Laux, P.

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KIT – Universität des Landes Baden-Württemberg und nationales Forschungszentrum in der Helmholtz-Gemeinschaft IINSTITUTE OF METEOROLOGY AND CLIMATE RESEARCH, GARMISCH-PARTENKIRCHEN, GERMANY www.kit.edu   Short introduction to WP1:  “Climate variability and seasonal prediction”  Patrick Laux  Institute of Meteorology and Climate Research  IMK-IFU  2 Overview of envisaged working tasks WT1.1: Quantification and predictability of climatic parameters affecting    rice growth at sensitive development stages  WT1.2: Long term regional climate simulations to study the impact of  LUC/LCC on climate  WT1.3: Quantification of climate induced uncertainties for future rice  production in EA   RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  3 Seasonal climate predictions: State-of-the-art  Problems for end-users:  • Sensitivity of crops to climatic variability is modulated at intraseasonal time scale and farmers mostly depend on local-scale climatic variability  • Tercile information not sufficient and no answers to intraseasonal issues  • Limited predictive skill:  almost no skill for JFM/AMJ, and moderate skill for OND  seasonal resolution may mask predictability if intraseasonal rainfall not matched the modulation of predictability RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  4 WT 1.1: Specific Objectives To analyze the intraseasonal modulation of predictable signals of rainfall jointly with the spatial coherency of the predictable signal (prerequisite for seasonal prediction)  To quantify the predictability of extreme events which severely affect rice growth  To analyze the predictability crucial intraseasonal features for different rice varieties at different spatiotemporal scales Start of wet season to determine suitable planting windows for rice Intraseasonal probabilities of dry spells etc.   RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  12-06-11 Institute of Meteorology and Climate Research  IMK-IFU  5 Methods 2-tiered forecast system (at IRI):  Forecasts of global tropical SSTs  Application for the suite of atmospheric models that respond to SST forcing  → surface temperature and precipitation anomaly patterns   Predictor screening (other than SST) for model improvement    Statistical analysis to assess the level of predictability of predictand (jointly with coherency of the predictand)           RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  6 Milestone: A prediction system … Current Seasonal Predictions End users Local scales /  Daily Regional to global / Seasonal NOISE  Signal Improved Intraseasonal  Predictions ? RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  7 Milestone: … accounting for vulnerability of rice (varieties) during development  Yoshida, 1978 Assessing vulnerability also for water availability, radiation, … Vulnerability:  1-2 hours of high T at anthesis result in large fraction of grain sterility! Overall objectives: Optimize planting dates of rice (varieties) to avoid crop  failure & stabilize food security! RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  8 Overview of envisaged working tasks WT1.1: Quantification and predictability of climatic parameters affecting    rice growth at sensitive development stages  WT1.2: Long term regional climate simulations to study the impact of  LUC/LCC on climate  WT1.3: Quantification of climate induced uncertainties for future rice  production in EA   RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  12-06-11 Institute of Meteorology and Climate Research  IMK-IFU  9 Regional climate predictions: State-of-the-art  Rationale: High spatiotemporal resolution climate information required for  agricultural impact studies (e.g. future rice productivity, future suitability  areas for rice growing) Problems for CC impact modelers:  • Description of the land surface not sufficient usually time-invariant, i.e. static LU maps  • Poor representation of lateral (subsurface and overland) fluxes: the process formulations of land surface schemes describe the vertical exchange of energy and water fluxes but no lateral transport is possible  Purely scientifically issue: RCMs do not explicitly account for the effects of the mixing ratios of greenhouse gases (GHGs) other than CO2 RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  10 WT 1.2: Specific Objectives To identify the spatial “target” resolution, i.e. to which resolution is DSS giving additional information for impact studies?  To analyze  the impact of GHG induced changes, separately for different greenhouse gases, and the impacts induced by LUC/LCC on climate  To analyze the impacts of small scale lateral water fluxes at surface and subsurface on atmosphere, and thus, to analyze the feedback of LUC/LCC on precipitation patterns    RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  11 Soil-Vegetation Atmos-phereTransfer Model Methods Hydrology Δx ≈  1km…100m GCMs Atmosphere & Ocean Δx ≈ 300…100km RCMs Δx ≈ 50…10km P, T, RH, v, Rn 1.) Regional Climate Modeling (WRF) to provide input e.g. for hydrological and agricultural impact studies  2.) Model improvement (lateral water and energy fluxes)  Explicit saturated  subsurface flow 3.) Implementation dynamic LUC/LCC  Explicit diffusive wave  overland flow Δt≈ 6sec for Δx≈100m  • Supervised/unsupervised classification of RS imagery • LUC/LCC scenarios RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  12 Milestone: RCM simulations for EA with improved model compartments  30-year time slice from 1971-2000 (baseline) & two future periods (2021- 2050, 2071-2100) → using identified target resolution → accounting for LUC/LCC & GHG induced changes → accounting for lateral water and energy fluxes     Overall objectives: Improved high resolution climate data for EA to provide  more accurate data for RICE-EA impact modelers  (hydrological and crop yield modelers) RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  13 Overview of envisaged working tasks WT1.1: Quantification and predictability of climatic parameters affecting    rice growth at sensitive development stages  WT1.2: Long term regional climate simulations to study the impact of  LUC/LCC on climate  WT1.3: Quantification of climate induced uncertainties for future rice  production in EA   RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  12-06-11 Institute of Meteorology and Climate Research  IMK-IFU  14 CC/CV uncertainty estimation: State-of-the-art  Problems for end-users:  • DDS very expensive  (computing resources)  → Usually: 1 GHG scenario, 1 GCMs, 1 RCM  • Uncertainties increase with increasing modeling chain (GHG scenario, GCM, RCM, etc.) … RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  15 WT 1.3: Specific Objectives Statistically downscale meteorological variables (P, T, R) using a multi-model & multi scenario approach  To quantify uncertainties in deriving hydrometeorological variables important for rice production in EA arising from different GCMs, emission scenarios, and ESDS approaches  To judge the probability of the RCM projection derived in WT1.2    RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  12-06-11 Institute of Meteorology and Climate Research  IMK-IFU  16 Methods Different ESDS methods: Expanded Downscaling (XDS, e.g. Bürger 1996, 2002)  Multi-Objective Fuzzy Rule-Based Classification (MOFRBC, Bárdossy, 1995) Statistical analysis of the ESDS results to derive PDFs of crucial variables for rice growth in EA for the past and future time slices EV Theory to assess probability (change) of rare events  RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  17 Milestone: Derive & provide RICE-EA partners with PDFs of crucial variables for rice  growing in EA to be used for CC impact analysis      Overall objectives: Quantification of uncertainties for future rice  production in EA related to the climate drivers RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  18 To be discussed Centralized Database for RICE-EA consortium  Missing partner for supervised/unsupervised classification of RS imagery to derive LUC/LCC scenarios  Suggestions for RCM simulations (GCM, GHG scenario, which time slices, etc.?)     RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  19 RICE-EA Workshop Garmisch-Partenkirchen 13.-15. June 2012  Institute of Meteorology and Climate Research  IMK-IFU  20 RICE-EA 17.04.-19.04.2012  

Short introduction to WP1: Climate variability and seasonal prediction

https://publikationen.bibliothek.kit.edu/230087640/3816101

Short introduction to WP1: Climate variability and seasonal prediction

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