Mauro Sulis
- 1. A synthesis of modeling and observa4onal data for an integrated assessment of the catchment-‐scale energy and water cycle Mauro Sulis Meteorological Ins4tute, University of Bonn Workshop on Coupled Hydrological Modeling Padova, September 23-‐24 2015
- 2. Collaborators Prabhakar Shrestha (MIUB) Sandra Steinke (Uni-‐Köln) Susanne Crewell (Uni-‐Köln) Clemens Simmer (MIUB) Stefan Kollet (IBG3)
- 3. Introduc4on The hydrological and meteorological community have recently converged toward a new integrated simula5on paradigm. Holis5c and physically-‐based view of the energy, water, and ma=er cycle across a range of spa5al and temporal scales. New opportuni5es and grand challenges: Integrated diagnosis of the catchment-‐scale energy and water cycle using fully-‐coupled simula5ons and observa5ons. Mo#va#ons of the work: • Powerful tools to test scien5fic hypothesis. • Integrated assessment of the water cycle for long-‐term climate projec5ons and short-‐ and medium-‐term weather forecasts. • Improved monitoring networks (e.g., mul5ple co-‐located measurements) that cover the SVA con5nuum.
- 4. Outline • Study area • Observa4onal dataset • TerrSysMP • Model setup • Results • Conclusions
- 5. Study area North-‐Rhine Westphalia (NRW) domain Land use classes: Topography: Al4tude range: 15 – 700 m • Cropland (~34 %) • Evergreen forest (~14 %) • Deciduous forest (~17%) • Grassland (~25 %)
- 6. • Study area • Observa4onal dataset • TerrSysMP • Model setup • Results • Conclusions
- 7. Observa4onal dataset – descrip4on 1HD(CP)2 Observa4onal Prototype Experiment (HOPE);2TERrestrial ENvironmental Observatories (TERENO) 3Jülich ObservatorY for Cloud Evolu4on (JOYCE);4Transregional Collabora4ve Research Centre – 32 (TR32) Data sources: TERENO2, JOYCE3, Er` Verband, and TR324 Time period: April – May 2013 HOPE1 campaign Variables: States, fluxes, and diagnos5cs across the subsurface, land surface, and atmosphere compartments of the terrestrial system. • Radia4on balance composites (radiometers) • Energy fluxes (eddy covariance measurements) • Soil moisture (cosmic-‐ray probes) • Precipita4on (X-‐band composites) • Boundary layer height • Water table depth • Humidity and temperature profiles (mul4ple meas.)
- 8. Observa4onal dataset – temporal distribu4on Average data coverage: 70% 56% 64% 70% 67% 67% 66% 67% 86% 76% 76% Latent heat Sensible heat 2m humidty Incoming longwave Emiged longwave Incoming shortwave Reflected shortwave 2m temperature 10m u-‐wind 10m v-‐wind
- 9. Observa4onal dataset – spa4al distribu4on
- 11. TerrSysMP COSMO Convec4on permihng configura4on (COSMO-‐DE) (Baldauf et al. 2011). CLM Land surface scheme (Oleson et al. 2008). ParFlow Integrated surface-‐subsurface flow model with terrain following coordinates (Kollet and Maxwell, 2006; Maxwell, 2012). OASIS3 – OASIS-‐MCT External coupler with mul4ple executable approach (Valcke 2013). Model developments, improvements, and applicaLons: Shrestha et al., 2014 MWR; Gasper et al., 2014 GMD; Sulis et al., 2015 JHM; Rahman et al., 2015 AWR Shrestha et al., 2014 MWR
- 13. Model setup SpaLal resoluLon: • COSMO: ΔX = ΔY = 1000 m • ParFlow-‐CLM: ΔX = ΔY = 500m Temporal resoluLon: • COSMO: Δt = 10 sec • ParFlow-‐CLM: Δt = 900 sec Coupling frequencies: • COSMO-‐CLM: CPL1 = 900 sec • CLM-‐ParFlow: CPL2 = 900 sec Boundary condiLons: • COSMO: Hourly reanalysis COSMO-‐DE forcing • ParFlow: No-‐flux condi4ons
- 15. Results – Radia4on balance *bias = (Xsim — Xobs) / Xobs Systema4c overes4ma4on of the net shortwave radia4on by TerrSysMP. Beger match of the net longwave,with the excep4on of Wuestbach.
- 16. Results – Radia4on balance Analysis of the shortwave radia5on composites: screening for “clear-‐sky” days Overes4ma4on of incoming shortwave: cloudiness effect. Underes4ma4on of reflected shortwave: albedo parameterizaLon.
- 17. Results – Radia4on balance Analysis of the longwave radia5on composites: screening for “clear-‐sky” days Underes4ma4on of incoming longwave: liquid water path. Good agreement in the emiged longwave: land surface temperature.
- 18. Results – Atmospheric states Analysis of the integrated water vapor (IWV): Slight underes4ma4on of the simulated IWV, especially with respect to MWR, and late in the a`ernoon. TerrSysMP response is consistent with COSMO-‐DE lateral BCs.
- 19. Results – Energy fluxes TerrSysMP overesLmates H, larger Bowen ra4os for most of the sta4ons.
- 20. Results – Land surface states Soil moisture dynamics : Soil porosity Underes5ma5on of precipita5on
- 21. Results – Land surface states Soil moisture dynamics :
- 23. Conclusions • Need of an accurate assessment of the radia4on balance. • Dras4c influence of local features in the soil moisture dynamics and par44oning of land surface energy fluxes. • Soil moisture dynamics generally well reproduced. • Es4mate the integrated water balance. • Perform ensemble simula4ons (e.g., COSMO-‐DE-‐EPS). • Extend the simula4on to longer 4me periods. Preliminary results: Next steps: • Coherence in observa4ons and modeling results.
- 24. Acknowledgments Alexander Graf and Marius Schmidt (IBG3-‐FZJ) Roland Baatz and Heye Bogena (IBG3-‐FZJ) Malte Diederich (MIUB) Stefan Simon (Er` Verband) Jan Schween (Uni-‐Köln) Sidney Marschollek (MIUB)