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- Author or Editor: Ha Pham-Thanh x
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Abstract
This study presents the application of k-means clustering to satellite-based solar irradiation in different regions of Vietnam. The solar irradiation products derived from the Himawari-8 satellite, named AMATERASS by the solar radiation consortium under the Japan Science and Technology Agency (JST), are validated with observations recorded at five stations in the period from October 2017 to September 2018 before their use for clustering. High correlations among them enable the use of satellite-based daily global horizontal irradiation for spatial variability analysis and regionalization. With respect to the climate regime in Vietnam, the defined 6-cluster groups demonstrate better agreement with the conventionally classified seven climatic zones rather than the four climatic zones of the Köppen classification. The spatial distribution and seasonal variation in the regionalized solar irradiation reflect interchangeable influences of large-scale atmospheric circulation in terms of the East Asian winter monsoon and the South Asian summer monsoon as well as the effect of local topography. Higher daily averaged solar radiation and its weaker seasonal variation were found in two clusters in the southern region where the South Asian summer monsoon dominates in the rainy season. Pronounced seasonal variability in solar irradiation in four clusters in the northern region is associated with the influence of the East Asian monsoon, resulting in its clear reduction during the winter months.
Abstract
This study presents the application of k-means clustering to satellite-based solar irradiation in different regions of Vietnam. The solar irradiation products derived from the Himawari-8 satellite, named AMATERASS by the solar radiation consortium under the Japan Science and Technology Agency (JST), are validated with observations recorded at five stations in the period from October 2017 to September 2018 before their use for clustering. High correlations among them enable the use of satellite-based daily global horizontal irradiation for spatial variability analysis and regionalization. With respect to the climate regime in Vietnam, the defined 6-cluster groups demonstrate better agreement with the conventionally classified seven climatic zones rather than the four climatic zones of the Köppen classification. The spatial distribution and seasonal variation in the regionalized solar irradiation reflect interchangeable influences of large-scale atmospheric circulation in terms of the East Asian winter monsoon and the South Asian summer monsoon as well as the effect of local topography. Higher daily averaged solar radiation and its weaker seasonal variation were found in two clusters in the southern region where the South Asian summer monsoon dominates in the rainy season. Pronounced seasonal variability in solar irradiation in four clusters in the northern region is associated with the influence of the East Asian monsoon, resulting in its clear reduction during the winter months.
Abstract
This study investigates the ability to apply National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) products and their downscaling by using the Regional Climate Model version 4.2 (RegCM4.2) on seasonal rainfall forecasts over Vietnam. First, the CFS hindcasts (CFS_Rfc) from 1982 to 2009 are used to assess the ability of the CFS to predict the overall circulation and precipitation patterns at forecast lead times of up to 6 months. Second, the operational CFS forecasts (CFS_Ope) and its RegCM4.2 downscaling (RegCM_CFS) for the period 2012–14 are used to derive seasonal rainfall forecasts over Vietnam. The CFS_Rfc and CFS_Ope are validated against the ECMWF interim reanalysis, the Global Precipitation Climatology Centre (GPCC) analyzed rainfall, and observations from 150 meteorological stations across Vietnam. The results show that the CFS_Rfc can capture the seasonal variability of the Asian monsoon circulation and rainfall distribution. The higher-resolution RegCM_CFS product is advantageous over the raw CFS in specific climatic subregions during the transitional, dry, and rainy seasons, particularly in the northern part of Vietnam in January and in the country’s central highlands during July.
Abstract
This study investigates the ability to apply National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) products and their downscaling by using the Regional Climate Model version 4.2 (RegCM4.2) on seasonal rainfall forecasts over Vietnam. First, the CFS hindcasts (CFS_Rfc) from 1982 to 2009 are used to assess the ability of the CFS to predict the overall circulation and precipitation patterns at forecast lead times of up to 6 months. Second, the operational CFS forecasts (CFS_Ope) and its RegCM4.2 downscaling (RegCM_CFS) for the period 2012–14 are used to derive seasonal rainfall forecasts over Vietnam. The CFS_Rfc and CFS_Ope are validated against the ECMWF interim reanalysis, the Global Precipitation Climatology Centre (GPCC) analyzed rainfall, and observations from 150 meteorological stations across Vietnam. The results show that the CFS_Rfc can capture the seasonal variability of the Asian monsoon circulation and rainfall distribution. The higher-resolution RegCM_CFS product is advantageous over the raw CFS in specific climatic subregions during the transitional, dry, and rainy seasons, particularly in the northern part of Vietnam in January and in the country’s central highlands during July.
Abstract
This study examines the climatic shift of the tropical cyclone (TC) frequency affecting Vietnam’s coastal region during 1975–2014. By separating TC databases into two different 20-yr epochs, it is found that there is a consistent increase in both the number of strong TCs and the number of TC occurrences during the recent epoch (1995–2014) as compared with the reference epoch (1975–94) across different TC databases. This finding suggests that not only the number of strong TCs but also the lifetime of strong TCs affecting Vietnam’s coastal region has been recently increasing as compared with the reference epoch from 1975 to 1994. To understand the physical connection of these shifts in the TC frequency and duration, large-scale conditions obtained from reanalysis data are analyzed. Results show that meridional surface temperature gradient (STG) during the recent epoch is substantially larger than that during 1975–94. Such an increase in the meridional STG is important because it is potentially linked to the increase in large-scale vertical wind shear as well as the reduced intensity of summer monsoon in the South China Sea between the two epochs.
Abstract
This study examines the climatic shift of the tropical cyclone (TC) frequency affecting Vietnam’s coastal region during 1975–2014. By separating TC databases into two different 20-yr epochs, it is found that there is a consistent increase in both the number of strong TCs and the number of TC occurrences during the recent epoch (1995–2014) as compared with the reference epoch (1975–94) across different TC databases. This finding suggests that not only the number of strong TCs but also the lifetime of strong TCs affecting Vietnam’s coastal region has been recently increasing as compared with the reference epoch from 1975 to 1994. To understand the physical connection of these shifts in the TC frequency and duration, large-scale conditions obtained from reanalysis data are analyzed. Results show that meridional surface temperature gradient (STG) during the recent epoch is substantially larger than that during 1975–94. Such an increase in the meridional STG is important because it is potentially linked to the increase in large-scale vertical wind shear as well as the reduced intensity of summer monsoon in the South China Sea between the two epochs.
Abstract
The onset of the rainy season is an important date for the mostly rain-fed agricultural practices in Vietnam. Subseasonal to seasonal (S2S) ensemble hindcasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) are used to evaluate the predictability of the rainy season onset dates (RSODs) over five climatic subregions of Vietnam. The results show that the ECMWF model reproduces well the observed interannual variability of RSODs, with a high correlation ranging from 0.60 to 0.99 over all subregions at all lead times (up to 40 days) using five different RSOD definitions. For increasing lead times, forecasted RSODs tend to be earlier than the observed ones. Positive skill score values for almost all cases examined in all subregions indicate that the model outperforms the observed climatology in predicting the RSOD at subseasonal lead times (∼28–35 days). However, the model is overall more skillful at shorter lead times. The choice of the RSOD criterion should be considered because it can significantly influence the model performance. The result of analyzing the highest skill score for each subregion at each lead time shows that criteria with higher 5-day rainfall thresholds tend to be more suitable for the forecasts at long lead times. However, the values of mean absolute error are approximately the same as the absolute values of the mean error, indicating that the prediction could be improved by a simple bias correction. The present study shows a large potential to use S2S forecasts to provide meaningful predictions of RSODs for farmers.
Abstract
The onset of the rainy season is an important date for the mostly rain-fed agricultural practices in Vietnam. Subseasonal to seasonal (S2S) ensemble hindcasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) are used to evaluate the predictability of the rainy season onset dates (RSODs) over five climatic subregions of Vietnam. The results show that the ECMWF model reproduces well the observed interannual variability of RSODs, with a high correlation ranging from 0.60 to 0.99 over all subregions at all lead times (up to 40 days) using five different RSOD definitions. For increasing lead times, forecasted RSODs tend to be earlier than the observed ones. Positive skill score values for almost all cases examined in all subregions indicate that the model outperforms the observed climatology in predicting the RSOD at subseasonal lead times (∼28–35 days). However, the model is overall more skillful at shorter lead times. The choice of the RSOD criterion should be considered because it can significantly influence the model performance. The result of analyzing the highest skill score for each subregion at each lead time shows that criteria with higher 5-day rainfall thresholds tend to be more suitable for the forecasts at long lead times. However, the values of mean absolute error are approximately the same as the absolute values of the mean error, indicating that the prediction could be improved by a simple bias correction. The present study shows a large potential to use S2S forecasts to provide meaningful predictions of RSODs for farmers.
Abstract
In this study, the spatiotemporal variability of drought over the entire Southeast Asia (SEA) region and its associations with the large-scale climate drivers during the period 1960–2019 are investigated for the first time. The 12-month Standardized Precipitation Evapotranspiration Index (SPEI) was computed based on the monthly Global Precipitation Climatology Centre (GPCC) precipitation and the monthly Climate Research Unit (CRU) 2-m temperature. The relationships between drought and large-scale climate drivers were examined using the principal component analysis (PCA) and maximum covariance analysis (MCA) techniques. Results showed that the spatiotemporal variability of drought characteristics over SEA is significantly different between mainland Indochina and the Maritime Continent and the difference has been increased substantially in recent decades. Moreover, the entire SEA is divided into four homogeneous drought subregions. Drought over SEA is strongly associated with oceanic and atmospheric large-scale drivers, particularly El Niño–Southern Oscillation (ENSO), following by other remote factors such as the variability of sea surface temperature (SST) over the tropical Atlantic, the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IOD). In addition, there exists an SST anomaly dipole over the Pacific Ocean, which modulates the atmospheric circulations and consequently precipitation over SEA, affecting drought conditions in the study region.
Abstract
In this study, the spatiotemporal variability of drought over the entire Southeast Asia (SEA) region and its associations with the large-scale climate drivers during the period 1960–2019 are investigated for the first time. The 12-month Standardized Precipitation Evapotranspiration Index (SPEI) was computed based on the monthly Global Precipitation Climatology Centre (GPCC) precipitation and the monthly Climate Research Unit (CRU) 2-m temperature. The relationships between drought and large-scale climate drivers were examined using the principal component analysis (PCA) and maximum covariance analysis (MCA) techniques. Results showed that the spatiotemporal variability of drought characteristics over SEA is significantly different between mainland Indochina and the Maritime Continent and the difference has been increased substantially in recent decades. Moreover, the entire SEA is divided into four homogeneous drought subregions. Drought over SEA is strongly associated with oceanic and atmospheric large-scale drivers, particularly El Niño–Southern Oscillation (ENSO), following by other remote factors such as the variability of sea surface temperature (SST) over the tropical Atlantic, the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IOD). In addition, there exists an SST anomaly dipole over the Pacific Ocean, which modulates the atmospheric circulations and consequently precipitation over SEA, affecting drought conditions in the study region.
