OVERVIEW OF THE MICE PROJECT
a. Objectives
The EU-funded project MICE (Modeling the Impacts of Climate Extremes) seeks to identify the likely changes in the occurrence of extremes of rainfall, temperature and windstorm due to global warming, using information from climate models as a basis, and to study the impacts of these changes in selected European environments. The objectives of MICE are:
* to identify and catalogue extremes in observed and modelled climate data,
* to evaluate the extent to which state-of-the-art climate models can successfully reproduce the present-day occurrence of extremes,
* to analyse future changes in climate extremes using a range of statistical techniques including Extreme Value Theory,
* to assess the impact of these changes in extremes on selected activity sectors,
* to communicate the results to stakeholders.
By looking at results from a number of climate model experiments, MICE will explore the uncertainties associated with predicting the future occurrence of extremes. These experiments will be selected to look at the effects of changing the model resolution (comparing regional and global climate model experiments), of using different scenarios of atmospheric greenhouse gas concentrations to force the models (which in turn reflect different visualizations of economic futures), and of using different model ensemble members (analysing relationships between natural variability and forced change). The impacts sectors to be investigated range from those where the relationships between climate and impact are well understood (agriculture, energy use) and those where the potential implications of climate change are only just beginning to be appreciated (winter sports and Mediterranean beach holidays). MICE will end with a large workshop bringing together scientists and end users from a range of sectors likely to be affected by changing occurrences of climate extremes.
b. Workpackages
MICE has six work packages:
(1) analyses of extremes' occurrence in climate models:
* Extraction of climate extremes for analysis
* Time series characteristics of extremes under climate change
* Spatial patterns of extremes under climate change Types of extremes to be analysed: principally temperature, for example:
* Number of days above 25oC in temperate locations, above 30oC in Mediterannean.
* Number of days below 0oC in south and west, below -10oC in east and north
* Date of first autumn frost
* Date of last spring frost
* Percentile exceedances: 90th, 95th
(2) Impacts evaluation
* Quantitatively modelling impacts of changes in climate extremes on activity sectors
* Expert-judgement based approaches to understanding impacts of changes in climate extremes on activity sectors
* Co-ordination and dissemination
c. European dimension of the problem
MICE addresses issues related to the impacts of global warming at the European scale, in particular the occurrence of extreme climatic events such as windstorm and floods. These climate changes will vary on a regional basis. For example, the latest GCM experiments suggest that rainfall will increase across most of the European Union in winter as a result of global warming. The exceptions lie on the Mediterranean fringe, with reduced rainfall in southern Spain, Italy and Greece. In summer, however, rainfall will be reduced almost everywhere, apart from Finland and northern Sweden. This example demonstrates that climate change and the associated impacts are of concern to the whole community of European nations. Contrasts exist in the likely future experience of climate change, both internationally and within Europe. These contrasts, when combined with the distinctive character of European societies, cultures and economies, mean that a European-wide programme of action is required to deal with the impacts of climate change. The MICE project contributed to this by:
* Bringing quantitative techniques to the analysis of climate model output with respect to impacts on selected activities within Europe.
* Concentrating on the study of extreme climate events and their impacts (the most severe impacts are expected from changes in the occurrence of extreme events).
d. Contribution to policy design or implementation
MICE looks at future impacts of climate change, especially related to extreme events. It concentrates on four ecosystem/activity sectors: forestry and agriculture, energy supply, tourism, and insurance (windstorm and flood damage).
Forestry: Forests are vulnerable to damage by windstorm and fire, future extremes of which are studied in MICE. European policies related to forestry include the EU Biodiversity Strategy, Natura 20000 and the implementation of the Climate Change Convention. (See Com(1998) 649, Communication from the Commission to the Council and the European Parliament on a Forestry Strategy for the European Union).
Agriculture: Ongoing reform of the Common Agricultural Policy (CAP) presents major opportunities to make key areas of European policy more sustainable. The European Consultative Forum on the Environment and Sustainable Development has identified five conclusions about kinds of policies needed for successful reform of CAP. These include the need to protect and perpetuate local diversity and environmental quality. MICE will concentrate on climate impacts in Mediterranean regions. Reforms of agricultural production to achieve sustainability can only be successful when the potential for climate change is understood, especially in the agricultural systems of the Mediterranean, already under stress from drought and excessive heat.
Energy policy: European energy policy is focussed on three objectives: overall competitiveness, security of supply and environmental protection (see COM(95)682 An Energy Policy for the European Union). In the implementation of future policies, it is necessary to understand not only changes in the social and economic context of energy supply and demand, but also changes in climate. Contrasting changes in regional energy use, especially the effect of extremes such as severe heatwaves, are explored in MICE.
Tourism: Article 3u of the Amsterdam Treaty included �measures in the sphere of tourism� in the list of Community activities foreseen in support of the Community�s overall objectives. Given the obvious importance of tourism at the European scale, and the sensitivity of this sector to weather, it is important to understand the possible impacts of climate change on Mediterranean beach holidays and winter sports. Floods and windstorm insurance and civil protection. Community action is administered by the Civil Protection and Environmental Emergencies Unit of DG Environment. The roles of this Unit include (a) enhancement of cooperation between Member States, (b) support and supplementation of national efforts with regard to disaster prevention and preparedness, and (c) enhancement of public awareness. Information on the regional potential for change in flood and windstorm frequency resulting from climate change, planned as deliverables from MICE, will contribute greatly to this role.
VARIATION OF EXTREME CLIMATE EVENTS ALONG 35o NORTH IN THE MEDITERRANEAN: RESULTS FROM THE MICE PROJECT
a. Research plan
It is widely recognized that changes in the severity and frequency of extreme climate events, such as windstorm and heatwaves, are likely to be more important than changes in the average climate. The climate model output used in this study is from HadCM3, a global model run at the Hadley Centre UK, with a resolution of 2.5o latitude x 3.75o longitude. Its resolution is quite coarse and Greece in this model, which forms the centre of this research work is covered by only 2 gridboxes.
As participants in MICE, we have carried out analyses of extremes with the following objectives:
(i) to compare modeled and observed data in the Eastern Mediterranean so as to evaluate the ability of the global climate model HadCM3 to reproduce the occurrence of extreme events and
(ii) to analyze model output with respect to future changes in the occurrence of extremes along 35oN in the Mediterranean. Our analysis seeks to determine the spatial and temporal patterns of extreme event occurrence along the above mentioned latitude band. For the comparison of gridded and station data, we selected the HadCM3 cells that cover Greece and compared with meteorological observations from two representative stations for the period 1961-1990. This comparison is more qualitative since the spatial resolution of HadCM3 does not allow a direct comparison with station data. It aids, however, to determine whether the model exhibits a cold or warm temperature bias in its continental or marine gridboxes respectively. Future changes in extreme event occurrence have been analyzed using two different forcing scenarios from HadCM3 global climate model. We separated land and sea gridboxes and examined the variations of future extreme events related to temperature, wind and precipitation up to 2100 along the 35oN latitude band in the Mediterranean .
b. Model evaluation - Comparison of station data with HadCM3 gridboxes
We used output from the global climate model HAdCM3 from the Hadley Centre to perform an evaluation of the model with observational data for the period 1961-1990. We selected two gridboxes in Greece, one continental (North Greece) and one sea gridbox (South Greece) and compared with a North Greek met station (Salonica/MIKRA) and a South Greek met station (Athens/NOA). The thin lines in the graphs depict the variation of a certain parameter from year to year whereas the thicker lines present the 5-year running average of the parameter.
Conclusions for HadCM3 model evaluation against met station data for the Greek territory
1. The land gridbox captures well the summer extremes although a bit hotter than reality. It is too cold regarding low temperatures. It exhibits a very strong continental character not encountered in station data.
2. The sea gridbox has too mild a character. No temperatures over 30oC in the summer nor below 0oC in winter.
3. Athens station (NOA) data resembles more the sea gridbox in winter (temperatures below 0oC are rare) and the land gridbox in the summer (it suffers from heat waves in the summer).
4. Salonika station (MIKRA) data lies somewhere in the middle and does not quite resemble any of the two gridboxes. It is generally milder than the land gridbox but not as mild or hot as Athens (NOA) station.
Conclusions for trends in HadCM3 model output and station data for the period of 1961-1990
* No significant trend in low temperatures and cold extremes
* Slight increase in the number of tropical nights (Tmin>20oC) for Micra, no significant change for model data and Athens (NOA) * Figure 1.
* Considerable increase for the number of days with Tmax>30oC for land gridpoint and Athens (NOA) - Figure 2.
* No considerable increase for the July Tmax exceedances of the 90th percentile
* Slight decrease for the January Tmin exceedances of the 10th percentile (Figure 3)
c. Future variations of extremes along the 35oN in the Mediterranean up to 2100
* To examine the variations of extremes along the 35oN latitude in the Mediterranean, we examined both land and sea gridboxes separately since it would be meaningless to compare a land with a sea gridbox due to their differences in characteristics.
* The study compares two HadCM3 land gridboxes one in North Africa, the other in the Middle East, both adjacent to the Mediterranean sea. In this way, it is possible to visualise the West-East variation of extreme events in the land gridboxes.
* We have also carried out a comparison of sea gridboxes in the Atlantic, the central and East Mediterranean. In this way, it is possible to visualise the West-East variation of extreme events in the sea gridboxes
Conclusions for West-East land gridboxes up to year 2100
* About similar increase in the number of tropical nights (from ~20 in 1960 to ~100 in year2100)
* Sharper increase in the number of heatwaves for Atlantic, more gradual for the East Mediterranean - Figure 4.
* Sharp decline in the number of frost nights for both gridcells (from ~65 to ~25)
* Significant increase in July Tmax exceedances of the 90th percentile (from 5 to 25) for both gridcells
* No changes for the wind percentiles of extremes
Conclusions for West-East sea gridboxes up to year 2100
* sharper increase in the number of tropical nights for Atlantic, more gradual increase for the central and East Mediterranean - Figure 5.
* no change in the number of heatwaves predicted (Tmax>30oC) -no heatwaves expected to occur in the sea gridboxes. The sole exception is the East Mediterranean which shows a small number (~5).
* number of the maximum wind exceedances of the 90th percentile increases for Atlantic but decreases as we enter the Mediterranean - Figure 6.
* precipitation exceedances of the 75th percentile shows a decreasing trend along the 35oN in a uniform manner (from 45 to 35 days-see also map).
References
1) Meehl, G.A., T. Karl, D.R. Esterling, S. Changnon, R. Pielke Jr., D. Changnon, J. Evans, P.Y. Groisman, T.R. Knutson, K.E. Kunkel, L.O. Mearns, C. Parmesan, R. Pulwarty, T. Root, R.T. Sylves, P. Whetton, and F. Zwiers, 2000: An introduction to trends in extreme weather and climate events: observations, socio-economic impacts, terrestrial ecological impacts and model projections. Bull. Amer. Meteor. Soc., 81, 413-416.
2) Parry, M., Rosenzweig, C., Iglesias, A., Fischer, G. and Livermore, M., 1999: Climate change and world food security: a new assessment. Global Environmental Change � Human and Policy Dimensions, 9, S51-S67, Suppl. S.
3) Hewitson, B.C. and Crane, R.G., 1996: Climate downscaling: techniques and application. Clim. Res., 7, 85-95.
4) Wilby, R.L., Hassan, H. and Hanaki, K. 1998: Statistical downscaling of hydrometeorological variables using general circulation model output. J. Hydrol., 205, 1-19.
5) Giorgi, F. and Francisco, R., 2000: Uncertainties in regional climate change prediction: a regional analysis of ensemble simulations with the HADCM2 coupled AOGCM. Climate Dynamics, 16, 169-182.
6) Corte-Real., J., Zhang, X. and Wang, X., 1995: Downscaling GCM information to regional scales: a non-parametric multivariate approach. Climate Dynamics, 11, 413-424.
7) Von Storch, H., Zorita, E. and Cubasch, U., 1993: Downscaling of global climate-change estimates to regional scales � an application to Iberian rainfall in wintertime. J. Climate, 6, 1161-1171.
8) Subak, S., Palutikof, J.P., Agnew, M. and others, 2000: The impact of the anomalous weather of 1995 on the UK economy. Climatic Change, 44(1/2), 1-26.
9) Ulbrich U. and Christoph, M., 1999: A shift of the NAO and increasing storm track activity over Europe due to anthropogenic greenhouse gas forcing Climate Dynamics, 15, 551-559.
10) Ruel, J.C., Quine, C.P., Meunier, S. and Suarez, J., 2000: Estimating windthrow risk in balsam fir stands with the ForestGales model. Forestry Chronicle, 76, 329-337.
11) Keatinge, W.R., Donaldson, C., Cordioli, E. and others, 2000: Heat related mortality in warm and cold regions of Europe: observational study. British Medical Journal, 321, 670-673.
12) Agnew, M.D., and Viner, D., 2001: Potential impacts of climate change on international tourism. Accepted for publication in International Journal of Tourism and Hospitality Research.
13) Maracchi, G. and Costantini, R., 1998: Un Modello Meteorologico pr la Previsione del Rischio d�Incendio Boschivo in Toscana. Proc. III International Conference on Forest Fire Research, Coimbra, 16-20 November 1998.
14) Millán, M. M., Estrela, M. J., and Badenas, C., 1997: Situaciones sinópticas asociadas a la dinámica de incendios forestales en la Comunidad Valenciana. Ecologia, 11, 3-29.
15) Kundzewicz, Z.W., Szamalek, K. and Kowalczak, P., 1999: The great flood of 1997 in Poland. Hydrological Sciences Journal, 44, 855-870.
16) Abegg, B. and Elsasser, H., 1996: Klimaänderung und Wintertourismus in den Schweizer Alpen. In: Geographische Rundschau.
17) Rohrer M. B: and L. N. Braun, 1994: Long term records of snowcover water equivalent in the Swiss Alps- 2. Simulation, Nord. Hydrol., 25, 65-78.
18) Easterling, D.R., Evans, J.L., P. Ya. Groisman, T.R. Karl, K.E. Kunkel, and P. Ambenje, 2000: Observed variability and trends in extreme climate events, a brief review. Bulletin of the American Meteorological Society, 81(3) 417-425.
19) Widmann M. and Bretherton C.S., 2000: Validation of mesoscale precipitation in the NCEP reanalysis using a new gridpoint dataset for the northwestern US. J. Climate, 13, 1936-1950.
20) Wilks, D.S., 1995: Statistical Methods in the Atmospheric Sciences. Academic Press, San Diego.
21) Davison, A.C. and Smith, R.L., 1990: Models for exceedances over high thresholds. J. R. Stat. Soc. B., 52, 393-442.
22) Smith, R.L., J.A. Tawn and S.G. Coles, 1997: Markov chain models for threshold exceedances. Biometrika, 84, 249-268.
23) Coe, R. and R. Stern, 1982: Fitting models to daily rainfall. J. Appl. Meteorol., 21, 1024-1031.
24) Stern, R., and R. Coe, 1984: A model fitting analysis of daily rainfall data (with discussion). J. Roy. Statist. Soc. A147, 1-34.
25) Cheng, E.D.H., 1991: Wind data generator: a knowledge-based expert system. J. Wind. Eng. Ind. Aerodyn., 38, 101-108.
26) Coles, S.G., 1999: Extreme value theory and applications. Lecture notes, with software, University of Bristol. http://www.stats.bris.ac.uk/~masgc/.
27) Onof C, Chandler RE, Kakou A, Northrop P, Wheater HS, Isham V., 2000: Rainfall modelling using Poisson-cluster processes: a review of developments. Stochastic Environmental Research and Risk Assessment, 14, 384-411.
28) Osborn, T.J., Briffa, K.R., Tett, S.F.B., Jones, P.D., and Trigo, R.M., 1998: Evaluation of the North Atlantic Oscillation as simulated by a climate model. Climate Dynamics, 15, 685-702.
29) Christoph, M.; Ulbrich, U., Oberhuber, J.M., Roeckner, E., 2000: The role of ocean dynamics for low-frequency fluctuations of the NAO in a coupled Ocean-Atmosphere GCM. J. Climate, 13, 2536 - 2549
30) Kushnir Y., Cardone V.J., Greenwood J.G. and Cane M., 1997: On the recent increase in North Atlantic wave heights. J. Climate 10, 2107-2113.
31) WASA Group, 1998, �Changing waves and storms in the north-east Atlantic?�, Bulletin of the American Meteorological Society, 79, 741-760.
32) Hurrell J.W. (1995) Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation. Science 269, 676-679.
33) Beniston, M. and Rebetez, M., 1996: Regional behaviour of minimum temperatures in Switzerland for the period 1979-1993. Theoretical and Applied Climatology, 53, 231-243.
34) Trigo, I. Davies, T.D., et al., 2000, �Decline in Mediterranean rainfall caused by weakening of Mediterranean cyclones�, Geoph. Res. Lett., 27, 2913-2916.
35) Cubasch U. (ed), Caneill J-Y., Filiberti M.A. et al., 1997, �Anthropogenic climate change�, Project EV5V-CT92-0123 final report. Office for Official Publications of the European Commission EUR 17466EN Luxembourg, 73pp.
36) Carnell R.E., Senior C.A., & Mitchell J.F.B., 1996, �An assessment of measures of storminess, simulated changes in Northern Hemisphere winter due to increasing CO2�, Climate Dynamics, 12, 467-476.
37) Lambert S.J., 1995, �The effect of enhanced greenhouse warming on winter cyclone frequencies and strengths�, Journal of Climate, 8, 1447-1452.
38) Beersma J.J., Rider K.M., et. al., 1997, �An analysis of extra-tropical storms in the North Atlantic region as simulated in a control and 2xCO2 time-slice experiment with a high-resolution atmospheric model�, Tellus A, 49, 347-361.
39) Zhang Y., & Wang W-C., 1997, �Model-simulated northern winter cyclone and anticyclone activity under greenhouse warming scenario�, Journal of Climate, 10, 1616-1634.
40) Watson, S.J. and Woods, J.C., 1997: Energy. Chapter 7 in Economic Impacts of the Hot Summer and Unusually Warm Year of 1995. Report prepared for the UK Department of the Environment.
41) Dorland, K., 2000: Storm damage analysis in Germany, the UK and the Netherland. Section 5.3 in Final Report of the WISE (Weather Impacts on natural, Social and Economic systems) Project, EU ENV4-CT97-0448.
42) Pielke, R. Jr. and C. W. Landsea, 1998: Normalized Hurricane Damages in the United States:, 1925-95. Weather and Forecasting 13, p. 622.
43) Dorland, K., Tol, R.S.J. and Palutikof, J.P., 1999: Vulnerability of the Netherlands and NW Europe to storm damage under climate change. Climatic Change, 43, 513-535.
44) Troen, I. and Petersen, E.L., 1989: European Wind Atlas. Risø National Laboratory, Roskilde.
45) Perry, A., 2000: Tourism and recreation. Chapter 12 in Assessment of Potential Effects and Adaptations for Climate Change in Europe (The Europe ACACIA Project), EU ENV4-CT97-0531.
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MICE : Modeling the impacts of climate extremes