Mauro Sulis

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.

Outline

•  Study area •  Observa4onal dataset •  TerrSysMP •  Model setup

•  Results

•  Conclusions

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 %)


•  Results

•  Conclusions

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

Observa4onal dataset – spa4al distribu4on


•  Results

•  Conclusions

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


•  Results

•  Conclusions

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

•  Conclusions

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.


Analysis of the shortwave radia5on composites:

screening for “clear-‐sky” days

Overes4ma4on of incoming shortwave: cloudiness effect. Underes4ma4on of reflected shortwave: albedo parameterizaLon.


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.

Results – Energy fluxes

TerrSysMP overesLmates H, larger Bowen ra4os for most of the sta4ons.

Results – Land surface states

Soil moisture dynamics :

Soil porosity

Underes5ma5on of precipita5on

Results – Land surface states

Soil moisture dynamics :


•  Results

•  Conclusions

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.

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)

Science

Mauro Sulis