May Monthly Student Highlight- Andrew DzamboMay 22, 2019
While awards and appointments attract much of the news attention, the Atmospheric and Oceanic Sciences department has a large variety of work going on behind the scenes. As part of a new Monthly Highlights series, the AOS news page will be featuring different faculty and student projects once a month. These highlights will be showcasing published papers, community outreach events, field campaigns, Q&As on climate change and weather phenomenon, and other topics as they come up.
For three years, Andrew has worked on NASA’s Observations of Clouds above Aerosols and their Interactions, or ‘ORACLES’, field campaign. Current climate models do not parametrize either cloud or precipitation processes well, and these already tricky measurements are further complicated by the inclusion of aerosols such as smoke and dust. To combat this issue, the ORACLES field campaign has prioritized gathering data on how aerosols interact with stratocumulus clouds in the Southeast Atlantic.
Andrew’s article on this subject can be found here.
What is the overall goal of the ORACLES field project?
The ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) is an ongoing 5-year NASA field campaign aimed at collecting a multitude of cloud and aerosol data using close to two-dozen different in-situ and remote sensing instruments. From 2016-2018, we deployed for ~4-5 weeks each year to Africa to collect data at the beginning, middle and end of the biomass burning season, with the goal of collecting an observational dataset spanning the entire season and to study how cloud & aerosol interactions evolve over the course of the season. This dataset will be used in the coming years to better understand cloud and aerosol interactions, aerosol direct effect, and many other processes that are poorly represented in current weather and climate models.
Why are aerosol interactions with cloud and precipitation processes not well understood?
The short answer stems from a severe lack of observational datasets, especially over the oceanic basins where only satellite remote sensing instruments have provided any kind of long-term dataset. We’ve been able to make considerable advances using active & passive satellite remote sensing instruments, however various limitations with both kinds of instruments have made specific scientific questions very hard to address. In particular, cloud and aerosol interactions occur on very small scales, hence quantifying those interactions & understanding those processes is very, very difficult to do without in-situ datasets.
What techniques are you using to acquire data and measurements?
I worked with the Advanced Precipitation Radar - 3rd generation (APR-3) aboard a NASA P-3 aircraft. Perhaps the biggest challenge of collecting radar data is correcting for “viewing geometry”, since the aircraft is (save for level flight legs) constantly banking and turning. The radar sensitivity also changes as a function of distance, depending on how close or far away we are from the clouds and any precipitating cells. Estimating precipitation rates in these cloud decks is an added challenge. Most of my PhD work to date has been focused on retrieving precipitation rates from these radar profiles & applying an optimal-estimation based algorithm that uses many other variables (environmental temperature and specific humidity, surface backscatter, surface winds, gas attenuation, etc.).
What takes place during the field campaigns?
Each field campaign operated similarly in that, upon arrival, we could spend the first couple of days resting and planning flight and observational strategies. On non-flight days, instrument teams would meet with the project PIs to discuss these strategies and spend time maintaining their instruments. Instrument maintenance was perhaps the most grueling part of the campaign: some groups, especially the in-situ aerosol data collectors, were constantly changing out filters or cleaning their probes such that the best possible data could be collected. Computer issues were a frequent problem with most groups (in-situ and remote sensing), and also required many hours to both fix and safeguard future issues. On flight days, which occurred every other day on average, scientists would spend 8-9 hours in the air running their instruments and working closely with each other to collect the best possible measurements. Some flights, for example, were designed to collect primarily cloud data, while others focused on radiation- or aerosol-based science objectives.
What has been the biggest breakthrough you have discovered so far while participating in the ORACLES field campaign?
I believe the biggest breakthroughs from this campaign are still to come! With that in mind, it’s been a breakthrough on its own that - despite certain challenges and occasional aircraft downtime due to necessary repairs and logistical challenges of traveling to underdeveloped African countries - we were able to achieve ALL of our baseline science objectives and collect a rich dataset. The radar data alone collected close to 20 million individual profiles over the SE Atlantic cloud deck alone. Tristan L’Ecuyer (my adviser), Simone Tanelli (the APR-3 instrument PI) and others on the team have been amazed to see how much virga and drizzle occurs in the cloud deck. To our knowledge, the APR-3 collected the highest resolution dataset of the SE Atlantic cloud deck to date. CloudSat, a spaceborne W-band radar similar to the one included in the APR-3, is blind to many of the cloud & precipitation observations we made during the 3 field deployments!
What information are you hoping to find with these new measurement techniques?
The main science objectives I’ll be working on, for the remainder of my PhD and beyond, focus around how cloud structure and precipitation vary when aerosols interact with the aforementioned cloud deck. The APR-3 dataset is extensive, and we can quantify cloud structure (typical reflectivity profiles, cloud base and top), precipitation characteristics (rainfall rate, rainfall frequency, rain shaft width) and spatial characteristics (cloud fraction, cloud width, etc). All of these variables can provide context for long-standing science questions such as, for example, if precipitation suppressed more when aerosols interact with the cloud layer or if clouds have a longer longevity when interaction with the biomass burning layer. Furthermore, I’ll be working on an updated precipitation retrieval algorithm that (hopefully!) dramatically reduces the uncertainty in our rainfall rate estimations. If we can get those uncertainties down, we will be much more confident in any quantitative assessments utilizing rainfall rate. As for the rest of the mission, we are hoping to provide observational context & understanding of the aerosol direct, semi-direct and indirect effects such that we can better constrain current weather and climate models.
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