Assessing reservoir operations risk under climate change

Risk-based planning offers a robust way to identify strategies that permit adaptive water resources management under climate change. This paper presents a flexible methodology for conducting climate change risk assessments involving reservoir operations. Decision makers can apply this methodology to their systems by selecting future periods and risk metrics relevant to their planning questions and by collectively evaluating system impacts relative to an ensemble of climate projection scenarios (weighted or not). This paper shows multiple applications of this methodology in a case study involving California\u27s Central Valley Project and State Water Project systems. Multiple applications were conducted to show how choices made in conducting the risk assessment, choices known as analytical design decisions, can affect assessed risk. Specifically, risk was reanalyzed for every choice combination of two design decisions: (1) whether to assume climate change will influence flood-control constraints on water supply operations (and how), and (2) whether to weight climate change scenarios (and how). Results show that assessed risk would motivate different planning pathways depending on decision-maker attitudes toward risk (e.g., risk neutral versus risk averse). Results also show that assessed risk at a given risk attitude is sensitive to the analytical design choices listed above, with the choice of whether to adjust flood-control rules under climate change having considerably more influence than the choice on whether to weight climate scenarios

Precipitation in a warming world: Assessing projected hydro-climate changes in California and other Mediterranean climate regions.

In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California's more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events

Climate change and the Delta, San Francisco Estuary and Watershed Science

Anthropogenic climate change amounts to a rapidly approaching, “new” stressor in the Sacramento–San Joaquin Delta system. In response to California’s extreme natural hydroclimatic variability, complex water-management systems have been developed, even as the Delta’s natural ecosystems have been largely devastated. Climate change is projected to challenge these management and ecological systems in different ways that are characterized by different levels of uncertainty. For example, there is high certainty that climate will warm by about 2°C more (than late-20th-century averages) by mid-century and about 4°C by end of century, if greenhouse-gas emissions continue their current rates of acceleration. Future precipitation changes are much less certain, with as many climate models projecting wetter conditions as drier. However, the same projections agree that precipitation will be more intense when storms do arrive, even as more dry days will separate storms. Warmer temperatures will likely enhance evaporative demands and raise water temperatures. Consequently, climate change is projected to yield both more extreme flood risks and greater drought risks. Sea level rise (SLR) during the 20th century was about 22cm, and is projected to increase by at least 3-fold this century. SLR together with land subsidence threatens the Delta with greater vulnerabilities to inundation and salinity intrusion. Effects on the Delta ecosystem that are traceable to warming include SLR, reduced snowpack, earlier snowmelt and larger storm-driven streamflows, warmer and longer summers, warmer summer water temperatures, and water-quality changes. These changes and their uncertainties will challenge the operations of water projects and uses throughout the Delta’s watershed and delivery areas. Although the effects of climate change on Delta ecosystems may be profound, the end results are difficult to predict, except that native species will fare worse than invaders. Successful preparation for the coming changes will require greater integration of monitoring, modeling, and decision making across time, variables, and space than has been historically normal

Climate change scenarios for the California region

To investigate possible future climate changes in California, a set of climate change model simulations was selected and evaluated. From the IPCC Fourth Assessment, simulations of twenty-first century climates under a B1 (low emissions) and an A2 (a medium-high emissions) emissions scenarios were evaluated, along with occasional comparisons to the A1fi (high emissions) scenario. The climate models whose simulations were the focus of the present study were from the Parallel Climate Model (PCM1) from NCAR and DOE, and the NOAA Geophysical Fluid Dynamics Laboratory CM2.1 model (GFDL). These emission scenarios and attendant climate simulations are not “predictions,” but rather are a purposely diverse set of examples from among the many plausible climate sequences that might affect California in the next century. Temperatures over California warm significantly during the twenty-first century in each simulation, with end-of-century temperature increases from approximately +1.5°C under the lower emissions B1 scenario in the less responsive PCM1 to +4.5°C in the higher emissions A2 scenario within the more responsive GFDL model. Three of the simulations (all except the B1 scenario in PCM1) exhibit more warming in summer than in winter. In all of the simulations, most precipitation continues to occur in winter. Relatively small (less than ~10%) changes in overall precipitation are projected. The California landscape is complex and requires that model information be parsed out onto finer scales than GCMs presently offer. When downscaled to its mountainous terrain, warming has a profound influence on California snow accumulations, with snow losses that increase with warming. Consequently, snow losses are most severe in projections by the more responsive model in response to the highest emissions

An Enhanced Archive Facilitating Climate Impacts and Adaptation Analysis

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 hydrologi- cal 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)

Precipitation regime change in Western North America: The role of Atmospheric Rivers.

Daily precipitation in California has been projected to become less frequent even as precipitation extremes intensify, leading to uncertainty in the overall response to climate warming. Precipitation extremes are historically associated with Atmospheric Rivers (ARs). Sixteen global climate models are evaluated for realism in modeled historical AR behavior and contribution of the resulting daily precipitation to annual total precipitation over Western North America. The five most realistic models display consistent changes in future AR behavior, constraining the spread of the full ensemble. They, moreover, project increasing year-to-year variability of total annual precipitation, particularly over California, where change in total annual precipitation is not projected with confidence. Focusing on three representative river basins along the West Coast, we show that, while the decrease in precipitation frequency is mostly due to non-AR events, the increase in heavy and extreme precipitation is almost entirely due to ARs. This research demonstrates that examining meteorological causes of precipitation regime change can lead to better and more nuanced understanding of climate projections. It highlights the critical role of future changes in ARs to Western water resources, especially over California

Hydrologic Scales, Cloud Variability, Remote Sensing, and Models: Implications for Forecasting Snowmelt and Streamflow

Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameter-izations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%–20 % reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencie

Downscaling With Constructed Analogues: Daily Precipitation and Temperature Fields Over The United States

Daily precipitation and average temperature patterns for the contiguous United States were downscaled from a 2.5 x 2.5 degree (coarse) resolution grid to a 1/8 x 1/8 degree (fine) resolution grid using a constructed‐analogues method. Choice of predictors, and the selection of subsets of most‐suitable historical dates to be included in the constructed analogues proved to be important determinants of the method’s skill, especially for precipitation. The downscaling method skillfully reproduces daily variations of precipitation and average temperature anomalies, as well as seasonal cycles, across the contiguous United States. The method tends to overestimate the number of wet days, producing a very light “drizzle” on many of the effectively dry days. There are also biases in the monthly climatologies of precipitation and average temperature in some regions, which tend to average out at annual timescales. Averaging daily downscaled patterns into monthly means yielded even more skillful results, capturing about 55 percent of the variations of monthly precipitation anomalies and about 80 percent of the variations of average temperature monthly anomalies across the contiguous United States. The choice of the domain of the predictor also influences the skill. For example, in California, the most skillful precipitation downscaling was obtained when the precipitation predictors covered the state, whereas average temperature downscaling was most skillful when average temperature predictors included continent‐wide patterns. Overall, the method showed encouraging results for downscaling daily precipitation and average temperature continentalwide patterns in North America—in particular, those of the western United States.California Energy Commission, PIER Energy ‐ Related Environmental Research/[CEC‐500‐2007‐123]//Estados UnidosCalifornia Energy Commission///Estados UnidosUnited States Department of Energy///Estados UnidosU.S. Geological Survey’s Priority Ecosystems Science//USGS/Estados UnidosUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI