17:15 〜 19:15
[ACG41-P12] 気候変動観測衛星GCOM-Cによる2023，2024年の高温が日本の展葉フェノロジーにもたらした影響の観測
キーワード：衛星リモートセンシング、GCOM-C/SGLI、気候変動、植物フェノロジー、Phenological Eyes Network (PEN)
In recent years, climate change has been recognized as a critical global issue. Notably, in 2023 and 2024, the world experienced abnormally high temperatures. Japan was among the most affected countries: it recorded the highest average temperature in 2023 since record-keeping began in 1891, surpassing the previous record set in 2020. Furthermore, the spring of 2024 also saw exceptionally high temperatures, highlighting the pronounced effects of climate change in Japan. There is an urgent need to detect the impacts of this warming on Japan’s ecosystems. These impacts of climate change have been shown to negatively affect vegetation. In this paper, we focus on vegetation phenology, which refers to seasonal events such as spring leaf flush phenology (SOS: Start of Season), flowering, autumn coloration, and leaf fall, all of which are strongly influenced by temperature. Changes in phenology serve as key indicators of climate change and may cause phenological mismatches. Such mismatches can, for instance, disrupt the synchrony between plants and their pollinators or herbivores, ultimately impacting entire ecosystems. The abnormally high temperatures in 2023 and the spring of 2024 may also have affected vegetation phenology. Gaining a deeper understanding of these changes, visualizing their impacts, and communicating them globally are crucial steps in addressing the ongoing challenges posed by climate change.
Traditionally, a lot of satellite-based vegetation phenology monitoring has relied on the National Aeronautics and Space Administration (NASA)'s Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. However, MODIS sensors have already exceeded their designed operational lifespan, and the Terra and Aqua satellites, which carry MODIS sensors, have been in operation for over 20 years. In recent years, maintaining their orbital stability has become increasingly challenging, raising concerns about a decline in data quality. Therefore, acquiring high-quality observation data for recent years, including 2023 and 2024, necessitates the use of alternative, reliable satellite sensors.
GCOM-C/SGLI (Global Change Observation Mission-Climate/Second-generation Global Imager), operated by the Japan Aerospace Exploration Agency (JAXA), presents an optimal alternative to meet these requirements. GCOM-C/SGLI began observations in 2018 and, despite exceeding its five-year design lifespan, continues to provide high-quality data. Several validation studies for phenology detection have already been conducted, demonstrating its advantages over MODIS, such as its higher spatial resolution (250 m) across multiple spectral bands. However, compared to MODIS, its usage remains limited.
In this study, we estimated the SOS for each spring from 2018 to 2024, using Chlorophyll Carotenoid Index (CCI) derived from GCOM-C/SGLI data. As a result, SOS occurs later in higher latitude areas compared with that in the lower ones, and at the same latitude, SOS occurs earlier in the coastal areas than in the inland areas. SOS occurred 3 to 7 days earlier than the 2018–2022 average in Kanto and Chubu regions in 2023 and in Tohoku and Hokuriku regions in 2024. Additionally, we found that air temperature has some influence on SOS: a 1 K rise in spring air temperature may shift SOS by an average of 4.4 days earlier nationwide. If this trend continues, extrapolating to the late 21st century (average of 2081–2100), SOS is projected to advance by approximately 7 days under the RCP2.6 scenario and by about 21 days under the RCP8.5 scenario compared to the late 20th century (average of 1986–2005). However, the reliability of future SOS predictions depends on several factors. This issue requires careful consideration and further discussion in future studies.
Furthermore, this content is currently under submission to Scientific Reports.
Traditionally, a lot of satellite-based vegetation phenology monitoring has relied on the National Aeronautics and Space Administration (NASA)'s Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. However, MODIS sensors have already exceeded their designed operational lifespan, and the Terra and Aqua satellites, which carry MODIS sensors, have been in operation for over 20 years. In recent years, maintaining their orbital stability has become increasingly challenging, raising concerns about a decline in data quality. Therefore, acquiring high-quality observation data for recent years, including 2023 and 2024, necessitates the use of alternative, reliable satellite sensors.
GCOM-C/SGLI (Global Change Observation Mission-Climate/Second-generation Global Imager), operated by the Japan Aerospace Exploration Agency (JAXA), presents an optimal alternative to meet these requirements. GCOM-C/SGLI began observations in 2018 and, despite exceeding its five-year design lifespan, continues to provide high-quality data. Several validation studies for phenology detection have already been conducted, demonstrating its advantages over MODIS, such as its higher spatial resolution (250 m) across multiple spectral bands. However, compared to MODIS, its usage remains limited.
In this study, we estimated the SOS for each spring from 2018 to 2024, using Chlorophyll Carotenoid Index (CCI) derived from GCOM-C/SGLI data. As a result, SOS occurs later in higher latitude areas compared with that in the lower ones, and at the same latitude, SOS occurs earlier in the coastal areas than in the inland areas. SOS occurred 3 to 7 days earlier than the 2018–2022 average in Kanto and Chubu regions in 2023 and in Tohoku and Hokuriku regions in 2024. Additionally, we found that air temperature has some influence on SOS: a 1 K rise in spring air temperature may shift SOS by an average of 4.4 days earlier nationwide. If this trend continues, extrapolating to the late 21st century (average of 2081–2100), SOS is projected to advance by approximately 7 days under the RCP2.6 scenario and by about 21 days under the RCP8.5 scenario compared to the late 20th century (average of 1986–2005). However, the reliability of future SOS predictions depends on several factors. This issue requires careful consideration and further discussion in future studies.
Furthermore, this content is currently under submission to Scientific Reports.