scholarly journals Evaluation of Indian summer monsoon rainfall features using TRMM and KALPANA-1 satellite derived precipitation and rain gauge observation

MAUSAM ◽  
2021 ◽  
Vol 61 (3) ◽  
pp. 317-336
Author(s):  
V. R. DURAI ◽  
S. K. ROY BHOWMIK ◽  
B. MUKHOPADHYAY
Keyword(s):  
Summer Monsoon ◽  
Western Ghats ◽  
Heavy Rainfall ◽  
Heavy Rain ◽  
Rain Gauge ◽  
Summer Monsoon Rainfall ◽  
North East ◽  
The North ◽  
Western Ghats Of India ◽  
The Western Ghats

The study provides a concise and synthesized documentation of the current level of skill of the satellite (3B42RT, 3B42V-6, KALPANA-1) products over Indian regions based on the data gathered during the summer monsoon seasons of 2006, 2007 and 2008. The inter-comparison of satellite products with the rain gauge observations suggests that the TRMM 3B42V6 product could distinctly capture characteristic features of the summer monsoon, such as north–south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. The KALPANA-1 and 3B42RT products reproduce only the broadest features of mean monsoon seasonal rainfall. The near real-time products 3B42RT and KALPANA-1 underestimate the orographic heavy rainfall along the Western Ghats of India. The precipitation estimates from TRMM 3B42V6 product, when accumulated over the whole season, could reproduce the observed pattern. However, the TRMM 3B42RT and KALPANA-1 estimates are comparatively lower than the observed rainfall over most parts of the country during the season. Inter comparison reveals that the TRMM 3B42V6 product showed better skill in estimating the daily and seasonal mean rainfall over all India and also over four homogeneous regions of India.  

scholarly journals Evaluation of Unified Model Rainfall Forecasts over the Western Ghats and North East states of India

2019 ◽  
Author(s):  
Kuldeep Sharma ◽  
Sushant Kumar ◽  
Raghavendra Ashrit ◽  
Sean Milton ◽  
Ashis K. Mitra ◽  
...  
Keyword(s):  
Western Ghats ◽  
Heavy Rainfall ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Atmospheric Modeling ◽  
Unified Model ◽  
Probability Of Detection ◽  
North East ◽  
The Western Ghats ◽  
Heavy Rains

Abstract. Prediction of heavy rains associated with orography is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. The aim of this study is to evaluate the performance of UK Met Office Unified Model (UM) in predicting heavy and very heavy rainfall exceeding 80th and 90th percentiles which occurs mainly due to the forced ascent of air parcels over the mountainous regions of the Western Ghats (WGs) and North East (NE) – states of India during the monsoon seasons of 2007 to 2018. Apart from the major upgrades in the dynamical core of UM from New Dynamics (ND) to Even Newer Dynamics for General Atmospheric Modeling of the environment (ENDGame), the horizontal resolution of the model has been increased from 40 km and 50 vertical levels in 2007 to 10 km and 70 vertical levels in 2018. In general, it is expected that the prediction of heavy rainfall events improves with increased horizontal resolution of the model. The evaluation based on verification metrics, including Probability of Detection (POD), False Alarm Ratio (FAR), Frequency Bias (Bias) and Critical Success Index (CSI), indicate that model rainfall forecasts from 2007 to 2018 have improved from 0.29 to 0.38 (CSI), 0.45 to 0.55 (POD) and 0.55 to 0.45 in the case of FAR over WGs for rainfall exceeding the 80th percentile (CAT-1) in the Day-1 forecast. Additionally, the Symmetric Extremal Dependence Index (SEDI) is also used with special emphasis on verification of extreme and rare events. SEDI also shows an improvement from 0.47 to 0.62 and 0.16 to 0.41 over WGs and NE-states during the period of study, suggesting an improved skill of predicting heavy rains over the mountains. It has also been found that the improvement is consistent and comparatively higher over WGs than NE-states.

Checklist of Indian Lebiinae Bonelli, 1810 (Coleoptera: Carabidae)

2019 ◽  
Vol 10 (1) ◽  
pp. 1-63
Author(s):  
RAJ T. SHIJU ◽  
THOMAS K. SABU
Keyword(s):  
Sri Lanka ◽  
Geographic Distribution ◽  
Western Ghats ◽  
Indian Subcontinent ◽  
Distribution Patterns ◽  
Indian Species ◽  
North East ◽  
The North ◽  
Gondwana Land ◽  
The Western Ghats

Distribution patterns and literature details of 263 Lebiinae species reported from India are provided. List includes 14 species missed out by Andrewes (1930a) and the 98 species described thereafter. Distribution patterns revealed among the 263 species, 104 species are exclusively Oriental species and 35 species are exclusively Palaearctic species. Among the 263 Indian speceis, 130 species are exclusively Indian species with reports only from the Indian subcontinent and one species with report only from Andaman & Nicobar Islands. Of the 130 Indian species,  89 species are recorded from the Oriental, 27 species from the Palaearctic and 14 species recorded from both Oriental and Palaearctic regions in India. Among the 129 Indian subcontinent species, 45 species are endemics to the three global hotspots of the biodiversity in India with 31 species endemic to the Western Ghats and Sri Lanka hotspot of biodiversity; six species endemic to the Eastern Himalayas hotspot of biodiversity; eight species endemic to the Indo-Burma hotspot of biodiversity; four species recorded only from Chota Nagpur plateu and 27 species recorded only from Indian Himalayas. Four species (Microlestes parvati, Singilis indicus, S. squalidus and Lebia cardoni) recorded only from Chota Nagpur plateu and the 31 endemic species from the Western Gahts and Sri Lanka are of special interest for their Gondwana relationships. 133 species have wider geographic distribution pattern with 15 species having distribution in Oriental and Indian regions; 8 species having distribution in Palaeractic and Indian regions; 10 species having distribution in Oriental and Indo-Australian regions; 48 species with distribution in Oriental and Palaearctic regions; 29 species with distribution in Oriental, Indo-Australian and Palaearctic regions; 2 species with distribution in Oriental, Australian and Palaearctic regions; 6 species with distribution in Oriental, Palaearctic and Afrotropical regions; 9 species with distribution in Oriental, Indo-Australian, Australian and Palaearctic regions; and 6 species with random distributions in different regions. Distribution records indicate that the arrival/origin of 228 species- 137 species with wider geographic distribution outside India and the 91 species with Indian distribution and not endemics to the Western Ghats and the Chotanagpur Plateau- is likely to have occurred after the joining of Indian subcontinent with Asian continent and during the subsequent faunal exchange between the newly formed Indian subcontinent and the surrounding regions (Indo-Burma and Indo-China on the north east front; Mediterranean and Ethiopian regions on the north-western front; Central Asian elements on the northern front). These 228 species represent the younger Indian Lebiinae species compared to the 35 species representing the older/ancient species with Gondwana land origin. Key words: Carabidae, Lebiinae, Perigonini, Pentagonicini, Odacanthini, Cyclosomini, Lebiini, India  

scholarly journals Epiphyllous Liverworts of India: An Overview

2016 ◽  
Vol 3 (2) ◽  
pp. 157 ◽  
Author(s):  
D K Singh ◽  
Devendra Singh
Keyword(s):  
Western Ghats ◽  
Eastern Himalaya ◽  
North East ◽  
The North ◽  
Nicobar Islands ◽  
The Western Ghats ◽  
Total Diversity

Taxonomy of the epiphyllous liverworts in India has been reviewed and their diversity and distribution has been discussed. A total of 160 species, one subspecies and two varieties of epiphyllous liverworts belonging to 23 genera in eight families have been recognized in Indian bryoflora, distributed only in eastern Himalaya and the north-east, Western Ghats, and the Andaman & Nicobar Islands.  Eastern Himalaya, including the north-east, with 133 taxa shows the maximum diversity of epiphylls, whereas Sikkim with 80 taxa is the richest amongst the States. Lejeuneaceae with 131 species belonging to 16 genera is the most prolific family of epiphyllous liverworts accounting for over 80 per cent of their total diversity in India, while Cololejeunea with 54 species is the most dominant genus. Twenty species are endemic to India, of which 11 are restricted to eastern Himalaya, three to Western Ghats, and one to Andaman & Nicobar, while five species are common between eastern Himalaya and the Western Ghats.

scholarly journals Heavy rain at Chennai and its relation to cyclonic disturbances

MAUSAM ◽  
2021 ◽  
Vol 51 (1) ◽  
pp. 17-24
Author(s):  
G. S. GANESAN ◽  
A. MUTHUCHAMI ◽  
A. S. PONNUSWAMY
Keyword(s):  
Bay Of Bengal ◽  
Heavy Rainfall ◽  
Heavy Rain ◽  
Total Rainfall ◽  
Cyclonic Storm ◽  
North East ◽  
The North ◽  
The Mean ◽  
Cyclonic Disturbances ◽  
Severe Cyclonic Storm

In this paper an attempt is made to study the characteristics of Heavy Rainfall (HR) and Very Heavy Rainfall (VHR) over Chennai in the North East Monsoon month of October, November and December and the period considered is 1964 to 19%. It is observed that it is mainly the duration which determines whether rainfall would be heavy or very heavy. Defining a system as Depression or Cyclonic Storm or Severe Cyclonic Storm in the Bay of Bengal, the mean rainfall in a System-affected day is 1.5 times that of Non-system-affected day in October and November. No striking differences could be found in intensity and duration characteristics of rainfall between system- affected days and non-system affected days. Even if system induced. heavy rainfall does not occur other thing being normal, the total rainfall of this season can continue to be normal.

scholarly journals Use of wastes from the tea and coffee industries for the production of cellulases using fungi isolated from the Western Ghats of India

2020 ◽  
Vol 1 (1) ◽  
pp. 33-41
Author(s):  
S. A. Saldaña-Mendoza ◽  
J. A. Ascacio-Valdés ◽  
A. S. Palacios-Ponce ◽  
J. C. Contreras-Esquivel ◽  
R. Rodríguez-Herrera ◽  
...  
Keyword(s):  
Western Ghats ◽  
Western Ghats Of India ◽  
The Western Ghats

scholarly journals Rapid mapping of landslides in the Western Ghats (India) triggered by 2018 extreme monsoon rainfall using a deep learning approach

Landslides ◽  
2021 ◽  
Author(s):  
Sansar Raj Meena ◽  
Omid Ghorbanzadeh ◽  
Cees J. van Westen ◽  
Thimmaiah Gudiyangada Nachappa ◽  
Thomas Blaschke ◽  
...  
Keyword(s):  
Deep Learning ◽  
Western Ghats ◽  
Auxiliary Information ◽  
Optical Data ◽  
Spectral Information ◽  
Topographic Slope ◽  
Western Ghats Of India ◽  
Landslide Inventory Map ◽  
Inventory Map ◽  
The Western Ghats

AbstractRainfall-induced landslide inventories can be compiled using remote sensing and topographical data, gathered using either traditional or semi-automatic supervised methods. In this study, we used the PlanetScope imagery and deep learning convolution neural networks (CNNs) to map the 2018 rainfall-induced landslides in the Kodagu district of Karnataka state in the Western Ghats of India. We used a fourfold cross-validation (CV) to select the training and testing data to remove any random results of the model. Topographic slope data was used as auxiliary information to increase the performance of the model. The resulting landslide inventory map, created using the slope data with the spectral information, reduces the false positives, which helps to distinguish the landslide areas from other similar features such as barren lands and riverbeds. However, while including the slope data did not increase the true positives, the overall accuracy was higher compared to using only spectral information to train the model. The mean accuracies of correctly classified landslide values were 65.5% when using only optical data, which increased to 78% with the use of slope data. The methodology presented in this research can be applied in other landslide-prone regions, and the results can be used to support hazard mitigation in landslide-prone regions.

Heavy rainfall in the northern coast of Ecuador in the aftermath of El Niño 2015/2016 and its predictability 

2021 ◽  
Author(s):  
Luis E. Pineda ◽  
Juan Changoluisa ◽  
Ángel G. Muñoz
Keyword(s):  
Heavy Rainfall ◽  
Heavy Rain ◽  
Rainfall Anomaly ◽  
Precipitation Event ◽  
Lead Times ◽  
Northern Coast ◽  
Atmospheric Conditions ◽  
The North ◽  
Ensemble Mean ◽  
Rainfall Anomalies

<p>In January 2016, a high precipitation event (HPE) affected the northern coast of Ecuador leading to devastating flooding in the Esmeraldas’ river basin. The HPE appeared in the aftermath of the 2015/2016 El Niño as an early onset of heavy rainfalls otherwise expected in the core rainy season (Mar-Apr). Using gauge data, satellite imagery and reanalysis we investigate the daily and ‘weather-within-climate’ characteristics of the HPE and its accompanying atmospheric conditions. The convective storms developed into a mesoscale convective complex (MCC) during nighttime on 24<sup>th</sup> January. The scale size of the heavy rainfall system was about 250 km with a lifecycle lasting 16 hours for the complete storm with 6 hours of convective showers contributing to the HPE. The genesis of the MCC was related to above-normal moisture and orographic lifting driving convective updrafts; the north-south mountain barrier acted as both a channel boosting upslope flow when it moves over hillslopes; and, as a heavy-rain divide for inner valleys. The above normal moisture conditions were favored by cross-time-scale interactions involving the very strong El Niño 2015/2016 event, an unusually persistent Madden–Julian oscillation (MJO) in phases 3 and 6, remotely forced by tropical synoptic scale disturbances. In the dissipation stage, a moderate low-level easterly shear with wind velocity of about 10 m/s moved away the unstable air and the convective pattern disappear on the shore of the Esmeraldas basin.</p><p> </p><p>We use ECMWF re-forecast from the Sub-seasonal to Seasonal (S2S) prediction project dataset and satellite observations to investigate the predictability of the HPE. Weekly ensemble-mean rainfall anomaly forecasts computed from raw (uncorrected) S2S reforecast initialized on 31st Dec 2015, 7th, 14th and 21st Jan 2016 are used to assess the occurrence of rainfall anomalies over the region. The reforecast represents consistently, over all lead times, the spatial pattern of the HPE. Also, the ensemble-mean forecast shows positive rainfall anomalies at times scales of 1-3 weeks (0-21 days) at nearly all initialization dates and lead times, predicting this way successfully the timing and amplitude of the highest HPE leading the 25th January flood.</p>

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