Linear and Non-Linear Approaches for Statistical Seasonal Rainfall Forecast in the Sirba Watershed Region (SAHEL)
Abstract
:1. Introduction
2. Review of the Main Drivers of the Sahelian Rainfall Variability
3. Materials and Methods
3.1. Study Area
3.2. Climate and Atmospheric Data
Station number (code) | Station name | Longitude (degrees: °) | Latitude (degrees: °) | Country |
---|---|---|---|---|
320006 | Torodi | 1.80 | 13.12 | Niger |
320002 | Tera | 0.82 | 14.03 | Niger |
320004 | Tillaberi | 1.45 | 14.20 | Niger |
320005 | Gotheye | 1.58 | 13.82 | Niger |
200082 | Boulsa | −0.57 | 12.65 | Burkina Faso |
200026 | Dori | 0.03 | 14.03 | Burkina Faso |
200085 | Bogande | 0.13 | 12.98 | Burkina Faso |
200048 | Dakiri | −0.27 | 13.30 | Burkina Faso |
200024 | Gorgadji | −0.52 | 14.03 | Burkina Faso |
200086 | Piela | −0.13 | 12.70 | Burkina Faso |
200047 | Tougouri | −0.52 | 13.65 | Burkina Faso |
(a) Zonal Wind and Meridional Wind
(b) Air Temperature
(c) SST
(d) SLP
(e) RHUM
3.3. Selection of Predictors and Optimal Lag Time
Parameter | Units | Level | Reference Data | Spatial coverage | Regions of the Predicto rs | Temporal Coverage |
---|---|---|---|---|---|---|
Sea level pressures (SLP) | Pa/s | 1000 hPa | NCEP 2 | 2.5° × 2.5° grid 15N–45S, 60W–10E | Atlantic ocean | 1979/01/01 to 2013/08/31 |
Air temperature (AirTemp) | °K | 1000 hPa | NCEP 2 | 2.5° × 2.5° grid 20N–15S, 120E–70W | Pacific ocean | 1979/01/01 to 2013/08/31 |
Meridional wind (VWND) | m/s | 1000 hPa | NCEP 2 | 2.5° × 2.5° grid 90N–90S, 0–180W | Sahel (Easterly jet) | 1979/01/01 to 2013/08/31 |
Zonal wind (UWND) | m/s | 1000 hPa | NCEP 2 | 2.5° × 2.5° grid 30N–25S 10W–10E | Sahel (Easterly jet) | 1979/01/01 to 2013/08/31 |
Relative humidity (RHUM) | % | 1000 hPa | NCEP 2 | 2.5° × 2.5° grid 40N–30N, 20E–35E | Mediterranean basin | 1979/01/01 to 2013/08/31 |
Sea surface temperature (SST) | °C | Surface | NOAA NCDC ERSST version3b | 2° × 2° grid 39N–15S, 60W–15E | Atlantic ocean | 1854/01/01 to 2013/08/31 |
Climatic research unit rainfall (CRU) | mm | Surface | CRU | 0.5° × 0.5° grid 2°W–2°E, 10°N–15°N | January 1901 to December 2012 |
- (a)
- For each year Y that the predictor was available,
- (i)
- The predictor of year Y-1 was removed from the predictor grid;
- (ii)
- The rainfall of year Y was removed from the rainfall data set;
- (iii)
- A coefficient of correlation (R) is used to screen the remaining predictor data: a correlation analysis between the predictor at each grid point and the rainfall was computed and its level of significance (P-value <0.05) was assessed. Once the correlation was not significant, the grid point was discarded. The remaining grid points were then ordered decreasingly;
- (iv)
- Afterward, a principal component analysis (PCA) was applied on the retained predictor gridded data from the previous step to reduce the number of predictors;
- (v)
- Since PCA gave rise to more sets of new predictor data, a stepwise regression (5% confidence interval) was used to keep only grid points with high predictive power;
- (vi)
- A linear regression was fitted between the predictors and precipitation time series;
- (vii)
- The fitted linear regression was used to simulate the rainfall of year Y. If predictor and rainfall were in the same year (Year Y), only predictor and rainfall time series for that year were removed in the first step.
- (b)
- Then, the coefficient of determination (R2), Nash-Sutcliffe coefficient (Nash), and Hit-Rate scores (HIT) were computed to estimate the model's performance.
3.4. Linear Approach
3.5. Non-Linear Approach
3.5.1. Non-Linear Principal Component Analysis
3.5.2. Feedforward Neural Network
4. Results and Discussions
4.1. Selected Predictors and Lag Time Period
4.2. Seasonal Rainfall Forecast
PREDICTOR | NMAX* | R2 | Nash coef. | HIT Score | Best period M1-M2** | Lag period |
---|---|---|---|---|---|---|
Sea Level Pressure (SLP) at 1000hPa | 50 | 0.48 | 0.46 | 60.71 | 17-18 | 0 |
Relative Humidity (RHUM) at 1000hPa | 80 | 0.58 | 0.52 | 64.29 | 10-10 | 8 months |
Air Temperature (AirTemp) at 1000hPa | 10 | 0.530 | 0.527 | 67.86 | 1-4 | 7 months |
Meridional Wind (VWND) at 1000hPa | 170 | 0.31 | 0.28 | 53.57 | 5-5 | 8 months |
Zonal Wind(UWND) at 1000hPa | 190 | 0.33 | 0.324 | 71.43 | 11-11 | 7 months |
Sea surface temperature (SST) | 30 | 0.43 | 0.34 | 58.54 | 3-6 | 12 months |
PREDICTOR | R2 | NASH | HIT score | Lag time Period |
---|---|---|---|---|
Sea Level Pressure (SLP) at 1000hPa | 0.32 | 0.31 | 53.57 | 9 months |
Relative Humidity (RHUM) at 1000hPa | 0.36 | 0.36 | 53.57 | 7 months |
Air Temperature (AirTemp) at 1000hPa | 0.46 | 0.45 | 60.71 | 8 months |
Predictors | R2 | Nash | HIT score (%) | Lag time (months) |
---|---|---|---|---|
AirTemp | 0.26 | 0.20 | 48.24 | 4 |
RHUM | 0.18 | 0.10 | 29.12 | 4 |
SLP | 0.21 | 0.09 | 18.03 | 2 |
SST | 0.18 | 0.044 | 11.49 | 5 |
5. Conclusions
Acknowledgements
Author Contributions
Conflicts of Interest
References
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Djibo, A.G.; Karambiri, H.; Seidou, O.; Sittichok, K.; Philippon, N.; Paturel, J.E.; Saley, H.M. Linear and Non-Linear Approaches for Statistical Seasonal Rainfall Forecast in the Sirba Watershed Region (SAHEL). Climate 2015, 3, 727-752. https://doi.org/10.3390/cli3030727
Djibo AG, Karambiri H, Seidou O, Sittichok K, Philippon N, Paturel JE, Saley HM. Linear and Non-Linear Approaches for Statistical Seasonal Rainfall Forecast in the Sirba Watershed Region (SAHEL). Climate. 2015; 3(3):727-752. https://doi.org/10.3390/cli3030727
Chicago/Turabian StyleDjibo, Abdouramane Gado, Harouna Karambiri, Ousmane Seidou, Ketvara Sittichok, Nathalie Philippon, Jean Emmanuel Paturel, and Hadiza Moussa Saley. 2015. "Linear and Non-Linear Approaches for Statistical Seasonal Rainfall Forecast in the Sirba Watershed Region (SAHEL)" Climate 3, no. 3: 727-752. https://doi.org/10.3390/cli3030727