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Rick, TC, Sillett TS, Ghalambor CK, Hofman CA, Ralls K, Anderson RS, Boser CL, Braje TJ, Cayan DR, Chesser RT, Collins PW, Erlandson JM, Faulkner KR, Fleischer R, Funk WC, Galipeau R, Huston A, King J, Laughrin L, Maldonado J, McEachern K, Muhs DR, Newsome SD, Reeder-Myers L, Still C, Morrison SA.  2014.  Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene. Bioscience. 64:680-692.   10.1093/biosci/biu094   AbstractWebsite

Historical ecology is becoming an important focus in conservation biology and offers a promising tool to help guide ecosystem management. Here, we integrate data from multiple disciplines to illuminate the past, present, and future of biodiversity on California's Channel Islands, an archipelago that has undergone a wide range of land-use and ecological changes. Our analysis spans approximately 20,000 years, from before human occupation and through Native American hunter-gatherers, commercial ranchers and fishers, the US military, and other land managers. We demonstrate how long-term, interdisciplinary research provides insight into conservation decisions, such as setting ecosystem restoration goals, preserving rare and endemic taxa, and reducing the impacts of climate change on natural and cultural resources. We illustrate the importance of historical perspectives for understanding modern patterns and ecological change and present an approach that can be applied generally in conservation management planning.

Corringham, TW, Cayan DR.  2019.  The effect of El Nino on flood damages in the western United States. Weather Climate and Society. 11:489-504.   10.1175/wcas-d-18-0071.1   AbstractWebsite

This paper quantifies insured flood losses across the western United States from 1978 to 2017, presenting a spatiotemporal analysis of National Flood Insurance Program (NFIP) daily claims and losses over this period. While considerably lower (only 3.3%) than broader measures of direct damages measured by a National Weather Service (NWS) dataset, NFIP insured losses are highly correlated to the annual damages in the NWS dataset, and the NFIP data provide flood impacts at a fine degree of spatial resolution. The NFIP data reveal that 1% of extreme events, covering wide spatial areas, caused over 66% of total insured losses. Connections between extreme events and El Nino-Southern Oscillation (ENSO) that have been documented in past research are borne out in the insurance data. In coastal Southern California and across the Southwest, El Nino conditions have had a strong effect in producing more frequent and higher magnitudes of insured losses, while La Nina conditions significantly reduce both the frequency and magnitude of losses. In the Pacific Northwest, the opposite pattern appears, although the effect is weaker and less spatially coherent. The persistent evolution of ENSO offers the possibility for property owners, policy makers, and emergency planners and responders that unusually high or low flood damages could be predicted in advance of the primary winter storm period along the West Coast. Within the 40-yr NFIP history, it is found that the multivariate ENSO index would have provided an 8-month look-ahead for heightened damages in Southern California.

Cayan, DR, Webb RH.  1992.  El Nino Southern Oscillation and streamflow in the Western United States. El Nino: historical and paleoclimatic aspects of the southern oscillation. ( Diaz HF, Markgraf V, Eds.).:29-68., Cambridge [England]; New York, NY, USA: Cambridge University Press Abstract
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Knowles, N, Cayan DR.  2004.  Elevational dependence of projected hydrologic changes in the San Francisco Estuary and watershed. Climatic Change. 62:319-336.   10.1023/B:CLIM.0000013696.14308.b9   AbstractWebsite

California's primary hydrologic system, the San Francisco Estuary and its upstream watershed, is vulnerable to the regional hydrologic consequences of projected global climate change. Previous work has shown that a projected warming would result in a reduction of snowpack storage leading to higher winter and lower spring-summer streamflows and increased spring-summer salinities in the estuary. The present work shows that these hydrologic changes exhibit a strong dependence on elevation, with the greatest loss of snowpack volume in the 1300 - 2700 m elevation range. Exploiting hydrologic and estuarine modeling capabilities to trace water as it moves through the system reveals that the shift of water in mid-elevations of the Sacramento river basin from snowmelt to rainfall runoff is the dominant cause of projected changes in estuarine inflows and salinity. Additionally, although spring-summer losses of estuarine inflows are balanced by winter gains, the losses have a stronger influence on salinity since longer spring-summer residence times allow the inflow changes to accumulate in the estuary. The changes in inflows sourced in the Sacramento River basin in approximately the 1300 - 2200 m elevation range thereby lead to a net increase in estuarine salinity under the projected warming. Such changes would impact ecosystems throughout the watershed and threaten to contaminate much of California's freshwater supply.

Hayhoe, K, Cayan D, Field CB, Frumhoff PC, Maurer EP, Miller NL, Moser SC, Schneider SH, Cahill KN, Cleland EE, Dale L, Drapek R, Hanemann RM, Kalkstein LS, Lenihan J, Lunch CK, Neilson RP, Sheridan SC, Verville JH.  2004.  Emissions pathways, climate change, and impacts on California. Proceedings of the National Academy of Sciences of the United States of America. 101:12422-12427.   10.1073/pnas.0404500101   AbstractWebsite

The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.

Maurer, EP, Brekke L, Pruitt T, Thrasher B, Long J, Duffy P, Dettinger M, Cayan D, Arnold J.  2014.  An enhanced archive facilitating climate impacts and adaptation analysis. Bulletin of the American Meteorological Society. 95:1011-+.   10.1175/bams-d-13-00126.1   AbstractWebsite

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrological variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_cmip_projections).

Cayan, DR, Redmond KT, Riddle LG.  1999.  ENSO and hydrologic extremes in the western United States. Journal of Climate. 12:2881-2893.   10.1175/1520-0442(1999)012<2881:eaheit>2.0.co;2   AbstractWebsite

Frequency distributions of daily precipitation in winter and daily stream flow from late winter to early summer, at several hundred sites in the western United States, exhibit strong and systematic responses to the two phases of ENSO. Most of the stream flows considered are driven by snowmelt. The Southern Oscillation index (SOI) is used as the ENSO phase indicator. Both modest (median) and larger (90th percentile) events were considered. In years with negative SOI values (El Nino), days with high daily precipitation and stream flow are more frequent than average over the Southwest and less frequent over the Northwest. During years with positive SOI values (La Nino), a nearly opposite pattern is seen. A more pronounced increase is seen in the number of days exceeding climatological 90th percentile values than in the number exceeding climatological 50th percentile values, for both precipitation and stream flow. Stream flow responses to ENSO extremes are accentuated over precipitation responses. Evidence suggests that the mechanism for this amplification involves ENSO-phase differences in the persistence and duration of wet episodes, affecting the efficiency of the process by which precipitation is converted to runoff. The SOI leads the precipitation events by several months,and hydrologic lags (mostly through snowmelt) delay the stream flow response by several more months. The combined 6-12-month predictive aspect of this relationship should be of significant benefit in responding to flood (or drought) risk and in improving overall water management in the western states.

Maurer, EP, Das T, Cayan DR.  2013.  Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction. Hydrology and Earth System Sciences. 17:2147-2159.   10.5194/hess-17-2147-2013   AbstractWebsite

When correcting for biases in general circulation model (GCM) output, for example when statistically down-scaling for regional and local impacts studies, a common assumption is that the GCM biases can be characterized by comparing model simulations and observations for a historical period. We demonstrate some complications in this assumption, with GCM biases varying between mean and extreme values and for different sets of historical years. Daily precipitation and maximum and minimum temperature from late 20th century simulations by four GCMs over the United States were compared to gridded observations. Using random years from the historical record we select a "base" set and a 10 yr independent "projected" set. We compare differences in biases between these sets at median and extreme percentiles. On average a base set with as few as 4 randomly-selected years is often adequate to characterize the biases in daily GCM precipitation and temperature, at both median and extreme values; 12 yr provided higher confidence that bias correction would be successful. This suggests that some of the GCM bias is time invariant. When characterizing bias with a set of consecutive years, the set must be long enough to accommodate regional low frequency variability, since the bias also exhibits this variability. Newer climate models included in the Intergovernmental Panel on Climate Change fifth assessment will allow extending this study for a longer observational period and to finer scales.