scholarly journals DMSP-SSM/I retrieval of proper surface winds during monsoon depression

MAUSAM ◽  
2022 ◽  
Vol 53 (3) ◽  
pp. 367-374
Author(s):  
P. N. MAHAJAN
Keyword(s):  
Satellite Data ◽  
Surface Wind ◽  
Monsoon Depression ◽  
Sea Surface ◽  
Surface Winds ◽  
Large Area ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Complete Life Cycle ◽  
Cycle Monitoring

Recently developed various global microwave algorithms for DMSP-SSM/I satellite data are used for the estimation of surface winds over the Indian ocean.  Sea surface wind speeds from these algorithms are compared with sea surface wind speeds reported by coincidental Minicoy island (lowest height 2 m a.s.l.) station over the Arabian sea.  A statistical comparison of these algorithms is made in terms of rms error, correlation coefficient, bias and standard deviation. Algorithm of Petty showed best results in the comparison.  On the basis of this algorithm a notable characteristic feature such as acquiring of large area of strong surface winds (12-15 ms-1) to the south of dipping of monsoon trough in head Bay and then encircling of these winds during further development of low and depression (22-27 July 1992) is observed. This complete life cycle monitoring assessment of monsoon depression in respect of surface winds based on DMSP-SSM/I satellite data encourages to utilise our IRS-P4 (Oceansat-1) satellite data at different frequencies to emerge more details of various weather systems over the Indian region.

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.

scholarly journals A Wind Speed Retrieval Model for Sentinel-1A EW Mode Cross-Polarization Images

2019 ◽  
Vol 11 (2) ◽  
pp. 153 ◽  
Author(s):  
Yuan Gao ◽  
Changlong Guan ◽  
Jian Sun ◽  
Lian Xie
Keyword(s):  
Wind Speed ◽  
Incidence Angle ◽  
Surface Wind ◽  
European Space Agency ◽  
Sea Surface ◽  
Cross Polarization ◽  
Retrieval Model ◽  
Sar Images ◽  
Wind Speeds ◽  
Sea Surface Wind

In contrast to co-polarization (VV or HH) synthetic aperture radar (SAR) images, cross-polarization (CP for VH or HV) SAR images can be used to retrieve sea surface wind speeds larger than 20 m/s without knowing the wind directions. In this paper, a new wind speed retrieval model is proposed for European Space Agency (ESA) Sentinel-1A (S-1A) Extra-Wide swath (EW) mode VH-polarized images. Nineteen S-1A images under tropical cyclone condition observed in the 2016 hurricane season and the matching data from the Soil Moisture Active Passive (SMAP) radiometer are collected and divided into two datasets. The relationships between normalized radar cross-section (NRCS), sea surface wind speed, wind direction and radar incidence angle are analyzed for each sub-band, and an empirical retrieval model is presented. To correct the large biases at the center and at the boundaries of each sub-band, a corrected model with an incidence angle factor is proposed. The new model is validated by comparing the wind speeds retrieved from S-1A images with the wind speeds measured by SMAP. The results suggest that the proposed model can be used to retrieve wind speeds up to 35 m/s for sub-bands 1 to 4 and 25 m/s for sub-band 5.

scholarly journals Sea Surface Wind Correction Using HF Ocean Radar and Its Impact on Coastal Wave Prediction

2017 ◽  
Vol 34 (9) ◽  
pp. 2001-2020 ◽  
Author(s):  
Yukiharu Hisaki
Keyword(s):  
Wind Direction ◽  
Surface Wind ◽  
Hf Radar ◽  
Sea Surface ◽  
Wave Parameter ◽  
Simple Method ◽  
Wind Speeds ◽  
Wave Prediction ◽  
Sea Surface Wind ◽  
The Impact

AbstractBoth wind speeds and wind directions are important for predicting wave heights near complex coastal areas, such as small islands, because the fetch is sensitive to the wind direction. High-frequency (HF) radar can be used to estimate sea surface wind directions from first-order scattering. A simple method is proposed to correct sea surface wind vectors from reanalysis data using the wind directions estimated from HF radar. The constraints for wind speed corrections are that the corrections are small and that the corrections of horizontal divergences are small. A simple algorithm for solving the solution that minimizes the weighted sum of the constraints is developed. Another simple method is proposed to correct sea surface wind vectors. The constraints of the method are that corrections of wind vectors and horizontal divergences from the reanalysis wind vectors are small and that the projection of the corrected wind vectors to the direction orthogonal to the HF radar–estimated wind direction is small. The impact of wind correction on wave parameter prediction is large in the area in which the fetch is sensitive to wind direction. The accuracy of the wave prediction is improved by correcting the wind in that area, where correction of wind direction is more important than correction of wind speeds for the improvement. This method could be used for near-real-time wave monitoring by correcting forecast winds using HF radar data.

Validation of Sea Surface Wind Speeds from Satellite Altimeters and Relation to Sea State Bias

2018 ◽  
Vol 39 (2) ◽  
pp. 139-153 ◽  
Author(s):  
Do-Young Choi ◽  
◽  
Hye-Jin Woo ◽  
Kyung-Ae Park ◽  
Do-Seong Byun ◽  
...  
Keyword(s):  
Surface Wind ◽  
Sea Surface ◽  
Sea State ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Sea State Bias

Simulation Research about HJ-1C SAR Wind Mapping Capability

2012 ◽  
Vol 500 ◽  
pp. 550-555
Author(s):  
Feng Feng Chen ◽  
Wei Gen Huang ◽  
Jing Song Yang
Keyword(s):  
Wave Spectrum ◽  
Surface Wind ◽  
Coastal Region ◽  
Sea Surface ◽  
Surface Model ◽  
Composite Surface ◽  
Envisat Asar ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Wind Mapping

Synthetic aperture radar (SAR) on aboard Chinese Huan Jing (HJ)-1C satellite has been planed to be launched in 2010. The satellite will fly in a sun-synchronous polar orbit of about 500-km altitude. SAR will operate in S band with HH polarization. Its image mode has the incidence angles 25°and 47°at the near and far sides of the swath respectively. SAR image has a spatial resolution of 20 m with a swath of 100 km. Here, the sea surface wind mapping capability of the SAR in the Chinese Coastal Region has been examined using M4S radar imaging model developed by Romeiser et al. The model is based on Bragg scattering theory in a composite surface model expansion. It accounts for contributions of the full ocean wave spectrum to the radar backscatter from ocean surface. The model reproduces absolute normalized radar cross section (NRCS) values for wide ranges of wind speeds. The model results of HJ-1C SAR have been compared with the model results of Envisat and Radarsat SAR signals. It shows that HJ-1C SAR is as good as both Envisat ASAR and Radarsat SAR at sea surface wind mapping Capability.

scholarly journals ESTIMATING AND FUSING OPTICAL FLOW, GEOSTROPHIC CURRENTS AND SEA SURFACE WIND IN THE WATERS AROUND KISH ISLAND

2015 ◽  
Vol XL-1-W5 ◽  
pp. 221-226 ◽  
Author(s):  
E. Ghalenoei ◽  
M. A. Sharifi ◽  
M. Hasanlou
Keyword(s):  
Spatial Resolution ◽  
Satellite Data ◽  
Satellite Altimetry ◽  
Surface Wind ◽  
Sea Surface ◽  
Data Sets ◽  
Surface Currents ◽  
Altimetry Data ◽  
Sea Surface Wind ◽  
Satellite Altimetry Data

The aim of this study is calculation of sea surface currents (SSCs) which are estimated from satellite data sets and processed with the variance component estimation (VCE) algorithm to check role of each data set, in fused surface currents (FSCs). The satellite data used in this study are sea surface temperature (SST), satellite altimetry data and sea surface wind (SSW) that plays the important role to make the SSCs and is measured by Ascat satellite. We use optical flow (OF) method (Horn-Schunck algorithm) to extract sea surface movements from sequential SST imageries; in addition, geostrophic currents (GCs) are estimated by satellite altimetry data like sea surface height (SSH). Combining these data sets, has its pros and cons, the OF results are so dense and precise due to high spatial resolution of MODIS data (SST), but sometimes cloud covering over the sea, does not allow the MODIS sensor to measure the SST. In contrast the SST data, the altimetry data have poor spatial resolution and the GCs are not able to determine small scale SSCs. The VCE algorithm shows variances of our data sets and it can be shown their correlations with themselves and with the FSCs. We also calculate angular differences between FSCs and OF, GCs and SSW, and plot distributions of these angular differences. We discover that, the OF and SSW are homolographic, but OF and GCs are accordant to each other.

scholarly journals Sea surface temperature changes due to polar lows over the Nordic Seas

2020 ◽  
Vol 65 (4) ◽  
Author(s):  
Pavel A. Golubkin ◽  
◽  
Julia E. Smirnova ◽  
Vsevolod S. Kolyada ◽  
◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Sea Surface ◽  
Polar Lows ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Polar Low ◽  
Upper Mixed Layer

In this study possible changes in sea surface temperature (SST) caused by passage of polar lows and analyzed. Polar lows are extreme atmospheric phenomena inherent to high latitudes. They develop sea surface wind speeds from 15 m/s up to hurricane force values and are characterized by small sizes (on average, 300 km) and lifetimes (less than two days), which complicates their detection and studies. It is assumed that as in case of tropical cyclones, which may considerably lower SST due to intense mixing and entrainment of colder waters to the ocean upper mixed layer, polar lows could similarly influence SST. Moreover, in the high latitude areas, where salt stratification may be present instead of temperature stratification, SST may increase due to mixing with deeper warmer layer. In this study 330 polar lows were analyzed using satellite passive microwave radiometer measurements of SST. In result, 47 cases when average SST values changed in polar low forcing areas were found. Out of these cases, in six cases SST increase of at least 0.5 °С was found, and in fifteen cases SST decrease of at least 0.5 °С was found. This indicates that upper ocean response to polar lows is quite rare phenomenon, which should be further analyzed along with its possible role in the ocean-ice-atmosphere system.

Effects of different sea surface wind speeds on performance of quantum satellite-to-ship communication

2021 ◽  
Vol 70 (4) ◽  
pp. 040303-040303
Author(s):  
Nie Min ◽  
◽  
Zhang Fan ◽  
Yang Guang ◽  
Zhang Mei-Ling ◽  
...  
Keyword(s):  
Surface Wind ◽  
Sea Surface ◽  
Wind Speeds ◽  
Sea Surface Wind

One Operational Method for Offshore Wind Speeds Retrieval from SAR Image

2015 ◽  
Vol 1092-1093 ◽  
pp. 47-51
Author(s):  
Xu Yan Fan ◽  
Peng Chen ◽  
Kai Guo Fan ◽  
Zhong Tang
Keyword(s):  
Wind Energy ◽  
Surface Wind ◽  
Sea Surface ◽  
Offshore Wind ◽  
Sar Image ◽  
Operational Method ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Business Application ◽  
Mean Square Errors

The high resolution offshore wind speeds retrieval from SAR image is of great signification in the field of offshore wind energy estimation. In this paper, one operational method for offshore wind speeds retrieval from SAR image is conducted. Taking one scene ENVISAT ASAR image as a case study, the offshore wind speeds is operational retrieved combing with the NCEP/QSCAT blended sea surface wind directions. The retrieved wind speeds are compared with those from both the NCEP/QSCAT blended sea surface wind speeds and daily averaged Quick Scatter meter sea surface wind speeds. The results show that they are in good agreement. The root mean square errors of wind speed are 1.9 m/s and 1.6 m/s respectively, which show that the operational method for offshore wind speeds retrieval from SAR is available and give the orientation of SAR offshore sea surface wind energy business application in the future.

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