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Simulation of monsoon intraseasonal variability in NCEP CFSv2 and its role on systematic bias
No full textWe have evaluated the simulation of Indian summer monsoon and its intraseasonal oscillations in the National Centers for Environmental Prediction climate forecast system model version 2 (CFSv2). The dry bias over the Indian landmass in the mean monsoon rainfall is one of the major concerns. In spite of this dry bias, CFSv2 shows a reasonable northward propagation of convection at intraseasonal (30-60Â day) time scale. In order to document and understand this dry bias over the Indian landmass in CFSv2 simulations, a two pronged investigation is carried out on the two major facets of Indian summer monsoon: one, the air-sea interactions and two, the large scale vertical heating structure in the model. Our analysis shows a possible bias in the co-evolution of convection and sea surface temperature in CFSv2 over the equatorial Indian Ocean. It is also found that the simulated large scale vertical heat source (Q1) and moisture sink (Q2) over the Indian region are biased relative to observational estimates. Finally, this study provides a possible explanation for the dry precipitation bias over the Indian landmass in the simulated mean monsoon on the basis of the biases associated with the simulated ocean-atmospheric processes and the vertical heating structure. This study also throws some light on the puzzle of CFSv2 exhibiting a reasonable northward propagation at the intraseasonal time scale (30-60Â day) despite a drier monsoon over the Indian land mass
Epochal changes in the seasonal evolution of tropical Indian Ocean warming associated with El Niño
No full textThe epochal changes in the seasonal evolution of El Niño induced tropical Indian Ocean (TIO) warming in the context of mid-1970s regime shift is investigated in this study. El Niño induced warming is delayed by one season in the northern TIO during epoch-2 (post mid-1970) and southern TIO during epoch-1 (pre mid-1970). Significant spatiotemporal changes in TIO (especially in the north) warming are apparent during the developing phase of El Niño. The ocean dynamics is the major driver in the basin wide warming during epoch-2 whereas heat fluxes are the dominant processes during epoch-1. Strong coupling between thermocline and sea surface temperature (SST) in epoch-2 indicates that El Niño induced oceanic changes are very significant in the seasonal evolution of basin-wide warming. The thermocline-SST coupling is strengthened by the upward propagating subsurface warming in epoch-2. The westward propagating barrier layer over southern TIO supports persistence of warm SST (over southwest TIO in epoch-2), which in turn induce spring asymmetric mode in winds and precipitation. The asymmetric wind pattern and persistent subsidence over maritime continent are primarily responsible for stronger spring warming in epoch-2. The strong east equatorial Indian Ocean cooling in epoch-2 is mainly driven by coastal upwelling over Java-Sumatra coast, whereas in epoch-1 the weak cooling is controlled by the latent heat flux. The spatiotemporal changes in TIO SST warming and their evolution have strong impact on atmospheric circulation and rainfall distribution over the Indian Oceanic rim through local air-sea interaction
Climatology of lightning over Indian region and its relationship with convective available potential energy
No full textThe spatial distribution of convective available potential energy (CAPE) and lightning activity in different seasons over the Indian region have been studied to find out the dependence of lightning activity on CAPE. It is observed that the lightning activity over the Indian region is not controlled by CAPE alone during pre-monsoon season. The prevailing meteorological conditions and orography over northern India, central India, northeast Pakistan and Bangladesh provide favourable conditions for formation of thunderstorms, and hence, lightning activity is higher in spite of lower value of CAPE over these regions compared to other parts of Indian region. During the monsoon season, lightning activity and CAPE are found to be better correlated with each other compared to other seasons over central and north India. It has been found that the high mountains of Himalayas generate strong updrafts necessary for the deep convective events by interacting with prevailing winds and the diabatic heating and radiative cooling of mountaintops create conditions favourable for convections. The diurnal variation of lightning activity at stations over the foothills of Himalayas showing a strong peak in lighting activity after midnight supports the idea that radiative cooling at mountaintops can create a moisture convergence at foothills and trigger the convections
Spatio-temporal rainfall variability over Goa, India
No full textGoa is India's smallest state by area and is located on the west coast. Nine major rivers run through it, of which the Mandovi and the Zuari rivers are the major and important rivers from an irrigation and hydropower point of view. The spatial and temporal variation of rainfall in these basins has a great influence on water resources of the state. In view of this, on the basis of available monthly rainfall data from 1901-2012 and daily rainfall data for the period of 2001-2012 for the stations located in north and south districts of Goa, an analysis was carried out to review the mean monthly, seasonal and annual rainfall intensity, trends and its spatial distribution; severe rainstorms and their raindepths for different durations. The analysis will be important in water planning projects, especially irrigation,hydropower and flood control, etc. for Goa
Impacts of the high loadings of primary and secondary aerosols on light extinction at Delhi during wintertime
No full textHigh emissions of anthropogenic aerosols over Indo-Gangetic Plain (IGP) inspired continuous measurements of fine particles (PM2.5), carbonaceous aerosols (BC, OC and EC), oxides of nitrogen (NOx) and estimation of light extinction (bext) and absorption (babs) coefficients over Delhi during high pollution season in winter from December 2011 to March 2012. During study period, the mass concentrations of PM2.5, BC and NOx were 186.5±149.7μgm-3, 9.6±8.5μgm-3 and 23.8±16.1ppb, respectively. The mass concentrations of OC and EC were studied by two different techniques (i) off-line (gravimetric method) and (ii) semi-continuous (optical method) and their mean mass concentrations were 51.1±15.2, 10.4±5.5μgm-3 and 33.8±27.7, 8.2±6.2μgm-3, respectively during the study period. The ratios of mass concentration of OC to EC in both cases were in between 4 and 5. The source contribution of carbonaceous aerosols in PM2.5 estimated over 24hrs, during day- and night-time where motor vehicles accounted for ~69, 90 and 61 whereas coal combustion accounted for ~31, 10 and 39, respectively. The estimated mean values of bext and babs over the station were 700.0±268.6 and 71.7±54.6Mm-1, respectively. In day and night analysis, bext is ~37 higher during night-time (863.4Mm-1) than in day-time (544.5Mm-1). Regression analysis between bext and visibility showed significant negative correlation (r=-0.85). The largest contribution in the light extinction coefficients was found to be due to organic carbon (~46), followed by elemental carbon (~24), coarse mode particles (~18), ammonium sulfate (~8) and ammonium nitrate (~4). The individual analysis of light extinction due to chemical species and coarse mode particles indicates that scattering type aerosols dominated by ~76 over the absorbing type. The aforementioned results suggest that the policy-induced control measures at local administration level are needed to mitigate the excess emissions of carbonaceous aerosols over IGP region which ranks highest in India and elsewhere in worldwide
Airborne LiDAR and high resolution satellite data for rapid 3D feature extraction
Get PDFThis work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary?.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM. The CHM or the normalized DSM represents the absolute height of all aboveground urban features relative to the ground. After normalization, the elevation value of a point indicates the height from the ground to the point. The above-ground points were used for tree feature and building footprint extraction. In individual tree extraction, first and last return point clouds were used along with the bare earth and building footprint models discussed above. In this study, scene dependent extraction criteria were employed to improve the 3D feature extraction process. LiDAR-based refining/ filtering techniques used for bare earth layer extraction were crucial for improving the subsequent 3D features (tree and building) feature extraction. The PAN-sharpened WV-2 image (with 0.5 m spatial resolution) was used to assess the accuracy of LiDAR-based 3D feature extraction. Our analysis provided an accuracy of 98% for tree feature extraction and 96% for building feature extraction from LiDAR data. This study could extract total of 15143 tree features using CHM method, out of which total of 14841 were visually interpreted on PAN-sharpened WV-2 image data. The extracted tree features included both shadowed (total 13830) and non-shadowed (total 1011). We note that CHM method could overestimate total of 302 tree features, which were not observed on the WV-2 image. One of the potential sources for tree feature overestimation was observed in case of those tree features which were adjacent to buildings. In case of building feature extraction, the algorithm could extract total of 6117 building features which were interpreted on WV-2 image, even capturing buildings under the trees (total 605) and buildings under shadow (total 112). Overestimation of tree and building features was observed to be limiting factor in 3D feature extraction process. This is due to the incorrect filtering of point cloud in these areas. One of the potential sources of overestimation was the man-made structures, including skyscrapers and bridges, which were confounded and extracted as buildings. This can be attributed to low point density at building edges and on flat roofs or occlusions due to which LiDAR cannot give as much precise planimetric accuracy as photogrammetric techniques (in segmentation) and lack of optimum use of textural information as well as contextual information (especially at walls which are away from roof) in automatic extraction algorithm. In addition, there were no separate classes for bridges or the features lying inside the water and multiple water height levels were also not considered. Based on these inferences, we conclude that the LiDAR-based 3D feature extraction supplemented by high resolution satellite data is a potential application which can be used for understanding and characterization of urban setup
Deviations from the O3-NO-NO2 photo-stationary state in Delhi, India
No full textA network of air quality and weather monitoring stations was set-up across Delhi, India, under the System of Air quality Forecasting And Research (SAFAR) project. The objective of this network was to enable better understanding of air quality in terms of atmospheric chemistry, emissions and forecasting in Delhi, one of the largest metropolises in the world. In this study, we focus on the O3–NO–NO2-triad Photo Stationary State (PSS), and investigate site-specific deviations in the Leighton Ratio (Φ) during a short period in 2012 (1–31 December). Large variations were observed in the NO ( 1) were also observed occasionally, and these data were used to estimate the total peroxy radical (PO2) mixing ratios. This is the first estimate of PO2 reported for the city of Delhi and compares well with the results in the literature
Water-soluble organic carbon aerosols during a full New Delhi winter: Isotope-based source apportionment and optical properties
No full textWater-soluble organic carbon (WSOC) is a major constituent (~ 20–80%) of the total organic carbon aerosol over the Indian subcontinent during the dry winter season. Due to its multiple primary and secondary formation pathways, the sources of WSOC are poorly characterized. In this study, we present radiocarbon constraints on the biomass versus fossil sources of WSOC in PM2.5 for the 2010/2011 winter period for the megacity Delhi, situated in the northern part of the heavily polluted Indo-Gangetic Plain. The fossil fuel contribution to Delhi WSOC (21 ± 4%) is similar to that recently found at two South Asian background sites. In contrast, the stable carbon isotopic composition of Delhi WSOC is less enriched in 13C relative to that at the two receptor sites. Although potentially influenced also by source variability, this indicates that near-source WSOC is less affected by atmospheric aging. In addition, the light absorptive properties of Delhi WSOC were studied. The mass absorption cross section at 365 nm (MAC365) was 1.1–2.7 m2/g with an Absorption Ångström Exponent ranging between 3.1 and 9.3. Using a simplistic model the relative absorptive forcing of the WSOC compared to elemental carbon in 2010/2011 wintertime Delhi was estimated to range between 3 and 11%. Taken together, this near-source study shows that WSOC in urban Delhi comes mainly (79%) from biomass burning/biogenic sources. Furthermore, it is less influenced by photochemical aging compared to WSOC at South Asian regional receptor sites and contributes with a relatively small direct absorptive forcing effect
Assessing Hydrological Response to Changing Climate in the Krishna Basin of India
Get PDFImpact of climate change on water balance components in the Krishna river basin are investigated using a semidistributed
hydrological model namely Soil and Water Assessment Tool (SWAT). The model is calibrated and validated
using the measured stream flow and meteorological data for the period (1970-1990) at a single guage outlet. The model
has been used further for hydrologic parameter simulations. Daily climate simulations from regional climate model
PRECIS (Providing Regional Climates for Impacts Studies) is used as input for running SWAT and monthly hydrologic
parameters such as precipitation, surface flow, water yield, Evapotranspiration (ET) and Potential Evapotranspiration
(PET) are generated under the assumption of no change in Land Use and Land Cover (LULC) pattern over time.
Simulations at 23 sub-basins of the Krishna basin have been obtained for the control runs (1961-1990) and the for
two time slices of future scenarios (2011-2040) and (2041-2070). Model projections indicate increase in the annual
discharge, surface runoff and base flow in the basin in mid-century
Rainfall and Groundwater Level Variation in Pune District, India
Get PDFRapid industrial development, urbanization and increase in agricultural production have led to freshwater shortages in many parts of the Pune district. The availability of groundwater is extremely uneven, both in space, time and depth which will be the case in future also. The present study concerns the impacts of a change in the rainfall regime on surface and groundwater resources in watersheds of Pune district during 2001 to 2012. This study shows that water level in many villages reachs almost bottom of the observatory well during May e.g. Dive Village in Purandar taluka reachs 32.40 m bgl in May 2004 as against 710 mm of rainfall recorded by the taluka. Categorization of groundwater level reveals that although there is rise in water level during October, even then 50% villages experience semi-critical condition. Therefore, there is an urgent need of planned and optimal development of water resources in this district