Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations
Abstract
Hight-resolved observations of vertical winds remain nearly non-existing over the Himalayas, despite of anticipated crucial role of vertical motions in transporting pollution across the Himalayan hills. The present study analyze the vertical wind observations from surface to 1 km above ground level over Manora Peak (29.4° N; 79.5° E; 1958 m amsl) in the Himalaya performed using a Doppler Lidar during the Ganges Valley Aerosol Experiment (GVAX). Vertical wind exhibited a pronounced diurnal variability at Manora Peak comprising of upward motions during the daytime (05–10 UT) and downward motions during nighttime typical of a mountain-valley system. Mean vertical wind speeds are observed to be varying from –0.8 to +0.8 ms–1 during the study period with a variance of 0.1–1.5 m2s-2, which is attributed to the thermally driven turbulence. Mean vertical winds are observed to be stronger in the Doppler Lidar profiles above Manora Peak (–0.8 to 0.8 ms–1) as compared to near surface measurements at this station using an ultrasonic anemometer (–0.4 to 0.4 ms–1), and low altitude stations in India. Daytime vertical wind speeds are observed to be higher during pre-monsoon (0.81 ms–1), as compared to post-monsoon (0.24 ms–1) and winter (0.33 ms–1). In conclusion, average Black Carbon (BC)more »
- Authors:
-
- National Chiao Tung Univ. (NCTU), Hsinchu (Taiwan); Physical Research Lab, Ahmedaba (India); Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital (India)
- Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital (India)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Physical Research Lab, Ahmedaba (India)
- The Univ. of Tokyo, Chiba (Japan)
- Hsinchu (Taiwan); Physical Research Lab, Ahmedaba (India)
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Vikram Sarabhai Space Center, Thiruvananthapuram (India)
- Publication Date:
- Research Org.:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Atmospheric Radiation Measurement (ARM) Program; Indian Institute of Science, India; Indian Space Research Organization (ISRO)
- OSTI Identifier:
- 1502131
- Grant/Contract Number:
- AC02-06CH11357
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Atmospheric and Solar-Terrestrial Physics
- Additional Journal Information:
- Journal Volume: 183; Journal Issue: C; Journal ID: ISSN 1364-6826
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 47 OTHER INSTRUMENTATION; 54 ENVIRONMENTAL SCIENCES; GVAX; WRF; black carbon; doppler lidar; vertical velocity
Citation Formats
Shukla, Krishna K., Phanikumar, D. V., Newsom, Rob K., Ojha, N., Kumar, K. Niranjan, Singh, Narendra, Sharma, Som, Kotamarthi, V. R., and Kumar, K. K. Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations. United States: N. p., 2019.
Web. doi:10.1016/j.jastp.2018.12.011.
Shukla, Krishna K., Phanikumar, D. V., Newsom, Rob K., Ojha, N., Kumar, K. Niranjan, Singh, Narendra, Sharma, Som, Kotamarthi, V. R., & Kumar, K. K. Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations. United States. https://doi.org/10.1016/j.jastp.2018.12.011
Shukla, Krishna K., Phanikumar, D. V., Newsom, Rob K., Ojha, N., Kumar, K. Niranjan, Singh, Narendra, Sharma, Som, Kotamarthi, V. R., and Kumar, K. K. Wed .
"Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations". United States. https://doi.org/10.1016/j.jastp.2018.12.011. https://www.osti.gov/servlets/purl/1502131.
@article{osti_1502131,
title = {Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations},
author = {Shukla, Krishna K. and Phanikumar, D. V. and Newsom, Rob K. and Ojha, N. and Kumar, K. Niranjan and Singh, Narendra and Sharma, Som and Kotamarthi, V. R. and Kumar, K. K.},
abstractNote = {Hight-resolved observations of vertical winds remain nearly non-existing over the Himalayas, despite of anticipated crucial role of vertical motions in transporting pollution across the Himalayan hills. The present study analyze the vertical wind observations from surface to 1 km above ground level over Manora Peak (29.4° N; 79.5° E; 1958 m amsl) in the Himalaya performed using a Doppler Lidar during the Ganges Valley Aerosol Experiment (GVAX). Vertical wind exhibited a pronounced diurnal variability at Manora Peak comprising of upward motions during the daytime (05–10 UT) and downward motions during nighttime typical of a mountain-valley system. Mean vertical wind speeds are observed to be varying from –0.8 to +0.8 ms–1 during the study period with a variance of 0.1–1.5 m2s-2, which is attributed to the thermally driven turbulence. Mean vertical winds are observed to be stronger in the Doppler Lidar profiles above Manora Peak (–0.8 to 0.8 ms–1) as compared to near surface measurements at this station using an ultrasonic anemometer (–0.4 to 0.4 ms–1), and low altitude stations in India. Daytime vertical wind speeds are observed to be higher during pre-monsoon (0.81 ms–1), as compared to post-monsoon (0.24 ms–1) and winter (0.33 ms–1). In conclusion, average Black Carbon (BC) concentrations are significantly higher during strong upward vertical winds, which indicates efficient transport of polluted air mass from low-altitude regions to the Himalaya. Weather Research and Forecasting (WRF) model reproduces the observed diurnal pattern in the vertical wind at the observation site however the model underestimates the variability.},
doi = {10.1016/j.jastp.2018.12.011},
journal = {Journal of Atmospheric and Solar-Terrestrial Physics},
number = C,
volume = 183,
place = {United States},
year = {2019},
month = {1}
}
Web of Science