Abstract.Verification of the EBU-POM regional atmosphere-ocean coupled model (RAOCM) was carried out using satellite observations of SST and surface winds over the Adriatic Sea. The atmospheric component has a horizontal resolution of 0.125 degree (approximately 10 km) and 32 vertical levels, while the ocean component has a horizontal resolution of approximately 4 km with 21 sigma vertical levels.Verification of the forecasted SST was performed for 15 forecasts during 2006, each of them seven days long. These forecasts coincide with the operating cycle of the Adriatic Regional Model (AREG), which provided the initial fields and boundary conditions for the ocean component of EBU-POM. Two sources of data were used for the initial and boundary conditions of the atmosphere: primary data were obtained from the European Center for Medium-Range Weather Forecasting (ECMWF), while data from National Centers for Environmental Prediction (NCEP) were used to test the sensitivity to boundary conditions. Forecast skill was expressed in terms of BIAS and root mean square error (RMSE). During most the of verification period, the model had a negative BIAS of approximately −0.3 • , while RMSE varied between 1.1 • and 1.2 • . Interestingly, these errors did not increase over time, which means that the forecast skill did not decline during the integrations.The 10-m wind verification was conducted for one period of 17 days in February 2007, during a strong bora episode, for which satellite estimates of surface winds were available. During the same period, SST measurements were conducted twice a day, which enabled us to verify diurnal variations of SST simulated by the RAOCM model. Since ECMWF's deterministic forecasts do not cover such a long period, we decided to use the ECMWF analysis, i.e. we ran the model in hindcast mode. The winds simulated in this analysis were Correspondence to: V. Djurdjevic (vdj@ff.bg.ac.yu) weaker than the satellite estimates, with a mean BIAS of −0.8 m/s.
A method for estimating profiles of turbulent transfer coefficients inside a vegetation canopy and their use in calculating the air temperature inside tall grass canopies in land surface schemes for environmental modeling is presented. The proposed method, based on K theory, is assessed using data measured in a maize canopy. The air temperature inside the canopy is determined diagnostically by a method based on detailed consideration of 1) calculations of turbulent fluxes, 2) the shape of the wind and turbulent transfer coefficient profiles, and 3) calculation of the aerodynamic resistances inside tall grass canopies. An expression for calculating the turbulent transfer coefficient inside sparse tall grass canopies is also suggested, including modification of the corresponding equation for the wind profile inside the canopy. The proposed calculations of K-theory parameters are tested using the Land–Air Parameterization Scheme (LAPS). Model outputs of air temperature inside the canopy for 8–17 July 2002 are compared with micrometeorological measurements inside a sunflower field at the Rimski Sancevi experimental site (Serbia). To demonstrate how changes in the specification of canopy density affect the simulation of air temperature inside tall grass canopies and, thus, alter the growth of PBL height, numerical experiments are performed with LAPS coupled with a one-dimensional PBL model over a sunflower field. To examine how the turbulent transfer coefficient inside tall grass canopies over a large domain represents the influence of the underlying surface on the air layer above, sensitivity tests are performed using a coupled system consisting of the NCEP Nonhydrostatic Mesoscale Model and LAPS.
The 'force-restore' approach is commonly used in order to calculate the surface temperature in atmospheric models. A critical point in this method is how to calculate the deep soil temperature which appears in the restore term of the 'force-restore' equation. If the prognostic equation for calculating the deep soil temperature is used, some errors in surface temperature calculation and consequently in partitioning the surface energy and land surface water can be introduced. Usually, these errors should appear as a result of incorrect parameterization of surface energy terms in the prognostic equation based on 'force-restore' approach.In this paper, the sensitivity of the 'force-restore' model for surface temperature to the: (a) changes of soil heat flux; (b) variations of deep soil temperature and (c) changes in soil water evaporation is examined. In addition, the impact of the deep soil temperature variations on partitioning the surface energy and land surface water is discussed. Finally, a new procedure for calculating the deep soil temperature based, on climatological data of soil temperature and its exponential attenuation in the deep soil layers is suggested. All numerical experiments with the LAPS land surface scheme were performed using two data sets, obtained from the micrometeorological measurements over a bare soil at Rimski S& ančevi (Yugoslavia), RS, and Caumont (France), HAPEX.
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