scholarly journals Bidirectional Modeling of Surface Winds and Significant Wave Heights in the Caribbean Sea

2021 ◽  
Vol 9 (5) ◽  
pp. 547
Author(s):  
Brandon J. Bethel ◽  
Changming Dong ◽  
Shuyi Zhou ◽  
Yuhan Cao
Keyword(s):  
Short Term Memory ◽  
Surface Wind ◽  
Specific Area ◽  
Wave Model ◽  
Caribbean Sea ◽  
Surface Winds ◽  
Significant Wave ◽  
Wind Speeds ◽  
Lstm Network ◽  
Instrumentation Failure

Though the ocean is sparsely populated by buoys that feature co-located instruments to measure surface winds and waves, their data is of vital importance. However, due to either minor instrumentation failure or maintenance, intermittency can be a problem for either variable. This paper attempts to mitigate the loss of valuable data from two opposite but equivalent perspectives: the conventional reconstruction of significant wave height (SWH) from Caribbean Sea buoy-observed surface wind speeds (WSP) and the inverse modeling of WSP from SWH using the long short-term memory (LSTM) network. In either direction, LSTM is strongly able to recreate either variable from its counterpart with the lowest correlation coefficient (r2) measured at 0.95, the highest root mean square error (RMSE) is 0.26 m/s for WSP, and 0.16 m for SWH. The highest mean absolute percentage errors (MAPE) for WSP and SWH are 1.22% and 5%, respectively. Additionally, in the event of complete instrument failure or the absence of a buoy in a specific area, the Simulating WAves Nearshore (SWAN) wave model is first validated and used to simulate mean and extreme SWH before, during, and after the passage of Hurricane Matthew (2016). Synthetic SWH is then fed to LSTM in a joint SWAN—LSTM model, and the corresponding WSP is reconstructed and compared with observations. Although the reconstruction is highly accurate (r2 > 0.9, RMSE < 1.3 m/s, MAPE < 0.8%), there remains great room for improvement in minimizing error and capturing high-frequency events.

scholarly journals The Probability Distribution of Sea Surface Wind Speeds: Effects of Variable Surface Stratification and Boundary Layer Thickness

2010 ◽  
Vol 23 (19) ◽  
pp. 5151-5162 ◽  
Author(s):  
Adam Hugh Monahan
Keyword(s):  
Boundary Layer ◽  
Layer Thickness ◽  
Boundary Layer Thickness ◽  
Surface Wind ◽  
Sea Surface ◽  
Surface Winds ◽  
Free Atmosphere ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Variable Surface

Abstract Air–sea exchanges of momentum, energy, and material substances of fundamental importance to the variability of the climate system are mediated by the character of the turbulence in the atmospheric and oceanic boundary layers. Sea surface winds influence, and are influenced by, these fluxes. The probability density function (pdf) of sea surface wind speeds p(w) is a mathematical object describing the variability of surface winds that arises from the physics of the turbulent atmospheric planetary boundary layer. Previous mechanistic models of the pdf of sea surface wind speeds have considered the momentum budget of an atmospheric layer of fixed thickness and neutral stratification. The present study extends this analysis, using an idealized model to consider the influence of boundary layer thickness variations and nonneutral surface stratification on p(w). It is found that surface stratification has little direct influence on p(w), while variations in boundary layer thickness bring the predictions of the model into closer agreement with the observations. Boundary layer thickness variability influences the shape of p(w) in two ways: through episodic downward mixing of momentum into the boundary layer from the free atmosphere and through modulation of the importance (relative to other tendencies) of turbulent momentum fluxes at the surface and the boundary layer top. It is shown that the second of these influences dominates over the first.

Effect of Uni- and Bi-Directional Coupling of Ocean-Met Interaction on Significant Wave Height and Local Wind

2017 ◽  
Author(s):  
Adil Rasheed ◽  
Jakob Kristoffer Süld ◽  
Mandar Tabib
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Surface Wind ◽  
Wave Model ◽  
Ocean Surface ◽  
Observation Data ◽  
Local Wind ◽  
Near Surface ◽  
Significant Wave ◽  
Bidirectional Coupling

Accurate prediction of near surface wind and wave height are important for many offshore activities like fishing, boating, surfing, installation and maintenance of marine structures. The current work investigates the use of different methodologies to make accurate predictions of significant wave height and local wind. The methodology consists of coupling an atmospheric code HARMONIE and a wave model WAM. Two different kinds of coupling methodologies: unidirectional and bidirectional coupling are tested. While in Unidirectional coupling only the effects of atmosphere on ocean surface are taken into account, in bidirectional coupling the effects of ocean surface on the atmosphere are also accounted for. The predicted values of wave height and local wind at 10m above the ocean surface using both the methodologies are compared against observation data. The results show that during windy conditions, a bidirectional coupling methodology has better prediction capability.

scholarly journals Characteristics of high monsoon wind-waves observed at multiple stations in the eastern Arabian Sea

2017 ◽  
Author(s):  
M. M. Amrutha ◽  
V. Sanil Kumar
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Arabian Sea ◽  
Wind Waves ◽  
Surface Wind ◽  
Wave Model ◽  
Spatial Distance ◽  
Significant Wave ◽  
Eastern Arabian Sea ◽  
Crest Height

Abstract. The growth and decay of surface wind-waves during one-month period in a typical Indian summer monsoon is investigated based on the data collected at 9 to 15 m water depth at 4 locations in the nearshore waters of the eastern Arabian Sea covering a spatial distance of ~ 350 km. The significant wave height varied from 0.7 to 5.5 m during the data collection considered in the analysis. The heights of waves during the measurement period often exceed 3 m. The most extreme wave height is 1.50 to 1.62 times the significant wave height and the most extreme crest height of the wave is 1.23 to 1.35 times the significant wave height of the same 30-minutes record. The average ratio of crest height of the wave to the height of the same wave is 0.58 to 0.67. The height of waves having maximum crest height is smaller than the maximum wave height during 30 minutes period. Measured waves are predominantly swell, but since the majority of wave generation during the monsoon is adjacent to the study area and the wind–wave coupling is strong, wave periods are rarely above 15 s. The numerical wave model could estimate the wave height reasonably well during the wave growth compared to the wave decay period. Hovmöller diagrams show a considerable spatial variability in the wave and wind pattern in the Indian Ocean during the high wave event at the eastern Arabian Sea.

scholarly journals An Assessment of NASA’s GMAO MERRA-2 Reanalysis Surface Winds

2019 ◽  
Vol 32 (23) ◽  
pp. 8261-8281 ◽  
Author(s):  
D. Carvalho
Keyword(s):  
Surface Wind ◽  
The Other ◽  
Surface Winds ◽  
Wind Fields ◽  
Near Surface ◽  
Wind Speeds ◽  
Wide Range ◽  
Ocean Surface Winds ◽  
The Tropics ◽  
Global Surface

Abstract The quality of MERRA-2 surface wind fields was assessed by comparing them with 10 years of measurements from a wide range of surface wind observing platforms. This assessment includes a comparison of MERRA-2 global surface wind fields with the ones from its predecessor, MERRA, to assess if GMAO’s latest reanalyses improved the representation of the global surface winds. At the same time, surface wind fields from other modern reanalyses—NCEP-CFSR, ERA-Interim, and JRA-55—were also included in the comparisons to evaluate MERRA-2 global surface wind fields in the context of its contemporary reanalyses. Results show that MERRA-2, CFSR, ERA-Interim, and JRA-55 show similar error metrics while MERRA consistently shows the highest errors. Thus, when compared with wind observations, the accuracy of MERRA-2 surface wind fields represents a clear improvement over its predecessor MERRA and is in line with the other contemporary reanalyses in terms of the representation of global near-surface wind fields. All reanalyses showed a tendency to underestimate ocean surface winds (particularly in the tropics) and, oppositely, to overestimate inland surface winds (except JRA-55, which showed a global tendency to underestimate the wind speeds); to represent the wind direction rotated clockwise in the Northern Hemisphere (positive bias) and anticlockwise in the Southern Hemisphere (negative bias), with the exception of JRA-55; and to show higher errors near the poles and in the ITCZ, particularly in the equatorial western coasts of Central America and Africa. However, MERRA-2 showed substantially lower wind errors in the poles when compared with the other reanalyses.

scholarly journals High-resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon

2015 ◽  
Vol 15 (7) ◽  
pp. 3785-3801 ◽  
Author(s):  
B. W. Butler ◽  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Surface Wind ◽  
Wind Data ◽  
Wind Flow ◽  
Surface Winds ◽  
Mean Flow ◽  
Near Surface ◽  
Wind Speeds ◽  
Synoptic Forcing

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ~ 100 m); however, there are very limited observational data available for evaluating these high-resolution models. This study presents high-resolution surface wind data sets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. In a downslope flow, wind speed did not have a consistent trend with position on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly down-canyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds on sub-grid scales in complex terrain. Measurement data can be found at http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.

The Impact of Hurricane Force Wind Fields on the North Pacific Ocean Environment

2015 ◽  
Vol 30 (3) ◽  
pp. 742-753 ◽  
Author(s):  
Steven Businger ◽  
Selen Yildiz ◽  
Thomas E. Robinson
Keyword(s):  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Surface Wind ◽  
Wave Model ◽  
Wind Data ◽  
Surface Winds ◽  
Wind Fields ◽  
The North ◽  
The North Pacific

AbstractThis study analyzes QuikSCAT surface wind data over the North Pacific Ocean to document the distribution of captured fetches in extratropical cyclones that produced hurricane force (HF) wind fields from January 2003 through May 2008. A case study is presented to introduce the datasets, which include surface wind analyses from the Global Forecast System (GFS) Global Data Assimilation System (GDAS), and wave hindcasts from the third-generation wave model (WAVEWATCH III; hereafter, WW3), in addition to the QuikSCAT surface wind data. The analysis shows significant interannual variability in the location of the captured fetches as documented by QuikSCAT, including a shift in the distribution of captured fetches associated with ENSO. GDAS surface winds over the ocean are consistently underanalyzed when compared to QuikSCAT surface winds, despite the fact that satellite observations of ocean surface winds are assimilated. When the WW3 hindcasts associated with HF cyclones are compared with buoy observations over the eastern and central North Pacific Ocean, the wave model significantly underestimates the large-swell events.

scholarly journals Projected Characteristic Changes of a Typical Tropical Cyclone under Climate Change in the South West Indian Ocean

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 232
Author(s):  
Callum Thompson ◽  
Christelle Barthe ◽  
Soline Bielli ◽  
Pierre Tulet ◽  
Joris Pianezze
Keyword(s):  
Indian Ocean ◽  
Climate Models ◽  
Surface Wind ◽  
Coupled Model ◽  
Wave Model ◽  
La Réunion ◽  
Intergovernmental Panel ◽  
Surface Warming ◽  
Wind Speeds ◽  
South West Indian Ocean

During 2 January 2014, Cyclone Bejisa passed near La Réunion in the southwestern Indian Ocean, bringing wind speeds of 41 m s−1, an ocean swell of 7 m, and rainfall accumulations of 1025 mm over 48 h. As a typical cyclone to impact La Réunion, we investigate how the characteristics of this cyclone could change in response to future warming via high-resolution, atmosphere–ocean coupled simulations of Bejisa-like cyclones in historical and future environments. Future environments are constructed using the pseudo global warming method whereby perturbations are added to historical analyses from six Coupled Model Intercomparison Project 5 (CMIP5) climate models. These models follow the Intergovernmental Panel for Climate Change’s (IPCC) Representative Concentration Pathways (RCP) RCP8.5 emissions scenario and project ocean surface warming of 1.1–4.2 °C by 2100. Under these conditions, we find that future Bejisa-like cyclones are 6.5% more intense on average and reach their lifetime maximum intensity 2 degrees further poleward. Additionally, future cyclones produce heavier rainfall, with a 33.8% average increase in the median rainrate, and are 9.2% smaller, as measured by the radius of 17.5 m s−1 winds. Furthermore, when surface wind output is used to run an ocean wave model in post, we find a 4.6% increase in the significant wave height.

scholarly journals Forecasting Hurricane-forced Significant Wave Heights using the Long Short-Term Memory Network in the Caribbean Sea

2021 ◽  
Author(s):  
Brandon Justin Bethel ◽  
Wenjin Sun ◽  
Changming Dong
Keyword(s):  
Neural Network ◽  
Short Term Memory ◽  
Caribbean Sea ◽  
Short Term ◽  
Term Memory ◽  
Significant Wave ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Long Short Term Memory ◽  
The Caribbean

Abstract. A Long Short-Term Memory (LSTM) neural network is proposed to predict hurricane-forced significant wave heights (SWH) in the Caribbean Sea (CS) based on a dataset of 20 CS, Gulf of Mexico, and Western Atlantic hurricane events collected from 10 buoys from 2010–2020. SWH nowcasting and forecasting are initiated using LSTM on 0-, 3-, 6-, 9-, and 12-hour horizons. Through examining study cases Hurricanes Dorian (2019), Sandy (2012), and Igor (2010), results illustrate that the model is well suited to forecast hurricane-forced wave heights. Forecasts are highly accurate with regard to observations. For example, Hurricane Dorian nowcasts had correlation (R), root mean square error (RMSE), and mean absolute percentage error (MAPE) values of 0.99, 0.16 m, and 2.6 %, respectively. Similarly, on the 3-, 6-, 9-, and 12-hour forecasts, results produced R (RMSE; MAPE) values of 0.95 (0.51 m; 7.99 %), 0.92 (0.74 m; 10.83 %), 0.85 (1 m; 13.13 %), and 0.84 (1.24 m; 14.82 %), respectively. However, the model also consistently over-predicted the maximum observed SWHs. To improve models results, additional research should be geared towards improving single-point LSTM neural network training datasets by considering hurricane track and identifying the hurricane quadrant in which buoy observations are made.

scholarly journals High resolution observations of the near-surface wind field over an isolated mountain and in a steep river canyon

2014 ◽  
Vol 14 (11) ◽  
pp. 16821-16863
Author(s):  
B. W. Butler ◽  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Surface Wind ◽  
Wind Flow ◽  
Surface Winds ◽  
Mean Flow ◽  
Near Surface ◽  
Flow Models ◽  
Wind Speeds ◽  
Synoptic Forcing

Abstract. A number of numerical wind flow models have been developed for simulating wind flow at relatively fine spatial resolutions (e.g., ∼100 m); however, there are very limited observational data available for evaluating these high resolution models. This study presents high-resolution surface wind datasets collected from an isolated mountain and a steep river canyon. The wind data are presented in terms of four flow regimes: upslope, afternoon, downslope, and a synoptically-driven regime. There were notable differences in the data collected from the two terrain types. For example, wind speeds collected on the isolated mountain increased with distance upslope during upslope flow, but generally decreased with distance upslope at the river canyon site during upslope flow. Wind speed did not have a simple, consistent trend with position on the slope during the downslope regime on the isolated mountain, but generally increased with distance upslope at the river canyon site. The highest measured speeds occurred during the passage of frontal systems on the isolated mountain. Mountaintop winds were often twice as high as wind speeds measured on the surrounding plain. The highest speeds measured in the river canyon occurred during late morning hours and were from easterly downcanyon flows, presumably associated with surface pressure gradients induced by formation of a regional thermal trough to the west and high pressure to the east. Under periods of weak synoptic forcing, surface winds tended to be decoupled from large-scale flows, and under periods of strong synoptic forcing, variability in surface winds was sufficiently large due to terrain-induced mechanical effects (speed-up over ridges and decreased speeds on leeward sides of terrain obstacles) that a large-scale mean flow would not be representative of surface winds at most locations on or within the terrain feature. These findings suggest that traditional operational weather model (i.e., with numerical grid resolutions of around 4 km or larger) wind predictions are not likely to be good predictors of local near-surface winds at sub-grid scales in complex terrain. The data from this effort are archived and available at: http://www.firemodels.org/index.php/windninja-introduction/windninja-publications.

scholarly journals Performance of the WRF Model for Surface Wind Prediction around Qatar

2018 ◽  
Vol 35 (3) ◽  
pp. 575-592 ◽  
Author(s):  
B. S. Sandeepan ◽  
V. G. Panchang ◽  
S. Nayak ◽  
K. Krishna Kumar ◽  
J. M. Kaihatu
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Surface Wind ◽  
Wrf Model ◽  
Wave Model ◽  
Sea Breeze ◽  
Surface Winds ◽  
Model Errors ◽  
Sea Breezes ◽  
Practical Applications

AbstractThe performance of the Weather Research and Forecasting (WRF) Model is examined for the region around Qatar in the context of surface winds. The wind fields around this peninsula can be complicated owing to its small size, to a complex pattern of land and sea breezes influenced by the prevailing shamal winds, and to its dry and arid nature. Modeled winds are verified with data from 19 land stations and two offshore buoys. A comparison with these data shows that nonlocal planetary boundary layer (PBL) schemes generally perform better than local schemes over land stations during the daytime, when convective conditions prevail; at nighttime, over land and over water, both schemes yield similar results. Among other parameters, modifications to standard USGS land-use descriptors were necessary to reduce model errors. The RMSE values are comparable to those reported elsewhere. Simulated winds, when used with a wave model, result in wave heights comparable to buoy measurements. Furthermore, WRF results, confirmed by data, show that at times sea breezes develop from both coasts, leading to convergence in the middle of the country; at other times, the large-scale wind impedes the formation of sea breezes on one or both coasts. Simulations also indicate greater land/sea-breeze activity in the summer than in the winter. Differences in the diurnal evolution of surface winds over land and water are found to be related to differences in the boundary layer stability. Overall, the results indicate that the WRF Model as configured here yields reliable simulations and can be used for various practical applications.

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