DATA PRODUCTION

Climate impact indicators
Global essential climate variables/indicators used

This case study used a ECMWF seasonal forecast ensemble (starting with  system 5) from 1993 to 2015 (hindcast) and 2018 (forecast), initialized on each month, available in the CDS catalogue. The climatic variables considered are daily precipitation, mean and extreme temperatures (minimum and maximum) at the seasonal scale. To properly characterize the initial conditions of the model, the model was run over the historical period with the WFDEI re-analysis data from 1979 to 2013. Comparative analysis were also carried out by considering the historical streamflow (river discharge station data from 1990).

Regional/local indicators used and produced

The current seasonal forecasts are delivered by the PRESAO process (Seasonal forecasts in West Africa). Each year, a consensual seasonal forecast on rainfall and river discharge for the West-African region is delivered.

Global data to regional/local scale

The main indicators produced are:

  • Cumulative rainfall map for the rainy season (May to November);
  • Map showing the rainfall situation of the season (above, near or below normal considering 1993-2015 as reference period);
  • Graph of the mean seasonal precipitation over the basin compared to the reference period (1993-2015);
  • Map showing the hydrological situation of the season (above, near or below normal considering 1993-2015 as reference period);
  • Graph of the mean seasonal stream flow over the Niger Basin compared to the reference period (1993-2015);
  • Graphs comparing monthly streamflows of 2018 to those of the reference period (1993-2015).

Step 1

  • Data collection: The data collected include ECMWF seasonal forecast ensemble (system 5) available in the CDS catalogue, WFDEI-reanalysis data, river discharge station data from 1907 to 2013;
  • Quality assessment: Climate forcing data (S5 system 5 and WFDEI) were on regular grids and it was first necessary to analyze their consistency once estimated on the sub-basins. Considering S5 seasonal forecast ensemble initialized on May 1st of each year, the season covers the period from May to November of each year. Over this period, the data were compared to WFDEI-Reanalysis data. Maps have been developed to visually appreciate the quality of the data;
  • Bias adjustment and preparation of all datasets to be used in the HYPE forecasting: Bias adjustment used historical WFDEI re-analysis data to readjust the ECMWF system 5 seasonal forecast ensemble. The quantile-quantile method was used for bias correction;

Step 2: Forecasting river discharge with HYPE for Niger River: Streamflow were forecasted by forcing the Niger-HYPE model with ECMWF seasonal climate forecasts at the scale of the rainy season in the Sahel (May-November). To properly characterize the initial conditions of the hydrological model, the model was run over the historical period with the WFDEI re-analysis data. The hydrological forecast were done by considering first the ECMWF system 5 raw seasonal forecast and the ECMWF system 5 bias adjusted seasonal forecast;

Step 3Interactions with clients at the regional level took place in december 2018 through physical meeting;

Step 4: The assessment of the predictive capacity is including dry spells, accumulated volumes, extreme wet and dry events (e.g. maximum daily, 3-day and weekly rainfall and discharge during the season), is assessing predictive capacity at local scale and comparing the different seasonal forecasting approaches;

Step 5The ensembles are revisited by putting less weight on low-performing ensemble members.


AGRHYMET Regional Centre

 

 

Poster displayed at the Kick–Off meeting, 7/8 September 2017, Norrköping, Sweden


Floods caused by the Niger River overflow in 2012