880 resultados para convective parameterization scheme
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The present workshop constitutes the 5th in the annual series on “Concepts for Convective Parameterizations in Large-Scale Models”. The purpose of the workshop series has been to discuss the fundamental theoretical issues of convection parameterization with a small number of European scientists. The workshop series has been funded by European Cooperation in the Field of Scientific and Technical Research (COST) Action ES0905. The theme of the workshop for the year 2012 was decided from a main conclusion of the previous workshop, which focused on the convective organization problem, seeking a means for implementing such effects into convection parameterizations (Yano et al. 2012). As it turned out, in order to discuss this implementation issue in any concrete manner, we have first to know very well the bells and whistles of convection parameterizations. This was the purpose of the 5th workshop. The title of the workshop is rather metaphorically tagged as “Bulk or Spectrum?”, because this is a typical decision we have to face at the outset of any parameterization development. The following report discusses selected issues of bells and whistles addressed during the meeting.
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The present paper presents a simple theory for the transformation of non-precipitating, shallow convection into precipitating, deep convective clouds. In order to make the pertinent point a much idealized system is considered, consisting only of shallow and deep convection without large–scale forcing. The transformation is described by an explicit coupling between these two types of convection. Shallow convection moistens and cools the atmosphere, whereas deep convection dries and warms, leading to destabilization and stabilization respectively. Consequently, in their own stand–alone modes, shallow convection perpetually grows, whereas deep convection simply damps: the former never reaches equilibrium, and the latter is never spontaneously generated. Coupling the modes together is the only way to reconcile these undesirable separate tendencies so that the convective system as a whole can remain in a stable periodic state under this idealized setting. Such coupling is a key missing element in current global atmospheric models. The energy–cycle description as originally formulated by Arakawa and Schubert, and presented herein is suitable for direct implementation into models using a mass–flux parameterization, and would alleviate the current problems with the representation of these two types of convection in numerical models. The present theory also provides a pertinent framework for analyzing large–eddy simulations and cloud–resolving modelling.
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In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.
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We perform simulations of several convective events over the southern UK with the Met Office Unified Model (UM) at horizontal grid lengths ranging from 1.5 km to 200 m. Comparing the simulated storms on these days with the Met Office rainfall radar network allows us to apply a statistical approach to evaluate the properties and evolution of the simulated storms over a range of conditions. Here we present results comparing the storm morphology in the model and reality which show that the simulated storms become smaller as grid length decreases and that the grid length that fits the observations best changes with the size of the observed cells. We investigate the sensitivity of storm morphology in the model to the mixing length used in the subgrid turbulence scheme. As the subgrid mixing length is decreased, the number of small storms with high area-averaged rain rates increases. We show that by changing the mixing length we can produce a lower resolution simulation that produces similar morphologies to a higher resolution simulation.
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The Surface Urban Energy and Water Balance Scheme (SUEWS) is developed to include snow. The processes addressed include accumulation of snow on the different urban surface types: snow albedo and density aging, snow melting and re-freezing of meltwater. Individual model parameters are assessed and independently evaluated using long-term observations in the two cold climate cities of Helsinki and Montreal. Eddy covariance sensible and latent heat fluxes and snow depth observations are available for two sites in Montreal and one in Helsinki. Surface runoff from two catchments (24 and 45 ha) in Helsinki and snow properties (albedo and density) from two sites in Montreal are also analysed. As multiple observation sites with different land-cover characteristics are available in both cities, model development is conducted independent of evaluation. The developed model simulates snowmelt related runoff well (within 19% and 3% for the two catchments in Helsinki when there is snow on the ground), with the springtime peak estimated correctly. However, the observed runoff peaks tend to be smoother than the simulated ones, likely due to the water holding capacity of the catchments and the missing time lag between the catchment and the observation point in the model. For all three sites the model simulates the timing of the snow accumulation and melt events well, but underestimates the total snow depth by 18–20% in Helsinki and 29–33% in Montreal. The model is able to reproduce the diurnal pattern of net radiation and turbulent fluxes of sensible and latent heat during cold snow, melting snow and snow-free periods. The largest model uncertainties are related to the timing of the melting period and the parameterization of the snowmelt. The results show that the enhanced model can simulate correctly the exchange of energy and water in cold climate cities at sites with varying surface cover.
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A new coupled cloud physics–radiation parameterization of the bulk optical properties of ice clouds is presented. The parameterization is consistent with assumptions in the cloud physics scheme regarding particle size distributions (PSDs) and mass–dimensional relationships. The parameterization is based on a weighted ice crystal habit mixture model, and its bulk optical properties are parameterized as simple functions of wavelength and ice water content (IWC). This approach directly couples IWC to the bulk optical properties, negating the need for diagnosed variables, such as the ice crystal effective dimension. The parameterization is implemented into the Met Office Unified Model Global Atmosphere 5.0 (GA5) configuration. The GA5 configuration is used to simulate the annual 20-yr shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA), as well as the temperature structure of the atmosphere, under various microphysical assumptions. The coupled parameterization is directly compared against the current operational radiation parameterization, while maintaining the same cloud physics assumptions. In this experiment, the impacts of the two parameterizations on the SW and LW radiative effects at TOA are also investigated and compared against observations. The 20-yr simulations are compared against the latest observations of the atmospheric temperature and radiative fluxes at TOA. The comparisons demonstrate that the choice of PSD and the assumed ice crystal shape distribution are as important as each other. Moreover, the consistent radiation parameterization removes a long-standing tropical troposphere cold temperature bias but slightly warms the southern midlatitudes by about 0.5 K.
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This study presents an evaluation of the size and strength of convective updraughts in high-resolution simulations by the UK Met Office Unified Model (UM). Updraught velocities have been estimated from range–height indicator (RHI) Doppler velocity measurements using the Chilbolton advanced meteorological radar, as part of the Dynamical and Microphysical Evolution of Convective Storms (DYMECS) project. Based on mass continuity and the vertical integration of the observed radial convergence, vertical velocities tend to be underestimated for convective clouds due to the undetected cross-radial convergence. Velocity fields from the UM at a resolution corresponding to the radar observations are used to scale such estimates to mitigate the inherent biases. The analysis of more than 100 observed and simulated storms indicates that the horizontal scale of updraughts in simulations tend to decrease with grid length; the 200 m grid length agreed most closely with the observations. Typical updraught mass fluxes in the 500 m grid length simulations were up to an order of magnitude greater than observed, and greater still in the 1.5 km grid length simulations. The effect of increasing the mixing length in the sub-grid turbulence scheme depends on the grid length. For the 1.5 km simulations, updraughts were weakened though their horizontal scale remained largely unchanged. Progressively more so for the sub-kilometre grid lengths, updraughts were broadened and intensified; horizontal scale was now determined by the mixing length rather than the grid length. In general, simulated updraughts were found to weaken too quickly with height. The findings were supported by the analysis of the widths of reflectivity patterns in both the simulations and observations.
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A generalization of Arakawa and Schubert's convective quasi-equilibrium principle is presented for a closure formulation of mass-flux convection parameterization. The original principle is based on the budget of the cloud work function. This principle is generalized by considering the budget for a vertical integral of an arbitrary convection-related quantity. The closure formulation includes Arakawa and Schubert's quasi-equilibrium, as well as both CAPE and moisture closures as special cases. The formulation also includes new possibilities for considering vertical integrals that are dependent on convective-scale variables, such as the moisture within convection. The generalized convective quasi-equilibrium is defined by a balance between large-scale forcing and convective response for a given vertically-integrated quantity. The latter takes the form of a convolution of a kernel matrix and a mass-flux spectrum, as in the original convective quasi-equilibrium. The kernel reduces to a scalar when either a bulk formulation is adopted, or only large-scale variables are considered within the vertical integral. Various physical implications of the generalized closure are discussed. These include the possibility that precipitation might be considered as a potentially-significant contribution to the large-scale forcing. Two dicta are proposed as guiding physical principles for the specifying a suitable vertically-integrated quantity.
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A single habit parameterization for the shortwave optical properties of cirrus is presented. The parameterization utilizes a hollow particle geometry, with stepped internal cavities as identified in laboratory and field studies. This particular habit was chosen as both experimental and theoretical results show that the particle exhibits lower asymmetry parameters when compared to solid crystals of the same aspect ratio. The aspect ratio of the particle was varied as a function of maximum dimension, D, in order to adhere to the same physical relationships assumed in the microphysical scheme in a configuration of the Met Office atmosphere-only global model, concerning particle mass, size and effective density. Single scattering properties were then computed using T-Matrix, Ray Tracing with Diffraction on Facets (RTDF) and Ray Tracing (RT) for small, medium, and large size parameters respectively. The scattering properties were integrated over 28 particle size distributions as used in the microphysical scheme. The fits were then parameterized as simple functions of Ice Water Content (IWC) for 6 shortwave bands. The parameterization was implemented into the GA6 configuration of the Met Office Unified Model along with the current operational long-wave parameterization. The GA6 configuration is used to simulate the annual twenty-year short-wave (SW) fluxes at top-of-atmosphere (TOA) and also the temperature and humidity structure of the atmosphere. The parameterization presented here is compared against the current operational model and a more recent habit mixture model.
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The South American low level jet (SALLJ) of the Eastern Andes is investigated with Regional Climate Model version 3 (RegCM3) simulations during the 2002-2003 austral summer using two convective parameterizations (Grell and Emanuel). The simulated SALLJ is compared with the special observations of SALLJEX (SALLJ Experiment). Both the Grell and Emanuel schemes adequately simulate the low level flow over South America. However, there are some intensity differences. Due to the larger (smaller) convective activity, the Emanuel (Grell) scheme simulates more intense (weaker) low level wind than analysis in the tropics and subtropics. The objectives criteria of Sugahara (SJ) and Bonner (BJ) were used for LLJ identification. When applied to the observations, both criteria suggest a larger frequency of the SALLJ in Santa Cruz, followed by Mariscal, Trinidad and Asuncin. In Mariscal and Asuncin, the diurnal cycle indicates that SJ occurs mainly at 12 UTCs (morning), while the BJ criterion presents the SALLJ as more homogenously distributed. The concentration into two of the four-times-a-day observations does not allow conclusions about the diurnal cycle in Santa Cruz and Trinidad. The simulated wind profiles result in a lower than observed frequency of SALLJ using both the SJ and BJ criteria, with fewer events obtained with the BJ. Due to the stronger simulated winds, the Emanuel scheme produces an equal or greater relative frequency of SALLJ than the Grell scheme. However, the Grell scheme using the SJ criterion simulates the SALLJ diurnal cycle closer to the observed one. Although some discrepancies between observed and simulated mean vertical profiles of the horizontal wind are noted, there is large agreement between the composites of the vertical structure of the SALLJ, especially when the SJ criterion is used with the Grell scheme. On an intraseasonal scale, a larger southward displacement of SALLJ in February and December when compared with January has been noted. The Grell and Emanuel schemes simulated this observed oscillation in the low-level flow. However, the spatial pattern and intensity of rainfall and circulation anomalies simulated by the Grell scheme are closer to the analyses than those obtained with the Emanuel scheme.
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This work describes the tropical town energy budget (t-TEB) scheme addressed to simulate the diurnal occurrence of the urban heat island (UHI) as observed in the Metropolitan Area of Rio de Janeiro (MARJ; -22A degrees S; -44A degrees W) in Brazil. Reasoning about the tropical urban climate have guided the scheme implementation, starting from the original equations from Masson (Bound-Lay Meteorol 94:357-397, 2000). The modifications include (a) local scaling approaches for obtaining flux-gradient relationships in the roughness sub-layer, (b) the Monin-Obukhov similarity framework in the inertial sub-layer, (c) increasing aerodynamic conductance toward more unstable conditions, and (d) a modified urban subsurface drainage system to transfer the intercepted rainwater by roofs to the roads. Simulations along 2007 for the MARJ are obtained and compared with the climatology. The t-TEB simulation is consistent with the observations, suggesting that the timing and dynamics of the UHI in tropical cities could vary significantly from the familiar patterns observed in mid-latitude cities-with the peak heat island intensity occurring in the morning than at night. The simulations are suggesting that the thermal phase shift of this tropical diurnal UHI is a response of the surface energy budget to the large amount of solar radiation, intense evapotranspiration, and thermal response of the vegetated surfaces over a very humid soil layer.
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This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.
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In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.