3194 research outputs found
Sort by
Radiative forcing estimation of aerosols at an urban site near the Thar Desert using ground-based remote sensing measurements
No full textThe focus of present study is to quantify the radiation budget of aerosols over Jaipur (Northwestern, India) from 2011 to
2015. The Aerosol radiative forcing (ARF) has been determined for shortwave spectrum (0.3–3.0 µm) individually for the
top of the atmosphere (TOA), bottom of the atmosphere (BOA) and within the atmosphere (ATM) over study region. Santa
Barbara DISORT Atmospheric Radiative Transfer model (SBDART) is used to simulate the aerosols radiative effect.
The inter-annual monthly average of ARF at TOA during 2011–2015 is found between –11.40 to –5.60 W m–2, while
the ARF at BOA is found to be between –32.2 to –22.49 W m–2. Likewise, the ARF within the atmosphere (ATM) comes
between 14.04 to 22.47 W m–2 over Jaipur.
The SBDART model is run discretely for Dust period (DSP) and non-Dust Period (NDP) during the year 2012 to inspect
the change in ARF during extreme events over the Jaipur site. During DSP, the net TOA and BOA forcing are found in the
range –20.71 to –16.81 W m–2 and –45.15 to –39.6 W m–2, respectively, and net ATM forcing varies in the range 22.7 to
24.4 W m–2. For the NDP, the corresponding value varies in the range –10.1 to –6.6 W m–2 and –23.6 to –22.3 W m–2. The
net ATM forcing during NDP is between 12.2 to 17.05 W m–2. The value of BOA increases more than ~67% during DSP
than NDP. The more increase (–ve) in surface forcing represents the cooling of the surface during DSP. The results depict
that dust over Jaipur in the vicinity of the Thar Desert is scattering in nature with high value (> 0.95) of SSA. The
scattering is mostly high during summer and low in winter
Homogeneous clusters over India using probability density function of daily rainfall
No full textThe Indian landmass has been divided into homogeneous clusters by applying the cluster analysis to the probability density function of a century-long time series of daily summer monsoon (June through September) rainfall at 357 grids over India, each of approximately 100 km × 100 km. The analysis gives five clusters over Indian landmass; only cluster 5 happened to be the contiguous region and all other clusters are dispersed away which confirms the erratic behavior of daily rainfall over India. The area averaged seasonal rainfall over cluster 5 has a very strong relationship with Indian summer monsoon rainfall; also, the rainfall variability over this region is modulated by the most important mode of climate system, i.e., El Nino Southern Oscillation (ENSO). This cluster could be considered as the representative of the entire Indian landmass to examine monsoon variability. The two-sample Kolmogorov-Smirnov test supports that the cumulative distribution functions of daily rainfall over cluster 5 and India as a whole do not differ significantly. The clustering algorithm is also applied to two time epochs 1901–1975 and 1976–2010 to examine the possible changes in clusters in a recent warming period. The clusters are drastically different in two time periods. They are more dispersed in recent period implying the more erroneous distribution of daily rainfall in recent period
Seminal role of stratiform clouds in large‑scale aggregation of tropical rain in boreal summer monsoon intraseasonal oscillations
No full textModification of the vertical structure of non-adiabatic heating by significant abundance of the stratiform rain in the tropics has been known to influence the large-scale circulation. However, the role of the stratiform rain on the space–time evolution of the observed Boreal summer monsoon intraseasonal oscillations (MISO) has so far been ignored. In the present study, we unravel a feedback mechanism through which the stratiform component of the rain leads to aggregation (organization) of rain on the MISO scale, making it an indispensable component of the MISO evolution dynamics. Using TRMM 3A25 monthly mean data (between 1998 and 2013), the ratio between convective and stratiform rain (RCS) is shown to be strongly related to the total rainfall. Further, composites of rainfall and circulation anomalies corresponding to high (low) values of RCS over the Central India or over the Equatorial Indian Ocean show spatial structures remarkably similar to that associated with the MISOs. Analyzing lead–lag relationship between the convective rain, the stratiform rain and the large scale moisture convergence with respect to peak active (break) spells from daily modern era retrospective-analysis for research and applications data, we unravel that the initial isolated convective elements spawn the stratiform rain which in turn modifies the vertical distribution of heating and leads to stronger large scale moisture convergence thereby producing more convective elements and more stratiform rain ultimately leading to aggregation of rain on the MISO scale. Our finding indicates that large and persisting systematic biases in simulating the summer monsoon rainfall over the Asian monsoon region by climate models are likely to be related to the systematic biases in simulating the MISOs which in turn are related to the serious underestimation of stratiform rain in most climate models
Evaluation of NCEP TIGGE short-range forecast for Indian summer monsoon intraseasonal oscillation
No full textThis study focuses on the short-range prediction of Monsoon Intraseasonal Oscillations (MISOs) using the National Centers for Environmental Prediction(NCEP) Ensemble Prediction System (EPS) data from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) archive. The Indian Summer Monsoon Rainfall (ISMR), which plays an important role in the socio-economic growth of the country, is highly variable and is mostly governed by the MISOs. In addition to this, deterministic forecasts of ISMR are not very reliable. Hence, a probabilistic approach at daily scale is required. Keeping this in mind, the present analysis is done by using daily forecast data for up to 7-day lead time and compared with observations. The analysis shows that the ensemble forecast well captures the variability as compared to observations even up to 7 days. The spatial characteristics and the northward propagation of MISO are observed thoroughly in the EPS. The evolution of dynamical and thermodynamical parameters such as specific humidity, moist static energy, moisture divergence, and vorticity is also captured well but show deviation from the observation from 96 h lead time onwards. The tropospheric temperature forecast captures the observed gradient but with certain bias in magnitude whereas the wind shear is simulated quite well both in pattern and magnitude. These analyses bring out the biases in TIGGE EPS forecast and also point out the possible moist processes which needs to be improved
Dominant modes of recycled monsoon rainfall over India
No full textThis study estimates the seasonal mean (June–September) recycled rainfall and investigates its dominant modes of variability over the continental regions of the Indian summer monsoon. A diagnostic method based on the basic atmospheric water vapor budget equation is employed in order to partition the observed rainfall into recycled and advected components. The global teleconnections with the recycled (advected) rainfall are found to be weak (strong), which is consistent with the basic assumptions of the sources of atmospheric water vapor. It is shown that the mean recycled rainfall over the Indo-Gangetic Plain, central India, and western Himalayas ranges between 10% and 40% of the total rainfall. While EOF1 (38.5%) of the recycled rainfall reveals covariability between the regional and external influences, EOF2 (14%) shows a mode independent to the external influences (i.e., advected rainfall), prevailing over the Indo-Gangetic Plain. Furthermore, a strong decreasing trend in PC2 over the last 36 years suggests a change in the local feedback (land, atmosphere), which in turn may have also contributed to the decreasing trend in the observed monsoon rainfall over central and northern India
Observed trends and changes in daily temperature and precipitation extremes over the Koshi river basin
Get PDFThe Koshi river basin is a sub-basin of the Ganges shared among China, Nepal, and India. The river system has a high potential for investment in hydropower development and for irrigation in downstream areas. The upper part of the basin contains a substantial reserve of freshwater in the form of snow and glaciers. Climate variability, climate change, and climate extremes might impact on these reserves, and in turn impact on systems that support livelihoods, such as agriculture, biodiversity and related ecosystem services. Climatological variability and trends over the Koshi river basin were studied using RClimDex. Daily temperature data (20 stations) and precipitation data (50 stations) from 1975 to 2010 were used in the analysis. The results show that the frequency and intensity of weather extremes are increasing. The daily maximum temperature (TXx) increased by 0.1 °C decade−1 on average between 1975 and 2010 and the minimum (TNn) by 0.3 °C decade−1. The number of warm nights increased at all stations. Most of the extreme temperature indices showed a consistently different pattern in the mountains than in the Indo-Gangetic plains, although not all results were statistically significant. The warm days (TX90p), warm nights (TN90p), warm spell duration (WSDI), and diurnal temperature range (DTR) increased at most of the mountain stations; whereas monthly maximum and minimum values of daily maximum temperature, TX90p, cool nights (TN10p), WSDI, cold spell duration indicator (CSDI), DTR decreased at the stations in the Indo-Gangetic plains, while the number of cold days increased. There was an increase in total annual rainfall and rainfall intensity, although no clear long-term linear trend, whereas the number of consecutive dry days increased at almost all stations. The results indicate that the risk of extreme climate events over the basin is increasing, which will increase people's vulnerability and has strong policy implications
Identification of coral reef feature using hyperspectral remote sensing
No full textPresent study employs reef-up approach to map coral reef zones along the Sentinel Island of Andaman using high spectral resolution offered by hyper spectral imagery by Hyperion mission of NASA. This data consisting of 242 spectral bands, provide a unique ability to identify Coral substrate based on their spectral properties. We applied atmospheric correction with the help of Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) module of ENVI software. This atmospherically corrected was used to extract Coral Reef Zones (CRZ) based on specific threshold limits after subtracting data of 782.95nm band from 579.45nm band of Hyperion imagery. Both of these bands were chosen due to their property of exhibiting maximum spectral contrast that determines threshold limits to distinguish a coral area from its non-coral counterpart. These CRZs were compared with the coral reef zones base map developed using LISS-III data by INCOIS, Hyderabad and SAC, Ahmadabad under CZS project. We observed that extracted CRZ area was 85.25 m2 and 110.1 m2 using LISS-III and Hyperion Data respectively. Despite the overestimation of CRZ by Hyperion data as compared to LISS-III, the spatial distribution of CRZ showed reasonable similarity in both
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
Observations of monsoon convective cloud microphysics over India and role of entrainment-mixing
No full textMicrophysical characteristics of premonsoon and monsoon deep cumuli over India observed by an instrumented aircraft are contrasted focusing on influences of environmental conditions and entrainment-mixing processes. Differences in the lower tropospheric temperature and moisture profiles lead to contrasting undiluted cloud buoyancy profiles around the cloud base, larger in the premonsoon case. It is argued that this affects the variation of the mean and maximum cloud droplet number concentrations and the droplet radius within the lowest several hundred meters above the cloud base. The conserved-variable thermodynamic diagram analysis suggests that entrained parcels originate from levels close to the observational level. Mixing processes and their impact on the droplet size distribution (DSD) are investigated contrasting 1 Hz and 10 Hz observations. Inhomogeneous-type mixing, likely because of unresolved small-scale structures associated with active turbulent stirring, is noted at cloud edge volumes where dilution is significant and DSDs shift toward smaller sizes with reduced droplet number concentrations due to complete evaporation of smaller droplets and partial evaporation of larger droplets. DSDs within cloud core volumes suggest that the largest droplets are formed in the least diluted volumes where raindrops can form at higher levels; no superadiabatic droplet growth is observed. The typical diluted parcel size is approximately 100–200 m for cloud edge volumes, and it is much smaller, 10–20 m, for cloud core volumes. Time scale analysis indicates the possibility of inhomogeneous type mixing within the diluted cloud edge volumes at spatial scales of a 100 m or more
Atmospheric controls on the precipitation isotopes over the Andaman Islands, Bay of Bengal
No full textIsotopic analysis of precipitation over the Andaman Island, Bay of Bengal was carried out for the year 2012 and 2013 in order to study the atmospheric controls on rainwater isotopic variations. The oxygen and hydrogen isotopic compositions are typical of the tropical marine sites but show significant variations depending on the ocean-atmosphere conditions; maximum depletion was observed during the tropical cyclones. The isotopic composition of rainwater seems to be controlled by the dynamical nature of the moisture rather than the individual rain events. Precipitation isotopes undergo systematic depletions in response to the organized convection occurring over a large area and are modulated by the integrated effect of convective activities. Precipitation isotopes appear to be linked with the monsoon intraseasonal variability in addition to synoptic scale fluctuations. During the early to mid monsoon the amount effect arose primarily due to rain re-evaporation but in the later phase it was driven by moisture convergence rather than evaporation. Amount effect had distinct characteristics in these two years, which appeared to be modulated by the intraseasonal variability of monsoon. It is shown that the variable nature of amount effect limits our ability to reconstruct the past-monsoon rainfall variability on annual to sub-annual time scale