scholarly journals Coastal Ocean Forecasting Science supported by GODAE OceanView Coastal Oceans and Shelf Seas Task Team (COSS-TT)—Part II

2021 ◽  
Author(s):  
Mauro Cirano ◽  
Guillaume Charria ◽  
Pierre De Mey-Frémaux ◽  
Vassiliki H. Kourafalou ◽  
Emil Stanev
Keyword(s):  
Coastal Ocean ◽  
Coastal Oceans ◽  
Shelf Seas ◽  
Task Team ◽  
Ocean Forecasting

scholarly journals Ocean forecasting for the German Bight: from regional to coastal scales

Ocean Science ◽  
2016 ◽  
Vol 12 (5) ◽  
pp. 1105-1136 ◽  
Author(s):  
Emil V. Stanev ◽  
Johannes Schulz-Stellenfleth ◽  
Joanna Staneva ◽  
Sebastian Grayek ◽  
Sebastian Grashorn ◽  
...  
Keyword(s):  
German Bight ◽  
Unstructured Grid ◽  
Wind Waves ◽  
Radar Data ◽  
Coastal Ocean ◽  
Hf Radar ◽  
Regional Models ◽  
Arctic Seas ◽  
The North ◽  
Ocean Forecasting

Abstract. This paper describes recent developments based on advances in coastal ocean forecasting in the fields of numerical modeling, data assimilation, and observational array design, exemplified by the Coastal Observing System for the North and Arctic Seas (COSYNA). The region of interest is the North and Baltic seas, and most of the coastal examples are for the German Bight. Several pre-operational applications are presented to demonstrate the outcome of using the best available science in coastal ocean predictions. The applications address the nonlinear behavior of the coastal ocean, which for the studied region is manifested by the tidal distortion and generation of shallow-water tides. Led by the motivation to maximize the benefits of the observations, this study focuses on the integration of observations and modeling using advanced statistical methods. Coastal and regional ocean forecasting systems do not operate in isolation but are linked, either weakly by using forcing data or interactively using two-way nesting or unstructured-grid models. Therefore, the problems of downscaling and upscaling are addressed, along with a discussion of the potential influence of the information from coastal observatories or coastal forecasting systems on the regional models. One example of coupling coarse-resolution regional models with a fine-resolution model interface in the area of straits connecting the North and Baltic seas using a two-way nesting method is presented. Illustrations from the assimilation of remote sensing, in situ and high-frequency (HF) radar data, the prediction of wind waves and storm surges, and possible applications to search and rescue operations are also presented. Concepts for seamless approaches to link coastal and regional forecasting systems are exemplified by the application of an unstructured-grid model for the Ems Estuary.

Coastal ocean forecasting systems in Europe

Eos ◽  
1993 ◽  
Vol 74 (49) ◽  
pp. 577
Author(s):  
John Dugan
Keyword(s):  
Coastal Ocean ◽  
Ocean Forecasting

scholarly journals Seasonality of CO<sub>2</sub> in coastal oceans altered by increasing anthropogenic nutrient delivery from large rivers: evidence from the Changjiang-East China Sea system

2012 ◽  
Vol 9 (12) ◽  
pp. 18993-19017 ◽  
Author(s):  
W.-C. Chou ◽  
G.-C. Gong ◽  
W.-J. Cai
Keyword(s):  
Surface Waters ◽  
Coastal Ocean ◽  
Changjiang Estuary ◽  
Inner Shelf ◽  
The Changjiang Estuary ◽  
Nutrient Delivery ◽  
Coastal Oceans ◽  
High Co2 ◽  
Bottom Waters ◽  
Autumn And Winter

Abstract. Model studies suggested that human-induced increase in nutrient load may have stimulated primary production and thus has enhanced the CO2 uptake capacity in the coastal ocean. In this study, we investigated the seasonal variations of the surface water's partial pressure of CO2 (pCO2sw) in the highly human-impacted Changjiang-East China Sea system between 2008 and 2011. The seasonality of pCO2sw has large spatial variations, with the largest extreme of 170 ± 75 μatm on the inner shelf near the Changjiang Estuary (from 271 ± 55 μatm in summer to 441 ± 51 μatm in autumn) and the weakest extreme of 53 ± 20 μatm on the outer shelf (from 328 ± 9 μatm in winter to 381 ± 18 μatm in summer). During the summer period, stronger stratification and biological production driven by the eutrophic Changjiang plume results in a very low CO2 in surface waters and a very high CO2 in bottom waters on the inner shelf, with the latter returning high CO2 to the surface water during the mixed period. Interestingly, a comparison with historical data shows that the average pCO2sw on the inner shelf near the Changjiang Estuary has decreased notably during summer, but it has increased during autumn and winter from the 1990s to the 2000s. We suggest that this decadal change is associated with recently increased eutrophication. This would increase both the photosynthetic removal of CO2 in surface waters and the respiratory release of CO2 in bottom waters during summertime, thereby returning more CO2 to the surface during the subsequent mixing seasons and/or episodic extreme weather events (e.g. typhoons). Our finding demonstrates that increasing anthropogenic nutrient delivery from a large river may enhance the sequestration capacity of CO2 in summer but may reduce it in autumn and winter. Consequently, the coastal ocean may not necessarily take up more atmospheric CO2 in response to increasing eutrophication, and the net effect largely depends on the relative time scale of air-sea gas exchange and offshore transport of the shelf water. Finally, the case we reported for the Changjiang system may have general ramifications for other eutrophic coastal oceans.

scholarly journals Coastal Ocean Forecasting: system integration and evaluation

2015 ◽  
Vol 8 (sup1) ◽  
pp. s127-s146 ◽  
Author(s):  
V.H. Kourafalou ◽  
P. De Mey ◽  
M. Le Hénaff ◽  
G. Charria ◽  
C.A. Edwards ◽  
...  
Keyword(s):  
System Integration ◽  
Coastal Ocean ◽  
Forecasting System ◽  
Ocean Forecasting

scholarly journals Coastal ocean forecasting in Spanish ports: the SAMOA operational service

2019 ◽  
Vol 13 (1) ◽  
pp. 37-54 ◽  
Author(s):  
Marcos G. Sotillo ◽  
P. Cerralbo ◽  
P. Lorente ◽  
M. Grifoll ◽  
M. Espino ◽  
...  
Keyword(s):  
Coastal Ocean ◽  
Ocean Forecasting ◽  
Operational Service

scholarly journals Coastal Ocean Forecasting: science foundation and user benefits

2015 ◽  
Vol 8 (sup1) ◽  
pp. s147-s167 ◽  
Author(s):  
V.H. Kourafalou ◽  
P. De Mey ◽  
J. Staneva ◽  
N. Ayoub ◽  
A. Barth ◽  
...  
Keyword(s):  
Coastal Ocean ◽  
Ocean Forecasting

Development of an Ocean Forecasting System off the West Coast of the United States: Sea Level Applications

2007 ◽  
Vol 41 (1) ◽  
pp. 84-93
Author(s):  
Yi Chao ◽  
Paul M. DiGiacomo
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
West Coast ◽  
Information Management System ◽  
Coastal Ocean ◽  
Model Management ◽  
Global Ocean ◽  
Forecasting System ◽  
Ocean Forecasting ◽  
Ocean Observing

In the context of continuing development and implementation of global and regional ocean observing systems, we describe here the need and essential ingredients for a coastal ocean forecasting system focused on sea level and associated inundation issues and applications. Such a system must consist of the following key components: 1) satellite and in situ observations, 2) atmospheric forcing, 3) ocean circulation and tide modeling, 4) data assimilation for initialization, 5) forecast error estimation, and 6) data and model management. We describe these components, their continuing development and integrated implementation and application as part of a prototype coastal ocean forecast system for the U.S. West Coast. The multiscale nested modeling approach utilized here has demonstrated that sea level simulation can be improved by increasing the spatial resolution of observations. This and other regional ocean forecast systems are complementary and necessary elements of the emerging Global Ocean Observing System (GOOS) needed to predict changes in sea level. Building on the increasing maturity of ocean observing and forecasting capabilities, there are a number of significant challenges that require immediate attention, planning and development. These include: 1) further development of models, data assimilation algorithms and information management system, 2) adaptive sampling to reduce uncertainty in ocean forecasting, 3) Observing System Simulation Experiments (OSSE) to optimize observing system design, 4) bridging the land-sea boundary, and 5) moving from measurements to information in support of management and decision-making.

scholarly journals Ocean Forecasting: From Regional to Coastal Scales

2016 ◽  
Author(s):  
Emil V. Stanev ◽  
Johannes Schulz-Stellenfleth ◽  
Joanna Staneva ◽  
Sebastian Grayek ◽  
Sebastian Grashorn ◽  
...  
Keyword(s):  
Unstructured Grid ◽  
Wind Waves ◽  
Storm Surges ◽  
Radar Data ◽  
Coastal Ocean ◽  
Hf Radar ◽  
Regional Models ◽  
Arctic Seas ◽  
The North ◽  
Ocean Forecasting

Abstract. In the past years, the Helmholtz Zentrum Geesthacht put in place the Coastal Observing System for the North and Arctic Seas (COSYNA) in the frame of which different aspects of forecasting the marine environment have been developed. This paper describes these developments, which are based on recent advances in coastal ocean forecasting in the field of numerical modelling, data assimilation and observational array design. The region of interest is the North and Baltic Sea; most of the coastal examples discussed in the paper are for the German Bight. Several pre-operational applications are presented exemplifying the outcome of using the best available science in coastal ocean predictions. They help to identify new challenges; most of them are associated with resolving the non-linear behavior of coastal ocean, which for the studied region, is manifested by the tidal distortion and generation of shallow-water tides. Led by the motivation to maximize the benefit from observations, the authors focus on the integration of observations and modelling by using advanced statistical methods. The coastal and regional ocean forecasting systems do not run in isolation, but are linked, either weakly by just using forcing data, or interactively by using two-way nesting or unstructured-grid models. Therefore the problem of downscaling and upscaling, which currently attracts much attention, is also addressed. One example shown is the coupling of the coarse-resolution regional models by using a two-way nesting method with fine resolution in the area of connecting straits. The major part of the paper presents illustrations from assimilation of remote sensing, in situ and HF radar data, prediction of wind waves and storm surges, as well as possible applications to search and rescue operations, and modelling support for assessing the environmental impact of wind parks. Concepts for seamless approaches to link coastal and regional forecasting systems are also presented and the two examples given illustrate (1) an application of unstructured-grid model for the Ems Estuary, and (2) the potential influence of the information from coastal observatories or coastal forecasting systems on the regional models.

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