Assimilation of DAWN Doppler wind lidar data during the 2017 Convective Processes Experiment (CPEX): impact on precipitation and flow structure
-
Published:2021-05-06
Issue:5
Volume:14
Page:3333-3350
-
ISSN:1867-8548
-
Container-title:Atmospheric Measurement Techniques
-
language:en
-
Short-container-title:Atmos. Meas. Tech.
Author:
Hristova-Veleva SvetlaORCID, Zhang Sara Q., Turk F. JosephORCID, Haddad Ziad S., Sawaya Randy C.
Abstract
Abstract. An improved representation of 3-D air motion and
precipitation structure through forecast models and assimilation of
observations is vital for improvements in weather forecasting capabilities.
However, there are few independent data to properly validate a model
forecast of precipitation structure when the underlying dynamics are
evolving on short convective timescales. Using data from the JPL
Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2 µm Doppler Aerosol
Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment
(CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble
Data Assimilation System (EDAS) modeling system was used to quantify the
impact of high-resolution sparsely sampled DAWN measurements on the
analyzed variables and on the forecast when the DAWN winds were assimilated.
Overall, the assimilation of the DAWN wind profiles had a discernible impact
on the wind field as well as the evolution and timing of the 3-D precipitation
structure. Analysis of individual variables revealed that the assimilation
of the DAWN winds resulted in important and coherent modifications of the
environment. It led to an increase in the near-surface convergence, temperature,
and water vapor, creating more favorable conditions for the development of
convection exactly where it was observed (but not present in the control
run). Comparison to APR-2 and observations by the Global Precipitation
Measurement (GPM) satellite shows a much-improved forecast after the
assimilation of the DAWN winds – development of precipitation where there
was none, more organized precipitation where there was some, and a much more
intense and organized cold pool, similar to the analysis of the dropsonde
data. The onset of the vertical evolution of the precipitation showed similar
radar-derived cloud-top heights, but delayed in time. While this
investigation was limited to a single CPEX flight date, the investigation
design is appropriate for further investigation of the impact of airborne
Doppler wind lidar observations upon short-term convective precipitation
forecasts.
Funder
National Aeronautics and Space Administration
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference38 articles.
1. Baker, W. E., Atlas, R., Cardinali, C., Clement, A., Emmitt, G. D., Gentry,
B. M., Hardesty, R. M., Källén, E., Kavaya, M. J., Langland, R., Ma,
Z., Masutani, M., McCarty, W., Pierce, R. B., Pu, Z., Riishojgaard, L. P.,
Ryan, J., Tucker, S., Weissmann, M., and Yoe, J. G.: Lidar-Measured Wind
Profiles: The Missing Link in the Global Observing
System, B. Am. Meteorol. Soc., 95, 543–564,
https://doi.org/10.1175/BAMS-D-12-00164.1, 2014. 2. Bedka, K. M., Nehrir, A. R., Kavaya, M., Barton-Grimley, R., Beaubien, M., Carroll, B., Collins, J., Cooney, J., Emmitt, G. D., Greco, S., Kooi, S., Lee, T., Liu, Z., Rodier, S., and Skofronick-Jackson, G.: Airborne Lidar Observations of Wind, Water Vapor, and Aerosol Profiles During The NASA Aeolus Cal/Val Test Flight Campaign, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2020-475, in press, 2021. 3. Chen, S. S., Kerns, B. W., Guy, N., Jorgensen, D. P., Delanoë, J., Viltard, N., Zappa, C. J., Judt, F., Lee, C.-Y., and Savarin, A.: Aircraft
Observations of Dry Air, the ITCZ, Convective Cloud Systems, and Cold Pools
in MJO during DYNAMO, B. Am. Meteorol. Soc., 97, 405–423, https://doi.org/10.1175/BAMS-D-13-00196.1, 2015. 4. Cui, Z., Pu, Z., Emmitt, G. D., and Greco, S.: The Impact of Airborne Doppler
Aerosol Wind (DAWN) Lidar Wind Profiles on Numerical Simulations of Tropical
Convective Systems during the NASA Convective Processes Experiment
(CPEX), J. Atmos. Ocean. Tech., 37, 705–722, https://doi.org/10.1175/JTECH-D-19-0123.1, 2020. 5. Drager, A. J. and van den Heever, S. C.: Characterizing convective cold pools, J. Adv. Model. Earth Sy., 9, 1091–1115, https://doi.org/10.1002/2016MS000788, 2017.
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|