Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models

Author:

Bianco LauraORCID,Adler BiancaORCID,Bariteau Ludovic,Djalalova Irina V.ORCID,Myers Timothy,Pezoa Sergio,Turner David D.ORCID,Wilczak James M.

Abstract

Abstract. Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the abovementioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

Funder

National Oceanic and Atmospheric Administration

Publisher

Copernicus GmbH

Reference33 articles.

1. Adler, B., Turner, D. D., Bianco, L., Djalalova, I. V., Myers, T., and Wilczak, J. M.: Improving solution availability and temporal consistency of an optimal estimation physical retrieval for ground-based thermodynamic boundary layer profiling, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-714, 2024.

2. Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C. R., Smirnova, T. G., Olson, J. B., James, E. P., Dowell, D. C., Grell, G. A., Lin, H., Peckham, S. E., Smith, T. L., Moninger, W. R., Kenyon, J. S., and Manikin, G. S.: A North American hourly assimilation and model forecast cycle: the Rapid Refresh, Mon. Weather Rev., 144, 1669–1694, https://doi.org/10.1175/MWR-D-15-0242.1, 2016.

3. Bianco, L.: NOAA PSL thermodynamic profiles retrieved from a combination of active and passive remote sensors and numerical weather prediction models with the optimal estimation physical retrieval TROPoe at Platteville, CO, USA, Zenodo [data set], https://doi.org/10.5281/zenodo.10815373, 2024.

4. Bianco, L., Friedrich, K., Wilczak, J. M., Hazen, D., Wolfe, D., Delgado, R., Oncley, S. P., and Lundquist, J. K.: Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications, Atmos. Meas. Tech., 10, 1707–1721, https://doi.org/10.5194/amt-10-1707-2017, 2017.

5. Blumberg, W., Turner, D., Löhnert, U., and Castleberry, S.: Ground-based temperature and humidity profiling using spectral infrared and microwave observations. Part 2: Actual retrieval performance in clear sky and cloudy conditions, J. Appl. Meteorol. Clim., 54, 2305–2319, https://doi.org/10.1175/JAMC-D-15-0005.1, 2015.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3