Improved Statement of the Relationship Between Surface Wind Speed and Oceanic Whitecap Coverage as Required for the Interpretation of Satellite Data

1981 ◽  
pp. 751-755 ◽  
Author(s):  
Edward C. Monahan ◽  
Iognaid Ó Muircheartaigh
Keyword(s):  
Wind Speed ◽  
Satellite Data ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Whitecap Coverage ◽  
The Relationship

scholarly journals Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network

2012 ◽  
Vol 5 (2) ◽  
pp. 377-388 ◽  
Author(s):  
A. Smirnov ◽  
A. M. Sayer ◽  
B. N. Holben ◽  
N. C. Hsu ◽  
S. M. Sakerin ◽  
...  
Keyword(s):  
Wind Speed ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Wind ◽  
Correlation Coefficients ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Strong Winds ◽  
The Relationship ◽  
Good Agreement

Abstract. The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (~0.004–0.005), even for strong winds over 10 m s−1. The relationships show significant scatter (correlation coefficients typically in the range 0.3–0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.

scholarly journals Analysis of influential factors for the relationship between PM<sub>2.5</sub> and AOD in Beijing

2017 ◽  
Vol 17 (21) ◽  
pp. 13473-13489 ◽  
Author(s):  
Caiwang Zheng ◽  
Chuanfeng Zhao ◽  
Yannian Zhu ◽  
Yang Wang ◽  
Xiaoqin Shi ◽  
...  
Keyword(s):  
Wind Speed ◽  
Vertical Structure ◽  
Surface Wind ◽  
Temporal Distribution ◽  
Surface Wind Speed ◽  
Time Of Day ◽  
Influential Factors ◽  
Remarkable Change ◽  
The Relationship ◽  
Aerosol Type

Abstract. The relationship between aerosol optical depth (AOD) and PM2.5 is often investigated in order to obtain surface PM2.5 from satellite observation of AOD with a broad area coverage. However, various factors could affect the AOD–PM2.5 regressions. Using both ground and satellite observations in Beijing from 2011 to 2015, this study analyzes the influential factors including the aerosol type, relative humidity (RH), planetary boundary layer height (PBLH), wind speed and direction, and the vertical structure of aerosol distribution. The ratio of PM2.5 to AOD, which is defined as η, and the square of their correlation coefficient (R2) have been examined. It shows that η varies from 54.32 to 183.14, 87.32 to 104.79, 95.13 to 163.52, and 1.23 to 235.08 µg m−3 with aerosol type in spring, summer, fall, and winter, respectively. η is smaller for scattering-dominant aerosols than for absorbing-dominant aerosols, and smaller for coarse-mode aerosols than for fine-mode aerosols. Both RH and PBLH affect the η value significantly. The higher the RH, the smaller the η, and the higher the PBLH, the smaller the η. For AOD and PM2.5 data with the correction of RH and PBLH compared to those without, R2 of monthly averaged PM2.5 and AOD at 14:00 LT increases from 0.63 to 0.76, and R2 of multi-year averaged PM2.5 and AOD by time of day increases from 0.01 to 0.93, 0.24 to 0.84, 0.85 to 0.91, and 0.84 to 0.93 in four seasons respectively. Wind direction is a key factor for the transport and spatial–temporal distribution of aerosols originated from different sources with distinctive physicochemical characteristics. Similar to the variation in AOD and PM2.5, η also decreases with the increasing surface wind speed, indicating that the contribution of surface PM2.5 concentrations to AOD decreases with surface wind speed. The vertical structure of aerosol exhibits a remarkable change with seasons, with most particles concentrated within about 500 m in summer and within 150 m in winter. Compared to the AOD of the whole atmosphere, AOD below 500 m has a better correlation with PM2.5, for which R2 is 0.77. This study suggests that all the above influential factors should be considered when we investigate the AOD–PM2.5 relationships.

scholarly journals Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network

2011 ◽  
Vol 4 (6) ◽  
pp. 7185-7209
Author(s):  
A. Smirnov ◽  
A. M. Sayer ◽  
B. N. Holben ◽  
N. C. Hsu ◽  
S. M. Sakerin ◽  
...  
Keyword(s):  
Wind Speed ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Wind ◽  
Correlation Coefficients ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Strong Winds ◽  
The Relationship ◽  
Good Agreement

Abstract. The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (∼0.004–0.005), even for strong winds over 10 m s−1. The relationships show significant scatter (correlation coefficients typically in the range 0.3–0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.

scholarly journals Impact of Satellite Data Assimilation in Atmospheric Reanalysis on the Marine Wind and Wave Climate

2016 ◽  
Vol 29 (17) ◽  
pp. 6351-6361 ◽  
Author(s):  
Wataru Sasaki
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Southern Ocean ◽  
Satellite Data ◽  
North Pacific ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Surface Winds ◽  
Near Surface ◽  
The Impact

Abstract This study investigated the impact of assimilating satellite data into atmospheric reanalyses on trends in ocean surface winds and waves. Two experiments were performed using a numerical wave model forced by near-surface winds: one derived from the Japanese 55-year Reanalysis (JRA-55; experiment A) and the other derived from JRA-55 using assimilated conventional observations only (JRA-55C; experiment B). The results showed that the satellite data assimilation reduced upward trends of the annual mean of wave energy flux (WEF) in the midlatitude North Pacific and southern ocean (30°–60°S), south of Australia, from 1959 to 2012. It was also found that the assimilation of scatterometer winds reduced the near-surface wind speed in the midlatitude North Pacific after the mid-1990s, which resulted in the reduced trend in WEF from 1959 to 2012. By contrast, assimilation of the satellite radiances for 1973–94 increased near-surface wind speed in the southern ocean, south of Australia, whereas the assimilation of the scatterometer winds after the mid-1990s reduced wind speed. The latter led to the reduced trend in WEF south of Australia from 1959 to 2012.

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

Ocean surface wind speed retrieval from C-band quad-polarized SAR measurements at optimal spatial resolution

2020 ◽  
Vol 12 (2) ◽  
pp. 155-164
Author(s):  
He Fang ◽  
William Perrie ◽  
Gaofeng Fan ◽  
Tao Xie ◽  
Jingsong Yang
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Ocean Surface Wind
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