scholarly journals MULTI-MODEL ENSEMBLE PROJECTION OF FUTURE COASTAL CLIMATE CHANGE

2012 ◽  
Vol 1 (33) ◽  
pp. 25
Author(s):  
Nobuhito Mori ◽  
Tomoya Shimura ◽  
Sota Nakajo ◽  
Tomohiro Yasuda ◽  
Hajime Mase
Keyword(s):  
Surface Wind ◽  
Sea Surface ◽  
Ocean Wave ◽  
Climate Data ◽  
Model Ensemble ◽  
Future Change ◽  
Data Set ◽  
Sea Surface Wind ◽  
Wave Heights ◽  
Year 2000

This study analyzes future change of averaged coastal physics such as sea level rises, sea surface winds and ocean wave heights based on the climate data set combining IPCC(2007) results and the latest MRI high-resolution AGCM results. The ocean wave height is statistically projected using an empirical formula with sea surface wind by multi-model ensemble. The ensemble means and their standard deviations of coastal forces are presented for the year 2000 to 2100. The signal of future change of Hs has stripped pattern in latitudinal direction and is clearer in the Southern Hemisphere than the Northern Hemisphere. The ratio of future change of $H_s$ to the present climate is 15% maximumly which is significant change than sea surface pressure and U10.

Wave- and Anemometer-Based Sea Surface Wind (WASWind) for Climate Change Analysis*

2011 ◽  
Vol 24 (1) ◽  
pp. 267-285 ◽  
Author(s):  
Hiroki Tokinaga ◽  
Shang-Ping Xie
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Wind Wave ◽  
Surface Wind ◽  
Sea Surface ◽  
Upward Trend ◽  
Data Set ◽  
Climate Trend ◽  
Sea Surface Wind ◽  
Trend Pattern

Abstract Ship-based measurements of sea surface wind speed display a spurious upward trend due to increases in anemometer height. To correct this bias, the authors constructed a new sea surface wind dataset from ship observations of wind speed and wind wave height archived in the International Comprehensive Ocean–Atmosphere Data Set (ICOADS). The Wave- and Anemometer-based Sea surface Wind (WASWind) dataset is available for wind velocity and scalar speed at monthly resolution on a 4° × 4° longitude–latitude grid from 1950 to 2008. It substantially reduces the upward trend in wind speed through height correction for anemometer-measured winds, rejection of spurious Beaufort winds, and use of estimated winds from wind wave height. The reduced global upward trend is smallest among the existing global datasets of in situ observations and comparable with those of reanalysis products. Despite the significant reduction of globally averaged wind speed trend, WASWind features rich spatial structures in trend pattern, making it a valuable dataset for studies of climate changes on regional scales. Not only does the combination of ship winds and wind wave height successfully reproduce major modes of seasonal-to-decadal variability; its trend patterns are also physically consistent with sea level pressure (SLP) measurements. WASWind is in close agreement with wind changes in satellite measurements by the Special Sensor Microwave Imagers (SSM/Is) for the recent two decades. The agreement in trend pattern with such independent observations illustrates the utility of WASWind for climate trend analysis. An application to the South Asian summer monsoon is presented.

scholarly journals Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters

2020 ◽  
Author(s):  
Haoyu Jiang ◽  
Hao Zheng ◽  
Lin Mu
Keyword(s):  
Surface Wind ◽  
Sea Surface ◽  
Atmospheric Parameters ◽  
Sea Temperature ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Wave Heights ◽  
Data Source ◽  
Significant Wave Heights ◽  
The Impact

Spaceborne altimeters are an important data source for obtaining global sea surface wind speeds (U10). Although many altimeter U10 algorithms have been proposed and they perform well, there is still room for improvement. In this study, the data from ten altimeters were collocated with buoys to investigate the error of the altimeter U10 retrievals. The U10 residuals were found to be significantly dependent on many oceanic and atmospheric parameters. Because these oceanic and atmospheric parameters are inter-correlated, an asymptotic strategy was used to isolate the impact of different parameters and establish a neural-network-based correction model of altimeter U10. The results indicated that significant wave heights and mean wave periods are effective in correcting U10 retrievals, probably due to the tilting modulation of long-waves on the sea surface. After the wave correction, the root-mean-square error of the retrieved U10 was reduced from 1.42 m/s to 1.24 m/s and the impacts of thermodynamic parameters, such as sea surface (air) temperate, became negligible. The U10 residuals after correction showed that the atmospheric instability can lead to errors on extrapolated buoy U10. The buoy measurements with large air-sea temperature differences need to be excluded in the Cal/Val of remotely sensed U10.

scholarly journals On the Use of Doppler Shift for Sea Surface Wind Retrieval From SAR

2012 ◽  
Vol 50 (7) ◽  
pp. 2901-2909 ◽  
Author(s):  
Alexis A. Mouche ◽  
Fabrice Collard ◽  
Bertrand Chapron ◽  
Knut-Frode Dagestad ◽  
Gilles Guitton ◽  
...  
Keyword(s):  
Doppler Shift ◽  
Surface Wind ◽  
Sea Surface ◽  
Wind Retrieval ◽  
Sea Surface Wind ◽  
Sea Surface Wind Retrieval

scholarly journals SST Anomalies in the Mozambique Channel Using Remote Sensing and Numerical Modeling Data

2019 ◽  
Vol 11 (9) ◽  
pp. 1112
Author(s):  
Guoqing Han ◽  
Changming Dong ◽  
Junde Li ◽  
Jingsong Yang ◽  
Qingyue Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mixed Layer Depth ◽  
Surface Wind ◽  
Radiant Heat ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Surface Mixed Layer ◽  
Mozambique Channel ◽  
Sea Surface Wind ◽  
Sst Anomalies

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.

scholarly journals FM-CW millimeter wave demonstrator system as a sensor of the sea surface wind vector

2004 ◽  
Vol 1 (6) ◽  
pp. 137-143 ◽  
Author(s):  
Alexey Nekrasov ◽  
Jacco J.M. de Wit ◽  
Peter Hoogeboom
Keyword(s):  
Millimeter Wave ◽  
Surface Wind ◽  
Sea Surface ◽  
Wind Vector ◽  
Sea Surface Wind

Wind Stress Over Waves: Effects of Sea Roughness and Atmospheric Stability

2002 ◽  
Vol 124 (3) ◽  
pp. 169-172 ◽  
Author(s):  
Dag Myrhaug ◽  
Olav H. Slaattelid
Keyword(s):  
Boundary Layer ◽  
Wind Stress ◽  
Local Equilibrium ◽  
Surface Wind ◽  
Atmospheric Stability ◽  
Sea Surface ◽  
Stability Function ◽  
Sea Surface Wind ◽  
Surface Wind Stress ◽  
Sea Surface Roughness

The paper considers the effects of sea roughness and atmospheric stability on the sea surface wind stress over waves, which are in local equilibrium with the wind, by using the logarithmic boundary layer profile including a stability function, as well as adopting some commonly used sea surface roughness formulations. The engineering relevance of the results is also discussed.

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