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Drought Predictability in Mexico

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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 - PowerPoint PPT Presentation
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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
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Drought Predictability in Mexico

Francisco Muñoz Arriola1, Shraddhanand Shukla1, Lifeng Luo2, Abel Muñoz Orozco3, and Dennis P. Lettenmaier1

1Department of Civil and Environmental Engineering, University of Washington2Department of Civil and Environmental Engineering, Princeton University

3Colegio de Posgraduados

American Meteorological Society

Phoenix, AZ January 12th 2009

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

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

17.81%

2.05%

0.52%

0.01%

79.62%

0 20 40 60 80

Drought

Hurricanes

Rainfall

FroztsHail

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

2

3

41

1. Mexico2. Northwestern3. North Central4. 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

Research QuestionsDue 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?

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

UW Extended WSHFS and ESP

•Based on the use ensemble techniques applied to generate forcing data for a Land-surface hydrology model

Drought Predictability Assessment

Long-termHistorical Observed

Atmos. Forcing

RealtimeAtmos. Forcing

VIC

Long-termHydrological States

VIC

RealtimeHydrological States

Soil Moisture Percentiles (SMI)ESPs , CFSs, and Nowcast

RMSE OBS (NCAST) and Forecast (ESP

and CFS)

1971-2000

2007 InitializationsMar, May, Jul,

Sep, Nov

Mexico, North Central,Northwest, andSouth

Modelling-basedAtmos. Forcing +

Long-term

VIC

CFS-Long-termHydrological States

1971-2000ESP CFSNCAST

Initial ConditionsMarch

April

May

June

Observations Forecasts

ESP CFS

Ensemble Performance (soil moisture Percentiles)

2007

1-month lead

2-month lead

3-month lead

Initialization Month

Forecast Month

RMSEforecast/RMSEclimatologyRMSEforecast

Drought PredictabilityESP

June

July

August

March3-m L

May1-m L

May2-m L

May3-m L

July1-m L

Initial ConditionsMonth-lead

Mexico

Forecast and North American Drought Monitor

ESP

Monitored Drought Indices (ESP) for August 2007

Standarized Precipiatation Index

Standarized Runoff IndexSoil Moisture Percentile-Observations

Soil moisture Percentile-Forecast

North American Drought Monitor

Shukla and Wood (2008)

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

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

Thank you!

Tlaloc, the Aztec God of Rain, responsible of drought and flood (Borgia Codex)

1-month lead

2-month lead

3-month lead

Initialization Month

Forecast Month

cccc

cccc

cccc

Forecasts Observations

I.C.

1-month lead

2-month lead

3-month lead

Initialization Month

Forecast Month

Forecasts Observations

I.C.

Climatology vs Forecast

RMSEforecast/RMSEclimatology

NorthwestNorth Central

Observed Forecast

Water Balance

March

May

4 5 69.82174 20.7722 24.6275

4 5 68.95524 10.1492 7.14049

6 7 819.448 21.8507 23.65036 7 8

4.55644 7.23925 10.2422


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