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 The Impact of Data Assimilation Length Scales on Analysis and Prediction of Convective Storms

2014 ◽  
Vol 142 (10) ◽  
pp. 3781-3808 ◽  
Author(s):  
Heiner Lange ◽  
George C. Craig
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Length Scales ◽  
Localization Radius ◽  
Filter Convergence ◽  
Analysis Scheme ◽  
High Resolution Analysis ◽  
Resolution Analysis ◽  
Set Up ◽  
The Impact

Abstract An idealized convective test bed for the local ensemble transform Kalman filter (LETKF) is set up to perform storm-scale data assimilation of simulated Doppler radar observations. Convective systems with lifetimes exceeding 6 h are triggered in a doubly periodic domain. Perfect-model experiments are used to investigate the limited predictability in precipitation forecasts by comparing analysis schemes that resolve different length scales. Starting from a high-resolution reference scheme with 8-km covariance localization and observations with 2-km resolution on a 5-min cycle, an experimental hierarchy is set up by successively choosing a larger covariance localization radius of 32 km, observations that are horizontally averaged by a factor of 4, a coarser resolution in the calculation of the analysis weights, and a cycling interval of 20 min. After 3 h of assimilation, the high-resolution analysis scheme is clearly superior to the configurations with coarser scales in terms of RMS error and field-oriented measures. The difference is associated with the observation resolution and a larger localization radius required for filter convergence with coarse observations. The high-resolution analysis leads to better forecasts for the first hour, but after 3 hours, the forecast quality of the schemes is indistinguishable. The more rapid error growth in forecasts from the high-resolution analysis appears to be associated with a limited predictability of the small scales, but also with gravity wave noise and spurious convective cells. The latter suggests that the field is in some sense less balanced, or less consistent with the model dynamics, than in the coarser-resolution analysis.

scholarly journals Assessing the Impact of the Assimilation of SWOT Observations in a Global High-Resolution Analysis and Forecasting System – Part 2: Results

2021 ◽  
Vol 8 ◽  
Author(s):  
Babette C. Tchonang ◽  
Mounir Benkiran ◽  
Pierre-Yves Le Traon ◽  
Simon Jan van Gennip ◽  
Jean Michel Lellouche ◽  
...  
Keyword(s):  
High Resolution ◽  
Positive Impact ◽  
Spatial Scales ◽  
Forecast Error ◽  
Wave Number ◽  
Altimeter Data ◽  
High Resolution Analysis ◽  
Resolution Analysis ◽  
Forecasting System ◽  
The Impact

A first attempt was made to quantify the impact of the assimilation of Surface Water Ocean Topography (SWOT) swath altimeter data in a global 1/12° high resolution analysis and forecasting system through a series of Observing System Simulation Experiments (OSSEs). The OSSE framework (Nature Run and Free Run) and data assimilation scheme have been described in detail in a companion article (Benkiran et al., 2021). The impact of assimilating data from SWOT and three nadir altimeters was quantified by estimating analysis and forecast error variances for sea surface height (SSH), temperature, salinity, zonal, and meridional velocities. Wave-number spectra and coherence analyses of SSH errors were also computed. SWOT data will significantly improve the quality of ocean analyses and forecasts. Adding SWOT observations to those of three nadir altimeters globally reduces the variance of SSH and surface velocities in analyses and forecasts by about 30 and 20%, respectively. Improvements are greater in high-latitude regions where space/time coverage of SWOT is much denser. The combination of SWOT data with data from three nadir altimeters provides a better resolution of wavelengths between 50 and 200 km with a more than 40% improvement outside tropical regions with respect to data from three nadir altimeters alone. The study has also highlighted that the impact of using SWOT data is likely to be very different depending on geographical areas. Constraining smaller spatial scales (wavelengths below 100 km) remains challenging as they are also associated with small time scales. Although this is only a first step, the study has demonstrated that SWOT data could be readily assimilated in a global high-resolution analysis and forecasting system with a positive impact at all latitudes and outstanding performances.

The Impact of MOPS Moisture Data in the U.K. Meteorological Office Mesoscale Data Assimilation Scheme

1996 ◽  
Vol 124 (8) ◽  
pp. 1746-1766 ◽  
Author(s):  
Bruce Macpherson ◽  
Bruce J. Wright ◽  
William H. Hand ◽  
Adam J. Maycock
Keyword(s):  
Data Assimilation ◽  
Data Assimilation Scheme ◽  
The Impact ◽  
Assimilation Scheme

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 improvements to the regional South China Sea Operational Oceanography Forecasting System

2020 ◽  
Author(s):  
Xueming Zhu ◽  
Ziqing Zu ◽  
Shihe Ren ◽  
Yunfei Zhang ◽  
Miaoyin Zhang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
South China Sea ◽  
South China ◽  
Sea Surface ◽  
Global Ocean ◽  
China Sea ◽  
Data Assimilation Scheme ◽  
Operational Oceanography ◽  
Forecasting System ◽  
Assimilation Scheme

Abstract. South China Sea Operational Oceanography Forecasting System (SCSOFS) had been built up and operated in National Marine Environmental Forecasting Center of China to provide daily updated hydrodynamic forecasting in SCS for the future 5 days since 2013. This paper presents comprehensive updates had been conducted to the configurations of the physical model and data assimilation scheme in order to improve SCSOFS forecasting skills in recent years. It highlights three of the most sensitive updates, sea surface atmospheric forcing method, tracers advection discrete scheme, and modification of data assimilation scheme. Scientific inter-comparison and accuracy assessment among five versions during the whole upgrading processes are performed by employing Global Ocean Data Assimilation Experiment OceanView Inter-comparison and Validation Task Team Class4 metrics. The results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version SCSOFSv1. Domain averaged monthly mean root mean square errors decrease from 1.21 °C to 0.52 °C for sea surface temperature, from 21.6 cm to 8.5 cm for sea level anomaly, respectively.

scholarly journals FYRE Climate: a high-resolution reanalysis of daily precipitation and temperature in France from 1871 to 2012

2021 ◽  
Vol 17 (5) ◽  
pp. 1857-1879
Author(s):  
Alexandre Devers ◽  
Jean-Philippe Vidal ◽  
Claire Lauvernet ◽  
Olivier Vannier
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Extreme Events ◽  
High Temporal Resolution ◽  
Temperature And Precipitation ◽  
Data Assimilation Scheme ◽  
Assimilation Scheme ◽  
Surface Observations ◽  
Better Than ◽  
Local Extreme

Abstract. Surface observations are usually too few and far between to properly assess multidecadal variations at the local scale and characterize historical local extreme events at the same time. A data assimilation scheme has been recently presented to assimilate daily observations of temperature and precipitation into downscaled reconstructions from a global extended reanalysis through an Ensemble Kalman fitting approach and to derive high-resolution fields. Recent studies also showed that assimilating observations at high temporal resolution does not guarantee correct multidecadal variations. The current paper thus proposes (1) to apply the data assimilation scheme over France and over the 1871–2012 period based on the SCOPE Climate reconstructions background dataset and all available daily historical surface observations of temperature and precipitation, (2) to develop an assimilation scheme at the yearly timescale and to apply it over the same period and lastly, (3) to derive the FYRE Climate reanalysis, a 25-member ensemble hybrid dataset resulting from the daily and yearly assimilation schemes, spanning the whole 1871–2012 period at a daily and 8 km resolution over France. Assimilating daily observations only allows reconstructing accurately daily characteristics, but fails in reproducing robust multidecadal variations when compared to independent datasets. Combining the daily and yearly assimilation schemes, FYRE Climate clearly performs better than the SCOPE Climate background in terms of bias, error, and correlation, but also better than the Safran reference surface reanalysis over France available from 1958 onward only. FYRE Climate also succeeds in reconstructing both local extreme events and multidecadal variability. It is freely available at https://doi.org/10.5281/zenodo.4005573 (precipitation, Devers et al., 2020b) and https://doi.org/10.5281/zenodo.4006472 (temperature, Devers et al., 2020c).

scholarly journals The improvements to the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv1)

2021 ◽  
Author(s):  
Xueming Zhu ◽  
Ziqing Zu ◽  
Shihe Ren ◽  
Miaoyin Zhang ◽  
Yunfei Zhang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
South China Sea ◽  
South China ◽  
Sea Surface ◽  
China Sea ◽  
Data Assimilation Scheme ◽  
Operational Oceanography ◽  
Forecasting System ◽  
Mean Square Errors ◽  
Assimilation Scheme

Abstract. South China Sea Operational Oceanography Forecasting System (SCSOFS) had been constructed and operated in National Marine Environmental Forecasting Center of China to provide daily updated hydrodynamic forecasting in SCS for the future 5 days since 2013. This paper presents recent comprehensive updates of the configurations of the physical model and data assimilation scheme in order to improve SCSOFS forecasting skills. It highlights three of the most sensitive updates, including sea surface atmospheric forcing method, tracers advection discrete scheme, and modification of data assimilation scheme. Inter-comparison and accuracy assessment among five versions during the whole upgrading processes are performed by employing OceanPredict Inter-comparison and Validation Task Team Class4 metrics. The results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version known as SCSOFSv1. Domain averaged monthly mean root mean square errors decrease from 1.21 °C to 0.52 °C for sea surface temperature, from 21.6 cm to 8.5 cm for sea level anomaly, respectively.

Very High Resolution Analysis of the Dynamics of a Coronal Plasmoid

1994 ◽  
Vol 144 ◽  
pp. 593-596
Author(s):  
O. Bouchard ◽  
S. Koutchmy ◽  
L. November ◽  
J.-C. Vial ◽  
J. B. Zirker
Keyword(s):  
High Resolution ◽  
Solar Eclipse ◽  
Total Solar Eclipse ◽  
Field Of View ◽  
Small Field ◽  
High Resolution Analysis ◽  
Ccd Observations ◽  
Resolution Analysis ◽  
Very High ◽  
Small Field Of View

AbstractWe present the results of the analysis of a movie taken over a small field of view in the intermediate corona at a spatial resolution of 0.5“, a temporal resolution of 1 s and a spectral passband of 7 nm. These CCD observations were made at the prime focus of the 3.6 m aperture CFHT telescope during the 1991 total solar eclipse.

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