scholarly journals Wind-Driven Coastal Upwelling in the Southern Coast of Yogyakarta

2018 ◽  
Vol 20 (1) ◽  
pp. 13
Author(s):  
Faizal Rachman ◽  
Ratih Ida Adharini ◽  
Riza Yuliratno Setiawan ◽  
Indun Dewi Puspita ◽  
Endy Triyannanto

Satellite measurement provides synoptic view of sea surface wind and can be used to study variability of coastal upwelling. Here we analyzed data of 12 years of satellite-derived sea surface wind, sea surface temperature (SST), and sea surface chlorophyll-a (Chl-a) to examine the spatial and temporal distributions of coastal upwelling off the Yogyakarta waters. Results show that upwelling occurs during the Southeast Monsoon (SEM) season. During this season, the Yogyakarta waters are dominated by strong wind speed (~7 m/s) and SST cooling (25 °C). Whereas during the Northwest Monsoon (NWM) season the low wind speed (<4 m/s) no longer favor upwelling and SST cooling. We suggest that as the Yogyakarta coastline is oriented east-west, northwesterly winds result in downwelling condition at the coast, while southeasterly winds lead to the offshore Ekman transport of surface water and subsequent upwelling.

2021 ◽  
Vol 925 (1) ◽  
pp. 012045
Author(s):  
Avrionesti ◽  
Faruq Khadami ◽  
Dayu W Purnaningtyas

Abstract Tropical Cyclone (TC) Seroja is a unique tropical cyclone that has significant impacts along its path, such as floods in East Nusa Tenggara and high waves along the southern coast of Indonesia. Research related to ocean responses to tropical cyclones in Indonesia is still limited due to its rarely occurence in Indonesian waters. The responses of the upper ocean to TC Seroja were investigated using multi-satellite remote sensing of sea surface wind (SSW), sea surface temperature (SST), sea surface height anomaly (SSHA), and numerical model of mixed layer depth (MLD) and chlorophyll-a (Chl-a). The SST cooling occurred around the TC Seroja track at 0.5 – 3°C after the storm had passed. During April 3 – 7, 2021, in addition to spatial SST cooling, changes in chlorophyll-a, SSHA, and MLD were also detected. The chlorophyll-a increase to 2.57 mg/m3 and SSHA reached -10 cm. Thus, the MLD was deeper around the eye of the storm during the cyclone and became uniform after the storm passed. These characteristics indicate the upwelling phenomenon induced by the cyclone.


2011 ◽  
Vol 29 (2) ◽  
pp. 393-399
Author(s):  
T. I. Tarkhova ◽  
M. S. Permyakov ◽  
E. Yu. Potalova ◽  
V. I. Semykin

Abstract. Sea surface wind perturbations over sea surface temperature (SST) cold anomalies over the Kashevarov Bank (KB) of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT) data during the summer-autumn period of 2006–2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August–September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 °C and wind speed lowered down to ~7 m s−1 relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of ~0.3 m s−1 on 1 °C.


2012 ◽  
Vol 32 (8) ◽  
pp. 0828002
Author(s):  
Wu Dong ◽  
Zhang Xiaoxue ◽  
Yan Fengqi ◽  
Liu Zhaoyan

2016 ◽  
Vol 33 (7) ◽  
pp. 1363-1375 ◽  
Author(s):  
Sungwook Hong ◽  
Hwa-Jeong Seo ◽  
Young-Joo Kwon

AbstractThis study proposes a sea surface wind speed retrieval algorithm (the Hong wind speed algorithm) for use in rainy and rain-free conditions. It uses a combination of satellite-observed microwave brightness temperatures, sea surface temperatures, and horizontally polarized surface reflectivities from the fast Radiative Transfer for TOVS (RTTOV), and surface and atmospheric profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF). Regression relationships between satellite-observed brightness temperature and satellite-simulated brightness temperatures, satellite-simulated brightness temperatures, rough surface reflectivities, and between sea surface roughness and sea surface wind speed are derived from the Advanced Microwave Scanning Radiometer 2 (AMSR-2). Validation results of sea surface wind speed between the proposed algorithm and the Tropical Atmosphere Ocean (TAO) data show that the estimated bias and RMSE for AMSR-2 6.925- and 10.65-GHz bands are 0.09 and 1.13 m s−1, and −0.52 and 1.21 m s−1, respectively. Typhoon intensities such as the current intensity (CI) number, maximum wind speed, and minimum pressure level based on the proposed technique (the Hong technique) are compared with best-track data from the Japan Meteorological Agency (JMA), the Joint Typhoon Warning Center (JTWC), and the Cooperative Institute for Mesoscale Meteorological Studies (CIMSS) for 13 typhoons that occurred in the northeastern Pacific Ocean throughout 2012. Although the results show good agreement for low- and medium-range typhoon intensities, the discrepancy increases with typhoon intensity. Consequently, this study provides a useful retrieval algorithm for estimating sea surface wind speed, even during rainy conditions, and for analyzing characteristics of tropical cyclones.


2019 ◽  
Vol 11 (2) ◽  
pp. 153 ◽  
Author(s):  
Yuan Gao ◽  
Changlong Guan ◽  
Jian Sun ◽  
Lian Xie

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.


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