Erland Källén

Vertical structure of recent Arctic warming

Near-surface warming in the Arctic has been almost twice as large as the global average over recent decades—a phenomenon that is known as the ‘Arctic amplification’. The underlying causes of this temperature amplification remain uncertain. The reduction in snow and ice cover that has occurred over recent decades may have played a role. Climate model experiments indicate that when global temperature rises, Arctic snow and ice cover retreats, causing excessive polar warming. Reduction of the snow and ice cover causes albedo changes, and increased refreezing of sea ice during the cold season and decreases in sea-ice thickness both increase heat flux from the ocean to the atmosphere. Changes in oceanic and atmospheric circulation, as well as cloud cover, have also been proposed to cause Arctic temperature amplification. Here we examine the vertical structure of temperature change in the Arctic during the late twentieth century using reanalysis data. We find evidence for temperature amplification well above the surface. Snow and ice feedbacks cannot be the main cause of the warming aloft during the greater part of the year, because these feedbacks are expected to primarily affect temperatures in the lowermost part of the atmosphere, resulting in a pattern of warming that we only observe in spring. A significant proportion of the observed temperature amplification must therefore be explained by mechanisms that induce warming above the lowermost part of the atmosphere. We regress the Arctic temperature field on the atmospheric energy transport into the Arctic and find that, in the summer half-year, a significant proportion of the vertical structure of warming can be explained by changes in this variable. We conclude that changes in atmospheric heat transport may be an important cause of the recent Arctic temperature amplification.

Characteristics of Occasional Poor Medium-Range Weather Forecasts for Europe

Medium-range weather prediction has become more skillful over recent decades, but forecast centers still suffer from occasional very poor forecasts, which are often referred to as “dropouts” or “busts.” This study focuses on European Centre for Medium-Range Weather Forecasts (ECMWF) day-6 forecasts for Europe. Although busts are defined by gross scores, bust composites reveal a coherent “Rex type” blocking situation, with a high over northern Europe and a low over the Mediterranean. Initial conditions for these busts also reveal a coherent flow, but this is located over North America and involves a trough over the Rockies, with high convective available potential energy (CAPE) to its east. This flow type occurs in spring and is often associated with a Rossby wave train that has crossed the Pacific. A composite on this initial flow type displays enhanced day-6 random forecast errors and some-what enhanced ensemble forecast spread, indicating reduced inherent predictability. Mesoscale convective systems, as...

Factors Influencing Skill Improvements in the ECMWF Forecasting System

AbstractDuring 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 20...

Comparison between Singular Vectors and Breeding Vectors as Initial Perturbations for the ECMWF Ensemble Prediction System

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) ...

Sensitivity of forecast errors to initial and lateral boundary conditions

The adjoint of a limited area model has been used to study the sensitivity of 12 h forecast errors to initial and lateral boundary conditions. Upper troposphere potential vorticity and mean sea level pressure verification scores for 1 month of operational forecasts from the Swedish Meteorological and Hydrological Institute were used to select 2 cases with particularly poor forecast performance. The sensitivity experiments show that errors in initial data is the most likely explanation for one of the forecast failures, while errors in initial as well as lateral boundary data can explain the 2nd forecast failure. Results from the sensitivity experiments with respect to the lateral boundary conditions indicate that poor quality lateral boundary conditions may be improved by utilizing subsequent downstream observations within the model integration area. This result is of great significance with regard to the possibilities for applying 4-dimensional variational data assimilation (4DVAR) for limited area forecast models. Results from the sensitivity experiments also reveal, however, that the lateral boundary treatment in operational limited area models needs to be improved with regard to the mathematical formulation. It is furthermore shown that modifications to be applied to the lateral boundary conditions need to be determined with appropriate time resolution and that some filtering of these lateral boundary modifications has to be introduced to avoid enhanced high-frequency gravity wave noise in the vicinity of the lateral boundaries.

Independent Estimations of the Asymptotic Variability in an Ensemble Forecast System

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.

Dynamical response of equatorial waves in four-dimensional variational data assimilation

In this study we question the relative importance of direct wind measurements in the tropics by investigating limits of four-dimensional variational assimilation (4D-Var) in the tropics when only wind or mass field observations are available. Typically observed equatorial wave motion fields (Kelvin, mixed Rossby-gravity and n = 1 equatorial Rossby waves) are assimilated in a non-linear shallow water model. Perfect observations on the full model grid are utilized and no background error term is used. The results illustrate limits of 4D-Var with only one type of information, in particular mass field information. First, there is a limit of information available through the internal model dynamics. This limit is defined by the length of the assimilation window, in relation to the characteristics of the motion being assimilated. Secondly, there is a limit related to the type of observations used. In all cases of assimilation of wind field data, two or three time instants with observations are sufficient to recover the mass field, independent of the length of the assimilation time window. Assimilation of mass field data, on the other hand, although capable of wind field reconstruction, is much more dependent on the dynamical properties of the assimilated motion system. Assimilating height information is less efficient, and the divergent part of the wind field is always recovered first and more completely than its rotational part.

Flow-dependent versus flow-independent initial perturbations for ensemble prediction

Abstract Ensemble prediction relies on a faithful representation of initial uncertainties in a forecasting system. Early research on initial perturbation methods tested random perturbations by adding ‘white noise’ to the analysis. Here, an alternative kind of random perturbations is introduced by using the difference between two randomly chosen atmospheric states (i.e. analyses). It yields perturbations (random field, RF, perturbations) in approximate flow balance. The RF method is compared with the operational singular vector based ensemble at European Centre for Medium Range Weather Forecasts (ECMWF) and the ensemble transform (ET) method. All three methods have been implemented on theECMWFIFS-modelwith resolution TL255L40. The properties of the different perturbation methods have been investigated both by comparing the dynamical properties and the quality of the ensembles in terms of different skill scores. The results show that the RF perturbations initially have the same dynamical properties as the natural variability of the atmosphere. After a day of integration, the perturbations from all three methods converge. The skill scores indicate a statistically significant advantage for the RF method for the first 2–3 d for the most of the evaluated parameters. For the medium range (3–8 d), the differences are very small.

Large-Scale Dynamical Response to Subgrid-Scale Organization Provided by Cellular Automata

Due to the limited resolution of numerical weather prediction (NWP) models, sub-grid scale physical processes are parameterized, and represented by grid-box means. However, some physical processes ...

Multiple Weather Regimes and Baroclinically Forced Spherical Resonance

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 establis...