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Assimilation scheme of the Mediterranean Forecasting System: operational implementation  [PDF]
E. Demirov,N. Pinardi,C. Fratianni,M. Tonani
Annales Geophysicae (ANGEO) , 2003,
Abstract: This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP). The assimilation scheme, System for Ocean Forecast and Analysis (SOFA), is a reduced order Optimal Interpolation (OI) scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF). The data assimilated are Sea Level Anomaly (SLA) and temperature profiles from Expandable Bathy Termographs (XBT). The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT). The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS) between the model forecast and the analysis (the forecast RMS) is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS) is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements. Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction)
Assimilation of ocean colour data into a Biochemical Flux Model of the Eastern Mediterranean Sea  [PDF]
G. Triantafyllou,G. Korres,I. Hoteit,G. Petihakis
Ocean Science Discussions (OSD) , 2006,
Abstract: Within the framework of the European MFSTEP project, an advanced multivariate sequential data assimilation system has been implemented to assimilate real chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) into a three-dimensional biochemical model of the Eastern Mediterranean. The physical ocean is described through the Princeton Ocean Model (POM) while the biochemistry of the ecosystem is tackled with the Biochemical Flux Model (BFM). The assimilation scheme is based on the Singular Evolutive Extended Kalman (SEEK) filter, in which the error statistics were parameterized by means of a suitable set of Empirical Orthogonal Functions (EOFs). A radius of influence was further selected around every data point to limit the range of the EOFs spatial correlations. The assimilation experiment was performed for one year over 1999 and forced with ECMWF 6 hour atmospheric fields. The accuracy of the ecological state identification by the assimilation system is assessed by the relevance of the system in fitting the data, and through the impact of the assimilation on non-observed biochemical processes. Assimilation of SeaWiFS data significantly improves the forecasting capability of the BFM model. Results, however, indicate the necessity of subsurface data to enhance the controllability of the ecosystem model in the deep layers.
Assimilation of SLA along track observations in the Mediterranean with an oceanographic model forced by atmospheric pressure  [PDF]
S. Dobricic,C. Dufau,P. Oddo,N. Pinardi
Ocean Science Discussions (OSD) , 2012, DOI: 10.5194/osd-9-1577-2012
Abstract: A large number of SLA observations at a high along track horizontal resolution are an important ingredient of the data assimilation in the Mediterranean Forecasting System (MFS). Recently new higher frequency SLA products have become available, and the atmospheric pressure forcing has been implemented in the numerical model used in the MFS data assimilation system. In a set of numerical experiments we show that in order to obtain the most accurate analyses the ocean model should include the atmospheric pressure forcing and the observations should contain the atmospheric pressure signal. When the model is not forced by the atmospheric pressure the high frequency filtering of SLA observations, however, improves the quality of the analyses. It is further shown that MFS analyses, produced by an assimilation system given by the numerical model and the high frequency SLA observations, have a correct power spectrum at high wave numbers and they filter efficiently the SLA assimilated observations which, on the other hand, are contaminated by high wavenumber noise.
Assimilation of SLA along track observations in the Mediterranean with an oceanographic model forced by atmospheric pressure  [PDF]
S. Dobricic,C. Dufau,P. Oddo,N. Pinardi
Ocean Science (OS) & Discussions (OSD) , 2012, DOI: 10.5194/os-8-787-2012
Abstract: A large number of SLA observations at a high along track horizontal resolution are an important ingredient of the data assimilation in the Mediterranean Forecasting System (MFS). Recently, new higher-frequency SLA products have become available, and the atmospheric pressure forcing has been implemented in the numerical model used in the MFS data assimilation system. In a set of numerical experiments, we show that, in order to obtain the most accurate analyses, the ocean model should include the atmospheric pressure forcing and the observations should contain the atmospheric pressure signal. When the model is not forced by the atmospheric pressure, the high-frequency filtering of SLA observations, however, improves the quality of the SLA analyses. It is further shown by comparing the power density spectra of the model fields and observations that the model is able to extract the correct information from noisy observations even without their filtering during the pre-processing.
Operational coastal ocean forecasting in the Eastern Mediterranean: implementation and evaluation  [PDF]
G. Zodiatis,R. Lardner,D. R. Hayes,G. Georgiou
Ocean Science Discussions (OSD) , 2006,
Abstract: The Cyprus Coastal Ocean Forecasting and Observing System (CYCOFOS) has been producing operational flow forecasts of the northeastern Levantine Basin since 2002 and has been substantially improved in 2005. It is the first system in the Mediterranean to produce a forecast every day at the coastal scale. CYCOFOS uses a the POM (Princeton Ocean Model) flow model, and recently, within the frame of the MFSTEP project (Mediterranean Forecasting System, Toward Environmental Prediction), the flow model was upgraded to use the hourly SKIRON atmospheric forcing, and its resolution was increased from 2.5 km to 1.8 km. The CYCOFOS model is now nested in the ALERMO (Aegean Levantine Eddy Resolving Model) regional model from the University of Athens, which is nested within the MFS (Mediterranean Forecasting System) basin model. The Variational Initialization and FOrcing Platform (VIFOP) has been implemented to reduce the numerical transient processes following initialization. Moreover, a five-day forecast is repeated every day, providing more detailed and more accurate information, of particular value to coastal end users. Forecast results are posted on the web page http://www.ucy.ac.cy/cyocean. The new, daily, high-resolution forecasts agree exceptionally well with the ALERMO regional model. The agreement is better and results more reasonable when VIFOP is used. Active and slave experiments suggest that a four-week active period produces realistic results with more small-scale features. Bias with respect to the slave mode is negligible and there is no detectable bias with remote sensing images (for September, 2004). In situ observed hydrographic data from south of Cyprus are similar in many ways to the corresponding forecast fields. Plans for further model improvement include assimilation of observed temperature profiles (XBT), conductivity-temperature-depth (CTD) profiles from drifters or research cruises, and CT data from the CYCOFOS ocean observatory.
Assimilation of radar altimeter data in numerical wave models: an impact study in two different wave climate regions
G. Emmanouil, G. Galanis, G. Kallos, L. A. Breivik, H. Heiberg,M. Reistad
Annales Geophysicae (ANGEO) , 2007,
Abstract: An operational assimilation system incorporating significant wave height observations in high resolution numerical wave models is studied and evaluated. In particular, altimeter satellite data provided by the European Space Agency (ESA-ENVISAT) are assimilated in the wave model WAM which operates in two different wave climate areas: the Mediterranean Sea and the Indian Ocean. The first is a wind-sea dominated area while in the second, swell is the principal part of the sea state, a fact that seriously affects the performance of the assimilation scheme. A detailed study of the different impact is presented and the resulting forecasts are evaluated against available buoy and satellite observations. The corresponding results show a considerable improvement in wave forecasting for the Indian Ocean while in the Mediterranean Sea the assimilation impact is restricted to isolated areas.
The Mediterranean ocean forecasting system: first phase of implementation (1998–2001)
N. Pinardi,I. Allen,E. Demirov,P. De Mey
Annales Geophysicae (ANGEO) , 2003,
Abstract: The Mediterranean Forecasting system Pilot Project has concluded its activities in 2001, achieving the following goals: 1. Realization of the first high-frequency (twice a month) Voluntary Observing Ship (VOS) system for the Mediterranean Sea with XBT profiles for the upper thermocline (0–700 m) and 12 n.m. along track nominal resolution; 2. Realization of the first Mediterranean Multidisciplinary Moored Array (M3A) system for the Near-Real-Time (NRT) acquisition of physical and biochemical observations. The actual observations consists of: air-sea interaction parameters, upper thermocline (0–500 m) temperature, salinity, oxygen and currents, euphotic zone (0–100 m) chlorophyll, nutrients, Photosinthetically Available Radiation (PAR) and turbidity; 3. Analysis and NRT dissemination of high quality along track Sea Level Anomaly (SLA), Sea Surface Temperature (SST) data from satellite sensors to be assimilated into the forecasting model; 4. Assembly and implementation of a multivariate Reduced Order Optimal Interpolation scheme (ROOI) for assimilation in NRT of all available data, in particular, SLA and VOS-XBT profiles; 5. Demonstration of the practical feasibility of NRT ten day forecasts at the Mediterranean basin scale with resolution of 0.125° in latitude and longitude. The analysis or nowcast is done once a week; 6. Development and implementation of nested regional (5 km) and shelf (2–3 km) models to simulate the seasonal variability. Four regional and nine shelf models were implemented successfully, nested within the forecasting model. The implementation exercise was carried out in different region/shelf dynamical regimes and it was demonstrated that one-way nesting is practical and accurate; 7. Validation and calibration of a complex ecosystem model in data reach shelf areas, to prepare for forecasting in a future phase. The same ecosystem model is capable of reproducing the major features of the primary producers’ carbon cycle in different regions and shelf areas. The model simulations were compared with the multidisciplinary M3A buoy observations and assimilation techniques were developed for the biochemical data. This paper overviews the methodological aspects of the research done, from the NRT observing system to the forecasting/modelling components and to the extensive validation/calibration experiments carried out with regional/shelf and ecosystem models. Key words. Oceanography: general (ocean prediction; instruments and techniques) Oceanography: physical (currents)
Simulating biomass assimilation in a Mediterranean ecosystem model using SOFA: setup and identical twin experiments
G. Crispi, M. Pacciaroni,D. Viezzoli
Ocean Science (OS) & Discussions (OSD) , 2006, DOI: 10.5194/os-2-123-2006
Abstract: Assessing the potential improvement of basin scale ecosystem forecasting for the Mediterranean Sea requires biochemical data assimilation techniques. To this aim, a feasibility study of surface biomass assimilation is performed following an identical twin experiment approach. NPZD ecosystem data generator, embedded in one eighth degree general circulation model, is integrated with the reduced-order optimal interpolation System for Ocean Forecasting and Analysis. The synthetic "sea-truth" data are winter daily averages obtained from the control run (CR). The twin experiments consist in performing two runs: the free run (FR) with summer-depleted phytoplankton initial conditions and the assimilated run (AR), in which, starting from the same FR phytoplankton concentrations, weekly surface biomasses averaged from the CR data are assimilated. The FR and AR initial conditions modify the winter bloom state of the phytoplankton all over the basin and reduce the total nitrogen, i.e. the energy of the biochemical ecosystem. The results of this feasibility study shows good performance of the system in the case of phytoplankton, zooplankton, detritus and surface inorganic nitrogen. The weak results in the case of basin inorganic nitrogen and total nitrogen, the latter nonperformant at surface, are discussed. Citation: Crispi, G., Pacciaroni, M., and Viezzoli, D.: Simulating biomass assimilation in a Mediterranean ecosystem model using SOFA: setup and identical twin experiments, Ocean Sci., 2, 123-136, doi:10.5194/os-2-123-2006, 2006.
Impact of high-resolution data assimilation of GPS zenith delay on Mediterranean heavy rainfall forecasting
K. Boniface, V. Ducrocq, G. Jaubert, X. Yan, P. Brousseau, F. Masson, C. Champollion, J. Chéry,E. Doerflinger
Annales Geophysicae (ANGEO) , 2009,
Abstract: Impact of GPS (Global Positioning System) data assimilation is assessed here using a high-resolution numerical weather prediction system at 2.5 km horizontal resolution. The Zenithal Tropospheric Delay (ZTD) GPS data from mesoscale networks are assimilated with the 3DVAR AROME data assimilation scheme. Data from more than 280 stations over the model domain have been assimilated during 15-day long assimilation cycles prior each of the two studied events. The results of these assimilation cycles show that the assimilation of GPS ZTD with the AROME system performs well in producing analyses closer to the ZTD observations in average. Then the impacts of assimilating GPS data on the precipitation forecast have been evaluated. For the first case, only the AROME runs starting a few hours prior the triggering of the convective system are able to simulate the convective precipitation. The assimilation of GPS ZTD observations improves the simulation of the spatial extent of the precipitation, but slightly underestimates the heaviest precipitation in that case compared with the experiment without GPS. The accuracy of the precipitation forecast for the second case is much better. The analyses from the control assimilation cycle provide already a good description of the atmosphere state that cannot be further improved by the assimilation of GPS observations. Only for the latest day (22 November 2007), significant differences have been found between the two parallel cycles. In that case, the assimilation of GPS ZTD allows to improve the first 6 to 12 h of the precipitation forecast.
Argo Global Ocean Data Assimilation and Its Applications in Short-Term Climate Prediction and Oceanic Analysis
Argo大洋观测资料的同化及其在短期气候预测和海洋分析中的应用

ZHANG Renhe,ZHU Jiang,XU Jianping,LIU Yimin,Li Qingquan,NIU Tao,
张人禾
,朱江,许建平,刘益民,李清泉,牛涛

大气科学 , 2013,
Abstract: The implementation of the international Array for Real-time Geostrophic Oceanography (Argo) Project facilitates unprecedented global ocean observations of sea-water temperature and salinity from the sea surface to a depth of 2000 m. Application of these new oceanic data in atmospheric and oceanic research and operation is essential for understanding the atmospheric and oceanic variability and increasing the accuracy of climate prediction and oceanic monitoring and analysis. The global ocean data assimilation systems are set up by developing a nonlinear temperature- salinity coordinated assimilation scheme and adjusting the temperature and salinity on the basis of altimetry data, which enhances the monitoring and analyzing capability for the global ocean. The global ocean data assimilation systems are integrated with coupled atmosphere-ocean models, which increases the forecast skills for short-term climate prediction. Argo data are applied for improving physical parameterization schemes in oceanic models, and the model capability of describing the real oceans and forecasting El Ni o/Southern Oscillation is increased. A novel method has been developed for estimating surface and mid-layer ocean currents on the basis of the trajectories of Argo float drifting, which improves the accuracy of estimation of global surface and mid-layer ocean currents and makes up the insufficiency in observed ocean currents.
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