Drought Prediction and Predictability An Overview Vikram Mehta, Katherin Mendoza, Hui Wang, and Norman Rosenberg Center for Research on the Changing Earth System, Catonsville, Maryland, U.S.A.! Causes of Multiyear to Multidecadal Droughts! Major Ocean Temperature Patterns Causing Multiyear to Multidecadal Droughts! Predictability of Past Droughts: Hindcasts from CMIP5 Experiments! Summary! Point to Ponder
Heat waves Storm track variations Madden-Julian Oscillation Intrinsic monsoon variability Drought Timescales (Adapted from a Roger Pulwarty presentation) El Niño-Southern Oscillation Pacific Decadal Oscillation Tropical Atlantic variability Atlantic Multidecadal Oscillation West Pacific Warm Pool variability Intrinsic monsoon variability Solar variability Greenhouse gases Natural and anthropogenic aerosols Land use-cover changes!"#$%"%$$&'" ()""!"#$%"'$!')*'"!"#$%"'$!')*'" ()""!"#$%"+$!,'"!"#$%"+$!,'" ()""!"#$%"-$.!-$'" MULTIYEAR Focus of this talk
Causes of Multiyear to Multidecadal Droughts
Causes of Multiyear to Multidecadal Droughts Variability/changes in atmospheric circulation and precipitation patterns driven by variability/ changes in oceanic heating
Causes of Multiyear to Multidecadal Droughts Variability of solar radiative, particulate, and electromagnetic field outputs
Causes of Multiyear to Multidecadal Droughts Positive feedback between soil moisture patterns and overlying atmospheric circulations
Causes of Multiyear to Multidecadal Droughts Changes in land use patterns, overgrazing, deforestation
Causes of Multiyear to Multidecadal Droughts Natural aerosols (such as volcanic matter and desert dust) Anthropogenic aerosols (such as industrial and vehicular emissions)
Major Ocean Temperature Patterns Causing Multiyear to Multidecadal Droughts
Warm/cold surface water in much of the Pacific Ocean Observed Pacific Decadal Oscillation SST Pattern: 1900 2012 Positive/warm phase Negative/cold phase Courtesy: Nathan Mantua, Stephen Hare Univ. of Washington Anomalous SST patterns Monthly Pacific Decadal Oscillation index: 1900-2012 Warm/cold phases persist for a few years to a few decades
Observed Tropical Atlantic SST Gradient Variability Pattern: 1861 2010 Crossequatorial SST gradient points south-tonorth or northto-south for a few years to a decade!"#$%&! '()*+,-"%.#+ Substantial SST anomalies ( o C) associated with one standard deviation in the time series below
Tropical Warm Pool definition: SST above 28.5 C Observed West Pacific Warm Pool Average SST Pattern Average Warm Pool SSTs ( C) Substantial increase in atmospheric convection and clouds when SST above 28.5 C
Observed West Pacific Warm Pool SST Anomaly Time Series Original and detrended time series Indo-Pacific Warm Pool becoming warmer over the last 50 years; also, multi-year to decadal variability
How does SST variability influence climate on continents? SST variability modulates transfers of heat and water vapor between ocean and atmosphere modulating cloud formation, rainfall, and largescale atmospheric motions influencing water vapor and heat transport to and pressure, temperature and winds over continents resulting in precipitation and temperature variability on continents.
PDO Associations between major SST patterns and anomalous Self-Calibrating PDSI Variability Red Dry, Blue Wet in Positive Phase of SST Pattern Trop Atl Warm Pool Niño 3.4
SST Patterns Prescribed in Experiments to Simulate Interannual to Decadal Droughts (From: Schubert et al., J. Clim., 2009) Red, Warming Warming trend Red, Warm Blue, Cool Red, Warm PDO-like pattern Atlantic Multidecadal Oscillation pattern
(From: Schubert et al., J. Clim., 2009) Cold Pacific, Warm Atlantic Simulated SST Impacts on US Great Plains Precipitation and Temperature Models GFDL AM2.1 NCEP GFS v.2 NASA NSIPP 1 NCAR CCM 3.0 NCAR CAM3.5 Warm Pacific, Cold Atlantic Dry and hot US Great Plains Wet and cool US Great Plains
Major drought patterns are forced by major SST patterns.
Skillful drought predictability depends critically on skillful predictability of major SST patterns.
Understanding physics of teleconnections between SST patterns and drought patterns is very important.
Predictability of Past Droughts: Preliminary Results from CMIP5 Experiments
Problems in producing decadal climate outlooks (From: Mehta et al., Bull. Amer. Meteorol. Soc., 2011) Data: Relatively short time series of ocean observations!! Analysis and interpretation: Coupled ocean-atmosphere modes with distinct timescales? Mechanisms?!! Models: Inadequate simulation of observed patterns and their modulation of weather!! Predictability: Is climate predictable beyond a few seasons lead times?!! Usefulness of predictions: What would be useful? Who would use predictions?!
Recently Published Interannual to Decadal Climate Predictability Findings Authors Smith et al., Science, 2007 Keenlyside et al., Nature, 2008 Pohlmann et al., J. Climate, 2009 Coelho and Goddard, J. Climate, 2009 Oldenborgh et al., Climate Dynamics, 2012 Yang et al., J. Climate, 2013 Mehta et al., Geophys. Res. Lett., 2013 Major Finding Skillful prediction of decadal, global-average temperature possible Skillful prediction of decadal, North Atlantic SSTs possible Patterns, magnitudes, and spatial extents of ENSOrelated droughts likely to remain same in 21 st century Skillful prediction of northern North Atlantic SSTs possible Inter-hemispheric, multidecadal SST pattern may be predictable 4-10 years in advance Significant, but variable decadal hindcast skill of global- and tropical ocean basin-average SSTs during 1961 to 2010; volcanic eruptions play an important role in providing skill!
WCRP Coupled Model Intercomparison Project 5 (CMIP5) Two sets of core decadal prediction experiments (Taylor et al., 2008; cmip-pcmdi.llnl.gov/cmip5), Meehl et al., BAMS, 2009) First set: A series of 10-year hindcasts starting approximately in 1960 Second set: A series of 30-year hindcasts starting in 1960, 1980, 2005 Volcanic aerosols and solar cycle prescribed from past observations Each experiment has a minimum ensemble size of three members; ten members in some models ensembles Outputs of both sets of experiments, containing a very large number of ocean-atmosphere-land variables, available for many participating models Results to be used in the IPCC Assessment Report 5 (2013-14)
Hybrid Dynamical-Statistical Prediction System for Decadal Climate and Hydro-meteorology $!"#!-&'!'$ =/*$260.(39$ (>$?3**,2(@0*$?+0*0A$ B(4)+,6)$+,5$ (.2*3$ +*3(0(4$ (1=)+4$ 5*1.20A$0(4+3$ 3+56+=(,$$ Dynamical System for SST Prediction 7+3.2$890.*/$:(5*4$ ;78:<$ 7,0*/C4*$ 6,6=+46D+=(,$090.*/E$!'-9*+3$*F1*36/*,.0$ 6,6=+46D*5$6,$!"#'A$!"G'A$HA$&'''$!"#!$%$&'!'$ ()*+,- +./(012*3*- 4+,5$26,5)+0.0$
Hybrid Dynamical-Statistical Prediction System for Decadal Climate and Hydro-meteorology Statistical System for Climate and Hydro-meteorological Prediction!"#!$%$&'!'$ ()*$+,-./$$ 0+,-1234$ 5678$9:;3$ <.=6.33+7,$75$ >6.-+142,-$?+40$()*$ +,-+1.3$23$>6.-+14763@$ AB$C.263$-242$./1.>4$ >.6+7-$47$D.$0+,-1234$ <.=6.33+7,$ 17.E1+.,43$ F3.-$+,$ >6.-+142,-$ 0+,-1234G$ F3+,=$()*$ +,-+1.3$576$ +,-.>.,-.,4!'HC.26$$ 0+,-1234$ >.6+7-$!'HC.26$ >6.-+142,-$ 0+,-1234$
CMIP5 Earth System Models and Observations-based Data Used in the Hybrid Decadal Drought Prediction System Models: NOAA-GFDL CM2.1, NCAR CCSM4, UKMO-HadCM3, Japan-MIROC5 Extended Reconstructed SST (ERSST); monthly, 2 x 2 ; 1961 2010 [Reynolds et al., J. Climate, 2002] Self-calibrating Palmer Drought Severity Index (P-M PE); 5 x 5 ; 1951-2005 [Wells et al., J. Climate, 2004; Dai, J. Geophys. Res., 2011] Objectively-analyzed, high resolution (12 km X 12 km) precipitation, and daily maximum and minimum temperatures for North America; 1949-2010 [Maurer et al., J. Climate, 2002]
Corr. Coeff. between Annual Obs. and MIROC5 Hindcast Indices: 1961-2010 Niño 3.4 18/50 corr. above 0.6 (95%) West Pac. Warm Pool Pac. Dec. Osc. 16/50 Trop. Atl. Grad. Var. 32/50 11/50
Observations-based and Hindcast SC-PDSI in the US Great Plains Obs. based DRY WET WET Hindcast with four predictor indices
Observations-based and Hindcast SC-PDSI in Southern Africa Obs. based Hindcast with four predictor indices DRY DRY WET WET
Observations-based and Hindcast SC-PDSI in the 1981-85 Period Using the MIROC5 ESM Without detrending With detrending Obs. SC- PDSI Hind cast SC- PDSI
Observations-based and Hindcast SC-PDSI in the 1986-90 Period Using the MIORC5 ESM Without detrending With detrending Obs. SC- PDSI Hind cast SC- PDSI
Observations-based and Hindcast SC-PDSI in the 1991-95 Period Using the MIORC5 ESM Without detrending With detrending Obs. SC- PDSI Hind cast SC- PDSI
Observations-based and Hindcast, June-July-August U.S. Precip. and Temperature in Using the MIROC5 ESM: 1981-85 (wet period in the Missouri River Basin) JJA Precipitation (mm/day) JJA Temperature ( C) Obs. Hind cast Error (%)
Observations-based and Hindcast, June-July-August U.S. Precip. and Temperature in Using the MIROC5 ESM: 1986-90 (dry period in the Missouri River Basin) JJA Precipitation (mm/day) JJA Temperature ( C) Obs. Hind cast Error (%)
Observations-based and Hindcast, June-July-August U.S. Precip. and Temperature in Using the MIROC5 ESM: 1991-95 (wet period in the Missouri River Basin) JJA Precipitation (mm/day) JJA Temperature ( C) Obs. Hind cast Error (%)
Summary Several natural and anthropogenic causes of multiyear to multidecadal droughts Pacific and Atlantic Ocean temperature variability most clearly associated with droughts Predictability and prediction of these temperature patterns key to drought predictability and prediction at multiyear to multidecadal timescales Very encouraging preliminary results of multiyear to decadal drought hindcasting using output from WCRP s CMIP5 project
Point To Ponder Prediction of impacts and continuous interactions with stakeholders vital for success of drought policies guided by drought prediction and other information.
Decadal Drought and Impacts Information for Decision Support in the Missouri River Basin DCV phenomena Influences on Basin hydrometeorology Applications In various sectors Influences on Agriculture Urban water Industries Navigation Recreation Others Rural and urban economies; Local, regional, national, international economies Adaptation strategies via understanding, prediction, and scenario development Data, information, and decisionsupport systems Active involvement of stakeholders and policymakers
Thank you!!
Publications available from missouri.crces.org Mehta, V.M., N. J. Rosenberg, and K. Mendoza, 2011: Simulated Impacts of Three Decadal Climate Variability Phenomena on Water Yields in the Missouri River Basin. Journal of the American Water Resources Association, 47, 126-135. Mehta, V.M., N. J. Rosenberg, and K. Mendoza, 2012: Simulated Impacts of Three Decadal Climate Variability Phenomena on Dryland Corn and Wheat Yields in the Missouri River Basin. Agricultural and Forest Meteorology, 152, 109-124. Mehta, V.M., C. L. Knutson, N. J. Rosenberg, J. R. Olsen, N. A. Wall, T. K. Bernadt, and M. J. Hayes, 2012: Decadal Climate Information Needs of Stakeholders for Decision Support in Water and Agriculture Production Sectors: A Case Study in the Missouri River Basin. Weather, Climate, and Society, 5, 27-42. Mehta, V.M., H. Wang, and K. Mendoza, 2013: Decadal Predictability of Tropical Basin-average and Global-average Sea-surface Temperatures in CMIP5 Experiments with the HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 Global Earth System Models. Geophys. Res. Lett., in press.
Towards Societally-relevant Drought Prediction
Towards Societally-relevant Drought Prediction Prediction of Drought Impacts on! Water Food Energy Transportation Public health Economy
An Example: The Missouri River Basin Missouri River Basin Produces 46% of wheat, 22% of grain corn, 34% of cattle in the United States Largest river basin in the US Covers 500,000 sq. miles, 10 States, many Native American reservations, parts of Alberta and Saskatchewan Value of crops and livestock over $100 billion in 2008 117 million acres cropland, only 12 million acres irrigated Dependence on the Missouri River for drinking water, irrigation and industrial needs, hydro-electricity, recreation, navigation, and fish and wildlife habitat
Droughts in the Missouri River Basin The Basin experiences severe to extreme decadal droughts.
Number of locations Simulation of DCV Impacts on Missouri River Basin Water Yield with the Soil and Water Analysis Tool (SWAT) (From: Mehta et al., J. Amer. Water Res. Assoc., 2011) Significant impacts on Basin-aggregated yield PDO neg. phase PDO pos. phase PDO impacts on water yield Percent change from climatology 50-60% change in individual locations; substantial impacts of tropical Atlantic and west Pacific Warm Pool variabilities also
Number of locations Simulation of DCV Impacts on Missouri River Basin Crop Yields with the Environmental Policy Integrated Climate (EPIC) Model Significant impacts on Basin-aggregated yield PDO neg. phase PDO impacts on spring wheat yield PDO pos. phase Percent change from climatology 30-40% change in individual locations; also, significant impacts on winter wheat and corn; substantial impacts of tropical Atlantic and west Pacific Warm Pool variabilities also