No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
PEMANFAATAN SATELIT ALTIMETRI UNTUK VERIFIKASI TINGGI GELOMBANG SIGNIFIKAN OCEAN FORECAST SYSTEM (OFS) – MODEL BMKG
... Nilai RMSE menunjukkan jauh atau dekatnya sebaran hasil model terhadap pengamatan lapangan. Semakin rendah nilainya semakin baik hasil model yang digunakan (Supriyadi, 2018 ...
Perairan Pantai Alau-Alau merupakan daerah pesisir yang dimanfaatkan sebagai kegiatan pariwisata dan juga kegiatan perikanan seperti bagan perahu. Peramalan tinggi gelombang sangat berguna untuk menghindari kejadian kecelakaan kapal ataupun hantaman ombak besar di sekitar kawasan pantai. Tujuan dari penelitian ini adalah untuk menganalisis tinggi gelombang signifikan di wilayah Pantai Alau-Alau, Kalianda, Lampung Selatan dan menganalisis tingkat akurasi model Wavewatch-III BMKG (Badan Meteorologi Klimatologi dan Geofisika) dengan data lapangan. Data dari Model Wavewatch-III divisualisasi menggunakan software GrADS, lalu dibandingkan dengan data pengukuran lapangan yang dilaksanakan selama 7 hari (20-26 November 2019). RMSE (Root Mean Square Error) digunakan untuk melihat akurasi dari model tersebut. Hasil penelitian pengukuran lapangan menunjukkan tinggi gelombang signifikan di Pantai Alau-Alau berkisar 0,082-0,405 meter. Hasil tinggi gelombang signifikan hasil model Wavewatch-III berkisar 0,027–0,118 meter. Hasil nilai RMSE model Wavewatch-III terhadap data lapangan sebesar 0,28. Alau-Alau Beach is a coastal area that used for tourism and fishery such as boat lift net. The forecast of wave height is very useful to avoid hitting big waves around coastal areas. The aims of this study are to analyze the significant wave height in the Alau-Alau Beach area, Kalianda, South Lampung and to analyze the accuracy of the Wavewatch-III BMKG (Climatology and Geophysics Meteorological Agency) with field data. Data of Wavewatch-III Model was visualized by using GrADS software, then compared it with field measurement data that was carried out for 7 days (20-26 November 2019). RMSE (Root Mean Square Error) was used in seing the accuracy of the model. The results from the field measurement showed that significant wave heights at Alau-Alau Beach ranged from 0.082 to 0.405 meters. The significant wave height from the Wavewatch-III model ranged from 0.027 to 0.118 meters. The results from the RMSE Wavewatch-III model on field data was 0.28.
... was categorized as moderate until a strong positive relationship [28] explained the diversity of satellite data. In Indonesia, water shows similar results that during one month (January) also resulted in a correlation of 0.69 [29]. The verification recapitulation in July 2018 -June 2019 is presented in Fig. 3b. ...
A limited number of marine meteorological instruments for making observations in Indonesian waters are problems in verifying the BMKG-OFS model. The satellite altimetry was selected as a verification tool due to its wide measurement range. The verification was carried out by adjusting the coordinates, time, and grid of SWH obtained and orbit of the satellite path from the satellite altimetry to the model and overlaying the models' results as a pattern analysis in July 2018 - June 2019. The next step was a statistical analysis to determine the performance of the model. The analysis obtained 43% maximum SWH formed due to the low-pressure centers in the Pacific Ocean. The remaining spreads across the South China Sea, Indian Ocean, Andaman Sea and the Gulf of Australia. This study revealed that the SWH values from satellites were higher than the model. On every three hourly and monthly bases, the SWH of the bias, RMSE, and correlation coefficient were equivalent. The lowest bias of 0.26 occurred at 9.00 UTC, the lowest RMSE of 0.48 occurred at 21:00 UTC, and the maximum correlation coefficient of 0.82 occurred at 18:00 UTC. Whereas on a monthly scale, the lowest bias and RMSE, and the maximum correlation coefficient occurred in November. Based on these results, the BMKG-OFS model can be used to predict SWH in Indonesian waters. Besides, this verification technique can be an alternative as a new tool to verify maritime weather in the operational of BMKG.
INA-WAVES is a wave model application developed by the Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG) and integrated into an Ocean Forecast System (OFS). It was derived from the wave spectrum model of Wave Watch III and utilized to provide many essential seas dynamics information. Because of the strategic role, it would be wise to verify the performance regularly. This study used altimetry data of Sentinel 3A and B to verify significant wave height (SWH) analysis data of INA-WAVES. The period of data was from October 2020 to August 2021. The authors demonstrated the data by a range category (qualitatively) and the root mean square error (RMSE) (quantitatively). The RMSE score assessed the model accuracy in six locations around Bali Island: two points in the Bali Sea, one in the southern Bali strait, and three in the south of Bali. Generally, a visual verification revealed that the percentage of equality between the model and the altimetry is promising, such as the Bali Sea (78.95%), the northern Bali Strait (90.91%), and the southern Lombok Strait (82.35%). In addition, the quantitative result confirmed that the Bali Sea has low RMSE values, 0.505 and 0.687 m. Unfortunately, the performance in the south of Bali (Indian Ocean), the Badung Strait, and the northern Lombok Strait should be evaluated further. In particular, in the Indian Ocean, the RMSE shows 1.267 m and 1.12 m.
Ni-based catalysts are an alternative to precious metal catalysts. However, monometallic Ni catalysts still have weaknesses, such as being easily deactivated and being able to agglomerate if the Ni concentration is too high. This can be overcome by adding a second metal (bimetallic catalyst) in which the structure and morphology of the bimetallic catalyst are strongly influenced by the method used. The wet-impregnation method is used to obtain a supported bimetallic catalyst where the order of metal carrying will affect the structure and morphology and is specific for each material. On the Ni-Zn/ZrO2 catalyst, which has been synthesized by co-impregnation (Cat-1) and sequentially (Cat-2) method, XRD results show that both catalysts have specific peaks of ZrO2, NiO, and ZnO. However, the Cat-2 catalyst has lower crystallinity and smaller NiO crystallite size (14.79 nm) than Cat-1 (19.45 nm). Micrograph results show that both catalysts have irregular particle shapes. Cat-1 has a smaller particle size and a more homogeneous metal dispersion than Cat-2. The elemental analysis shows that metal concentration at the surface is close to the theoretical (10%). Further research with further characterization and application to a specific chemical reaction is needed to determine which of the two catalysts perform better. This is because each reaction has specific requirements, and each catalyst will produce different results in each reaction even though they have the same properties.
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.
We examine the issue of sustained measurements of sea level in the coastal zone, first by summarizing the long-term observations from tide gauges, then showing how those are now complemented by improved satellite altimetry products in the coastal ocean. We present some of the progresses in coastal altimetry, both from dedicated reprocessing of the radar waveforms and from the development of improved corrections for the atmospheric effects. This trend towards better altimetric data at the coast comes also from technological innovations such as Ka-band altimetry and SAR altimetry, and we discuss the advantages deriving from the AltiKa Ka-band altimeter and the SIRAL altimeter on CryoSat-2 that can be operated in SAR mode. A case study along the UK coast demonstrates the good agreement between coastal altimetry and tide gauge observations, with root mean square differences as low as 4 cm at many stations, allowing the characterization of the annual cycle of sea level along the UK coasts. Finally, we examine the evolution of the sea level trend from the open to the coastal ocean along the western coast of Africa, comparing standard and coastally improved products. Different products give different sea level trend profiles, so the recommendation is that additional efforts are needed to study sea level trends in the coastal zone from past and present satellite altimeters. Further improvements are expected from more refined processing and screening of data, but in particular from the constant improvements in the geophysical corrections.
The results of wave simulation in the Black Sea using the SWAN spectral wave model
and wind forcing data from the NCEP/CFSR reanalyze are presented in this paper.
The calculations were done using the special unstructured mesh with spatial resolution
of 10 km in the open sea and 200 m in the Tsemes Bay. The assessment of the wave
simulation accuracy was performed on the basis of the satellite altimetry data and direct
wave measurements in the shallow water. When comparing the calculated significant wave
height with observational data the correlation equaled 0.8, while the root mean square
error equaled 0.3. The comparison of simulation results and satellite data also showed
good correlation.
To characterize some of the world’s ocean physical processes such as its wave height, wind speed and sea surface elevation is a major need for coastal and marine infrastructure planning and design, tourism activities, wave power and storm surge risk assessment, among others. Over the last decades, satellite remote sensing tools have provided quasi-global measurements of ocean altimetry by merging data from different satellite missions. While there is a widely use of altimeter data for model validation, practical tools for model validation remain scarce. Our purpose is to fill this gap by introducing ALTWAVE, a MATLAB user-oriented toolbox for oceanographers and coastal engineers developed to validate wave model results based on visual features and statistical estimates against satellite derived altimetry. Our toolbox uses altimetry information from the GlobWave initiative, and provides a sample application to validate a one year wave hindcast for the Gulf of Mexico. ALTWAVE also offers an effective toolbox to validate wave model results using altimeter data, as well as a guidance for non-experienced satellite data users. This article is intended for wave modelers with no experience using altimeter data to validate their results.
Benefiting from the high spatiotemporal resolution and near-global coverage, satellite-based precipitation products are applied in many research fields. However, the applications of these products may be limited due to lack of information on the uncertainties. To facilitate applications of these products, it is crucial to quantify and document their error characteristics. In this study, four satellite-based precipitation products (TRMM-3B42, TRMM-3B42RT, CMORPH, GSMaP) were evaluated using gauge-based rainfall analysis based on a high-density gauge network throughout the Chinese Mainland during 2003-2006. To quantitatively evaluate satellite-based precipitation products, continuous (e.g., ME, RMSE, CC) and categorical (e.g., POD, FAR) verification statistics were used in this study. The results are as follows: (1) GSMaP and CMORPH underestimated precipitation (about -0.53 and -0.14 mm/day, respectively); TRMM-3B42RT overestimated precipitation (about 0.73 mm/day); TRMM-3B42, which is the only dataset corrected by gauges, had the best estimation of precipitation amongst all four products; (2) GSMaP, CMORPH and TRMM-3B42RT overestimated the frequency of low-intensity rainfall events; TRMM-3B42 underestimated the frequency of low-intensity rainfall events; GSMaP underestimated the frequency of high-intensity rainfall events; TRMM-3B42RT tended to overestimate the frequency of high-intensity rainfall events; TRMM-3B42 and CMORPH produced estimations of high-intensity rainfall frequency that best aligned with observations; (3) All four satellite-based precipitation products performed better in summer than in winter. They also had better performance over wet southern region than dry northern or high altitude regions. Overall, this study documented error characteristics of four satellite-based precipitation products over the Chinese Mainland. The results help to understand features of these datasets for users and improve algorithms for algorithm developers in the future.
Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency (Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational significant wave height (SWH) for more than three years (October 1, 2011 to present).We validated along-track Ku-band SWH data of HY-2 satellite against National Data Buoy Center (NDBC) in-situ measurements over a time period of three years from October 1, 2011 to September 30, 2014, the root mean square error (RMSE) and mean bias of HY-2 SWH is 0.38 m and (-0.13±0.35) m, respectively. We also did cross validation against Jason-2 altimeter SWH data,the RMSE and the mean bias is 0.36m and (-0.22±0.28) m, respectively. In order to compare the statistical results between HY-2 and Jason-2 satellite SWH data, we validated the Jason-2 satellite radar altimeter along-track Ku-band SWH data against NDBC measurements using the same method. The results demonstrate the validation method in this study is scientific and the RMSE and mean bias of Jason-2 SWH data is 0.26 m and (0.00±0.26) m, respectively. We also validated both HY-2 and Jason-2 SWH data every month, the mean bias of Jason-2 SWH data almost equaled to zero all the time, while the mean bias of HY-2 SWH data was no less than -0.31m before April 2013 and dropped to zero after that time. These results indicate that the statistical results for HY-2 altimeter SWH are reliable and HY-2 altimeter along-track SWH data were steady and of high quality in the last three years. The results also indicate that HY-2 SWH data have greatly been improved and have the same accuracy with Jason-2 SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.
SARAL AltiKa GDR-T are analysed to assess the quality of the significant wave height (SWH) measurements. SARAL along-track SWH plots reveal cases of erroneous data, more or less isolated, not detected by the quality flags. The anomalies are often correlated with strong attenuation of the Ka-band backscatter coefficient, very sensitive to clouds and rain. A quality test based on the 1 Hz standard deviation is proposed to detect such anomalies. From buoy comparison, it is shown that SARAL SWH is more accurate than Jason-2, particularly at low SWH, and globally does not require any correction. Results are better with open ocean than with coastal buoys. The scatter and the number of outliers are much larger for coastal buoys. SARAL is then compared with Jason-2 and Cryosat-2. The altimeter data are extracted from the global altimeter SWH Ifremer data base, including specific corrections to calibrate the various altimeters. The comparison confirms the high quality of SARAL SWH. The 1 Hz standard deviation is much less than for Jason-2 and Cryosat-2, particularly at low SWH. Furthermore, results show that the corrections applied to Jason-2 and to Cryosat-2, in the data base, are efficient, improving the global agreement between the three altimeters.
Subsurface coherent vortices in the North Atlantic, whose saline water originates from the Mediterranean Sea and which are known as Mediterranean eddies (meddies), have been of particular interest to physical oceanographers since their discovery, especially for their salt and heat transport properties into the North Atlantic Ocean. Many studies in the past have been successful in observing and studying the typical properties of meddies by probing them with in situ techniques. The use of remote sensing techniques would offer a much cheaper and easier alternative for studying these phenomena, but only a few past studies have been able to study meddies by remote sensing, and a reliable method for observing them remotely remains elusive. This research presents a new way of locating and tracking meddies in the North Atlantic Ocean using satellite altimeter data. The method presented in this research makes use of ensemble empirical mode decomposition (EEMD) as a means to isolate the surface expressions of meddies on the ocean surface and separates them from any other surface constituents, allowing robust meddies to be consistently tracked by satellite. One such meddy is successfully tracked over a 6-month time period (2 November 2005 to 17 May 2006). Results of the satellite tracking method are verified using expendable bathythermographs (XBT).
This paper describes wave climate and variability in the Gulf of Mexico based on a 30-years wave hindcast. The North American Regional Reanalysis wind fields (NCEP at NOAA) are employed to drive a third generation spectral wave model with high- spatial (0.005° - 0.06°) and temporal (3 hourly) resolution from 1979 through 2008. The wave hindcast information is validated using NDBC buoy data and altimeter wave information (GlobWave). The model performance is satisfactory (r2 ~0.90) in the Gulf of Mexico and to a lesser extent in the Caribbean Sea (r2~0.87) where only locally generated waves are considered. However, the waves generated by the Caribbean Low Level Jet (CLLJ) are discussed in this work. Subsequently, the yearly/monthly mean and extreme wave climates are characterized based on the (30-years) wave hindcast information. The model results show that the mean wave climate is mainly modulated by winter cold fronts (Nortes) in the Gulf of Mexico, whereas extreme wave climate is modulated by both hurricane and Norte events. Extreme wave heights in the Gulf of Mexico have increased at a rate of 0.07-0.08 m/yr in September/October, due to increased cyclone intensity in the last decade. However, there is no significant trend when considering the annual statistics for extreme events. Furthermore, modeling results also suggest that the CLLJ modulates the mean wave climate in the Caribbean Sea and controls the rate of mean wave height increase (0.03 m/yr) in the Caribbean. However, these later results need to be corroborated by extending the computational domain in order to include the swell coming from the Atlantic Ocean.
The applicability of altimeter data for the coastal region is examined by comparing the gridded multi-mission and along-track mono-mission significant wave height (SWH) data with the in situ buoy measurements at four stations off the east and west coasts of India. Among all of the satellites, a greater number of collocated points and better correlation were found for Jason-2. A comparison of the SWH data from multi-mission products (Jason-1, Jason-2, Envisat, and ERS-2) obtained from AVISO with the measured buoy data shows that all of the satellites overestimated the SWH. Applying a correction factor of 0.75, 0.70 and 0.69 to the altimeter data for stations 1, 2 and 4, respectively, resulted in close agreement with the buoy data (correlation coefficient ~0.9–0.96). Monthly averaged buoy and altimeter SWH values show convincing correlation ranging from 0.97 to 0.98 for three stations. The smallest correlation coefficient (0.6) was found at station 3, where the selected grid points are located close to the coast and are influenced by land contamination and wave decay effects. For waves with a SWH<0.5 m, the correlation coefficient is sparingly low for all stations, which underlines the fact that the altimeter observations for SWH<0.5 m are unreliable.
Integrations of GIS and Remote Sensing
- V Mesev
V. Mesev, Integrations of GIS and Remote
Sensing. UK: John Wiley & Sons, Ltd, pp. 1
-13, 2007.
An Introductory Study on Time Series Modeling and Forecasting
- R Adikari
R. Adikari, & R. K. Agrawal, "An Introductory
Study on Time Series Modeling and
Forecasting."
Internet:
https://arxiv.org/ftp/arxiv/papers/1302/1302.
6613.pdf, di akses 8 Maret 2019.
Satelit Altimetri dan aplikasinya dalam bidang kelautan, Pertemuan Ilmiah Tahunan I Teknik Geodesi -ITS Surabaya
- E Y Handoko
E. Y. Handoko, 2004, Satelit Altimetri dan
aplikasinya
dalam
bidang
kelautan,
Pertemuan Ilmiah Tahunan I Teknik
Geodesi -ITS Surabaya, pp. 137 -144.
Pokok-Pokok Materi Statistik 1 (Statistik Deskriptif)
- M I Hasan
M. I. Hasan, Pokok-Pokok Materi Statistik 1
(Statistik Deskriptif). Jakarta: Bumi Aksara,
pp. 227 -261, 2001.