A risk assessment of climate change and the impact of forest diseases on forest ecosystems in the Western United States and Canada

2011 ◽  
Author(s):  
John T. Kliejunas
Keyword(s):  
Climate Change ◽  
United States ◽  
Risk Assessment ◽  
Forest Ecosystems ◽  
Western United States ◽  
The Impact ◽  
Forest Diseases

A MODELING SYSTEM FOR CLIMATE CHANGE RISK ASSESSMENT, MANAGEMENT AND HEDGING IN COASTAL AREAS

2017 ◽  
Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Coastal Areas ◽  
Mitigation Strategies ◽  
System Structure ◽  
The Arctic ◽  
Risk Modeling ◽  
Wide Range ◽  
Adverse Weather ◽  
The Impact

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.

scholarly journals Influence of Atmospheric Rivers on Mountain Snowpack in the Western United States

2018 ◽  
Vol 31 (24) ◽  
pp. 9921-9940 ◽  
Author(s):  
N. Goldenson ◽  
L. R. Leung ◽  
C. M. Bitz ◽  
E. Blanchard-Wrigglesworth
Keyword(s):  
United States ◽  
Sierra Nevada ◽  
Snow Water Equivalent ◽  
Region Of Interest ◽  
Internal Variability ◽  
Western United States ◽  
Historical Period ◽  
Atmospheric Rivers ◽  
Atmospheric River ◽  
The Impact

In the coastal mountains of western North America, most extreme precipitation is associated with atmospheric rivers (ARs), narrow bands of moisture originating in the tropics. Here we quantify how interannual variability in atmospheric rivers influences snowpack in the western United States in observations and a model. We simulate the historical climate with the Model for Prediction Across Scales (MPAS) with physics from the Community Atmosphere Model, version 5 [CAM5 (MPAS-CAM5)], using prescribed sea surface temperatures. In the global variable-resolution domain, regional refinement (at ~30 km) is applied to our region of interest and upwind over the northeast Pacific. To better characterize internal variability, we conduct simulations with three ensemble members over 30 years of the historical period. In the Cascade Range, with some exceptions, winters with more atmospheric river days are associated with less snowpack. In California’s Sierra Nevada, winters with more ARs are associated with greater snowpack. The slope of the linear regression of observed snow water equivalent (SWE) on reanalysis-based AR count has the same sign as that arrived at using the model, but is statistically significant in observations only for California. In spring, internal variance plays an important role in determining whether atmospheric river days appear to be associated with greater or less snowpack. The cumulative (winter through spring) number of atmospheric river days, on the other hand, has a relationship with spring snowpack, which is consistent across ensemble members. Thus, the impact of atmospheric rivers on winter snowpack has a greater influence on spring snowpack than spring atmospheric rivers in the model for both regions and in California consistently in observations.

scholarly journals Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

2018 ◽  
Author(s):  
Michalis I. Vousdoukas ◽  
Dimitrios Bouziotas ◽  
Alessio Giardino ◽  
Laurens M. Bouwer ◽  
Evangelos Voukouvalas ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Epistemic Uncertainty ◽  
Coastal Protection ◽  
Flood Risk Assessment ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
The Impact

Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policy-making and harmonization of climate change adaptation strategies. There is, however, limited insight on the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the Coastal Flood Risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea-level (ESL); (ii) inundation modelling; (iii) the underlying uncertainty in the Digital Elevation Model (DEM); (iv) flood defence information; (v) the assumptions behind the use of depth-damage functions that express vulnerability; and (vi) different climate change projections. The impact of these uncertainties to estimated Expected Annual Damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal and in the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, as well as their absolute/relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large-extent datasets with sufficient resolution and accuracy the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

scholarly journals Aspects Concerning the Impact of Climate Aridization on Forest Ecosystems (Case Study)

2017 ◽  
Vol 11 (2) ◽  
pp. 63-75
Author(s):  
Nedealcov Maria ◽  
Donica Ala ◽  
Brașoveanu Valeriu ◽  
Grigoraș Nicolae ◽  
Deomidova Cristina
Keyword(s):  
Climate Change ◽  
Forest Ecosystems ◽  
Temporal Dynamics ◽  
Negative Impact ◽  
Local Level ◽  
Aridity Index ◽  
Climatic Conditions ◽  
Study Region ◽  
Climate Aridization ◽  
The Impact

Abstract Assessment activity and surveillance of the forests health, held at the global, regional and local level, has continuously developed, culminating in the current period with interdisciplinary and extensive scientific researches, that evaluate the effects of the main factors on forest ecosystems state, in particular, air pollution and climate change. Scientific researches have shown that among trees ecophysiological processes, forest life processes and meteorological parameters there are direct dependences, particularly in the case of trees supply with water during the growing period (May-July), with major influences for critical months (July and August), which have a decisive impact on growth, vitality and production of organic matter in forests. Dry years, from the beginning of the third millennium can lead to a decrease of mesophilic forests area (beech, sessile oak and penduculate oak), which will tend to retreat towards the center of the area (central Europe) in favor of thermophilic forests with pubescent oak. It was determined that a most significant negative impact of climate aridization will feel the forest ecosystems from Southern and central regions of country (conditioned by the mean air temperature (July-August), monthly rainfall (May-August), evapotranspiration and geographic latitude), and less - the Northern part of the country (Forestry Aridity Index calculated for 3 experimental stations revealed variations of this index between 7.8 - 8.3 - in the Central part of country, and 8.4 - 8.6 - for Southern part of country). At the same time the impact of climate change will determine the spatial and temporal dynamics of pests and pathogenic species. The phenomenon of climate aridization was expressed also through the impact of the Microsphaera alphitoides disease, intensity of “mildew” attack being based on the climatic conditions of the study region. Obtained data, for confirmation, were correlated with indications of bioindicators, present in the study region.

Investigation of mb and MS formulas for the Western United States and their impact on the MS/mb discriminant

1987 ◽  
Vol 77 (3) ◽  
pp. 987-995
Author(s):  
Marvin D. Denny ◽  
Steven R. Taylor ◽  
Eileen S. Vergino
Keyword(s):  
United States ◽  
Systematic Error ◽  
Analysis Of Variance ◽  
Magnitude Estimate ◽  
Peak Amplitude ◽  
Western United States ◽  
Station Correction ◽  
Simple Analysis ◽  
The Impact ◽  
Distance Correction

Abstract The impact of regional mb and MS formulas on regional MS/mb discrimination is investigated using a large number of Western United States earthquakes and explosions. Comparison of NEIS mb values with regional mb values shows a systematic error of 1.2. Additionally, a simple analysis of variance shows that the variance of the magnitude estimate is reduced when log(A) replaces log(A/T). These changes, along with a refinement of the distance correction, yield a new regional mb for the Western United States given by mb = log(A) + 2.4 log(Δ) − 3.95 + cj, where A = 0 to peak amplitude in nanometers, Δ is the distance in kilometers, and ci is a station correction. Usage of this formula improves the performance of regional MS/mb discrimination by a factor of 2 to 6.

How to model the impact of climate change on vector-borne diseases?

2021 ◽  
pp. 26-31
Author(s):  
Cyril Caminade
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Mathematical Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Risk ◽  
Vector Borne Diseases ◽  
Impact Of Climate Change ◽  
Vector Borne ◽  
The Impact

Abstract This expert opinion provides an overview of mathematical models that have been used to assess the impact of climate change on ticks and tick-borne diseases, ways forward in terms of improving models for the recent context and broad guidelines for conducting future climate change risk assessment.

scholarly journals Taken by Storm: Hurricanes, Migrant Networks, and US Immigration

2020 ◽  
Vol 12 (2) ◽  
pp. 250-277 ◽  
Author(s):  
Parag Mahajan ◽  
Dean Yang
Keyword(s):  
Climate Change ◽  
United States ◽  
International Migration ◽  
The United States ◽  
Quarter Century ◽  
Migrant Networks ◽  
Disaster Impacts ◽  
The Impact ◽  
Natural Disaster Impacts ◽  
Us Immigration

Do negative shocks in origin countries encourage or inhibit international migration? What roles do networks play in modifying out-migration responses? The answers to these questions are not theoretically obvious, and past empirical findings are equivocal. We examine the impact of hurricanes on a quarter century of international migration to the United States. Hurricanes increase migration to the United States, with the effect’s magnitude increasing in the size of prior migrant stocks. We provide new insights into how networks facilitate legal, permanent US immigration in response to origin country shocks, a matter of growing importance as climate change increases natural disaster impacts. (JEL F22, J15, Q54, Z13)

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