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- Author or Editor: Rashmi Sharma x
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Abstract
A 2-yr (June 1999–June 2001) observation of ocean surface wind speed (SWS) and sea surface temperature (SST) derived from microwave radiometer measurements made by a multifrequency scanning microwave radiometer (MSMR) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is compared with direct measurements by Indian Ocean buoys. Also, for the first time SWS and SST values of the same period obtained from 40-yr ECMWF Re-Analysis (ERA-40) have been evaluated with these buoy observations. The SWS and SST are shown to have standard deviations of 1.77 m s−1 and 0.60 K for TMI, 2.30 m s−1 and 2.0 K for MSMR, and 2.59 m s−1 and 0.68 K for ERA-40, respectively. Despite the fact that MSMR has a lower-frequency channel, larger values of bias and standard deviation (STD) are found compared to those of TMI. The performance of SST retrieval during the daytime is found to be better than that at nighttime. The analysis carried out for different seasons has raised an important question as to why one spaceborne instrument (TMI) yields retrievals with similar biases during both pre- and postmonsoon periods and the other (MSMR) yields drastically different results. The large bias at low wind speeds is believed to be due to the poorer sensitivity of microwave emissivity variations at low wind speeds. The extreme SWS case study (cyclonic condition) showed that satellite-retrieved SWS captured the trend and absolute magnitudes as reflected by in situ observations, while the model (ERA-40) failed to do so. This result has direct implications on the real-time application of satellite winds in monitoring extreme weather events.
Abstract
A 2-yr (June 1999–June 2001) observation of ocean surface wind speed (SWS) and sea surface temperature (SST) derived from microwave radiometer measurements made by a multifrequency scanning microwave radiometer (MSMR) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is compared with direct measurements by Indian Ocean buoys. Also, for the first time SWS and SST values of the same period obtained from 40-yr ECMWF Re-Analysis (ERA-40) have been evaluated with these buoy observations. The SWS and SST are shown to have standard deviations of 1.77 m s−1 and 0.60 K for TMI, 2.30 m s−1 and 2.0 K for MSMR, and 2.59 m s−1 and 0.68 K for ERA-40, respectively. Despite the fact that MSMR has a lower-frequency channel, larger values of bias and standard deviation (STD) are found compared to those of TMI. The performance of SST retrieval during the daytime is found to be better than that at nighttime. The analysis carried out for different seasons has raised an important question as to why one spaceborne instrument (TMI) yields retrievals with similar biases during both pre- and postmonsoon periods and the other (MSMR) yields drastically different results. The large bias at low wind speeds is believed to be due to the poorer sensitivity of microwave emissivity variations at low wind speeds. The extreme SWS case study (cyclonic condition) showed that satellite-retrieved SWS captured the trend and absolute magnitudes as reflected by in situ observations, while the model (ERA-40) failed to do so. This result has direct implications on the real-time application of satellite winds in monitoring extreme weather events.
Abstract
This study focuses on two major aspects: the impact of satellite forcings (winds and precipitation) on the simulations of a multilayer Indian Ocean (IO) model (IOM) and the analysis of the processes responsible for salinity variations in the Indian Ocean during dipole years (1994 and 1997). It is observed that the European Remote Sensing Satellite-2 (ERS-2) scatterometer wind-driven solutions describe the interannual variabilities of sea surface temperature (SST) more realistically than the National Centers for Environmental Prediction (NCEP) wind-driven solutions. The equatorial westward current jet [hereafter referred to as reverse Wyrtki jet (RWJ)] originating near the Sumatra coast in response to anomalous easterlies during fall of 1994 and 1997 is quite strong in the scatterometer-forced solutions. This RWJ is found to be weak in the NCEP solution. Two more experiments differing by their precipitation forcings [climatological and interannually varying Global Precipitation Climatology Project (GPCP) rainfall] are carried out. Model-simulated variables like SST, sea surface salinity (SSS), and mixed layer depth (MLD) have been compared with in situ observations to verify the performance of the model. The model suggests a dipolelike structure in surface salinity during late 1994 and 1997, with low salinity in the central equatorial Indian Ocean (EIO) and high salinity near the Sumatra coast. The low-salinity tongue is caused by the transport of fresh surface waters via RWJ, which is further strengthened by a southward branch (which is absent in normal years) coming from the Bay of Bengal. A major inference of the study is that the low-salinity tongue is caused mainly by advection, not by a direct effect of precipitation. On the contrary, the high salinity near the Sumatra coast is due to the strong upwelling caused by anomalous easterlies. Another inference made out of this study is that there is apparently a definite signature of the evolution of the dipole event in the MLD approximately 2 months prior to the peak occurring in SSS in the south EIO.
Abstract
This study focuses on two major aspects: the impact of satellite forcings (winds and precipitation) on the simulations of a multilayer Indian Ocean (IO) model (IOM) and the analysis of the processes responsible for salinity variations in the Indian Ocean during dipole years (1994 and 1997). It is observed that the European Remote Sensing Satellite-2 (ERS-2) scatterometer wind-driven solutions describe the interannual variabilities of sea surface temperature (SST) more realistically than the National Centers for Environmental Prediction (NCEP) wind-driven solutions. The equatorial westward current jet [hereafter referred to as reverse Wyrtki jet (RWJ)] originating near the Sumatra coast in response to anomalous easterlies during fall of 1994 and 1997 is quite strong in the scatterometer-forced solutions. This RWJ is found to be weak in the NCEP solution. Two more experiments differing by their precipitation forcings [climatological and interannually varying Global Precipitation Climatology Project (GPCP) rainfall] are carried out. Model-simulated variables like SST, sea surface salinity (SSS), and mixed layer depth (MLD) have been compared with in situ observations to verify the performance of the model. The model suggests a dipolelike structure in surface salinity during late 1994 and 1997, with low salinity in the central equatorial Indian Ocean (EIO) and high salinity near the Sumatra coast. The low-salinity tongue is caused by the transport of fresh surface waters via RWJ, which is further strengthened by a southward branch (which is absent in normal years) coming from the Bay of Bengal. A major inference of the study is that the low-salinity tongue is caused mainly by advection, not by a direct effect of precipitation. On the contrary, the high salinity near the Sumatra coast is due to the strong upwelling caused by anomalous easterlies. Another inference made out of this study is that there is apparently a definite signature of the evolution of the dipole event in the MLD approximately 2 months prior to the peak occurring in SSS in the south EIO.
Abstract
A forward trajectory advection scheme has been designed for its use in an icosahedral–hexagonal grid model. The scheme has been evaluated with two-dimensional test cases: solid-body rotation and deformational flow; both depict important characteristics of atmospheric flows. The main motivation of this study is to achieve good accuracy without using higher-order interpolations in a numerical advection scheme, so that it may become viable in fine-resolution GCMs. The computation of the error norm shows its gradient as constant and the scheme is approximately first-order accurate. The other interesting feature of this study is that its downstream search algorithm reduces the complexity from O(n 2) to O(n).
Abstract
A forward trajectory advection scheme has been designed for its use in an icosahedral–hexagonal grid model. The scheme has been evaluated with two-dimensional test cases: solid-body rotation and deformational flow; both depict important characteristics of atmospheric flows. The main motivation of this study is to achieve good accuracy without using higher-order interpolations in a numerical advection scheme, so that it may become viable in fine-resolution GCMs. The computation of the error norm shows its gradient as constant and the scheme is approximately first-order accurate. The other interesting feature of this study is that its downstream search algorithm reduces the complexity from O(n 2) to O(n).
Abstract
A long-period (15 yr) simulation of sea surface salinity (SSS) obtained from a hindcast run of an ocean general circulation model (OGCM) forced by the NCEP–NCAR daily reanalysis product is analyzed in the tropical Indian Ocean (TIO). The objective of the study is twofold: assess the capability of the model to provide realistic simulations of SSS and characterize the SSS variability in view of upcoming satellite salinity missions. Model fields are evaluated in terms of mean, standard deviation, and characteristic temporal scales of SSS variability. Results show that the standard deviations range from 0.2 to 1.5 psu, with larger values in regions with strong seasonal transitions of surface currents (south of India) and along the coast in the Bay of Bengal (strong Kelvin-wave-induced currents). Comparison of simulated SSS with collocated SSS measurements from the National Oceanographic Data Center and Argo floats resulted in a high correlation of 0.85 and a root-mean-square error (RMSE) of 0.4 psu. The correlations are quite high (>0.75) up to a depth of 300 m. Daily simulations of SSS compare well with a Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) buoy in the eastern equatorial Indian Ocean (1.5°S, 90°E) with an RMSE of 0.3 psu and a correlation better than 0.6. Model SSS compares well with observations at all time scales (intraseasonal, seasonal, and interannual). The decorrelation scales computed from model and buoy SSS suggest that the proposed 10-day sampling of future salinity sensors would be able to resolve much of the salinity variability at time scales longer than intraseasonal. This inference is significant in view of satellite salinity sensors, such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius.
Abstract
A long-period (15 yr) simulation of sea surface salinity (SSS) obtained from a hindcast run of an ocean general circulation model (OGCM) forced by the NCEP–NCAR daily reanalysis product is analyzed in the tropical Indian Ocean (TIO). The objective of the study is twofold: assess the capability of the model to provide realistic simulations of SSS and characterize the SSS variability in view of upcoming satellite salinity missions. Model fields are evaluated in terms of mean, standard deviation, and characteristic temporal scales of SSS variability. Results show that the standard deviations range from 0.2 to 1.5 psu, with larger values in regions with strong seasonal transitions of surface currents (south of India) and along the coast in the Bay of Bengal (strong Kelvin-wave-induced currents). Comparison of simulated SSS with collocated SSS measurements from the National Oceanographic Data Center and Argo floats resulted in a high correlation of 0.85 and a root-mean-square error (RMSE) of 0.4 psu. The correlations are quite high (>0.75) up to a depth of 300 m. Daily simulations of SSS compare well with a Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA) buoy in the eastern equatorial Indian Ocean (1.5°S, 90°E) with an RMSE of 0.3 psu and a correlation better than 0.6. Model SSS compares well with observations at all time scales (intraseasonal, seasonal, and interannual). The decorrelation scales computed from model and buoy SSS suggest that the proposed 10-day sampling of future salinity sensors would be able to resolve much of the salinity variability at time scales longer than intraseasonal. This inference is significant in view of satellite salinity sensors, such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius.
Abstract
Large-scale features of sea surface temperature, wind speed, water vapor, and cloud liquid water, derived from multifrequency scanning microwave radiometer (MSMR) on board Indian oceanographic satellite IRS-P4 could be identified during 15 June–23 August 1999. This is the period during which extensive validation was carried out. MSMR is the only sensor in orbit operating at 6.6 GHz. Average distribution of these parameters brings out large-scale atmospheric and oceanographic features. Zonal averages of these parameters were also studied to examine the consistency of MSMR data over larger spatial scales. Linear correlations between all parameters were also computed to check for the interconsistency of these parameters. The present analysis shows the potential use of MSMR products in studying the oceanographic and atmospheric phenomena.
Abstract
Large-scale features of sea surface temperature, wind speed, water vapor, and cloud liquid water, derived from multifrequency scanning microwave radiometer (MSMR) on board Indian oceanographic satellite IRS-P4 could be identified during 15 June–23 August 1999. This is the period during which extensive validation was carried out. MSMR is the only sensor in orbit operating at 6.6 GHz. Average distribution of these parameters brings out large-scale atmospheric and oceanographic features. Zonal averages of these parameters were also studied to examine the consistency of MSMR data over larger spatial scales. Linear correlations between all parameters were also computed to check for the interconsistency of these parameters. The present analysis shows the potential use of MSMR products in studying the oceanographic and atmospheric phenomena.
Abstract
Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes.
Abstract
Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes.
Abstract
In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.
Abstract
In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.
