Fraction Of Stations Research Articles

Intra-seasonal and inter-decadal variability in ENSO impacts on the Pacific Northwest

Across the western United States, seasonal-scale El Nino-Southern Oscillation (ENSO) teleconnections have been extensively described. Less attention has been paid to spatial and temporal details of these relationships that might be particularly important to managers and decision makers. Here, we explore intra-seasonal relationships between the Southern Oscillation Index (SOI) and average temperature, wet-day temperature, overall precipitation amount, precipitation frequency, and rain/snow partitioning at 138 Global Historical Climatology Network weather stations across the Pacific Northwest of the United States. Results of this study indicate that ENSO influences were generally more pronounced along the coast and in the northern Idaho/western Montana region than in the lee of the Cascades. There was a distinct seasonality in response, with stronger correlations in the late winter (February–March) than in the autumn (October–November) or mid-winter (December–January). The fraction of stations demonstrating correlations to SOI has changed over time, with a trend towards greater spring teleconnections in recent decades.

Future air quality in Europe: a multi-model assessment of projected exposure to ozone

Abstract. In order to explore future air quality in Europe at the 2030 horizon, two emission scenarios developed in the framework of the Global Energy Assessment including varying assumptions on climate and energy access policies are investigated with an ensemble of six regional and global atmospheric chemistry transport models. A specific focus is given in the paper to the assessment of uncertainties and robustness of the projected changes in air quality. The present work relies on an ensemble of chemistry transport models giving insight into the model spread. Both regional and global scale models were involved, so that the ensemble benefits from medium-resolution approaches as well as global models that capture long-range transport. For each scenario a whole decade is modelled in order to gain statistical confidence in the results. A statistical downscaling approach is used to correct the distribution of the modelled projection. Last, the modelling experiment is related to a hind-cast study published earlier, where the performances of all participating models were extensively documented. The analysis is presented in an exposure-based framework in order to discuss policy relevant changes. According to the emission projections, ozone precursors such as NOx will drop down to 30% to 50% of their current levels, depending on the scenario. As a result, annual mean O3 will slightly increase in NOx saturated areas but the overall O3 burden will decrease substantially. Exposure to detrimental O3 levels for health (SOMO35) will be reduced down to 45% to 70% of their current levels. And the fraction of stations where present-day exceedences of daily maximum O3 is higher than 120 μg m−3 more than 25 days per year will drop from 43% down to 2 to 8%. We conclude that air pollution mitigation measures (present in both scenarios) are the main factors leading to the improvement, but an additional cobenefit of at least 40% (depending on the indicator) is brought about by the climate policy.

Trends in Average Snow Depth Across the Western United States

A network of cooperative observation stations was used to examine trends in average snow depth across the western United States. This station network includes a greater number of low- to moderate-elevation stations, where the snow is particularly sensitive to temperature changes, than the snow course and SNOTEL datasets used in other studies. Results indicate a widespread decrease in snow depth across the region; 70% of stations with statistically significant trends (p ≤ 0.5 or p ≤ 0.10) exhibit negative trends. Elevation is a key factor in explaining the spatial pattern of snow depth trends across the region. The fraction of stations with significant negative trends is greatest (80%) at the lower-elevation stations (<1000 m) and is somewhat less (62%) for stations between 2000 and 3000 m. Pacific climate indices, including the Pacific Decadal Oscillation (PDO) and North Pacific Index (NPI), are shown to have important but spatially varying influences upon average seasonal snow depths.

Performing work in broadcast networks

We consider the problem of how to schedule t similar and independent tasks to be performed in a synchronous distributed system of p stations communicating via multiple-access channels. Stations are prone to crashes whose patterns of occurrence are specified by adversarial models. Work, defined as the number of the available processor steps, is the complexity measure. We consider only reliable algorithms that perform all the tasks as long as at least one station remains operational. It is shown that every reliable algorithm has to perform work Omega(t + p root t) even when no failures occur. An optimal deterministic algorithm for the channel with collision detection is developed, which performs work O(t + p root t). Another algorithm, for the channel without collision detection, performs work O(t + p root t + p min {f, t}), where f < p is the number of failures. This algorithm is proved to be optimal, provided that the adversary is restricted in failing no more than f stations. Finally, we consider the question if randomization helps against weaker adversaries for the channel without collision detection. A randomized algorithm is developed which performs the expected minimum amount O(t + p root t) of work, provided that the adversary may fail a constant fraction of stations and it has to select failure-prone stations prior to the start of an execution of the algorithm.

Multisite simulation of daily precipitation and temperature in the Rhine Basin by nearest‐neighbor resampling

The method of nearest‐neighbor resampling is extended to simultaneous simulation of daily precipitation and temperature at multiple locations over a large area (25 stations in the German part of the Rhine basin). Nearest neighbors refer here to historical days for which the observed weather is closest to that of the simulated weather for a given day. Resampling is done from these nearest neighbors to obtain the weather variables for the next day. The nearest neighbors are defined in terms of a weighted Euclidean distance to a feature vector containing summary statistics of the daily precipitation and temperature fields (spatial averages, fraction of stations with precipitation, and principal components). The inclusion of atmospheric circulation variables in the feature vector is also studied. There is a weak tendency to underestimate the standard deviations and autocorrelation coefficients of daily precipitation and temperature and the standard deviations of the monthly precipitation totals and monthly mean temperatures. However, the underprediction of these second‐order moment statistics is not statistically significant if the number k of nearest neighbors in the resampling procedure is small (k≈ 5) and the dimensionqof the feature vector is low (q≈ 3). A small systematic underprediction is also observed for the quantiles of the distributions of theN‐day winter maximum precipitation amounts. The spatial dependence of these extremes and the distributions ofN‐day maximum snowmelt are adequately reproduced. Long‐duration simulations show that realistic unprecedented multiday precipitation amounts can be generated.