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Impact of upper ocean processes and air-sea fluxes on seasonal SST biases over the tropical Indian Ocean in the NCEP Climate Forecasting System
No full textThe present study aims to examine the role of air–sea interactions and upper ocean processes in determining the tropical Indian Ocean (TIO) seasonal sea surface temperature (SST) bias in Climate Forecast System version 1 (CFSv1) and version 2 (CFSv2) free runs. CFSv1 displayed dipole like east–west SST bias over the equatorial Indian Ocean from boreal summer to winter and is consistent with errors (bias) in surface winds and upper ocean advection. Large zonal gradients in sea level pressure (SLP) bias and the associated surface wind biases are primarily responsible for the upper ocean current bias. However, over the southern Indian Ocean and parts of Arabian Sea, strong bias in heat flux and mixed layer depth (MLD) have mainly contributed for the SST biases in CFSv1. Equatorial current system is better represented in CFSv2 compared to CFSv1. Improvement in the representation of land-surface processes appears to be contributing towards improving atmospheric circulation and SLP gradients in CFSv2, which may be responsible for the improved ocean circulation. Importantly, east–west dipole like SST bias prevalent in CFSv1 is absent in CFSv2. However, there is a prominent systematic basin-wide TIO cold SST bias in CFSv2. Large biases in surface heat flux (net negative bias) and MLD (deeper) are mainly responsible for SST biases in CFSv2. Negative net heat flux bias in CFSv2 is primarily due to specific humidity bias-induced excess latent heat flux (LHF). Deepening of MLD is mainly due to strong convective mixing, a resultant of anomalous LHF release, which in turn leads to negative SST bias. Models comparison reveals that although representation of SST in CFSv2 is better than in CFSv1, it is essential to improve further the equatorial ocean dynamics and off-equatorial thermodynamics in the form of moist processes and radiative parameterization in order to reduce SST bias in CFSv2
Significant seismic anisotropy beneath southern Tibet inferred from splitting of direct S-waves
No full textThis study presents a total of 12008 shear wave splitting measurements obtained using the reference-station technique applied to direct S-waves from 106 earthquakes recorded at 143 seismic stations of the Hi-CLIMB seismic network. The results reveal significant anisotropy in regions of southern Tibet where null or negligible anisotropy has been hitherto reported from SK(K)S measurements. While the individual fast polarization direction (FPD) at each station are found to be consistent, the splitting time delays (TDs) exhibit deviations particularly at stations located south of the Indus-Tsangpo Suture Zone. The fast polarization directions (FPDs) are oriented (a) NE-SW to E-W to the south of the Indus-Tsangpo Suture Zone (b) NE-SW to ENE-SSW between Bangong-Nujiang Suture Zone and the Indus-Tsangpo Suture Zone (ITSZ) and (c) E-W to the extreme north of the profile. The splitting time delays (δ. t) vary between 0.45 and 1.3. s south of the ITSZ (<30°N latitude), while they range from 0.9 to 1.4. s north of it. The overall trends are similar to SKS/SKKS results. However, the differences may be due to the not so near vertical paths of direct S waves which may sample the anisotropy in a different way in comparison to SKS waves, or insufficient number of SKS observations. The significant anisotropy (~0.8. s) observed beneath Himalaya reveals a complex deformation pattern in the region and can be best explained by the combined effects of deformation related to shear at the base of the lithosphere and subduction related flows with possible contributions from the crust. Additional measurements obtained using direct S-waves provide new constraints in regions with complex anisotropy. © 2015 Elsevier B.V
On the decreasing trend of the number of monsoon depressions in the Bay of Bengal
Get PDFThis study unravels the physical link between the weakening of the monsoon circulation and the decreasing trend in the frequency of monsoon depressions over the Bay of Bengal. Based on the analysis of the terms of Genesis Potential Index, an empirical index to quantify the relative contribution of large scale environmental variables responsible for the modulation of storms, it is shown here that the reduction in the mid-tropospheric relative humidity is the most important reason for the decrease in the number of monsoon depressions. The net reduction of relative humidity over the Bay of Bengal is primarily due to the decrease in the moisture flux convergence, which is attributed to the weakening of the low level jet, a characteristic feature of monsoon circulation. Further, the anomalous moisture convergence over the western equatorial Indian Ocean associated with the rapid warming of the sea surface, reduces the moisture advection into the Bay of Bengal and hence adversely affect the genesis/intensification of monsoon depressions. Hence, the reduction in the number of monsoon depression over the Bay of Bengal could be one of the manifestations of the differential rates in the observed warming trend of the Indian Ocean basi
Fifteen years of ocean observations with the global Argo array
No full textMore than 90% of the heat energy accumulation in the climate system between 1971 and the present has been in the ocean. Thus, the ocean plays a crucial role in determining the climate of the planet. Observing the oceans is problematic even under the most favourable of conditions. Historically, shipboard ocean sampling has left vast expanses, particularly in the Southern Ocean, unobserved for long periods of time. Within the past 15 years, with the advent of the global Argo array of profiling floats, it has become possible to sample the upper 2,000 m of the ocean globally and uniformly in space and time. The primary goal of Argo is to create a systematic global network of profiling floats that can be integrated with other elements of the Global Ocean Observing System. The network provides freely available temperature and salinity data from the upper 2,000 m of the ocean with global coverage. The data are available within 24 hours of collection for use in a broad range of applications that focus on examining climate-relevant variability on seasonal to decadal timescales, multidecadal climate change, improved initialization of coupled ocean–atmosphere climate models and constraining ocean analysis and forecasting system
Argo data quality control based on climatological convex hulls
Get PDFThis report discusses a new method of identifying erroneous data in temperature and salinity (T/S) profiles measured by Argo profiling floats. The proposed method uses World Ocean Atlas 2009 (WOA09) climatology to classify good against bad data. An 'n' sided polygon (convex hull) with least area encompassing all the points is constructed based on the Jarvis March algorithm. The mean and standard deviation
fields of temperature and salinity obtained from WOA09 corresponding to each standard depth are used for building these polygons. Subsequently Points In Polygon (PIP) principle which is implemented using ray casting algorithm is used to classify the T/S data as within or without acceptable bounds. It is observed that various types of anomalies in the Argo profile data viz., spikes, bias, sensor drifts etc can be identified using this method
Basin-scale retrieval of zooplankton using split algorithm and MODIS data in the Arabian Sea
Get PDFSplit-algorithm has been developed to estimate zooplankton in the Arabian Sea using the remote sensing inputs; sea surface temperature and particulate organic carbon. In situ data on zooplankton bio-volume were collected from research vessels of the Ministry of Earth Sciences of India for the period 2000-2012 representing multiple seasons round the year. An exponential increase in zooplankton concentration was observed with increase in the sea surface temperature up to 25oC in the cold waters and it decreased at non-linear rate with further increase in the temperature. The results presented here highlight a critical role of temperature, rather than food, in causing distribution and abundance of zooplankton. Another feature of the algorithm is the use of particulate organic carbon instead of chlorophyll to account for feeding behavior of omnivorous zooplankton. The algorithm was implemented on Aqua MODIS data and validated for low as well as high temperature point
Indirect forcing of black carbon on clouds over northeast India
No full textBlack carbon (BC) induced indirect radiative forcing and cloud albedo effect has been studied for the first time over northeast India. Measurements of BC and cloud microphysical parameters were carried out during Phase-I of the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) over northeast India (Guwahati) in 2009. Liquid water path (LWP) in the cloud layers coherent with BC on different experimental days was found to be 206–327 g m−2 over the region. Black carbon aerosol indirect effect (BCIE) for fixed LWP is found to be 0.32–0.48 on different days of observations. The indirect forcing corresponding to this BCIE has been estimated using a radiative transfer model for fixed LWP by altering the derived BC-AOD (aerosol optical depth from measured BC profiles) and cloud effective radius (Re) combinations. The estimated average BC-induced indirect forcing (BCIF) was −24 to −37.1 W m−2 at the surface and +2.5 to +14.8 W m−2 at the top of the atmosphere (TOA). The average albedo due to BCIF at TOA was 0.49–0.61. BCIF is found to reduce the cloud reflection by 1.5–2% over the region. The sensitivities of cloud parameters to BCIF and the albedo effect are illustrated
Indian summer monsoon intra-seasonal oscillation associated with the developing and decaying phase of El Nino
No full textThe present study investigates the characteristics of active and break cycles associated with the Indian summer monsoon (ISM) during developing and decaying phase of El Niño and in the years in which Indian Ocean Dipole (IOD) co-occurred with El Niño (co-occurred years). Observations show that break days are more in number (∼2–3 times) and long lasting (∼15–20 days) than active days in El Niño developing summers and vice versa for decay years. During El Niño developing years, northward propagation is well organized with significant anomalies in both active and break phases. The increased convection associated with active phase persists longer over Indian Ocean, than over the monsoon region, while the reduced convection in break phase propagates faster from ocean to land and persists there for a longer time. Compared to break events, active events have slower (faster) propagation over the monsoon (oceanic) region during El Nino decay years. The present study put forward the argument that the contrasting persistent circulations over Indo-western Pacific regions favour particular phase of intra-seasonal oscillation (ISO) in developing and decay phase of El Nino. These long-lasting circulations advect anomalous dry (moist) air to ISM region for longer period, resulting in long-lasting break (active) events in El Niño developing (decay) years. During co-occurrence years, the number of break (active) days is reduced by two to three times compared to the developing (decaying) phase of El Niño. It is found that 30- to 60-day scale ISO is strongly modulated, than 10 - to 20-day scale, by the changes in seasonal mean state associated with El Nino. Thus, this study demonstrates that the ISO characteristics such as its variance, northward propagation, spatial distribution and duration of active and break days are strongly modulated by seasonal background anomalies over the Indo-Pacific region
Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error
No full textA detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and Pacific Ocean basin, with special emphasis on the Indian land region. The simulated seasonal mean and the inter-annual standard deviations of rainfall, upper and lower level atmospheric circulations and Sea Surface Temperature (SST) tend to be more skillful as the lead forecast time decreases (5 month lead to 0 month lead time i.e. L5–L0). In general spatial correlation (bias) increases (decreases) as forecast lead time decreases. This is further substantiated by their averaged value over the selected study regions over the Indian and Pacific Ocean basins. The tendency of increase (decrease) of model bias with increasing (decreasing) forecast lead time also indicates the dynamical drift of the model. Large scale lower level circulation (850 hPa) shows enhancement of anomalous westerlies (easterlies) over the tropical region of the Indian Ocean (Western Pacific Ocean), which indicates the enhancement of model error with the decrease in lead time. At the upper level circulation (200 hPa) biases in both tropical easterly jet and subtropical westerlies jet tend to decrease as the lead time decreases. Despite enhancement of the prediction skill, mean SST bias seems to be insensitive to the initialization. All these biases are significant and together they make CFSv2 vulnerable to seasonal uncertainties in all the lead times. Overall the zeroth lead (L0) seems to have the best skill, however, in case of Indian summer monsoon rainfall (ISMR), the 3 month lead forecast time (L3) has the maximum ISMR prediction skill. This is valid using different independent datasets, wherein these maximum skill scores are 0.64, 0.42 and 0.57 with respect to the Global Precipitation Climatology Project, CPC Merged Analysis of Precipitation and the India Meteorological Department precipitation dataset respectively for L3. Despite significant El-Niño Southern Oscillation (ENSO) spring predictability barrier at L3, the ISMR skill score is highest at L3. Further, large scale zonal wind shear (Webster–Yang index) and SST over Niño3.4 region is best at L1 and L0. This implies that predictability aspect of ISMR is controlled by factors other than ENSO and Indian Ocean Dipole. Also, the model error (forecast error) outruns the error acquired by the inadequacies in the initial conditions (predictability error). Thus model deficiency is having more serious consequences as compared to the initial condition error for the seasonal forecast. All the model parameters show the increase in the predictability error as the lead decreases over the equatorial eastern Pacific basin and peaks at L2, then it further decreases. The dynamical consistency of both the forecast and the predictability error among all the variables indicates that these biases are purely systematic in nature and improvement of the physical processes in the CFSv2 may enhance the overall predictability
Sub-seasonal behaviour of Asian summer monsoon under a changing climate: assessments using CMIP5 models
No full textNumerous global warming studies show the anticipated increase in mean precipitation with the rising levels of carbon dioxide concentration. However, apart from the changes in mean precipitation, the finer details of daily precipitation distribution, such as its intensity and frequency (so called daily rainfall extremes), need to be accounted for while determining the impacts of climate changes in future precipitation regimes. Here we examine the climate model projections from a large set of Coupled Model Inter-comparison Project 5 models, to assess these future aspects of rainfall distribution over Asian summer monsoon (ASM) region. Our assessment unravels a north–south rainfall dipole pattern, with increased rainfall over Indian subcontinent extending into the western Pacific region (north ASM region, NASM) and decreased rainfall over equatorial oceanic convergence zone over eastern Indian Ocean region (south ASM region, SASM). This robust future pattern is well conspicuous at both seasonal and sub-seasonal time scales. Subsequent analysis, using daily rainfall events defined using percentile thresholds, demonstrates that mean rainfall changes over NASM region are mainly associated with more intense and more frequent extreme rainfall events (i.e. above 95th percentile). The inference is that there are significant future changes in rainfall probability distributions and not only a uniform shift in the mean rainfall over the NASM region. Rainfall suppression over SASM seems to be associated with changes involving multiple rainfall events and shows a larger model spread, thus making its interpretation more complex compared to NASM. Moisture budget diagnostics generally show that the low-level moisture convergence, due to stronger increase of water vapour in the atmosphere, acts positively to future rainfall changes, especially for heaviest rainfall events. However, it seems that the dynamic component of moisture convergence, associated with vertical motion, shows a strong spatial and rainfall category dependency, sometimes offsetting the effect of the water vapour increase. Additionally, we found that the moisture convergence is mainly dominated by the climatological vertical motion acting on the humidity changes and the interplay between all these processes proves to play a pivotal role for regulating the intensities of various rainfall events in the two domains