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Rohit Chakraborty

Bio: Rohit Chakraborty is an academic researcher from University of Calcutta. The author has contributed to research in topics: Nowcasting & Convective available potential energy. The author has an hindex of 9, co-authored 24 publications receiving 224 citations. Previous affiliations of Rohit Chakraborty include National Atmospheric Research Laboratory.

Papers
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Journal ArticleDOI
TL;DR: In this article, a microwave radiometer was used for nowcasting of heavy rain events at Kolkata (22.65°N, 88.45°E), a tropical location.

39 citations

Journal ArticleDOI
TL;DR: In this article, a random forest based machine learning algorithm is tested for nowcasting of convective rain with a ground-based radiometer and the results indicate that the proposed model is very sensitive to the boundary layer instability as indicated by the variable importance measure.

36 citations

Journal ArticleDOI
TL;DR: In this article, the effectiveness of nowcasting convective activities using a microwave radiometer has been examined for Kolkata (22.65° N, 88.45° E), a tropical location.

26 citations

Journal ArticleDOI
01 May 2017
TL;DR: In this paper, the authors investigated the behavior of various meteorological parameters during 1981-2010 to obtain any asymmetric variability of summertime near surface wind over Indian coastal boundaries, and found that no significant changes were obtained in the trends of surface pressure, surface relative humidity, 2-metre temperature and surface precipitation.
Abstract: The behaviors of various meteorological parameters during 1981–2010 are investigated to obtain any asymmetric variability of summertime near surface wind over Indian coastal boundaries. No significant changes were obtained in the trends of surface pressure, surface relative humidity, 2-metre temperature and surface precipitation; although, near surface wind speed is found to have significantly declined on the eastern coast with respect to the western coast during this period. Summertime surface wind speed on the eastern coast have decreased from 3.5 to 2.5 m s − 1 (7 to 5 knots) whereas 4.5 to 4 m s − 1 (9 to 8 knots) during the last three decades (statistical significance level ~ 95%). A decrease in the atmospheric instability may serve as the potential reason for the suppression of severe convective occurrences manifested by a parallel decrease in surface wind speeds over these regions. The local heating up of middle atmosphere (300–500 hPa pressure level) due to increased humidity and the difference in net heat flux over Arabian Sea and Bay of Bengal due to the variance of temperature gradient (1000–925 hPa) along the coastal boundaries might be responsible for this climatic disparity between the coastal regions of India since the last three decades. Summertime near surface wind speed projections for Indian sub-continent based on 7 best climate models, for RCP8.5 scenarios, has been calculated to show a mean increase by ~ 10–15% on the eastern coast (Eastern Ghats), ~ 1–2% on the western coasts (Western Ghats), ~ 1–5% decrease in the Indo-Gangetic Basin and ~ 3% decrease in the Gangetic West Bengal and adjoining Bangladesh.

26 citations


Cited by
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01 May 2007
TL;DR: The authors examined the response of the tropical atmospheric and oceanic circulation to increasing greenhouse gases using a coordinated set of twenty-first-century climate model experiments performed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4).
Abstract: This study examines the response of the tropical atmospheric and oceanic circulation to increasing greenhouse gases using a coordinated set of twenty-first-century climate model experiments performed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The strength of the atmospheric overturning circulation decreases as the climate warms in all IPCC AR4 models, in a manner consistent with the thermodynamic scaling arguments of Held and Soden. The weakening occurs preferentially in the zonally asymmetric (i.e., Walker) rather than zonal-mean (i.e., Hadley) component of the tropical circulation and is shown to induce substantial changes to the thermal structure and circulation of the tropical oceans. Evidence suggests that the overall circulation weakens by decreasing the frequency of strong updrafts and increasing the frequency of weak updrafts, although the robustness of this behavior across all models cannot be confirmed because of the lack of data. As the cli...

78 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the effects of climate and land use changes on flood susceptibility areas in the Tajan watershed, Iran and found that elevation (21.55), distance from river (15.28), land use (11.1), slope (10.58), and rainfall (6.8) are the most important factors affecting flooding in this basin.

69 citations

Journal ArticleDOI
TL;DR: It is shown that in climate research, intermediate categories exist between classical domain science and big data, and that big-data elements have also been applied without the possibility of repeated evaluation.
Abstract: Commercial success of big data has led to speculation that big-data-like reasoning could partly replace theory-based approaches in science. Big data typically has been applied to ‘small problems’, which are well-structured cases characterized by repeated evaluation of predictions. Here, we show that in climate research, intermediate categories exist between classical domain science and big data, and that big-data elements have also been applied without the possibility of repeated evaluation. Big-data elements can be useful for climate research beyond small problems if combined with more traditional approaches based on domain-specific knowledge. The biggest potential for big-data elements, we argue, lies in socioeconomic climate research. Big data is increasingly popular in many research domains. This Perspective discusses where elements of big data approaches have been employed in climate research and where combining big data with theory-driven research can be most fruitful.

49 citations

Journal ArticleDOI
TL;DR: Higher values for the mean Pearson coefficient (R) and the symmetric index of agreement (λ) were obtained for the RF model, indicating that this RF model could reasonably estimate the grassland AGB (65.01%) on the Loess Plateau.
Abstract: Grasslands are an important component of terrestrial ecosystems that play a crucial role in the carbon cycle and climate change. In this study, we collected aboveground biomass (AGB) data from 223 grassland quadrats distributed across the Loess Plateau from 2011 to 2013 and predicted the spatial distribution of the grassland AGB at a 100-m resolution from both meteorological station and remote sensing data (TM and MODIS) using a Random Forest (RF) algorithm. The results showed that the predicted grassland AGB on the Loess Plateau decreased from east to west. Vegetation indexes were positively correlated with grassland AGB, and the normalized difference vegetation index (NDVI) acquired from TM data was the most important predictive factor. Tussock and shrub tussock had the highest AGB, and desert steppe had the lowest. Rainfall higher than 400 m might have benefitted the grassland AGB. Compared with those obtained for the bagging, mboost and the support vector machine (SVM) models, higher values for the mean Pearson coefficient (R) and the symmetric index of agreement (λ) were obtained for the RF model, indicating that this RF model could reasonably estimate the grassland AGB (65.01%) on the Loess Plateau.

46 citations

Journal ArticleDOI
01 Mar 2019-Heliyon
TL;DR: The trend patterns of Tmax, Tmin, and MTR reveal that most of the regions of the country have been colder during winter and hotter during the monsoon, while the wind speed has decreased significantly all over the country and decreased by a higher rate in the north-western (NW) region.

42 citations