Fourth Study Conference on BALTEX Scala Cinema Gudhjem

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- 146 - Comparison of Simulations with the Atmosphere-Only Regional Climate Model REMO against Simulations with the Fully Coupled Regional Climate Model System BALTIMOS Philip Lorenz and Daniela Jacob Max-Planck-Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany; email: philip.lorenz@dkrz.de 1. Introduction A major task of the BALTic Sea EXperiment (BALTEX) is to simulate the water and energy cycle of the Baltic Sea catchment to identify important processes, which are relevant to the climate in the Baltic region. A fully coupled regional climate model system for the Baltic Sea region, called BALTIMOS, was developed in the framework of DEKLIM/BALTEX by linking existing model components for the atmosphere, for the ocean including sea ice, for the hydrology as well as for lakes. With this system it is possible to model the complete water and energy cycle for the Baltic catchment for today’s climate; as well as for the future with climates szenarios. The emphasis of this presentation is on the description of the model system and on the comparison of the results of the fully coupled BALTIMOS system against the results of the atmosphere only model REMO for today’s climate. 2. The DEKLIM-project BALTIMOS Figure 1. Integration of sub-projects within the BALTIMOS project DEKLIM is the German Climate Research Programme (2001 – 2006) funded by the Federal Ministry of Education and Research (BMBF). Within DEKLIM there is a project called “BALTIMOS” which has the objective to develop and validate a coupled model system for the Baltic region. Nine german institutions are participating; two of them for the development and the others for the validation of the coupled model system. The linking between these subprojects of BALTIMOS is shown in figure 1. 3. Description of the coupled model system The coupled model system consists of the following highresolution components: REMO: regional atmospheric climate model. The used horizontal resolution is 1/6° (~ 18 km) with 20 vertical levels. The model domain covers the whole drainage basin of the Baltic Sea as well as major parts of Europe. BSIOM: regional ocean model for the Baltic Sea including a sea-ice component. The horizontal resolution is 5 km with 60 vertical levels LARSIM: hydrological model with lateral transport scheme; horizontal resolution is identical to REMO; the model domain is the drainage basin of the Baltic Sea. The coupling time step between all components is one hour. 4. Comparison of coupled vs. uncoupled simulations In order to estimate the added value of the above described coupled regional model system, multi year simulations of both the BALTIMOS system and the “uncoupled” (standalone) atmosphere only model REMO have been carried out. Both simulations are driven at the atmospheric lateral boundaries with ECMWF analysis data. In the uncoupled run the sea surface temperature (SST) and ice surface temperature (IST) analysed by ECMWF are prescribed; while in the coupled run SST and IST are provided by the ocean/sea-ice model BSIOM. The atmospheric results of these simulations will be compared against each other. Also comparisons of the results with atmospheric observations will be presented as far as reasonable. References Bremicker, M.: Das Wasserhaushaltsmodell LARSIM; Modellgrundlagen und Anwendungsbeispiele, Freiburger Schriften zur Hydrologie, Band 11, 2000 Jacob, D., U. Andrae, G. Elgered, C. Fortelius, L. P. Graham, S. D. Jackson, U. Karstens, Chr. Koepken, R. Lindau, R. Podzun, B. Rockel, F. Rubel, H.B. Sass, R.N.D. Smith, B.J.J.M. Van den Hurk, X. Yang: A Comprehensive Model Intercomparison <strong>Study</strong> Investigating the Water Budget during the BALTEX- PIDCAP Period, Meteorology and Atmospheric Physics, Vol.77, Issue 1-4, pp. 19-43, 2001 Jacob, D.: A note to the simulation of the annual and interannual variability of the water budget over the Baltic Sea drainage basin, Meteorology and Atmospheric Physics, Vol.77, Issue 1-4, pp. 61-73, 2001 Lehmann, A. and Hinrichsen, H.-H.: On the thermohaline variability of the Baltic Sea, J. Marine Systems, Vol. 25, Issue 3-4, pp. 333-357, 2000
- 147 - Significance of Feedback in Land-Use Change Studies J. Overgaard 1 , M. B. Butts 2 , D. Rosbjerg 1 1 Technical University of Denmark, Department of Hydrodynamics and Water Resources, Lyngby, Denmark, Jeo@er.dtu.dk 2 DHI Water and Environment, Hørsholm, Denmark Traditionally, hydrological impact assessment of landuse changes is carried out by forcing hydrological models with time series of climate observations. The underlying assumption is that a change in land-surface properties will not influence on the atmospheric conditions. However, it can be expected that a change in land-surface properties will have a significant impact on the local and down-wind atmospheric conditions. These feedback mechanisms may work to either dampen or amplify the sensitivity of the simulated surface fluxes to changes in the land-surface properties and hence dampen or amplify the impact of land use changes. This study seeks to quantify the effect of feedback on model sensitivity using a non-hydrostatic atmospheric meso-scale model coupled to a hydrological model through a shared Soil-Vegetation-Atmosphere-Transfer (SVAT) model. The effect of feedback for regional scale land-use changes is investigated by applying the modelling system in 1D mode. The simulation period is 24 hours. Initially, a sensitivity experiment is carried out for both the coupled and uncoupled SVAT. Three land-use types are investigated. In coupled mode, the climate is dynamically simulated and in uncoupled mode, the SVAT is forced by time series of simulated climate, extracted from the coupled model for each land-use type. This ensures that, for reference land-use conditions, the coupled and uncoupled model yields exactly the same results. Sensitivities for each of the three land-use types are calculated and compared for the coupled and uncoupled systems by perturbing the vegetation parameters for each land-use conditions. The difference in sensitivity indicates the significance of atmospheric feedback. The sensitivity of latent heat flux for three different land-use types (Agriculture, natural vegetation and forest) to changes in stomata resistance are shown in figure 1. Three different soilmoisture conditions are (wet, intermediate and dry) are represented. Wet Intermediate Dry Figure 1: Relative sensitivity [-] of latent heat flux to changes in minimum stomata resistance in the coupled (RS-c) and uncoupled (RS-uc) model system. The white bars (F) show the ratio between the coupled and uncoupled sensitivity. The results in figure 1 show that atmospheric feedback has a dampening effect on the sensitivity to a change in stomata resistance, and reduces the relative sensitivity by up to 60%. Results from similar sensitivity experiments (not shown here) show that atmospheric feedback increases sensitivity of latent heat to a change in albedo by up to 70%, and dampens sensitivity to a change in leaf area index by up to 30%. To assess the consequences of not allowing atmospheric feedback in regional land-use change studies, several landuse change scenarios were carried out in both coupled and uncoupled mode and the impact compared. Figure 2 shows the difference in the predicted impact of a agriculture-toforest land use change study. Figure 2: The difference in the predicted impact of a agriculture-to-forest land-use change study. The hatched bars show the difference in the predicted change, while the black bars show the absolute difference in the simulated fluxes. The results in figure 2 show that the difference in the predicted change is significant. For example, the simulated change in total latent heat flux is 54% higher in the uncoupled system than in the coupled system. The absolute difference in latent heat flux is 6%. The corresponding change in total sensible heat flux is 134% higher in the coupled system than in the uncoupled system. Due to a strong dependence of the importance of atmospheric feedback to land-use properties, soil type, climate and scale, no general conclusions should be made from the results shown here. However, the results do indicate that, at least for regional land-use change studies, feedback can have a significant effect on the predicted impact and needs to be taken into consideration.
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Fourth Stu
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Preface The 4 th Study</str
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- I - Table of Abstracts Title Auth
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- III - Sensitivity in Calculation
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- V - Parameter Estimation of the S
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- VII - The Realism of the ECHAM5.2
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Adam, W. K. .......................
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- 1 - Activities of the GEWEX Hydro
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eference site archive (Cabauw, Neth
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- 5 - Remote Sensing of Atmospheric
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minute averages around the satellit
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- 9 - Precipitation Type Statistics
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- 11 - Assimilation of New Land Sur
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Multichannel Microwave Radiometer f
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output has been processed in an equ
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height dependence of the Z-R-relati
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- 19 - CERES and Surface Radiation
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- 21 - Coastal Wind Mapping from Sa
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- 23 - Clouds and Water Vapor over
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- 25 - Broadband Cloud Albedo from
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- 27 - Observation of Clouds and Wa
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shows a ground-track of the vessel
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- 31 - Determination and Comparison
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- 33 - Spatial Variability of Snow
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- 35 - EVA-GRIPS: Regional Evaporat
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- 37 - LITFASS-2003 - A Land Surfac
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-39- Calibrated Surface Temperature
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- 41 - The Marine Boundary Layer -
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- 43 - Characteristics of the Atmos
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Figure 2. Surface stress from two d
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During the experiment the water was
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While the number of smallest drops
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SCANDIA will not be supported any l
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- 53 - Relationships Between Precip
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- 55 - Analysis of the Role of Atmo
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- 57 - Meteorological Peculiarities
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Baltic Sea Inflow Events Jan Piechu
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- 61 - The Different Baltic Inflows
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- 63 - Observations of Turbulent Ki
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- 65 - The Influence of Synoptic Si
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-67- Improved Method for the Determ
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-69- The Helicopter-Borne Turbulenc
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- 71 - CEOP Reference Site Data fro
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- 73 - The BALTEX Hydrological Data
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- 75 - Hydrological and Hydrochemic
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-77- Sea-level Monitoring at MARNET
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1 0.8 0.6 0.4 0.2 GO(CLD-M) ERA40 S
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Figure 2. Monhly mean values of lat
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In the case of an ideal fit, the co
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- 85 - Influence of Atmospheric For
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The largest inter-annual variabilit
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References Andrejev, O, Sokolov, A.
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On the other hand, if the stratific
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Cyberska 1989, Cyberska and Krzymin
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Page 115 and 116: The subsurface flow calculation is
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Page 119 and 120: - 103 - Modelling the Impact of Ine
Page 121 and 122: - 105 - Objective Calibration of th
Page 123 and 124: - 107 - Validation of Boundary Laye
Page 125 and 126: - 109 - Simulated Dynamical Process
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Page 131 and 132: Figure 2. Long-term variability in
Page 133 and 134: obvious from temperature charts. Ho
Page 135 and 136: shortening of the winter seasons by
Page 137 and 138: Maximum 5 day precipitation (mm) Nu
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Page 143 and 144: - 127 - Storminess on the Western C
Page 145 and 146: - 129 - Trends in Wind Speed over t
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Page 149 and 150: - 133 - Detection of Climate Change
Page 151 and 152: Figure 3. Cross section of salinity
Page 153 and 154: of 35 m/s up to 3 hours. Data on wi
Page 155 and 156: Figure 2. Time series of Mean Sea L
Page 157 and 158: - 141 - Calculation and Forecast of
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Page 161: - 145 - Baltic Sea Saltwater Inflow
Page 165 and 166: Lindström, G., Johansson, B., Pers
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Page 177 and 178: conditions even more challenging th
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Page 189 and 190: 6. Results There are many possible
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Page 193 and 194: The structure of water bodies cadas
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Page 199 and 200: - 183 - Generating Synthetic Daily
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Page 203 and 204: Model parameters and coefficients:
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Fourth Study Conference on BALTEX Scala Cinema Gudhjem

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