Aaron Boone and Bertrand Decharme CNRM-GAME Météo-France SWOT Meeting, Sep.15-17, Columbus, OH.

1. SWOT measurements for improving hydrological parameterizations in Regional and Global Climate Models Aaron Boone and Bertrand Decharme CNRM-GAME Météo-France SWOT Meeting, Sep.15-17, Columbus, OH.

2. GCM: Global Climate Model • Typical GCM configuration: • 15-30 vertical levels • 1-5 degree horiz resolution • *RCM higher res (n,z,t) (sub-domain, downscaling…) • This limits the level of complexity: only first order processes relevant to the climate are considered…

3. Modes of usage: • High resolution (~50 km)  10 years • Climate Projection (~1-5 deg)  100 years • * fixed SSTs OR fully coupled OGCMs • Long term, paleo-climate 1000+ years… • * Regional (RCM) : downscaling. Large scale forcing imposed (possibly by re-analysis data)  process studies

4. GCM-system of models for different Processes: Example at Météo-France: MOCAGE atmospheric chemistry ARPEGE (GCM) ALADIN (RCM) ISBA continental land surface TRIP river routing Oasis Coupler GELATO sea ice OPA NEMO ocean model

5. Goal of Continental hydrology in GCMs: the past • (although still the present for some GCMs): • Obtain good estimates of the surface latent heat flux (implies correct paritioning of incoming net radiation into evaporation and atmospheric sensible heating) • Implies a good estimate of the paritioning between infiltration, runoff and soil storage • Runoff purely a diagnostic Present & Future…the dream: Estimates of river discharge from climate change simulations can aslo be used to assess the impact of climate change on water resources and the hydrology of the major river basins. Arora and Boer, 1999, JGR

6. GCM representation of continental hydrology: • Representation of wetlands, bogs • Lake parameterizations • Flooded zones: dynamics, interactions with lakes, rivers • Freshwater discharge into sea/oceans • River/Groundwater exchanges • Precipitation spatial distribution at the surface • Snow, ice (permafrost) representations • Soil moisture, energy balance (evapotranspiration…) • Runoff (Dunne and Horton) and baseflow

7. GCM representation of continental hydrology: • Representation of wetlands, bogs generally not accounted for explicitly • Lake parameterizations often prescribed Tsfc or 1D thermal transfer • Flooded zones: dynamics, interactions with lakes, rivers few GCMs • Freshwater discharge into sea/oceans…explicit, implicit, just a diagnostic • River/Groundwater exchanges few GCMs • Precipitation spatial distribution at the surface few GCMs • Snow, ice (permafrost) representations • Soil moisture, energy balance (evapotranspiration…) • Runoff (Dunne and Horton) and baseflow • Important to keep in mind: the above are primarily sub-grid parameterizations, and there are restrictions on the complexity. Also, resulting feedback mechanisms must be studied carefully…

8. ISBA-TRIP coupling system • Land surface model (ISBA) model to genrate runoff • River routing using TRIP (1 or 0.5 degrees)

9. The ISBA-TRIP coupling system TRIP ISBA • Prognostic variables: • The river height, hs • The river flow velocity, v (Manning formula) • The floodplain volume (calculated using the sub-grid topography) • Other important variables: • The flood fraction, fflood • The flood height, hf • Evaluations: • In-situ river discharge • Satellite-derived wetland estimates (Prigent et al., JGR, 2007) • SWOT derived slope, depths, floodplain water depth and extent…(d /dt) (Decharme et al., 2007, JGR)

10. The ISBA-TRIP coupling system TRIP ISBA Key scientific question for SWOT: better quantify the echange between rivers and floodplains for improved prediction Development Methodology • Improve in « offline » mode  validation with obs and/or assimilation • Use in (fully-coupled) projection  extrapolate in n,t ! • * NEED Global scale data! Key variables from SWOT

11. Spatial comparison between the Flood experiment and the Satellite-derived wetland estimates % % Satellite-derived wetland estimates from Prigent et al. (2007, JGR). ISBA-TRIP flood-plain simulation Difference

12. 2 simulations (10-years atmospheric forcing from GSWP-2 at 1° by 1°): with (Flood) and without (CTL) the flooding scheme • Evaporation from floodplains quite significant for some regions: possible feedbacks with atmosphere… GSWP-2, Dirmeyer et al., 2006

13. Inconvenient Truth: reliable river discharge in climate projections is still a ways off… West African Monsoon Modelling and Evaluation (WAMME) Project Y. Xue, B. Lau, et al. • 14 GCM and 4 RCM simulations • 2000, 2003, 2004, 2005 • Use AMMA Land surface Model Intercomparison Project (ALMIP)Forcing and simulated fields to evaluate fully coupled WAMME models (surface component)

15. Large biases in terms of the placement of the monsoon rains by the GCMs & RCMs • Turns out, ensemble AVG good!

16. Cimate Projections: • SWOT data esp important a high lats in the context of projected climate change: a sample of IPCC Météo-France results…(B2 scenario) • Significant Change in regimes for: • Wetlands, flooded zones • Lakes • Discharge (potenial feedbacks with ocean and ice….) • Wetland Carbon, Methane emssions… Need global scale data to develop & improve parameterizations for useful climate projections of hydrological impacts!

17. Message: The main need for SWOT products in terms of GCM applications is to provide multi-year data at the global scale of discharge, water height and slope within the context of improving the hydrological parameterizations: notably in terms of exchanges between rivers and floodplains, changes in lakes/wetlands, and freshwater discharge into the oceans. Critical if we are to have reliable estimates of projected changes in water storage and river volume, and possible feedbacks with the atmosphere… • Some caveats: • Precipitation generally not well predicted by GCMs, notably for monsoon circulations • Not all GCMs include river/floodplain, lake, wetland models • Ditto for carbon and methane wetland processes • Need multi-year records to develop robust GCM parameterizations (length of SWOT mission? Followup?) Partly due to a lack of adequate data…

18. Extra…………..

19. Some words on assimilation: GCMS not really relevant RCMs could be, but… Reanalysis…don’t use GCMs, but NWP at global scale (GFS, ECMWF)….but need to incorporate river routing/floodplain type models

20. Potential research and operational hydrology applications of WATER-HM at Météo-France • I) Need to evaluate river routing and floodplain parameterizations for use in GCMs and regional scale modeling: • Used to study possible global climate change impacts on flood risk/frequency • Long term impact on lake storage: possible aid to water resource planning (seasonal and long term) • Better description of lake changes at high latitudes: links with freeze thaw, greenhouse gas release • NEED river depth, floodplain depth/extent, river velocity: WATER-HM probably adequate! • *End Result: Better river discharge/routing, lake parameterizations to be utilized within fully-coupled OGCM model (complete description of water cycle) • II) Operational Hydrological Forecasting: • Real-time monitoring of the water resources at the national level (France): SAFRAN-ISBA-MODCOU distributed hydrological modeling system • Ensemble streamflow forecast studies: initialized using current river heights: potential flood risk forcasted • NEED high spatial resolution (100m probably not fine enough?) and daily (?) observations • Potential uses in developing countries with relatively low spatial density observational discharge/river monitoring networks (eg. Western Africa)

21. Conclusions & Perspectives • Good results in terms of river discharges. • Reasonable agreement between the simulated flooded areas and Satellite-derived wetland estimates. • Must be confirmed over other large river basins using an extended atmospheric forcing such as the global 1948-2000 dataset of Sheffield et al. (J. Climate, 2006). • Nevertheless, underestimation of floodplains compared to satellite data. • Some limitations could be raised by adding an explicit representation of lakes, marshes, and large ponds. • Other limitations come from the lack of global and temporal observations like: • River and/or floodplains height • River velocity

22. Assesment of a 10-year application of SIM-France Comparison of the daily riverflow The SAFRAN-ISBA-MODCOU (SIM) hydrometeorological model applied over France Spatial repartition of the discharge error: • Real-time monitoring of the water resources at the national scale • Ensemble streamflow forecast studies Two kinds of Ensemble streamflow were tested: Long term : 10-day forecast, using ECMWF EPF (50 members + ctrl) Rousset et al., ECMWF Newsletter 2007 Short term: 2-day forecast, using PEARP EPF (10 members + ctrl) Thiriel et al., submitted 2007 *The SIM real-time application is used to initialize the ensemble streamflow forecast: could be improved using real-time WATER-HM Habets, Boone, Champeaux, Etchevers, Franchistéguy, Leblois, Ledoux, Le Moigne, Martin, Morel, Noilhan, Quintana-Segui, Rousset, Viennot

23. Potential research and operational hydrology applications of WATER-HM at Météo-France • I) Need to evaluate river routing and floodplain parameterizations for use in GCMs and regional scale modeling: • Used to study possible global climate change impacts on flood risk/frequency • Long term impact on lake storage: possible aid to water resource planning (seasonal and long term) • Better description of lake changes at high latitudes: links with freeze thaw, greenhouse gas release • NEED river depth, floodplain depth/extent, river velocity: WATER-HM probably adequate! • *End Result: Better river discharge/routing, lake parameterizations to be utilized within fully-coupled OGCM model (complete description of water cycle) • II) Operational Hydrological Forecasting: • Real-time monitoring of the water resources at the national level (France): SAFRAN-ISBA-MODCOU distributed hydrological modeling system • Ensemble streamflow forecast studies: initialized using current river heights: potential flood risk forcasted • NEED high spatial resolution (100m probably not fine enough?) and daily (?) observations • Potential uses in developing countries with relatively low spatial density observational discharge/river monitoring networks (eg. Western Africa)