scholarly journals Field Measurements of Surface and Near-Surface Turbulence in the Presence of Breaking Waves

2015 ◽  
Vol 45 (4) ◽  
pp. 943-965 ◽  
Author(s):  
Peter Sutherland ◽  
W. Kendall Melville
Keyword(s):  
Field Experiments ◽  
North Pacific Ocean ◽  
Large Fraction ◽  
Field Measurements ◽  
Breaking Waves ◽  
Sea Surface ◽  
Near Surface ◽  
Wave Energy Dissipation ◽  
Eddy Simulation ◽  
The North

AbstractWave breaking removes energy from the surface wave field and injects it into the upper ocean, where it is dissipated by viscosity. This paper presents an investigation of turbulent kinetic energy (TKE) dissipation beneath breaking waves. Wind, wave, and turbulence data were collected in the North Pacific Ocean aboard R/P FLIP, during the ONR-sponsored High Resolution Air-Sea Interaction (HiRes) and Radiance in a Dynamic Ocean (RaDyO) experiments. A new method for measuring TKE dissipation at the sea surface was combined with subsurface measurements to allow estimation of TKE dissipation over the entire wave-affected surface layer. Near the surface, dissipation decayed with depth as z−1, and below approximately one significant wave height, it decayed more quickly, approaching z−2. High levels of TKE dissipation very near the sea surface were consistent with the large fraction of wave energy dissipation attributed to non-air-entraining microbreakers. Comparison of measured profiles with large-eddy simulation results in the literature suggests that dissipation is concentrated closer to the surface than previously expected, largely because the simulations did not resolve microbreaking. Total integrated dissipation in the water column agreed well with dissipation by breaking for young waves, (where cm is the mean wave frequency and is the atmospheric friction velocity), implying that breaking was the dominant source of turbulence in those conditions. The results of these extensive measurements of near-surface dissipation over three field experiments are discussed in the context of observations and ocean boundary layer modeling efforts by other groups.

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

scholarly journals Neural Network Approach to Retrieving Ocean Subsurface Temperatures from Surface Parameters Observed by Satellites

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li
Keyword(s):  
Neural Network ◽  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
Satellite Measurements ◽  
Surface Parameters ◽  
The North ◽  
The North Pacific ◽  
Bpnn Model

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.

Recent intensified influence of the winter North Pacific sea surface temperature on the withdrawal date of Meiyu

2021 ◽  
pp. 1-53
Author(s):  
Hua Li ◽  
Shengping He ◽  
Ke Fan ◽  
Yong Liu ◽  
Xing Yuan
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Interannual Variability ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
The North ◽  
Time Period ◽  
The North Pacific ◽  
Sst Anomalies

AbstractThe Meiyu withdrawal date (MWD) is a crucial indicator of flood/drought conditions over East Asia. It is characterized by a strong interannual variability, but its underlying mechanism remains unknown. We investigated the possible effects of the winter sea surface temperature (SST) in the North Pacific Ocean on the MWD on interannual to interdecadal timescales. Both our observations and model results suggest that the winter SST anomalies associated with the MWD are mainly contributed by a combination of the first two leading modes of the winter SST in the North Pacific, which have a horseshoe shape (the NPSST). The statistical results indicate that the intimate linkage between the NPSST and the MWD has intensified since the early 1990s. During the time period 1990–2016, the NPSST-related SST anomalies persisted from winter to the following seasons and affected the SST over the tropical Pacific in July. Subsequently, the SST anomalies throughout the North Pacific strengthened the southward migration of the East Asian jet stream (EAJS) and the southward and westward replacement of the western North Pacific subtropical high (WPSH), leading to an increase in Meiyu rainfall from July 1 to 20. More convincingly, the anomalous EAJS and WPSH induced by the SST anomalies can be reproduced well by numerical simulations. By contrast, the influence of the NPSST on the EASJ and WPSH were not clear between 1961 and 1985. This study further illustrates that the enhanced interannual variability of the NPSST may be attributed to the more persistent SST anomalies during the time period 1990–2016.

scholarly journals The pliocene record of climatic change: equator-to-pole biotic response

1992 ◽  
Vol 6 ◽  
pp. 78-78
Author(s):  
Thomas M. Cronin ◽  
H.J. Dowsett
Keyword(s):  
Ocean Circulation ◽  
North Atlantic ◽  
North Pacific ◽  
Global Climate ◽  
North Pacific Ocean ◽  
Thermal Gradients ◽  
High Latitudes ◽  
Near Surface ◽  
Temperature Changes ◽  
The North

Pliocene faunal events in tropical and subtropical regions of the Americas and the Caribbean have been causally linked to global climatic events, particularly, progressive cooling and increased amplitude of climatic cycles between 3.5 and 2.0 Ma. However, the rate and magnitude of Pliocene temperature changes has been determined in only a few climate proxy records. Our study contrasts paleoceanographic conditions at 3 Ma, an extremely warm period in many areas, with conditions 2.4 Ma, a much cooler interval, in equator-to-pole transects for the North Atlantic and the North Pacific Oceans. By using microfaunal data (ostracodes from ocean margin environments and planktic foraminifers from deep sea cores), quantitative factor analytic and modern analog dissimilarity coefficient analyses were carried out on faunas from the following sections.Our studies lead to the following conclusions: (1) Equator-to-pole thermal gradients in the oceans at 3.0 Ma were not as steep as they are today, but thermal gradients at 2.4 Ma were steeper than those today; (2)At 3 Ma middle to high latitudes were substantially warmer than today, but tropical regions were about the same; (3)Substantial cooling occurred in middle and high latitudes in the western North Pacific Ocean and the western North Atlantic between 3 Ma and 2.4 Ma; (4)Ocean water temperatures off the southeastern U.S. remained the same or cooled only slightly between 3 Ma and 2.4 Ma. Our results support the hypothesis that ocean circulation changes, probably resulting from the closure of near surface water by the Isthmus of Panama, had significant impact on equator-to-pole heat transport and global climate between about 3 and 2.4 Ma. They also argue against the hypothesis that climatically induced ocean temperature changes were directly linked to a major marine extinction in the southwestern North Atlantic and Caribbean.

Estimated Global Hydrographic Variability

2007 ◽  
Vol 37 (8) ◽  
pp. 1997-2008 ◽  
Author(s):  
Gaël Forget ◽  
Carl Wunsch
Keyword(s):  
Ocean Circulation ◽  
Large Fraction ◽  
World Ocean ◽  
Three Dimensional ◽  
Sea Surface Height ◽  
Sea Surface ◽  
The North ◽  
Salinity Variability ◽  
Vertical Displacements ◽  
Diffusive Processes

Abstract An estimate is made of the three-dimensional global oceanic temperature and salinity variability, omitting the seasonal cycle, both as a major descriptive element of the ocean circulation and for use in the error estimates of state estimation. Historical hydrography, recent data from the World Ocean Circulation Experiment, and Argo profile data are all used. Root-mean-square vertical displacements in the upper 300 m of the ocean are generally smaller than 50 m, except in energetic boundary currents and in the North Atlantic subpolar gyre. Variability in temperature and salinity is strongly correlated below the top 100 m. Salinity contributions to sea surface height variability appear more significant at low latitudes than expected, possibly resulting from advective and diffusive processes. Results are generally consistent with altimetric variability under two simple kinematic hypotheses, and much of the observed structure coincides with known dynamical features. A large fraction of the sea surface height variability is consistent with the hypothesis of dominance of the first baroclinic mode.

scholarly journals Prediction of groundwater drawdown using artificial neural networks

2021 ◽  
Author(s):  
Vahid Gholami ◽  
Hossein Sahour
Keyword(s):  
Neural Network ◽  
Field Experiments ◽  
Accuracy Assessment ◽  
Field Measurements ◽  
Training Data ◽  
Validation Data ◽  
The North ◽  
Groundwater Drawdown ◽  
Ann Models ◽  
Artificial Neural

Abstract Groundwater drawdown is typically measured using pumping tests and field experiments; however, the traditional methods are time-consuming and costly when applied to extensive areas. In this research, a methodology is introduced based on artificial neural network (ANN)s and field measurements in an alluvial aquifer in the north of Iran. First, the annual drawdown as the output of the ANN models in 250 piezometric wells was measured, and the data were divided into three categories of training data, cross-validation data, and test data. Then, the effective factors in groundwater drawdown including groundwater depth, annual precipitation, annual evaporation, the transmissivity of the aquifer formation, elevation, distance from the sea, distance from water sources (recharge), population density, and groundwater extraction in the influence radius of each well (1000 m) were identified and used as the inputs of the ANN models. Several ANN methods were evaluated, and the predictions were compared with the observations. Results show that, the modular neural network (MNN) showed the highest performance in modeling groundwater drawdown ​​(Training R-sqr = 0.96, test R-sqr = 0.81). The optimum network was fitted to available input data to map the annual drawdown ​​across the entire aquifer. The accuracy assessment of the final map yielded favorable results (R-sqr = 0.8). The adopted methodology can be applied for the prediction of groundwater drawdown in the study site and similar settings elsewhere.

Sign in / Sign up

Export Citation Format

Share Document