Disciplines:

Atmospheric Science

Computer Science or related fields

Mentor:

JPL: Jonathan Jiang (329J). Email: Jonathan.H.Jiang@jpl.nasa.gov; Phone: (818) 207-8734

UCLA: Yu Gu (JIFRESSE). Email: gu@atmos.ucla.edu; Phone: (310) 206-0377

Mentor URL:

http://science.jpl.nasa.gov/people/JJiang/

http://people.atmos.ucla.edu/gu/

Background:

Background
A simulation and retrieval system for ENTICE (Earth’s NexT generation ICE)  mission concept has been recently developed to simulate simultaneous retrievals of cloud ice particle size, ice water content, water vapor content, and temperature. Additional study is needed to conduct further retrieval experiments to test different orbits  to determine the capability, resolution and sampling frequency for potential Earth Venture Mission (Ev-M) or Decadal Survey mission platforms.

Description
This project is to make use of this developed software or other software tools to simulate ice cloud retrieval from different orbit options, including: (1) Following GPM with nadir view or scan side-by-side (2) In ISS orbit: Nadir view or scan side-by-side (3) Following EarthCare with nadir view or scan side-by-side The goal is to test pros and corns for each orbit option and help to select the best option in order to prepare future mission proposals.

Description:

This project is to help extend the a-priori database by using the most recent airborne measurements, especially those at mid- and high latitudes. The student will work under the instruction of the mentor to build and test this extended database, which will effectively help us to prepare the EV-M (Earth Venture Mission) proposal.

References:

Jiang et al. (2017), https://doi.org/10.1002/2017EA000296.

Student Requirements:

Strong physics and math background and programming skills. Knowledge of radiative transfer and atmospheric science in general.

Location:

UCLA Campus or JPL 183-715

Program:

JIFRESSE Summer Internship Program

Disciplines: 

Earth Sciences, air quality, remote sensing of atmospheric composition

Mentors: 

JPL: Kevin W. Bowman.   Email: Kevin.W.Bowman@jpl.nasa.gov; Phone: (818) 354-2995

UCLA: Pablo E. Saide (Department of Atmospheric & Oceanic Sciences). Email: saide@atmos.ucla.edu; Phone: (310) 825-4432

Mentor URLs: 

https://science.jpl.nasa.gov/people/Bowman/

https://dept.atmos.ucla.edu/saide

Background: 

Smoke from biomass burning are important contributors to short-term health exposure but are highly uncertain because direct and secondary emissions of both gases and particles can vary immensely depending of the burning conditions (e.g., flaming or smoldering) of the fires. These uncertainties are fundamental limitations to air quality predictions.  New satellite observations of both trace gases and particulates have the potential to better partition these phases, leading to more accurate representation of fire evolution and its impact on air quality.  Integration of these data into air quality assimilation systems is an important step that could lead to the formulation of future missions that would better support estimates of fire emissions

Description: 

An undergraduate intern is needed to work on these topics during summer 2019 over the course of 10 weeks. The intern will gain experience on reading satellite data from multiple instruments including MODIS MAIAC aerosol optical depth (AOD), and TROPOMI and CrIS Carbon monoxide (CO). These retrievals will be combined to produce AOD to CO ratios (which reflect burning conditions) for multiple fires over multiple days. The intern will also gain expertise on reading air quality model output which will be compared to the satellite data to assess emission uncertainties.

Student Requirements: 

Basic experience with Matlab and the Linux environment, willingness to learn about satellite data and air quality modeling.

Location: 

Department of Atmospheric & Oceanic Sciences, UCLA

Program: 

JIFRESSE Summer Internship Program

Disciplines: 

Terrestrial Hydrology

Mentor: 

JPL: John T Reager (329F). Email: John.Reager@jpl.nasa.gov; Phone: (818) 354-0552

UCLA: Rong Fu (JIFRESSE & Department of Atmospheric & Oceanic Sciences). Email: rfu@atmos.ucla.edu; Phone: (310) 825-3057

Mentor URL: 

https://science.jpl.nasa.gov/people/Reager/

Background: 

Few would debate the importance of monitoring changes in global water cycle due to its practical implication on land water resources as well as its coupled relationship with global energy budget. However, despite recent spurt in satellite-based observational systems of several important water cycle variables, gaps exist. Wide variation also exists among current observational systems. The proposed study would intercompare multiple concurrent satellite-based observations to characterize similarities and differences between them and to provide a synthesized ensemble approach of the ‘best guess’ observations of several water cycle variables. Applying traditional hydrology methods, the study would also highlight gaps in the current observation systems in terms of hydrology variables, important spatial resolutions, and temporal frequencies.

Description: 

The student would be provided with multiple datasets of precipitation, evapotranspiration, moisture divergence, discharge, and terrestrial water storage and would intercompare them using several statistical methods.

References: 

Chandanpurkar, H. A., Reager, J. T., Famiglietti, J. S., & Syed, T. H. (2017). Satellite- and reanalysis-based mass balance estimates of global continental discharge (1993-2015). Journal of Climate, 30(21), 8481–8495. https://doi.org/10.1175/JCLI-D-16-0708.1

Rodell, M., and Coauthors, 2015: The observed state of the water cycle in the early twenty-first century. J. Climate, 28, 8289–8318, doi:10.1175/JCLI-D-14-00555.1.

Student Requirements: 

The student relevant educational background in earth sciences with special focus on terrestrial hydrology. Acquaintance with scientific computing language such as Python or Matlab, as well as in typical statistical methods used in data processing and analysis are beneficial.  

Location: 

Department of Atmospheric & Oceanic Sciences, UCLA

Program: 

JIFRESSE Summer Internship Program

Disciplines: 

Satellite remote sensing, Geophysics, Computer Science, Atmosphere science

Mentor: 

JPL: Zhen Liu (329). Email: Zhen.Liu@jpl.nasa.gov; Phone: (818) 393-7506

UCLA: Zhengkang Shen ( Earth, Planetary, and Space Sciences). Email: zshen@ucla.edu; Phone: (310) 206-4070

Mentor URL: 

https://science.jpl.nasa.gov/people/ZLiu/

https://epss.ucla.edu/people/researchers/423/

Background: 

Space geodetic measurements from Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) technologies and Global Navigation Satellite System

 (GNSS) provide capability to image surface deformation and change (SDC) at various spatiotemporal scales. Modern SAR satellites such as Sentinel-1 and forthcoming NISAR mission enable imaging global Earth surface change with finer spatial resolution and short temporal interval. Maximizing science return from existing and future SAR missions critically rely on improved approaches and/or algorithms for correcting various noise sources in satellite data. Of special interest are atmospheric and other corrections for active SAR sensors. Growing observations and data volume also call for advances in techniques for rapid and reliable data processing, and improved time series analysis. Advanced corrections for known confounding effects are essential for future SAR mission (e.g., NISAR follow-on) development.

Description: 

The student will assess/improve/develop state-of-the-art techniques for noise correction with emphasis on atmospheric correction and transient detection using InSAR and GPS, and incorporate them in the improved time series analysis for earth system applications.

References: 

Liu, Z., H. S. Jung, Z. Lu, 2014, Joint correction of ionosphere noise and orbital error in L-band SAR interferometry of interseismic deformation in southern California, IEEE TGRS, 52(6), 3421-3427, doi:10.1109/TGRS.2013.2272791.

Liang, C., Z. Liu, E. Fielding, R. Burgmann, 2018, InSAR time series analysis of L-band wide-swath SAR data acquired by ALOS-2, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2018.2821150.

Student Requirements: 

Proficiency in python/matlab/C/C++/linux. Backgrounds in math, computer and signal processing, atmosphere science. InSAR background is preferred.

Location: 

UCLA campus and/or JPL

Program: 

JIFRESSE Summer Internship Program

Disciplines: 

Atmospheric Science, Planetary Science

Electrical Engineering

Mentor: 

JPL: Evan Fishbein (329E). Email: Evan.Fishbein@jpl.nasa.gov; Phone: (818) 354-2250

UCLA: K. N. Liou (JIFRESSE). Email: knliou@atmos.ucla.edu; Phone: (310) 794-9832

Mentor URL: 

https://science.jpl.nasa.gov/people/Fishbein

Background: 

Understanding energy and water vapor fluxes in the marine planetary boundary layer (MPBL)is an important NASA earth science research problem.  This research will explore the sensitivity of microwave thermal emission in the 20 to 183 GHz spectral to thermal and hydrologic features in the PBL.

Description: 

The student will use a microwave line-by-line radiative transfer model to perform sensitivity studies of microwave spectro-radiometers to marine PBL structure.

References: 

Janssen, M. A., 1993: Atmospheric Remote Sensing by Microwave Radiometry.  John Wiley and Sons.

Wood, R., 2012: Stratocumulus Clouds. Mon. Wea. Rev., 140, 2373-2423

Student Requirements: 

Mathematics, physics or electrical engineering., knowledge of radiative transfer, electromagnetism with electromagnetic wave propagation, polarization or microwave.  Programming skill with a high-level languages such as Matlab, IDL, or Python numpy.

Location: 

UCLA Campus and/or JPL Bldg. 233

Program: 

JIFRESSE Summer Internship Program

Disciplines: 

Remote sensing trace gases in the upper troposphere/stratosphere (UT/S)

Mentor: 

JPL: Shanshan Yu (329H). Email: shanshan.yu@jpl.nasa.gov; Phone: (818) 354-5829

UCLA: Jochen Stutz (Department of Atmospheric and Oceanic Sciences). Email: jochen@atmos.ucla.edu; Phone: (310) 825-5364

Mentor URL: 

https://science.jpl.nasa.gov/people/SYu/

Background: 

SHS is a Fourier transform spectrometer with the two mirrors replaced by diffraction gratings. Dr. Sona Hosseini from the planetary science section has developed an UV SHS for CubeSats.  SHS is wavelength scalable from UV to IR. In this project we will perform OSSE for a compact infrared SHS to advance our new mission concept of combining SHS and MLS for limb observations of the upper troposphere/stratosphere. SHS can provide synergetic measurements of CH4, SF6 and CFCs which pose challenges to MLS. These species have been identified as crucial UT/S observables by the 2014 NASA Science Mission Directorate workshop, and 2017 Earth science decadal survey community. The JPL’s next generation MLS together with SHS will continue JPL’s legacy in providing information that will help improve our understanding of Earth's atmosphere and global change.

Description: 

The intern will survey the state-of-the-art in remote sensing CH4, SF6 and CFCs from suborbital and orbital platforms; then quantify the precisions/accuracy improvements enabled by SHS, in comparison to the state-of-the-art.

References: 

https://science.jpl.nasa.gov/people/Hosseini/

https://mls.jpl.nasa.gov

Kaipachery et al. “Design and modeling of a tunable spatial heterodyne spectrometer for emission line studies”, J. of Astronomical Telescopes, Instruments, and Systems, 4(2), 025001 (2018).

Student Requirements: 

OSSE experience in VLIDORT required

OSSE experience in satellite limb observations preferred

Location: 

UCLA Campus and/or JPL 231-B1

Program: 

JIFRESSE Summer Internship Program