Observing, Measuring, and Assessing the Consequences of Snow Drought

Abstract

Warmer and shorter winters from climate change will reduce snowpacks in most seasonally snow-covered regions of the world, with consequences for freshwater availability in spring and summer when people and ecosystems demand water most. Recent record low snowpacks, such as those in the winters of 2013/14 and 2014/15 in the Western United States, have led to a surge in research on ‘snow droughts,’ which are pointed to as harbingers of global warming that pose significant societal hazards. Yet despite the importance of understanding snow droughts to best prepare for their attendant impacts, the concept remains amorphous, with no agreed-upon definition of what they are, how best to measure them, and how such snow droughts connect to warm-season impacts. These knowledge gaps limit our understanding of the risks posed by snow droughts in the present and future, and thus our preparedness for their differential impacts on freshwater resources. To address these issues, we compile a hemispheric ensemble of in situ, satellite, and reanalysis snowpack datasets. We use this ensemble to evaluate the scientific challenges and uncertainties arising from differences in defining and measuring snow droughts, and identify opportunities to leverage this information to better understand the significance of snow droughts. We show that a clearer quantification of what constitutes a snow drought, including its uncertainties, improves our ability to anticipate costly and disruptive warm-season droughts, which is vital for informing risk management and adaptation to changing snow regimes.

National attribution of historical climate damages

“…We similarly average precipitation from Global Precipitation Climatology Centre (Schneider et al, 2011) and UDel at a 0.5°-by-0.5° resolution. We average multiple datasets to reduce observational uncertainty associated with any single gridded data product, as ensembles of datasets have been shown to outperform individual datasets (Gottlieb & Mankin, 2021). However, we note that we find very similar regression results using each individual data product, so this choice does not substantially affect our results (Supplementary Fig.…”

Changes in China's Snow Droughts Characteristics From 1993 to 2019

“…In addition, due to complex topographical heterogeneity, the current understanding and capacity to diagnose and predict the hydrological and ecological consequences of snow droughts are still poor (Gottlieb & Mankin, 2021;…”

“…Furthermore, using a Standardized Snow Melt and Rain Index, Staudinger et al (2014) effectively accounted for the influence of snow droughts in seven Swiss catchments. However, current snowpack metrics still face important bottlenecks to accurately estimate snow droughts (Dierauer et al, 2019;Gottlieb & Mankin, 2021;Staudinger et al, 2014). For example, point-in-time measurements in snowpacks, such as 1 April SWE (considered closest to the maximum accumulation of snowpack) or peak SWE, have been widely used to analyze the entire process of snow droughts around the world, retrospectively.…”

Persistent effect of El Niño on global economic growth

“…We use observational climate data from multiple sources: Monthly mean sea surface temperatures (SST) averaged across the ERSST (48) and HadISST (49) datasets, monthly mean atmospheric temperatures averaged across the Berkeley Earth (50), University of Delaware (51), and 20 th Century Reanalysis (52) datasets, and monthly total precipitation data from the Global Precipitation Climatology Center (53). These datasets are averaged together to reduce observational uncertainty from any one gridded data product (54)(55)(56). Temperature and precipitation are aggregated to population-weighted country-level means using year-2000 population data from the Gridded Population of the World (57).…”