Search Results

You are looking at 1 - 10 of 10 items for :

  • Author or Editor: Erland Källén x
  • Refine by Access: All Content x
Clear All Modify Search
Linus Magnusson
and
Erland Källén

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.

Full access
Linus Magnusson
,
Martin Leutbecher
, and
Erland Källén

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.

Full access
Shuting Yang
,
Brian Reinhold
, and
Erland Källén

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.

Full access
Lisa K. Bengtsson
,
Linus Magnusson
, and
Erland Källén

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.

Full access
Xiang-Yu Huang
,
Annette Cederskov
, and
Erland Källén

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.

Full access
Lisa Bengtsson
,
Heiner Körnich
,
Erland Källén
, and
Gunilla Svensson

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.

Full access
Ad Stoffelen
,
Jean Pailleux
,
Erland Källén
,
J. Michael Vaughan
,
Lars Isaksen
,
Pierre Flamant
,
Werner Wergen
,
Erik Andersson
,
Harald Schyberg
,
Alain Culoma
,
Roland Meynart
,
Martin Endemann
, and
Paul Ingmann

The prime aim of the Atmospheric Dynamics Mission is to demonstrate measurements of vertical wind profiles from space. Extensive studies conducted by the European Space Agency over the past 15 years have culminated in the selection of a high-performance Doppler wind lidar based on direct-detection interferometric techniques. Such a system, with a pulsed laser operating at 355-nm wavelength, would utilize both Rayleigh scattering from molecules and Mie scattering from thin cloud and aerosol particles; measurement of the residual Doppler shift from successive levels in the atmosphere provides the vertical wind profiles. The lidar would be accommodated on a satellite flying in a sun-synchronous orbit, at an altitude of ~400 km, providing near-global coverage; target date for launch is in 2007. Processing of the backscatter signals will provide about 3000 globally distributed wind profiles per day, above thick clouds or down to the surface in clear air, at typically 200-km separation along the satellite track. Such improved knowledge of the global wind field is crucial to many aspects of climate research and weather prediction. Knowledge over large parts of the Tropics and major oceans is presently quite incomplete—leading to major difficulties in studying key processes in the climate system and in improving numerical simulations and predictions; progress in climate modeling is indeed intimately linked to progress in numerical weather prediction. The background studies, potential impact on climate and weather prediction, choice of measurement specifications, and the lidar technology are discussed.

Full access
Mark J Rodwell
,
Linus Magnusson
,
Peter Bauer
,
Peter Bechtold
,
Massimo Bonavita
,
Carla Cardinali
,
Michail Diamantakis
,
Paul Earnshaw
,
Antonio Garcia-Mendez
,
Lars Isaksen
,
Erland Källén
,
Daniel Klocke
,
Philippe Lopez
,
Tony McNally
,
Anders Persson
,
Fernando Prates
, and
Nils Wedi

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, associated with the high levels of CAPE, act to slow the motion of the trough. Hence, convection errors play an active role in the busts. The subgrid-scale nature of convection highlights the importance of the representation of model uncertainty in probabilistic forecasts. The cloud and extreme conditions associated with mesoscale convective systems also reduce the availability and utility of observations provided to the data assimilation.

A question of relevance to the wider community is, do we have observations with sufficient accuracy to better constrain the important error structures in the initial conditions? Meanwhile, improvements to ensemble prediction systems should help us better predict the increase in forecast uncertainty.

Full access
Ad Stoffelen
,
Angela Benedetti
,
Régis Borde
,
Alain Dabas
,
Pierre Flamant
,
Mary Forsythe
,
Mike Hardesty
,
Lars Isaksen
,
Erland Källén
,
Heiner Körnich
,
Tsengdar Lee
,
Oliver Reitebuch
,
Michael Rennie
,
Lars-Peter Riishøjgaard
,
Harald Schyberg
,
Anne Grete Straume
, and
Michael Vaughan

Abstract

The Aeolus mission objectives are to improve numerical weather prediction (NWP) and enhance the understanding and modeling of atmospheric dynamics on global and regional scale. Given the first successes of Aeolus in NWP, it is time to look forward to future vertical wind profiling capability to fulfill the rolling requirements in operational meteorology. Requirements for wind profiles and information on vertical wind shear are constantly evolving. The need for high-quality wind and profile information to capture and initialize small-amplitude, fast-evolving, and mesoscale dynamical structures increases, as the resolution of global NWP improved well into the 3D turbulence regime on horizontal scales smaller than 500 km. In addition, advanced requirements to describe the transport and dispersion of atmospheric constituents and better depict the circulation on climate scales are well recognized. Direct wind profile observations over the oceans, tropics, and Southern Hemisphere are not provided by the current global observing system. Looking to the future, most other wind observation techniques rely on cloud or regions of water vapor and are necessarily restricted in coverage. Therefore, after its full demonstration, an operational Aeolus-like follow-on mission obtaining globally distributed wind profiles in clear air by exploiting molecular scattering remains unique.

Full access
Wayman E. Baker
,
Robert Atlas
,
Carla Cardinali
,
Amy Clement
,
George D. Emmitt
,
Bruce M. Gentry
,
R. Michael Hardesty
,
Erland Källén
,
Michael J. Kavaya
,
Rolf Langland
,
Zaizhong Ma
,
Michiko Masutani
,
Will McCarty
,
R. Bradley Pierce
,
Zhaoxia Pu
,
Lars Peter Riishojgaard
,
James Ryan
,
Sara Tucker
,
Martin Weissmann
, and
James G. Yoe

The three-dimensional global wind field is the most important remaining measurement needed to accurately assess the dynamics of the atmosphere. Wind information in the tropics, high latitudes, and stratosphere is particularly deficient. Furthermore, only a small fraction of the atmosphere is sampled in terms of wind profiles. This limits our ability to optimally specify initial conditions for numerical weather prediction (NWP) models and our understanding of several key climate change issues.

Because of its extensive wind measurement heritage (since 1968) and especially the rapid recent technology advances, Doppler lidar has reached a level of maturity required for a space-based mission. The European Space Agency (ESA)'s Atmospheric Dynamics Mission Aeolus (ADM-Aeolus) Doppler wind lidar (DWL), now scheduled for launch in 2015, will be a major milestone.

This paper reviews the expected impact of DWL measurements on NWP and climate research, measurement concepts, and the recent advances in technology that will set the stage for space-based deployment. Forecast impact experiments with actual airborne DWL measurements collected over the North Atlantic in 2003 and assimilated into the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model are a clear indication of the value of lidar-measured wind profiles. Airborne DWL measurements collected over the western Pacific in 2008 and assimilated into both the ECMWF and U.S. Navy operational models support the earlier findings.

These forecast impact experiments confirm observing system simulation experiments (OSSEs) conducted over the past 25–30 years. The addition of simulated DWL wind observations in recent OSSEs performed at the Joint Center for Satellite Data Assimilation (JCSDA) leads to a statistically significant increase in forecast skill.

Full access