2024 Vol. 30, No. 1
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2024, 30(1): .
Abstract:
2024, 30(1): 1-10.
doi: 10.3724/j.1006-8775.2024.001
Abstract:
Drought events have become more frequent and intense over East Asia in recent decades, leading to huge socioeconomic impacts. Although the droughts have been studied extensively by cases or for individual regions, their leading variability and associated causes remain unclear. Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and ERA5 reanalysis product from 1979 to 2020, this study evealuates the severity of spring droughts in East Asia and investigates their variations and associated drivers. The results indicate that North China and Mongolia have experienced remarkable trends toward dryness during spring in recent decades, while southwestern China has witnessed an opposite trend toward wetness. The first Empirical Orthogonal Function mode of SPEI variability reveals a similar seesawing pattern, with more severe dryness in northwestern China, Mongolia, North China, South Korea, and Japan but increased wetness in Southwestern China and southeast Asia. Further investigation reveals that the anomalously dry (wet) surface in North (Southwestern) China is significantly associated with anomalously high (low) temperature, less (more) precipitation, and reduced (increased) soil moisture during the previous winter and early spring, regulated by an anomalous anticyclone (cyclone) and thus reduced (increased) water vapor convergence. The spring dry-wet pattern in East Asia is also linked to cold sea surface temperature anomalies in the central-eastern Pacific. The findings of this study have important implications for improving the prediction of spring drought events in East Asia.
Drought events have become more frequent and intense over East Asia in recent decades, leading to huge socioeconomic impacts. Although the droughts have been studied extensively by cases or for individual regions, their leading variability and associated causes remain unclear. Based on the Standardized Precipitation Evapotranspiration Index (SPEI) and ERA5 reanalysis product from 1979 to 2020, this study evealuates the severity of spring droughts in East Asia and investigates their variations and associated drivers. The results indicate that North China and Mongolia have experienced remarkable trends toward dryness during spring in recent decades, while southwestern China has witnessed an opposite trend toward wetness. The first Empirical Orthogonal Function mode of SPEI variability reveals a similar seesawing pattern, with more severe dryness in northwestern China, Mongolia, North China, South Korea, and Japan but increased wetness in Southwestern China and southeast Asia. Further investigation reveals that the anomalously dry (wet) surface in North (Southwestern) China is significantly associated with anomalously high (low) temperature, less (more) precipitation, and reduced (increased) soil moisture during the previous winter and early spring, regulated by an anomalous anticyclone (cyclone) and thus reduced (increased) water vapor convergence. The spring dry-wet pattern in East Asia is also linked to cold sea surface temperature anomalies in the central-eastern Pacific. The findings of this study have important implications for improving the prediction of spring drought events in East Asia.
2024, 30(1): 11-19.
doi: 10.3724/j.1006-8775.2024.002
Abstract:
The South China Sea is a hotspot for regional climate research. Over the past 40 years, considerable improvement has been made in the development and utilization of the islands in the South China Sea, leading to a substantial change in the land-use of the islands. However, research on the impact of human development on the local climate of these islands is lacking. This study analyzed the characteristics of local climate changes on the islands in the South China Sea based on data from the Yongxing Island Observation Station and ERA5 re-analysis. Furthermore, the influence of urbanization on the local climate of the South China Sea islands was explored in this study. The findings revealed that the 10-year average temperature in Yongxing Island increased by approximately 1.11 ℃ from 1961 to 2020, and the contribution of island development and urbanization to the local warming rate over 60 years was approximately 36.2%. The linear increasing trend of the annual hot days from 1961–2020 was approximately 14.84 days per decade. The diurnal temperature range exhibited an increasing trend of 0.05 ℃ per decade, whereas the number of cold days decreased by 1.06 days per decade. The rapid increase in construction on Yongxing Island from 2005 to 2021 led to a decrease in observed surface wind speed by 0.32 m s–1 per decade. Consequently, the number of days with strong winds decreased, whereas the number of days with weak winds increased. Additionally, relative humidity exhibited a rapid decline from 2001 to 2016 and then rebounded. The study also found substantial differences between the ERA5 re-analysis and observation data, particularly in wind speed and relative humidity, indicating that the use of re-analysis data for climate resource assessment and climate change evaluation on island areas may not be feasible.
The South China Sea is a hotspot for regional climate research. Over the past 40 years, considerable improvement has been made in the development and utilization of the islands in the South China Sea, leading to a substantial change in the land-use of the islands. However, research on the impact of human development on the local climate of these islands is lacking. This study analyzed the characteristics of local climate changes on the islands in the South China Sea based on data from the Yongxing Island Observation Station and ERA5 re-analysis. Furthermore, the influence of urbanization on the local climate of the South China Sea islands was explored in this study. The findings revealed that the 10-year average temperature in Yongxing Island increased by approximately 1.11 ℃ from 1961 to 2020, and the contribution of island development and urbanization to the local warming rate over 60 years was approximately 36.2%. The linear increasing trend of the annual hot days from 1961–2020 was approximately 14.84 days per decade. The diurnal temperature range exhibited an increasing trend of 0.05 ℃ per decade, whereas the number of cold days decreased by 1.06 days per decade. The rapid increase in construction on Yongxing Island from 2005 to 2021 led to a decrease in observed surface wind speed by 0.32 m s–1 per decade. Consequently, the number of days with strong winds decreased, whereas the number of days with weak winds increased. Additionally, relative humidity exhibited a rapid decline from 2001 to 2016 and then rebounded. The study also found substantial differences between the ERA5 re-analysis and observation data, particularly in wind speed and relative humidity, indicating that the use of re-analysis data for climate resource assessment and climate change evaluation on island areas may not be feasible.
2024, 30(1): 20-28.
doi: 10.3724/j.1006-8775.2024.003
Abstract:
Tropical cyclone (TC) genesis forecasting is essential for daily operational practices during the typhoon season. The updated version of the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) offers forecasters reliable numerical weather prediction (NWP) products with improved configurations and fine resolution. While traditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesis forecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims to evaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South China Sea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has been proposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, predicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 h in advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors of operational models according to the annual evaluation. The study also briefly investigated the forecast of Noul (2011). The forecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, consistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized three-dimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis, fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.
Tropical cyclone (TC) genesis forecasting is essential for daily operational practices during the typhoon season. The updated version of the Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) offers forecasters reliable numerical weather prediction (NWP) products with improved configurations and fine resolution. While traditional evaluation of typhoon forecasts has focused on track and intensity, the increasing accuracy of TC genesis forecasts calls for more comprehensive evaluation methods to assess the reliability of these predictions. This study aims to evaluate the effectiveness of the CMA-TRAMS for cyclogenesis forecasts over the western North Pacific and South China Sea. Based on previous research and typhoon observation data over five years, a set of localized, objective criteria has been proposed. The analysis results indicate that the CMA-TRAMS demonstrated superiority in cyclogenesis forecasts, predicting 6 out of 22 TCs with a forecast lead time of up to 144 h. Additionally, over 80% of the total could be predicted 72 h in advance. The model also showed an average TC genesis position error of 218.3 km, comparable to the track errors of operational models according to the annual evaluation. The study also briefly investigated the forecast of Noul (2011). The forecast field of the CMA-TRAMS depicted thermal and dynamical conditions that could trigger typhoon genesis, consistent with the analysis field. The 96-hour forecast field of the CMA-TRAMS displayed a relatively organized three-dimensional structure of the typhoon. These results can enhance understanding of the mechanism behind typhoon genesis, fine-tune model configurations and dynamical frameworks, and provide reliable forecasts for forecasters.
2024, 30(1): 29-41.
doi: 10.3724/j.1006-8775.2024.004
Abstract:
This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts (ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation (MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon "Rumbia" as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects' forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and long-lifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and short-lifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan (such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model's simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.
This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts (ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation (MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon "Rumbia" as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects' forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and long-lifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and short-lifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan (such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model's simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.
2024, 30(1): 42-50.
doi: 10.3724/j.1006-8775.2024.005
Abstract:
The properties of salinity in the South China Sea (SCS), a significant marginal sea connecting the Pacific and Indian Oceans, are greatly influenced by the transport of fresh water flux between the two oceans. However, the long-term changes in the intermediate water in the SCS have not been thoroughly studied due to limited data, particularly in relation to its thermodynamic variations. This study utilized reanalysis data products to identify a 60-year trend of freshening in the intermediate waters of the northern South China Sea (NSCS), accompanied by an expansion of low-salinity water. The study also constructed salinity budget terms, including advection and entrainment processes, and conducted an analysis of the salinity budget to understand the impacts of external and internal dynamic processes on the freshening trend of the intermediate water in the NSCS. The analysis revealed that the freshening in the northwest Pacific Ocean and the intensification of intrusion through the Luzon Strait at intermediate levels are the primary drivers of the salinity changes in the NSCS. Additionally, a weakened trend in the intensity of vertical entrainment also contributes to the freshening in the NSCS. This study offers new insights into the understanding of regional deep sea changes in response to variations in both thermodynamics and oceanic dynamic processes.
The properties of salinity in the South China Sea (SCS), a significant marginal sea connecting the Pacific and Indian Oceans, are greatly influenced by the transport of fresh water flux between the two oceans. However, the long-term changes in the intermediate water in the SCS have not been thoroughly studied due to limited data, particularly in relation to its thermodynamic variations. This study utilized reanalysis data products to identify a 60-year trend of freshening in the intermediate waters of the northern South China Sea (NSCS), accompanied by an expansion of low-salinity water. The study also constructed salinity budget terms, including advection and entrainment processes, and conducted an analysis of the salinity budget to understand the impacts of external and internal dynamic processes on the freshening trend of the intermediate water in the NSCS. The analysis revealed that the freshening in the northwest Pacific Ocean and the intensification of intrusion through the Luzon Strait at intermediate levels are the primary drivers of the salinity changes in the NSCS. Additionally, a weakened trend in the intensity of vertical entrainment also contributes to the freshening in the NSCS. This study offers new insights into the understanding of regional deep sea changes in response to variations in both thermodynamics and oceanic dynamic processes.
2024, 30(1): 51-60.
doi: 10.3724/j.1006-8775.2024.006
Abstract:
The movement speed of Typhoon In-Fa (2021) was notably slow, at 10 km h−1 or less, for over 20 hours following its landfall in Zhejiang, China, in contrast to other typhoons that have made landfall. This study examines the factors contributing to the slow movement of Typhoon In-Fa, including the steering flow, diabatic heating, vertical wind shear (VWS), and surface synoptic situation, by comparing it with Typhoons Yagi (2018) and Rumbia (2018) which followed similar tracks. The findings reveal that the movement speed of Typhoons Yagi and Rumbia is most closely associated with their respective 500 hPa environmental winds, with a steering flow of 10–12 m s−1. In contrast, Typhoon In-Fa's movement speed is most strongly correlated with the 850 hPa environmental wind field, with a steering flow speed of only 2 m s−1. Furthermore, as Typhoon In-Fa moves northwest after landfall, its intensity is slightly greater than that of Typhoons Yagi and Rumbia, and the pressure gradient in front of Typhoon In-Fa is notably smaller, leading to its slow movement. Additionally, the precipitation distribution of Typhoon In-Fa differs from that of the other two typhoons, resulting in a weak asymmetry of wavenumber-1 diabatic heating, which indirectly affects its movement speed. Further analysis indicates that VWS can alter the typhoon's structure, weaken its intensity, and ultimately impact its movement.
The movement speed of Typhoon In-Fa (2021) was notably slow, at 10 km h−1 or less, for over 20 hours following its landfall in Zhejiang, China, in contrast to other typhoons that have made landfall. This study examines the factors contributing to the slow movement of Typhoon In-Fa, including the steering flow, diabatic heating, vertical wind shear (VWS), and surface synoptic situation, by comparing it with Typhoons Yagi (2018) and Rumbia (2018) which followed similar tracks. The findings reveal that the movement speed of Typhoons Yagi and Rumbia is most closely associated with their respective 500 hPa environmental winds, with a steering flow of 10–12 m s−1. In contrast, Typhoon In-Fa's movement speed is most strongly correlated with the 850 hPa environmental wind field, with a steering flow speed of only 2 m s−1. Furthermore, as Typhoon In-Fa moves northwest after landfall, its intensity is slightly greater than that of Typhoons Yagi and Rumbia, and the pressure gradient in front of Typhoon In-Fa is notably smaller, leading to its slow movement. Additionally, the precipitation distribution of Typhoon In-Fa differs from that of the other two typhoons, resulting in a weak asymmetry of wavenumber-1 diabatic heating, which indirectly affects its movement speed. Further analysis indicates that VWS can alter the typhoon's structure, weaken its intensity, and ultimately impact its movement.
2024, 30(1): 61-75.
doi: 10.3724/j.1006-8775.2024.007
Abstract:
A second rain belt sometimes occurs ahead of a frontal rain belt in the warm sector over coastal South China, leading to heavy precipitation. We examined the differences in the mesoscale characteristics and microphysics of the frontal and warm sector rain belts that occurred in South China on May 10–13, 2022. The southern rain belt occurred in an environment with favorable mesoscale conditions but weak large-scale forcing. In contrast, the northern rain belt was related to low-level horizontal shear and the surface-level front. The interaction between the enhanced southeasterly winds and the rainfall-induced cold pool promoted the persistent growth of convection along the southern rain belt. The convective cell propagated east over the coastal area, where there was a large temperature gradient. The bow-shaped echo in this region may be closely related to the rear-inflow jet. By contrast, the initial convection of the northern rain belt was triggered along the front and the region of low-level horizontal shear, with mesoscale interactions between the enhanced warm-moist southeasterly airflow and the cold dome associated with the earlier rain. The terrain blocked the movement of the cold pool, resulting in the stagnation of the frontal convective cell at an early stage. Subsequently, a meso-γ-scale vortex formed during the rapid movement of the convective cell, corresponding to an enhancement of precipitation. The representative raindrop spectra for the southern rain belt were characterized by a greater number and higher density of raindrops than the northern rain belt, even though both resulted in comparable hourly rainfalls. These results help us better understand the characteristics of double rain belts over South China.
A second rain belt sometimes occurs ahead of a frontal rain belt in the warm sector over coastal South China, leading to heavy precipitation. We examined the differences in the mesoscale characteristics and microphysics of the frontal and warm sector rain belts that occurred in South China on May 10–13, 2022. The southern rain belt occurred in an environment with favorable mesoscale conditions but weak large-scale forcing. In contrast, the northern rain belt was related to low-level horizontal shear and the surface-level front. The interaction between the enhanced southeasterly winds and the rainfall-induced cold pool promoted the persistent growth of convection along the southern rain belt. The convective cell propagated east over the coastal area, where there was a large temperature gradient. The bow-shaped echo in this region may be closely related to the rear-inflow jet. By contrast, the initial convection of the northern rain belt was triggered along the front and the region of low-level horizontal shear, with mesoscale interactions between the enhanced warm-moist southeasterly airflow and the cold dome associated with the earlier rain. The terrain blocked the movement of the cold pool, resulting in the stagnation of the frontal convective cell at an early stage. Subsequently, a meso-γ-scale vortex formed during the rapid movement of the convective cell, corresponding to an enhancement of precipitation. The representative raindrop spectra for the southern rain belt were characterized by a greater number and higher density of raindrops than the northern rain belt, even though both resulted in comparable hourly rainfalls. These results help us better understand the characteristics of double rain belts over South China.
2024, 30(1): 76-88.
doi: 10.3724/j.1006-8775.2024.008
Abstract:
Based on the lightning observation data from the Fengyun-4A (FY-4A) Lightning Mapping Imager (FY-4A/LMI) and the Lightning Imaging Sensor (LIS) on the International Space Station (ISS), we extract the "event" type data as the lightning detection results. These observations are then compared with the cloud-to-ground (CG) lightning observation data from the China Meteorological Administration. This study focuses on the characteristics of lightning activity in Southeast China, primarily in Jiangxi Province and its adjacent areas, from April to September, 2017–2022. In addition, with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis data, we further delved into the potential factors influencing the distribution and variations in lightning activity and their primary related factors. Our findings indicate that the lightning frequency and density of the FY-4A/LMI, ISS-LIS and CG data are higher in southern and central Jiangxi, central Fujian Province, and western and central Guangdong Province, while they tend to be lower in eastern Hunan Province. In general, the high-value areas of lightning density for the FY-4A/LMI are located in inland mountainous areas. The lower the latitude is, the higher the CG lightning density is. High-value areas of the CG lightning density are more likely to be located in eastern Fujian and southeastern Zhejiang Province. However, the high-value areas of lightning density for the ISS-LIS are more dispersed, with a scattered distribution in inland mountainous areas and along the coast of eastern Fujian. Thus, the mountainous terrain is closely related to the high-value areas of the lightning density. The locations of the high-value areas of the lightning density for the FY-4A/LMI correspond well with those for the CG observations, and the seasonal variations are also consistent. In contrast, the distribution of the high-value areas of the lightning density for the ISS-LIS is more dispersed. The positions of the peak frequency of the FY-4A/LMI lightning and CG lightning contrast with local altitudes, primarily located at lower altitudes or near mountainsides. K-index and convective available potential energy (CAPE) can better reflect the local boundary layer conditions, where the lightning density is higher and lightning seasonal variations are apparent. There are strong correlations in the annual variations between the dew-point temperature (Td) and CG lightning frequency, and the monthly variations of the dew-point temperature and CAPE are also strongly correlated with monthly variations of CG lightning, while they are weakly correlated with the lightning frequency for the FY-4A/LMI and ISS-LIS. This result reflects that the CAPE shows a remarkable effect on the CG lightning frequency during seasonal transitions.
Based on the lightning observation data from the Fengyun-4A (FY-4A) Lightning Mapping Imager (FY-4A/LMI) and the Lightning Imaging Sensor (LIS) on the International Space Station (ISS), we extract the "event" type data as the lightning detection results. These observations are then compared with the cloud-to-ground (CG) lightning observation data from the China Meteorological Administration. This study focuses on the characteristics of lightning activity in Southeast China, primarily in Jiangxi Province and its adjacent areas, from April to September, 2017–2022. In addition, with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis data, we further delved into the potential factors influencing the distribution and variations in lightning activity and their primary related factors. Our findings indicate that the lightning frequency and density of the FY-4A/LMI, ISS-LIS and CG data are higher in southern and central Jiangxi, central Fujian Province, and western and central Guangdong Province, while they tend to be lower in eastern Hunan Province. In general, the high-value areas of lightning density for the FY-4A/LMI are located in inland mountainous areas. The lower the latitude is, the higher the CG lightning density is. High-value areas of the CG lightning density are more likely to be located in eastern Fujian and southeastern Zhejiang Province. However, the high-value areas of lightning density for the ISS-LIS are more dispersed, with a scattered distribution in inland mountainous areas and along the coast of eastern Fujian. Thus, the mountainous terrain is closely related to the high-value areas of the lightning density. The locations of the high-value areas of the lightning density for the FY-4A/LMI correspond well with those for the CG observations, and the seasonal variations are also consistent. In contrast, the distribution of the high-value areas of the lightning density for the ISS-LIS is more dispersed. The positions of the peak frequency of the FY-4A/LMI lightning and CG lightning contrast with local altitudes, primarily located at lower altitudes or near mountainsides. K-index and convective available potential energy (CAPE) can better reflect the local boundary layer conditions, where the lightning density is higher and lightning seasonal variations are apparent. There are strong correlations in the annual variations between the dew-point temperature (Td) and CG lightning frequency, and the monthly variations of the dew-point temperature and CAPE are also strongly correlated with monthly variations of CG lightning, while they are weakly correlated with the lightning frequency for the FY-4A/LMI and ISS-LIS. This result reflects that the CAPE shows a remarkable effect on the CG lightning frequency during seasonal transitions.
2024, 30(1): 89-96.
doi: 10.3724/j.1006-8775.2024.009
Abstract:
Sea surface temperature (SST) is one of the important parameters of global ocean and climate research, which can be retrieved by satellite infrared and passive microwave remote sensing instruments. While satellite infrared SST offers high spatial resolution, it is limited by cloud cover. On the other hand, passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall, coastal effects, and high wind speeds. To achieve high-precision, comprehensive, and high-resolution SST data, it is essential to fuse infrared and microwave SST measurements. In this study, data from the Fengyun-3D (FY-3D) medium resolution spectral imager Ⅱ (MERSI-Ⅱ) SST and microwave imager (MWRI) SST were fused. Firstly, the accuracy of both MERSI-Ⅱ SST and MWRI SST was verified, and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST. After pretreatment and quality control of MERSI SST and MWRI SST, a Piece-Wise Regression method was employed to correct biases in MWRI SST. Subsequently, SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date. Finally, an optimal interpolation method was applied to fuse the FY-3D MERSI-Ⅱ SST and MWRI SST. The results demonstrated a significant improvement in spatial coverage compared to MERSI-Ⅱ SST and MWRI SST. Furthermore, the fusion SST retained true spatial distribution details and exhibited an accuracy of –0.12±0.74℃ compared to OSTIA SST. This study has improved the accuracy of FY satellite fusion SST products in China.
Sea surface temperature (SST) is one of the important parameters of global ocean and climate research, which can be retrieved by satellite infrared and passive microwave remote sensing instruments. While satellite infrared SST offers high spatial resolution, it is limited by cloud cover. On the other hand, passive microwave SST provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall, coastal effects, and high wind speeds. To achieve high-precision, comprehensive, and high-resolution SST data, it is essential to fuse infrared and microwave SST measurements. In this study, data from the Fengyun-3D (FY-3D) medium resolution spectral imager Ⅱ (MERSI-Ⅱ) SST and microwave imager (MWRI) SST were fused. Firstly, the accuracy of both MERSI-Ⅱ SST and MWRI SST was verified, and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI SST. After pretreatment and quality control of MERSI SST and MWRI SST, a Piece-Wise Regression method was employed to correct biases in MWRI SST. Subsequently, SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date. Finally, an optimal interpolation method was applied to fuse the FY-3D MERSI-Ⅱ SST and MWRI SST. The results demonstrated a significant improvement in spatial coverage compared to MERSI-Ⅱ SST and MWRI SST. Furthermore, the fusion SST retained true spatial distribution details and exhibited an accuracy of –0.12±0.74℃ compared to OSTIA SST. This study has improved the accuracy of FY satellite fusion SST products in China.
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