1. Drought Predictability in Mexico Francisco Muñoz Arriola 1, Shraddhanand Shukla 1, Lifeng Luo 2, Abel Muñoz Orozco 3, and Dennis P. Lettenmaier 1 1 Department of Civil and Environmental Engineering, University of Washington 2 Department of Civil and Environmental Engineering, Princeton University 3 Colegio de Posgraduados American Meteorological Society Phoenix, AZ January 12 th 2009

2. Outline Motivation Mexican Droughts Objectives The University of Washington West-wide Forecast System Drought assessment Soil Moisture Percentile, Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) assessments Conclusions Future Work

3. Physical Features Source: Instituto Nacional de Estadistica e Informatica (INEGI) More than 70% of its surface is considered topographically steep Has the largest biological diversity, natural and agricultural (e.g. corn) found in North America Precipitation regimes dominated by summer events (with different spatiotemporal patterns) Various drought periods along the year

4. 17.81 % 2.05 % 0.52 % 0.01 % 79.62 % 020406080 Drought Hurricanes Rainfall Frozts Hail Source: SAGARPA. 1995-2004 Agricultural Damages by Hydrometeorological Phenomena Great part of the agriculture is unirrigated 44% during the Fall-Winter cycle 84% during the Spring-Summer cycle The largest damages are related to hydromet. Phenomena Interannual differences in the spatial patterns of drought occurrence

5. 2 3 4 1 1.Mexico 2.Northwestern 3.North Central 4.South Droughts in Mexico Great winter drought (3 and 4) – winter and part of the spring – Affects moisture availability for crop seeding – Distribution, same as MSD Mid-summer drought (3 and 4) – Eastern of Sierra Madre Occidental, Central and Southern Mexico – Decrease in rainfall (July-August) – Affects flowering in Mexican unirrigated croplands Pre-monsoonal drought (2) – Spring drought over Northwestern Mexico – Affects water storage and irrigate agriculture Mediterranean drought (2) – Occurs in areas of Mediterranean climates – Affects agriculture and water availability in the Peninsula of Baja California – All over the year except Fall and Winter

6. Research Questions Due to the reduced availability of information regarding drought predictability and given the impacts of this condition in Mexico we aimed to answer the following questions Are there changes in the seasonal predictability of drought given the initial conditions along the year 2007? How drought predictability varies in different parts of Mexico? Are there differences between the Ensemble Streamflow Prediction (ESP) and the Climate Forecast System?

7. OBJECTIVE Evaluate the seasonal drought predictability in Mexico at different sub-domains through the use of the UW Extended West-wide Seasonal Hydrological Forecast System – Apply the ESP and CFS to distinguish differences in drought predictability

8. UW Extended WSHFS and ESP Based on the use ensemble techniques applied to generate forcing data for a Land-surface hydrology model

9. Seasonal Hydrological Prediction System LSM VIC Noah SAC Routing Multiple GCM Ensemble Forecast NLDAS (initial conditions) Bayesian Merging Weather “Generator” (resampling and scaling historical time series) 1/8 degree daily time step 1/8 degree Monthly time step Obs. Climatology Climate indices Teleconnection 1/8 degree GCM resolution and Coarser Large scale Bayesian Merging ESP VIC Noah SAC

10. Drought Predictability Assessment Long-term Historical Observed Atmos. Forcing Realtime Atmos. Forcing VIC Long-term Hydrological States VIC Realtime Hydrological States Soil Moisture Percentiles (SMI) ESPs, CFSs, and Nowcast RMSE OBS (NCAST) and Forecast (ESP and CFS) 1971-2000 2007 Initializations Mar, May, Jul, Sep, Nov Mexico, North Central, Northwest, andSouth Modelling-based Atmos. Forcing + Long-term VIC CFS-Long-term Hydrological States 1971-2000 ESPCFS NCAST

11. Initial Conditions March April May June ObservationsForecasts ESPCFS Ensemble Performance (soil moisture Percentiles) 2007

12. 1-month lead 2-month lead 3-month lead Initialization Month Forecast Month RMSE forecast /RMSE climatology RMSE forecast Drought Predictability ESP

13. June July August March 3-m L May 1-m L May 2-m L May 3-m L July 1-m L Initial Conditions Month-lead Mexico Forecast and North American Drought Monitor ESP

14. Monitored Drought Indices (ESP) for August 2007 Standarized Precipiatation Index Standarized Runoff Index Soil Moisture Percentile-Observations Soil moisture Percentile-Forecast North American Drought Monitor Shukla and Wood (2008)

15. Conclusions Differences in the predictability along Mexico showed The largest drought predictability occurred in North-central Mexico, while the lowest occurred in the South. Largest values of RMSE were observed during the Summer period in all sub-domains Low RMSE values indicate high skill in the forecast for those initialized late in the Fall Initialized in March 2007, ESP and CFS performances show spatial differences, while ESP outperforms CFS in general, over particular domains such as in South Mexico CFS outperform ESP. The UW-West-wide Hydrological Forecast System registered drought events recorded by the NADM plus other events reported by Mexican agencies regarding agriculture impacts of drought in parts of Baja California Peninsula, San Luis Potosi, Michoacan, and Northern Oaxaca

16. Future Work Evaluate the interannual variability in the ESP and CFS performances to complement the drought predictability assessment Involve more land surface models through the application of the University of Washington Surface Water Monitor, which uses (NOAH, LCM, and SAC models to monitor and predict drought (its development is currently in progress). Evaluate the drought predictability over a larger domain

17. Thank you! Tlaloc, the Aztec God of Rain, responsible of drought and flood (Borgia Codex)

18. 1-month lead 2-month lead 3-month lead Initialization Month Forecast Month cccccccc cccccccc cccccccc cccccccc cccccccc cccccccc Forecasts Observations I.C.

19. 1-month lead 2-month lead 3-month lead Initialization Month Forecast Month ForecastsObservations I.C.

20. Climatology vs Forecast RMSE forecast /RMSE climatology

21. NorthwestNorth Central Observed Forecast Water Balance March May 456 9.8217420.772224.6275 456 8.9552410.14927.14049 678 19.44821.850723.6503 678 4.556447.2392510.2422