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101.
102.
This paper examines whether experience of extreme weather events—such as excessive heat, droughts, flooding, and hurricanes—increases an individual’s level concern about climate change. We bring together micro-level geospatial data on extreme weather events from NOAA’s Storm Events Database with public opinion data from multiple years of the Cooperative Congressional Election Study to study this question. We find evidence of a modest, but discernible positive relationship between experiencing extreme weather activity and expressions of concern about climate change. However, the effect only materializes for recent extreme weather activity; activity that occurred over longer periods of time does not affect public opinion. These results are generally robust to various measurement strategies and model specifications. Our findings contribute to the public opinion literature on the importance of local environmental conditions on attitude formation. 相似文献
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Charles L. Curry Bárbara Tencer Kirien Whan Andrew J. Weaver Michel Giguère Edward Wiebe 《大气与海洋》2016,54(4):364-384
We evaluate the capacity of a regional climate model to represent observed extreme temperature and precipitation events and also examine the impact of increased resolution, in an effort to identify added value in this respect. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA-40) for the period 1973–1995. The simulations were evaluated using the spline-interpolated dataset ANUSPLIN, a daily observational gridded surface temperature and precipitation product with a nominal resolution of approximately 10?km. We examine a range of climate extremes, comprising the 10th and 90th percentiles of daily maximum (TX) and minimum (TN) temperatures, the 90th percentile of daily precipitation (PR90), and the 27 core Climate Daily Extremes (CLIMDEX) indices.Both simulations exhibit cold biases compared with observations over WCan, with the bias exacerbated at higher resolution, suggesting little added value for temperature overall. There are instances, however, of regional improvement in the spatial pattern of temperature extremes at the higher resolution of CRCM15 (e.g., the CLIMDEX index for the annual number of days when TX?>?25°C). The high-resolution simulations also reveal similarly localized features in precipitation (e.g., rain shadows) that are not resolved at the 45?km resolution. With regard to precipitation extremes, although both simulations generally display wet biases, CRCM15 features a reduced bias in PR90 in all seasons except winter. This improvement occurs despite the fact that spatial and interannual variability of PR90 in CRCM15 is significantly overestimated relative to both CRCM45 and ANUSPLIN. We posit that these characteristics are the result of demonstrable differences between corresponding topographical datasets used in the gridded observations and CRCM, the resulting errors propagated to physical variables tied to elevation and the beneficial effect of subsequent spatial averaging. Because topographical input is often discordant between simulations and gridded observations, it is argued that a limited form of spatial averaging may contribute added value beyond that which has already been noted in previous studies with respect to small-scale climate variability. 相似文献
106.
US wilderness search and rescue consumes thousands of person‐hours and millions of dollars annually. Timeliness is critical: the probability of success decreases substantially after 24 hours. Although over 90% of searches are quickly resolved by standard “reflex” tasks, the remainder require and reward intensive planning. Planning begins with a probability map showing where the lost person is likely to be found. The MapScore project described here provides a way to evaluate probability maps using actual historical searches. In this work we generated probability maps the Euclidean distance tables in (Koester 2008 ), and using Doke's ( 2012 ) watershed model. Watershed boundaries follow high terrain and may better reflect actual barriers to travel. We also created a third model using the joint distribution using Euclidean and watershed features. On a metric where random maps score 0 and perfect maps score 1, the Euclidean distance model scored 0.78 (95%CI: 0.74–0.82, on 376 cases). The simple watershed model by itself was clearly inferior at 0.61, but the Combined model was slightly better at 0.81 (95%CI: 0.77–0.84). 相似文献
107.
Anomalies found when apportioning responsibility for streamflow depletion are examined. The anomalies arise when responsibility is assigned to the two states that contribute to depletion of Beaver Creek in the Republican River Basin in the United States. The apportioning procedure for this basin presumes that the sum of streamflow depletions, computed by comparing simulation model runs with and without groundwater pumping from individual states, approximates the streamflow depletion when both states are pumping. In the case study presented here, this presumed superposition fails dramatically. The stream drying and aquifer-storage depletion, as represented in the simulation model used for allocation, are examined in detail to understand the hydrologic and numerical basis for the severe nonlinear response. Users of apportioning procedures that rely on superposition should be aware of the presence and likely magnitude of nonlinear responses in modeling tools. 相似文献
108.
Pascale?A.?L.?GoertlerEmail author Charles?A.?Simenstad Daniel?L.?Bottom Susan?Hinton Lia?Stamatiou 《Estuaries and Coasts》2016,39(2):542-559
Estuarine rearing has been shown to enhance within watershed biocomplexity and support growth and survival for juvenile salmon (Oncorhynchus sp.). However, less is known about how growth varies across different types of wetland habitats and what explains this variability in growth. We focused on the estuarine habitat use of Columbia River Chinook salmon (Oncorhynchus tshawytscha), which are listed under the Endangered Species Act. We employed a generalized linear model (GLM) to test three hypotheses: (1) juvenile Chinook growth was best explained by temporal factors, (2) habitat, or (3) demographic characteristics, such as stock of origin. This study examined estuarine growth rate, incorporating otolith microstructure, individual assignment to stock of origin, GIS habitat mapping, and diet composition along ~130 km of the upper Columbia River estuary. Juvenile Chinook grew on average 0.23 mm/day in the freshwater tidal estuary. When compared to other studies in the basin our growth estimates from the freshwater tidal estuary were similar to estimates in the brackish estuary, but ~4 times slower than those in the plume and upstream reservoirs. However, previous survival studies elucidated a possible tradeoff between growth and survival in the Columbia River basin. Our GLM analysis found that variation in growth was best explained by habitat and an interaction between fork length and month of capture. Juvenile Chinook salmon captured in backwater channel habitats and later in the summer (mid-summer and late summer/fall subyearlings) grew faster than salmon from other habitats and time periods. These findings present a unique example of the complexity of understanding the influences of the many processes that generate variation in growth rate for juvenile anadromous fish inhabiting estuaries. 相似文献
109.
Aaron T. David Charles A. Simenstad Jeffery R. Cordell Jason D. Toft Christopher S. Ellings Ayesha Gray Hans B. Berge 《Estuaries and Coasts》2016,39(3):767-780
During the transition of juveniles from fresh water to estuarine and coastal environments, the survival of Pacific salmon (Oncorhynchus spp.) can be strongly size selective and cohort abundance is partly determined at this stage. Because quantity and quality of food influence juvenile salmon growth, high rates of prey and energy acquisition during estuarine residence are important for survival. Human activities may have affected the foraging performance of juvenile salmon in estuaries by reducing the area of wetlands and by altering the abundance of salmon. To improve our understanding of the effects of wetland loss and salmon density on juvenile salmon foraging performance and diet composition in estuaries, we assembled Chinook salmon (Oncorhynchus tshawytscha) diet and density data from nine US Pacific Northwest estuaries across a gradient of wetland loss. We evaluated the influence of wetland loss and density on juvenile Chinook salmon instantaneous ration and energy ration, two measures of foraging performance, and whether the effect of density varied among estuaries with different levels of wetland loss. We also assessed the influence of wetland loss and other explanatory variables on salmon diet composition. There was no evidence of a direct effect of wetland loss on juvenile salmon foraging performance, but wetland loss appeared to mediate the effect of density on salmon foraging performance and alter salmon diet composition. Specifically, density had no effect on foraging performance in the estuaries with less than 50 % wetland loss but had a negative effect on foraging performance in the estuaries with greater than 50 % wetland loss. These results suggest that habitat loss may interact with density to constrain the foraging performance of juvenile Chinook salmon, and ultimately their growth, during a life history stage when survival can be positively correlated with growth and size. 相似文献
110.
Pece V. Gorsevski M. Kenneth Brown Kurt Panter Charles M. Onasch Anita Simic Jeffrey Snyder 《Landslides》2016,13(3):467-484
The purpose of this study was to detect shallow landslides using hillshade maps derived from light detection and ranging (LiDAR)-based digital elevation model (DEM) derivatives. The landslide susceptibility mapping used an artificial neural network (ANN) approach and backpropagation method that was tested in the northern portion of the Cuyahoga Valley National Park (CVNP) located in northeast Ohio. The relationship between landslides and predictor attributes, which describe landform classes using slope, profile and plan curvatures, upslope drainage area, annual solar radiation, and wetness index, was extracted from LiDAR-based DEM using geographic information system (GIS). The approach presented in this paper required a training study area for the development of the susceptibility model and a validation study area to test the model. The results from the validation showed that within the very high susceptibility class, a total of 42.6 % of known landslides that were associated with 1.56 % of total area were correctly predicted. In contrast, the very low susceptibility class that represented 82.68 % of the total area was associated with 1.20 % of known landslides. The results suggest that the majority of the known landslides occur within a small portion of the study area, consistent with field investigation and other studies. Sample probabilistic maps of landslide susceptibility potential and other products from this approach are summarized and presented for visualization to help park officials in effective management and planning. 相似文献