scholarly journals “Pixels May Lose Kelp Canopy”: The Photomosaic as Epistemic Figure for the Satellite Mapping and Modeling of Seaweeds

2021 ◽  
Author(s):  
Melody Jue
Keyword(s):  
Kelp Canopy ◽  
Satellite Mapping

Nowcasting with Data Assimilation: A Case of Global Satellite Mapping of Precipitation

2016 ◽  
Vol 31 (5) ◽  
pp. 1409-1416 ◽  
Author(s):  
Shigenori Otsuka ◽  
Shunji Kotsuki ◽  
Takemasa Miyoshi
Keyword(s):  
Data Assimilation ◽  
Space Time ◽  
Motion Vectors ◽  
The Past ◽  
Variational Techniques ◽  
Alternative Approach ◽  
Ensemble Transform Kalman Filter ◽  
Global Precipitation ◽  
Time Extrapolation ◽  
Satellite Mapping

Abstract Space–time extrapolation is a key technique in precipitation nowcasting. Motions of patterns are estimated using two or more consecutive images, and the patterns are extrapolated in space and time to obtain their future patterns. Applying space–time extrapolation to satellite-based global precipitation data will provide valuable information for regions where ground-based precipitation nowcasts are not available. However, this technique is sensitive to the accuracy of the motion vectors, and over the past few decades, previous studies have investigated methods for obtaining reliable motion vectors such as variational techniques. In this paper, an alternative approach applying data assimilation to precipitation nowcasting is proposed. A prototype extrapolation system is implemented with the local ensemble transform Kalman filter and is tested with the Japan Aerospace Exploration Agency’s Global Satellite Mapping of Precipitation (GSMaP) product. Data assimilation successfully improved the global precipitation nowcasting with the real-case GSMaP data.

Satellite mapping of tillage practices in the North Central US region from 2005 to 2016

2019 ◽  
Vol 221 ◽  
pp. 417-429 ◽  
Author(s):  
George Azzari ◽  
Patricio Grassini ◽  
Juan Ignacio Rattalino Edreira ◽  
Shawn Conley ◽  
Spyridon Mourtzinis ◽  
...  
Keyword(s):  
North Central ◽  
Tillage Practices ◽  
The North ◽  
Satellite Mapping

scholarly journals Spatiotemporal Evaluation of the Gauge-Adjusted Global Satellite Mapping of Precipitation at the Basin Scale

2016 ◽  
Vol 94 (2) ◽  
pp. 185-195 ◽  
Author(s):  
Kentaro TAKIDO ◽  
Oliver C. SAAVEDRA VALERIANO ◽  
Masahiro RYO ◽  
Kazuki TANUMA ◽  
Tomoo USHIO ◽  
...  
Keyword(s):  
Basin Scale ◽  
Satellite Mapping

scholarly journals KAJIAN KONDISI ATMOSFER DI WILAYAH INDONESIA SAAT PERIODE AKTIFNYA BADAI TROPIS KAI-TAK

2019 ◽  
Vol 3 ◽  
pp. 216
Author(s):  
Prabu Aditya Sugianto ◽  
Mukhamad Adib Azka ◽  
Reynold Mahubessy ◽  
Paulus Agus Winarso
Keyword(s):  
Tropical Cyclone ◽  
Moisture Transport ◽  
Weather Forecast ◽  
Northern Region ◽  
Moderate Intensity ◽  
Tropical Storms ◽  
Atmospheric Conditions ◽  
Air Masses ◽  
Tropical Depression ◽  
Satellite Mapping

<p class="AbstractEnglish"><strong><span lang="EN-GB">Abstract:</span></strong><span lang="EN-GB"> </span><span lang="EN">Tropical cyclone are weather phenomena that hardly occur in Indonesia, but their effects can affect atmospheric conditions in the Indonesian region, especially in areas near its growth. One of the tropical cyclones that occurred near the territory of Indonesia is Kai-Tak tropical cyclone. Kai-Tak tropical cyclone occurred on December 13-22, 2017 in Philippine waters. In this study, atmospheric conditions in the Indonesian region will be examined during the Kaitak tropical cyclone. The data used in this study are ECMWF reanalysis model data (European Center for Medium Weather Forecast) in the form of vorticity data, Moisture Transport, and wind speed and direction, and also satellite data, namely Himawari-8 satellite IR-1 channel for viewing distribution. spatial cloud propagation index occurring as well as the Global Satellite Mapping of Precipitation (GSMaP) satellite to see the spatial distribution of rainfall as a result of Kai-Tak tropical cyclone. The results showed that in the period December 13-16 2017, in the northern part of Sulawesi, the eastern part of Kalimantan Island, the northern region of Sulawesi Island to the northern part of Halmahera Island and parts of Southern Sumatra and Java were indirectly affected by tropical storms Kai -not where Kai-Tak tropical storms cause light to moderate intensity rainfall in the region. Whereas in the period of 17-22 December 2017 where the weak tropical storms (tropical depression) rainfall that occurred in most parts of Indonesia occurred due to the spread of air masses from Asia.</span></p><p class="KeywordsEngish"><strong><span lang="EN-GB">Abstrak:</span></strong><span lang="EN-GB"> Badai tropis merupakan fenomena cuaca yang hampir tidak terjadi di Indonesia, tetapi dampaknya dapat mempengaruhi kondisi atmosfer di wilayah Indonesia khususnya di wilayah dekat pertumbuhannya. Salah satu badai tropis yang terjadi di dekat wilayah Indonesia yaitu badai tropis Kai-tak.  Badai tropis Kai-tak terjadi pada periode 13-22 Desember 2017 di perairan Filipina. Pada penelitian ini akan dikaji kondisi atmosfer di wilayah Indonesia pada saat  terjadinya badai tropis Kaitak. Data yang digunakan dalam penelitian ini yaitu data model <em>reanalysis </em>ECMWF (European Centre for Medium Weather Forecast) berupa data vortisitas,<em>Moisture Transport</em>, serta arah dan kecepatan angin, Selain itu digunakan juga data satelit yaitu satelit Himawari-8 kanal IR-1 untuk melihat distribusi spasial indeks konvektif sebaran awan yang terjadi serta satelit  <em>Global Satellite Mapping of Precipitation</em> (GSMaP) untuk melihat distribusi spasial curah hujan sebagai dampak dari badai tropis Kai-tak. Hasil penelitian menunjukkan bahwa pada periode 13-16 Desember 2017 , di wilayah Sulawesi bagian utara,wilayah Pulau Kalimantan bagian timur,wilayah utara Pulau Sulawesi hingga wilayah utara Pulau Halmahera serta sebagian Sumatera bagian Selatan dan Pulau Jawa terkena dampak secara tidak langsung dari badai tropis Kai-tak dimana badai tropis Kai-tak mengakibatkan hujan dengan intensitas ringan hingga sedang di wilayah tersebut.  Sedangkan pada periode 17-22 Desember 2017 dimana badai tropis melemah (tropical depression) curah hujan yang terjadi di sebagian besar wilayah Indonesia terjadi akibat adanya penjalaran massa udara dari Asia.</span></p>

scholarly journals A Comparison Between Global Satellite Mapping of Precipitation Data and High-Resolution Radar Data – A Case Study of Localized Torrential Rainfall over Japan

2021 ◽  
Vol 16 (4) ◽  
pp. 786-793
Author(s):  
Yoshiaki Hayashi ◽  
Taichi Tebakari ◽  
Akihiro Hashimoto ◽  
◽  
Keyword(s):  
High Resolution ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Radar Data ◽  
Rain Gauge ◽  
Hourly Rainfall ◽  
The Difference ◽  
Microwave Imager ◽  
Satellite Mapping

This paper presents a case study comparing the latest algorithm version of Global Satellite Mapping of Precipitation (GSMaP) data with C-band and X-band Multi-Parameter (MP) radar as high-resolution rainfall data in terms of localized heavy rainfall events. The study also obliged us to clarify the spatial and temporal resolution of GSMaP data using high-accuracy ground-based radar, and evaluate the performance and reporting frequency of GSMaP satellites. The GSMaP_Gauge_RNL data with less than 70 mm/day of daily rainfall was similar to the data of both radars, but the GSMaP_Gauge_RNL data with over 70 mm/day of daily rainfall was not, and the calibration by rain-gauge data was poor. Furthermore, both direct/indirect observations by the Global Precipitation Measurement/Microwave Imager (GPM/GMI) and the frequency thereof (once or twice) significantly affected the difference between GPM/GMI data and C-band radar data when the daily rainfall was less than 70 mm/day and the hourly rainfall was less than 20 mm/h. Therefore, it is difficult for GSMaP_Gauge to accurately estimate localized heavy rainfall with high-density particle precipitation.

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