Implications of Climate Change on Long Lead Forecasting and Global Agriculture. Ray Motha

Transcription

1 Implications of Climate Change on Long Lead Forecasting and Global Agriculture Ray Motha

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4 ENSO Teleconnections

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7 30 Observed Monthly Sea Surface Temperatures Central Central Equatorial Pacific Ocean Ocean (Region (Region Niño-3.4) Niño-3.4) Dotted black line is the normal Sea Surface Temperature ( ). Observed Temperatures (Degrees C) Normal Seasonal Variation of SSTs Dec-99 Jun-00 Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Mar-00 Sep-00 Mar-01 Sep-01 Mar-02 Sep-02 Mar-03 Sep-03 Mar-04 Sep-04 World Agricultural Outlook Board Data updated thru October 2004

8 30 Observed Monthly Sea Surface Temperatures Central Central Equatorial Pacific Ocean Ocean (Region (Region Niño-3.4) Niño-3.4) Thick green line is the actual Sea Surface Temperature (SST). Dotted black line is the normal Sea Surface Temperature ( ). Observed Temperatures (Degrees C) Overlay Actual SST s Dec-99 Jun-00 Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Mar-00 Sep-00 Mar-01 Sep-01 Mar-02 Sep-02 Mar-03 Sep-03 Mar-04 Sep-04 World Agricultural Outlook Board Data updated thru October 2004

9 Observed Temperatures (Degrees C) Observed Monthly Sea Surface Temperatures Central Central Equatorial Pacific Ocean Ocean (Region (Region Niño-3.4) Niño-3.4) Thick green line is the actual Sea Surface Temperature (SST). Dotted black line is the normal Sea Surface Temperature ( ). Red areas are above normal Sea Surface Temperatures. Blue areas are below normal Sea Surface Temperatures. La Niña La Niña Neutral El Niño Neutral Dec-99 Jun-00 Dec-00 Jun-01 Dec-01 Jun-02 Dec-02 Jun-03 Dec-03 Jun-04 Dec-04 Mar-00 Sep-00 Mar-01 Sep-01 Mar-02 Sep-02 Mar-03 Sep-03 Mar-04 Sep-04 World Agricultural Outlook Board Data updated thru October 2004

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11 Monthly Sea Surface Temperature Departures from Normal Central Equatorial Pacific Ocean (Region Niño-3.4) 4 Temperature Departure from Normal (Degrees C) Warm Episodes (El Niño) Circles denote individual events -3 Cold Episodes (La Niña) World Agricultural Outlook Board Joint Agricultural Weather Facility Data updated thru February 2001 Data from Climate Prediction Center (NWS)

12 Example of a Strong El-Niño

13 Example of a Strong La-Niña

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16 Defining El Niño / La Niña Crop Weather Impacts TYPICAL RAINFALL IMPACTS FROM EL NIÑO (BASED ON STATISTICAL CORRELATIONS) APR(0)-OCT(0) INDETERMINATE JUN(0)- SEP(0) OCT(0)- MAR(+) OCT(0)- APR(+) OCT(0)- DEC(0) JUN(0)-NOV(0) NOV(0)-MAY(+) MAY(0)-APR(+) NOV(0)-APR(+) JUL(0)- OCT(0) JUL(0)- MAR(+) NOV(0)-MAY(+) SEP(0)-MAR(+) APR(0)-MAR(+) MAR(0)-FEB(+) MAY(0)-OCT(0) NOV(0)- FEB(+) WET DRY Prepared by the Joint Agricultural Weather Facility Source: Ropelewski and Halpert, Monthly Weather Review, (115) p (0) = YEAR OF EL NIÑO (+) = YEAR FOLLOWING EL NIÑO World Agricultural Outlook Board

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18 Defining El Niño / La Niña Crop Weather Impacts TYPICAL RAINFALL IMPACTS FROM LA NIÑA (BASED ON STATISTICAL CORRELATIONS) INDETERMINATE JUN(0)- SEP(0) OCT(0)- APR(+) NOV(0)- MAR(+) OCT(0)- DEC(0) NOV(0)-APR(+) APR(0)-JUN(+) JUN(0)- MAR(+) JUN(0)-DEC(0) NOV(0)-APR(+) SEP(0)-JAN(+) MAR(0)-FEB(+) AUG(0)-DEC(0) SEP(0)-MAR(+) JUN(0)- DEC(0) WET DRY (0) = YEAR OF LA NIÑA (+) = YEAR FOLLOWING LA NIÑA Prepared by the Joint Agricultural Weather Facility Source: Ropelewski and Halpert, Journal of Climate, (2) p World Agricultural Outlook Board

19 Assessing El Niño / La Niña Crop Weather Impacts Moderate to strong: El Niño La Niña Impacts are rarely the same between events. World Agricultural Outlook Board

20 Climate Prediction Center Forecast System Schematic owquency: rend Seasonal CPC Forecast System High Frequency: Interannual Weather/climate links Schematic - Composites - Teleconnections - Extreme events - Tropical storms - Drought/Floods - Climate/Weather Monitoring Extended Range U.S. Threats Assessment 6-10 Day Week Two Monthly International Threats adal Variability DO O/NAO lobal Warming Inter-Annual Variability - ENSO Dynamical/statistical models - Real-Time Diagnostics - Model Simulations - Ensembles - Verification Intra-seasonal Variability - Tropical MJO - Blocking - AO/NAO/NPO/PNA Applied Research, Diagnostics and Forecast Tools Collaborators: EMC, TPC, CDC, GFDL, IRI, Scripps, COLA, U. W ash.

21 Forecast Process Schematic Dissemination to public Dynamical model forecasts/multimodel ensembles Recent observations Historical observations.. Verifications/Statistical tools Downscaling, Analogs, Composites WEB PAGES/AUTOMATED DATABASES Peer-reviews of the forecast tools and of the penultimate forecast via web/telephone conference with partners and through local discussions (map discussions,sanity check, conference calls, etc ) Forecaster-created or automated products

22 Part 1. Long-Lead Seasonal Forecasts

23 Background: A Variety of Forecasts Weather mostly regional, short-lived events Deterministic forecasts protection of life Seasonal climate Global, seasons in advance Probabilistic forecasts deviations from normal seasons Mitigation energy, food, water, health, etc sectors Climate change scenarios Global, visions of the future Includes chemistry and biology modeling Projections of possible future changes to regional climatology Understanding unintended consequences & adaptation Solving the carbon problem

24 Overview of Weather and Climate Models and the Required Observations Mid-1970s Mid-1980s Early 1990s Late 1990s Present Day Early 2000s? Atmosphere Atmosphere Atmosphere Atmosphere Atmosphere Atmosphere Weather Land Surface Land Surface Land Surface Ocean & Sea IceOcean & Sea Ice Land Surface Land Surface Ocean & Sea IceOcean & Sea Ice Climate Variability Sulphate Aerosol Sulphate Aerosol Sulphate Aerosol Non-sulphate Aerosol Carbon Cycle Non-sulphate Aerosol Carbon Cycle Climate Change Dynamic Vegetation Atmospheric Chemistry

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27 Mother Earth -- Our Home

28 Food production needs to double to meet the needs of an additional 3 billion people in the next 30 years Climate change is projected to decrease agricultural productivity in the tropics and sub-tropics for almost any amount of warming Robert Watson

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30 Water Services Climate change is projected to decrease water availability in many arid- and semi-arid regions One third of the world s population is now subject to water scarcity Population facing water scarcity will more than double over the next 30 years Robert Watson

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33 Potential Climate Change Impacts Health Impacts Weather-related Mortality Infectious Diseases Air Quality-Respiratory Illnesses Climate Changes Temperature Precipitation Sea Level Rise Agriculture Impacts Crop yields Irrigation demands Forest Impacts Change in forest composition Shift geographic range of forests Forest Health and Productivity Water Resource Impacts Changes in water supply Water quality Increased competition for water Impacts on Coastal Areas Erosion of beaches Inundate coastal lands Costs to defend coastal communities Species and Natural Area Shift in ecological zones Loss of habitat and species

34 Potential Impacts of Global Warming Modest warming, higher production More heat waves, tropical diseases More storm surges/erosion Sea ice melts Longer growing season, increased production Intense cyclones Frequent floods/drought, increased disease Coastal flooding More drought/floods, decreased production Drier, yields decrease, desertification Warmer, glacial melt, oceans rise Map is an interpretation of concerns expressed by the Intergovernmental Panel on Climate Change (sponsered by the United Nations). Office of the Chief Economist World Agricultural Outlook Board

35 Climate Models - Differing Forecasts Change in Average Annual Temperature Observed 20 th century Canadian Model 21 st century U.S. temperatures 20 th century most areas - warmed southeast - cooled slightly Forecasts for 21 st century warmer throughout Hadley - 3 to 7 o F Canadian - 5 to 15 o F Hadley Model 21 st century Source: Maps and findings from the Intergovernmental Panel of Climate Change (sponsored by U.N.)

36 Annual U.S. Temperatures Lower 48 States ( , 31 Years) Trend = Degrees F Trend = Trend = Trend =

37 Climate Models - Differing Forecasts Change in Average Annual Precipitation Observed 20 th century Canadian Model 21 st century U.S. precipitation 20 th century most areas - wetter locally drier Forecasts for 21 st century Canadian - much wetter west, drier east, parts of Plains Hadley - wetter throughout Hadley Model 21 st century Source: Maps and findings from the Intergovernmental Panel of Climate Change (sponsored by U.N.)

38 Possible benefits and drawbacks of climate change on agriculture Source: Scientific American, March, 1994.

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40 The Grand Challenges for 21 st Century Issues associated with global population growth Climate change/variability and natural disasters Potential impacts of global warming New products to meet emerging societal needs Sustainable agriculture Adaptation strategies

41 Agricultural Weather While focusing on sustainable agriculture, farmers have to cope with variable weather throughout the growing season, extreme events during the season, and changing climate patterns. Agriculture has learned to adapt to climate variability and climate change, but past changes have been relatively transitional.

42 New Directions in Agricultural Weather Long-lead seasonal forecasting is improving. Climate change/variability and natural disasters are key issues for agricultural decision-makers. Potential impacts vary by region and by season with the most vulnerable agricultural systems at the greatest risk. Risk management planning should be developed (or adopted) by region with adaptation strategies and mitigation plans to cope with extreme events.

43 Disaster Management Shift from Crisis to Risk Management Risk Management: Based on preparedness and mitigation. Preparedness is designed to increase the level of pre-disaster readiness to respond to an event. Mitigation refers to activities designed to reduce the impact of a disaster prior to its occurrence (land use planning).

44 Drought Research What instigates drought? What prolongs drought? What ends drought? Drought forecast? To forecast drought, you need to know what causes drought. Much of the atmospheric variability may be random, but feedback between the atmosphere, the land, and oceans influences weather and climate for weeks and months.

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46 Principal Drought Monitor Inputs CPC Daily Soil Model USGS Streamflow Palmer Drought Index 30-day Precip. USDA Soil Ratings Satellite Veg Health

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48 Agroclimatic Risk Management Plan Vulnerability Analyses Impact Assessments Mitigation Planning Adaptation Strategies

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50 Adaptation Strategies 1. Adaptation measures are assessed in a developmental context. 2. Adaptation to short-term climate variability and extreme events are explicitly included as a step toward reducing vulnerability to longer-term climate change 3. Adaptation occurs at all levels, ranging from local to national and international levels.

51 Agricultural Weather and Climate Policy Develop an agricultural weather and climate policy with preparedness as its foundation (concept similar to Australia s Drought Plan or U.S. National Drought Policy). Outline a course of action that includes a preparedness initiative to help reduce the economic hardships caused by extreme climate events.

52 Agricultural Weather and Climate Policy Recommending a paradigm shift in policy from Response to Readiness. Goal: Reduce the impacts of climate variability and change on the agricultural sector. Objective: Preparedness must become the cornerstone of an agricultural weather and climate policy.

53 Agricultural Weather and Climate Policy Preparedness is the key to a proactive policy.

54 Agricultural Weather and Climate Policy GOAL 1: Incorporate planning, implementation of plans and proactive mitigation measures, risk management, resource stewardship, environmental considerations, and public education as the key elements of an effective agricultural weather and climate policy.

55 Agricultural Weather and Climate Policy GOAL 2: Improve collaboration among scientists and managers to enhance the effectiveness of observation networks, monitoring, prediction, information delivery, and applied research, and, to foster public understanding of and preparedness for climate variability and change.

56 Summary Developing an agricultural weather and climate policy that addresses climate issues for policy makers and scientists would aid risk management, conservation of natural resources, and mitigation of climate variability/change. A win-win scenario!

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58 THANK YOU