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Issue sup1: Copernicus Marine Service Ocean State Report, Issue 5 Supplement.-- Karina von Schuckmann (Editor), Pierre-Yves Le Traon (Editor), Neville Smith (Chair) (Review Editor), Ananda Pascual (Review Editor), Samuel Djavidnia (Review Editor), Jean-Pierre Gattuso (Review Editor), Marilaure Grégoire (Review Editor), The work was supported by the Copernicus Marine Environment Monitoring Service (CMEMS) LATEMAR project. CMEMS is implemented by Mercator Ocean in the framework of a delegation agreement with the European Union. This work has also been conducted as part of the bilateral project EOLO-1 (“Extreme Oceanic waves during tropical, tropical-like, and bomb cyclones”) between CNR-ISMAR and the University of Tokyo (Japan; Prof. Takuji Waseda). Antonio Ricchi funding have been provided via the PON “AIM” - Attraction and international mobility program AIM1858058. Joanna Staneva acknowledges H2020 IMMERSE Project, Arno Behrens was supported by CMEMS Waveflow project and G. Gayer by ESA Black Sea and Danube Regional Initiative (EO4BS).

Aerosol feedbacks are becoming more accepted as physical mechanisms that should be included in numerical weather prediction models in order to improve the accuracy of the weather forecasts. The default set-up in the Aire Limitee Adaptation dynamique Developpement INternational (ALADIN) — High Resolution Limited Area Model (HIRLAM) numerical weather prediction system includes monthly aerosol climatologies to account for the average direct radiative effect of aerosols. This effect was studied using the default aerosol climatology in the system and compared to experiments run using the more up-to-date Max-Planck-Institute Aerosol Climatology version 1 (MACv1), and time-varying aerosol data from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis aerosol dataset. Accounting for the direct radiative effect using monthly aerosol climatologies or near real-time aerosol distributions improved the accuracy of the simulated radiative fluxes and temperature and humidity forecasts in the lower troposphere. However, the dependency of forecast meteorological conditions on the aerosol dataset itself was found to be weak.

Persistent high pressure conditions over the European part of Russia during summer 2010 were responsible for an extended period of hot and dry weather, creating favourable conditions for severe wildfires. The chemical transport model SILAM is used to simulate the dispersion of smoke aerosol for this case. Aerosol fields from SILAM are compared to the Monitoring Atmospheric Composition and Climate (MACC) reanalysis. Moreover, the model output is compared to in situ and remote sensing measurements, paying particular attention to the most intense fire period of August 7 to 9, when the plume reached the Baltic countries and Finland. The maximum observed aerosol optical depth was more than 4 at 550 nm during this time. The aerosol distributions from the SILAM run and the MACC reanalysis are subsequently used in meteorological simulations using the Hirlam Aladin Research for Mesoscale Operational Numerical Weather Prediction in Euromed (HARMONIE) model. The modelling results show a significant reduction of the daily average shortwave radiation fluxes at the surface (up to 125 W/m2) and daily average near-surface temperature (up to 4 °C) through the aerosol direct radiative effect. The simulated near-surface temperature and vertical temperature profile agree better with the observations, when the aerosol direct radiative effect is considered in the meteorological simulation. The boundary layer is more stably stratified, creating poorer dispersion conditions for the smoke.

On August 8, 2010, a derecho swept over Northern Europe, causing widespread wind damage and more than 2 million Euros in economic loss in Estonia during its most destructive stage. This paper presents a modelling study of the derecho-producing storm utilising the Hirlam Aladin Research for Mesoscale Operational Numerical Weather Prediction in Europe (HARMONIE) model. The model setup is chosen to mimic near-future, nearly kilometre-scale, operational environments in European national weather services. The model simulations are compared to remote sensing and in situ observations. The HARMONIE model is capable of reproducing the wind gust severity and precipitation intensity. Moreover, 2.5-km grid spacing is shown to be sufficient for producing a reliable signal of the severe convective storm. Storm dynamics are well simulated, including the rear inflow jet. Although the model performance is promising, a strong dependence on the initial data, a weak trailing stratiform precipitation region and an incorrect timing of the storm are identified.

On August 8, 2010, a severe derecho type thunderstorm in the Baltic Sea region coincided with smoke from wildfires in Russia. Remarkable smoke aerosol concentrations, with a maximum aerosol optical depth of more than 2 at 550 nm, were observed near the thunderstorm. The impact of the wildfire smoke on the thunderstorm through direct radiative effects was investigated using the Hirlam Aladin Research for Mesoscale Operational Numerical Weather Prediction in Euromed (HARMONIE) model. HARMONIE was successfully able to resolve the dynamics of the thunderstorm, and simulations that considered the influence of the smoke-related aerosols were compared to simulation without aerosols. As simulated by the HARMONIE model, the smoke reduced the shortwave radiation flux at the surface by as much as 300 W/m 2 and decreased the near-surface temperature by as much as 3 °C in the vicinity of the thunderstorm and respectively 100 W/m 2 and 1 °C in the thunderstorm region. Atmospheric instability decreased through the direct radiative effect of aerosols, and several dynamic features of the simulated thunderstorm appeared slightly weaker.

We present ice-free and ice-included statistics for the Baltic Sea using a wave hindcast validated against data from 13 wave measurement sites. In the hindcast 84% of wave events with a significant wave height over 7 m occurred between November and January. The effect of the ice cover is largest in the Bay of Bothnia, where the mean significant wave height is reduced by 30% when the ice time is included in the statistics. The difference between these two statistics are less than 0.05 m below a latitude of 59.5°. The seasonal ice cover also causes measurement gaps by forcing an early recovery of the instruments. Including the time not captured by the wave buoy can affect the estimates for the significant wave height by roughly 20%. The impact below the 99th percentiles are still under 5%. The significant wave height is modelled accurately even close to the shore, but the highest peak periods are underestimated in a narrow bay. Sensitivity test show that this underestimation is most likely caused by an excessive refraction towards the shore. Reconsidering the role of the spatial resolution and the physical processes affecting the low-frequency waves is suggested as a possible solution.

The high-resolution reanalysis data-base BaltAn65+ covers the period of 1965–2005. Here, this dataset is used to derive essential climate parameters for the Baltic Sea region and Estonia. In particular, monthly mean temperature and total precipitation are calculated and a trend analysis is performed to analyze the temporal evolution of these climatological parameters during the reanalysis period. Monthly, seasonal, and annual maps of the climate characteristics, including trend maps, are created for the Baltic Sea region. Time series of monthly and annually averaged temperature and precipitation sum are presented over the Baltic Sea and Estonian domains together with fitted linear trends and trend significance analysis. Then, comparison with an observational database is performed to assess the quality of the reanalysis database. Additionally, the time series are compared with official climate normals for the period of 1971–2000, as calculated by the Estonian Environment Agency (EtEA). Findings of other publications in the scientific literature dealing with the climate of similar time period for Estonia and the Baltic Sea region are discussed. The quality of the BaltAn65+ reanalysis is found to be generally good for temperature but weak for precipitation.

Orographic drag formation is investigated using a numerical wave model (NWM), based on the pressure-coordinate dynamics of non-hydrostatic HIRLAM. The surface drag, wave stress (vertical flux of horizontal momentum), and wave drag are split to the longitudinal and transverse components and presented as Fourier sums of their spectral amplitudes weighted with the power spectrum of relative orographic height. The NWM is accomplished, enabling a spectral investigation of the buoyancy wave stress, and drag generation by orography and is then applied to a cold front, characterised by low static stability of the upper troposphere, large vertical and directional wind variations, and intensive trapped wave generation downstream of obstacles. Resonances are discovered in the stress and drag spectra in the form of high narrow peaks. The stress conservation problem is revisited. Longitudinal stress conserves in unidirectional flow, 2D orography conditions, but becomes convergent for rotating wind or 3D orography. Even in the convergent case the vertical momentum flux from the troposphere to stratosphere remains substantial. The transverse stress never conserves. Disappearing at the surface and on the top, it realises the main momentum exchange between lower an upper parts of the troposphere. Existence of stationary stratospheric quasi-turbulence (SQT) is established above wind minimum in the stratosphere.

This study is focused on a wild-land fire episode in 2010, August 7–9, when the plume of severe wildfires in European part of Russia reached Estonia and southern Finland, thus giving a chance to evaluate the modelling results against a relatively dense network of air quality monitoring stations. The chemistry-transport model SILAM, driven by the ECMWF meteo fields, was run within the European domain of AQMEII2 model validaton exercise with a 0.2-degree grid resolution, applying the AQMEII2 chemical and aerosol boundary conditions. The modelling results were compared with measured three-hourly average concentrations of PM2.5 in Estonia and Finland. The observed peak values in most of stations reached 60–80 µg/m3 (narrow peaks in the easternmost stations: up to 106 µg/m3 in Estonia and 220 µg/m3 in Finland, whereas SILAM predicted up to 75 µg/m3). Remarkably enhanced particulate matter concentrations were found in all 7 continental (rural and urban) monitoring stations of Estonia, reproduced by the model within 10 % of the peak values in 5 stations. The general shape of the peak was reproduced by SILAM within 3–6 h of a time error. The model runs suggest that the wildfires were not solely responsible for enhanced concentrations: the continental aerosols constituted about a half of the total mass. The westernmost maritime station in Estonia was left almost untouched by the plume. Remarkable direct effect of the aerosols on boundary-layer meteorological conditions, PBL height, near-surface wind and temperature was found during this episode when the aerosol direct radiative effect was considered in numerical weather prediction model HARMONIE.

Regional reanalysis database BaltAn65+ comprising meteorological data for Baltic Sea region for the time period 1965–2005 is described. For data assimilation and hindcasts, the numerical weather prediction model HIRLAM 7.1.4 is applied, with 11 km horizontal and 60-layer vertical resolution. Reanalysis includes three-dimensional weather analysis data. Standard surface observations and meteorological soundings together with ship and buoy measurements from WMO observational network are used in analysis. Boundary fields are obtained from ECMWF ERA-40 global re-analysis. The BaltAn65+ can be considered as a regional refinement of ERA-40 for Baltic Sea region, providing the historical weather and climate data with enhanced spatial resolution, which is main motivation for creation of this novel reanalysis database.

The possibilities of using High Resolution Limited Area Model (HIRLAM) version 6.4.0 outputs to describe wind parameters in the coastal zone of Estonia were investigated. For this purpose output from 3-dimensional variational (3DVAR) analysis and 24 h forecast files were compared with measurements at nine coastal sites during January and April-December 2007. Special attention was paid to moderate and strong winds (wind speed > 5 m/s) that are responsible for sea level changes and high wave heights in the coastal area. It is shown that HIRLAM overestimates the wind speed. This overestimation is stronger in cases where HIRLAM uses an inadequate land-sea fraction in the respective cells. The model describes the angular distribution of moderate and strong winds better than that of weak winds. Except for one station, approximately 90% of HIRLAM estimates of the direction of moderate and strong winds differ less than ± 22.5° from the measured values; in approximately 60% of cases the direction differs less than ± 10°. The HIRLAM system approximates best the winds at the westernmost stations on the Estonian islands and in Parnu, whereas a 24 h forecast gives somewhat better results than the winds diagnosed from 3DVAR analysis.

Estimation of accuracy of different high-resolution, sound-filtered, pressure-coordinate models is carried out by modeling their response to orographic forcing. Evaluated models are the elastic nonhydrostatic model (EFM), the anelastic nonhydrostatic model (AEM), and the hydrostatic primitive equation model (HSM). These models are compared to the exact, nonfiltered, nonhydrostatic, pressure-coordinate dynamics (ExM). All model equations are linearized, a wave equation for vertical displacements of air particles is derived, and exact analytical stationary solutions for each model are compared for uniform flow over given smooth orography (bell-shaped mountain). These linear solutions reveal that compressible (ExM, EFM) and incompressible (AEM, HSM) models are different at long horizontal scales l ∼ 1000 km. Differences are especially large in the vertical velocity field (up to 100%) at the medium and upper levels of the atmosphere, where incompressible models give systematic reductions of wave ampl...

Low-level jets (LLJ) are important for turbulence in the stably stratified atmospheric boundary layer, but their occurrence, properties, and generation mechanisms in the Arctic are not well known. We analysed LLJs over the central Arctic Ocean in spring and summer 2007 on the bases of data collected in the drifting ice station Tara. Instead of traditional radiosonde soundings, data from tethersonde soundings with a high vertical resolution were used. The Tara results showed a lower occurrence of LLJs (46%) than many previous studies over polar sea ice. Strong jet core winds contributed to growth of the turbulent layer. Complex relationship between the jet core height and the temperature inversion top height were detected: substantial correlation (r = 0.72; p < 0.01) occurred when the jet core was above the turbulent layer, but inside the turbulent layer there was no correlation. The most important forcing mechanism for LLJs was baroclinicity, which was responsible for generation of strong and warm LLJs, which on average occurred at lower altitudes than other jets. Baroclinic jets were mostly associated to transient cyclones instead of the climatological air temperature gradients. Besides baroclinicity, cases related to inertial oscillations, gusts, and fronts were detected. In approximately 50% of the observed LLJs the generation mechanism remained unclear, but in most of these cases the wind speed was strong in the whole vertical profile, the jet core representing only a weak maximum. Further research needs on LLJs in the Arctic include investigation of low-level jet streams and their effects on the sea ice drift and atmospheric moisture transport.

Two-time-level, semi-implicit, semi-Lagrangian (SISL) scheme is applied to the non-hydrostatic pressure coordinate equations, constituting a modified Miller–Pearce–White model, in hybrid-coordinate framework. Neutral background is subtracted in the initial continuous dynamics, yielding modified equations for geopotential, temperature and logarithmic surface pressure fluctuation. Implicit Lagrangian marching formulae for single time-step are derived. A disclosure scheme is presented, which results in an uncoupled diagnostic system, consisting of 3-D Poisson equation for omega velocity and 2-D Helmholtz equation for logarithmic pressure fluctuation. The model is discretized to create a non-hydrostatic extension to numerical weather prediction model HIRLAM. The discretization schemes, trajectory computation algorithms and interpolation routines, as well as the physical parametrization package are maintained from parent hydrostatic HIRLAM. For stability investigation, the derived SISL model is linearized with respect to the initial, thermally non-equilibrium resting state. Explicit residuals of the linear model prove to be sensitive to the relative departures of temperature and static stability from the reference state. Relayed on the stability study, the semi-implicit term in the vertical momentum equation is replaced to the implicit term, which results in stability increase of the model.

The semi-implicit semi-Lagrangian (SISL), two-time-level, non-hydrostatic numerical scheme, based on the non-hydrostatic, semi-elastic pressure-coordinate equations, is tested in model experiments with flow over given orography (elliptical hill, mountain ridge, system of successive ridges) in a rectangular domain with emphasis on the numerical accuracy and non-hydrostatic effect presentation capability. Comparison demonstrates good (in strong primary wave generation) to satisfactory (in weak secondary wave reproduction in some cases) consistency of the numerical modelling results with known stationary linear test solutions. Numerical stability of the developed model is investigated with respect to the reference state choice, modelling dynamics of a stationary front. The horizontally area-mean reference temperature proves to be the optimal stability warrant. The numerical scheme with explicit residual in the vertical forcing term becomes unstable for cross-frontal temperature differences exceeding 30 K. Stability is restored, if the vertical forcing is treated implicitly, which enables to use time steps, comparable with the hydrostatic SISL.

Pressure (isobaric or p-) coordinates in non-hydrostatic (NH) dynamics with pressure in the role of the vertic al coordinate were first introduced by (1974), and generalized to sigma-coordinate framework by (1984). First numerical applicat ions of the NH model in pressure related coordinates where developed by (1991) for twodimensional case, and by (1992) for three-dimensional motion.

A nonhydrostatic pressure-coordinate model of atmospheric dynamics is developed. The model filters acoustic mode. Internal acoustic waves are filtered using the assumption of non-divergence of motion in pressure-space. External (Lamb mode) waves are filtered using the surface pressure adjustment. The model is implemented in the framework of the numerical weather prediction model HIRLAM (High Resolution Limited Area Model) as an extension to the hydrostatic kernel. The integration scheme is either the explicit or semi-implicit Eulerian leapfrog time stepping. Due to the acoustic filtration, the explicit scheme supports quite large time-steps. To check the validity of the model, several flow experiments with artificial orography are performed. The hydrostatic and nonhydrostatic flow regimes are investigated. The results of different models are compared mutually and with the analytic solutions. The real situation simulations are also presented to show the model’s forecasting capabilities. DOI: 10.1034/j.1600-0870.2003.00018.x

This paper presents a comparison of the wind data measured by the ASCAT polar-orbiting satellite scatterometer and winds forecast by the numerical weather prediction model HIRLAM in the Baltic Sea region during the stormy season in 2009. Two different resolution models were used in the comparison. Mutual quality and uncertainty characteristics of the measurements and predictions are determined. The results of the study show that the ASCAT wind data are well correlated with the HIRLAM predicted winds, which raises the credibility of both data sources in operational and hindcasting applications over the Baltic Sea. A case of phase error in a HIRLAM forecast of cyclonic activity over the Baltic Sea is discussed.