Downscaling of GCM for i’ts use in Agriculture and NRM Research

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  • Para hacer estos cálculos de vulnerabilidad (incapacidad de un sistema para afrontar los efectos adversos del CC), necesitamos datos climáticos. Saber que va a pasar, cuando, para proyectar Planes de adaptación. La evaluación de los impactos de cambio climáticoincluye: Desarrollar modelos -> Conocer incertidumbres -> Planes de acción -> Generación de políticas LimitacionesSistema climático complejo: Modelos todavía no pueden representar cientos de procesos de forma adecuadaResoluciones de modelos inadecuadas: Se requieren modelos con escalas finas.Incertidumbres: Incertidumbres en cuanto a futuras emisiones f(suposiciones concentraciones, población, desarrollo económico, tecnológico)
  • Analizan de qué manera influirán las fuerzas determinantes en las emisiones futuras, y para evaluar el margen de incertidumbre de dicho análisis. Representannuestracapacidad de respuesta (mitigación)… desarrollotecnológico, sostenibilidadambientalIPCC hadesarrollado 4 familias de escenarios A1B : Rápidocrecimientoeconómico y demográfico con pico a ½ siglo A2 : Crecimientoeconómico regional y lento, población en contínuocrecimiento B1 : Población A1 pero con introducción de tecnologíaslimpias B2 : Desarrolloeconómicointermedio y regional, crecimientopoblacionalmenor. Son escenariosprobablespero no se sabensusprobabilidadesrelativas.
  • Los escenarios de emisiones imponen condiciones para los modelos climáticos globales (basados en ciencias atmosféricas, química, física, biología, etc).Dividen el mundo el grillas y miran las relaciones entre factores que ocurren entre la atmósfera, los oceános, la superficie de la tierra. Por supuesto, hay cientos de procesos que salen de la comprensión de los modelos matemáticos así que estos modelos utilizan parametrizaciones para representar fenomenos incomprensibles. Son tan elaborados estos modelos que tienen que correrse en supercomputadoras. Entre más complejo sea el modelo, más factores tiene en cuenta y menos suposiciones usa. Se corre desde el pasado hasta el futuro
  • CC es la mismahistoria … Cambiosantropogénicosllevan a cambiosatmosféricosCrecimientopoblacionalExpansion agricola e industrialTecnologiasambientalmente no amigables Resultan en Aumento de gases de efectoinvernaderoLas temperaturaspodrianincrementarsehasta en 6 oC en 2100Lo queestáocurriendo no tieneprecedentes, poresodebemosmirar lo quemuestran los modeloscomonunca antes.
  • Estosmodelospuedenllegar a ser tan complejosquepuedenexpandirseverticalmente a muchosniveles, sin embargo lasresolucionesespaciales de sussalidas no son lasmásadecuadas. Fenómenosescala local : Especialmente en regiones con orografíacompleja, suelohetereogéneo, líneacostas.
  • GCMs y ResolucionesDifieren en Formulación (ecuaciones)ResoluciónEntradasPrecisiónDisponibilidadProyectandiferentespatrones y magnitudes para un mismoperiodo. Todoestoaumenta la incertidumbre. Recomendación : Usarmuchos GCMs comodatos de entrada (estudios de impacto)
  • Grado de cobertura diff segun modelo. Y resultados tambien yield o suitability. Tambien difieren en escala espacio-temporal a la que se usan.
  • Those change are happening and are affecting crop around the world. We need to know how and how much climate change is going to have an impact on crops to be able to build adaptation strategy and decrease the potential impact of CC on crops and agricultural systems.
  • Downscaling of GCM for i’ts use in Agriculture and NRM Research

    1. 1. 10/10/2012Carlos Navarro, Julian Ramirez,Andy Jarvis, Peter Laderach
    2. 2. Contents• Brief about climate & agricultre• Climate data, availability, difficulties, options• Our databases
    3. 3. We know…• Any agroecosystem respond to changes of anthropogenic factors, biotics, abiotics.• Weather and climate predictability is fairly limited.• The climate will change.• Each system is an specific case.• Crops are very sensitive to climatic conditions
    4. 4. Climate & Agriculture – Multiple variables – Very high spatial –T° • Max, resolution • Min, Less importance More certainty • Mean – Mid-high temporal (i.e. monthly, daily) resolution –Prec – Accurate weather forecasts and climate – HR projections – Radiation – High certainty – Wind• Both for present and – ……. future
    5. 5. We don’t know… What are the conditions in 30, 50, 100 years? • How our system respond to these conditions? • When, where and what type of change requiere to adapt? • Who should plan? >> UNCERTAINTIES Who should leads the process ? Who should run?
    6. 6. Needs Limitations
    7. 7. Emission Scenarios Pessimistic Intermediate “Bussiness as usual” P Economic P E E Global Regional P P E E Perfect World Environmental Optimistic
    8. 8. In agriculture, the different emission scenarios are not important ... by2030 the difference between the scenarios is minimal
    9. 9. GCM “Global Climate Model” GCMs are the only way Using the past to learnwe can predict the future for the future climate
    10. 10. What are saying the models? Atmospheric concentrations Variations of the Earth’s surface temperature: 1000 to 2100 Anthropogenic changes lead to changes in weather
    11. 11. Resolutions • Horizontal resolution 100 to 300 km • 18 and 56 vertical levels Global scale  Regional or local scale 
    12. 12. Model Country Atmosphere OceanBCCR-BCM2.0 Norway T63, L31 1.5x0.5, L35CCCMA-CGCM3.1 (T47) Canada T47 (3.75x3.75), L31 1.85x1.85, L29CCCMA-CGCM3.1 (T63) Canada T63 (2.8x2.8), L31 1.4x0.94, L29CNRM-CM3 France T63 (2.8x2.8), L45 1.875x(0.5-2), L31CSIRO-Mk3.0 Australia T63, L18 1.875x0.84, L31CSIRO-Mk3.5 Australia T63, L18 1.875x0.84, L31GFDL-CM2.0 USA 2.5x2.0, L24 1.0x(1/3-1), L50GFDL-CM2.1 USA 2.5x2.0, L24 1.0x(1/3-1), L50GISS-AOM USA 4x3, L12 4x3, L16GISS-MODEL-EH USA 5x4, L20 5x4, L13GISS-MODEL-ER USA 5x4, L20 5x4, L13IAP-FGOALS1.0-G China 2.8x2.8, L26 1x1, L16INGV-ECHAM4 Italy T42, L19 2x(0.5-2), L31INM-CM3.0 Russia 5x4, L21 2.5x2, L33IPSL-CM4 France 2.5x3.75, L19 2x(1-2), L30MIROC3.2-HIRES Japan T106, L56 0.28x0.19, L47MIROC3.2-MEDRES Japan T42, L20 1.4x(0.5-1.4), L43MIUB-ECHO-G Germany/Korea T30, L19 T42, L20MPI-ECHAM5 Germany T63, L32 1x1, L41MRI-CGCM2.3.2A Japan T42, L30 2.5x(0.5-2.0)NCAR-CCSM3.0 USA T85L26, 1.4x1.4 1x(0.27-1), L40NCAR-PCM1 USA T42 (2.8x2.8), L18 1x(0.27-1), L40UKMO-HADCM3 UK 3.75x2.5, L19 1.25x1.25, L20UKMO-HADGEM1 UK 1.875x1.25, L38 1.25x1.25, L20 Uncertainties!
    13. 13. Difficulty 1. They differ on resolution
    14. 14. • Difficulty 2. They differ in availability (via IPCC) WCRP CMIP3 A1B-P A1B-T A1B-Tx A1B-Tn A2-P A2-T A2-Tx A2-Tn B1-P B1-T B1-Tx B1-TnBCCR-BCM2.0 OK OK OK OK OK OK OK OK OK OK OK OKCCCMA-CGCM3.1-T63 OK OK NO NO NO NO NO NO OK OK NO NOCCCMA-CGCM3.1-T47 OK OK NO NO OK OK NO NO OK OK NO NOCNRM-CM3 OK OK NO NO OK OK NO NO OK OK NO NOCSIRO-MK3.0 OK OK OK OK OK OK OK OK OK OK OK OKCSIRO-MK3.5 OK OK OK OK OK OK OK OK OK OK OK OKGFDL-CM2.0 OK OK OK OK OK OK OK OK OK OK OK OKGFDL-CM2.1 OK OK OK OK OK OK OK OK OK OK OK OKGISS-AOM OK OK OK OK NO NO NO NO OK OK OK OKGISS-MODEL-EH OK OK NO NO NO NO NO NO NO NO NO NOGISS-MODEL-ER OK OK NO NO OK OK NO NO OK OK NO NOIAP-FGOALS1.0-G OK OK NO NO NO NO NO NO OK OK NO NOINGV-ECHAM4 OK OK NO NO OK OK NO NO NO NO NO NOINM-CM3.0 OK OK OK OK OK OK OK OK OK OK OK OKIPSL-CM4 OK OK NO NO OK OK NO NO OK OK NO NOMIROC3.2.3-HIRES OK OK OK OK NO NO NO NO OK OK OK OKMIROC3.2.3-MEDRES OK OK OK OK OK OK OK OK OK OK OK OKMIUB-ECHO-G OK OK NO NO OK OK NO NO OK OK NO NOMPI-ECHAM5 OK OK NO NO OK OK NO NO OK OK NO NOMRI-CGCM2.3.2A OK OK NO NO OK OK NO NO OK OK NO NONCAR-CCSM3.0 OK OK OK OK OK OK OK OK OK OK OK OKNCAR-PCM1 OK OK OK OK OK OK OK OK OK OK OK OKUKMO-HADCM3 OK OK NO NO OK OK NO NO OK OK NO NOUKMO-HADGEM1 OK OK NO NO OK OK NO NO NO NO NO NO
    15. 15. Difficulty 3. limited ability to represent present climates Depender de un solo GCM es peligroso!
    16. 16. How I can use this information? Options Downscaling by Needs statistical or To increase dynamical resolution, uniformise, methods.. Problem provide high Even the most resolution and precise GCM is contextualised data too coarse (~100km)
    17. 17. The Delta Method• Use anomalies and discard baselines in GCMs – Climate baseline: WorldClim – Used in the majority of studies – Takes original GCM timeseries – Calculates averages over a baseline and future periods (i.e. 2020s, 2050s) – Compute anomalies – Spline interpolation of anomalies – Sum anomalies to WorldClim
    18. 18. Stations by variable: • 47,554 precipitation Mean annualtemperature (ºC) • 24,542 -30.1 tmean 30.5 • 14,835 tmax y tmin Sources: •GHCN •FAOCLIM Annual •WMOprecipitation (mm) 0 •CIAT •R-Hydronet 12084 •Redes nacionales
    19. 19. RCM PRECIS Providing REgional Climates for– They use outputs of Impacts Studies GCMs– Area are limited .. Need boundary conditions.– Performs calculations of atmospheric dynamics and solve equations for each grid.– Daily data– Resolution varies between 25- 50km– More than 170 output variables
    20. 20. Method + - *Easy to implement * Change variable only at big scale Statistical *  resolutions * Variables do not change their relationsdownscaling *Apply to all GCMs with time *Uniforme baseline *  variables *Few platforms (PRECIS, CORDEX) * Robust *Many processes and stockages Dynamic *Apply to GCMs if data *Limited resolution (25-50km)downscaling available *Missing development * variables *Dificulty to quantify uncertainties
    21. 21. We need models to quantify the impacts and adaptation options for effective design Based on process GCMs Statistical Downscaling MarkSim Dynamical downscaling: Regional Climate ModelBased on niches DSSAT Probability EcoCrop Statistical Downscaling Environmental gradient Effective MaxEnt adaptation options
    22. 22. Changes in climate affect the adaptability of crops… There will be winners… Number of crops with more than 5% gain…But muchmore losers indevelopingcountries Number of crops with more than 5% loss
    23. 23. http://ccafs-climate.org
    24. 24. • Downscaling is inevitable.• Continuous improvements are being done• Strong focus on uncertainty analysis and improvement of baseline data• We need multiple approaches to improve the information base on climate change scenarios  Development of RCMs (multiple: PRECIS not enough)  Downscaling empirical, methods Hybrids  We tested different methodologies

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