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Rajeevan, M.

Earth Sciences for Societal and Economic Benefits

Performance of the Operational and Experimental Long-Range Forecasts for the 2015 Southwest Monsoon Rainfall

Abstract Views :247 | PDF Views:72

Authors

D. S. Pai ¹, A. Suryachandra Rao ², Soma Senroy ¹, Maheswar Pradhan ², Prasanth A. Pillai ², M. Rajeevan ³

Affiliations
1 India Meteorological Department, Shivajinagar, Pune 411 005, IN
2 Indian Institute of Tropical Meteorology, Dr Homi Bhabha Road, Pashan, Pune 411 008, IN
3 Ministry of Earth Sciences, Prithvi Bhavan, Opp. India Habitat Centre, Lodhi Road, New Delhi 110 003, IN

Source

Current Science, Vol 112, No 01 (2017), Pagination: 68-75

Abstract

India experienced deficient monsoon rainfall in 2015 that followed the deficient monsoon of 2014. India Meteorological Department (IMD) correctly predicted the large rainfall deficiency (86% of long period average) in 2015. Incidentally, this was the first ever deficient monsoon forecast issued by IMD, though it had earlier issued below-normal rainfall forecasts in the previous two deficient monsoon years (2009 and 2014) and was partially correct. The fact that there were only three previous occasions of consecutive two deficient monsoon years during the last 114 years (1901-2014) was itself a challenge to IMD to issue the forecast in 2015. It may be mentioned that IMD persisted with the deficient monsoon forecast for 2015, even though there were predictions from private agencies for a normal monsoon and apprehensions from the press and media about the low probability of two consecutive deficient years. IMD was also able to correctly predict the regional distribution of seasonal rainfall during the season. IMD's first deficient monsoon forecast was based on the state-of-the-art operational statistical forecasting system, which was introduced in 2007. IMD was further confident for a deficient monsoon due to the clear indications of a strong El Niño event by June itself. Forecasts from high-resolution coupled forecasting system (CFS) developed by the Indian Institute of Tropical Meteorology, Pune, under the Monsoon Mission also suggested a deficient monsoon in 2015. In this article we provide details of the operational forecasting models and verification of these forecasts. Brief description about the experimental CFS developed under the Monsoon Mission and CFS forecast for the 2015 southwest monsoon season is also presented.

Keywords

AISMR Data, Long-Range Forecasts, IMD, Monsoon Rainfall.

Full Text

Winter Fog Experiment Over the Indo-Gangetic Plains of India

Abstract Views :305 | PDF Views:85

Authors

Sachin D. Ghude ¹, G. S. Bhat ², Thara Prabhakaran ¹, R. K. Jenamani ³, D. M. Chate ¹, P. D. Safai ¹, A. K. Karipot ⁴, M. Konwar ¹, Prakash Pithani ¹, V. Sinha ⁵, P. S. P. Rao ¹, S. A. Dixit ¹, S. Tiwari ¹, K. Todekar ¹, S. Varpe ¹, A. K. Srivastava ¹, D. S. Bisht ¹, P. Murugavel ¹, Kaushar Ali ¹, Usha Mina ⁶, M. Dharua ¹, J. Rao ¹, B. Padmakumari ¹, A. Hazra ¹, N. Nigam ³, U. Shende ³, D. M. Lal ¹, B. P. Chandra ⁵, A. K. Mishra ⁵, A. Kumar ⁵, H. Hakkim ⁵, H. Pawar ⁵, P. Acharja ¹, Rachana Kulkarni ¹, C. Subharthi ¹, B. Balaji ¹, M. Varghese ¹, S. Bera ¹, M. Rajeevan ⁷

Affiliations
1 Indian Institute of Tropical Meteorology, Pashan, Pune 411 008, IN
2 Indian Institute of Science, Bengaluru 560 012, IN
3 India Meteorological Department, New Delhi 110 003, IN
4 Savitribai Phule Pune University, Pune 411 007, IN
5 Indian Institute of Science Education and Research Mohali, Mohali 140 306, IN
6 Indian Agricultural Research Institute, Pusa, New Delhi 110 012, IN
7 Ministry of Earth Sciences, Government of India, New Delhi 110 003, IN

Source

Current Science, Vol 112, No 04 (2017), Pagination: 767-784

Abstract

The objectives of the Winter Fog Experiment (WIFEX) over the Indo-Gangetic Plains of India are to develop better now-casting and forecasting of winter fog on various time- and spatial scales. Maximum fog occurrence over northwest India is about 48 days (visibility <1000 m) per year, and it occurs mostly during the December-February time-period. The physical and chemical characteristics of fog, meteorological factors responsible for its genesis, sustenance, intensity and dissipation are poorly understood. Improved understanding on the above aspects is required to develop reliable forecasting models and observational techniques for accurate prediction of the fog events. Extensive sets of comprehensive ground-based instrumentation were deployed at the Indira Gandhi International Airport, New Delhi. Major in situ sensors were deployed to measure surface micro-meteorological conditions, radiation balance, turbulence, thermodynamical structure of the surface layer, fog droplet and aerosol microphysics, aerosol optical properties, and aerosol and fog water chemistry to describe the complete environmental conditions under which fog develops. In addition, Weather Forecasting Model coupled with chemistry is planned for fog prediction at a spatial resolution of 2 km. The present study provides an introductory overview of the winter fog field campaign with its unique instrumentation.

Keywords

Aerosols, Atmospheric Profiles, Forecasting, Winter Fog.

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Odd–Even Traffic Rule Implementation during Winter 2016 in Delhi Did Not Reduce Traffic Emissions of VOCs, Carbon Dioxide, Methane and Carbon Monoxide

Abstract Views :219 | PDF Views:89

Authors

B. P. Chandra ¹, V. Sinha ¹, H. Hakkim ¹, A. Kumar ¹, H. Pawar ¹, A. K. Mishra ¹, G. Sharma ¹, Pallavi ¹, S. Garg ¹, Sachin D. Ghude ², D. M. Chate ², Prakash Pithani ², Rachana Kulkarni ², R. K. Jenamani ³, M. Rajeevan ⁴

Affiliations
1 Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Sector 81, S.A.S. Nagar, Manauli PO 140 306, IN
2 Indian Institute of Tropical Meteorology, Pashan, Pune 411 008, IN
3 India Meteorological Department, New Delhi 110 003, IN
4 Ministry of Earth Sciences, Government of India, New Delhi 110 003, IN

Source

Current Science, Vol 114, No 06 (2018), Pagination: 1318-1325

Abstract

We studied the impact of the odd–even traffic rule (implemented in Delhi during 1–15 January 2016) on primary traffic emissions using measurements of 13 volatile organic compounds, carbon monoxide, carbon dioxide and methane at a strategic arterial road in Delhi (28.57°N, 77.11°E, 220 m amsl). Whole air samples (n = 27) were collected during the odd–even rule active (OA) and inactive (OI) days, and analysed at the IISER Mohali Atmospheric Chemistry Facility. The average mass concentration ranking and toluene/benzene ratio were characteristic of primary traffic emissions in both OA and OI samples, with the largest fraction comprising aromatic compounds (55– 70% of total). Statistical tests showed likely increase (p ≤ 0.16; OA > OI) in median concentration of 13 out of 16 measured gases during morning and afternoon periods (sampling hours: 07 : 00–08 : 00 and 13 : 30–14 : 30 IST), whereas no significant difference was observed for evening samples (sampling hour: 19 : 00–20 : 00 IST). This suggests that many four-wheeler users chose to commute earlier, to beat the 8 : 00 AM–8 : 00 PM restrictions, and/or there was an increase in the number of exempted public transport vehicles. Thus, the odd–even rule did not result in anticipated traffic emission reductions in January 2016, likely due to the changed temporal and fleet emission behaviour triggered in response to the regulation.

Keywords

Odd–Even Rule, Pollution, PTR-MS, Traffic, VOCs.

Full Text

References

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Tiruvalam Natarajan Krishnamurti (1932–2018)

Why Should India Invest in Deep Ocean Research?

Evaluation of PM_2.5 Forecast using Chemical Data Assimilation in the WRF-Chem Model: A Novel Initiative Under the Ministry of Earth Sciences Air Quality Early Warning System for Delhi, India

Abstract Views :159 | PDF Views:73

Authors

Sachin D. Ghude ¹, Rajesh Kumar ², Chinmay Jena ¹, Sreyashi Debnath ¹, Rachana G. Kulkarni ¹, Stefano Alessandrini ², Mrinal Biswas ², Santosh Kulkrani ³, Prakash Pithani ¹, Saurab Kelkar ¹, Veeresh Sajjan ¹, D. M. Chate ¹, V. K. Soni ⁴, Siddhartha Singh ⁴, Ravi S. Nanjundiah ¹, M. Rajeevan ⁵

Affiliations
1 Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune 411 008, IN
2 National Center for Atmospheric Research, Boulder, CO 80301, US
3 Centre for Development of Advanced Computing, Pune 411 008, IN
4 India Meteorological Department, Ministry of Earth Sciences, New Delhi 110 003, IN
5 Ministry of Earth Sciences, Government of India, New Delhi 110 003, IN

Source

Current Science, Vol 118, No 11 (2020), Pagination: 1803-1815

Abstract

Air quality has become one of the most important environmental concerns for Delhi, India. In this perspective, we have developed a high-resolution air quality prediction system for Delhi based on chemical data assimilation in the chemical transport model – Weather Research and Forecasting with Chemistry (WRF-Chem). The data assimilation system was applied to improve the PM2.5 forecast via assimilation of MODIS aerosol optical depth retrievals using threedimensional variational data analysis scheme. Near real-time MODIS fire count data were applied simultaneously to adjust the fire-emission inputs of chemical species before the assimilation cycle. Carbon monoxide (CO) emissions from biomass burning, anthropogenic emissions, and CO inflow from the domain boundaries were tagged to understand the contribution of local and non-local emission sources. We achieved significant improvements for surface PM2.5 forecast with joint adjustment of initial conditions and fire emissions.

Keywords

Air Quality, Particulate Matter, Chemical Data Assimilation, Aerosol Optical Depth, Fire Emissions.

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Current Science

Current Science

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Rajeevan, M.

Earth Sciences for Societal and Economic Benefits

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Performance of the Operational and Experimental Long-Range Forecasts for the 2015 Southwest Monsoon Rainfall

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Winter Fog Experiment Over the Indo-Gangetic Plains of India

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Odd–Even Traffic Rule Implementation during Winter 2016 in Delhi Did Not Reduce Traffic Emissions of VOCs, Carbon Dioxide, Methane and Carbon Monoxide

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Tiruvalam Natarajan Krishnamurti (1932–2018)

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Why Should India Invest in Deep Ocean Research?

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Evaluation of PM2.5 Forecast using Chemical Data Assimilation in the WRF-Chem Model: A Novel Initiative Under the Ministry of Earth Sciences Air Quality Early Warning System for Delhi, India

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The impact of global warming on the oceans

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Evaluation of PM_2.5 Forecast using Chemical Data Assimilation in the WRF-Chem Model: A Novel Initiative Under the Ministry of Earth Sciences Air Quality Early Warning System for Delhi, India