12 results on '"Dmitrovic, Sanja"'
Search Results
2. Developing Optical Algorithms to Advance Airborne Measurements of Aerosol and Meteorological Properties
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Milster, Thomas D., Sawyer, Travis W., Dmitrovic, Sanja, Milster, Thomas D., Sawyer, Travis W., and Dmitrovic, Sanja
- Abstract
The marine atmospheric boundary layer (MABL), the layer between the ocean and free troposphere, hosts a suite of important atmospheric processes such as heat and temperature flux, gas exchange of carbon dioxide and water vapor, cloud evolution, and aerosol particle transport. To measure these complex processes and provide a complete picture of the MABL, organizations such as the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the Office of Naval Research (ONR) conduct airborne field campaigns that use a multitude of in-situ and remote sensing platforms. This dissertation introduces two studies that aim to improve airborne measurements of 1) ocean surface wind speeds and 2) atmospheric aerosol particles. Both of these studies focus on the in-situ and remote sensing instruments used in NASA’s Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) field campaign that took place from 2020 – 2022. The first study of this dissertation introduces a new 10 m ocean surface wind speed product from the High Spectral Resolution Lidar – generation 2 (HSRL-2) developed at the NASA Langley Research Center (LaRC) and evaluates it using coincident dropsonde surface wind speed data collected during the NASA ACTIVATE field campaign. The HSRL-2 directly retrieves vertically resolved aerosol backscatter and extinction profiles without relying on an assumed lidar ratio or other external aerosol constraints, enabling accurate estimates of the attenuation of the atmosphere and direct retrieval of surface wind speed through probing the variance of ocean wave slopes (i.e., wave-slope variance). The important findings from this study are 1) HSRL-2 surface wind speed retrieval accuracy is 0.15 m s-1 ± 1.80 m s-1, 2) dropsonde surface wind speed measurements most closely match with the Hu et al. (2008) wind speed-wave-slope variance model for surface wind speeds below 7 m s-1, showing that this
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- 2024
3. High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation.
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Dmitrovic, Sanja, Hair, Johnathan W., Collister, Brian L., Crosbie, Ewan, Fenn, Marta A., Ferrare, Richard A., Harper, David B., Hostetler, Chris A., Hu, Yongxiang, Reagan, John A., Robinson, Claire E., Seaman, Shane T., Shingler, Taylor J., Thornhill, Kenneth L., Vömel, Holger, Zeng, Xubin, and Sorooshian, Armin
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ATMOSPHERIC boundary layer , *WIND speed , *ATMOSPHERIC aerosols , *WEATHER & climate change , *WIND speed measurement - Abstract
Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or ∼ 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and y intercepts of - 0.13 and - 1.05 ms-1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 ms-1. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 ms-1 , with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 ms-1 and between 7 and 13.3 ms-1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 ms-1 and an error of ∼ 1.5 ms-1 , a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (- 0.18 ± 1.52 ms-1) than in the winter (0.63 ± 2.07 ms-1), but the HSRL-2 is still able to make numerous (N=236) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals, and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets. [ABSTRACT FROM AUTHOR]
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- 2024
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4. On the Nature of Caspian Clouds
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Rashedi Shahnaz, Mohammadi Golamhasan, Jahanbakhshasl Saeed, Khorshiddoust Ali Mohammad, Sorooshian Armin, Dmitrovic Sanja, and Tajbar Sapna
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General Medicine - Published
- 2023
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5. HSRL-2 Retrievals of Ocean Surface Wind Speeds
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Dmitrovic, Sanja, primary, Hair, Johnathan W., additional, Collister, Brian L., additional, Crosbie, Ewan, additional, Fenn, Marta A., additional, Ferrare, Richard A., additional, Harper, David B., additional, Hostetler, Chris A., additional, Hu, Yongxiang, additional, Reagan, John A., additional, Robinson, Claire E., additional, Seaman, Shane T., additional, Shingler, Taylor J., additional, Thornhill, Kenneth L., additional, Vömel, Holger, additional, Zeng, Xubin, additional, and Sorooshian, Armin, additional
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- 2023
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6. Supplementary material to "HSRL-2 Retrievals of Ocean Surface Wind Speeds"
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Dmitrovic, Sanja, primary, Hair, Johnathan W., additional, Collister, Brian L., additional, Crosbie, Ewan, additional, Fenn, Marta A., additional, Ferrare, Richard A., additional, Harper, David B., additional, Hostetler, Chris A., additional, Hu, Yongxiang, additional, Reagan, John A., additional, Robinson, Claire E., additional, Seaman, Shane T., additional, Shingler, Taylor J., additional, Thornhill, Kenneth L., additional, Vömel, Holger, additional, Zeng, Xubin, additional, and Sorooshian, Armin, additional
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- 2023
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7. Spatially coordinated airborne data and complementary products for aerosol, gas, cloud, and meteorological studies: the NASA ACTIVATE dataset
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Sorooshian, Armin, primary, Alexandrov, Mikhail D., additional, Bell, Adam D., additional, Bennett, Ryan, additional, Betito, Grace, additional, Burton, Sharon P., additional, Buzanowicz, Megan E., additional, Cairns, Brian, additional, Chemyakin, Eduard V., additional, Chen, Gao, additional, Choi, Yonghoon, additional, Collister, Brian L., additional, Cook, Anthony L., additional, Corral, Andrea F., additional, Crosbie, Ewan C., additional, van Diedenhoven, Bastiaan, additional, DiGangi, Joshua P., additional, Diskin, Glenn S., additional, Dmitrovic, Sanja, additional, Edwards, Eva-Lou, additional, Fenn, Marta A., additional, Ferrare, Richard A., additional, van Gilst, David, additional, Hair, Johnathan W., additional, Harper, David B., additional, Hilario, Miguel Ricardo A., additional, Hostetler, Chris A., additional, Jester, Nathan, additional, Jones, Michael, additional, Kirschler, Simon, additional, Kleb, Mary M., additional, Kusterer, John M., additional, Leavor, Sean, additional, Lee, Joseph W., additional, Liu, Hongyu, additional, McCauley, Kayla, additional, Moore, Richard H., additional, Nied, Joseph, additional, Notari, Anthony, additional, Nowak, John B., additional, Painemal, David, additional, Phillips, Kasey E., additional, Robinson, Claire E., additional, Scarino, Amy Jo, additional, Schlosser, Joseph S., additional, Seaman, Shane T., additional, Seethala, Chellappan, additional, Shingler, Taylor J., additional, Shook, Michael A., additional, Sinclair, Kenneth A., additional, Smith Jr., William L., additional, Spangenberg, Douglas A., additional, Stamnes, Snorre A., additional, Thornhill, Kenneth L., additional, Voigt, Christiane, additional, Vömel, Holger, additional, Wasilewski, Andrzej P., additional, Wang, Hailong, additional, Winstead, Edward L., additional, Zeider, Kira, additional, Zeng, Xubin, additional, Zhang, Bo, additional, Ziemba, Luke D., additional, and Zuidema, Paquita, additional
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- 2023
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8. HSRL-2 Retrievals of Ocean Surface Wind Speeds.
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Dmitrovic, Sanja, Hair, Johnathan W., Collister, Brian L., Crosbie, Ewan, Fenn, Marta A., Ferrare, Richard A., Harper, David B., Hostetler, Chris A., Hu, Yongxiang, Reagan, John A., Robinson, Claire E., Seaman, Shane T., Shingler, Taylor J., Thornhill, Kenneth L., Vömel, Holger, Zeng, Xubin, and Sorooshian, Armin
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WIND speed ,WIND speed measurement ,ATMOSPHERIC aerosols ,OCEAN-atmosphere interaction ,AIRBORNE-based remote sensing ,COLLOCATION methods - Abstract
This study introduces and evaluates ocean surface wind speed retrieval capabilities of the High Spectral Resolution Lidar – generation 2 (HSRL-2) instrument through comparison with wind speed data collected by National Center for Atmospheric Research (NCAR) Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes. Wind speed is derived from HSRL-2 measurements of the transmitted laser's specular reflection off the ocean surface. The magnitude of the surface reflectivity is determined by the surface's wave-slope variance, which is driven by surface winds. The assessment relies on the multi-year airborne data set collected as part of NASA's Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) campaign, where HSRL-2 retrievals and AVAPS dropsonde measurements of surface wind speeds were horizontally synchronized owing to their joint deployment on one of two aircraft used during the mission. A total of 577 collocated HSRL-2 - dropsonde surface wind speed data points over the northwest Atlantic Ocean are used for this study. Treating the dropsonde wind speeds as truth, it is found that, through two established wind speed – wave-slope parameterizations, the HSRL-2 wind speed retrievals have small errors (0.15 m s
−1 ± 1.80 m s−1 and 0.62 m s−1 ± 1.70 m s−1 ) and high correlation coefficients (0.89 and 0.88) with dropsonde wind speed measurements. Also, HSRL-2 wind speed error is higher in winter than in summer due at least partly to the higher frequency of low wind speeds and reduced cloud fraction in summer. Two research flights from 28 August 2020 and 1 March 2020 serve as detailed case studies to show the success of the collocation method based on ACTIVATE's spatial-coordination strategy and how HSRL-2 wind speed retrievals can enhance science-oriented studies such as those related to cloud evolution and general air-sea interaction. Another case flight examined from 11 January 2022 demonstrates the challenge of conducting HSRL-2 wind speed retrievals in high cloud fraction conditions. Overall, this study highlights the airborne HSRL-2's ability to retrieve surface wind speeds with accuracy as well as the potential of using dropsondes to validate aircraft instrument data sets within a field campaign. [ABSTRACT FROM AUTHOR]- Published
- 2023
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9. Organic enrichment in droplet residual particles relative to out of cloud over the northwestern Atlantic: analysis of airborne ACTIVATE data
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Dadashazar, Hossein, primary, Corral, Andrea F., additional, Crosbie, Ewan, additional, Dmitrovic, Sanja, additional, Kirschler, Simon, additional, McCauley, Kayla, additional, Moore, Richard, additional, Robinson, Claire, additional, Schlosser, Joseph S., additional, Shook, Michael, additional, Thornhill, K. Lee, additional, Voigt, Christiane, additional, Winstead, Edward, additional, Ziemba, Luke, additional, and Sorooshian, Armin, additional
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- 2022
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10. Analysis of MONARC and ACTIVATE Airborne Aerosol Data for Aerosol-Cloud Interaction Investigations: Efficacy of Stairstepping Flight Legs for Airborne In Situ Sampling
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Dadashazar, Hossein, primary, Crosbie, Ewan, additional, Choi, Yonghoon, additional, Corral, Andrea F., additional, DiGangi, Joshua P., additional, Diskin, Glenn S., additional, Dmitrovic, Sanja, additional, Kirschler, Simon, additional, McCauley, Kayla, additional, Moore, Richard H., additional, Nowak, John B., additional, Robinson, Claire E., additional, Schlosser, Joseph, additional, Shook, Michael, additional, Thornhill, Kenneth Lee, additional, Voigt, Christiane, additional, Winstead, Edward L., additional, Ziemba, Luke D., additional, and Sorooshian, Armin, additional
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- 2022
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11. Supplementary material to "Organic enrichment in droplet residual particles relative to out of cloud over the northwest Atlantic: Analysis of airborne ACTIVATE data"
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Dadashazar, Hossein, primary, Corral, Andrea F., additional, Crosbie, Ewan, additional, Dmitrovic, Sanja, additional, Kirschler, Simon, additional, McCauley, Kayla, additional, Moore, Richard, additional, Robinson, Claire, additional, Schlosser, Joseph, additional, Shook, Michael, additional, Thornhill, K. Lee, additional, Voigt, Christiane, additional, Winstead, Edward, additional, Ziemba, Luke, additional, and Sorooshian, Armin, additional
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- 2022
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12. Polarimeter + Lidar–Derived Aerosol Particle Number Concentration
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Schlosser, Joseph S., primary, Stamnes, Snorre, additional, Burton, Sharon P., additional, Cairns, Brian, additional, Crosbie, Ewan, additional, Van Diedenhoven, Bastiaan, additional, Diskin, Glenn, additional, Dmitrovic, Sanja, additional, Ferrare, Richard, additional, Hair, Johnathan W., additional, Hostetler, Chris A., additional, Hu, Yongxiang, additional, Liu, Xu, additional, Moore, Richard H., additional, Shingler, Taylor, additional, Shook, Michael A., additional, Thornhill, Kenneth Lee, additional, Winstead, Edward, additional, Ziemba, Luke, additional, and Sorooshian, Armin, additional
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- 2022
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