PMID- 36518178
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20221221
IS  - 2212-0963 (Print)
IS  - 2212-0963 (Electronic)
IS  - 2212-0963 (Linking)
VI  - 38
DP  - 2022
TI  - Estimating impact likelihoods from probabilistic projections of climate and 
      socio-economic change using impact response surfaces.
PG  - None
LID - 10.1016/j.crm.2022.100466 [doi]
AB  - Estimates of future climate change impacts using numerical impact models are 
      commonly based on a limited selection of projections of climate and other key 
      drivers. However, the availability of large ensembles of such projections offers 
      an opportunity to estimate impact responses probabilistically. This study 
      demonstrates an approach that combines model-based impact response surfaces 
      (IRSs) with probabilistic projections of climate change and population to 
      estimate the likelihood of exceeding pre-specified thresholds of impact. The 
      changing likelihood of exceeding impact thresholds during the 21st century was 
      estimated for selected indicators in three European case study regions (Iberian 
      Peninsula, Scotland and Hungary), comparing simulations that incorporate 
      adaptation to those without adaptation. The results showed high likelihoods of 
      increases in heat-related human mortality and of yield decreases for some crops, 
      whereas a decrease of NPP was estimated to be exceptionally unlikely. For a water 
      reservoir in a Portuguese catchment, increased likelihoods of severe water scarce 
      conditions were estimated for the current rice cultivation. Switching from rice 
      to other crops with lower irrigation demand changes production risks, allowing 
      for expansion of the irrigated areas but introducing a stronger sensitivity to 
      changes in rainfall. The IRS-based risk assessment shown in this paper is of 
      relevance for policy making by addressing the relative sensitivity of impacts to 
      key climate and socio-economic drivers, and the urgency for action expressed as a 
      time series of the likelihood of crossing critical impact thresholds. It also 
      examines options to respond by incorporating alternative adaptation actions in 
      the analysis framework, which may be useful for exploring the types, choice and 
      timing of adaptation responses.
CI  - (c) 2022 The Author(s).
FAU - Fronzek, Stefan
AU  - Fronzek S
AD  - Finnish Environment Institute (SYKE), Finland.
FAU - Honda, Yasushi
AU  - Honda Y
AD  - The University of Tsukuba, Japan.
AD  - National Institute for Environmental Studies, Japan.
FAU - Ito, Akihiko
AU  - Ito A
AD  - National Institute for Environmental Studies, Japan.
FAU - Nunes, Joao Pedro
AU  - Nunes JP
AD  - CE3C: Centre for Ecology, Evolution and Environmental Changes, Faculdade de 
      Ciencias, Universidade de Lisboa, Portugal.
AD  - Soil Physics and Land Management Group, Wageningen University and Research, 
      Wageningen, the Netherlands.
FAU - Pirttioja, Nina
AU  - Pirttioja N
AD  - Finnish Environment Institute (SYKE), Finland.
FAU - Raisanen, Jouni
AU  - Raisanen J
AD  - Institute for Atmospheric and Earth System Research, University of Helsinki, 
      Finland.
FAU - Takahashi, Kiyoshi
AU  - Takahashi K
AD  - National Institute for Environmental Studies, Japan.
FAU - Terama, Emma
AU  - Terama E
AD  - Finnish Environment Institute (SYKE), Finland.
FAU - Yoshikawa, Minoru
AU  - Yoshikawa M
AD  - Mizuho Information and Research Institute, Japan.
FAU - Carter, Timothy R
AU  - Carter TR
AD  - Finnish Environment Institute (SYKE), Finland.
LA  - eng
PT  - Journal Article
PL  - Netherlands
TA  - Clim Risk Manag
JT  - Climate risk management
JID - 101701807
PMC - PMC9733490
OTO - NOTNLM
OT  - Impact model
OT  - Population
OT  - Precipitation
OT  - Sensitivity analysis
OT  - Temperature
COIS- The authors declare that they have no known competing financial interests or 
      personal relationships that could have appeared to influence the work reported in 
      this paper.
EDAT- 2022/12/16 06:00
MHDA- 2022/12/16 06:01
PMCR- 2022/01/01
CRDT- 2022/12/15 02:15
PHST- 2022/08/17 00:00 [received]
PHST- 2022/11/17 00:00 [revised]
PHST- 2022/11/22 00:00 [accepted]
PHST- 2022/12/15 02:15 [entrez]
PHST- 2022/12/16 06:00 [pubmed]
PHST- 2022/12/16 06:01 [medline]
PHST- 2022/01/01 00:00 [pmc-release]
AID - S2212-0963(22)00073-0 [pii]
AID - 100466 [pii]
AID - 10.1016/j.crm.2022.100466 [doi]
PST - ppublish
SO  - Clim Risk Manag. 2022;38:None. doi: 10.1016/j.crm.2022.100466.