scholarly journals The unpredictable truth: A proposed roadmap for a ‘reflect-then-act’ approach to climate uncertainties and lessons learned from Norwegian municipalities

2022 ◽  
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Climate Model ◽  
Policy Decision ◽  
Major Elements ◽  
Lessons Learned ◽  
Address Climate Change ◽  
New Approach ◽  
Political Processes ◽  
The Way

Abstract Several papers have through the years criticized climate policy decision making for being naïve with respect to how they view climate model outputs as objective facts and use the outputs directly to program policies. From this and similar observations, many of the papers conclude that there is a need for shifting to a new approach on how climate policymakers may relate to climate change uncertainties. The article proposes such a shift by presenting a roadmap on how to address uncertainties in climate change adaptation. It consists of three major elements: Firstly, to accept that in many cases we will not be able to reduce climate change uncertainties. Secondly, to diversify the way in which we describe climate change uncertainties, moving from a one-dimensional technical perspective to a multi-dimensional perspective which applies uncertainties also to social and political processes and systems. Thirdly, to change the way we address climate change uncertainties by moving from a predict-then-act to a reflect-then-act approach, implying that we must adapt to climate change even under high and various forms of uncertainties. Embedded in this last point is to accept unlike that of climate change mitigation, the precautionary principle will apply in many situations of climate change adaptation. In the last part of the article the usability of the proposed roadmap is demonstrated post-ante on four Norwegian cases of climate related natural hazard events.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

A new approach for assessing climate change impacts in ecotron experiments

2019 ◽  
Author(s):  
Inne Vanderkelen ◽  
Jakob Zschleischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
New Approach ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future, preserving the co-variances between variables and the projected changes in variability. Here we present a new experimental design for studying climate change impacts on terrestrial ecosystems and apply it to the UHasselt Ecotron Experiment. The new methodology consists of generating climate forcing along a gradient representative of increasingly high global mean temperature anomalies and uses data derived from the best available regional climate model (RCM) projection. We first identified the best performing regional climate model (RCM) simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European Domain (EURO-CORDEX) ensemble with a 0.11° (12.5 km) resolution based on two criteria: (i) highest skill of the simulations compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. Our results reveal that no single RCM simulation has the best score for all possible combinations of the four meteorological variables and evaluation metrics considered. Out of the six best performing simulations, we selected the simulation with the lowest bias for precipitation (CCLM4-8-17/EC-EARTH), as this variable is key to ecosystem functioning and model simulations deviated the most for this variable, with values ranging up to double the observed values. The time window is subsequently selected from the RCM projection for each ecotron unit based on the global mean temperature of the driving Global Climate Model (GCM). The ecotron units are forced with 3-hourly output from the RCM projections of the five-year period spanning the year in which the global mean temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The gradient approach will allow to identify possible threshold and tipping points.

scholarly journals Stakeholder integrated research (STIR): a new approach tested in climate change adaptation research

2014 ◽  
Vol 128 (3-4) ◽  
pp. 201-214 ◽  
Author(s):  
Marc Gramberger ◽  
Katharina Zellmer ◽  
Kasper Kok ◽  
Marc J. Metzger
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
New Approach ◽  
Integrated Research

scholarly journals Climate change adaptation frameworks: an evaluation of plans for coastal, Suffolk, UK

2015 ◽  
Vol 3 (6) ◽  
pp. 4059-4094
Author(s):  
J. Armstrong ◽  
R. Wilby ◽  
R. J. Nicholls
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Climate Change Adaptation ◽  
Stakeholder Engagement ◽  
Online Survey ◽  
Climate Model ◽  
Economic Knowledge ◽  
Framework Analysis ◽  
Further Development

Abstract. This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: Scenario-Led (SL), Vulnerability-Led (VL) and Decision–Centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.

scholarly journals Attitudes of Farmers and Rural Area Residents Toward Climate Change Adaptation Measures: Their Preferences and Determinants of Their Attitudes

Climate ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 71
Author(s):  
Kenshi Baba ◽  
Mitsuru Tanaka
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Policy Decision ◽  
Decision Making Process ◽  
Willingness To Participate ◽  
Adaptation Measures ◽  
Multiple Risks ◽  
Climate Change Risks ◽  
Policy Decision Making ◽  
The Government

In this study, data obtained from an online survey were analyzed to identify the perception gap between farmers and nonfarmers (rural area residents) toward climate change adaptation measures with conventional and new elements of the psychological mechanism. Key findings from the study were as follows. First, the perception of climate change risk and awareness of impacts of climate change had strong effects on the preferences for and willingness to participate in measures rather than trusting the government and values pertaining to the policy decision-making process. Second, farmers tended to prefer “protection” and “transfer of risks (insurance)” as climate change adaptation measures more than nonfarmers did. Farmers also tended to be unwilling to participate in “withdrawal”, reflecting the difficulty of relocating agricultural land. Third, farmers’ willingness to participate in climate change adaptation measures was determined strongly by their preferences. Therefore, to increase preference, there needs to be communication about multiple risks including climate change risks associated with not only “adjustment” and “protection”, which tend to be preferred, but also “withdrawal”, which tends to not be preferred. Contrasting with these, nonfarmers tended to prefer any particular climate change adaptation measures statistically-significantly, but they tended to be willing to accept “self-help” absolutely and “withdrawal” relatively. Also, farmers’ willingness to participate in climate change adaptation measures was determined strongly by their preference. One of the ways to increase the preference is communicating about the multiple risks including climate change risks associated with “adjustment,” “protection” and “transfer” which tend to be preferred more than nonfarmers did. Finally, trust in the government and values pertaining to the policy decision-making process did not necessarily have a serious impact on policy preferences and willingness to participate, both for farmers and nonfarmers. More analyses for other sectors will be needed for further study.

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