Nedjeljka Žagar

Assessment of the accuracy of (re)analyses in the equatorial lower stratosphere

The accuracy of horizontal winds and temperature in the equatorial lower stratosphere is evaluated in different (re)analyses (European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis, ERA Interim, and Modern-Era Retrospective Analysis for Research and Applications) using an independent data set collected at low latitudes during long-duration balloon flights in early 2010. The three analyzed wind products are found significantly less accurate than in the extratropics, with periods of ≳10m/sdisagreement with the observations lasting several days. To highlight the dynamical context in which the major disagreement events occur, case studies are carried out. The events are shown to be related to an improper representation of large-scale equatorial Kelvin and Yanai wave packets with vertical wavelengths smaller than 5 km. Such events can induce large errors on trajectories computed with analyzed winds relatively to the actual (balloon) trajectory: 4000 km separation after 5 days of calculation. Reasons for analyses inaccuracy are discussed. The vertical resolution of the underlying model likely plays a role, but the main factor responsible for deficiencies appears to be the lack of wind observations. Indeed, errors in analyzed winds during the campaign have a strong longitudinal structure, with root-mean-square errors twice as large over the Indian Ocean and western Pacific, poorly covered by radiosounding stations, as over the Maritime Continent or South America. For the ECMWF analysis, this structure mirrors that of the analysis increments, which have largest amplitudes over observed regions. We argue that the reported events are more likely to happen during maximum shear phases of the quasi-biennial oscillation.

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.

Uncertainties of Estimates of Inertia–Gravity Energy in the Atmosphere. Part II: Large-Scale Equatorial Waves

Abstract This paper analyzes the spectra and spatiotemporal features of the large-scale inertia-gravity (IG) circulations in four analysis systems in the tropics. Of special interest is the Kelvin wave (KW), which represents between 7% and 25% of the total IG wave (zonal wavenumber k ≠ 0) energy. The mixed Rossby–gravity (MRG) mode comprises between 4% and 15% of the IG wave energy. At the longest scales, the KW spectra are fitted by a law while the MRG energy spectrum appears flat. At shorter scales both modes follow a −3 law. Energy spectra of the total IG wave motion at long zonal scales (zonal wavenumber smaller than 7) have slopes close to −1. The average circulation associated with KW is characterized by reverse flows in the upper and lower troposphere consistent with the ideas behind simple tropical models. The inverse projection is used to quantify the role of Kelvin and MRG waves in current analysis systems in the upper troposphere over the Indian Ocean. At these levels, easterlies between 10°S a...

Rotational and divergent kinetic energy in the mesoscale model ALADIN

Kinetic energy spectra from the mesoscale numerical weather prediction (NWP) model ALADIN with horizontal resolution 4.4 km are split into divergent and rotational components which are then compared at horizontal scales below 300 km and various vertical levels. It is shown that about 50% of kinetic energy in the free troposphere in ALADIN is divergent energy. The percentage increases towards 70% near the surface and in the upper troposphere towards 100 hPa. The maximal percentage of divergent energy is found at stratospheric levels around 100 hPa and at scales below 100 km which are not represented by the global models. At all levels, the divergent energy spectra are characterised by shallower slopes than the rotational energy spectra, and the difference increases as horizontal scales become larger. A very similar vertical distribution of divergent energy is obtained by using the standard ALADIN approach for the computation of spectra based on the extension zone and by applying detrending approach commonly used in mesoscale NWP community.

Self-Organizing Maps-based ocean currents forecasting system

An ocean surface currents forecasting system, based on a Self-Organizing Maps (SOM) neural network algorithm, high-frequency (HF) ocean radar measurements and numerical weather prediction (NWP) products, has been developed for a coastal area of the northern Adriatic and compared with operational ROMS-derived surface currents. The two systems differ significantly in architecture and algorithms, being based on either unsupervised learning techniques or ocean physics. To compare performance of the two methods, their forecasting skills were tested on independent datasets. The SOM-based forecasting system has a slightly better forecasting skill, especially during strong wind conditions, with potential for further improvement when data sets of higher quality and longer duration are used for training.

Impact of new aircraft observations Mode‐S MRAR in a mesoscale NWP model

The impact of recently available high-resolution Mode-S Meteorological Routine Air Report (MRAR) wind and temperature observations is evaluated in the mesoscale numerical weather prediction (NWP) model Aire Limitee Adaptation dynamique Developpement InterNational (ALADIN). Data available from the airspace communicating with the Ljubljana Airport in Slovenia are assimilated by using the three-dimensional variational assimilation procedure on top of all other observations assimilated operationally. A data selection method based on aircraft type was shown to be important for the first application of the new observations in ALADIN. The evaluation of Mode-S MRAR impact included both winter and summer periods. In both seasons a clear improvement of wind and temperature forecasts was found for in the short forecast range, 1–3 h. The impact in the 24 h forecast range depends on season, with a consistent positive improvement of the boundary layer temperature forecasts obtained for the stable anticyclonic winter situations. In summer, the impact was mixed and it was found to be sensitive to the multivariate aspects of the moisture analysis. Overall presented results suggest that the new aircraft-derived observations Mode-S MRAR have a significant potential for mesoscale NWP and improved data assimilation modeling.

A Three-Dimensional Multivariate Modal Analysis of Atmospheric Predictability with Application to the ECMWF Ensemble

AbstractA new methodology for the analysis of ensemble prediction systems (ENSs) is presented and applied to 1 month (December 2014) of ECMWF operational ensemble forecasts. The method relies on the decomposition of the global three-dimensional wind and geopotential fields onto the normal-mode functions. The ensemble properties are quantified in terms of the 50-member ensemble spread associated with the balanced and inertio-gravity (IG) modes for forecast ranges every 12 h up to 7 days. Ensemble reliability is defined for the balanced and IG modes comparing the ensemble spread with the control analysis in each scale.Modal analysis shows that initial uncertainties in the ECMWF ENS are largest in the tropical large-scale modes and their spatial distribution is similar to the distribution of the short-range forecast errors. Initially the ensemble spread grows most in the smallest scales and in the synoptic range of the IG modes but the overall growth is dominated by the increase of spread in balanced modes i...

Multivariate Data Assimilation in the Tropics by Using Equatorial Waves

This paper reports recent advances in understanding of dynamical aspects of the tropical data assimilation. In contrast with the mid-latitudes, there is no a well-defined approach for the tropical data assimilation in numerical weather prediction (NWP) community which has traditionally been concentrated on the mid-latitude analysis problem. In particular, the impact of the equatorial Rossby, inertio-gravity, and mixed Rossby-gravity waves on the tropical forecast-error covariances is difficult to quantify. Various tropical waves are characterized by different couplings between the mass field and the wind field. The average mixture of these waves, built into the background-error covariance matrix for data assimilation provides analysis increments which appear nearly univariate even though they result from the advanced multivariate assimilation methodology. This applies to both dry and moist idealized tropical systems as well as to a 4D-Var NWP assimilation system.

Sensitivity of HF radar-derived surface current self-organizing maps to various processing procedures and mesoscale wind forcing

We performed a number of sensitivity experiments by applying a mapping technique, self-organizing maps (SOM) method, to the surface current data measured by high-frequency (HF) radars in the northern Adriatic and surface winds modelled by two state-of-the-art mesoscale meteorological models, the Aladin (Aire Limitée Adaptation Dynamique Développement InterNational) and the Weather and Research Forecasting models. Surface current data used for the SOM training were collected during a period in which radar coverage was the highest: between February and November 2008. Different pre-processing techniques, such as removal of tides and low-pass filtering, were applied to the data in order to test the sensitivity of characteristic patterns and the connectivity between different SOM solutions. Topographic error did not exceed 15 %, indicating the applicability of the SOM method to the data. The largest difference has been obtained when comparing SOM patterns originating from unprocessed and low-pass filtered data. Introduction of modelled winds in joint SOM analyses stabilized the solutions, while sensitivity to wind forcing coming from the two different meteorological models was found to be small. Such a low sensitivity is considered to be favourable for creation of an operational ocean forecasting system based on neural networks, HF radar measurements and numerical weather prediction mesoscale models.

Impact of the Vertical Resolution of Analysis Data on the Estimates of Large-Scale Inertio-Gravity Energy

AbstractThis paper deals with the large-scale inertio-gravity (IG) wave energy in the operational ECMWF analyses in July 2007. Energy percentages of the IG waves obtained from the standard-pressure-level data are compared to those derived from various discretizations of the model-level data. The results show a small albeit systematic increase of the IG energy percentage as the vertical level density increases from the standard-pressure levels toward the model-level density; the small relative change is explained by the sufficient vertical resolution to resolve the large-scale IG waves in the tropics that make the majority of the global IG energy on large scales. A relatively larger increase of the IG energy is obtained when the mesospheric model levels are included; however, the analyses at these levels in July 2007 are less reliable. Furthermore, two numerical methods for the normal-mode function (NMF) decomposition are shown to provide similar results. The decomposition of atmospheric analyses into the ...