Project 1: The Role of PBL Height in Ocean Surface Flux Variability
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Disciplines: |
Atmospheric Science |
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Mentor (JPL): |
Tian Baijun (329E), baijun.tian@jpl.nasa.gov, 626-720-7512, https://science.jpl.nasa.gov/people/btian/ |
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Mentor (UCLA): |
Shakeel Asharaf (JIFRESSE), sasharaf@ucla.edu, 818-393-5358, https://science.jpl.nasa.gov/people/asharaf/ |
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Background: |
The Planetary Boundary Layer (PBL), spanning the lowest few meters to kilometers of the Earth's atmosphere, plays a key role in regulating the vertical exchange of moisture, heat, and momentum between the ocean and the atmosphere. These exchange processes are closely tied to surface heat fluxes and are essential for understanding air-sea interactions, yet accurately characterizing them remains a significant challenge. |
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Description: |
This work seeks to improve the accuracy of ocean surface heat flux estimates by effectively incorporating planetary boundary layer (PBL) height information from satellite observations and reanalysis data (e.g., AIRS, ERA5) and comparing the results with buoy-derived flux estimates. The COARE (Fairall et al., 2003, Edson et al., 2015) bulk aerodynamic algorithm will be used to facilitate this analysis. By integrating spaceborne observations with model reanalysis data, we expect to better capture PBL-driven processes that contribute to flux uncertainties, ultimately enhancing our understanding of air-sea interactions. |
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References: |
Edson, J. B., and Coauthors (2013). On the Exchange of Momentum over the Open Ocean. Journal of Physical Oceanography, 43, 1589–1610, https://doi.org/10.1175/JPO-D-12-0173.1. Fairall, C. W., E. F. Bradley, J. E. Hare, A. A. Grachev, and J. B. Edson (2003). Bulk Parameterization of Air–Sea Fluxes: Updates and Verification for the COARE Algorithm. J. Climate, 16, 571–591, https://doi.org/10.1175/15200442(2003)016<0571:BPOASF>2.0.CO;2. |
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Student Requirements: |
Basic knowledge of atmospheric or Boundary-layer meteorology and satellite data. Proficiency in programming language (e.g., R, Python, MATLAB, or Fortran). |
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Work Location: |
JPL / UCLA |
Project 2: Study of Advanced Propulsion Concepts for Deep Space Exploration Missions
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Disciplines: |
Plasma Physics |
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Mentor (JPL): |
Dan Goebel, dan.m.goebel@jpl.nasa.gov |
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Mentor (UCLA): |
Artur Davoyan (Mechanical and Aerospace Engineering Department), davoyan@seas.ucla.edu |
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Background: |
Deep space exploration holds promise to elucidate makings of the solar systems and shed light on the origins of life. However, at present deep space travel is slow and requires many years of flight time to reach outer planets. Indeed, only two probes have reached the heliopause to date. It took Voyager 1 travelling at a record breaking speed of 17 km/s 35 years to enter the interstellar medium. A number of envisioned missions, including solar gravity lens or solar polar imaging remain beyond the reach of current technologies. One of the key limitations precluding fast and low cost exploration of the outer solar system is propulsion. Deep space missions would benefit greatly from fuel efficient propulsion systems that would allow saving on fuel, while delivering high velocity gains. This is where study of novel propulsion systems going beyond conventional electric propulsion systems is important. |
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Description: |
This program aims to explore experimentally and theoretically two advanced propulsion approaches, currently being developed by JPL and UCLA. The first program will explore magnetic reconnection thrusters for ultrahigh specific impulse electric propulsion systems. Plasmas in strong magnetic fields experience energetic burst-like phenomena that could efficiently deposit energy into plasmas. Such energy deposition could lead to heating of plasmas to very high temperatures. The phenomenon of magnetic reconnection is of the key mechanisms for solar corona heating. In the context of propulsion such high temperature plasmas could yield ultra-high specific impulse systems. However, in a laboratory environment control of magnetic reconnection is challenging. The project will examine experimental conditions that could enable new regimes for taming magnetic reconnection for propulsion. A related program examines laser-ablation for propulsion. High energy lasers could also create high temperature plasmas that could lead to high specific impulse propulsion systems. This research program explores laser target interaction. Students would perform time resolved imaging and spectroscopy of laser induced plasma plumes. The data will then be used to predict plasma temperature and specific impulse. The result of the program is to explore promise of these two advanced propulsion systems based on acquired experiential data. |
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References: |
[1] Stephen N. Bathgate et al. “A thruster using magnetic reconnection to create a high-speed plasma jet” IEPC-2019-940 [2] C. Phipps et al. “Review: Laser-Ablation Propulsion” Journal of Propulsion and Power (2010) |
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Student Requirements: |
PhD student |
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Work Location: |
UCLA and JPL |
Project 3: Investigating Space Environment of Earth / Jupiter by Analyzing Satellite Data and/or Building Machine Learning Models
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Disciplines: |
Space physics |
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Mentor (JPL): |
Jonathan Jiang, Jonathan.H.Jiang@jpl.nasa.gov, 8182078734 |
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Mentor (UCLA): |
Jinxing Li, jxli87@ucla.edu, 4243457187, https://sites.google.com/site/jinxingli87 |
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Background: |
Space physics |
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Description: |
Naturally occuring electromagnetic waves are generated in Earth’s and Jupiter’s space. They typically occur within the human hearing frequency (20-20,000 Hz) range, and thus can be converted to audio, and are also known as “sound of space”. They play an important role in accelerating particles to close to the speed of light, similar to the mechanism that microwave heating food. Exploring the charactieristics of these “sound of space”, and how they heat electrons and ions reshape the magnetospheres of Earth and Jupiter. Machine learning techniques has been widely used in scientific research. We will utilize neural networks to build models that can predict space environment. |
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References: |
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Student Requirements: |
GPA ranked above 50% |
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Work Location: |
UCLA office |
Project 4: Joint Constraints on Star and Black Hole Formation in the Early Universe from the 21-cm, Near-infrared, and X-ray Backgrounds
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Disciplines: |
Astronomy, Astrophysics |
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Mentor (JPL): |
Jordan Mirocha (3266), jordan.mirocha@jpl.nasa.gov, 952-239-6882, https://science.jpl.nasa.gov/people/jordan-mirocha/ Tzu-Ching Chang (3266), tzu-ching.chang@jpl.nasa.gov, 626-298-5446, https://science.jpl.nasa.gov/people/tchang/ |
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Mentor (UCLA): |
Steven Furlanetto (Physics and Astronomy), sfurlane@astro.ucla.edu, 310-206-4127, https://www.astro.ucla.edu/~sfurlane/ |
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Background: |
The “cosmic dawn,” when stars and black holes (BHs) first formed and illuminated the cosmos, is the target of a variety of current and near-future experiments. Answers to long-standing puzzles are thought to reside in this epoch, e.g., how and when did the first BHs form? What were the first stars like? And, how was the intergalactic medium transformed from a mostly-neutral to mostly-ionized state in the first billion years of cosmic history? In the near-infrared (NIR), galaxy surveys with JWST continue to find an abundance of bright galaxies, while wide-field maps from SPHEREx will soon constrain the entire galaxy population in aggregate, including those too faint to be detected directly in surveys. Complementary constraints on the diffuse X-ray background (measured by Chandra) place an upper limit on early BH activity, while 21-cm power spectrum constraints (from HERA) set a lower bound on how much the early intergalactic medium has been heated. |
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Description: |
Bringing this diverse assortment of measurements to bear on theories of galaxy assembly is a challenging modeling and inference problem. The goal of this project is to explore the impact of the latest constraints from JWST and expected constraints from SPHEREx on the global 21-cm signal from high redshifts – the target of JPL mission concept CHIC. For example, what are the implications of the apparent ‘overabundance’ of JWST galaxies and extreme ionizing photon production for CHIC? The student will take advantage of the publicly available code ARES, which can be used to model the relevant signals, but has not been used to examine the relative constraining power of this diverse set of measurements in light of recent JWST results. Time permitting, the student may also develop extensions to the ARES model, e.g., including a treatment of intermediate and super-massive BHs, rather than the default approach which includes stellar mass BHs only. |
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References: |
https://arxiv.org/abs/2409.13020 https://arxiv.org/abs/astro-ph/0604040 |
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Student Requirements: |
Experience with Python programming, coursework in astrophysics and cosmology ideal |
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Work Location: |
JPL/UCLA |
Project 5: Is Los Angeles Ready for Compounding Weather Hazards during the 2028 Summer Olympics?
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Disciplines: |
Geography, Policy Analysis, Atmospheric Science, Climate Science |
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Mentor (JPL): |
Duane Waliser Email: duane.e.waliser@jpl.nasa.gov Phone: 818-393-4094 |
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Mentor (UCLA): |
Colin Raymond Email: csraymond@ucla.edu Phone: 607-279-2752 |
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Background: |
Many disasters, including recent ones in the Los Angeles area, stem from a combination of physical hazards, socioeconomic context, and operational decision-making (De Ruiter & Van Loon 2022). For example, the catastrophic Eaton and Palisades fires of Jan 2025 were characterized by vegetation and air dryness, extreme windstorms, and failures in key infrastructure and public communications. The San Bernardino Mountains snowstorms of Feb-Mar 2023 played out over a quite different timescale but similarly saw ill-fated assumptions, insufficient preparations, and struggles to respond to community needs in a timely and effective way, resulting in some neighborhoods being cut off for weeks after unprecedentedly heavy snowfalls (Lupear et al. 2023). Both situations typified how ‘compounding’ of hazards can overwhelm and expose deficiencies in planning for extreme weather events. An especially critical and weather-sensitive time will be when Los Angeles is in the global spotlight as host of the 2028 Summer Olympics. |
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Description: |
The project will examine the potential for combinations of severe weather-related hazards — such as extreme heat, poor air quality, fire weather, and flooding — to occur in the lead-up to the 2028 Olympics or during the Games themselves (DeFlorio et al. 2024; Gershunov et al. 2021; Shreevastava et al. 2023). Depending on student skillset and interest, this may be done through direct analysis of observational and model data, and/or through a more descriptive synthesis of existing analyses. These risks will then be cross-compared with extreme-weather plans developed by the Olympic organizing committee as well as local government agencies. Both project components will be enriched by mentor-arranged conversations with physical scientists at JPL and UCLA and with various decision-making entities, and will conceptually borrow from a recent similar risk assessment conducted for NASA facilities. Particular focus will be placed on using a storyline approach to consider the extent to which these plans account for multi-hazards, including cascading interactions, across impact categories, jurisdictions, and timescales (Raymond et al. 2020; Shepherd et al. 2018). |
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References: |
DeFlorio, M., et al. (2024). From California’s extreme drought to major flooding. Bull. Amer. Meteorol. Soc. doi:10.1175/bams-d-22-0208.1. De Ruiter, M., and Van Loon, A. (2022). The challenges of dynamic vulnerability and how to assess it. iScience. doi: 10.1016/j.isci.2022.104720. Gershunov, A., et al. (2021). Hot and cold flavors of southern California's Santa Ana winds: Their causes, trends, and links with wildfire. Clim. Dynam. doi:10.1007/s00382-021-05802-z. Lupear, D., Harris, C., and Henry, B. (2023). 2023 Mountain Storm Response Summary and After-Action Review. San Bernardino County Sheriff’s Department. https://wp.sbcounty.gov/sheriff/wp-content/uploads/sites/17/2023-Mountain-Storm-After-Action.pdf Raymond, C., et al. (2020). Understanding and managing connected extreme events. Nat. Clim. Change. doi:10.1038/s41558-020-0790-4. Shepherd, T., et al. (2018). Storylines: An alternative approach to representing uncertainty in physical aspects of climate change. Clim. Change. doi:10.1007/s10584-018-2317-9. Shreevastava, A., Raymond, C., and Hulley, G. (2023). Contrasting intraurban signatures of humid and dry heatwaves over Southern California. J. Appl. Meteorol. Climatol. doi:10.1175/jamc-d-22-0149.1. |
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Student Requirements: |
The student should have had some coursework in physical geography, atmospheric science, or environmental science, as well as an interest in policy analysis, government, or related areas. Experience with Python would be helpful but is not required. |
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Work Location: |
Hybrid, with in-person component at JPL and/or UCLA |
Project 6: Understand the Structural Shift of the Time Series from the Data Records of Modern Satellite Observations?
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Disciplines: |
Atmosphere, climate |
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Mentor (JPL): |
Qing Yue (329E), qyue@jpl.nasa.gov, https://science.jpl.nasa.gov/people/qyue/ Hai Nguyen (398L), hai.nguyen@jpl.nasa.gov |
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Mentor (UCLA): |
Gang Chen (AOS), gchenpu@atmos.ucla.edu, https://atmos.ucla.edu/people/faculty/gang-chen |
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Background: |
Modern satellite observations provide important observational benchmarks to the theoretical and model simulated physical processes of the Earth climate system. Many methods have been developed to construct such benchmarks, among which, a large number focus on the temporal characteristics of the long-term timeseries obtained from stable satellite observations (IPCC, 2013). Studying the temporal characteristics of the satellite observations therefore helps the community to understand the physical factors that cause the shift in the timeseries, including the long-term climate trends and large-scale modes of climate variability (https://science2017.globalchange.gov/chapter/5/), or even extreme events such as volcano eruptions. However, the structural shifts in these observational timeseries could also be caused by the operational status change of the sensors, such as orbital shifts, spacecraft maneuvers, and sensor abnormalities. To establish better observational benchmarks, it is necessary to better understand the structural shift in the modern satellite data records. |
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Description: |
In this study, we will focus on the A-Train data records (L’Ecuyer and Jiang 2010), especially the long-term timeseries of the Atmospheric Infrared Sounder (AIRS, https://airs.jpl.nasa.gov/) Version 7 and CLIMCAPS Level 3 (https://disc.gsfc.nasa.gov/information/documents?title=AIRS%20Documentation) dataset. AIRS data is chosen here for its robust stability (Huang et al. 2022). The breakpoint in the time series (Zeileis et al. 2003, Zeileis et al. 2024 and references therein) will be analyzed and evaluated to build potential connections with the large-scale climate variability and the instrument operational status change. Following tasks will be carried out:
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References: |
IPCC, 2013: https://archive.ipcc.ch/publications_and_data/ar4/wg1/en/ch9s9-6-4.html. L’Ecuyer and Jiang 2010: https://pubs.aip.org/physicstoday/article/63/7/36/391065/Touring-the-atmosphere-aboard-the-A-Train Huang et al. 2022: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022JD037598 Zeileis et al. 2003: https://www.sciencedirect.com/science/article/pii/S0167947303000306 Zeileis et al. 2024: https://cran.r-project.org/web/packages/strucchange/strucchange.pdf |
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Student Requirements: |
Students with good background in statistics and timeseries analysis are required. Proficiency in R, python, matlab or other programming language is required. The example codes from the mentors are in R. Potential applicants are expected to read the references listed in the AO. |
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Work Location: |
Hybrid |
Project 7: Advancing the EZIE Observing System Simulation Experiment (OSSE) for Auroral Space Weather Analysis
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Disciplines: |
Earth Sciences |
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Mentor (JPL): |
Frank Werner, 818-354-1918 |
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Mentor (UCLA): |
Yu Gu, 310-634-6076 |
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Background: |
The Electrojet Zeeman Imaging Explorer (EZIE) is a NASA heliophysics mission to explore space weather near Earth. In particular, it aims to understand small perturbations in Earth’s magnetic field and the auroral electrojets, which are electrical currents flowing about 60 to 90 miles above the poles. EZIE launched on 15 March 2025 and will provide first science data in the upcoming weeks. |
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Description: |
In order to understand the collected data, it is necessary to simulate the instrument observations in the presence of realistic Earth conditions, which is commonly done by developing an Observing System Simulation Experiment (OSSE). Great efforts have been put into developing a powerful OSSE at JPL, however, higher-level functionality is still missing and existing capabilities will need to be updated once actual EZIE observation are available. We seek a motivated student that works with the current OSSE and improves its capabilities, compare simulated to observed measurements, and use existing tools to derive magnetic field information from those measurements. |
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References: |
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Student Requirements: |
Technical Skills:
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Work Location: |
JPL |
Project 8: Developing Strategies for Participation in CMIP7
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Disciplines: |
Earth Sciences |
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Jonathan H. Jiang, 818-207-8734 |
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Mentor (UCLA): |
Yu Gu, 310-794-9832 |
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Background: |
Jet Propulsion Laboratory (JPL) conducts extensive Earth science research, generating invaluable data on ocean circulation, atmospheric dynamics, the carbon cycle, chemical composition, aerosols and clouds. The upcoming Coupled Model Intercomparison Project (CMIP7) focuses on advancing climate projections through the various experiments and associated community research, including a targeted “fast track” for the IPCC’s AR7. Integrating JPL’s high-quality observational datasets into CMIP7 can enhance model validation, reduce uncertainties, and foster deeper insights into key climate processes. |
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Description: |
The selected student will help design a roadmap for harmonizing JPL Earth science data products and modeling capabilities with the CMIP7 framework. This involves identifying high-priority datasets relevant to sea surface change, dangerous weather patterns, the water-carbon-climate nexus, and potential tipping points. The student will propose data-sharing protocols, outline best practices for model-data intercomparison, and cultivate collaborations with relevant MIPs. They will also recommend strategies for aligning JPL’s contributions with the AR7 Fast Track timeline to ensure timely, impactful participation in the broader CMIP7 goals. |
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References: |
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Student Requirements: |
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Work Location: |
JPL |