A synthesis of modeling and observa4onal data for an integrated assessment of the catchmentscale energy and water cycle Mauro Sulis Meteorological Ins4tute, University of Bonn Workshop on Coupled Hydrological Modeling Padova, September 2324 2015
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
Collaborators
Prabhakar Shrestha (MIUB) Sandra Steinke (Uni-‐Köln) Susanne Crewell (Uni-‐Köln) Clemens Simmer (MIUB) Stefan Kollet (IBG3)
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.
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 %)
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.)
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
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
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
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.
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.
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.
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.
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.