, California. USGS Open File Rep. 05-1067, 12 pp., https://pubs.usgs.gov/of/2005/1067/pdf/OF2005-1067.pdf.

    • Search Google Scholar
    • Export Citation
  • Kelley, R., 1998: Battling the Inland Sea: Floods, Public Policy, and the Sacramento Valley. University of California Press, 426 pp.

  • Kirschbaum, D. B., R. Adler, Y. Hong, S. Hill, and A. Lerner-Lam, 2010: A global landslide catalog for hazard applications: Methods, results, and limitation. Nat. Hazards, 52, 561575, https://doi.org/10.1007/s11069-009-9401-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamjiri, M. A., M. D. Dettinger, F. M. Ralph, and B. Guan, 2017: Hourly storm characteristics along the U.S. West Coast: Role of atmospheric rivers in extreme precipitation. Geophys. Res. Lett., 44, 70207028, https://doi.org/10.1002/2017GL074193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., F. M. Ralph, G. A. Wick, J. D. Lundquist, and M. D. Dettinger, 2008: 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. Hydrometeor., 9, 2247, https://doi.org/10.1175/2007JHM855.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nilsen, T. H., and B. L. Turner, 1975: Influence of rainfall and ancient landslide deposits on recent landslides (1950–71) in urban areas of Contra Costa County, California. USGS Bulletin 1388, 18 pp., https://doi.org/10.3133/b1388.

    • Search Google Scholar
    • Export Citation
  • Nilsen, T. H., F. A. Taylor, and E. E. Brabb, 1976: Recent landslides in Alameda County, California (1940–71): An estimate of economic losses and correlations with slope, rainfall, and ancient landslide depots. USGS Bulletin 1398, 21 pp., https://doi.org/10.3133/b1398.

    • Search Google Scholar
    • Export Citation
  • NOAA, 2011: California isopluvials of 2-year 24-hour precipitation in inches. NOAA Atlas 14, Vol. 6, Version 2, accessed 10 June 2018, ftp://hdsc.nws.noaa.gov/pub/hdsc/data/sw/ca2y24h.pdf.

    • Search Google Scholar
    • Export Citation
  • NOAA, 2017: 20CR climate indices: SOI. Accessed 10 July 2017, www.esrl.noaa.gov/psd/data/20thC_Rean/timeseries/monthly/SOI.

  • NWS, 1982: Report on the San Francisco Bay area storm January 3–5, 1982. Western Region Headquarters, National Weather Service, 39 pp., www.weather.gov/media/publications/assessments/San%20Francisco%20Bay%20Area%20Storm%20January%201982.pdf.

  • Oakley, N. S., J. T. Lancaster, M. L. Kaplan, and F. Martin Ralph, 2017: Synoptic conditions associated with cool-season post-fire debris flows in the Transverse Ranges of Southern California. Nat. Hazards, 88, 327354, https://doi.org/10.1007/s11069-017-2867-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oakley, N. S., J. T. Lancaster, B. J. Hatchett, J. Stock, F. M. Ralph, S. Roj, and S. Lukashov, 2018: A 22-year climatology of cool-season hourly precipitation thresholds conducive to shallow landslides in California. Earth Interact ., 22, https://doi.org/10.1175/EI-D-17-0029.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and M. D. Dettinger, 2012: Historical and national perspectives on extreme west coast precipitation associated with atmospheric rivers during December 2010. Bull. Amer. Meteor. Soc., 93, 783790, https://doi.org/10.1175/BAMS-D-11-00188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., P. J. Neiman, R. J. Zamora, and M. D. Dettinger, 2013: Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal in coastal Northern California. J. Hydrometeor., 14, 443459, https://doi.org/10.1175/JHM-D-12-076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., J. J. Rutz, J. M. Cordeira, M. Dettinger, M. Anderson, D. Reynolds, L. J. Schick, and C. Smallcomb, 2019: A scale to characterize the strength and impacts of atmospheric rivers. Bull. Amer. Meteor. Soc., 100, 269289, https://doi.org/10.1175/BAMS-D-18-0023.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reid, M., 1994: A pore-pressure diffusion model for estimating landslide-inducing rainfall. J. Geol., 102, 709717, https://doi.org/10.1086/629714.

  • Ropelewski, C. F., and P. D. Jones, 1987: Extension of the Tahiti–Darwin Southern Oscillation index. Mon. Wea. Rev., 115, 21612165, https://doi.org/10.1175/1520-0493(1987)115<2161:AEOTTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rutz, J. J., W. J. Steenburgh, and F. M. Ralph, 2014: Climatological characteristics of atmospheric rivers and their inland penetration over the western United States. Mon. Wea. Rev., 142, 905921, https://doi.org/10.1175/MWR-D-13-00168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stock, J. D., and W. E. Dietrich, 2003: Valley incision by debris flows: Evidence of a topographic signature. Water Resour. Res., 39, 1089, https://doi.org/10.1029/2001WR001057.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, A. K., 1996: Colluvium and Talus. Landslides: Investigation and Mitigation: Special Report 247, A. K. Turner and R. L. Schuster, Eds., National Academy of Sciences, 525555.

    • Search Google Scholar
    • Export Citation
  • Varnes, D. J., 1954: Landslide types and processes. Landslides and Engineering Practice: Special Report 28, E. B. Eckel, Eds., National Academy of Sciences, 2047.

    • Search Google Scholar
    • Export Citation
  • Waliser, D., and B. Guan, 2017: Extreme winds and precipitation during landfall of atmospheric rivers. Nat. Geosci., 10, 179183, https://doi.org/10.1038/ngeo2894.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wieczorek, G. F., 1987: Effect of rainfall intensity and duration on debris flows in central Santa Cruz Mountains, California. Debris Flows/Avalanches: Process, Recognition, and Mitigation, J. E. Costa and G. F. Wieczorek, Eds., Reviews in Engineering Geology, Vol. 7, Geological Society of America, 93104.

    • Search Google Scholar
    • Export Citation
  • Wilson, R. C., and A. S. Jayko, 1997: Preliminary maps showing rainfall thresholds for debris-flow activity, San Francisco Bay region, California. USGS Open-File Rep. 97-745 F, 20 pp., https://doi.org/10.3133/ofr97745F.

    • Search Google Scholar
    • Export Citation
  • Young, A. M., K. T Skelly, and J. M. Cordeira, 2017: High-impact hydrologic events and atmospheric rivers in California: An investigation using the NCEI storm events database. Geophys. Res. Lett., 44, 33933401, https://doi.org/10.1002/2017GL073077.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • View in gallery

    (a),(b) Analyses of sea level pressure (hPa; gray contours with labeled storms L1 and L2), IWV (cm; shaded according to scale), and IVT vectors (plotted for magnitudes >150 kg m–1 s–1 and scaled according to reference vector) from the NOAA 20CR, and (c) annotated analysis by the USGS showing distribution of mapped debris flows and locations of deaths caused by landslides during 3–5 Jan 1982. Panel (c) provided by Fig. 2 of Ellen and Wieczorek (1988, p. 3).

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    Identified number of San Francisco Bay Area landslide onset days 1871–2012 (a) by water year, (b) by month with and without concurrence of IVT magnitudes ≥250 kg m–1 s–1 at 38°N, 122°W, and (c) by county per decade. Panel (c) created using Esri ArcMap 10.3.1 with county and state outlines obtained from the U.S. Census Bureau (www.census.gov/geo/maps-data/data/tiger-cart-boundary.html).

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    Time-lagged composite mean time series of IVT magnitude (kg m–1 s–1 red line) and 3-h instantaneous precipitation rate [mm (3 h)–1; gray and green bars] relative to the time of maximum IVT magnitude for San Francisco Bay Area landslide onset days (N = 214) at 38°N, 122°W. The +1 and –1 standard deviation of the IVT magnitude (solid blue lines), climatology of mean IVT magnitude (solid black line), and IVT magnitude of 250 kg m–1 s–1 (dashed black line) are provided for reference. Green bars emphasize the 3-h instantaneous precipitation rate for the time from 12 h before to 60 h after the time of maximum IVT magnitude as discussed in the text. Inset: 6-h values of IVT magnitude and direction for 1871–2012 (gray circles) and maximum IVT for landslide onset days (red circles) plotted in rotated polar coordinates similar to a wind rose such that IVT magnitude is indicated by the radial coordinate, the IVT direction is indicated by the angular coordinate rotated such that a westerly water vapor flux is on the left-most portion of the diagram. The IVT magnitude climatology is created using an 1871–2012 climatological mean value using a random sample Monte Carlo–type simulation with 1,000 iterations.

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    Composite analyses at time of maximum IVT magnitude of sea level pressure (hPa; gray contours), IWV (cm; shaded according to scale), and IVT vectors (plotted for magnitudes >150 kg m–1 s–1 and scaled according to reference vector) are shown for (a) all landslide onset days, (b) days associated with landfalling ARs, (c) days not associated with ARs, and (d)–(f) days associated ARs in Sep–Nov, Dec–Feb, and Mar–May, respectively.

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A 142-Year Climatology of Northern California Landslides and Atmospheric Rivers

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  • 1 Meteorology Program, Plymouth State University, Plymouth, New Hampshire
  • 2 U.S. Geological Survey, Menlo Park, California
  • 3 Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, and U.S. Geological Survey, Carson City, Nevada
  • 4 Meteorology Program, Plymouth State University, Plymouth, New Hampshire
  • 5 Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California
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Abstract

We compare a novel dataset of San Francisco Bay Area landslides from 1871 to 2012 to corresponding atmospheric conditions commonly associated with Pacific winter storms and landfalling atmospheric rivers (ARs). Landslides in the San Francisco Bay Area occur primarily during winter months, coinciding with enhanced integrated water vapor transport (IVT) magnitudes ≥250 kg m–1 s–1 at the coast 76% of the time and with landfalling ARs over the near-offshore northeast Pacific 82% of the time. Results illustrate that days, or the first in a series of days, with a landslide (i.e., landslide onset days) typically occur in association with NOAA Twentieth Century Reanalysis–derived IVT magnitudes ≥250 kg m–1 s–1 that persist for ∼20 h and temporal maxima in precipitation rates. Composite analyses of sea level pressure, integrated water vapor, and IVT during 3-month periods during September–May on landslide onset days further illustrate that these events coincide with regions of low pressure to the northwest of California and high pressure to the south, synoptic-scale flow conditions associated with strong onshore flow, and water vapor transports in the form of landfalling ARs.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Jason M. Cordeira, j_cordeira@plymouth.edu

Abstract

We compare a novel dataset of San Francisco Bay Area landslides from 1871 to 2012 to corresponding atmospheric conditions commonly associated with Pacific winter storms and landfalling atmospheric rivers (ARs). Landslides in the San Francisco Bay Area occur primarily during winter months, coinciding with enhanced integrated water vapor transport (IVT) magnitudes ≥250 kg m–1 s–1 at the coast 76% of the time and with landfalling ARs over the near-offshore northeast Pacific 82% of the time. Results illustrate that days, or the first in a series of days, with a landslide (i.e., landslide onset days) typically occur in association with NOAA Twentieth Century Reanalysis–derived IVT magnitudes ≥250 kg m–1 s–1 that persist for ∼20 h and temporal maxima in precipitation rates. Composite analyses of sea level pressure, integrated water vapor, and IVT during 3-month periods during September–May on landslide onset days further illustrate that these events coincide with regions of low pressure to the northwest of California and high pressure to the south, synoptic-scale flow conditions associated with strong onshore flow, and water vapor transports in the form of landfalling ARs.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Jason M. Cordeira, j_cordeira@plymouth.edu

San Francisco Bay Area landslide days predominantly occur during December–March in Sonoma, Marin, San Mateo, and Santa Cruz Counties, where 82% of these days coincide with landfalling atmospheric rivers.

Extreme precipitation events can have a large influence on ecosystems, agriculture, infrastruc- ture, and water resources that are particularly important to society. Costly effects from extreme precipitation events, depending on their location, intensity, and duration can be attributed to subsequent hazards such as flooding and landslides. For example, floods caused more loss of life and property damage than any other natural disaster in the United States between 1900 and 1999 (Easterling et al. 2000), and landslides cause an estimated 25–50 deaths and ∼$3.5 billion (2001 USD) in damages in the United States annually (Highland 2004). The U.S. West Coast region is particularly susceptible to extreme precipitation events (Ralph and Dettinger 2012; Lamjiri et al. 2017), subsequent flooding (Kelley 1998), and landslides (Highland 2004).

A majority of the annual precipitation (30%–50%) and extreme precipitation events (60%–100%) along the U.S. West Coast are attributed to landfalling atmospheric rivers (ARs) that accompany North Pacific winter storms (Ralph and Dettinger 2012; Lamjiri et al. 2017). ARs are typically characterized by water vapor flux from lower latitudes along enhanced corridors of integrated water vapor (IWV) and IWV transport (IVT) (American Meteorological Society 2017) that can result in orographic precipitation along coastal and inland mountain ranges (e.g., Neiman et al. 2008). As a result, 24-h precipitation amounts of >100–150 mm have 2-yr recurrence intervals in the mountainous areas of the California Coast Ranges (NOAA 2011). These North Pacific winter storms and their associated precipitation are therefore known to produce both shallow and deep-seated landslides given appropriate antecedent conditions (e.g., saturated soils and/or prior wildfire activity; see next section) that may lead to significant damages in heavily developed areas such as the San Francisco Bay Area (Ellen and Wieczorek 1988; Biasutti et al. 2016). A historical example of AR-associated landslides occurred during 3–5 January 1982 in conjunction with two landfalling ARs (Figs. 1a,b) that produced 400 mm (Marin County) to 600 mm (Santa Cruz County) of precipitation (NWS 1982). These ARs and their precipitation led to more than 18,000 landslides and debris flows, 25 landslide-related deaths, damage to thousands of homes, and damage to kilometers of transportation infrastructure throughout the San Francisco Bay Area (Fig. 1c; NWS 1982; Ellen and Wieczorek 1988). Given that ARs and their precipitation are known to produce individual shallow landslide events, the purpose of this study is to illustrate and quantify the extent to which landslides occurring in the San Francisco Bay Area have historically been associated with landfalling ARs using a novel 142-yr landslide dataset from 1871 to 2012.

Fig. 1.
Fig. 1.

(a),(b) Analyses of sea level pressure (hPa; gray contours with labeled storms L1 and L2), IWV (cm; shaded according to scale), and IVT vectors (plotted for magnitudes >150 kg m–1 s–1 and scaled according to reference vector) from the NOAA 20CR, and (c) annotated analysis by the USGS showing distribution of mapped debris flows and locations of deaths caused by landslides during 3–5 Jan 1982. Panel (c) provided by Fig. 2 of Ellen and Wieczorek (1988, p. 3).

Citation: Bulletin of the American Meteorological Society 100, 8; 10.1175/BAMS-D-18-0158.1

BACKGROUND ON LANDSLIDES.

This study focuses on shallow landslides associated with hillslope failures primarily involving soils that mobilize during or soon after a storm. A subset of these failures mobilize as debris flows, mixtures of soil, water, rock, and vegetation that flow down steepland valleys (e.g., Iverson 1997; Stock and Dietrich 2003). Historic shallow failures occur during or shortly after storms that contain hourly rainfall rates >5–10 mm h–1 (Campbell 1975; Wieczorek 1987; Campbell et al. 1998). In the California Coast Ranges, and perhaps elsewhere, even intense storms do not seem to trigger failures unless the soils are already moist from early season rain. Historic events indicate that seasonal antecedent rainfalls (i.e., rainfall totaled from 1 October onward) must exceed 250 mm (Nilsen and Turner 1975; Campbell 1975; Nilsen et al. 1976; Cannon and Ellen 1985; Wieczorek 1987; Wilson and Jayko 1997) before steepland soils are susceptible to shallow landsliding. Threshold rainfall rates and accumulations may be greatly lowered for locations influenced by wildfire activity and changes in soil and vegetative characteristics (Florsheim et al. 1991; Turner 1996; Cannon and Gartner 2005). Individual shallow landslide events and debris flows have been linked to North Pacific winter storms such as the aforementioned January 1982 storms and those occurring during winter 1997/98 (Coe et al. 2004). Recently, Young et al. (2017) identified that 89% (25 of 28) of the days with a debris flow report in the National Centers for Environmental Information Storm Events Database over Northern California during October–March in 2004–14 were associated with a landfalling AR at the coast on the day of or the day before the storm event report.

Some of the landslide reports in our catalog (see next section) may also include deep-seated landslides that involve both soil and underlying bedrock. Consequently, they exceed a depth of several meters and have a wide range of failure geometries and styles (Varnes 1954). Many deep-seated landslides appear to be long-lived, creeping episodically once rainfalls have brought sufficient free water to their failure plane to generate positive pore pressures (Reid 1994). Failure planes and the hydraulic conductivities of the layers above them vary over orders of magnitude. For this reason, there appear to be a range of rainfall totals that activate these failures; motion may happen days, weeks, or months after a large storm. A subset of large landslides seems to happen catastrophically during or shortly after large storms, and these kinds of failures are among the deadliest (Jibson 2005; Iverson et al. 2015).

CALIFORNIA LANDSLIDE DATASET.

Timing and locations of known California-wide landslides of both types described above between 1871 and 2012 were compiled by the second author from published reports from the U.S. Geological Survey (USGS; e.g., Nilsen et al. 1976), digitized newspaper records and photos (e.g., published in the San Francisco Chronicle or the San Francisco Call newspapers with print dates beginning in the late nineteenth century), and unpublished sources. Thus, it is important to note that this dataset likely only includes a small fraction of all possible landslides that have occurred over California since 1871. The dataset provides an opportunity to understand the impact of known landslides on California prior to published scientific studies on the topic in the 1970s. Each record includes the date, time of the event (if reported), location (or approximate location based on event details), and any text describing the failure or failures. The location description is used to associate a county with each event. To first order, this dataset was constructed using a similar methodology to the global landslide catalog by Kirschbaum et al. (2010) except for a longer period of record and a focus on California. Note that the reliance on newspaper reports prior to modern landslide mapping (e.g., Ellen et al. 1997) introduces strong biases. For instance, landslides that impacted infrastructure (e.g., railroads, roads, houses) are much more likely to appear in newspaper accounts and are therefore overrepresented in the dataset. The same effect means that populated areas like the San Francisco Bay Area are overrepresented in the dataset and form an ideal study population.

This study uses landslide events recorded between 1871 and 2012 in 10 San Francisco Bay Area counties: Marin, Sonoma, Napa, Solano, Contra Costa, Alameda, Santa Clara, Santa Cruz, San Mateo, and San Francisco. These counties contain 428 distinct landslide reports, occurring on 254 unique days across the region. Of these, 214 days represent an isolated day with a landslide report or the first day of a span of days with consecutive daily landslide reports. We call these “landslide onset days,” and we compare their occurrence to characteristics of ARs as discussed in the next section. Note that six landslide onset days occurred with a 1-day gap between events and are included in the subsequent analysis.

ANALYSIS METHODOLOGY.

Characteristics of ARs on landslide onset days are investigated from data provided by the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL)/Physical Sciences Division (PSD) Twentieth Century Reanalysis Project (20CRP) version 2c dataset (Compo et al. 2011). The 20CRP dataset contains 6-h meteorological data between 0000 UTC 1 January 1871 and 1800 UTC 31 January 2012 on 24 pressure levels (every 50 hPa between 1000 and 50 hPa, and 70, 30, 20, and 10 hPa), and 3-h meteorological data for select surface variables, on a 2° latitude × 2° longitude global grid. The analyses in this study are constructed from the 20CRP ensemble-mean gridded fields of sea level pressure (SLP), IWV (which is contained in the 20CRP as total column precipitable water), the IVT vector that is calculated following the methodology of Neiman et al. (2008), and 3-hourly instantaneous precipitation rates. Linkages between landslide onset days and ARs are determined using two characteristics of ARs specific to north coastal California. The first characteristic includes using a threshold IVT magnitude of 250 kg m–1 s–1 that is a common instantaneous threshold used by past studies to identify and forecast minimum “AR conditions” in this region as described by Rutz et al. (2014), Cordeira et al. (2017), and Ralph et al. (2019). Note that using this threshold may have obvious limitations, especially at times with ARs of marginal or uncertain intensity near the threshold chosen and with ARs of variable or uncertain locations. These uncertainties are derived from the relatively coarse grid spacing, ensemble-mean data, and innate uncertainty of the 20CRP dataset prior to the satellite era and for data derived from surface pressure observations (e.g., Compo et al. 2006). Some of these uncertainties are addressed by using a second characteristic that includes spatial analyses of SLP, IWV, and IVT in order to identify landfalling ARs (as already seen in Figs. 1a,b). This spatial identification of ARs is comparable to that performed by Neiman et al. (2008) using IWV only [see Rutz et al. (2014) for justification of using IVT over IWV]. The spatial analyses allow for a more subjective analysis of the long (e.g., >2,000 km), narrow (e.g., <1,000 km), and intense (e.g., IVT magnitude ≥250 kg m–1 s–1) characteristics of atmospheric water vapor flux commonly used to identify ARs using objective criteria.

Composite analyses are constructed for landslide onset days in a “time of maximum IVT” framework. This framework identifies the time of maximum IVT magnitude from the 20CRP at 38°N, 122°W (i.e., the grid point located slightly inland over the San Francisco Bay) from a 73-h period from two days prior to one day after the landslide onset day. For example, the methodology identified the time of maximum IVT magnitude between 0000 UTC 2 January and 0000 UTC 5 January 1982 for a landside report on 4 January 1982. The framework 1) allowed for flexibility and also specificity in linking the local calendar day associated with a landslide report to one of the 6-h UTC times associated with the 20CRP dataset, 2) yielded more coherent and less smeared composite analyses of atmospheric parameters, and 3) shifted the composite time of events on average ∼11.3 h earlier than just using 0000 UTC on the day of the landslide report.

RESULTS.

Landslide onset days (N = 214) occurred in 78 of the 142 (55%) water years studied. In those years, the number of landslide onset days ranged from 1 yr–1 to 8–10 yr–1, with 1890, 1952, 1973, and 2006 yielding the most (Fig. 2a). Landslide onset days occur primarily during the cool- and wet-season months between October and May, with a peak during January and February (Fig. 2b). The January–February peak in landslide onset days lags the December temporal peak in landfalling AR events identified by Rutz et al. (2014, see their Fig. 6). The highest spatial frequency of landslide onset days in the San Francisco Bay Area occurs along coastal and steepland regions of Sonoma, Marin, San Mateo, and Santa Cruz Counties (Fig. 2c). Additional analysis reveals that there is no correlation (correlation coefficient of –0.028) between the annual frequency of landslide onset days per year and December–February monthly mean values of the 20CRP El Niño–Southern Oscillation index (not shown; e.g., Ropelewski and Jones 1987; NOAA 2017). It is important to note, however, that trends in the annual frequency of landslides onset days, especially during the nineteenth and early twentieth centuries, cannot necessarily be analyzed due to the possibility of unknown remote landslide events that are not identified in the dataset.

Fig. 2.
Fig. 2.

Identified number of San Francisco Bay Area landslide onset days 1871–2012 (a) by water year, (b) by month with and without concurrence of IVT magnitudes ≥250 kg m–1 s–1 at 38°N, 122°W, and (c) by county per decade. Panel (c) created using Esri ArcMap 10.3.1 with county and state outlines obtained from the U.S. Census Bureau (www.census.gov/geo/maps-data/data/tiger-cart-boundary.html).

Citation: Bulletin of the American Meteorological Society 100, 8; 10.1175/BAMS-D-18-0158.1

Landslide onset days occur primarily during 8–10-day periods with enhanced IVT magnitudes relative to climatology (∼150 kg m–1 s–1 as compared to ∼50 kg m–1 s–1) at 38°N, 122°W (Fig. 3). The composite mean IVT magnitude increases from ∼150 to ∼386 kg m–1 s–1 in the 36 h leading up to the time of maximum IVT. The daily average IVT magnitude centered on the time of maximum IVT is ∼288 kg m–1 s–1. The total duration of the composite mean IVT magnitude ≥250 kg m–1 s–1 is 20.7 h, which is similar in duration to results presented by Rutz et al. (2014), who found an average AR duration using IVT magnitude ≥250 kg m–1 s–1 over north coastal California of ∼18–20 h (see their Fig. 7; Ralph et al. 2013). The time of maximum IVT magnitude coincides with the average time of maximum 3-h precipitation rates, which is enhanced with respect to the 10-day analysis for the 72-h period from ∼12 h before to ∼60 h after the time of maximum IVT magnitude. While these average precipitation rate values are relatively low in the time of maximum IVT framework [e.g., a composite mean rate of ∼3 mm (3 h)–1], they do represent precipitation rates in the 98.8th percentile of all 3-h precipitation rates and the 96.2th percentile of all nonzero 3-h precipitation rates at 38°N, 122°W derived from the relatively coarse-resolution 20CRP dataset from 1871 to 2012. The average of the maximum precipitation rates identified during each event for the period from 12 h before to 60 h after the time of maximum IVT magnitude was 4.75 mm (3 h)–1 and represents values in the 99.6th and 98.6th percentiles, respectively, as partitioned above.

Fig. 3.
Fig. 3.

Time-lagged composite mean time series of IVT magnitude (kg m–1 s–1 red line) and 3-h instantaneous precipitation rate [mm (3 h)–1; gray and green bars] relative to the time of maximum IVT magnitude for San Francisco Bay Area landslide onset days (N = 214) at 38°N, 122°W. The +1 and –1 standard deviation of the IVT magnitude (solid blue lines), climatology of mean IVT magnitude (solid black line), and IVT magnitude of 250 kg m–1 s–1 (dashed black line) are provided for reference. Green bars emphasize the 3-h instantaneous precipitation rate for the time from 12 h before to 60 h after the time of maximum IVT magnitude as discussed in the text. Inset: 6-h values of IVT magnitude and direction for 1871–2012 (gray circles) and maximum IVT for landslide onset days (red circles) plotted in rotated polar coordinates similar to a wind rose such that IVT magnitude is indicated by the radial coordinate, the IVT direction is indicated by the angular coordinate rotated such that a westerly water vapor flux is on the left-most portion of the diagram. The IVT magnitude climatology is created using an 1871–2012 climatological mean value using a random sample Monte Carlo–type simulation with 1,000 iterations.

Citation: Bulletin of the American Meteorological Society 100, 8; 10.1175/BAMS-D-18-0158.1

A large majority (163 of 214; 76%) of landslide onset days coincided with maximum IVT magnitudes ≥250 kg m–1 s–1 at 38°N, 122°W (Figs. 2b and 3). The fraction of landslide onset days that coincided with maximum IVT magnitudes ≥250 kg m–1 s–1 at 38°N, 122°W by month is between 73% and 83% during October–March, 67% in April, and 0% (0 of 2) in May (Fig. 2b). The composite mean IVT vector direction at 38°N, 122°W at the time of maximum IVT magnitude is west-southwest at ∼220°, with a majority (174 of 214; 81%) of IVT directions between 180° and 270° (Fig. 3, inset). The identified IVT characteristics (magnitude and direction) are common characteristics of water vapor transport associated with landfalling ARs in the San Francisco Bay Area as shown by Neiman et al. (2008).

Although composite mean IVT magnitudes over the San Francisco Bay Area on landslide onset days are 386 kg m–1 s–1, they occur at the terminus of an offshore composite mean corridor of maximum IVT magnitudes >500 kg m–1 s–1 and IWV values >2.6 cm that resembles an AR over the northeast Pacific (Fig. 4a). Consequently, 12 landslide onset days with maximum IVT magnitudes <250 kg m–1 s–1 at 38°N, 122°W contained maximum IVT magnitudes ≥250 kg m–1 s–1 at 36°N, 124°W (∼285 km upstream; not shown). This result motivated visual inspection of all 214 landslide onset days, of which 176 of 214 (82%) were found to contain spatial characteristics consistent with landfalling ARs (e.g., a corridor of IVT magnitude ≥250 kg m–1 s–1 with a length >2,000 km). Note that this analysis found both days with coastal IVT magnitudes ≥250 kg m–1 s–1 that were not associated with ARs offshore and days with coastal IVT magnitudes <250 kg m–1 s–1 that were associated with ARs offshore. As a result, this analysis found 82% of the identified landslide onset days to be associated with ARs even if the coastal IVT magnitudes did not necessarily exceed 250 kg m–1 s–1. This 82% fraction of events associated with ARs is similar in magnitude to the 89% of debris flow reports tallied across Northern California that occurred in association with a landfalling ARs located somewhere along the Northern California coastline studied by Young et al. (2017).

Fig. 4.
Fig. 4.

Composite analyses at time of maximum IVT magnitude of sea level pressure (hPa; gray contours), IWV (cm; shaded according to scale), and IVT vectors (plotted for magnitudes >150 kg m–1 s–1 and scaled according to reference vector) are shown for (a) all landslide onset days, (b) days associated with landfalling ARs, (c) days not associated with ARs, and (d)–(f) days associated ARs in Sep–Nov, Dec–Feb, and Mar–May, respectively.

Citation: Bulletin of the American Meteorological Society 100, 8; 10.1175/BAMS-D-18-0158.1

Composite analysis for the subset of landslide onset days associated with ARs offshore (N = 176) illustrates a prominent AR with a corridor of maximum IVT magnitudes of >500 kg m–1 s–1 and IWV values >2.6 cm located between a region of low pressure <996 hPa located west of Vancouver and British Columbia and a region of high pressure >1,016 hPa located over the subtropical northeast Pacific (Fig. 4b). Alternatively, those landslide onset days not associated with ARs (N = 38) occur in conjunction with IWV values >1.8 cm and IVT magnitudes <200 kg m–1 s–1 downstream of a region of high pressure >1,022 hPa over the northeast Pacific and in the wake of a region of low pressure <1,010 hPa over the Great Basin (Fig. 4c). While not associated with landfalling ARs, these landslide onset days appear to occur in a moist postfrontal environment where convective precipitation (i.e., thunderstorms) or shallow orographic precipitation may influence landslide occurrence.

December–February (DJF) landslide onset days associated with ARs (N = 127; Fig. 4e) comprise 72% of the total number of events and the composite patterns for this season resemble those for all landslide onset days associated with ARs (cf. Figs. 4b and 4e). September–November (SON) landslide onset days associated with ARs (N = 13; Fig. 4d) are fewer in number and occur in conjunction with a quasi-zonal water vapor pattern that contains IVT magnitudes of ∼600 kg m–1 s–1 and IWV >3.0 cm over the northeast Pacific, whereas March–May (MAM) landslide onset days associated with ARs (N = 36; Fig. 4f) occur in conjunction with an amplified water vapor pattern that contains IVT magnitudes of 350–400 kg m–1 s–1 and IWV values of 2.3–2.4 cm over the northeast Pacific. When the three 3-month seasons are considered, SON landslide onset days appear to occur in association with more amplified synoptic-scale flow patterns and more intense ARs as compared to DJF and MAM onset days; however, the low sample sizes of SON and MAM landslide onset days relative to the sample size of DJF landslide onset days challenge the integrity of this assertion with the available data.

A 72-h analysis of the time-integrated 3-hourly instantaneous precipitation rate from ∼12 h before to ∼60 h after the time of maximum IVT magnitude (i.e., a proxy for 72-h precipitation) for landslide onset days associated with landfalling ARs illustrates that SON, DJF, and MAM landslide onset days occur on average in association with 72-h precipitation totals of 52.5, 45.8, and 35.7 mm, respectively (not shown). Keeping the sample size in mind, these results may also suggest that on average more intense early-season landfalling ARs that result in higher precipitation totals may be needed to trigger a landslide as compared to less intense late-season landfalling ARs (e.g., Oakley et al. 2018). A similar time-integrated analysis from the start of the water year (1 October) to 12 h before the time of maximum IVT magnitude (i.e., a proxy for water-year-to-date precipitation) for all landslide onset days identified average antecedent precipitation totals of 265.3 mm (262.5 mm for those associated with ARs and 278.0 mm for those not associated with ARs). These values are comparable to earlier described estimates that establish a 250 mm minimum threshold for antecedent precipitation totals associated with historic shallow landslides. Further analysis related to precipitation and environmental hydrological conditions associated with landslides is beyond the scope of this study and is considered more in depth by Oakley et al. (2018).

DISCUSSION AND CONCLUSIONS.

We use a 142-yr record of San Francisco Bay Area landslides between 1871 and 2012 to illustrate a spatiotemporal relationship between 214 identified landslide onset days and the atmospheric conditions commonly associated with landfalling ARs. The onset of landslides in the San Francisco Bay Area occurs during winter with a peak in January and February and is particularly focused in coastal counties with steep topography across Sonoma, Marin, San Mateo, and Santa Cruz Counties. A majority (76%) of the identified landslide onset days occurred in association with strong atmospheric water vapor flux quantified by coastal IVT magnitudes ≥250 kg m–1 s–1 that persist for ∼20 h and intense precipitation characterized by precipitation rates above the 98th percentile with respect to climatology over the San Francisco Bay Area. Upon closer examination of all 214 landslide onset days, 82% of these days occurred in association with long and narrow corridors of enhanced IWV and IVT that are consistent with ARs over the near-offshore northeast Pacific. These results suggest that extreme precipitation associated with landfalling ARs precede or may trigger a large majority of landslides across the San Francisco Bay Area. The duration of enhanced IVT magnitudes, extreme precipitation rates with respect to climatology, and spatial patterns of IWV and IVT are all generally consistent with previous studies of hydrological extremes over California and their association with ARs. For example, landfalling ARs have been linked with ∼40%–75% of extreme wind and precipitation events over 40% of the world’s coastlines (Waliser and Guan 2017), 31%–65% of coastal western U.S. avalanche fatalities (Hatchett et al. 2017), ∼64% of high-impact hydrological events (i.e., floods, flash floods, or debris flows) over Northern California (Young et al. 2017), and 60%–90% of extreme precipitation events (Oakley et al. 2018) that may produce shallow landslides.

This study specifically provides insight into what fraction of known San Francisco Bay Area landslide onset days likely occurred in association with landfalling ARs and their associated synoptic-scale atmospheric processes from a relatively coarse reanalysis dataset with innate uncertainties (e.g., Compo et al. 2006). Given that the landslide dataset does not include all possible landslides, it is problematic to perform a complementary analysis that identifies those characteristics of ARs that produce landslides and those that do not for the 1871–2012 period from the 20CRP. With this caveat, the IVT data for the San Francisco Bay Area reveal possible landfalling ARs on 4,373 days with an instantaneous IVT magnitude ≥250 kg m–1 s–1 at any of the 6-h synoptic times and 1,854 days with a daily average IVT magnitude ≥250 kg m–1 s–1. These data suggest that a small fraction of possible AR days (4.9% and 11.5%, respectively) occurred on the same day as a known landslide onset day. In other words, relatively few ARs of all possible ARs produced the known landslides in this study.

Of those landfalling ARs that produced known landslides, many of these were likely all accompanied by mesoscale processes that promoted orographic precipitation (e.g., Lamjiri et al. 2017; Oakley et al. 2018) or may have been accompanied by narrow cold-frontal rainbands (Hobbs and Persson 1982; Oakley et al. 2017) that helped trigger the landslide or landslides in regions of complex terrain. In these cases, it is not necessarily the enhanced IVT (i.e., with a magnitude ≥250 kg m–1 s–1) and long duration of orographic precipitation associated with a landfalling AR that triggered the landslide, but rather the period of intense short-duration precipitation. These aforementioned processes are not resolvable by the 20CRP. This study also suggests that higher IVT magnitudes and more intense precipitation along landfalling ARs during SON may be required to produce an early-season landslide as compared to lower IVT magnitudes and less intense precipitation along landfalling ARs during DJF or MAM, with a noted limitation due to sample size. This result potentially underscores the role of antecedent soil moisture provided by season-to-date precipitation and also complements findings by Chen et al. (2018), who show that higher IVT magnitude thresholds in landfalling ARs are more predictive of extreme precipitation. The veracity of this particular result is ultimately contingent upon the complex relationship among the IVT vector, precipitation processes, and the location-dependent antecedent hydrometeorological conditions (e.g., soil moisture, terrain, antecedent wildfire activity). Future work is aimed at investigating forecasts and analyses of meso–synoptic-scale atmospheric processes and location-dependent hydrometeorological ingredients that might help differentiate between landfalling ARs that may trigger a landslide (or multiple landslides) and those that may not trigger a landslide. For example, landfalling ARs in this study could be categorized based on their maximum intensity and duration following the AR scale developed by Ralph et al. (2019) in order to determine whether those ARs categorized as “mostly hazardous, also beneficial” or “primarily hazardous” are more likely to trigger a landslide (or multiple landslides) as opposed to those categorized as “primarily beneficial” or “mostly beneficial, also hazardous” (see their Table 2 and their Fig. 4).

ACKNOWLEDGMENTS

Support for this project was provided by the State of California–Department of Water Resources Award 4600010378 and the U.S. Army Corps of Engineers Award W912HZ-15-2-0019, both as part of broader projects led by the University of California, San Diego, Scripps Institution of Oceanography’s Center for Western Weather and Water Extremes. The authors thank three anonymous reviewers for their feedback, which greatly improved the quality of this manuscript. Data used in this study can be obtained by contacting the second author (jstock@usgs.gov) and were manipulated through the methodologies mentioned in the fourth section of this paper. Support for the Twentieth Century Reanalysis Project version 2c dataset is provided by the U.S. Department of Energy, Office of Science Biological and Environmental Research, and by the National Oceanic and Atmospheric Administration Climate Program Office.

REFERENCES

  • American Meteorological Society, 2017: Atmospheric river. Glossary of Meteorology, http://glossary.ametsoc.org/wiki/Atmospheric_river.

  • Biasutti, M., R. Seager, and D. B. Kirschbaum, 2016: Landslides in West Coast metropolitan areas: The role of extreme weather events. Wea. Climate Extremes, 14, 6779, https://doi.org/10.1016/j.wace.2016.11.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Campbell, R. H., 1975: Soil slips, debris flows, and rainstorms in the Santa Monica Mountains and vicinity, Southern California. USGS Professional Paper 851, 51 pp., https://pubs.usgs.gov/pp/0851/report.pdf.

    • Crossref
    • Export Citation
  • Campbell, R. H., R. L. Bernknopf, and D. R. Soller, 1998: Mapping time-dependent changes in soil slip-debris flow probability. USGS Miscellaneous Investigations Series Map I-2586, https://doi.org/10.3133/i2586.

    • Crossref
    • Export Citation
  • Cannon, S. H., and S. Ellen, 1985: Rainfall conditions for abundant debris avalanches, San Francisco Bay, California. Calif. Geol., 38 (12), 267272.

    • Search Google Scholar
    • Export Citation
  • Cannon, S. H., and J. E. Gartner, 2005: Debris-flow hazard analysis. Debris-Flow Hazards and Related Phenomena, M. Jakob and O. Hungr, Eds. Springer, 363374.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, X., L. R. Leung, Y. Gao, Y. Liu, M. Wigmosta, and M. Richmond, 2018: Predictability of extreme precipitation in western U.S. watersheds based on atmospheric river occurrence, intensity, and duration. Geophys. Res. Lett., 45, 11 69311 701, https://doi.org/10.1029/2018GL079831.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coe, J. A., J. W. Godt, R. L. Baum, R. C. Bucknam, and J. A. Michael, 2004: Landslide susceptibility from topography in Guatemala, Landslides: Evaluation and Stabilization, Proceedings of the 9th International Symposium on Landslides, Rio de Janeiro, Brazil, June 28-July 2, 2004, W. A. Lacerda et al., Eds., A. A. Balkema, 69–78.

    • Search Google Scholar
    • Export Citation
  • Compo, G. P., J. S. Whitaker, and P. D. Sardeshmukh, 2006: Feasibility of a 100-year reanalysis using only surface pressure data. Bull. Amer. Meteor. Soc., 87, 175190, https://doi.org/10.1175/BAMS-87-2-175.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Compo, G. P., and Coauthors, 2011: The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc., 137, 128, https://doi.org/10.1002/qj.776.

  • Cordeira, J. M., F. M. Ralph, A. Martin, N. Gaggini, J. R. Spackman, P. J. Neiman, J. Rutz, and R. Pierce, 2017: Forecasting atmospheric rivers during CalWater 2015. Bull. Amer. Meteor. Soc., 98, 449459, https://doi.org/10.1175/BAMS-D-15-00245.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Easterling, D. R., G. A. Meehl, C. Parmesan, S. A. Changnon, T. R. Karl, and L. O. Mearns, 2000: Climate extremes: Observations, modeling, and impacts. Science, 289, 20682074, https://doi.org/10.1126/science.289.5487.2068.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ellen, S. D., and G. F. Wieczorek, 1988: Landslides, floods, and marine effects of the storm of January 3–5, 1982, in the San Francisco Bay Region, California. USGS Professional Paper 1434, 310 pp., https://pubs.usgs.gov/pp/1988/1434/pp1434.pdf.

    • Search Google Scholar
    • Export Citation
  • Ellen, S. D., R. K. Mark, G. F. Wieczorek, C. M. Wentworth, D. W. Ramsey, and T. E. May, 1997: Map showing principal debris-flow source areas in the San Francisco Bay region, California. USGS Open-File Rep. 97-745 E, 8 pp., https://doi.org/10.3133/ofr97745E.

    • Search Google Scholar
    • Export Citation
  • Florsheim, J. L., E. A. Keller, and D. W. Best, 1991: Fluvial sediment transport in response to moderate storm flows following chaparral wildfire, Ventura County, Southern California. Geol. Soc. Amer. Bull., 103, 504511, https://doi.org/10.1130/0016-7606(1991)103<0504:FSTIRT>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hatchett, B. J., S. Burak, J. J. Rutz, N. S. Oakley, E. H. Bair, and M. L. Kaplan, 2017: Avalanche fatalities during atmospheric river events in the western United States. J. Hydrometeor., 18, 13591374, https://doi.org/10.1175/JHM-D-16-0219.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Highland, L. M., 2004: Landslide types and processes. USGS Fact Sheet 2004-3072, 4 pp., https://doi.org/10.3133/fs20043072.

  • Hobbs, P. V., and P. O. G. Persson, 1982: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. Part V: the substructure of narrow cold-frontal rainbands. J. Atmos. Sci., 39, 280295, https://doi.org/10.1175/1520-0469(1982)039<0280:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Iverson, R. M., 1997: The physics of debris flows. Rev. Geophys., 35, 245296.

  • Iverson, R. M., and Coauthors, 2015: Landslide mobility and hazards: Implications of the 2014 Oso disaster. Earth Planet. Sci. Lett., 412, 197208, https://doi.org/10.1016/j.epsl.2014.12.020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jibson, R. W., 2005: Landslide hazards at La Conchita, California. USGS Open File Rep. 05-1067, 12 pp., https://pubs.usgs.gov/of/2005/1067/pdf/OF2005-1067.pdf.

    • Search Google Scholar
    • Export Citation
  • Kelley, R., 1998: Battling the Inland Sea: Floods, Public Policy, and the Sacramento Valley. University of California Press, 426 pp.

  • Kirschbaum, D. B., R. Adler, Y. Hong, S. Hill, and A. Lerner-Lam, 2010: A global landslide catalog for hazard applications: Methods, results, and limitation. Nat. Hazards, 52, 561575, https://doi.org/10.1007/s11069-009-9401-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamjiri, M. A., M. D. Dettinger, F. M. Ralph, and B. Guan, 2017: Hourly storm characteristics along the U.S. West Coast: Role of atmospheric rivers in extreme precipitation. Geophys. Res. Lett., 44, 70207028, https://doi.org/10.1002/2017GL074193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., F. M. Ralph, G. A. Wick, J. D. Lundquist, and M. D. Dettinger, 2008: 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. Hydrometeor., 9, 2247, https://doi.org/10.1175/2007JHM855.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nilsen, T. H., and B. L. Turner, 1975: Influence of rainfall and ancient landslide deposits on recent landslides (1950–71) in urban areas of Contra Costa County, California. USGS Bulletin 1388, 18 pp., https://doi.org/10.3133/b1388.

    • Search Google Scholar
    • Export Citation
  • Nilsen, T. H., F. A. Taylor, and E. E. Brabb, 1976: Recent landslides in Alameda County, California (1940–71): An estimate of economic losses and correlations with slope, rainfall, and ancient landslide depots. USGS Bulletin 1398, 21 pp., https://doi.org/10.3133/b1398.

    • Search Google Scholar
    • Export Citation
  • NOAA, 2011: California isopluvials of 2-year 24-hour precipitation in inches. NOAA Atlas 14, Vol. 6, Version 2, accessed 10 June 2018, ftp://hdsc.nws.noaa.gov/pub/hdsc/data/sw/ca2y24h.pdf.

    • Search Google Scholar
    • Export Citation
  • NOAA, 2017: 20CR climate indices: SOI. Accessed 10 July 2017, www.esrl.noaa.gov/psd/data/20thC_Rean/timeseries/monthly/SOI.

  • NWS, 1982: Report on the San Francisco Bay area storm January 3–5, 1982. Western Region Headquarters, National Weather Service, 39 pp., www.weather.gov/media/publications/assessments/San%20Francisco%20Bay%20Area%20Storm%20January%201982.pdf.

  • Oakley, N. S., J. T. Lancaster, M. L. Kaplan, and F. Martin Ralph, 2017: Synoptic conditions associated with cool-season post-fire debris flows in the Transverse Ranges of Southern California. Nat. Hazards, 88, 327354, https://doi.org/10.1007/s11069-017-2867-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oakley, N. S., J. T. Lancaster, B. J. Hatchett, J. Stock, F. M. Ralph, S. Roj, and S. Lukashov, 2018: A 22-year climatology of cool-season hourly precipitation thresholds conducive to shallow landslides in California. Earth Interact ., 22, https://doi.org/10.1175/EI-D-17-0029.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., and M. D. Dettinger, 2012: Historical and national perspectives on extreme west coast precipitation associated with atmospheric rivers during December 2010. Bull. Amer. Meteor. Soc., 93, 783790, https://doi.org/10.1175/BAMS-D-11-00188.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., P. J. Neiman, R. J. Zamora, and M. D. Dettinger, 2013: Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal in coastal Northern California. J. Hydrometeor., 14, 443459, https://doi.org/10.1175/JHM-D-12-076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., J. J. Rutz, J. M. Cordeira, M. Dettinger, M. Anderson, D. Reynolds, L. J. Schick, and C. Smallcomb, 2019: A scale to characterize the strength and impacts of atmospheric rivers. Bull. Amer. Meteor. Soc., 100, 269289, https://doi.org/10.1175/BAMS-D-18-0023.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reid, M., 1994: A pore-pressure diffusion model for estimating landslide-inducing rainfall. J. Geol., 102, 709717, https://doi.org/10.1086/629714.

  • Ropelewski, C. F., and P. D. Jones, 1987: Extension of the Tahiti–Darwin Southern Oscillation index. Mon. Wea. Rev., 115, 21612165, https://doi.org/10.1175/1520-0493(1987)115<2161:AEOTTS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rutz, J. J., W. J. Steenburgh, and F. M. Ralph, 2014: Climatological characteristics of atmospheric rivers and their inland penetration over the western United States. Mon. Wea. Rev., 142, 905921, https://doi.org/10.1175/MWR-D-13-00168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stock, J. D., and W. E. Dietrich, 2003: Valley incision by debris flows: Evidence of a topographic signature. Water Resour. Res., 39, 1089, https://doi.org/10.1029/2001WR001057.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Turner, A. K., 1996: Colluvium and Talus. Landslides: Investigation and Mitigation: Special Report 247, A. K. Turner and R. L. Schuster, Eds., National Academy of Sciences, 525555.

    • Search Google Scholar
    • Export Citation
  • Varnes, D. J., 1954: Landslide types and processes. Landslides and Engineering Practice: Special Report 28, E. B. Eckel, Eds., National Academy of Sciences, 2047.

    • Search Google Scholar
    • Export Citation
  • Waliser, D., and B. Guan, 2017: Extreme winds and precipitation during landfall of atmospheric rivers. Nat. Geosci., 10, 179183, https://doi.org/10.1038/ngeo2894.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wieczorek, G. F., 1987: Effect of rainfall intensity and duration on debris flows in central Santa Cruz Mountains, California. Debris Flows/Avalanches: Process, Recognition, and Mitigation, J. E. Costa and G. F. Wieczorek, Eds., Reviews in Engineering Geology, Vol. 7, Geological Society of America, 93104.

    • Search Google Scholar
    • Export Citation
  • Wilson, R. C., and A. S. Jayko, 1997: Preliminary maps showing rainfall thresholds for debris-flow activity, San Francisco Bay region, California. USGS Open-File Rep. 97-745 F, 20 pp., https://doi.org/10.3133/ofr97745F.

    • Search Google Scholar
    • Export Citation
  • Young, A. M., K. T Skelly, and J. M. Cordeira, 2017: High-impact hydrologic events and atmospheric rivers in California: An investigation using the NCEI storm events database. Geophys. Res. Lett., 44, 33933401, https://doi.org/10.1002/2017GL073077.

    • Crossref
    • Search Google Scholar
    • Export Citation
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