ANALISIS RETRACKING WAVEFORM DATA SATELIT ALTIMETER PADA TELUK, PERAIRAN PULAU-PULAU KECIL, DAN LAUT DALAM DI LAUT HALMAHERA

Akurasi estimasi tinggi muka laut (SSH) dari satelit altimeter sangat dipengaruhi oleh kondisi perairan dan daratan disekitar perairan tersebut. Estimasi SSH di laut lepas umumnya sudah akurat. Namun, pada daerah pantai, estimasi SSH kurang akurat karena gangguan pantulan sinyal dari daratan. Penelitian ini bertujuan untuk melakukan analisis retracking waveform satelit altimeter pada perairan yang kompleks di Laut Halmahera. Data yang digunakan pada penelitian ini yaitu data waveform dari Sensor Geophysical Data Record type D (SGDR-D) Jason-2 dan Jason-3 tahun 2017. Algoritma retracking yang digunakan yaitu Offset Centre of Gravity (OCOG), Iced, Threshold, dan Improved Threshold. Hasil retracking waveform menunjukkan semua retracker memberikan perbaikan data SSH yang signifikan kecuali OCOG. Retracker yang paling cocok diaplikasikan di Laut Halmahera pada teluk dangkal dan sempit yaitu Threshold 10%, pada teluk dalam dan lebar yaitu Threshold 50%, serta pada perairan dekat pulau pulau kecil yaitu Threshold 10% dan Threshold 20%. Secara umum, Non-Brown waveform lebih banyak ditemukan di perairan teluk dangkal dan sempit (rata-rata=63,49%) dibandingkan dengan teluk dalam dan lebar (rata-rata=11,51%) dan perairan pulau-pulau kecil (rata-rata=9,57%). Namun demikian, tingkat perbaikan data SSH di perairan teluk dangkal dan sempit lebih tinggi dibandingkan dengan teluk dalam dan lebar serta perairan pulau-pulau kecil dan laut dalam. Persentase peningkatan perbaikan data (IMP) tertinggi yaitu 96,71% dengan algoritma Improved Threshold 10% pada Jason-2 pass 164.

Coastal Waveform Retracking in the Slick-Rich Sulawesi Sea of Indonesia, Based on Variable Footprint Size with Homogeneous Sea Surface Roughness

Waveforms of radar altimeters are often corrupted due to heterogeneous sea surface roughness within footprints, such as slicks. In past studies, subwaveform retrackers such as the adaptive leading edge subwaveform retracker (ALES) which use only a section of the waveform have been proposed. However, it is difficult to choose a reasonable estimation window from an individual waveform. In the present study, a post-processed subwaveform retracker is proposed which identifies the waveforms of surrounding along-track points. The size of the estimation window is variable and is determined to keep the sea surface roughness within the corresponding footprint homogeneous. The method was applied to seven years of 20 Hz Jason-2 altimeter data over the slick-rich Sulawesi Sea of Indonesia and compared with ALES and sensor geophysical data record (SGDR) products. The standard deviation of the sea surface dynamic heights was around 0.13 m, even without spatial smoothing or some geophysical corrections. This is only 75% and 25% of the ALES and SGDR results, respectively. Moreover, all retrievals of the range, SWH, and sigma0 include less outliers than the other products. These results indicate that the variable estimation windows determined in the present study can adapt well to the variation of sea surface roughness.

Evaluation and Validation of CryoSat-2-Derived Water Levels Using In Situ Lake Data from China

CryoSat-2 altimetry has become a valuable tool for monitoring the water level of lakes. In this study, a concentrated probability density function (PDF) method was proposed for preprocessing CryoSat-2 Geophysical Data Record (GDR) data. CryoSat-2 altimetry water levels were preprocessed and evaluated by in situ gauge data from 12 lakes in China. Results showed that the accuracy of the raw GDR data was limited due to outliers in most of the along-track segments. The outliers were generally significantly lower than the in situ values by several meters, and some by more than 30 m. Outlier detection, therefore, improves upon the accuracy of CryoSat-2 measurements. The concentrated PDF method was able to greatly improve the accuracy of CryoSat-2 measurements. The preprocessed CryoSat-2 measurements were able to observe lake levels with a high accuracy at nine of the twelve lakes, with an absolute mean difference of 0.09 m, an absolute standard deviation difference of 0.04 m, a mean root mean square error of 0.27 m, and a mean correlation coefficient of 0.84. Overall, the accuracy of CryoSat-2-derived lake levels was validated in China. In addition, the accuracy of Database for Hydrological Time Series of Inland Waters (DAHITI) and HYDROWEB water level products was also validated by in situ gauge data.

Calibration and Validation of Reprocessed HY-2A Altimeter Wave Height Measurements Using Data from Buoys, Jason-2, Cryosat-2, and SARAL/AltiKa

The Haiyang-2A (HY-2A) satellite is China’s first ocean dynamic environment satellite, and the radar altimeter is one of its main payloads. In this study the HY-2A altimeter sensor interim geophysical dataset records (SIGDR) data are reprocessed to obtain better significant wave height (Hs) measurements over a period of more than four years (from 1 October 2011 to 15 March 2016). The reprocessed HY-2A Hs measurements are calibrated and validated using National Data Buoy Center (NDBC) buoys and several operating altimeters: Joint Altimetry Satellite Oceanography Network-2 (Jason-2), CryoSat-2, and Satellite with Argos Data Collection System and Ka-Band Altimeter (SARAL/ALtiKa) The final results of buoys and cross-altimeter comparisons show that the accuracy of the reprocessed HY-2A Hs measurements is significantly improved with respect to the Hs measurements in the operational HY-2A interim geophysical data record (IGDR) publicly distributed by the National Satellite Ocean Application Service (NSOAS), State Oceanic Administration (SOA) of China. Compared with the NDBC Hs measurements, the reprocessed HY-2A Hs measurements show a root-mean-square error (RMSE) of 0.215 m with a positive bias of 0.117 m. After calibrating with the two-branched corrections, the RMSE for the reprocessed HY-2A Hs measurements is reduced to 0.173 m, which is lower than those for the calibrated HY-2A IGDR, Jason-2, Cryosat-2, and SARAL measurements with an RMSE of 0.278, 0.233, 0.239, and 0.184 m, respectively. Long-term validation of the altimeter Hs measurements shows that the reprocessed HY-2A Hs measurements after calibration are stable with respect to the buoys and three other altimeters over the entire period. The reprocessed HY-2A Hs measurements are expected to improve the practical applicability of HY-2A Hs measurements significantly.

WAVEFORM IDENTIFICATION OF ALTIMETRY SATELLITE DATA OF SHALLOW AND DEEP WATERS IN SOUTHERN JAVA WATERS

<p><strong><em>ABSTRACT</em></strong></p> <p><em>Waveform patterns of satellite altimetry affect the accuracy of sea surface height estimation from the satellite. The waveform</em><em> patterns found in the coastal waters are generally not in the ideal form (Brown-waveform), resulting inaccurate in sea surface height estimation. The objec-tives of this research were to identify patterns of the waveform and determine their variability. Satellite altimetry Jason-2 SGDR</em> (<em>Sensor Geophysical Data Record</em>) <em>type D data located in the southern Java island waters of the year of 2013 were used and downloaded from “NOAA's Comprehensive Large Array-data Stewardship System</em>”<em> (www.class.ncdc.noaa.gov)<em> </em><a href="http://www.class.ncdc.noaa.gov"><em></em></a><em></em></em><em>.</em> <em>Waveform identification and analyses were conducted along the satel</em><em>l</em><em>it</em><em>e</em><em> pass within the distance of 0-10 km, 10-50 km, and 50-100 km form the coastline. Results showed that the highest number of non-Brown-waveform was found within 0-10 km of the coastline (69%). Meanwhile, within the distance of 10-50 km and 50-100 km from the coastline, the number of non-Brown waveform was 5% and 3%, respectively. Brown waveform patterns could be found generally starting at 7.58 km from the coastline</em>. <em>Factors such as</em><em> land near coastal waters, the depth and shape of the surface waters, aerosols in the atmosphere, building (example: lighthouse or ship) found in coastal areas suspected to be the cause of the noise in waveforms.</em></p> <p><strong><em> </em></strong></p> <strong><em>Keywords: </em></strong><em>Borwn and non-Brown waveform, sea level height, altimetry satellite, identification</em>

WAVEFORM IDENTIFICATION OF ALTIMETRY SATELLITE DATA OF SHALLOW AND DEEP WATERS IN SOUTHERN JAVA WATERS

ABSTRACT Waveform patterns of satellite altimetry affect the accuracy of sea surface height estimation from the satellite. The waveform patterns found in the coastal waters are generally not in the ideal form (Brown-waveform), resulting inaccurate in sea surface height estimation. The objec-tives of this research were to identify patterns of the waveform and determine their variability. Satellite altimetry Jason-2 SGDR (Sensor Geophysical Data Record) type D data located in the southern Java island waters of the year of 2013 were used and downloaded from “NOAA's Comprehensive Large Array-data Stewardship System” (www.class.ncdc.noaa.gov) . Waveform identification and analyses were conducted along the satellite pass within the distance of 0-10 km, 10-50 km, and 50-100 km form the coastline. Results showed that the highest number of non-Brown-waveform was found within 0-10 km of the coastline (69%). Meanwhile, within the distance of 10-50 km and 50-100 km from the coastline, the number of non-Brown waveform was 5% and 3%, respectively. Brown waveform patterns could be found generally starting at 7.58 km from the coastline. Factors such as land near coastal waters, the depth and shape of the surface waters, aerosols in the atmosphere, building (example: lighthouse or ship) found in coastal areas suspected to be the cause of the noise in waveforms. Keywords: Borwn and non-Brown waveform, sea level height, altimetry satellite, identification

A Global View on the Swell and Wind Sea Climate by the Jason-1 Mission: A Revisit

In this study, a global climatology of swells and wind seas was investigated using near-10-yr collocated wind speed and significant wave height (SWH) measurements from the basic Geophysical Data Record (GDR) of the Jason-1 mission. A statistical method to estimate the wind sea and swell SWHs, respectively, on the basis of wave energy and wind sea/swell probability was proposed. The global distributions of swell/wind sea probability displayed the swell's dominance in the World Ocean. Their seasonal variation showed not only the regions called “swell pools” with high swell probability throughout the year at low latitudes, which have been found in previous studies, but also the regions with high swell probability only in hemispheric summer, termed “seasonal swell pools,” located at the midlatitudes of open oceans. The seasonal geographical patterns of the swell SWH were similar to those of the SWH due to the swell's dominance, and the patterns of the wind SWH were similar to those of the wind speed because of their well-coupled nature. The results could be used as a reference for related applications such as ocean engineering, seafaring, validation of wave models, and studies on climate change.