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- Author or Editor: Erland Källén x
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Abstract
In a low-order, two-layer model with orographic and zonal thermal and momentum forcing, two different types of orographically induced instabilities exist. One is of a barotropic nature with a westerly flow in the bottom layer, while the other one is close to a baroclinic instability of the basic long wave and has a very weak westerly or easterly bottom layer flow.
Abstract
In a low-order, two-layer model with orographic and zonal thermal and momentum forcing, two different types of orographically induced instabilities exist. One is of a barotropic nature with a westerly flow in the bottom layer, while the other one is close to a baroclinic instability of the basic long wave and has a very weak westerly or easterly bottom layer flow.
Abstract
During the past 30 years the skill in ECMWF numerical forecasts has steadily improved. There are three major contributing factors: 1) improvements in the forecast model, 2) improvements in the data assimilation, and 3) the increased number of available observations. In this study the authors are investigating the relative contribution from these three components by using the simple error growth model introduced in a previous study by Lorenz and extended in another study by Dalcher and Kalnay, together with the results from the ECMWF Re-Analysis Interim (ERA-Interim) forecasts where the improvement is only due to an increased number of observations. The authors are also applying the growth model on “lagged” forecast differences in order to investigate the usefulness of the forecast jumpiness as a diagnostic tool for improvements in the forecasts. The main finding is that the main contribution to the reduced forecast error comes from significant initial condition error reductions between 1996 and 2001 together with continuous model improvements. The changes in the available observations contributed to a lesser degree, but the authors note that all the ERA-Interim forecasts are from the satellite era and here the focus is on the midtroposphere in the extratropics. Regarding the jumpiness in the forecasts, this is mainly a function of the error in the initial conditions and is therefore an insufficient tool to investigate improvements in the full forecasting system.
Abstract
During the past 30 years the skill in ECMWF numerical forecasts has steadily improved. There are three major contributing factors: 1) improvements in the forecast model, 2) improvements in the data assimilation, and 3) the increased number of available observations. In this study the authors are investigating the relative contribution from these three components by using the simple error growth model introduced in a previous study by Lorenz and extended in another study by Dalcher and Kalnay, together with the results from the ECMWF Re-Analysis Interim (ERA-Interim) forecasts where the improvement is only due to an increased number of observations. The authors are also applying the growth model on “lagged” forecast differences in order to investigate the usefulness of the forecast jumpiness as a diagnostic tool for improvements in the forecasts. The main finding is that the main contribution to the reduced forecast error comes from significant initial condition error reductions between 1996 and 2001 together with continuous model improvements. The changes in the available observations contributed to a lesser degree, but the authors note that all the ERA-Interim forecasts are from the satellite era and here the focus is on the midtroposphere in the extratropics. Regarding the jumpiness in the forecasts, this is mainly a function of the error in the initial conditions and is therefore an insufficient tool to investigate improvements in the full forecasting system.
Abstract
The response of the atmospheric circulation to an enhanced radiative greenhouse gas forcing is investigated. It has been proposed that the response of the climate system to an enhanced forcing projects directly onto the preexisting natural modes of variability. An evaluation of this possibility and in particular of the implications of unchanged flow regimes is performed with a focus on the Southern Hemisphere extratropical atmospheric circulation. Low-pass-filtered mean sea level pressure and geopotential height at 500 and 200 hPa from a transient integration with a coupled global climate model is used.
The response to an enhanced forcing projects strongly onto the leading modes of present-day variability, in agreement with other studies. However, the spatial patterns of the leading modes are changed in response to enhanced forcing. The first and second modes of interweekly variability are the Pacific–South American modes, zonal wavenumber-3 wave trains from the central Pacific to the southern Atlantic. In response to the enhanced forcing, the spatial patterns of these modes change, and the wave train extends along a circumpolar path with amplitude also in the Eastern Hemisphere. This change in the spatial patterns is associated with a strengthening of the waveguide for barotropic Rossby waves.
Abstract
The response of the atmospheric circulation to an enhanced radiative greenhouse gas forcing is investigated. It has been proposed that the response of the climate system to an enhanced forcing projects directly onto the preexisting natural modes of variability. An evaluation of this possibility and in particular of the implications of unchanged flow regimes is performed with a focus on the Southern Hemisphere extratropical atmospheric circulation. Low-pass-filtered mean sea level pressure and geopotential height at 500 and 200 hPa from a transient integration with a coupled global climate model is used.
The response to an enhanced forcing projects strongly onto the leading modes of present-day variability, in agreement with other studies. However, the spatial patterns of the leading modes are changed in response to enhanced forcing. The first and second modes of interweekly variability are the Pacific–South American modes, zonal wavenumber-3 wave trains from the central Pacific to the southern Atlantic. In response to the enhanced forcing, the spatial patterns of these modes change, and the wave train extends along a circumpolar path with amplitude also in the Eastern Hemisphere. This change in the spatial patterns is associated with a strengthening of the waveguide for barotropic Rossby waves.
Abstract
No abstract available.
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No abstract available.
Abstract
In this paper a study aimed at comparing the perturbation methodologies based on the singular vector ensemble prediction system (SV-EPS) and the breeding vector ensemble prediction system (BV-EPS) in the same model environment is presented. A simple breeding system (simple BV-EPS) as well as one with regional rescaling dependent on an estimate of the analysis error variance (masked BV-EPS) were used. The ECMWF Integrated Forecast System has been used and the three experiments are compared for 46 forecast cases between 1 December 2005 and 15 January 2006. By studying the distribution of the perturbation energy it was possible to see large differences between the experiments initially, but after 48 h the distributions have converged. Using probabilistic scores, these results show that SV-EPS has a somewhat better performance for the Northern Hemisphere compared to BV-EPS. For the Southern Hemisphere masked BV-EPS and SV-EPS yield almost equal results. For the tropics the masked breeding ensemble shows the best performance during the first 6 days. One reason for this is the current setup of the singular vector ensemble at ECMWF yielding in general very low initial perturbation amplitudes in the tropics.
Abstract
In this paper a study aimed at comparing the perturbation methodologies based on the singular vector ensemble prediction system (SV-EPS) and the breeding vector ensemble prediction system (BV-EPS) in the same model environment is presented. A simple breeding system (simple BV-EPS) as well as one with regional rescaling dependent on an estimate of the analysis error variance (masked BV-EPS) were used. The ECMWF Integrated Forecast System has been used and the three experiments are compared for 46 forecast cases between 1 December 2005 and 15 January 2006. By studying the distribution of the perturbation energy it was possible to see large differences between the experiments initially, but after 48 h the distributions have converged. Using probabilistic scores, these results show that SV-EPS has a somewhat better performance for the Northern Hemisphere compared to BV-EPS. For the Southern Hemisphere masked BV-EPS and SV-EPS yield almost equal results. For the tropics the masked breeding ensemble shows the best performance during the first 6 days. One reason for this is the current setup of the singular vector ensemble at ECMWF yielding in general very low initial perturbation amplitudes in the tropics.
Abstract
Systematically recurrent, geographically fixed weather regimes forced by a single isolated mountain in a two-layer, high-resolution, quasigeostrophic model modified for the sphere are found to be robust phenomena. While the climatological stationary wave is often confined to (or has maximum amplitude in) the region just downstream of the orography, giving the appearance of a wave train propagating into the Tropics, the regional maximum centers of low-frequency variance appear around the hemisphere, giving the appearance of zonal resonance or some type of zonally confined propagation. This result is not anticipated in light of Rossby wave dispersion theory on the sphere. On the other hand, baroclinic disturbances developing on a meridional temperature gradient of finite extent force subtropical and polar easterlies as well as a sharpened midlatitude westerly jet, which provides a zonal waveguide (by refraction and/or reflection) for the Rossby waves. These conditions are favorable for the establishment of multiple weather regimes. The baroclinicity of the atmosphere is then continuously forcing a mean state that favors forced zonal propagation, counteracting the meridional dispersion generated by the spherical geometry alone. These ideas suggest that the multiple-equilibria theories may be more applicable to the atmosphere than originally suggested by linear dispersion theory on the sphere. It may also help explain why channel models work as well as they do even for the largest scales.
Abstract
Systematically recurrent, geographically fixed weather regimes forced by a single isolated mountain in a two-layer, high-resolution, quasigeostrophic model modified for the sphere are found to be robust phenomena. While the climatological stationary wave is often confined to (or has maximum amplitude in) the region just downstream of the orography, giving the appearance of a wave train propagating into the Tropics, the regional maximum centers of low-frequency variance appear around the hemisphere, giving the appearance of zonal resonance or some type of zonally confined propagation. This result is not anticipated in light of Rossby wave dispersion theory on the sphere. On the other hand, baroclinic disturbances developing on a meridional temperature gradient of finite extent force subtropical and polar easterlies as well as a sharpened midlatitude westerly jet, which provides a zonal waveguide (by refraction and/or reflection) for the Rossby waves. These conditions are favorable for the establishment of multiple weather regimes. The baroclinicity of the atmosphere is then continuously forcing a mean state that favors forced zonal propagation, counteracting the meridional dispersion generated by the spherical geometry alone. These ideas suggest that the multiple-equilibria theories may be more applicable to the atmosphere than originally suggested by linear dispersion theory on the sphere. It may also help explain why channel models work as well as they do even for the largest scales.
Abstract
One desirable property within an ensemble forecast system is to have a one-to-one ratio between the root-mean-square error (rmse) of the ensemble mean and the standard deviation of the ensemble (spread). The ensemble spread and forecast error within the ECMWF ensemble prediction system has been extrapolated beyond 10 forecast days using a simple model for error growth. The behavior of the ensemble spread and the rmse at the time of the deterministic predictability are compared with derived relations of rmse at the infinite forecast length and the characteristic variability of the atmosphere in the limit of deterministic predictability. Utilizing this methodology suggests that the forecast model and the atmosphere do not have the same variability, which raises the question of how to obtain a perfect ensemble.
Abstract
One desirable property within an ensemble forecast system is to have a one-to-one ratio between the root-mean-square error (rmse) of the ensemble mean and the standard deviation of the ensemble (spread). The ensemble spread and forecast error within the ECMWF ensemble prediction system has been extrapolated beyond 10 forecast days using a simple model for error growth. The behavior of the ensemble spread and the rmse at the time of the deterministic predictability are compared with derived relations of rmse at the infinite forecast length and the characteristic variability of the atmosphere in the limit of deterministic predictability. Utilizing this methodology suggests that the forecast model and the atmosphere do not have the same variability, which raises the question of how to obtain a perfect ensemble.
Abstract
The objective of this study is to examine the performance of the adiabatic digital filtering initialization scheme of Lynch and Huang, the diabatic digital filtering initialization scheme of Huang and Lynch, and the diabatic nonlinear normal-mode initialization scheme of Cederskov in a complete data assimilation system. In particular, the authors wish to examine the handling of observations and the changes that the initialization makes to the analysis in an intermittent data assimilation cycle. As a reference the authors use the adiabatic nonlinear normal-mode initialization of Machenhauer, formulated according to Bijlsma and Hafkenscheid, which is the current operational initialization scheme at the, Danish Meteorological Institute.
The initialization schemes tested are found to produce a well-balanced model state that is at least as good as that produced by the reference scheme. Furthermore, the changes to the analysis made by the different initialization schemes are similar and the observations are therefore treated similarly with the different schemes. It is thus found that the introduction of a new initialization procedure has no detrimental effect on the data assimilation cycle. On the contrary, the two diabatic schemes reduce the noise level considerably compared to the adiabatic ones albeit at an increased computational cost. Considering the advantages of a diabatic scheme, in particular the future possibility of including cloud properties in the initialization procedure (Huang and Sundqvist), the use of a diabatic scheme seems well justified. The noise reduction is perhaps not the most important aspect as all schemes behave identically in the handling of observations. Instead, the possibility of including satellite-derived cloudiness and precipitation data in the analysis and initialization cycle is a much move important aspect. From this point of view the digital filter has a clear advantage over the normal-mode initialization scheme as all dependent variables of the model are initialized.
Abstract
The objective of this study is to examine the performance of the adiabatic digital filtering initialization scheme of Lynch and Huang, the diabatic digital filtering initialization scheme of Huang and Lynch, and the diabatic nonlinear normal-mode initialization scheme of Cederskov in a complete data assimilation system. In particular, the authors wish to examine the handling of observations and the changes that the initialization makes to the analysis in an intermittent data assimilation cycle. As a reference the authors use the adiabatic nonlinear normal-mode initialization of Machenhauer, formulated according to Bijlsma and Hafkenscheid, which is the current operational initialization scheme at the, Danish Meteorological Institute.
The initialization schemes tested are found to produce a well-balanced model state that is at least as good as that produced by the reference scheme. Furthermore, the changes to the analysis made by the different initialization schemes are similar and the observations are therefore treated similarly with the different schemes. It is thus found that the introduction of a new initialization procedure has no detrimental effect on the data assimilation cycle. On the contrary, the two diabatic schemes reduce the noise level considerably compared to the adiabatic ones albeit at an increased computational cost. Considering the advantages of a diabatic scheme, in particular the future possibility of including cloud properties in the initialization procedure (Huang and Sundqvist), the use of a diabatic scheme seems well justified. The noise reduction is perhaps not the most important aspect as all schemes behave identically in the handling of observations. Instead, the possibility of including satellite-derived cloudiness and precipitation data in the analysis and initialization cycle is a much move important aspect. From this point of view the digital filter has a clear advantage over the normal-mode initialization scheme as all dependent variables of the model are initialized.
Abstract
Because of the limited resolution of numerical weather prediction (NWP) models, subgrid-scale physical processes are parameterized and represented by gridbox means. However, some physical processes are better represented by a mean and its variance; a typical example is deep convection, with scales varying from individual updrafts to organized mesoscale systems. This study investigates, in an idealized setting, whether a cellular automaton (CA) can be used to enhance subgrid-scale organization by forming clusters representative of the convective scales and thus yield a stochastic representation of subgrid-scale variability. The authors study the transfer of energy from the convective to the larger atmospheric scales through nonlinear wave interactions. This is done using a shallow water (SW) model initialized with equatorial wave modes. By letting a CA act on a finer resolution than that of the SW model, it can be expected to mimic the effect of, for instance, gravity wave propagation on convective organization. Employing the CA scheme permits the reproduction of the observed behavior of slowing down equatorial Kelvin modes in convectively active regions, while random perturbations fail to feed back on the large-scale flow. The analysis of kinetic energy spectra demonstrates that the CA subgrid scheme introduces energy backscatter from the smallest model scales to medium scales. However, the amount of energy backscattered depends almost solely on the memory time scale introduced to the subgrid scheme, whereas any variation in spatial scales generated does not influence the energy spectra markedly.
Abstract
Because of the limited resolution of numerical weather prediction (NWP) models, subgrid-scale physical processes are parameterized and represented by gridbox means. However, some physical processes are better represented by a mean and its variance; a typical example is deep convection, with scales varying from individual updrafts to organized mesoscale systems. This study investigates, in an idealized setting, whether a cellular automaton (CA) can be used to enhance subgrid-scale organization by forming clusters representative of the convective scales and thus yield a stochastic representation of subgrid-scale variability. The authors study the transfer of energy from the convective to the larger atmospheric scales through nonlinear wave interactions. This is done using a shallow water (SW) model initialized with equatorial wave modes. By letting a CA act on a finer resolution than that of the SW model, it can be expected to mimic the effect of, for instance, gravity wave propagation on convective organization. Employing the CA scheme permits the reproduction of the observed behavior of slowing down equatorial Kelvin modes in convectively active regions, while random perturbations fail to feed back on the large-scale flow. The analysis of kinetic energy spectra demonstrates that the CA subgrid scheme introduces energy backscatter from the smallest model scales to medium scales. However, the amount of energy backscattered depends almost solely on the memory time scale introduced to the subgrid scheme, whereas any variation in spatial scales generated does not influence the energy spectra markedly.
