Black Sea coastal forecasting systems

Introduction Conclusions References


Introduction
Coastal waters have always been area of high societal interest.Increasing human migration to coastal regions raises complex public-policy issues concerning the quality of life of people and their impact on the marine environment.Continuing concerns about sustainable utilization of natural resources and preservation of environmental quality attract more and more attention of the society.An effective management and sustainable use of coastal areas and resources demands realistic multidisciplinary information about the state of marine environment and its changes.Marine nowcasting and forecasting systems are proper tools capable to satisfy such needs.
Nowcasting and forecasting of coastal dynamics in the Black Sea has several specific features.The basin-scale nowcasting and forecasting system operating in the real-time provides simulation on the rectangular Caresian grid with 5 × 5 km resolution.Such resolution is relevant to resolve mesoscale variability in the deep basin where the Rossby radius is greater than 20 km.Diminishing of the basin depth in the coastal area significantly reduces the value of the internal Rossby radius and, thus, curtails the characteristic temporal and spatial scales of major dynamical processes.Rapid Introduction

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Full surface in the coastal regions that results in occurrence of small scale fronts and filaments.The features of the coastal dynamics can be adequately reproduced by the general circulation models only if the grid size is substantially shorter than that in the open part of the basin.The peculiarities of the coastal dynamics can be taken into account in various ways.
The method of the nested grids is one of them that is used in the ECOOP project.The essence of this method consists of higher spatial resolution in a selected region adjoining the coast compatible with the characteristic spatial scales of the phenomena taking place in the coastal area of the sea.The liquid boundaries of the selected region should coincide with the boundaries of the boxes of the large-scale model.The liquid boundary conditions for the nested grid model are taken from the simulations of the basin-scale model.In the models, a passive, off-line, one way interaction nesting method has been used which means that the boundary conditions of the fine grid model are prescribed in some way by external data taken from the coarse resolution model, while the solution of the latter is not modified by the solution of the fine grid model in their common overlapping area.The nesting method provides flow of information through the open boundaries from the coarse resolution basin-scale model to the coastal high-resolution models.An integral constraint is applied to ensure that the net mass flux across the open boundaries is identical to the net flux in the basin scale model.
A pilot version of the Black Sea coastal forecasting system has been developed in the framework of EU FP5 ARENA project (Kubryakov et al., 2006).Six regional models of different types both in z-coordinates or in σ-coordinates with various resolutions were nested in the basin scale model working in the operational mode (Fig. 1).Two regional models -for the Burgas Bay and for the Georgian coastal zone -are in z-coordinates.The other regional models represent the version of the Princeton Ocean Model for the Kalamita Bay near the western Crimea, for the Romanian coastal zone, for the North-Western Shelf zone and Russian coastal zone of the Black Sea.Full system operated during five days in July 2005 in the manual mode.Introduction

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Full The further improvement of the coastal zone nowcasting and forecasting in the Black Sea was carried out in the framework of EU FP6 ECOOP project (Kubryakov et al., 2008b).Five sub-regions were selected for the nesting of coastal models to the basin scale one.The sub-regions were selected to cover areas of potential pollutions and intense traffic.They include the Bulgarian coast-Bosphorus Strait region with intense shipping and two large ports (Burgas and Varna), Romanian coast and North-Western shelf of the Black Sea where major rivers transport potentially polluted freshwater and three big ports are situated (Constanta, Odessa and Il'ichevsk); South of Crimea until the Kerch Strait mouth, significant recreation area; Russian coast near Novorossiysk port and Georgian coast near ports Poti and Batumi (Fig. 2).The first three regions were part of the basic ECOOP coastal nowcasting and forecasting system.The regions in the Russian and Georgian coastal waters are parts of the Black Sea GOOS initiative supported by the ECOOP partnership.

Hydrodynamic models for all coastal regions
An initial requirement for the high resolution regional models was that they should be capable to resolve scales associated with mesoscale phenomena, such as fronts and eddies.The spatial resolution of 1 × 1 km was selected for all five coastal regions.All of these models have 18 sigma-surfaces in the vertical.The POM-version has been adapted to the selected coastal regions of the Black Sea in Marine Hydrophysical Institute (Sevastopol, Crimea) (Kubryakov, 2004, Stefanescu et al., 2004).The models operated during ECOOP have been carefully calibrated to the Black Sea conditions against observations.The model developed by the Institute of Geophysics in Georgia was installed for the Georgian coastal zone (Kordzadze and Demeterashvili, 2011) The basin-scale Black Sea nowcasting and forecasting system forms a basis for the initial and boundary conditions of the coastal models.It provides initial fields of temperature, salinity and current velocity on a regular grid with 5 km resolution and 33 vertical z-levels.3 System architecture and system products

System architecture
The real-time basin-scale nowcasting and forecasting system of the Black Sea provides atmospheric forcing, initial and boundary conditions for the coastal forecasting for all five regions.The Black Sea circulation model uses atmospheric forcing of the regional atmospheric model of ALADIN family simulated by the National Meteorological Administration of Romania (NMA) and assimilates space altimetry, SST and climatic temperature and salinity profiles.A detailed description of the basin-scale Black Sea nowcasting and forecasting system is presented by Korotaev et al. (2011).
The regional models run in the oceanographic institutes of the corresponding riparian countries.The special training of responsible oceanographer-users has been carried out to install the regional models (Kubryakov et al., 2008a).The training included: (i) preparation of atmospheric forcing, initial and boundary conditions; (ii) setting of models parameters and run of models in nowcasting or forecasting modes; and (iii) installation of software for visualisation and analysis of input and output model products.
The basin-scale nowcast and forecast are usually ready at 11 a.m.every day.Then atmospheric forcing, initial and boundary conditions are automatically prepared for each coastal region and uploaded on the FTP-server at MHI.Initial conditions are uploaded for the day before the present.Atmospheric forcing and boundary conditions are provided for all four days including one day of hindcast and three days of forecast.
The regional operators then download these atmospheric forcing, initial and boundary conditions and automatically run their models providing analysis and three days forecast of the three-dimensional fields of temperature, salinity and current velocity.Operational data of the regional ECOOP nowcast and forecast then collected on the OpenDAP server of IMS-METU and transmitted to the EuroMISS server of the ECOOP project.Any user was able to select some section of the simulated fields or even to build cartoon using EuroMISS facilities.The scheme of the data exchange in the Black Sea coastal nowcasting and forecasting system is shown on the Fig. 4.

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System products
Full three-dimensional arrays of temperature, salinity and current velocity data as well as static and dynamic previews of temperature and salinity fields on different depths were made available via EuroMISS server.Figure 5 shows the distribution of SST and surface salinity in the south-western corner of the basin.The structure of Rim Current transporting patches of warm water along the shore is well presented on the salinity map as a boundary between red and yellow colours.The cold and low salinity water associated with the Danube runoff is also seen along the coast.This narrow jet of the cold water along the western coast of the Black Sea is often observed on the satellite infrared imagery in winter time.
The result of three days forecast of SST on the North-Western shelf of the Black Sea and near the Crimea coast are presented on Fig. 6.The formation of cold water near the northern boundary of the shelf is evident on the left panel of Fig. 6.Four days forecast demonstrate complex mixing of warm and cold water on the shelf by means of intrusions.The set of maps on the left panel of Fig. 6 shows also the process of anticyclonic eddy formation near the Danube mouth where the cooler water propagates to the south-west along the right edge of the eddy and warmer water moves to the north-east along the coast.
The most interesting phenomenon presented on the left panel of Fig. 6 is the warm water transport to the Crimea coast by the Rim Current.Relatively cold water is seen on the panel to the south from the Rim Current jet and in the north-eastern part of the basin near the mouth of the Kerch Strait.The warm water transport to the Crimea coast by the Rim Current has important significance for the region.It supports mild winters and subtropical climate along the southern beach of Crimea.However Fig. 6 shows that the warm water flow is intermittent.Therefore it remains to investigate modulation Validation of the coastal system products was essential part of the ECOOP project.
Both off line and on line validations were considered during the project development.
On line validation of SST was carried out according to the common standards by means of the comparison of simulations with temperature field derived from NOAA AVHRR data.Off line validation was based on the use of archived data, non-operational or any other set of observations.Off line validation of the three-dimensional temperature and salinity fields was fulfilled based on the cruise data.
In-situ temperature and salinity profiles which are used for validation the models of the Crimean coastal region and the North-Western shelf region were obtained during oceanographic surveys, carried out by R/V Eksperiment from July 2005 to October 2007.Some information about sampling locations is presented in Tables 1 and 2.
The hydrodynamic model set up for the Western part of the Black Sea was validated using in situ measurements of database which consists of CTD casts performed in this area mainly during regular monitoring cruises with R/V Akademik in a 4-year period  3.
NOAA satellites IR imagery is received and on-line processed at the MHI Receiving Center.The data processing includes all necessary corrections, filtration of clouds and simulation of SST maps with 1 km spatial resolution every 6 hours using multichannel algorithm.These maps were daily averaged and then used for assimilation in the basinscale model to increase accuracy of nowcast and forecast.IR SST maps obtained every day near the midnight are also used for the validation of the coastal forecast.Introduction

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Full Figure 9 presents some examples of the comparison when the prediction time is than 13.5 h.The temperature profiles, derived from the basin-scale (red, "BAS"), sub-regional (blue, "LOC") model simulations and in situ data (black, "InS"), are presented on the left panel.Deviations between basin-scale model and in-situ profiles (red, "BAS-InS"), sub-regional model and in-situ profiles (blue, "LOC-InS"), basin-scale and sub-regional models (black, "LOC-BAS") are presented on the right panel.The difference between observations and simulations is within 0.5 • for most of the depths.The maximal deviation is observed in the seasonal thermocline (10-30 m) where vertical gradient of temperature is largest and even small distortion of the isotherm position provides significant difference of the temperature value.Good consistency between simulations and observations is typical for the beginning of the upper layer heating in May, and at the beginning of upper layer cooling in September-October.The temperature profiles predicted by the sub-regional models in this case better resemble the in situ profiles with respect to those simulated by the basin-scale model.The difference between forecasted and observed temperature profiles was calculated for three different groups.The first group includes the prediction time from 0 to 24 h, the second group consists of the cases with prediction time from 24 to 48 h and the third one for the prediction time from 48 to 72 h.Thus, every station was used for the comparison up to four times, due to intersection of the time intervals for different prediction cycles.Then, the bias and standard deviation between simulations and observations were estimated by averaging on every z-level over all stations for each group.We observe that the error statistics have common features for all groups.Bias, standard deviation, minimal and maximal deviations have maximum value in the Introduction

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Full seasonal thermocline with standard deviations up to 3 • C, whereas it may be as high as 1.5 • C in the upper homogeneous layer.They slightly increase as the time of prediction grows from first group to the third one.Generally, error statistics for the sub-regional models and the basin-scale one are rather close in spite of the sub-regional model reproduce better small-scale features.
Profiles of biases (µ) and standard deviations (σ) for the surveys near the Crimea coast are shown on Fig. 10 as an example.Common information about stations, observation time, local prediction time (PredTime), and number stations (nObs) is presented on the figure caption.We note that the number of the comparisons decreases with depth because the most part of observations were collected in the coastal and shelf zones with limited depths.Figure 10 shows that the temperature profiles, predicted by the sub-regional model, have slightly higher bias and standard deviation than that simulated by the basin-scale model.The most significant difference between observations and model prediction is concentrated in the upper mixed layer and seasonal thermocline.Very similar results are obtained for the North-West shelf area (Fig. 11).
Comparison of individual salinity profiles are presented on Fig. 12. for the prediction time of roughly 2.5 days.The sub-regional models demonstrate a bad skill especially in the permanent pycnocline depth range of 150-300 m.However both model predictions are in the range of about 0.2 ppt within the upper 100 m layer.
Bias and standard deviation of simulated salinity profiles against measured ones are presented on Fig. 13 for the prediction time interval 48-72 h based on observations near the Southern Coast of Crimea.These profiles are shown up to 200 m because of the lack of deep stations.Most significant differences in the bias for the basin-scale and sub-regional models are observed in 120-200 m layer.In this layer absolute value of the bias for sub-regional model is higher then for basin-scale model.Both models have the standard deviation about 0.6 ppt in the upper 0-30 m layer.However an accuracy of the salinity forecast is rather good for both models at depths 30-100 m.Bias and standard deviation, as usual, decrease from third till first prediction interval.The similar results apply for the North-West shelf.Introduction

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On-line validation of SST
The standard on-line validation of all the ECOOP regional and coastal systems was carried out during the operational phase of the project.The goal of the on-line validation was to control the forecasting systems in operation and assess the consistency of simulations and observations evaluating accuracy of model outputs.SST as the simplest common variable was selected for the on-line validation.High resolution SST data sets were available for every ECOOP area through the EuroMISS catalogue and so it was easy to compare observed and simulated SST in the real time.The ECOOP coastal forecasting systems including the Black Sea one operate daily.Forecasted SST for the current date, one and two days before were compared with the AVHRR-SST observed for today.Three figures were prepared and displayed on the ECOOP web to present validation results.Every figure contained maps of SST observation, prediction or analysis and difference between observed and simulates values (where observations were available).Simple statistical information such as bias, standard deviation, and number of pixels available for the comparison was presented on the third Similar results are obtained for the South-Western corner of the basin (Fig. 16).The nowcasted SST field is characterised by the bias equal 0.14 • C and standard deviation of 0.6 • C. The standard deviation and the bias increase to 0.79 • C and 0.54 • C, respectively, after two days forecast.On the average based on almost one year SST validation, the standard deviation is evolved from 0.67 • C for the nowcast up to 0.92 • C for one day forecast, then to 1.1 • C for two days forecast and finally to 1.27 • C for three days forecast.It is interesting to note that the model nowcast corresponds better to the SST derived from the satellite measurements than the in situ data as it follows from Fig. 10.The most probable explanation is related with the difference in the discrete surface sampling at sea and by the model and satellites.

Conclusions
The Black Sea coastal forecasting system was efficiently developed by the consortium of the riparian countries.Full  Full Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | gen, and hydrogen sulfide.Ammonium and hydrogen sulphide fluxes are prescribed at the lower boundary for regions deeper than 200 m.Conditions on the lateral liquid boundaries for state variables of the biogeochemical model are provided by basin-wide model.As an example for the coastal ecosystem model output, Fig. 3 demonstrates seasonmean distribution of surface nitrate (left), phytoplankton (central) and zooplankton (right) concentrations.In summer and autumn seasons there are increased values of surface nitrate concentration near the southern Crimea coast due to strong upwelling; as a result, high values of phytoplankton and zooplankton occurred.Comparison between season-mean surface phytoplankton concentrations derived from coastal and basin-wide models shows that the results of the basin model are evidently smoother.Local phytoplankton bloom near the southern Crimea coast is more noticeable in the case of the regional model.Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | of the local weather by warm and cold water spots transported by the Rim Current.Discussion Paper | Discussion Paper | Discussion Paper | 4 Validation of the system products

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[2004][2005][2006][2007]. Monitoring scheme implemented by the Institute of Oceanology of Bulgarian Academy of Sciences (IO-BAS), shown in Fig.7, covers the Bulgarian economic zone and sampling is carried out at least 4 times per year.The total number of cruises included in the database is 19 that are performed mainly in summer and autumn.There are 3 winter and 2 spring cruises present.The average number of sampling stations is 28 per cruise and the maximum -80 stations during June 2006 cruise.Stations sampled during 2004-2007 are shown on Fig. 8. Exact cruise duration and number of stations are listed in Table were used for the comparison of simulations and observations near the South Coast region of Crimea and 240 for North-West shelf collected in different dates, times and geographical locations.
Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Fig. 15.Only the difference between nowcast/forecast and observations is shown.The bias of simulated fields against the observed one is rather low and almost the same for the nowcast (−0.15•C) and forecast (−0.11 • C).The standard deviation is equal 0.66• C for the nowcast but grows with the time of prediction up to 1.05• C after two days of forecast.
Six groups that were involved in this operational work are Institute of Oceanology (Bulgaria), Institute Geophysics (Georgia), National Institute of Marine Research (Romania), State Oceanographic Institute (Russia), Institute of Marine Sciences-Middle East Technical University (Turkey) and Marine Hydrophysical Institute (Ukraine).Developed system of coastal forecasts demonstrates its efficiency Introduction Discussion Paper | Discussion Paper | Discussion Paper | and relevance to the end user needs as assessed by the Black Sea GOOS that further considered continuation of the real-time operation of these coastal forecasting systems.Environmental ministries and hydrometeorological services are among customers of the coastal forecasting.The Black Sea coastal forecasting system forms a basis for the operations of the Black Sea Marine Forecasting Centre of the EU Discussion Paper | Discussion Paper | Discussion Paper | edited by: Dahlin, H., Bell, M. J., Flemming, N. C., and Petersson, S. E., Proceedings of the Fifth International Conference on EuroGOOS, 20-22 May, Exeter, UK, 293-296, 2008b.Stefanescu, S., Cordoneanu, E., and Kubryakov, A.: Ocean Wave and Circulation Modelling for the Black Sea, Romanian Journal of Meteorology, 6(1-2), ISSN 1223-1118, 75-88, 2004Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Ecosystem model of the South Coast of Crimea and North East Black Sea.
Initialisation of the coastal models started a day before the current 1058 Introduction

Table 1 .
Period of observations and number of hydrographic profiles obtained near the Southern Coast of Crimea.

Table 2 .
Period of observations and number of hydrographic profiles obtained on the North-Western shelf.

Table 3 .
Duration and number of sampled stations presented in the IO-BAS database.