scholarly journals Pattern-based downscaling of snowpack variability in the western United States

2021 ◽  
Author(s):  
Nicolas Gauthier ◽  
Kevin J. Anchukaitis ◽  
Bethany Coulthard

AbstractThe decline in snowpack across the western United States is one of the most pressing threats posed by climate change to regional economies and livelihoods. Earth system models are important tools for exploring past and future snowpack variability, yet their coarse spatial resolutions distort local topography and bias spatial patterns of accumulation and ablation. Here, we explore pattern-based statistical downscaling for spatially-continuous interannual snowpack estimates. We find that a few leading patterns capture the majority of snowpack variability across the western US in observations, reanalyses, and free-running simulations. Pattern-based downscaling methods yield accurate, high resolution maps that correct mean and variance biases in domain-wide simulated snowpack. Methods that use large-scale patterns as both predictors and predictands perform better than those that do not and all are superior to an interpolation-based “delta change” approach. These findings suggest that pattern-based methods are appropriate for downscaling interannual snowpack variability and that using physically meaningful large-scale patterns is more important than the details of any particular downscaling method.

2017 ◽  
Vol 18 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Edwin Sumargo ◽  
Daniel R. Cayan

Abstract This study investigates the spatial and temporal variability of cloudiness across mountain zones in the western United States. Daily average cloud albedo is derived from a 19-yr series (1996–2014) of half-hourly Geostationary Operational Environmental Satellite (GOES) images. During springtime when incident radiation is active in driving snowmelt–runoff processes, the magnitude of daily cloud variations can exceed 50% of long-term averages. Even when aggregated over 3-month periods, cloud albedo varies by ±10% of long-term averages in many locations. Rotated empirical orthogonal functions (REOFs) of daily cloud albedo anomalies over high-elevation regions of the western conterminous United States identify distinct regional patterns, wherein the first five REOFs account for ~67% of the total variance. REOF1 is centered over Northern California and Oregon and is pronounced between November and March. REOF2 is centered over the interior northwest and is accentuated between March and July. Each of the REOF/rotated principal components (RPC) modes associates with anomalous large-scale atmospheric circulation patterns and one or more large-scale teleconnection indices (Arctic Oscillation, Niño-3.4, and Pacific–North American), which helps to explain why anomalous cloudiness patterns take on regional spatial scales and contain substantial variability over seasonal time scales.


2014 ◽  
Vol 23 (2) ◽  
pp. 143-148 ◽  
Author(s):  
J. Daniel Oppenheimer ◽  
Stacy K. Beaugh ◽  
Julie A. Knudson ◽  
Peter Mueller ◽  
Nikki Grant-Hoffman ◽  
...  

2009 ◽  
Vol 24 (6) ◽  
pp. 1625-1643 ◽  
Author(s):  
Heather Dawn Reeves ◽  
David J. Stensrud

Abstract Valley cold pools (VCPs), which are trapped, cold layers of air at the bottoms of basins or valleys, pose a significant problem for forecasters because they can lead to several forms of difficult-to-forecast and hazardous weather such as fog, freezing rain, or poor air quality. Numerical models have historically failed to routinely provide accurate guidance on the formation and demise of VCPs, making the forecast problem more challenging. In some case studies of persistent wintertime VCPs, there is a connection between the movement of upper-level waves and the timing of VCP formation and decay. Herein, a 3-yr climatology of persistent wintertime VCPs for five valleys and basins in the western United States is performed to see how often VCP formation and decay coincides with synoptic-scale (∼200–2000 km) wave motions. Valley cold pools are found to form most frequently as an upper-level ridge approaches the western United States and in response to strong midlevel warming. The VCPs usually last as long as the ridge is over the area and usually only end when a trough, and its associated midlevel cooling, move over the western United States. In fact, VCP strength appears to be almost entirely dictated by midlevel temperature changes, which suggests large-scale forcing is dominant for this type of VCP most of the time.


2011 ◽  
Vol 20 (8) ◽  
pp. 982 ◽  
Author(s):  
Mary Ellen Miller ◽  
Lee H. MacDonald ◽  
Peter R. Robichaud ◽  
William J. Elliot

Many forests and their associated water resources are at increasing risk from large and severe wildfires due to high fuel accumulations and climate change. Extensive fuel treatments are being proposed, but it is not clear where such treatments should be focussed. The goals of this project were to: (1) predict potential post-fire erosion rates for forests and shrublands in the western United States to help prioritise fuel treatments; and (2) assess model sensitivity and accuracy. Post-fire ground cover was predicted using historical fire weather data and the First Order Fire Effects Model. Parameter files from the Disturbed Water Erosion Prediction Project (WEPP) were combined with GeoWEPP to predict post-fire erosion at the hillslope scale. Predicted median annual erosion rates were 0.1–2 Mg ha–1 year–1 for most of the intermountain west, ~10–40 Mg ha–1 year–1 for wetter areas along the Pacific Coast and up to 100 Mg ha–1 year–1 for north-western California. Sensitivity analyses showed the predicted erosion rates were predominantly controlled by the amount of precipitation rather than surface cover. The limited validation dataset showed a reasonable correlation between predicted and measured erosion rates (R2 = 0.61), although predictions were much less than measured values. Our results demonstrate the feasibility of predicting post-fire erosion rates on a large scale. The validation and sensitivity analysis indicated that the predictions are most useful for prioritising fuel reduction treatments on a local rather than interregional scale, and they also helped identify model improvements and research needs.


2020 ◽  
Author(s):  
Christopher A. Halsch ◽  
Aimee Code ◽  
Sarah M. Hoyle ◽  
James A. Fordyce ◽  
Nicolas Baert ◽  
...  

AbstractMonarch butterflies (Danaus plexippus) are in decline in the western United States and are encountering a range of anthropogenic stressors. Pesticides are among the factors that likely contribute to this decline, though the concentrations of these chemicals in non-crop plants is not well documented, especially in complex landscapes with a diversity of crop types and land uses. In this study, we collected 227 milkweed (Asclepias spp.) leaf samples from 19 sites representing different land use types across the Central Valley of California. We also sampled plants purchased from two stores that sell to home gardeners. We found 64 pesticides (25 insecticides, 27 fungicides, and 11 herbicides, as well as 1 adjuvant) out of a possible 262 in our screen. Pesticides were detected in every sample, even at sites with little or no pesticide use based on information from landowners. On average, approximately 9 compounds were detected per plant across all sites, with a range of 1 to 25 compounds in any one sample. For the vast majority of pesticides detected, we do not know the biological effects on monarch caterpillars that consume these plants, however we did detect a few compounds for which effects on monarchs have been experimentally investigated. Chlorantraniliprole in particular was identified in 91% of our samples and found to exceed a tested LD50 for monarchs in 58 out of 227 samples. Our primary conclusion is the ubiquity of pesticide presence in milkweeds in an early-summer window of time that monarch larvae are likely to be present in the area. Thus, these results are consistent with the hypothesis that pesticide exposure could be a contributing factor to monarch declines in the western United States. This both highlights the need for a greater understanding of the lethal and sublethal effects of these compounds (individually, additively, and synergistically) and suggests the urgent need for strategies that reduce pesticide use and movement on the landscape.Contribution to the FieldInsects are facing multifaceted stressors in the Anthropocene and are in decline in many parts of the world. The widespread use of pesticides is believed to be an important part of the problem. In particular, the monarch butterfly is in sharp decline in the western United States. Here we show that milkweeds in the Central Valley of California, a large urban and agricultural landscape that is part of the monarch breeding and migration route, are contaminated with a diverse array of pesticides. We found a few in high concentrations and many in trace amounts. We do not know how these compounds act together and with other large-scale stressors to cause declines, but it is clear that monarchs and other non-target insects are encountering these pesticides. These results provide critical insight into the growing literature on the impact of pesticides on butterflies specifically and non-target insects more broadly. We hope these field realistic concentrations will aid in the design of further experiments in the field and the lab.


2021 ◽  
Author(s):  
Abby C. Lute ◽  
John Abatzoglou ◽  
Timothy Link

Abstract. Seasonal snowpack dynamics shape the biophysical and societal characteristics of many global regions. However, snowpack accumulation and duration have generally declined in recent decades largely due to anthropogenic climate change. Mechanistic understanding of snowpack spatiotemporal heterogeneity and climate change impacts will benefit from snow data products that are based on physical principles, that are simulated at high spatial resolution, and that cover large geographic domains. Existing datasets do not meet these requirements, hindering our ability to understand both contemporary and changing snow regimes and to develop adaptation strategies in regions where snowpack patterns and processes are important components of Earth systems. We developed a computationally efficient physics-based snow model, SnowClim, that can be run in the cloud. The model was evaluated and calibrated at Snowpack Telemetry sites across the western United States (US), achieving a site-median root mean square error for daily snow water equivalent of 62 mm, bias in peak snow water equivalent of −9.6 mm, and bias in snow duration of 1.2 days when run hourly. Positive biases were found at sites with mean winter temperature above freezing where the estimation of precipitation phase is prone to errors. The model was applied to the western US using newly developed forcing data created by statistically downscaling pre-industrial, historical, and pseudo-global warming climate data from the Weather Research and Forecasting (WRF) model. The resulting product is the SnowClim dataset, a suite of summary climate and snow metrics for the western US at 210 m spatial resolution (Lute et al., 2021). The physical basis, large extent, and high spatial resolution of this dataset will enable novel analyses of changing hydroclimate and its implications for natural and human systems.


2016 ◽  
Vol 25 (2) ◽  
pp. 182 ◽  
Author(s):  
Sean A. Parks ◽  
Carol Miller ◽  
Lisa M. Holsinger ◽  
L. Scott Baggett ◽  
Benjamin J. Bird

Several aspects of wildland fire are moderated by site- and landscape-level vegetation changes caused by previous fire, thereby creating a dynamic where one fire exerts a regulatory control on subsequent fire. For example, wildland fire has been shown to regulate the size and severity of subsequent fire. However, wildland fire has the potential to influence other properties of subsequent fire. One of those properties – the extent to which a previous wildland fire inhibits new fires from igniting and spreading within its perimeter – is the focus of our study. In four large wilderness study areas in the western United States (US), we evaluated whether or not wildland fire regulated the ignition and spread (hereafter occurrence) of subsequent fire. Results clearly indicate that wildland fire indeed regulates subsequent occurrence of fires ≥ 20 ha in all study areas. We also evaluated the longevity of the regulating effect and found that wildland fire limits subsequent fire occurrence for nine years in the warm/dry study area in the south-western US and over 20 years in the cooler/wetter study areas in the northern Rocky Mountains. Our findings expand upon our understanding of the regulating capacity of wildland fire and the importance of wildland fire in creating and maintaining resilience to future fire events.


Sign in / Sign up

Export Citation Format

Share Document