Andrea J. Ray

Water supply risk on the Colorado River: Can management mitigate?

[1] Population growth and a changing climate will tax the future reliability of the Colorado River water supply. Using a heuristic model, we assess the annual risk to the Colorado River water supply for 2008―2057. Projected demand growth superimposed upon historical climate variability results in only a small probability of annual reservoir depletion through 2057. In contrast, a scenario of 20% reduction in the annual Colorado River flow due to climate change by 2057 results in a near tenfold increase in the probability of annual reservoir depletion by 2057. However, our analysis suggests that flexibility in current management practices could mitigate some of the increased risk due to climate change― induced reductions in flows.

Applications of Monsoon Research: Opportunities to Inform Decision Making and Reduce Regional Vulnerability

Abstract This article presents ongoing efforts to understand interactions between the North American monsoon and society in order to develop applications for monsoon research in a highly complex, multicultural, and binational region. The North American monsoon is an annual precipitation regime that begins in early June in Mexico and progresses northward to the southwestern United States. The region includes stakeholders in large urban complexes, productive agricultural areas, and sparsely populated arid and semiarid ecosystems. The political, cultural, and socioeconomic divisions between the United States and Mexico create a broad range of sensitivities to climate variability as well as capacities to use forecasts and other information to cope with climate. This paper highlights methodologies to link climate science with society and to analyze opportunities for monsoon science to benefit society in four sectors: natural hazards management, agriculture, public health, and water management. A list of stakeh...

The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

Suppose you are a city planner, regional water manager, or wildlife conservation specialist who is asked to include the potential impacts of climate variability and change in your risk management and planning efforts. What climate information would you use? The choice is often regional or local climate projections downscaled from global climate models (GCMs; also known as general circulation models) to include detail at spatial and temporal scales that align with those of the decision problem. A few years ago this information was hard to come by. Now there is Web-based access to a proliferation of high-resolution climate projections derived with differing downscaling methods.

Future climate: projected average

Global climate models (GCMs) are the fundamental drivers of regional climate-change projections (IPCC 2007). GCMs allow us to characterize changes in atmospheric circulation associated with human causes at global and continental scales. However, because of the planetary scope of the GCMs, their resolution, or level of detail, is somewhat coarse. A typical GCM grid spacing is about 62 miles (100 km) or greater, which is inadequate for creating projections and evaluating impacts of climate change at a regional scale. Thus, a “downscaling” procedure is needed to provide finer spatial detail of the model results.

Hydroclimate Variability and Change in the Prairie Pothole Region, the "Duck Factory" of North America

AbstractThe Prairie Pothole Region (PPR) of the northern Great Plains is a vital ecosystem responsible each year for producing 50%–80% of new recruits to the North American duck population. Climate variability and change can impact the hydrology and ecology of the region with implications for waterfowl populations. The historical relationship between PPR wetlands, duck populations, and seasonal hydroclimate are explored. Model experiments from phase 5 of the Coupled Model Intercomparison Project are used to determine whether a recent wetting trend is due to natural variability or changing climate and how PPR hydroclimate will change into the future. Year-to-year variations in May duck populations, pond numbers, and the Palmer drought severity index are well correlated over past decades. Pond and duck numbers tend to increase in spring following La Nina events, but the correlation is not strong. Model simulations suggest that the strengthening of the precipitation gradient across the PPR over the past cent...

Future Climate: Projected Extremes

Extreme events can be defined in many ways. Typical definitions of weather and climate extremes consider either the maximum value during a specified time interval (such as season or year) or exceedance of a threshold (the “peaks-over-threshold” [POT] approach), in which universal rather than local thresholds are frequently applied. For example, temperatures above 95°F (35°C) are often considered extreme in most locations across the United States, except in areas such as the low-lying deserts of Arizona and California, where such temperatures are typical in the summer. Temperatures at these levels are obviously extreme for living organisms from a non-adapted, physiological perspective, and technological adaptation for humans is required for day-to-day functioning in such temperatures. But such temperatures are not necessarily extreme from the statistical or local climate perspectives. In statistics, extremes are considered low-probability events that differ greatly from typical occurrences. The IPCC defines extremes as 1% to 10% of the largest or smallest values of a distribution (Trenberth et al. 2007). Studies over large or complex regions marked by significant climatic variation require definitions that are relevant to local climate. Across the Southwest, location-specific definitions of extreme temperature, precipitation, humidity, and wind are required if a meaningful region-wide perspective is desired.

Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

Abstract Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross‐validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland‐dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross‐validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross‐validation results were correlated with extrapolation results, the use of cross‐validation performance metrics to guide modeling choices where knowledge is limited was supported.

Advancing Science and Services during the 2015-16 El Niño: The NOAA El Niño Rapid Response Field Campaign

AbstractForecasts by mid-2015 for a strong El Nino during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climat...

Understanding the Dominant Sources and Tracks of Moisture for Summer Rainfall in the Southwest United States

We investigated the moisture sources and tracks that enable summer rainfall over the four-state southwestern U.S. region of Arizona, New Mexico, Colorado, and Utah by employing a high-resolution Lagrangian particle tracking model. Six locations were selected—Cedar City (Utah), Grand Junction (Colorado), Eastonville (Colorado), Laveen (Arizona), Redrock (New Mexico), and Melrose (New Mexico) —together, they represent six spatial regions of summer precipitation for the Southwest. Moisture tracks were generated for all the rainy days at these stations for the historical period 1979–2013. Tracks were generated for a 3-day period ending with the day of rainfall, which were then used to identify the source of moisture, pathway or trajectory, and the modulation along the track. The four major sources of moisture—Gulf of California, Gulf of Mexico (GoM), land, and the Pacific Ocean—were identified as responsible for summer rainfall over southwestern United States. The two dominant moisture sources at Laveen, Cedar City, Redrock, Grand Junction, and Eastonville were Gulf of California and land; at Melrose GoM and land were the dominant sources. The leading source of moisture at each location contributed to most of the extreme rainfall events. Tracks from GoM traveled the fastest and those from land sources were the slowest. Large-scale circulation features–pressure, convergence, and specific humidity–were consistent with the moisture tracks and were found to be strong throughout the 3-day period. This detailed and comprehensive generation of rainfall tracks offers unique insights into the moisture source and delivery for summer rainfall over southwestern United States.

Regional Climate Response Collaboratives: Multi-institutional Support for Climate Resilience

AbstractFederal investments by U.S. agencies to enhance climate resilience at regional scales grew over the past decade (2010s). To maximize efficiency and effectiveness in serving multiple sectors and scales, it has become critical to leverage existing agency-specific research, infrastructure, and capacity while avoiding redundancy. We discuss lessons learned from a multi-institutional “regional climate response collaborative” that comprises three different federally-supported climate service entities in the Rocky Mountain west and northern plains region. These lessons include leveraging different strengths of each partner, creating deliberate mechanisms to increase cross-entity communication and joint ownership of projects, and placing a common priority on stakeholder-relevant research and outcomes. We share the conditions that fostered successful collaboration, which can be transferred elsewhere, and suggest mechanisms for overcoming potential barriers. Synergies are essential for producing actionable ...