New climatic classification of Nepal     

Ramchandra Karki  Rocky Talchabhadel  Juha Aalto  Saraju Kumar Baidya 《Theoretical and Applied Climatology》2016,125(3-4):799-808

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Characterization and radiative impact of dust aerosols over northwestern part of India: a case study during a severe dust storm     

Atinderpal Singh  Shani Tiwari  Deepti Sharma  Darshan Singh  Suresh Tiwari  Atul Kumar Srivastava  Neeraj Rastogi  A. K. Singh 《Meteorology and Atmospheric Physics》2016,128(6):779-792

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Is the interdecadal variation of the summer rainfall over eastern China associated with SST?   总被引：1，自引：0，他引：1  

Dong Si  Zeng-Zhen Hu  Arun Kumar  Bhaskar Jha  Peitao Peng  Wanqiu Wang  Rongqing Han 《Climate Dynamics》2016,46(1-2):135-146

The present study examined the major features of the interdecadal variation of the summer rainfall over eastern China (IVRC) and the possible association with sea surface temperature (SST). We noted that the first leading mode of IVRC (accounting for nearly half of the total variance and with maximum loading for the summer rainfall anomalies over South China) may be not forced by SST. On the other hand, the second and third leading modes [accounting for 17.1 and 13.6 % of the total variance and mainly associated with the summer rainfall anomalies over the Yangtze River valley (YRV) and North China, respectively] in some extent are forced by SST anomalies. These observational results are confirmed by atmospheric general circulation model (AGCM) simulations forced by observed SST. By eliminating the internal dynamical process driven rainfall though ensemble mean, the simulations further suggest an overall enhancement of the intensity of IVRC in the corresponding ensemble mean, especially in the YRV and North China regions, but not in South China. That implies the different role of SST in driving IVRC over different regions.  相似文献   

Erratum to: Climate change projections over India by a downscaling approach using PRECIS     

Prasanta Kumar Bal  Andimuthu Ramachandran  Kandasamy Palanivelu  Perumal Thirumurugan  Rajadurai Geetha  Balakrishnan Bhaskaran 《Asia-Pacific Journal of Atmospheric Sciences》2016,52(5):519-519

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.  相似文献   

Use of Geospatial Tools to Prioritize Zones of Hydro-Energy Potential in Glaciated Himalayan Terrain     

Lydia Sam  Anshuman Bhardwaj  Vinay S P Sinha  Pawan K Joshi  Rajesh Kumar 《Journal of the Indian Society of Remote Sensing》2016,44(3):409-420

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Review of the Book “India’s Journey Towards Excellence in Building Earth Observation Cameras” by Dr. George Joseph,Notion Press,India, 2016     

A. Senthil Kumar 《Journal of the Indian Society of Remote Sensing》2016,44(6):1025-1026

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Large-Scale Soil Resource Mapping Using IRS-P6 LISS-IV and Cartosat-1 DEM in Basaltic Terrain of Central India     

Nisha Sahu  S. K. Singh  G. P. Obi Reddy  Nirmal Kumar  M. S. S. Nagaraju  Rajeev Srivastava 《Journal of the Indian Society of Remote Sensing》2016,44(5):811-819

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TEC variation over an equatorial and anomaly crest region in India during 2012 and 2013     

Sanjay Kumar  Kalpana Patel  Abhay Kumar Singh 《GPS Solutions》2016,20(4):617-626

Using the global positioning system (GPS) measurements, the total electron content (TEC) at station Bangalore (13.02°N, 77.57°E geographic; 04.44°N, 150.84°E geomagnetic), lying at the equatorial region, and station Lucknow (26.91°N, 80.95°E geographic; 17.96°N, 155.24°E geomagnetic), lying at equatorial ionospheric anomaly (EIA) crest region, have been estimated for the year 2012–2013. In order to evaluate the International Reference Ionosphere (IRI) model regarding simulation/modeling of ionospheric studies specially at equatorial and EIA crest regions, we have compared the TEC derived from the recent version of the IRI-2012 model and the older IRI-2007 with its three topside options, namely IRI-NeQuick (IRI-NeQ), IRI-2001, and IRI01-corr, with that of GPS-TEC over Bangalore and Lucknow. For the EIA station Lucknow, the IRI-2012 model with IRI-NeQ and IRI01-corr topside is found in good agreement with GPS-TEC during summer and equinox season, while the IRI-2012 model for all three topside options significantly overestimates the GPS-TEC during winter season. The IRI-2001 topside overestimates the GPS-TEC over both the stations during all seasons. The anomalous difference between the IRI-2012 model prediction and ground-based GPS-TEC in daytime hours during the winter season observed at Lucknow could be attributed to discrepancies in the slab thickness predicted by the model, which is more during the winter season as compared to summer and equinox. These large discrepancies in the slab thickness predicted by the IRI-2012 as well as the IRI-2007 model during the winter season have been supported by using the foF2 data from Constellation Observing System for Meteorology, Ionosphere, and Climate radio occultation-based measurements. We also observed that the discrepancies in the recent IRI-2012 model with respect to GPS-TEC are found to be slightly larger than those with the older IRI-2007 model over the EIA region Lucknow. However, over the equatorial region Bangalore, the discrepancy with the older model IRI-2007 was found to be larger than with the recent IRI-2012 model. This suggests that the performance of the IRI-2012 model is poorer than the IRI-2007 model at the EIA region while better at equatorial region, and that further improvements in the IRI-2012 models are required particularly in the low-latitude and EIA regions. The GPS-TEC showed disappearance of the winter anomaly during 2012–2013, while the IRI model failed to predict the disappearance of winter anomaly.  相似文献   

Multiple statistical approaches for the discrimination of mangrove species of Rhizophoraceae using transformed field and laboratory hyperspectral data   总被引：1，自引：0，他引：1  

Kumar Arun Prasad 《国际地球制图》2016,31(8):891-912

This study aims at discriminating eight mangrove species of Rhizophoraceae family of Indian east coast using field and laboratory spectra in spectral range (350–2500 nm). Parametric and non-parametric statistical analyses were applied on spectral data in four spectral modes: (i) reflectance (ii) continuum removed, (iii) additive inverse and (iv) continuum removed additive inverse. We introduced continuum removal of inverse spectra to utilize the advantage of continuum removal in reflectance region. Non-parametric test gave better separability than parametric test. Principal component analysis and stepwise discriminant analysis were applied for feature reduction and to identify optimal wavelengths for species discrimination. To quantify the separability, Jeffries–Matusita distance measure was derived. Green (550 nm), red edge (680–720 nm) and water absorption region (1470 and 1850 nm) were found to be optimal wavelengths for species discrimination. The continuum removal of additive inverse spectra gave better separability than the continuum removed spectra.  相似文献   

Quantification of LST and CO2 levels using Landsat-8 thermal bands on urban environment     

Venkatesh Reddy Chejarla  Pramod Kumar Maheshuni 《国际地球制图》2016,31(8):913-926

Land surface temperature (LST) is an important aspect in global to regional change studies, for control of climate change and balancing of high temperature. Urbanization is one of the influencing factors increasing land surface and atmospheric temperature, by the emission of greenhouse gases (e.g. CO₂, NO and methane). In the present study, LST was derived from Landsat-8 of multitemporal data sets to analyse the spatial structure of the urban thermal environment in relation to the urban surface characteristics and land use–land cover (LULC). LST is influenced by the greenhouse gases i.e. CO₂ plays an important role in increasing the earth’s surface temperature. In order to provide the evidence of influence of CO₂ on LST, the relationship between LST, air temperature and CO₂ was analysed. Landsat-8 satellite has two thermal bands, 10 and 11. These bands were used to accurately to calculate the temperature over the study area. Results showed that the strength of correlation between ground monitoring data and satellite data was high. Based on correlation values of each month April (R² = 0.994), May (R² = 0.297) and June (R² = 0.934), observed results show that band 10 was significantly correlating with air temperature. Relationship between LST and CO₂ levels were obtained from linear regression analysis. band 11 was correlating significantly with CO₂ values in each of the months April (R² = 0.217), May (R² = 0.914) and June, (R² = 0.934), because band 11 is closer to the 15-micron band of CO₂. From the results, it was observed that band 10 can be used for calculating air temperature and band 11 can be used for estimation of greenhouse gases.  相似文献