Results 11 to 20 of about 868 (182)

Detection of Polar Mesospheric Clouds Utilizing Himawari‐8/AHI Full‐Disk Images

open access: yesEarth and Space Science, 2022
With the objective of advancing the polar mesospheric cloud (PMC) detection capability by the Advanced Himawari Imager (AHI) onboard the Japanese geostationary‐Earth‐orbit (GEO) meteorological satellite Himawari‐8, a novel two‐step PMC detection ...
T. T. Tsuda   +10 more
doaj   +1 more source

HOW WELL DOES SATELLITE FINE MODE AEROSOL PRODUCT VALIDATE WITH GROUND-BASED MEASUREMENTS FOR MODIS AND HIMAWARI-8? [PDF]

open access: yesThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Currently, the validation of MODIS and Himawari-8 aerosol products mostly focuses on AOD, but the validation of their fine mode aerosol data is limited. In this paper, 22 AERONET sites in Asia from 2015 to 2016 were selected to validate the MODIS and the
J. Jin   +10 more
doaj   +1 more source

A Machine Learning Algorithm for Himawari-8 Total Suspended Solids Retrievals in the Great Barrier Reef

open access: yesRemote Sensing, 2022
Remote sensing of ocean colour has been fundamental to the synoptic-scale monitoring of marine water quality in the Great Barrier Reef (GBR). However, ocean colour sensors onboard low orbit satellites, such as the Sentinel-3 constellation, have ...
Larissa Patricio-Valerio   +4 more
doaj   +1 more source

Initial report on polar mesospheric cloud observations by Himawari-8 [PDF]

open access: yesAtmospheric Measurement Techniques, 2018
We provide an initial report on polar mesospheric cloud (PMC) observations by the Japanese Geostationary Earth Orbit (GEO) meteorological satellite Himawari-8. Heights of the observed PMCs were estimated to be 80–82 km.
T. T. Tsuda   +6 more
doaj   +1 more source

Comparison of Himawari-8 AHI SST with Shipboard Skin SST Measurements in the Australian Region

open access: yesRemote Sensing, 2020
Sea surface temperature (SST) measurements from the geostationary satellite Himawari-8 Advanced Himawari Imager (AHI) are compared with in situ skin SSTs derived from shipboard Infrared SST Autonomous Radiometers (ISAR) in the Australian region. The mean
Minglun Yang   +5 more
doaj   +1 more source

Application of Empirical Orthogonal Function Analysis to 1 km Ensemble Simulations and Himawari–8 Observation in the Intensification Phase of Typhoon Hagibis (2019)

open access: yesAtmosphere, 2022
An empirical orthogonal function (EOF) analysis was performed for the inner core of Typhoon Hagibis (2019) in the intensification phase. The Himawari–8 geostationary infrared (IR) brightness temperature (BT) collocated at the Hagibis’s center was ...
Akiyoshi Wada   +2 more
doaj   +1 more source

The Deep‐Learning‐Based Fast Efficient Nighttime Retrieval of Thermodynamic Phase From Himawari‐8 AHI Measurements

open access: yesGeophysical Research Letters, 2023
Retrieval of the cloud thermodynamic phase (CP) is essential for satellite remote sensing and downstream applications. However, there is still a lack of efficient nighttime CP data products.
Xuan Tong   +6 more
doaj   +1 more source

Geolocation Accuracy Assessment of Himawari-8/AHI Imagery for Application to Terrestrial Monitoring

open access: yesRemote Sensing, 2020
Recent advancements in new generation geostationary satellites have facilitated the application of their datasets to terrestrial monitoring. In this application, geolocation accuracy is an essential issue because land surfaces are generally heterogeneous.
Yuhei Yamamoto   +3 more
doaj   +1 more source

Rainfall Forecast Using Machine Learning with High Spatiotemporal Satellite Imagery Every 10 Minutes

open access: yesRemote Sensing, 2022
Increasing the accuracy of rainfall forecasts is crucial as an effort to prevent hydrometeorological disasters. Weather changes that can occur suddenly and in a local scope make fast and precise weather forecasts increasingly difficult to inform ...
Febryanto Simanjuntak   +4 more
doaj   +1 more source

Assessment of Nighttime Cloud Cover Products from MODIS and Himawari-8 Data with Ground-Based Camera Observations

open access: yesRemote Sensing, 2022
Comparing cloud cover (CC) products from different satellites with the same ground-based CC dataset provides information on the similarities or differences of values among satellite products. For this reason, 42-month CC products from Moderate Resolution
Nofel Lagrosas   +3 more
doaj   +1 more source

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