Deliverable D1.2 Technical report with the characteristics of the models. Atmospheric model WRF-ARW

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1 Deliverable D1.2 Technical report with the characteristics of the models Atmospheric model WRF-ARW The Weather Research and Forecasting (WRF) Model ( is an advanced mesoscale numerical weather prediction system. It is suitable for operational forecasting as well as for research purposes. It has many features like multiple dynamical cores, a 3-dimensional variational (3DVAR) data assimilation scheme and it may work on parallel platforms (Michalakes et. al., 2004, William et. al, 2008). Moreover, it is suitable for a wide area of applications with its spatial resolution ranging from meters to thousands of kilometers. The development of WRF has been a collaborative partnership, principally among the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (the National Centers for Environmental Prediction (NCEP) and the Forecast Systems Laboratory (FSL), the Air Force Weather Agency (AFWA), the Naval Research Laboratory, the University of Oklahoma, and the Federal Aviation Administration (FAA). WRF allows researchers the ability to conduct simulations reflecting either real data or idealized configurations. WRF provides operational forecasting a model that is flexible and efficient computationally, while offering the advances in physics, numerics, and data assimilation contributed by the research community. WRF has a rapidly growing community of users, and workshops and tutorials are held each year at NCAR. WRF is currently in operational use at NCEP, AFWA and other centers. The atmospheric modelling system has been installed at the computer infrastructure of the Cyprus Oceanography Center (OC-UCY) and of the Hellenic Naval Academy (HNA). Fine tuning and adaptation to the local environment test-cases have been also performed in order to reach an optimum configuration of the model. The proposed configuration for the WRF-ARW model is: Horizontal Resolution: 0.1 degrees 35 vertical levels 4 soil levels 60 hours forecasting (up to 120h) GFS atmospheric input (GRIB2 format) 00UTC start time (may change to 12UTC) Nested domain (2-way nesting): Cyclades-Central Aegean Horizontal Resolution: 0.02degrees 35 vertical levels 4 soil levels 60 hours forecasting (up to 120h) 00UTC start time (may change to 12UTC)

2 Output-Post processing Model output: Netcdf files Post process tools: NCL, Matlab Some indicative results of the tests performed, are presented here. Fig. 1: Temperature at 2m height for the greater Mediterranean region. Fig. 2: Wind at 10m height for the greater Mediterranean region.

3 Fig. 3: Skin temperature (degrees Kelvin) for the greater Mediterranean region. Fig. 4: Surface temperature, Sea level pressure and Wind for the greater Mediterranean region.

4 Fig. 5: Sea level pressure for the USA region. Fig. 6: Water vapor mixing ratio for the greater Mediterranean region.

5 Ocean wave model WAM: A state of the art numerical sea wave analysis and prediction system has been installed in the Cyprus Oceanography Center and Hellenic Naval Academy s computer infrastructure. This is based on the latest version of WAM model (Komen G.J. et. al., 1994; WAMDIG, 1988), which is recognized today as one of the most reliable models, being widely used by several operational and research centers worldwide. The new WAM version is enriched with improvements in the advection scheme and the parameterization of shallow water effects, concerning both the time evolution of the wave spectrum and the determination of the kurtosis of the wave field. The wave model WAM (WAMDIG, 1988; Komen et al., 1994) is a third generation wave model which solves the wave transport equation explicitly without any presumptions on the shape of the wave spectrum. It represents the physics of the wave evolution in accordance with our current knowledge and uses the full set of degrees of freedom of a 2d wave spectrum. The model runs for any given regional or global grid with a prescribed bathymetric dataset. The grid resolution can be arbitrary in space and time. The propagation can be done on a latitudinal longitudinal or on a Cartesian grid. The model can run for deep and shallow water (from the abyssal seas up to a few meters) and includes the effect of wave refraction from changes in depth and from ocean currents. The integration can be interrupted and restarted at arbitrary times. In the framework of the MOSEP project, the ECMWF version, CY33R1 (Jansen, 2000; Bidlot and Janssen, 2003) has been adopted. This new version contains a number of important updates that increase significantly the potential capabilities of the wave system. In particular, the following improvements, comparing to older WAM systems, have been adopted: 1. A new advection scheme is used by the introduction of contributions from the corner points. More precisely, in older versions the wave energy balance equation F ( ugf) ( vgf) 0, t x y where F is the wave variance spectrum and (ug,vg) the group speed, was solved using a first order upwinding scheme considering contributions from neighboring points only in x and y directions ignoring the corners of the grid used in the local calculation. In this way, no contributions from the corners of the grid were considered. In the new version of the model the advection scheme is extended to account also for the corner points by using the Corner Transport Upstream scheme providing a more uniform propagation in all directions.

6 2. Following the work of Janssen and Onorato (2007), a new parametrization of shallow water effects is introduced that affects both the time evolution of the wave spectrum and the determination of the kurtosis of the wave field. 3. Two extreme wave parameters have been introduced, namely the average maximum wave height and the corresponding wave period. Following the work of Mori and Janssen (2006), it is suggested to use the maximum wave height, observed during a period of length T as an indicator of how extreme the sea state is. For a known probability distribution of the sea surface elevation it is shown how to obtain an estimate of the average maximum wave height. 4. A number of technical modifications have been made, concerning the way that the minimum time step can be defined, and has proven valuable for the use of the model in high resolution grids. After the installation and testing, WAM model will be used for the simulation of the main sea wave parameters (significant wave height and direction, wave period and wind speed), necessary for power applications, for a ten-year period covering the Greek sea areas at a very high resolution. The proposed configuration of WAM is the following Wave model Characteristics WAM ECMWF CY33R1 Model s domain Mediterranean (29N 47N, 6W 42E) Horizontal Resolution 0.10 x 0.10 degrees Frequencies 25 (range Hz logarithmically spaced) Directions Timestep 24 (equally spaced) 120 sec The model outputs cover a wide range of wave parameters and components. More precisely, for each grid point of the domain, the following data are provided: S_WHT = Significant Wave Height in m

7 MEANWDIR = Mean Wave Direction in deg (meteorological convention) PEAK_FR = Peak Frequency in Hz MEAN_FR = Mean Frequency in Hz USTAR = Friction Velocity in m/sec WIND_DIR = Wind Direction in deg CDG = Drag Coefficient WIND_SPEED = Wind Speed at 10m in m/sec DEPTH = Model Bathymetry in m MAXWH = Maximum Wave Height in m MAXWP = Maximum Wave Period in sec SWE_H = Swell Wave Height in m MEANSDIR = Mean Swell Direction in deg (meteorologcal convention) MEANSFR = Mean Swell Frequency in Hz WSEA_H = Wind Sea Wave Height in m WSEAD = Wind Sea Direction in deg WSEA_FR = Wind Sea Frequency in Hz MSP1 = Mean Swell Period 1 in sec MSP2 = Mean Swell Period 2 in sec MWSEAP1 = Mean Wind Sea Period 1 in sec MWSEAP2 = Mean Wind Sea Period 2 in sec Some results of the test cases performed for the wave model are presented below: Fig. 7: Significant wave height and direction for the Mediterranean Sea.

8 Fig. 8: Swell height and direction for the Mediterranean Sea. Fig. 9: Mean wave period and direction for the Mediterranean Sea. References: Bidlot, J. and Janssen, P. 2003: Unresolved bathymetry, neutral winds and new stress tables in WAM. ECMWF Research Department Memo R60.9/JB/0400. Jansen, P.A.E.M., 2000: ECMWF wave modeling and satellite altimeter wave data. In D. Halpern (Ed.), Satellites, Oceanography and Society, pp , Elsevier. Janssen, P.A.E.M., and M. Onorato, The Intermediate Water Depth Limit of the Zakharov Equation and Consequences for Wave Prediction. J.Phys.Oceanogr.37,

9 Komen G., Cavaleri L., Donelan M., Hasselmann K., Hasselmann S., Janssen P.A.E.M., 1994: Dynamics and Modelling of ocean waves, Cambridge University Press. Michalakes, J., J. Dudhia, D. Gill, T. Henderson, J. Klemp, W. Skamarock, and W. Wang, 2004: "The Weather Reseach and Forecast Model: Software Architecture and Performance,"to appear in proceedings of the 11 th ECMWF Workshop on the Use of High Performance Computing In Meteorology, October 2004, Reading U.K. Ed. George Mozdzynski. Mori N. and P.A.E.M. Janssen, 2006: On kurtosis and occurrence probability of freak waves. J. Phys. Oceanogr. 36, WAMDIG, The WAM-Development and Implementation Group: Hasselmann S., Hasselmann K., Bauer E., Bertotti L., Cardone C.V., Ewing J. A., Greenwood J.A., Guillaume A., Janssen P. A. E. M., Komen G. J., Lionello P., Reistad M., Zambresky L., 1988: The WAM Model - a third generation ocean wave prediction model, Journal of Physical Oceanography, 18(12), William C. Skamarock, Joseph B. Klemp, Jimy Dudhia, David O. Gill, Dale M. Barker, Michael G. Duda, Xiang-Yu Huang, Wei Wang, Jordan G. Powers, A Description of the Advanced Research WRF Version 3, NCAR TECHNICAL NOTE, June 2008