RECAST - REviewing Climate change simulations for enhanced Adaptation in Sectors and Technical infrastructure: implications of growing weather variability and uncertainty for weather sensitive capital intensive systems
The RECAST study aims to assess the impacts of climate change induced uncertainty and growth of climate variability on the social and economic coping range of selected infrastructure and real estate, with the aim to generate insights, methods and procedures that enable better adaptation to climate change, i.e. leading to recasting of asset management approaches.
In addition, the following supplementary objectives are being pursued:
To assess to what extent the change in uncertainty in coping ranges requires anticipatory adaptation in order to avoid significant (damage) cost or not to forego benefits
To assess what sort of adaptation is effective, depending on the extent and pace of change of the considered uncertainty on coping range, and what would be the order of magnitude of avoided (damage) cost of adequate adaptation
To assess to what extent the functioning of considered markets can be enhanced with respect to the ability to adapt to effects of climate change, and to what extent further intervention is needed due to inherent myopia of these markets and/or due to deep uncertainty
Adequate adaptation to climate change crucially depends on the predictability of weather and climate conditions. There is a consensus view1 that for many climate variables inter- and intra-annual variability will go up. More in particular for Northern Europe this is supported by focused research2. Users of this information are interested either in the changes in the lower and upper bounds of the projected ranges in relation to the physical and economic coping range of a sector, and/or in changes in risks for costly deviations from optimal operations in normal conditions. For sectors sensitive to weather conditions and with high capital intensity these changes in upper and lower bounds and overall distributional characteristics of weather phenomena can create substantial extra cost, regrets for missed opportunities, and in exceptional cases serious shortfall or collapse of the system. This concerns energy systems, transport infrastructure, water resource regulation, sewage and waste water treatment, and real estate at large.
The study is organised in three work packages. Work package no.1 (WP1) deals with the analysis of the uncertainty of climate data and climate change simulation output in the context of their intended use in subsequent stages of analysis and decision making. More in particular a new approach is developed for estimating extremes on the basis of observed past extremes without prior assumptions regarding the type of underlying distribution.
The second work package (WP2) is focusing on the generation and analysis of coping range relevant information derived from climate change simulations. More in particular candidates for improved bias correction methods are tested regarding RCM output for temperature and precipitation and their behaviour regarding realizations at the high end of daily precipitation and temperature. This includes also review of the consequences of different extents of spatial smoothing climate data.
The third work package (WP3) assesses the implications of changed variability and its uncertainty for economic analysis and decision making with respect to adaptation of hydro power management and urban real estate valuation. Consequences of increased climate variability per season for hydro power management are assessed by means of real options approaches, and entail the use of both a hydrological model of Nordic countries' river basins and self-developed explorative real options decision models. The consequences for urban real estate value formation are explored by means of a spatially explicit rich hedonic pricing model, with special reference to various ecosystem service effects. The model results provide the basis for urban simulation model oriented towards appraisal of adaptation solutions, such as green roofs.
In later phases of the project WP1 will serve WP2 and WP3, whereas also interaction between WP2 and WP3 is taken up.
Output to date
In WP 1 an optimal and iterative extreme value analysis method has been developed and demonstrated in an extensive extreme climate data analysis for Europe (Vajda et al. 2012). The method has provided good results and is more powerful than the conventional maximum-likelihood-method in analysing the probability of extremes from short records.
That the plotting position in extreme value analysis is explicitly P = m/(N+1) has been proven directly from the fundamentals of statistics (Makkonen et al. 2012a). This removes the methodological uncertainty related to more than ten plotting position formulae used so far.
The work in WP 1 alters the foundations of statistical analysis. We, for example, propose a new definition for the empirical distribution function and the quantile function (Makkonen & Pajari 2012).
WP 1 researchers have had a presentation in the following meetings:
European Science Foundation High-Level Research Conference Extreme Environmental Events 13-17.12.2010, Cambridge, UK. (L. Makkonen: Have we underestimated climate extremes?)
From WP1 there are so far 12 publications out of which 3 in peer reviewed journals and 3 submitted. The most important publications are:
Makkonen, L., Rabb, R. & Tikanmäki, M., 2012b: Size effect based on extreme value statistics of defects. Probabilistic Engineering Mechanics. Submitted.
Makkonen, L. & Pajari, M., 2013: Quantiles revisited. Methodology and Computing in Applied Probability. Submitted.
Vajda, A., Tuomenvirta, H., Jokinen, P., Luomaranta, A., Makkonen, L., Tikanmäki, M., Groenemeijer, P., Saarikivi, P., Michaelides, S., Papadakis, M., Tymvios, F. & Athanasatos, S., 2012. Probabilities of adverse weather affecting transport in Europe: climatology and scenarios up to the 2050s. Geophysical Research Abstracts, Vol. 14, European Geophysical Union EGU2012-12279-3. pdf
Bias correction methods: Several methods of combining climate model data with baseline observations to produce scenarios of daily temperature and precipitation variability in the future have been tested using regional climate model simulations from the ENSEMBLES project. A cross-validation approach suggests that (i) quantile-quantile type bias correction methods as a whole have the best potential to provide plausible daily time series and statistics of future temperature and precipitation climate, but that (ii) the methodological uncertainty may be best dealt with by using several well-performing delta change and bias correction methods simultaneously.
Hydrological modelling: Simulations of present-day hydrology have been started with the HYPE model developed at the Swedish Meteorological and Hydrological Institute. Next, hydrological scenarios for the future will be developed by replacing the present-day temperature and precipitation input of HYPE with temperature and precipitation scenarios based on bias-corrected ENSEMBLES regional climate model simulations.
Publications and conference presentations:
Räisänen, J., 2012: How to make projections of daily-scale temperature variability in the future: a cross-validation study using the ENSEMBLES regional climate models. International Conference on End User Needs for Regional Climate Change Scenarios, Kiel, 8 March 2012. pdf
Räisänen, J. and O. Räty, 2012: Projections of daily mean temperature variability in the future: cross-validation tests with ENSEMBLES regional climate simulations. Climate Dynamics. DOI: 10.1007/s00382-012-1515-9. pdf [
Räty, O., 2012: Cross-validation of projection methods for daily mean temperature and precipitation. Sharp statistical tools in climate science, a workshop for participants in Nordic Centers of Excellence, Charlottelund, 17 October 2012. Poster. pdf
Hydro power: Owing to maternity leave this segment of the study started in earnest in September 2012. The HYPE hydrological model system has been acquired from SMHI in co-operation with Helsinki University. Also co-operation with VTT electricity market modellers is developing. First explorations into real options based modelling applications have been made.
Urban real estate: A GIS based dataset has been created with data on 330000 dwelling prices in selected Finnish cities and many characteristics of the involved dwellings covering the period 1970-2011. To this is added spatial information on nearness to water, (urban) green, distance to main city centre, and access to transport services. Addition of high resolution observed climate data and of flood risk areas is in process. A large part of hedonic price estimations is carried out, which paves the way for building an urban simulation model with special reference to ecosystem services and appraisal of adaptation measures. The work entails close co-operation with the HENVI ENSURE project.
Publications and conference presentations:
Votsis, A., Nurmi, V., & Perrels, A. (2013): Spatial effects of ecosystem service variation on urban real estate value under a changing climate. ECCA: European Climate Change Adaptation Conference 2013, p. 113-114. Directorate-general for Research Innovation, European Commission. pdf
Faehnle, M., Söderman, T., Schulman, H., Gabrych, M., Perrels, A., Votsis, A., Setälä, H., Yli-Pelkonen, V., Hakala, A., Tani, S., Tyrväinen, L., Välimaa, I., Niemelä, J., Lehvävirta, S. Ecosystem services in urban planning: scale-sensitive integration of interdisciplinary knowledge, Land Use Policy [submitted March 2013].
Votsis, A. 2012. Modelling the formal structure of the urban built environment under conditions of climate stress, Applied Urban Modelling: Assessing Pathways Towards Energy Efficient and Climate-Wise City Regions, University of Cambridge, May 2012. Poster. pdf
Votsis, A. 2012. Planning a sustainable and climate-proof built environment: the special case of real estate value formation and residential qualities, Second Nordic international conference on climate change adaptation, Aug 2012. Poster & abstract in conference proceedings. pdf
Nurmi, V. 2012, Green roofs as an urban adaptation tool – Cost-benefit analysis, Second Nordic international conference on climate change adaptation, Aug 2012. Poster & abstract in conference proceedings. pdf
Votsis, A. 16.12.2012. Modeling the effects of ecosystem services on the formation of urban real estate value: a spatial econometrics and geoinformatics approach. Asumisen talous II – Workshop, VATT & Helsingin Yliopisto. pdf
Perrels, A.: 16.3.2012 – Valuation of ecosystem services in urban areas: now or later somebody may pay for it – somehow, luento osana HENVI luentosarjasta "Rethinking urban sustainability – Ecosystem services as treasures for the future", Helsinki. pdf
Nurmi, V., Votsis A., Perrels A. & Lehvävirta S. 2013. Cost-benefit analysis of green roofs in urban areas: case study in Helsinki. Finnish Meteorological Institute Reports 2013:2. Helsinki. 58 pp. pdf
About every 6 months a RECAST workshop has been held in which new results were presented and next steps discussed. All partners have actively participated in all workshops, often with several presentations, whereas also presentations from co-operating projects (in VTT & FMI) were presented. Networking is expected to intensify as the emphasis shifts to impact analysis.
Various researchers of RECAST have contributed to the Synthesis Report of the national climate change adaptation programme (ISTO)3, which provides a state of the art of climate change impacts and adaptation knowledge relevant for Finland.
The 2nd Nordic International Climate Change Adaptation Conference 29-31.8.2012 in Helsinki was kindly supported by the Academy's FICCA programme. Various RECAST researchers were active in the organisation and in paper contributions for the conference.
1 Meehl, G.A. and co-authors (2007), Global Climate Projections. Climate Change 2007: the Physical Science Basis, S Solomon et al., Eds., Cambridge University Press, pp 747-845.
2 Makkonen, L., Ruokolainen, L., Räisänen, J. & Tikanmäki, M., 2007: Regional Climate model estimates for changes in Nordic extreme events. Geophysica 43 (1-2): 19-42; Jylhä, K., Ruosteenoja, K., Räisänen, J., Venäläinen, A., Tuomenvirta, H., Ruokolainen, L., Saku, S. ja Seitola, S., 2009. Arvioita Suomen muuttuvasta ilmastosta sopeutumis-tutkimuksia varten. ACCLIM-hankkeen raportti 2009.
3Ruuhela, R. (Toim.), 2012. Miten väistämättömään ilmastonmuutokseen voidaan varautua? Yhteenveto Suomalaisesta sopeutumistutkimuksesta eri toimialoilla. MMM, 176 s.