scholarly journals The impact of a new high-resolution ocean model on the Met Office North-West European Shelf forecasting system

Ocean Science ◽  
2019 ◽  
Vol 15 (4) ◽  
pp. 1133-1158 ◽  
Author(s):  
Marina Tonani ◽  
Peter Sykes ◽  
Robert R. King ◽  
Niall McConnell ◽  
Anne-Christine Péquignet ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Superior Performance ◽  
North West ◽  
Resolution System ◽  
European Shelf ◽  
Forecasting System ◽  
The Impact ◽  
New System ◽  
West European

Abstract. The North-West European Shelf ocean forecasting system has been providing oceanographic products for the European continental shelf seas for more than 15 years. In that time, several different configurations have been implemented, updating the model and the data assimilation components. The latest configuration to be put in operation, an eddy-resolving model at 1.5 km (AMM15), replaces the 7 km model (AMM7) that has been used for 8 years to deliver forecast products to the Copernicus Marine Environment Monitoring Service and its precursor projects. This has improved the ability to resolve the mesoscale variability in this area. An overview of this new system and its initial validation is provided in this paper, highlighting the differences with the previous version. Validation of the model with data assimilation is based on the results of 2 years (2016–2017) of trial experiments run with the low- and high-resolution systems in their operational configuration. The 1.5 km system has been validated against observations and the low-resolution system, trying to understand the impact of the high resolution on the quality of the products delivered to the users. Although the number of observations is a limiting factor, especially for the assessment of model variables like currents and salinity, the new system has been proven to be an improvement in resolving fine-scale structures and variability and provides more accurate information on the major physical variables, like temperature, salinity, and horizontal currents. AMM15 improvements are evident from the validation against high-resolution observations, available in some selected areas of the model domain. However, validation at the basin scale and using daily means penalized the high-resolution system and does not reflect its superior performance. This increment in resolution also improves the capabilities to provide marine information closer to the coast even if the coastal processes are not fully resolved by the model.

scholarly journals The impact of a new high-resolution ocean model on the Met Office North-West European Shelf forecasting system

2019 ◽  
Author(s):  
Marina Tonani ◽  
Peter Sykes ◽  
Robert R. King ◽  
Niall McConnell ◽  
Anne-Christine Pequignet ◽  
...  
Keyword(s):  
High Resolution ◽  
Superior Performance ◽  
North West ◽  
Resolution System ◽  
Basin Scale ◽  
European Shelf ◽  
Forecasting System ◽  
The Impact ◽  
New System ◽  
West European

Abstract. The North-West European shelf ocean forecasting system has been providing oceanographic products for the European continental shelf seas for more than fifteen years. In that time several different configurations have been implemented, updating the model and the data assimilation components. The latest configuration to be put in operations, an eddy resolving model at 1.5 km (AMM15), replaces the 7 km model (AMM7) that has been used for a number of years. This has improved the ability to resolve the mesoscale variability in this area. An overview of this new system and its initial validation is provided in this paper, highlighting the differences with the previous version. Validation of the model is based on the results of two years (2016–2017) trial experiments run with the low and high resolution systems in their operational configuration. The 1.5 km system has been validated against observations and the low resolution system, trying to understand the impact of the high resolution on the quality of the products delivered to the users. Although the number of observations is a limiting factor, especially for the assessment of model variables like currents and salinity, the new system has been proven to be an improvement in resolving fine scale structures and variability and provides more accurate information on the major physical variables, like temperature, salinity and horizontal currents. AMM15 improvements are evident from the validation against high-resolution observations, available in some selected areas of the model domain. However, validation at the basin scale and using daily means penalised the high-resolution system and does not reflect its superior performance. This increment in resolution also improves the capabilities to provide marine information closer to the coast even if the coastal processes are not fully resolved by the model.

scholarly journals Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System Part 1: Methods

2021 ◽  
Vol 8 ◽  
Author(s):  
Mounir Benkiran ◽  
Giovanni Ruggiero ◽  
Eric Greiner ◽  
Pierre-Yves Le Traon ◽  
Elisabeth Rémy ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Companion Paper ◽  
Ocean Model ◽  
Data Assimilation Scheme ◽  
High Resolution Analysis ◽  
Resolution Analysis ◽  
Forecasting System ◽  
The Impact ◽  
Assimilation Scheme

The future Surface Water Ocean Topography (SWOT) mission due to be launched in 2022 will extend the capability of existing nadir altimeters to enable two-dimensional mapping at a much higher effective resolution. A significant challenge will be to assimilate this kind of data in high-resolution models. In this context, Observing System Simulation Experiments (OSSEs) have been performed to assess the impact of SWOT on the Mercator Ocean and Copernicus Marine Environment Monitoring Service (CMEMS) global, high-resolution analysis and forecasting system. This paper focusses on the design of these OSSEs, in terms of simulated observations and assimilation systems (ocean model and data assimilation schemes). The main results are discussed in a companion paper. Two main updates of the current Mercator Ocean data assimilation scheme have been made to improve the assimilation of information from SWOT data. The first one is related to a different parametrisation of the model error covariance, and the second to the use of a four-dimensional (4D) version of the data assimilation scheme. These improvements are described in detail and their contribution is quantified. The Nature Run (NR) used to represent the “truth ocean” is validated by comparing it with altimeter observations, and is then used to simulate pseudo-observations required for the OSSEs. Finally, the design of the OSSEs is evaluated by ensuring that the differences between the assimilation system and the NR are statistically consistent with the misfits between real ocean observations and real-time operational systems.

scholarly journals Can wave coupling improve operational regional ocean forecasts for the north-west European Shelf?

Ocean Science ◽  
2019 ◽  
Vol 15 (3) ◽  
pp. 669-690 ◽  
Author(s):  
Huw W. Lewis ◽  
Juan Manuel Castillo Sanchez ◽  
John Siddorn ◽  
Robert R. King ◽  
Marina Tonani ◽  
...  
Keyword(s):  
Sea Surface ◽  
Ocean Wave ◽  
Prediction System ◽  
Wave Coupling ◽  
North West ◽  
The North ◽  
European Shelf ◽  
Ocean Prediction ◽  
The Impact ◽  
West European

Abstract. Operational ocean forecasts are typically produced by modelling systems run using a forced mode approach. The evolution of the ocean state is not directly influenced by surface waves, and the ocean dynamics are driven by an external source of meteorological data which are independent of the ocean state. Model coupling provides one approach to increase the extent to which ocean forecast systems can represent the interactions and feedbacks between ocean, waves, and the atmosphere seen in nature. This paper demonstrates the impact of improving how the effect of waves on the momentum exchange across the ocean–atmosphere interface is represented through ocean–wave coupling on the performance of an operational regional ocean prediction system. This study focuses on the eddy-resolving (1.5 km resolution) Atlantic Margin Model (AMM15) ocean model configuration for the north-west European Shelf (NWS) region. A series of 2-year duration forecast trials of the Copernicus Marine Environment Monitoring Service (CMEMS) north-west European Shelf regional ocean prediction system are analysed. The impact of including ocean–wave feedbacks via dynamic coupling on the simulated ocean is discussed. The main interactions included are the modification of surface stress by wave growth and dissipation, Stokes–Coriolis forcing, and wave-height-dependent ocean surface roughness. Given the relevance to operational forecasting, trials with and without ocean data assimilation are considered. Summary forecast metrics demonstrate that the ocean–wave coupled system is a viable evolution for future operational implementation. When results are considered in more depth, wave coupling was found to result in an annual cycle of relatively warmer winter and cooler summer sea surface temperatures for seasonally stratified regions of the NWS. This is driven by enhanced mixing due to waves, and a deepening of the ocean mixed layer during summer. The impact of wave coupling is shown to be reduced within the mixed layer with assimilation of ocean observations. Evaluation of salinity and ocean currents against profile measurements in the German Bight demonstrates improved simulation with wave coupling relative to control simulations. Further, evidence is provided of improvement to simulation of extremes of sea surface height anomalies relative to coastal tide gauges.

scholarly journals Phytoplankton Distribution in Relation to Environmental Drivers on the North West European Shelf Sea

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164482 ◽  
Author(s):  
Beatrix Siemering ◽  
Eileen Bresnan ◽  
Stuart C. Painter ◽  
Chris J. Daniels ◽  
Mark Inall ◽  
...  
Keyword(s):  
Environmental Drivers ◽  
North West ◽  
The North ◽  
Phytoplankton Distribution ◽  
European Shelf ◽  
Shelf Sea ◽  
West European

scholarly journals Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model

2014 ◽  
Vol 21 (5) ◽  
pp. 1027-1041 ◽  
Author(s):  
K. Apodaca ◽  
M. Zupanski ◽  
M. DeMaria ◽  
J. A. Knaff ◽  
L. D. Grasso
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
New Information ◽  
Forecasting System ◽  
Maximum Likelihood Ensemble Filter ◽  
The Impact

Abstract. Lightning measurements from the Geostationary Lightning Mapper (GLM) that will be aboard the Geostationary Operational Environmental Satellite – R Series will bring new information that can have the potential for improving the initialization of numerical weather prediction models by assisting in the detection of clouds and convection through data assimilation. In this study we focus on investigating the utility of lightning observations in mesoscale and regional applications suitable for current operational environments, in which convection cannot be explicitly resolved. Therefore, we examine the impact of lightning observations on storm environment. Preliminary steps in developing a lightning data assimilation capability suitable for mesoscale modeling are presented in this paper. World Wide Lightning Location Network (WWLLN) data was utilized as a proxy for GLM measurements and was assimilated with the Maximum Likelihood Ensemble Filter, interfaced with the Nonhydrostatic Mesoscale Model core of the Weather Research and Forecasting system (WRF-NMM). In order to test this methodology, regional data assimilation experiments were conducted. Results indicate that lightning data assimilation had a positive impact on the following: information content, influencing several dynamical variables in the model (e.g., moisture, temperature, and winds), and improving initial conditions during several data assimilation cycles. However, the 6 h forecast after the assimilation did not show a clear improvement in terms of root mean square (RMS) errors.

scholarly journals Impact of Sea Surface Temperature Forcing on Weeks 3 and 4 Forecast Skill in the NCEP Global Ensemble Forecasting System

2017 ◽  
Vol 32 (6) ◽  
pp. 2159-2174 ◽  
Author(s):  
Yuejian Zhu ◽  
Xiaqiong Zhou ◽  
Malaquias Peña ◽  
Wei Li ◽  
Christopher Melhauser ◽  
...  
Keyword(s):  
North America ◽  
Forecast Skill ◽  
Ensemble Forecasting ◽  
Superior Performance ◽  
Seasonal Forecasts ◽  
Skill Scores ◽  
Short Period ◽  
Forecasting System ◽  
Sst Forcing ◽  
The Impact

Abstract The Global Ensemble Forecasting System (GEFS) is being extended from 16 to 35 days to cover the subseasonal period, bridging weather and seasonal forecasts. In this study, the impact of SST forcing on the extended-range land-only global 2-m temperature, continental United States (CONUS) accumulated precipitation, and MJO skill are explored with version 11 of the GEFS (GEFSv11) under various SST forcing configurations. The configurations consist of 1) the operational GEFS 90-day e-folding time of the observed real-time global SST (RTG-SST) anomaly relaxed to climatology, 2) an optimal AMIP configuration using the observed daily RTG-SST analysis, 3) a two-tier approach using the CFSv2-predicted daily SST, and 4) a two-tier approach using bias-corrected CFSv2-predicted SST, updated every 24 h. The experimental period covers the fall of 2013 and the winter of 2013/14. The results indicate that there are small differences in the ranked probability skill scores (RPSSs) between the various SST forcing experiments. The improvements in forecast skill of the Northern Hemisphere 2-m temperature and precipitation for weeks 3 and 4 are marginal, especially for North America. The bias-corrected CFSv2-predicted SST experiment generally delivers superior performance with statistically significant improvement in spatially and temporally aggregated 2-m temperature RPSSs over North America. Improved representation of the SST forcing (AMIP) increased the forecast skill for MJO indices up through week 2, but there is no significant improvement of the MJO forecast skill for weeks 3 and 4. These results are obtained over a short period with weak MJO activity and are also subject to internal model weaknesses in representing the MJO. Additional studies covering longer periods with upgraded model physics are warranted.

A 20-year reforecast study combining high-resolution hydrological modelling, ensemble forecasting and data assimilation for the 12 largest tributaries of the Rhine

2020 ◽  
Author(s):  
Bart van Osnabrugge ◽  
Maarten Smoorenburg ◽  
Remko Uijlenhoet ◽  
Albrecht Weerts
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Hydrological Model ◽  
Forecast Skill ◽  
Ensemble Forecasting ◽  
Added Value ◽  
River Rhine ◽  
Medium Term ◽  
Initial State ◽  
The Impact

<p>There is an ongoing trend in hydrological forecasting towards both spatially distributed (gridded) models, ensemble forecasting and data assimilation techniques to improve forecasts’ initial states. While in the last years those different aspects have been investigated separately, there are only few studies where the three techniques are combined: ensemble forecasts with state updating of a gridded hydrological model. Additionally, the studies that have addressed this combination of techniques either focus on a small area, a short study period, or both. We here aim to fill this knowledge gap with a 20-year data assimilation and ensemble reforecast experiment with a high resolution gridded hydrological model (wflow_hbv, 1200x1200m) of the full Rhine basin (160 000 km<sup>2</sup>). To put the impact of state updating in an operational forecasting context, the data assimilation results were compared with AR post-processing as used by the Dutch Forecasting Centre (WMCN).</p><p>This data assimilation and reforecast experiment was conducted for the twelve main tributaries of the river Rhine. The effect on forecast skill of state updating with the Asynchronous Ensemble Kalman Filter (AEnKF) and AR error correction are compared for medium-term (15-day) forecasts over a period of 20 years (1996 to 2016). State updating improved the initial state for all subbasins and resulted in lasting skill score increase. AR also improved the forecast skill, but the forecast skill with AR did not always converge towards the uncorrected model skill, and instead can deteriorate for longer lead times. AR correction outperformed the AEnKF state updating for the first two days, after which state updating became more effective and outperformed AR. We conclude that state updating has more potential for medium-term hydrological forecasts than the operational AR procedure.</p><p>Further research is underway to investigate the importance, or added value, of long-term reforecasts as opposed to studies covering a short time span which are often more feasible and therefore more often found in literature.</p>

Sign in / Sign up

Export Citation Format

Share Document