09 October 2008

Update of the ENSEMBLES RT6 webpage

An update of the RT6 ENSEMBLES webpage has been done: here
The template has changed
The "news" section has been updated
A section Document and Download has been added.
In this section the RT6 partners can find informations on how to access the datas
(few shell scripts are uploaded to retrieve the files). Few documents and usefull links concerning
various climate data portals and freeware to perform the analysis are available as well.

Validation of ENSEMBLES/DEMETER seasonal forecasts over the Sahel: Intraseasonal features

EMS conference in Amsterdam (29/09 - 03/10/2008)

The Sahel is the region of the globe which has experienced the most severe drying, from 1970 to 2000, with dramatic social and economic impacts. As a consequence, forecasting rainfall over West Africa at seasonal time scales became essential regarding to impacts in terms of food, health and security managements since the 1970’s.
One of the aims of the recent initiated AMMA (African Monsoon Multidisciplinary Analysis) project is to improve the prediction of the West African Monsoon (WAM) system and its impacts on West African nations. In parallel, within the European DEMETER and ENSEMBLES projects framework, a well-validated European coupled multi-model ensemble forecast system for reliable seasonal to interannual prediction has been developed. Coordinating studies on seasonal prediction between ENSEMBLES and AMMA participants became obvious from the first AMMA/ENSEMBLES meeting that took place in Bamako, Mali.
Thus, in this paper we propose to both validate ENSEMBLES and DEMETER seasonal forecast simulations over the Sahel, with respect to different reference observation data sets during the monsoon period (from July to September) for a common period (1991-2001). An overview of the performance of the different models participating in the projects in capturing the mean features of the WAM, as well as of the multi-model hindcasts is achieved using typical indices, maps, determinist and probabilistic scores commonly used in seasonal forecast studies. Preliminary results highlight common rainfall bias as simulated by coarse resolution GCM, namely overestimation of precipitation over the high mountains (Ethiopia plateau) and underestimation over the low ones (Cameroon mounts, Senegal coast). Other common bias (similar to the ones highlighted in the CMIP3 IPCC coupled simulations) can be shown for relevant SST areas (which are strongly related to rainfall interannual variability over the Sahel), namely a warm bias over the Gulf of Guinea and the ENSO (eastern Pacific) region. Based on a perfect model approach, rainfall potential predictability (PP) is estimated. Strong rainfall PP values can be shown over the Guinea Coast whereas the predictability is relatively weak over the Sahel. Moreover, the model rainfall forecasts seem to be more skilful over the Guinea Coast and the tropical Atlantic Ocean than the Sahel.
The Impact Studies community (agriculture, health....) have expressed a significant need in terms of forecasting intra-seasonal features of the WAM (onset date of the monsoon, occurrence of dry spells during the rainy season...). The performance of DEMETER/ENSEMBLES hindcasts in reproducing these features will be investigated with respect to both ERA40 and NCEP reanalysis.
Similarities and divergence points between DEMETER and ENSEMBLES hindcasts system performance over sub-Saharan Africa will then be discussed as a conclusion. A discussion will also be done about the selected time period. Namely, is 10 year model climate meaningful to build significant statistical results (mean, variance, etc) over the Sahel? Development strategies to improve the model scores will be suggested as perspectives.

Associated presentation:

Mapping the effects of climate change on bluetongue transmission in Europe

Conference in Bangkok (Thailand) and Paris

Helene Guis123, Cyril Caminade4, Andy Morse4, François Roger2, Matthew Baylis1

1 Lucinda (Liverpool University Climate and Infectious Diseases of Animals Group), Liverpool University, UK
2 AGIRs (Animal and Integrated Risk Management Unit), Cirad, France
3 TETIS (Territories, Environment, Remote Sensing and Spatial Information Unit), Cirad, Cemagref, Engref, France
4 Department of Geography, Liverpool University, UK

Bluetongue (BT) is an arboviral disease of ruminants which emerged in Europe in 1998 and has, since then, caused an unprecedented series of epizootics of major economic consequence. Two distinct epidemiological events underlie this emergence: the northward expansion of the Afro-asian midge Culicoides imicola, probably under the influence of climate change; and the involvement of indigenous European Culicoides of the Obsoletus and Pulicaris groups.
In order to assess the effects of climate change in the distribution of BT in Europe, the basic reproduction number R0 of BT was modelled by a unique integration of epidemiological models with state-of-the-art climate models. This approach allows us to map R0 throughout Europe on an annual basis under past, present and future conditions simulated using several different climate models, with outputs in terms of model means and uncertainties
R0 was computed for a population of two hosts as sheep and cattle have different epidemiological roles in the transmission of BT (the latter being less affected by the disease but presenting a long viraemia) and for both the exotic (C. imicola) and indigenous vectors.
Climatic data for recent past (1961-2000) and future (1950-2050) periods was provided by the ENSEMBLES European project at a spatial scale of 25*25 km. For the recent past, improved regional climate simulations were produced by running a subset of four regional climatic models with the most realistic boundary conditions (ERA40 reanalysis) and external forcing. For the future conditions, simulations were carried out by running three regional climate models forced at their boundaries by a general circulation models forced by the IPCC’s (Intergovernmental Panel on Climate Change) Special Report on Emissions Scenario (SRES) A1B (integrated world with a balanced emphasis on all energy sources).
This modelling approach was carried out in three steps to assess the effects of climate change on each of the components of the BT epidemiological cycle: i) viral replication only, ii) viral transmission taking into account host distribution and iii) the combination of the viral, host and vector components. Results show the coherence between past anomalies in R0 and past incursions of Culicoides-borne diseases in Europe and highlight the fact that the vector component is both the most critical and yet the least well-defined one.

Here is the associated presentation: