Data Assimilation in a Simple Tropical Ocean Model with Wind Stress Errors

1994 ◽  
Vol 24 (10) ◽  
pp. 2111-2128 ◽  
Author(s):  
Zheng Hao ◽  
Michael Ghil
Keyword(s):  
Data Assimilation ◽  
Wind Stress ◽  
Ocean Model ◽  
Tropical Ocean

scholarly journals Adjusting the Wind Stress Drag Coefficient in Storm Surge Forecasting Using an Adjoint Technique

2013 ◽  
Vol 30 (3) ◽  
pp. 590-608 ◽  
Author(s):  
Shiqiu Peng ◽  
Yineng Li ◽  
Lian Xie
Keyword(s):  
Data Assimilation ◽  
Drag Coefficient ◽  
Storm Surge ◽  
Wind Stress ◽  
Weather Prediction ◽  
Ocean Model ◽  
Error Sources ◽  
Empirical Parameter ◽  
Forecasting Errors ◽  
Storm Surge Forecasting

Abstract A three-dimensional ocean model and its adjoint model are used to adjust the drag coefficient in the calculation of wind stress for storm surge forecasting. A number of identical twin experiments (ITEs) with different error sources imposed are designed and performed. The results indicate that when the errors come from the wind speed, the drag coefficient is adjusted to an “optimal value” to compensate for the wind errors, resulting in significant improvements of the specific storm surge forecasting. In practice, the “true” drag coefficient is unknown and the wind field, which is usually calculated by an empirical parameter model or a numerical weather prediction model, may contain large errors. In addition, forecasting errors may also come from imperfect model physics and numerics, such as insufficient resolution and inaccurate physical parameterizations. The results demonstrate that storm surge forecasting errors can be reduced through data assimilation by adjusting the drag coefficient regardless of the error sources. Therefore, although data assimilation may not fix model imperfection, it is effective in improving storm surge forecasting by adjusting the wind stress drag coefficient using the adjoint technique.

scholarly journals Local and Equatorial Forcing of Seasonal Variations of the North Equatorial Countercurrent in the Atlantic Ocean

2006 ◽  
Vol 36 (2) ◽  
pp. 238-254 ◽  
Author(s):  
Jiayan Yang ◽  
Terrence M. Joyce
Keyword(s):  
Atlantic Ocean ◽  
Wind Stress ◽  
Seasonal Variability ◽  
Ocean Model ◽  
Wind Stress Curl ◽  
Tropical Ocean ◽  
Southern Boundary ◽  
The North ◽  
Forcing Mechanisms ◽  
Wind Stress Field

Abstract The seasonal variation of the North Equatorial Countercurrent (NECC) in the tropical Atlantic Ocean is investigated by using a linear, one-layer reduced-gravity ocean model and by analyzing sea surface height (SSH) data from Ocean Topography Experiment (TOPEX)/Poseidon (T/P) altimeters. The T/P data indicate that the seasonal variability of the NECC geostrophic transport, between 3° and 10°N, is dominated by SSH changes in the southern flank of the current. Since the southern boundary of the NECC is located partially within the equatorial waveguide, the SSH variation there can be influenced considerably by the equatorial dynamics. Therefore, it is hypothesized that the wind stress forcing along the equator is the leading driver for the seasonal cycle of the NECC transport. The wind stress curl in the NECC region is an important but smaller contributor. This hypothesis is tested by several sensitivity experiments that are designed to separate the two forcing mechanisms. In the first sensitivity run, a wind stress field that has a zero curl is used to force the ocean model. The result shows that the NECC geostrophic transport retains most of its seasonal variability. The same happens in another experiment in which the seasonal wind stress is applied only within a narrow band along the equator outside the NECC range. To further demonstrate the role of equatorial waves, another experiment was run in which the wind stress in the Southern Hemisphere is altered so that the model excludes hemispherically symmetrical waves (Kelvin waves and odd-numbered meridional modes of equatorial Rossby waves) and instead excites only the antisymmetrical equatorial Rossby modes. The circulation in the northern tropical ocean, including the NECC, is affected considerably even though the local wind stress there remains unchanged. All these appear to support the hypothesis presented in this paper.

scholarly journals On the Impact of Unmanned Aerial System Observations on Numerical Weather Prediction in the Coastal Zone

2018 ◽  
Vol 146 (2) ◽  
pp. 599-622 ◽  
Author(s):  
David D. Flagg ◽  
James D. Doyle ◽  
Teddy R. Holt ◽  
Daniel P. Tyndall ◽  
Clark M. Amerault ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Research Laboratory ◽  
Weather Prediction ◽  
Ocean Model ◽  
Naval Research ◽  
Unmanned Aerial System ◽  
Numerical Weather ◽  
The Impact

Abstract The Trident Warrior observational field campaign conducted off the U.S. mid-Atlantic coast in July 2013 included the deployment of an unmanned aerial system (UAS) with several payloads on board for atmospheric and oceanic observation. These UAS observations, spanning seven flights over 5 days in the lowest 1550 m above mean sea level, were assimilated into a three-dimensional variational data assimilation (DA) system [the Naval Research Laboratory Atmospheric Variational Data Assimilation System (NAVDAS)] used to generate analyses for a numerical weather prediction model [the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)] with a coupled ocean model [the Naval Research Laboratory Navy Coastal Ocean Model (NCOM)]. The impact of the assimilated UAS observations on short-term atmospheric prediction performance is evaluated and quantified. Observations collected from 50 radiosonde launches during the campaign adjacent to the UAS flight paths serve as model forecast verification. Experiments reveal a substantial reduction of model bias in forecast temperature and moisture profiles consistently throughout the campaign period due to the assimilation of UAS observations. The model error reduction is most substantial in the vicinity of the inversion at the top of the model-estimated boundary layer. Investigations reveal a consistent improvement to prediction of the vertical position, strength, and depth of the boundary layer inversion. The relative impact of UAS observations is explored further with experiments of systematic denial of data streams from the NAVDAS DA system and removal of individual measurement sources on the UAS platform.

scholarly journals The Effect of Wind Stress on Seasonal Sea-Level Change on the Northwestern European Shelf

2022 ◽  
pp. 1-31
Keyword(s):  
Sea Level ◽  
Wind Stress ◽  
Sea Level Change ◽  
Ocean Model ◽  
Seasonal Differences ◽  
Sea Levels ◽  
Level Change ◽  
Stress Changes ◽  
European Shelf ◽  
Emissions Scenario

Abstract Projections of relative sea-level change (RSLC) are commonly reported at an annual mean basis. The seasonality of RSLC is often not considered, even though it may modulate the impacts of annual mean RSLC. Here, we study seasonal differences in 21st-century ocean dynamic sea-level change (DSLC, 2081-2100 minus 1995-2014) on the Northwestern European Shelf (NWES) and their drivers, using an ensemble of 33 CMIP6 models complemented with experiments performed with a regional ocean model. For the high-end emissions scenario SSP5-8.5, we find substantial seasonal differences in ensemble mean DSLC, especially in the southeastern North Sea. For example, at Esbjerg (Denmark), winter mean DSLC is on average 8.4 cm higher than summer mean DSLC. Along all coasts on the NWES, DSLC is higher in winter and spring than in summer and autumn. For the low-end emissions scenario SSP1-2.6, these seasonal differences are smaller. Our experiments indicate that the changes in winter and summer sea-level anomalies are mainly driven by regional changes in wind-stress anomalies, which are generally southwesterly and east-northeasterly over the NWES, respectively. In spring and autumn, regional wind-stress changes play a smaller role. We also show that CMIP6 models not resolving currents through the English Channel cannot accurately simulate the effect of seasonal wind-stress changes on he NWES. Our results imply that using projections of annual mean RSLC may underestimate the projected changes in extreme coastal sea levels in spring and winter. Additionally, changes in the seasonal sea-level cycle may affect groundwater dynamics and the inundation characteristics of intertidal ecosystems.

scholarly journals Variational data assimilation with superparameterization

2015 ◽  
Vol 2 (2) ◽  
pp. 513-536 ◽  
Author(s):  
I. Grooms ◽  
Y. Lee
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Climate Models ◽  
Low Cost ◽  
Ocean Model ◽  
Variational Data Assimilation ◽  
Scale Model ◽  
Small Scale ◽  
New Applications ◽  
Lorenz 96

Abstract. Superparameterization (SP) is a multiscale computational approach wherein a large scale atmosphere or ocean model is coupled to an array of simulations of small scale dynamics on periodic domains embedded into the computational grid of the large scale model. SP has been successfully developed in global atmosphere and climate models, and is a promising approach for new applications. The authors develop a 3D-Var variational data assimilation framework for use with SP; the relatively low cost and simplicity of 3D-Var in comparison with ensemble approaches makes it a natural fit for relatively expensive multiscale SP models. To demonstrate the assimilation framework in a simple model, the authors develop a new system of ordinary differential equations similar to the two-scale Lorenz-'96 model. The system has one set of variables denoted {Yi}, with large and small scale parts, and the SP approximation to the system is straightforward. With the new assimilation framework the SP model approximates the large scale dynamics of the true system accurately.

scholarly journals The Benguela Upwelling System: Quantifying the Sensitivity to Resolution and Coastal Wind Representation in a Global Climate Model*

2015 ◽  
Vol 28 (23) ◽  
pp. 9409-9432 ◽  
Author(s):  
R. Justin Small ◽  
Enrique Curchitser ◽  
Katherine Hedstrom ◽  
Brian Kauffman ◽  
William G. Large
Keyword(s):  
Wind Stress ◽  
Climate Model ◽  
Coastal Upwelling ◽  
Ocean Model ◽  
Wind Stress Curl ◽  
Upwelling System ◽  
Wind Structure ◽  
Eastern Boundary ◽  
Benguela Upwelling ◽  
Atmosphere Model

Abstract Of all the major coastal upwelling systems in the world’s oceans, the Benguela, located off southwest Africa, is the one that climate models find hardest to simulate well. This paper investigates the sensitivity of upwelling processes, and of sea surface temperature (SST), in this region to resolution of the climate model and to the offshore wind structure. The Community Climate System Model (version 4) is used here, together with the Regional Ocean Modeling System. The main result is that a realistic wind stress curl at the eastern boundary, and a high-resolution ocean model, are required to well simulate the Benguela upwelling system. When the wind stress curl is too broad (as with a 1° atmosphere model or coarser), a Sverdrup balance prevails at the eastern boundary, implying southward ocean transport extending as far as 30°S and warm advection. Higher atmosphere resolution, up to 0.5°, does bring the atmospheric jet closer to the coast, but there can be too strong a wind stress curl. The most realistic representation of the upwelling system is found by adjusting the 0.5° atmosphere model wind structure near the coast toward observations, while using an eddy-resolving ocean model. A similar adjustment applied to a 1° ocean model did not show such improvement. Finally, the remote equatorial Atlantic response to restoring SST in a broad region offshore of Benguela is substantial; however, there is not a large response to correcting SST in the narrow coastal upwelling zone alone.

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