Spatial Hedonic Models for Measuring the Impact of Sea-Level Rise on Coastal Real Estate

This study uses a unique integration of geospatial and hedonic property data to estimate the impact of sea-level rise on coastal real estate in North Carolina. North Carolina’s coastal plain is one of several large terrestrial systems around the world threatened by rising sea-levels. High-resolution topographic LIDAR (Light Detection and Ranging) data are used to provide accurate inundation maps for all properties that will be at risk under six different sea-level rise scenarios. A simulation approach based on spatial hedonic models is used to provide consistent estimates of the property value losses. Results indicate that the northern part of the North Carolina coastline is comparatively more vulnerable to the effect of sea-level rise than the southern part. Low-lying and heavily developed areas in the northern coastline are especially at high risk from sea-level rise. Key Words: Climate change, coastal real estate, sea-level rise, spatial hedonic models

Measuring the Impacts of Sea Level Rise on Marine Recreational Shore Fishing in North Carolina

We develop estimates of the economic effects of sea level rise on marine recreational shore fishing in North Carolina. We estimate the relationship between angler behavior and spatial differences in beach width using the Marine Recreational Fishing Statistics Survey and geospatial data. We exploit the empirical relationship between beach width and site choice by simulating the effects of (1) sea level rise on beach width and (2) beach width on angler site choice. We find that the welfare losses are potentially substantial, ranging up to a present value of $1.26 billion over 75 years. Key Words: marine recreational fishing, travel cost method, climate change, sea level rise

Atmospheric Methane in GEOS-5: Development of the Methane Module in GEOS, Current Status and Planned Capabilities

No abstract availabl

Effects of climate extremes on the terrestrial carbon cycle : concepts, processes and potential future impacts

This article is protected by copyright. All rights reserved. Acknowledgements This work emerged from the CARBO-Extreme project, funded by the European Community’s 7th framework programme under grant agreement (FP7-ENV-2008-1-226701). We are grateful to the Reviewers and the Subject Editor for helpful guidance. We thank to Silvana Schott for graphic support. Mirco Miglivacca provided helpful comments on the manuscript. Michael Bahn acknowledges support from the Austrian Science Fund (FWF; P22214-B17). Sara Vicca is a postdoctoral research associate of the Fund for Scientific Research – Flanders. Wolfgang Cramer contributes to the Labex OT-Med (n° ANR-11- LABX-0061) funded by the French government through the A*MIDEX project (n° ANR-11-IDEX-0001-02). Flurin Babst acknowledges support from the Swiss National Science Foundation (P300P2_154543).Peer reviewedPublisher PD

The terrestrial carbon budget of South and Southeast Asia

Accomplishing the objective of the current climate policies will require establishing carbon budget and flux estimates in each region and county of the globe by comparing and reconciling multiple estimates including the observations and the results of top-down atmospheric carbon dioxide (CO2) inversions and bottom-up dynamic global vegetation models. With this in view, this study synthesizes the carbon source/sink due to net ecosystem productivity (NEP), land cover land use change (ELUC), fires and fossil burning (EFIRE) for the South Asia (SA), Southeast Asia (SEA) and South and Southeast Asia (SSEA=SA+SEA) and each country in these regions using the multiple top-down and bottom-up modeling results. The terrestrial net biome productivity (NBP=NEP-ELUC-EFIRE) calculated based on bottom-up models in combination with EFIRE based on GFED4s data show net carbon sinks of 217±147, 10±55, and 227±279 TgC yr?1 for SA, SEA, and SSEA. The top-down models estimated NBP net carbon sinks were 20±170, 4±90 and 24±180 TgC yr?1. In comparison, regional emissions from the combustion of fossil fuels were 495, 275, and 770 TgC yr?1, which are many times higher than the NBP sink estimates, suggesting that the contribution of the fossil fuel emissions to the carbon budget of SSEA results in a significant net carbon source during the 2000s. When considering both NBP and fossil fuel emissions for the individual countries within the regions, Bhutan and Laos were net carbon sinks and rest of the countries were net carbon source during the 2000s. The relative contributions of each of the fluxes (NBP, NEP, ELUC, and EFIRE, fossil fuel emissions) to a nation’s net carbon flux varied greatly from country to country, suggesting a heterogeneous dominant carbon fluxes on the country-level throughout SSEA

Terrestrial Biosphere Model Performance for Inter-Annual Variability of Land-Atmosphere CO2 Exchange

Interannual variability in biosphere-atmosphere exchange of CO2 is driven by a diverse range of biotic and abiotic factors. Replicating this variability thus represents the ‘acid test’ for terrestrial biosphere models. Although such models are commonly used to project responses to both normal and anomalous variability in climate, they are rarely tested explicitly against inter-annual variability in observations. Herein, using standardized data from the North American Carbon Program, we assess the performance of 16 terrestrial biosphere models and 3 remote sensing products against long-term measurements of biosphere-atmosphere CO2 exchange made with eddy-covariance flux towers at 11 forested sites in North America. Instead of focusing on model-data agreement we take a systematic, variability-oriented approach and show that although the models tend to reproduce the mean magnitude of the observed annual flux variability, they fail to reproduce the timing. Large biases in modeled annual means are evident for all models. Observed interannual variability is found to commonly be on the order of magnitude of the mean fluxes. None of the models consistently reproduce observed interannual variability within measurement uncertainty. Underrepresentation of variability in spring phenology, soil thaw and snowpack melting, and difficulties in reproducing the lagged response to extreme climatic events are identified as systematic errors, common to all models included in this study.Organismic and Evolutionary Biolog

RECCAP2 Future Component: Consistency and Potential for Regional Assessment to Constrain Global Projections

This is the final version. Available from Wiley via the DOI in this record. Data Availability Statement: All CMIP6 model output datasets analyzed during this study are available online at https://esgf-node.llnl.gov/search/cmip6/ and code required to reproduce figures is available at https://github.com/ChrisJones-MOHC/RECCAP2Future_2023 (ChrisJones-MOHC, 2023) and Zenodo at https://doi.org/10.5281/zenodo.8420250.Projections of future carbon sinks and stocks are important because they show how the world's ecosystems will respond to elevated CO2 and changes in climate. Moreover, they are crucial to inform policy decisions around emissions reductions to stay within the global warming levels identified by the Paris Agreement. However, Earth System Models from the 6th Coupled Model Intercomparison Project (CMIP6) show substantial spread in future projections—especially of the terrestrial carbon cycle, leading to a large uncertainty in our knowledge of any remaining carbon budget (RCB). Here we evaluate the global terrestrial carbon cycle projections on a region‐by‐region basis and compare the global models with regional assessments made by the REgional Carbon Cycle Assessment and Processes, Phase 2 activity. Results show that for each region, the CMIP6 multi‐model mean is generally consistent with the regional assessment, but substantial cross‐model spread exists. Nonetheless, all models perform well in some regions and no region is without some well performing models. This gives confidence that the CMIP6 models can be used to look at future changes in carbon stocks on a regional basis with appropriate model assessment and benchmarking. We find that most regions of the world remain cumulative net sources of CO2 between now and 2100 when considering the balance of fossil‐fuels and natural sinks, even under aggressive mitigation scenarios. This paper identifies strengths and weaknesses for each model in terms of its performance over a particular region including how process representation might impact those results and sets the agenda for applying stricter constraints at regional scales to reduce the uncertainty in global projections.European Union’s Horizon 2020European Union’s Horizon 2020European Union’s Horizon 2020Joint UK BEIS/Defra Met Office Hadley Centre Climate ProgrammeCarbonWatch-NZ Endeavour Research ProgrammeSão Paulo Research FoundationSão Paulo Research FoundationSão Paulo Research FoundationNational Science FoundationAndrew Carnegie Fellow ProgramCNPqKorea Ministry of EnvironmentNatural Environment Research Council (NERC)Natural Environment Research Council (NERC)National Environmental Science Progra

Identifying beliefs underlying pre-drivers’ intentions to take risks: an application of the theory of planned behaviour

Novice motorists are at high crash risk during the first few months of driving. Risky behaviours such as speeding and driving while distracted are well-documented contributors to crash risk during this period. To reduce this public health burden, effective road safety interventions need to target the pre-driving period. We use the Theory of Planned Behaviour (TPB) to identify the pre-driver beliefs underlying intentions to drive over the speed limit (N = 77), and while over the legal alcohol limit (N = 72), talking on a hand-held mobile phone (N = 77) and feeling very tired (N = 68). The TPB explained between 41% and 69% of the variance in intentions to perform these behaviours. Attitudes were strong predictors of intentions for all behaviours. Subjective norms and perceived behavioural control were significant, though weaker, independent predictors of speeding and mobile phone use. Behavioural beliefs underlying these attitudes could be separated into those reflecting perceived disadvantages (e.g., speeding increases my risk of crash) and advantages (e.g., speeding gives me a thrill). Interventions that can make these beliefs safer in pre-drivers may reduce crash risk once independent driving has begun