Midwinter Dry Spells Amplify Post‐Fire Snowpack Decline

Hatchett, Benjamin J.; Koshkin, Arielle L.; Guirguis, Kristen; Rittger, Karl; Nolin, A. W.; Heggli, Anne; Rhoades, Alan M.; East, Amy E.; Siirila‐Woodburn, Erica R.; Brandt, W. Tyler; Gershunov, Alexander; Haleakala, Kayden

doi:10.1029/2022gl101235

Cited by 13 publications

(16 citation statements)

References 82 publications

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“…There was also skill in forecasting the negative phase of the Offshore-California mode in week 3 during January and weeks 3-4 during February, which is associated with a ridge offshore from California. This persistent ridge during January-February was responsible for the extremely dry conditions that occurred in California and contributed to the continuation of the drought during WY2022 (Figure S5 in Supporting Information S1; Hatchett et al, 2023).…”

Section: Example Realtime Application From Wy2022mentioning

confidence: 99%

“…ARs cause most of the region's floods (Corringham et al., 2019; Dettinger, 2013; Ralph et al., 2006, 2011) while downslope winds are often associated with coastal heat waves as well as wildfire and smoke impacts (Abatzoglou, 2013; Aguilera et al., 2021; Cayan et al., 2022; Gershunov et al., 2021; Guzman‐Morales et al., 2016; Hughes & Hall, 2010). Winter heat waves and dry spells accelerate mountain snowmelt (Hatchett et al., 2023), exacerbate drought and endanger human health, particularly along the densely populated coast (Gershunov et al., 2021; Schwarz et al., 2020). Improved prediction of these impactful weather events is critical for emergency preparedness and planning to mitigate impacts to society (DeFlorio et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

“…

Winter heat waves and dry spells accelerate mountain snowmelt (Hatchett et al, 2023), exacerbate drought and endanger human health, particularly along the densely populated coast (Gershunov et al, 2021;Schwarz et al, 2020). Improved prediction of these impactful weather events is critical for emergency preparedness and planning to mitigate impacts to society (DeFlorio et al, 2021).

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confidence: 99%

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Subseasonal Prediction of Impactful California Winter Weather in a Hybrid Dynamical‐Statistical Framework

Guirguis,

Gershunov,

Hatchett

et al. 2023

Geophysical Research Letters

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Atmospheric rivers (ARs) and Santa Ana winds (SAWs) are impactful weather events for California communities. Emergency planning efforts and resource management would benefit from extending lead times of skillful prediction for these and other types of extreme weather patterns. Here we describe a methodology for subseasonal prediction of impactful winter weather in California, including ARs, SAWs and heat extremes. The hybrid approach combines dynamical model and historical information to forecast probabilities of impactful weather outcomes at weeks 1–4 lead. This methodology uses dynamical model information considered most reliable, that is, planetary/synoptic‐scale atmospheric circulation, filters for dynamical model error/uncertainty at longer lead times and increases the sample of likely outcomes by utilizing the full historical record instead of a more limited suite of dynamical forecast model ensemble members. We demonstrate skill above climatology at subseasonal timescales, highlighting potential for use in water, health, land, and fire management decision support.

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Section: Example Realtime Application From Wy2022mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Subseasonal Prediction of Impactful California Winter Weather in a Hybrid Dynamical‐Statistical Framework

Guirguis,

Gershunov,

Hatchett

et al. 2023

Geophysical Research Letters

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“…Regional April 1 snowpacks may accumulate and persist as low as 750 m asl (E. Sproles et al., 2013). These snowpacks vary semi‐independently both from those in Washington (Cayan, 1996; Hatchett, Koshkin, et al., 2022; Mote et al., 2018) and also south of the Pacific dipole transition zone located between 40 and 42°N in northern California (Wise, 2010). Oregon Cascade snowpack dynamics are also influenced by internal large‐scale ocean‐atmosphere climate modes, as well as forced (external) mechanisms including anthropogenically‐driven warming (Barnett et al., 2008; Pierce et al., 2008).…”

Section: Introductionmentioning

confidence: 99%

The Severity of the 2014–2015 Snow Drought in the Oregon Cascades in a Multicentury Context

Dye

Coulthard

Hatchett

et al. 2023

Water Resources Research

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The western United States (US) is a global snow drought hotspot (Huning & AghaKouchak, 2020b), and has experienced significant mountain snowpack declines (∼15%-30%) since the mid-1900s (Mote et al., 2018. In particular, the Cascade Range (Cascades) in the US Pacific Northwest (PNW) has undergone the most dramatic declines during the instrumental era (Mote et al., 2005(Mote et al., , 2018, with the largest climate sensitivities and reduced snowpack predictability (Livneh & Badger, 2020). Oregon has sustained the greatest reductions (Mote, 2003;Mote et al., 2005) and contains approximately half of "at-risk" Cascades snow (Nolin & Daly, 2006). Analysis of observational data sets dating to the mid-20th century suggest a 16% loss in Cascades snowpack independent of internal variability from 1930 to 2007 (Stoelinga et al., 2010).Oregon Cascade snowpacks act as natural reservoirs for water supply that are slowly released in the spring and summer months when demand is highest (Barnett et al., 2005;Siirila-Woodburn et al., 2021). Located adjacent to the state's largest human population centers, they supply up to 75% of annual societal, economic, agriculture, and ecosystem water demands (United States Department of Agriculture, Natural Resources Conservation Service, 2022). The potential impacts of snow drought (Harpold et al., 2017) in Oregon were brought into sharp focus during the 2014-2015 snow drought event (spanning the 2014 and 2015 water years) when near-average winter precipitation was accompanied by exceptionally warm temperatures, resulting in precipitation primarily falling as rain rather than snow (a "warm snow drought") (

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“…We did not analyze these areas so as to avoid conflating changes in snow RF with changes in land cover. However, the fSCA, snow albedo, and snow duration data have separately been analyzed for a few small fires in California which identified snow susceptibility from melt with both decreased snow albedo and canopy cover (shading) resulting in 50% less snow cover in 2022 and 50 fewer snow cover days compared to 2013, a year with similar snow accumulation(Hatchett et al 2023). In addition to forests, we also masked out glaciated areas due to challenges with discerning RF by particulates over bare ice with MODIS retrievals.…”

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confidence: 99%

Spatio-temporal patterns and trends in MODIS-retrieved radiative forcing by snow impurities over the Western US from 2001 to 2022

Jensen,

Rittger,

Raleigh

2024

Environ. Res.: Climate

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The seasonal mountain snowpack of the western U.S. (WUS) is a key water resource to millions of people and an important component of the regional climate system. Impurities at the snow surface can affect snowmelt timing and rate through snow radiative forcing (RF), resulting in earlier streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning whether snow RF has changed over recent decades. Here we analyzed the relative magnitude and spatio-temporal variability of snow RF across the WUS at three spatial scales (pixel, watershed, regional) using remotely sensed RF from spatially and temporally complete (STC) MODIS data sets (STC-MODSCAG/MODDRFS) from 2001-2022. To quantify snow RF impacts, we calculated a pixel-integrated metric over each snowmelt season (March 1st - June 30th) in all 22 years. We tested for long-term trend significance with the Mann-Kendall test and trend magnitude with Theil-Sen's slope. Mean snow RF was highest in the Upper Colorado region, but notable in less-studied regions, including the Great Basin and Pacific Northwest. Watersheds with high snow RF also tended to have high spatial and temporal variability in RF, and these tended to be near arid regions. Snow RF trends were largely absent; only a small percent of mountain ecoregions (0.03-8%) had significant trends, and these were typically decreasing trends. All mountain ecoregions exhibited a net decline in snow RF. While the spatial extent of significant RF trends was minimal, we found declining trends most frequently in the Sierra Nevada, North Cascades, and Canadian Rockies, and increasing trends in the Idaho Batholith. This study establishes a two-decade chronology of snow impurities in the WUS, helping inform where and when RF impacts on snowmelt may need to be considered in hydrologic models and regional hydroclimate studies.

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Midwinter Dry Spells Amplify Post‐Fire Snowpack Decline

Abstract: Communities and ecosystems worldwide rely on snowpacks to meet water demands (Immerzeel et al., 2020). A warming climate changes the spatial patterns and timing of snowpack accumulation and melt by altering rain-snow partitioning, decreasing cold content and extending dry spell length (

Cited by 13 publications

References 82 publications

Subseasonal Prediction of Impactful California Winter Weather in a Hybrid Dynamical‐Statistical Framework

Subseasonal Prediction of Impactful California Winter Weather in a Hybrid Dynamical‐Statistical Framework

The Severity of the 2014–2015 Snow Drought in the Oregon Cascades in a Multicentury Context

Spatio-temporal patterns and trends in MODIS-retrieved radiative forcing by snow impurities over the Western US from 2001 to 2022

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