232 research outputs found
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Cloudiness over the Mountains of the Western United States: Variability and Influences on Snowmelt and Streamflow
No full textThis dissertation demonstrates the uses of satellite and surface observations, in tandem with hydrologic modeling, to characterize daily-to-interannual cloudiness variability and its influence on spring-summer snowmelt and streamflow fluctuations over the mountains of the western United States from 1996 to 2015. Daily cloudiness variations can exceed 50% of long-term averages during the springtime. When aggregated over three-month periods, cloudiness varies by ±10% of long-term averages in many locations. Rotated empirical orthogonal functions (REOFs) analysis indicates the first five REOFs account for ~67% of the total variance, each of which has distinct regional and seasonal emphases. Each of the REOF modes associates with anomalous large scale atmospheric circulation patterns and one or more large-scale teleconnection indices, which helps to explain why anomalous cloudiness patterns take on regional spatial scales and contain substantial variability over seasonal time scales.Cloud cover indices (CC) are, to some extent, related linearly to snowmelt (ΔSWE) and snow-fed streamflow (ΔQ) fluctuations. Local CC-ΔSWE and CC-ΔQ associations vary with time and location, with the dominance of negative correlations between CC and ΔSWE, exemplifying the cloud-shading (or clear-sky) effect on snowmelt. The magnitude of CC-ΔSWE association (R2) amounts to 5%-56%, typically peaking in May. These associations fade earlier in summer during dry years than wet years, indicating the differing responses of higher vs. lower snowpack. The CC-ΔQ association displays less consistent arrangement, with R2 amounting to 2%-47%. The ΔSWE and ΔQ fluctuations exhibit spatially extensive patterns of correlations with daily CC anomalies, indicating the effects of cloudiness often operate over regional scales.On a watershed scale, cloudiness variability redistributes the seasonal runoff and hastens the spring onset by 1-3 days. Higher elevation cloudiness exerts a greater influence on the basin runoff than lower elevation cloudiness does. Overall, cloudiness delays spring onset by 2-15 days regardless of the elevation. Lastly, the experiment on the intensification of cloudiness fluctuations suggests greater streamflow sensitivity to the “relatively cloudy periods get cloudier” scheme than to the “relatively clear periods get clearer” scheme, with the former producing 3-5 days later spring onsets
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Wildfires, Floods, and Climate Variability
No full textThe first chapter surveys fire and fuels managers at local, regional, and national levels. Survey results in the form of fire managers’ decision calendars show how climate information needs vary seasonally, over space, and through the organizational network. The study identifies opportunities to use climate information in fire management, including seasonal to inter-annual climate forecasts at all organizational levels, to improve the targeting of fuels treatments and prescribed burns, the positioning and movement of initial attack resources, and staffing and budgeting decisions.The second chapter analyzes National Flood Insurance Program (NFIP) data to quantify the economic impacts of flooding across the western United States from 1978 to 2007. The study compares National Flood Insurance Program data to National Weather Service measures of total damages, and presents a spatial and temporal analysis of daily claims and loss data over this period. The NFIP data reveals that a small number winter-season extreme hydrologic events, covering wide spatial areas, are responsible for a large proportion of total losses. In coastal southern California and across the southwest, El Niño conditions have had a strong effect in producing more frequent and higher magnitudes of insured losses while La Niña conditions significantly reduce both the frequency and magnitude losses. In the Pacific Northwest, the opposite pattern appears, though the effect is somewhat weaker, and less spatially coherent.The third chapter quantifies the economic impacts of flooding due to atmospheric river (AR) events in the western United States from 1978 to 2007, using NFIP claims and loss data. The study confirms that AR-related flood events cause significant economic damages and form the primary source of insurance claims and insured flood losses in the western coastal states. It provides spatial and temporal characterizations of damages as a function of integrated vapor transport (IVT) and antecedent hydrologic conditions.As the magnitude and frequency of wildfire and flood events change in response to anthropogenic climate change, and as economic and demographic contributions to vulnerability increase over time, public policy must adapt to respond. The results in these papers may be used to inform policies to mitigate losses and respond to future disaster scenarios, and may be of interest to policy makers and applied climate researchers alike
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Empirical approaches for near-term climate predictions
No full textClimate variations on seasonal to decadal time scales can have enormous social, economical and environmental impacts. As such, the ability to make skilful and reliable climate predictions at these time scales offers many benefits for climate preparedness, adaptation and resilience. In the recent years, major progress has been made in the development of such predictions with the advent of simulations with global climate models that are initialized from the current climate state. However, many challenges remain including an understanding of the underlying physical mechanisms for skilful predictions and whether such predictions could be improved. The purpose of this thesis is to establish new benchmarks for seasonal to decadal predictions in diverse components of the climate system and to provide some pieces of evidence that help to understand what are the drivers for these predictable patterns. Specifically, we use a suite of empirical models to perform predictions of oceanic and atmospheric variables together with initialized climate predictions to: 1. Understand the contribution of remote and local factors to the predictability of North and Tropical Pacific Oceans Sea Surface Temperature and Land Surface Temperature over Western North America; 2. Provide a higher baseline level skill for the state-of-art global prediction systems, from seasonal to decadal time scales; 3. Explore possible sources of errors in the global climate model simulations using statistical predictive models.First, we isolate contributions to the forecast skill from different spatial and time scales in the Pacific Ocean using a Liner Inverse Modelling (LIM) approach, showing the importance of temporal scale interactions in improving the predictions on decadal time scales. Specifically, we show that the Extratropical North Pacific is a source of predictability for the tropics on seasonal to interannual time scales, while the tropics enhance the forecast skill for the decadal component. We then show that the skill for an empirically-built LIM is comparable to and sometimes better than that from two state-of-art global prediction systems, from seasonal to decadal timescales and for several regions around the globe. These results indicate that the evolution of the system in those areas may not be not fully driven by unpredictable dynamics and that there may be some room for improvement in the dynamical models predictions, given that a low-dimensional linear model is able to generate better skill than the fully-coupled nonlinear model. Bearing that in mind, we use the LIM linear feedback matrix to explore possible sources of errors in the dynamical model simulations and we find that some of the simulated atmospheric and oceanic local and remote feedbacks differ in several key regions from that obtained with observations. These results may indicate sources of error in the dynamical models and therefore in its prediction skill that merit focused attention.We then investigate the role of remote and local predictors in seasonal predictors of minimum and maximum air temperatures over the Western North America, using a Canonical Correlation Analysis approach. We show that remote predictors, in the form of Pacific climate modes, provide the best predictive skill for temperature over land, particularly during wintertime. Lastly, considering that persistence is the widely-used measure when evaluating the predictive skill for dynamical models, we suggest the use of CCA as a much higher benchmark for seasonal predictions of land surface air temperatures
A method for prediction of California summer air surface temperature
No full textWhile significant progress has been made in seasonal climate prediction in recent years, summertime mid-latitude climate prediction remains problematic [e.g., Gershunov and Cayan, 2003]. Several previous studies have explored the skill of Pacific Sea Surface Temperatures (PSST) in the seasonal prediction of various atmospheric variables [e.g., Barnett and Preisendorfer, 1987],but few have focused on the value of PSST in forecasting summer conditions [e.g., Douville, 2003]. Advances in summertime temperature forecasts are important for planning in different economic sectors, such as the energy industry. This issue is especially important in California, where the summer peak energy demand is about 50% higher than that in winter, in response to heavy loads from air conditioners, pumping water, and other seasonal issues.Oceanic and Atmospheric Research/[NOAA/NA17RJ1231]/OAR-NOAA/Estados UnidosCalifornia Energy Commission/[]//Estados UnidosUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Físic
Drought and the California Delta—A Matter of Extremes
No full textdoi: http://dx.doi.org/10.15447/sfews.2014v12iss2art4<An abstract is not required for an essay.> --SFEWS editors</p
"Cool" vs. "warm" winter precipitation and its effect on streamflow in California
No full textPrecipitation is a difficult variable to understand and predict. In this study, monthly precipitation in California is divided into two classes according to the monthly temperature to better diagnose the atmospheric circulation that causes precipitation, and to illustrate how temperature compounds the precipitation to runoff process
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Climate variability and snow pack in the Sierra Nevada
No full textAn important part of the water supply in California and the western United States is derived from runoff fed by mountain snow melt. Snow accumulation responds to both precipitation and temperature variations, and forms an interesting climatic index, since it integrates these influences over the entire late fall-spring period. The study area includes the Sierra Nevada, which accumulates most of the snow pack and comprises a major portion of the water-bearing region of California. The purpose of this study is to shed light upon the link between climate and year-to-year variability in the snow pack. Specifically, we wanted to determine (a) the dependence of snow pack and streamflow upon natural climate variability, and (b) if the relationships linking snow and streamflow to climate variations are stable over the history of instrumental records by using pre-1948 historical records to test the results from 1948-present. The basis of the study will be several long series of historical observations containing observed variability over daily-toseasonal time scales. Our focus is on measurements on/around April 1, when snow accumulation is typically greatest. The primary data is from a network of mountainous snow courses; many have records of six decades or more. For any given year, the spring snow water equivalent (SWE) anomaly at a particular snow course is likely to be 25-60% of its long-term average. Although effects vary with region and with elevation, in general, the anomalous winter precipitation has the strongest influence on spring SWE fluctuations. Anomalous temperature has a weaker effect overall, but it has great influence in lower elevations such as in the coastal Northwest, and during spring in higher elevations. Patterns of the precipitation, temperature, and snow anomalies extend over broad regional areas, much larger than individual watersheds. These surface anomalies are organized by the atmospheric circulation, with primary anomaly centers over the North Pacific Ocean as well as over western North America. For most of the regions, anomalously low SWE is associated with a winter circulation resembling the PNA pattern. With a strong low in the central North Pacific and high pressure over the Pacific Northwest, this pattern diverts North Pacific storms northward, away from the region. Both warm and cool phases of ENSO tend to produce regional patterns with out-of-phase SWE anomalies in the Northwest and the Southwest
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The Influence of Climate Variations on Long Period Fluctuations in California Streamflow: July 1988 - June 1990
No full textThere is considerable seasonal-to-interannual variability in the flow of major watersheds in the Sierra Nevadas. This study examines that variability in terms of seasonal average surface weather variables, including atmospheric circulation, temperature, precipitation, and snow.Of particular importance is an apparent decline in spring-early summer runoff from the Sierra Nevadas first pointed out by M. Roos of the California Department of Water Resources. While measured October-September (water year) and April-July (AMJJ) runoff have increased, the AMJ J / annual fractional runoff has decreased by approximately 10% over the 80+ years of record.Further inspection shows that many streams in the West have a significant decline in spring-early summer fractional runoff as seen from a network of river gauging stations from Alaska south to Arizona and from California east to the Rockies. The cause of the trends at these stations is complex, involving both precipitation and temperature. For many basins the fractional spring-early summer runoff is affected by climatic behavior across all the seasons. In the Sierra, the decreased AMJJ fraction appears to have been produced by increased precipitation in the late summer, fall, and winter with decreased precipitation in spring. In addition, temperature along the West Coast has increased during the non-summer seasons, enhancing earlier runoff, and possibly evapotranspiration in spring.Other combinations of temperature and precipitation were involved in fractional runoff trends in other regions. Reversals in temperature and precipitation trends in remote regions over the eastern part of North America suggest that much of these changes were produced by shifts in the long wave patterns of atmospheric circulation, perhaps discounting a greenhouse effect scenario.Additional studies partially funded by this grant involve the influence of large scale atmospheric features usually emanating from the North Pacific Ocean during winter. These winter atmospheric patterns have strong connections to fluctuations in streamflow in watersheds in California and elsewhere in western North America
Planning for Climate Change on Top of Already High Climate Variability
No full textThe State of Climate Action Planning in Californi
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