Understanding Climatic Impacts, Vulnerabilities, and Adaptation in the United States: Building a Capacity for Assessment

Based on the experience of the U.S. National Assessment, we propose a program of research and analysis to advance capability for assessment of climate impacts, vulnerabilities, and adaptation options. We identify specific priorities for scientific research on the responses of ecological and socioeconomic systems to climate and other stresses; for improvement in the climatic inputs to impact assessments; and for further development of assessment methods to improve their practical utility to decision-makers. Finally, we propose a new institutional model for assessment, based principally on regional efforts that integrate observations, research, data, applications, and assessment on climate and linked environmental-change issues. The proposed program will require effective collaboration between scientists, resource managers, and other stakeholders, all of whose expertise is needed to define and prioritize key regional issues, characterize relevant uncertainties, and assess potential responses. While both scientifically and organizationally challenging, such an integrated program holds the best promise of advancing our capacity to manage resources and the economy adaptively under a changing climate.     

Non-stationary extreme value analysis in a changing climate

This paper introduces a framework for estimating stationary and non-stationary return levels, return periods, and risks of climatic extremes using Bayesian inference. This framework is implemented in the Non-stationary Extreme Value Analysis (NEVA) software package, explicitly designed to facilitate analysis of extremes in the geosciences. In a Bayesian approach, NEVA estimates the extreme value parameters with a Differential Evolution Markov Chain (DE-MC) approach for global optimization over the parameter space. NEVA includes posterior probability intervals (uncertainty bounds) of estimated return levels through Bayesian inference, with its inherent advantages in uncertainty quantification. The software presents the results of non-stationary extreme value analysis using various exceedance probability methods. We evaluate both stationary and non-stationary components of the package for a case study consisting of annual temperature maxima for a gridded global temperature dataset. The results show that NEVA can reliably describe extremes and their return levels.     

Mean and Turbulent Flow Statistics in a Trellised Agricultural Canopy

Flow physics is investigated in a two-dimensional trellised agricultural canopy to examine that architecture’s unique signature on turbulent transport. Analysis of meteorological data from an Oregon vineyard demonstrates that the canopy strongly influences the flow by channelling the mean flow into the vine-row direction regardless of the above-canopy wind direction. Additionally, other flow statistics in the canopy sub-layer show a dependance on the difference between the above-canopy wind direction and the vine-row direction. This includes an increase in the canopy displacement height and a decrease in the canopy-top shear length scale as the above-canopy flow rotates from row-parallel towards row-orthogonal. Distinct wind-direction-based variations are also observed in the components of the stress tensor, turbulent kinetic energy budget, and the energy spectra. Although spectral results suggest that sonic anemometry is insufficient for resolving all of the important scales of motion within the canopy, the energy spectra peaks still exhibit dependencies on the canopy and the wind direction. These variations demonstrate that the trellised-canopy’s effect on the flow during periods when the flow is row-aligned is similar to that seen by sparse canopies, and during periods when the flow is row-orthogonal, the effect is similar to that seen by dense canopies.     

GPS Water Vapor and Its Comparison with Radiosonde and ERA-Interim Data in Algeria

Remote sensing of atmospheric water vapor using global positioning system(GPS) data has become an effective tool in meteorology,weather forecasting and climate research. This paper presents the estimation of precipitable water(PW)from GPS observations and meteorological data in Algeria,over three stations located at Algiers,Bechar and Tamanrasset.The objective of this study is to analyze the sensitivity of the GPS PW estimates for the three sites to the weighted mean temperature(T_m),obtained separately from two types of T_m–T_s regression [one general,and one developed specifically for Algeria(T_s stands for surface temperature)],and calculated directly from ERA-Interim data. The results show that the differences in T_m are of the order of 18 K,producing differences of 2.01 mm in the final evaluation of PW. A good agreement is found between GPS-PW and PW calculated from radiosondes,with a small mean difference with Vaisala radiosondes.A comparison between GPS and ERA-Interim shows a large difference(4 mm) in the highlands region. This difference is possibly due to the topography. These first results are encouraging,in particular for meteorological applications in this region,with good hope to extend our dataset analysis to a more complete,nationwide coverage over Algeria.     

On the pH-dependent formation constants of iron(III)-sulfur(IV) transient complexes

An experimental study is described of Fe(III)-S(IV) formation constants measured as a function of pH (1–3), ionic strength (0.2–0.5 M) and [Fe(III)] _T (2.5–5.0×10^–4 M) using a continuous-flow spectrophotometric technique to make observations 160 ms after mixing. Preliminary experiments using pulse-accelerated-flow (PAF) spectrophotometry to measure rate constants on a microsecond timescale are also described. The conditional formation constant at 25 °C can be modeled with the following equation: {ie307-1} where {ie307-2}K ₇ andK ₈ can be interpreted as intrinsic constants for the coordination of HSO ₃ ^– by FeOH²⁺ and Fe³⁺, respectively, but until further evidence is obtained they should be regarded as fitting constants. PAF spectrophotometry showed that the initial reaction of Fe(III) with S(IV) (pH 2.0) is characterized by a second-order rate constant of 4×10⁶ M^–1 s^–1 which is comparable to rate of reaction of FeOH²⁺ with SO ₄ ^2– . However, the PAF results should be regarded as preliminary since unexpected features in the initial data indicate that the reaction may be more complex than expected.     

Future climate in the Pacific Northwest

Climate models used in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) on the whole reproduce the observed seasonal cycle and twentieth century warming trend of 0.8°C (1.5°F) in the Pacific Northwest, and point to much greater warming for the next century. These models project increases in annual temperature of, on average, 1.1°C (2.0°F) by the 2020s, 1.8°C (3.2°F) by the 2040s, and 3.0°C (5.3°F) by the 2080s, compared with the average from 1970 to 1999, averaged across all climate models. Rates of warming range from 0.1°C to 0.6°C (0.2°F to 1.0°F) per decade. Projected changes in annual precipitation, averaged over all models, are small (+1% to +2%), but some models project an enhanced seasonal cycle with changes toward wetter autumns and winters and drier summers. Changes in nearshore sea surface temperatures, though smaller than on land, are likely to substantially exceed interannual variability, but coastal upwelling changes little. Rates of twenty-first century sea level rise will depend on poorly known factors like ice sheet instability in Greenland and Antarctica, and could be as low as twentieth century values (20 cm, 8^″) or as large as 1.3 m (50^″).     

Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.     

Preparing for climate change in Washington State

Climate change is expected to bring potentially significant changes to Washington State’s natural, institutional, cultural, and economic landscape. Addressing climate change impacts will require a sustained commitment to integrating climate information into the day-to-day governance and management of infrastructure, programs, and services that may be affected by climate change. This paper discusses fundamental concepts for planning for climate change and identifies options for adapting to the climate impacts evaluated in the Washington Climate Change Impacts Assessment. Additionally, the paper highlights potential avenues for increasing flexibility in the policies and regulations used to govern human and natural systems in Washington.     

Upper Limit of Iodine Oxide in the Lower Stratosphere

It has been suggested that iodine oxides, IOx, could play a significant role in the ozone destruction in the lower stratosphere. To investigate this suggestion, spectra from nine SAOZ uv-visible spectrometer balloon flights were examined for the IO absorption signature between 405 and 450 nm. IO was not detected, either at mid- or high latitude, in the morning or the evening, in summer or winter. An upper limit of 0.2 parts per trillion by volume (pptv) at 20 km and 0.1 pptv at 15 km at the 95% confidence level (2), was derived from the best measurements at 90° SZA at sunset and sunrise. Since a photochemical model shows that 70% of inorganic iodine should be in the form IO at that time, it is concluded that unless iodine chemistry is different from that assumed at the moment, the role of iodine in stratospheric ozone depletion is small.     

Isolation of 12 microsatellite markers following a pyrosequencing procedure and cross-priming in two invasive cryptic species, Alexandrium catenella (group IV) and A. tamarense (group III) (Dinophyceae)

Alexandrium catenella (group IV) and Alexandrium tamarense (group III) (Dinophyceae) are two cryptic invasive phytoplankton species belonging to the A. tamarense species complex. Their worldwide spread is favored by the human activities, transportation and climate change. In order to describe their diversity in the Mediterranean Sea and understand their settlements and maintenances in this area, new microsatellite markers were developed based on Thau lagoon (France) samples of A. catenella and A. tamarense strains. In this study twelve new microsatellite markers are proposed. Five of these microsatellite markers show amplifications on A. tamarense and ten on A. catenella. Three of these 12 microsatellite markers allowed amplifications on both cryptic species. Finally, the haplotypic diversity ranged from 0.000 to 0.791 and 0.000 to 0.942 for A. catenella and A. tamarense respectively.