EGU2012-8848

1. EGU2012-8848 Regional and sub-regional climate simulations over Sub-Saharian African regions and the influence on the heat waves hazard E. Bucchignani (1), P. Mercogliano (1), M. Montesarchio (1), P. Capuano (2) (3), M. Sellerino (2), A. Di Ruocco (2), and W. Kombe (4) (1) C.M.C.C., Impacts on Soil and Coast, Italy (e.bucchignani@cira.it), (2) AMRA S.c. a r.l., Napoli, Italy, (3) University of Salerno, Fisciano, Italy, (4) ARDHI University, Dar Es Salaam, Tanzania 5. Heat Waves 1. Introduction 3. Dar Es Salaam case The number of hot days per year (Fig. 7a) shows an increase of heat wave recurrence from 1961 to 1995. The successive period 1996-2000 shows a minimum in the recurrence of the phenomenon, but the last period 2001-2011 has experienced a strong increase in the Heat Wave occurrence. Hot days number evaluated by observed and modeled data are also compared. The forecasted period 2011-2050 shows a strong increase in the heat waves occurrence Africa is considered a continent particularly vulnerable to the effects of climate change but the development of reliable predictions of future climate change is complicated by the lack of accurate baseline data on current climate and the complexity of drivers of African climate variability (i.e., El Niño/Southern Oscillation, land cover change). In the framework of the EU-FP7 CLUVA project (CLimate change and Urban Vulnerability in Africa), regional projections of climate change at high spatial resolution, based on the IPCC RCP4.5 and RCP8.5 scenarios have been performed for selected areas surrounding five African cities of interest (i. e. the project test cities). Climate simulations, spanning over the period 1950-2050, have been compared with large scale observed data (CRU) and with local data provided by the municipalities of the test cities, in terms of two-metre temperature and precipitation. The variations of the fundamental climate parameters will constrain different hazard at different time-scales. In the framework of the assessment of the environmental impacts and the risks of climate changed induced hazards likely to affect urban areas at various time frames, we analyzed a dataset of daily maximum temperature from Dar Es Salaam (Tanzania) in the period 1961-2000 to evaluate the generation of heat waves, defined following a peak over threshold approach, and the evolution in the extreme warm conditions up to 2050. (a) Fig. 3 shows the map of the bias of 2-meter temperature, (averaged over the time period 1971-2000) for DJF (a) and JJA (b) obtained by comparing the CLM solution with CRU dataset. Fig. 4 shows the seasonal cycle of temperature, respectively for CLM solution (with and without bias correction) and for observed data. Heat wave duration (Fig. 7b) is a key element to evaluate the societal heat wave impacts, reducing the capacity of adaptation. The maximum length (days) of heat wave episodes per year shows a mean value of 4-5 days with some peak in 1974, 1987, 1994 and 2009. Successively, there is a clear increase in the average duration of heat wave with peaks of 18-19 days. (b) Fig. 4 Fig. 7a,b Fig. 3 (a) (b) Heat wave duration and hot days number are strictly correlated (Fig. 8) showing that the temperature rise could generate not only an increase of heat waves number but mainly a longer average duration, that can strongly affect the resilience capacity of the population, particularly the elder people. 2. Regional and sub-regional climate simulations over Sub-Saharian African regions Climate projections are generally conducted using global models, which provide information around the whole Earth surface. However, they are generally unsuitable to simulate the climate of very limited areas, since they are characterized by resolutions generally around or coarser than 100 km, which is too poor for impact studies on areas where many important phenomena occur at spatial scales lower than 10 km. The usage of a Regional Climate Model (RCM) with a horizontal resolution of about 10 km can be a useful tool for the description of the climate variability on local scale. The CLM is the climate version of the COSMO model, which is the operational non-hydrostatic mesoscale weather forecast model developed by the German Weather Service. Successively, the model has been updated by the CLM-Community, in order to develop also climatic applications. A huge variety of applications of the model system exists, covering high resolution simulations of mega-cities to medium resolution simulations of continents, tropical to arctic latitudes, paleo studies, the recent past and climate scenarios for the 21st century. This makes it highly relevant for climate science and for climate mitigation and adaptation politics. Fig. 5 shows the time series of 2-meter temperature averaged over a square area (length 40 km), centred on Dar Es Salaam and obtained with both the considered scenarios. An increase of temperature is projected, especially employing RCP8.5 scenarios. Fig. 5 Fig.8 Fig. 9 The frequency distribution plot of hot days duration (Fig. 9) for five separate bi-decadal periods, according to the legend of top right corner, shows the temporal change of heat wave characteristics. This distribution have became longer tailed with time. The number of events of the maximum length lasting 5 days could increase from 3 to 24 over 100 years (from 1950-70 to 2030-2050). 4. Heat Waves Heat wave generally refers to periods of exceptionally warm temperatures, but there is no universal technical definition (Robinson, 2001). The impacts of heat waves on the society are determined also by temporal duration (Stephenson, 2008), in addition to their frequency, in fact the capacity of adaptation can be reduced with prolonged exposure to high temperature and humidity. For this specific activity, the utility of COSMO-CLM is due to the fact that the model contains physical parameterizations (cloud, precipitations, moist convection radiation) suitable for African areas. In the present work the climate predictions have been obtained forcing COSMO-CLM with the CMCC-MED global model output. The IPCC emission scenarios considered are the RCP4.5 and RCP8.5. A heat-wave is defined, here, as a period in which the maximum temperatures are over the 90th percentile of the monthly distribution for at least three days, fixing a minimum threshold for Tmax to exclude months with less hot temperature (similar to winter time), that for Dar Es Salaam was fixed to 32°C. The 90th percentile has been evaluated over a climatological base period (1961-1990). 6. Conclusions Regional Climate Model with a horizontal resolution lesser than 10x10 km can be a useful tool for the description of the climate variability on local scale, suitable for impact studies. We evaluate regional climate projection for some African areas, particularly for Dar Es Salaam. We use the climate simulations to evaluate the changes in the heat wave occurrence. The combined change in the mean and variance of CRFD has contributed to an increase in the frequency of hot days and in their duration. Projected future warming in the Dar Es Salaam area shows a further increase in the heat waves parameters. The expected persistence of long-lived heat waves lasting approximately 1.5-2 weeks is clearly longer with respect to the climatological period (1961-1990). During 100 years, short lived but more intense waves are more than doubled in duration. It is evident the needs for the national health services to develop strategies for the mitigation of the heat wave effects, to enhance the resilience of the population, particularly the elder people. A rectangular limited domain centred over the city of Dar Es Salaam has been considered (Fig.1). It has been discretized using a spatial resolution of 8 km, employing a computational grid with 95 x 135 grid points and 40 vertical levels. The time resolution is 50 sec. Fig. 2 shows the Carbon Dioxide concentration time series used to force the model, according to the different scenarios. Fig. 6a Fig. 6a shows the comparison between the observed and bias-corrected modelled cumulative relative frequency distribution (CRFD) for daily Tmax. The differences are partly due to an effect of the incompleteness of observed dataset. Fig. 6b shows CRFD change over time, for each of ten independent periods, according to the legend in the top right-hand corner. Taking into account for the data coverage, it is clear that the Tmax peak increases from 30.4°C (1961-70) to 31.5° (2001-2011). In addition all the distribution is moving towards higher temperature in the last decades. Fig. 1 References Stephenson, D. B. (2008). Definition, diagnosis, and origin of extreme weather and climate events. In Diaz, H. and Murnane, R., editors, Climate extremes and society, chapter 1, pages 11–23. Cambridge University Press; Robinson P. J. (2001), On the Definition of a Heat Wave, J. Appl. Meteor., 40, 762-775; Rockel B., Will A., Hense A., 2008. The regional Climate Model COSMO-CLM (CCLM), Meteorologische Zeitschrift, 17 (4): 347-348. Fig. 6b Fig. 2