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- Author or Editor: Alejandra Sanchez-Franks x
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Abstract
The Gulf Stream’s north wall east of Cape Hatteras marks the abrupt change in velocity and water properties between the slope sea to the north and the Gulf Stream itself. An index of the north wall position constructed by Taylor and Stephens, called Gulf Stream north wall (GSNW), is analyzed in terms of interannual changes in the Icelandic low (IL) pressure anomaly and longitudinal displacement. Sea surface temperature (SST) composites suggest that when IL pressure is anomalously low, there are lower temperatures in the Labrador Sea and south of the Grand Banks. Two years later, warm SST anomalies are seen over the Northern Recirculation Gyre and a northward shift in the GSNW occurs. Similar changes in SSTs occur during winters in which the IL is anomalously west, resulting in a northward displacement of the GSNW 3 years later. Although time lags of 2 and 3 years between the IL and the GSNW are used in the calculations, it is shown that lags with respect to each atmospheric variable are statistically significant at the 5% level over a range of years. Utilizing the appropriate time lags between the GSNW index and the IL pressure and longitude, as well as the Southern Oscillation index, a regression prediction scheme is developed for forecasting the GSNW with a lead time of 1 year. This scheme, which uses only prior information, was used to forecast the GSNW from 1994 to 2015. The correlation between the observed and forecasted values for 1994–2014 was 0.60, significant at the 1% level. The predicted value for 2015 indicates a small northward shift of the GSNW from its 2014 position.
Abstract
The Gulf Stream’s north wall east of Cape Hatteras marks the abrupt change in velocity and water properties between the slope sea to the north and the Gulf Stream itself. An index of the north wall position constructed by Taylor and Stephens, called Gulf Stream north wall (GSNW), is analyzed in terms of interannual changes in the Icelandic low (IL) pressure anomaly and longitudinal displacement. Sea surface temperature (SST) composites suggest that when IL pressure is anomalously low, there are lower temperatures in the Labrador Sea and south of the Grand Banks. Two years later, warm SST anomalies are seen over the Northern Recirculation Gyre and a northward shift in the GSNW occurs. Similar changes in SSTs occur during winters in which the IL is anomalously west, resulting in a northward displacement of the GSNW 3 years later. Although time lags of 2 and 3 years between the IL and the GSNW are used in the calculations, it is shown that lags with respect to each atmospheric variable are statistically significant at the 5% level over a range of years. Utilizing the appropriate time lags between the GSNW index and the IL pressure and longitude, as well as the Southern Oscillation index, a regression prediction scheme is developed for forecasting the GSNW with a lead time of 1 year. This scheme, which uses only prior information, was used to forecast the GSNW from 1994 to 2015. The correlation between the observed and forecasted values for 1994–2014 was 0.60, significant at the 1% level. The predicted value for 2015 indicates a small northward shift of the GSNW from its 2014 position.
Abstract
The strong stratification of the Bay of Bengal (BoB) causes rapid variations in sea surface temperature (SST) that influence the development of monsoon rainfall systems. This stratification is driven by the salinity difference between the fresh surface waters of the northern bay and the supply of warm, salty water by the Southwest Monsoon Current (SMC). Despite the influence of the SMC on monsoon dynamics, observations of this current during the monsoon are sparse. Using data from high-resolution in situ measurements along an east–west section at 8°N in the southern BoB, we calculate that the northward transport during July 2016 was between 16.7 and 24.5 Sv (1 Sv ≡ 106 m3 s−1), although up to ⅔ of this transport is associated with persistent recirculating eddies, including the Sri Lanka Dome. Comparison with climatology suggests the SMC in early July was close to the average annual maximum strength. The NEMO 1/12° ocean model with data assimilation is found to faithfully represent the variability of the SMC and associated water masses. We show how the variability in SMC strength and position is driven by the complex interplay between local forcing (wind stress curl over the Sri Lanka Dome) and remote forcing (Kelvin and Rossby wave propagation). Thus, various modes of climatic variability will influence SMC strength and location on time scales from weeks to years. Idealized one-dimensional ocean model experiments show that subsurface water masses advected by the SMC significantly alter the evolution of SST and salinity, potentially impacting Indian monsoon rainfall.
Abstract
The strong stratification of the Bay of Bengal (BoB) causes rapid variations in sea surface temperature (SST) that influence the development of monsoon rainfall systems. This stratification is driven by the salinity difference between the fresh surface waters of the northern bay and the supply of warm, salty water by the Southwest Monsoon Current (SMC). Despite the influence of the SMC on monsoon dynamics, observations of this current during the monsoon are sparse. Using data from high-resolution in situ measurements along an east–west section at 8°N in the southern BoB, we calculate that the northward transport during July 2016 was between 16.7 and 24.5 Sv (1 Sv ≡ 106 m3 s−1), although up to ⅔ of this transport is associated with persistent recirculating eddies, including the Sri Lanka Dome. Comparison with climatology suggests the SMC in early July was close to the average annual maximum strength. The NEMO 1/12° ocean model with data assimilation is found to faithfully represent the variability of the SMC and associated water masses. We show how the variability in SMC strength and position is driven by the complex interplay between local forcing (wind stress curl over the Sri Lanka Dome) and remote forcing (Kelvin and Rossby wave propagation). Thus, various modes of climatic variability will influence SMC strength and location on time scales from weeks to years. Idealized one-dimensional ocean model experiments show that subsurface water masses advected by the SMC significantly alter the evolution of SST and salinity, potentially impacting Indian monsoon rainfall.
Abstract
In the Bay of Bengal (BoB), surface heat fluxes play a key role in monsoon dynamics and prediction. The accurate representation of large-scale surface fluxes is dependent on the quality of gridded reanalysis products. Meteorological and surface flux variables from five reanalysis products are compared and evaluated against in situ data from the Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) in the BoB. The reanalysis products: ERA-Interim (ERA-I), TropFlux, MERRA-2, JRA-55, and CFSR are assessed for their characterization of air–sea fluxes during the southwest monsoon season [June–September (JJAS)]. ERA-I captured radiative fluxes best while TropFlux captured turbulent and net heat fluxes Q net best, and both products outperformed JRA-55, MERRA-2, and CFSR, showing highest correlations and smallest biases when compared to the in situ data. In all five products, the largest errors were in shortwave radiation Q SW and latent heat flux Q LH, with nonnegligible biases up to approximately 75 W m−2. The Q SW and Q LH are the largest drivers of the observed Q net variability, thus highlighting the importance of the results from the buoy comparison. There are also spatially coherent differences in the mean basinwide fields of surface flux variables from the reanalysis products, indicating that the biases at the buoy position are not localized. Biases of this magnitude have severe implications on reanalysis products’ ability to capture the variability of monsoon processes. Hence, the representation of intraseasonal variability was investigated through the boreal summer intraseasonal oscillation, and we found that TropFlux and ERA-I perform best at capturing intraseasonal climate variability during the southwest monsoon season.
Abstract
In the Bay of Bengal (BoB), surface heat fluxes play a key role in monsoon dynamics and prediction. The accurate representation of large-scale surface fluxes is dependent on the quality of gridded reanalysis products. Meteorological and surface flux variables from five reanalysis products are compared and evaluated against in situ data from the Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) in the BoB. The reanalysis products: ERA-Interim (ERA-I), TropFlux, MERRA-2, JRA-55, and CFSR are assessed for their characterization of air–sea fluxes during the southwest monsoon season [June–September (JJAS)]. ERA-I captured radiative fluxes best while TropFlux captured turbulent and net heat fluxes Q net best, and both products outperformed JRA-55, MERRA-2, and CFSR, showing highest correlations and smallest biases when compared to the in situ data. In all five products, the largest errors were in shortwave radiation Q SW and latent heat flux Q LH, with nonnegligible biases up to approximately 75 W m−2. The Q SW and Q LH are the largest drivers of the observed Q net variability, thus highlighting the importance of the results from the buoy comparison. There are also spatially coherent differences in the mean basinwide fields of surface flux variables from the reanalysis products, indicating that the biases at the buoy position are not localized. Biases of this magnitude have severe implications on reanalysis products’ ability to capture the variability of monsoon processes. Hence, the representation of intraseasonal variability was investigated through the boreal summer intraseasonal oscillation, and we found that TropFlux and ERA-I perform best at capturing intraseasonal climate variability during the southwest monsoon season.
Abstract
The southwest monsoon delivers over 70% of India’s annual rainfall and is crucial to the success of agriculture across much of South Asia. Monsoon precipitation is known to be sensitive to sea surface temperature (SST) in the Bay of Bengal (BoB). Here, we use a configuration of the Unified Model of the Met Office coupled to an ocean mixed layer model to investigate the role of upper-ocean features in the BoB on southwest monsoon precipitation. We focus on the pronounced zonal and meridional SST gradients characteristic of the BoB; the zonal gradient in particular has an as-yet unknown effect on monsoon rainfall. We find that the zonal SST gradient is responsible for a 50% decrease in rainfall over the southern BoB (approximately 5 mm day−1), and a 50% increase in rainfall over Bangladesh and northern India (approximately 1 mm day−1). This increase is remotely forced by a strengthening of the monsoon Hadley circulation. The meridional SST gradient acts to decrease precipitation over the BoB itself, similarly to the zonal SST gradient, but does not have comparable effects over land. The impacts of barrier layers and high-salinity subsurface water are also investigated, but neither has significant effects on monsoon precipitation in this model; the influence of barrier layers on precipitation is felt in the months after the southwest monsoon. Models should accurately represent oceanic processes that directly influence BoB SST, such as the BoB cold pool, in order to faithfully represent monsoon rainfall.
Abstract
The southwest monsoon delivers over 70% of India’s annual rainfall and is crucial to the success of agriculture across much of South Asia. Monsoon precipitation is known to be sensitive to sea surface temperature (SST) in the Bay of Bengal (BoB). Here, we use a configuration of the Unified Model of the Met Office coupled to an ocean mixed layer model to investigate the role of upper-ocean features in the BoB on southwest monsoon precipitation. We focus on the pronounced zonal and meridional SST gradients characteristic of the BoB; the zonal gradient in particular has an as-yet unknown effect on monsoon rainfall. We find that the zonal SST gradient is responsible for a 50% decrease in rainfall over the southern BoB (approximately 5 mm day−1), and a 50% increase in rainfall over Bangladesh and northern India (approximately 1 mm day−1). This increase is remotely forced by a strengthening of the monsoon Hadley circulation. The meridional SST gradient acts to decrease precipitation over the BoB itself, similarly to the zonal SST gradient, but does not have comparable effects over land. The impacts of barrier layers and high-salinity subsurface water are also investigated, but neither has significant effects on monsoon precipitation in this model; the influence of barrier layers on precipitation is felt in the months after the southwest monsoon. Models should accurately represent oceanic processes that directly influence BoB SST, such as the BoB cold pool, in order to faithfully represent monsoon rainfall.
Abstract
The Bay of Bengal (BoB) plays a fundamental role in controlling the weather systems that make up the South Asian summer monsoon system. In particular, the southern BoB has cooler sea surface temperatures (SST) that influence ocean–atmosphere interaction and impact the monsoon. Compared to the southeastern BoB, the southwestern BoB is cooler, more saline, receives much less rain, and is influenced by the summer monsoon current (SMC). To examine the impact of these features on the monsoon, the BoB Boundary Layer Experiment (BoBBLE) was jointly undertaken by India and the United Kingdom during June–July 2016. Physical and biogeochemical observations were made using a conductivity–temperature–depth (CTD) profiler, five ocean gliders, an Oceanscience Underway CTD (uCTD), a vertical microstructure profiler (VMP), two acoustic Doppler current profilers (ADCPs), Argo floats, drifting buoys, meteorological sensors, and upper-air radiosonde balloons. The observations were made along a zonal section at 8°N between 85.3° and 89°E with a 10-day time series at 8°N, 89°E. This paper presents the new observed features of the southern BoB from the BoBBLE field program, supported by satellite data. Key results from the BoBBLE field campaign show the Sri Lanka dome and the SMC in different stages of their seasonal evolution and two freshening events during which salinity decreased in the upper layer, leading to the formation of thick barrier layers. BoBBLE observations were taken during a suppressed phase of the intraseasonal oscillation; they captured in detail the warming of the ocean mixed layer and the preconditioning of the atmosphere to convection.
Abstract
The Bay of Bengal (BoB) plays a fundamental role in controlling the weather systems that make up the South Asian summer monsoon system. In particular, the southern BoB has cooler sea surface temperatures (SST) that influence ocean–atmosphere interaction and impact the monsoon. Compared to the southeastern BoB, the southwestern BoB is cooler, more saline, receives much less rain, and is influenced by the summer monsoon current (SMC). To examine the impact of these features on the monsoon, the BoB Boundary Layer Experiment (BoBBLE) was jointly undertaken by India and the United Kingdom during June–July 2016. Physical and biogeochemical observations were made using a conductivity–temperature–depth (CTD) profiler, five ocean gliders, an Oceanscience Underway CTD (uCTD), a vertical microstructure profiler (VMP), two acoustic Doppler current profilers (ADCPs), Argo floats, drifting buoys, meteorological sensors, and upper-air radiosonde balloons. The observations were made along a zonal section at 8°N between 85.3° and 89°E with a 10-day time series at 8°N, 89°E. This paper presents the new observed features of the southern BoB from the BoBBLE field program, supported by satellite data. Key results from the BoBBLE field campaign show the Sri Lanka dome and the SMC in different stages of their seasonal evolution and two freshening events during which salinity decreased in the upper layer, leading to the formation of thick barrier layers. BoBBLE observations were taken during a suppressed phase of the intraseasonal oscillation; they captured in detail the warming of the ocean mixed layer and the preconditioning of the atmosphere to convection.
