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Alan K. Betts, Pedro Viterbo, and Anton C. M. Beljaars

Abstract

Data from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment for the summer season of 1987 are used to assess the land-surface interaction of the ECMWF reanalysis. In comparison with an earlier study, using the 1992 ECMWF operational model, the land-surface interaction is greatly improved. The bias in the incoming solar radiation has been removed, although there seems to be a small low bias in the incoming longwave, which is significant at night. The four-layer soil moisture model depicts the seasonal cycle well, and the root zone is recharged satisfactorily after major rain events. Consequently, the evaporative fraction (EF) over the season is now generally quite good. There is, however, a low bias in EF in June and high bias in October, which is probably due to the absence of a seasonal cycle in the model vegetation. The evaporative fraction also appears too high in the model just after rainfall. It also appears that the model lacks a realistic seasonal control on the soil heat flux. The surface diurnal thermodynamic cycle has two noticeable errors. The temperature minimum at sunrise is too low, because the surface uncouples too much at night under the stable boundary layer, and the incoming longwave radiation is biased low. There is also an unrealistic diurnal cycle of mixing ratio, q, with too strong a midmorning peak, and too large a fall during the day to a late afternoon minimum that is biased low. These errors in the diurnal cycle of q may feed back on the diurnal cycle of precipitation. The morning peak is partly related to the too-strong inversion at sunrise, which slows the deepening of the boundary layer. The late afternoon minimum of mixing ratio (below that of the model analysis) leads to a positive nudging of soil moisture in the analysis cycle. The model summer mixing ratio has a small high bias of 0.5 g kg−1.

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Peter A. E. M. Janssen, Anton C. M. Beljaars, Adrian Simmons, and Pedro Viterbo

Abstract

By forcing a third-generation wave-prediction model with surface stresses from the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric model, it was discovered that lower wave heights were generated than by forcing with the ECMWF surface winds. The apparent inconsistency between surface stresses and surface winds in the atmospheric model turns out to be time-step dependent. A similar conclusion may be inferred from results of the WAMDI group.

Apparently, a number of atmospheric models have inaccuracies in the boundary-layer scheme near the surface. In this paper it is argued that the reason for the inaccuracies is related to the numerical integration scheme that is used in these models. It is shown that a numerical scheme that treats physics and dynamics separately has an equilibrium that is time-step dependent. An alternative scheme—namely, simultaneous, implicit treatment of both physics and dynamics—removes this deficiency. Possible consequences for atmospheric-, wave-, and ocean-circulation models are briefly discussed.

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Anton C. M. Beljaars, Pedro Viterbo, Martin J. Miller, and Alan K. Betts

Abstract

This paper discusses the sensitivity of short- and medium-range precipitation forecasts for the central United States to land surface parametrization and soil moisture anomalies. Two forecast systems with different land surface and boundary layer schemes were running in parallel during the extreme rainfall events of July 1993. One forecast system produces much better precipitation forecasts due to a more realistic thermodynamic structure resulting from improved evaporation in an area that is about 1 day upstream from the area of heaviest rain. The paper also discusses two ensembles of 30-day integrations for July 1993. In the first ensemble, soil moisture is initialized at field capacity (100% availability); in the second ensemble it is at 25% of soil moisture availability. It is shown that the moist integrations produce a much more realistic precipitation pattern than the dry integrations. These results suggest that there may be some predictive skill in the monthly range related to the time-scale of the soil moisture reservoir. The mechanism responsible for the precipitation differences is concluded to be the result of differences in surface heating in the area 1 day upstream, impacting the atmospheric thermo-dynamic structure. Increased evaporation and reduced heating in moist soil conditions upstream result in the absence of significant boundary layer capping inversion and hence little inhibition of deep precipitating convection.

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Hervé Douville, Pedro Viterbo, Jean-François Mahfouf, and Anton C. M. Beljaars

Abstract

Initialization of land surface prognostic variables is a crucial issue for short- and medium-range forecasting as well as at seasonal timescales. In this study, two sequential soil moisture analysis schemes are tested, both based on the comparison between observed and predicted 2-m parameters: the nudging technique used operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the optimum interpolation technique proposed by J. F. Mahfouf and used operationally at Météo-France. Both techniques compute the soil moisture increments as a linear function of analysis increments of 2-m parameters (specific humidity at ECMWF, temperature and relative humidity at Météo-France). Following the preliminary study by Y. Hu et al., the optimum interpolation technique has been adapted to the four soil-level ECMWF land surface scheme. Both methods are tested in the ECMWF single column model, which has been run for 4 months in 1987 at a grid point close to the location of the First International Satellite Land-Surface Climatology Project Field Experiment. The upper-air variables are updated every 6 h using the ECMWF reanalysis. The surface downward radiation and precipitation fluxes are prescribed at each time step according to in situ observations. The soil moisture analysis is performed every 6 h, using either the nudging or the optimum interpolation. The nudging is shown to be very sensitive to model biases and sometimes produces unrealistic results. The optimum interpolation technique is more robust and reliable, due to the use of two screen-level parameters and a careful selection of the meteorological situations for which the atmosphere is expected to be informative about soil moisture. It leads to improved evaporation and soil moisture and is able to compensate for biases in both the land surface scheme and the precipitation forcing.

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