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Large-scale teleconnection patterns of Indian summer monsoon as revealed by CFSv2 retrospective seasonal forecast runs
No full textThe seasonal prediction skill [defined as the linear correlation (cc) between the observed and forecasted rainfall] of the Indian Summer Monsoon Rainfall (ISMR) is evaluated in the Climate Forecast System version 2 (CFSv2) model, at different lead times on the basis of its representation of large scale tropical teleconnection. Surprisingly, the model exhibits reasonable skill at a longer lead time (e.g. forecasts initialized with February initial conditions, Feb IC run, cc > 0.5) that is reasonably better when compared with that with forecast initialized at shorter lead time [April/May IC (Apr/May IC) runs, cc < 0.5]. Although the prediction skill of ISMR improves as lead time increases, the ENSO forecast skill improves as lead time decreases. Probable reasons for these counter-intuitive findings are investigated in this study.
The model shows unrealistic teleconnection of ISMR with Indian Ocean Dipole (IOD) and is unable to represent the large scale rainfall pattern over the Indian land region. The Equatorial Indian Ocean Oscillation (EQUINOO) shows unrealistic teleconnection with ISMR as well as equatorial Pacific from all the initial condition runs. Unrealistic EQUINOO and the IOD teleconnection suggest that the air–sea interaction in the Indian Ocean requires to be improved in the model. The relationship between El Nino-Southern Oscillation (ENSO) and monsoon in CFSv2 is realistic in terms of spatial pattern though it is somewhat stronger than that in observations.
The equatorial central Pacific sea surface temperature and rainfall show very strong cold and dry biases respectively, and these biases enhance from the Feb IC run to the May IC run. It is found that these biases are due to strong unrealistic coupled feedback in this region. As a result, the associated ENSO–monsoon teleconnection pattern shifts westward with decreasing lead time, resulting in unrealistic patterns as compared with observations, and causing a loss of prediction skill at shorter lead times
Cloud aerosol interactions and its influence on cloud microphysical parameters during dry and wet spells of Indian summer monsoon using CAIPEEX data
No full textThe variations of cloud condensation nuclei (CCN), aerosol and cloud particle concentration (PCASP), cloud droplet effective radius (CDPRe), and Liquid water content (LWC) have been measured using instrumented aircraft over Hyderabad, Bengaluru and Bareilly in India during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX-2009). Three intensive observation periods (IOPs) i.e. 17-22 June and 13 July representing the dry spells, and the IOP during 16-25 August, representing wet spells of Indian summer monsoon were analyzed. Cloud droplet size is highly sensitive to liquid water content and temperature in the cloud environment. The CDPRe and LWC show strong linear correlation during both dry spells and wet spells of ISMR. The mid level clouds CM ~ 2000 meters are more favorable for coalescence of cloud droplets leading to growth of CDPRe > 14 µm required for warm rain formation
Monsoon mixing cycles in the Bay of Bengal: A year-long subsurface mixing record
Get PDFBased on the first year-long record of mixing collected in the eastern central Bay of Bengal, we quantify the role that subsurface turbulent heat fluxes play in upper-ocean cooling brought on by southwest (SW) and northeast (NE) monsoons. During the NE (dry, or winter) monsoon, atmospheric and subsurface turbulent heat fluxes each contribute about 50% of the net sea surface cooling. During the SW (wet, or summer) monsoon, the atmospheric heat flux varied widely due to “active” and “break” cycles of the monsoon intraseasonal oscillations, but had a net positive seasonal average. The subsurface turbulent heat flux during the SW monsoon led to surface cooling at rates more than three times greater than those measured during the NE monsoon. Since the seasonally averaged atmospheric heat flux was positive, subsurface mixing accounted for nearly all of the cooling during the SW monsoon. During the transition between the NE and SW monsoons, subsurface heat flux was near zero, and atmospheric heating rapidly warmed the sea surface. Following the SW monsoon, passage of Tropical Storm Hudhud led to O(1) m2 s–1 rates of turbulence diffusivity and strong subsurface heat flux, accounting for roughly half of the 1.4°C surface cooling that occurred over a 60-hour period
Large-scale air-sea coupling processes in the Bay of Bengal using space-borne observations
Get PDFFor the last several decades, sensors aboard satellites have provided a rich array of information about ocean surface parameters, especially sea surface temperature. The latest addition to the satellite toolbox, sea surface salinity, has paved the way for much greater understanding of large-scale air-sea coupling in the Bay of Bengal. This region is replete with mesoscale and submesoscale features and associated surface currents that profoundly impact air-sea heat exchanges and vertical mixing in the ocean. Sea surface height from satellite altimeters is widely used for understanding the dynamics of such features. This article reviews how satellite data are used to monitor and understand various air-sea interactions in the Bay of Bengal and presents a brief overview of modeling efforts underway in this important region
Relation between tropical cyclone heat potential and cyclone intensity in the North Indian Ocean
No full textOcean Heat Content (OHC) plays a significant role in modulating the intensity of Tropical Cyclones (TC) in terms of the oceanic energy available to TCs. TC Heat Potential (TCHP), an estimate of OHC, is thus known to be a useful indicator of TC genesis and intensification. In the present study, we analyze the role of TCHP in intensification of TCs in the North Indian Ocean (NIO) through statistical comparisons between TCHP and Cyclone Intensities (CI). A total of 27 TCs (20 in the Bay of Bengal, and 7 in the Arabian Sea) during the period 2005–2012 have been analyzed using TCHP data from Global Ocean Data Assimilation System (GODAS) model of Indian National Center for Ocean Information Services and cyclone best track data from India Meteorological Department. Out of the 27 cyclones analyzed, 58% (86%) in the Bay (Arabian Sea) have negative correlation and 42% (14%) cyclones have positive correlation between CI and TCHP. On the whole, more than 60% cyclones in the NIO show negative correlations between CI and TCHP. The negative percentage further increases for TCHP leading CI by 24 and 48 hours. Similar trend is also seen with satellite derived TCHP data obtained from National Remote Sensing Center and TC best track data from Joint Typhoon Warming Centre. Hence, it is postulated that TCHP alone need not be the only significant oceanographic parameter, apart from sea surface temperature, responsible for intensification and propagation of TCs in the NI
Near-surface salinity and stratification in the north Bay of Bengal from moored observations
No full textA thin layer of fresh water from summer monsoon rain and river runoff in the Bay of Bengal (BoB) has profound influence on air-sea interaction across the south Asian region, but the mechanisms that sustain the low-salinity layer are as yet unknown. Using the first long time series of high-frequency observations from a mooring in the north BoB and satellite salinity data, we show that fresh water from major rivers is transported by large-scale flow and eddies, and shallow salinity stratification persists from summer through the following winter. The moored observations show frequent 0.2–1.2 psu salinity jumps with time scales of 10 min to days, due to O(1–10) km submesoscale salinity fronts moving past the mooring. In winter, satellite sea surface temperature shows 10 km wide filaments of cool water, in line with moored data. Rapid salinity and temperature changes at the mooring are highly coherent, suggesting slumping of salinity-dominated fronts. Based on these observations, we propose that submesoscale fronts may be one of the important drivers for the persistent fresh layer in the north Bo
Phytoplankton community structure in local water types at a coastal site in north-western Bay of Bengal
No full textA comprehensive analysis on seasonal distribution of phytoplankton community structure and their interaction with environmental variables was carried out in two local water types (type 1 30 m isobath) at a coastal site in north-western Bay of Bengal. Phytoplankton community was represented by 211 taxa (146 marine, 37 fresh, 2 brackish, 20 marine–fresh, and 6 marine–brackish–fresh) belonging to seven major groups including 45 potential bloom forming and 22 potential toxin producing species. The seasonal variability depicted enrichment of phytoplankton during pre-monsoon in both water types. Total phytoplankton abundance pattern observed with inter-annual shift during monsoon and post-monsoon period at both water types. In both water types, diatom predominance was observed in terms of species richness and abundance comprising of centric (82 sp.) and pennate (58 sp.) forms. Pennate diatoms, Thalassiothrix longissima and Skeletonema costatum preponderated in both the water types. The diatom abundance was higher in type 1 in comparison to type 2. In general, SiO4 found to fuel growth of the dominant phytoplankton group, diatom in both the water types despite comparative lower concentration of other macronutrients in type
Indian summer monsoon simulations with CFSv2: a microphysics perspective
No full textThe present study explores the impact of two different microphysical parameterization schemes (i.e. Zhao and Carr, Mon Wea Rev 125:1931-1953, 1997:called as ZC; Ferrier, Amer Meteor Soc 280-283, 2002: called as BF) of National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) on Indian summer monsoon (ISM). Critical relative humidity (RHcrit) plays a crucial role for the realistic cloud formation in a general circulation model (GCM). Hence, impact of RHcrit along with microphysical scheme on ISM is evaluated in the study. Model performance is evaluated in terms of simulation of rainfall, lower and upper tropospheric circulations, cloud fraction, cloud condensate and outgoing longwave radiation (OLR). Climatological mean features of rainfall are better represented by all the sensitivity experiments. Overall, ZC schemes show relatively better rainfall patterns as compared to BF schemes. BF schemes along with 95 % RHcrit (called as BF95) show excess precipitable water over Indian Ocean basin region, which seems to be unrealistic. Lower and upper tropospheric features are well simulated in all the sensitivity experiments; however, upper tropospheric wind patterns are underestimated as compared to observation. Spatial pattern and vertical profile of cloud condensate is relatively better represented by ZC schemes as compared to BF schemes. Relatively more (less) cloud condensate at upper level has lead to relatively better (low) high cloud fraction in ZC (BF) simulation. It is seen that OLR in ZC simulation have great proximity with observation. ZC (BF) simulations depict low (high) OLR which indicates stronger (weaker) convection during ISM period. It implies strong (weak) convection having stronger (weaker) updrafts in ZC (BF). Relatively more (less) cloud condensate at upper level of ZC (BF) may produce strong (weak) latent heating which may lead to relatively strong (weak) convection during ISM. The interaction among microphysics, thermodynamics, and dynamics works in tandem through a closed feedback loop
A reduction in marine primary productivity driven by rapid warming over the tropical Indian Ocean
No full textAmong the tropical oceans, the western Indian Ocean hosts one of the largest concentrations of marine phytoplankton blooms in summer. Interestingly, this is also the region with the largest warming trend in sea surface temperatures in the tropics during the past century - although the contribution of such a large warming to productivity changes has remained ambiguous. Earlier studies had described the western Indian Ocean as a region with the largest increase in phytoplankton during the recent decades. On the contrary, the current study points out an alarming decrease of up to 20 in phytoplankton in this region over the past six decades. We find that these trends in chlorophyll are driven by enhanced ocean stratification due to rapid warming in the Indian Ocean, which suppresses nutrient mixing from subsurface layers. Future climate projections suggest that the Indian Ocean will continue to warm, driving this productive region into an ecological desert
Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951–2005 using a regional climate model
Get PDFDaily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1–1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over central India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1–1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over India during the monsoon season. Although, the regional climate model helps in better resolving land–atmosphere feedbacks over the Indian region, the inferences do depend on the fidelity of the model in capturing the features of Indian monsoon realistically. It is proposed that similar studies using a suite of climate models will further enrich our understanding about the role of LULCC in the Indian monsoon climate