the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
21 Jan 2021
21 Jan 2021
Exploring the elevated water vapor signal associated with the free-tropospheric biomass burning plume over the southeast Atlantic Ocean
- 1Bay Area Environmental Research Institute, Moffett Field, CA, USA
- 2NASA Ames Research Center, Moffett Field, CA, USA
- 3University of Miami/Rosenstiel School of Marine and Atmospheric Science, Miami, FL, USA
- 4University of Washington, Seattle, WA, USA
- 5NASA Goddard Space Flight Center, Greenbelt, MD, USA
- 6Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA, USA
- 7University of California, Los Angeles, Los Angeles, CA, USA
- 8Science and Technology Corporation, Moffett Field, CA, USA
- 9Department of Physics, University of Auckland, Auckland, NZ
- 10College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, OR, USA
- 11University of Oklahoma, Norman, OK, USA
- 12Department of Geophysics, Porter School of the Environment and Earth Sciences, Tel-Aviv University, Tel-Aviv, Israel
- anow at: JT4, LLC, Las Vegas, NV, USA
- 1Bay Area Environmental Research Institute, Moffett Field, CA, USA
- 2NASA Ames Research Center, Moffett Field, CA, USA
- 3University of Miami/Rosenstiel School of Marine and Atmospheric Science, Miami, FL, USA
- 4University of Washington, Seattle, WA, USA
- 5NASA Goddard Space Flight Center, Greenbelt, MD, USA
- 6Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA, USA
- 7University of California, Los Angeles, Los Angeles, CA, USA
- 8Science and Technology Corporation, Moffett Field, CA, USA
- 9Department of Physics, University of Auckland, Auckland, NZ
- 10College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, OR, USA
- 11University of Oklahoma, Norman, OK, USA
- 12Department of Geophysics, Porter School of the Environment and Earth Sciences, Tel-Aviv University, Tel-Aviv, Israel
- anow at: JT4, LLC, Las Vegas, NV, USA
Abstract. In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the Southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free-tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol-cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments.
Using ECMWF and MERRA-2 reanalyses and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it is subjected to conditions of strong westward advection, namely the South African Easterly Jet (AEJ-S). Our analysis indicates that airmasses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to 5–6 km) which produced fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (~6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. HYSPLIT back trajectories support this interpretation. Better understanding of the conditions and processes which cause the water vapor to covary with plume strength is important to accurately quantify direct, semi-direct, and indirect aerosol effects in this region.
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Kristina Pistone et al.
Status: final response (author comments only)
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RC1: 'Comment on acp-2020-1322', Anonymous Referee #1, 15 Feb 2021
The manuscript titled “Exploring the elevated water vapor signal associated with the free-tropospheric biomass burning plume over the southeast Atlantic Ocean” by Kristina Pistone and co-authors investigated the association of CO-q with ORACLES aircraft data over SEA ocean. They have also analyzed the reanalysis and model simulations to understand the meteorological and dynamical dependence of BB plume-water vapour relationship. This manuscript is well written and scientifically sound. I recommend the publication of this manuscript in ACP.
The explanation for the source of water vapour in the continental plume and its close association with BB CO and aerosols is not adequate. Since reanalysis and model results also showed similar variabilities, this could be of a meteorological coincidence rather than direct emissions. But why such a strong association exist between CO and q is not yet clear and needs to be explained in detail. Is there any study on source tagging or isotopic measurements of water vapour and aerosols over SEA?
Authors discussed the influence of boundary layer evolution over land on the vertical transport of CO and water vapour over the continents. I could not find further quantitative supporting information on the boundary layer parameters (boundary layer height, fluxes: SHF and LHF etc) to supplement the arguments. Small write-up on the general boundary layer features and its diurnal structure during the BB events could be useful.
The year-to-year variability of CO-q relationship is worth noting. Authors mentioned the airmass history over the BB regions, but more information is required on this point. Whether airmass pattern shows significant difference between 2016, 2017 and 2018? Notwithstanding the variability in time and meteorological conditions, what about the CO-q association for co-located measurements made during 2016, 2017 and 2018? Whether re-analysis and model simulations also depict weak association during 2017 and 2018?
Section 4.1 analyze the isentropic and kinematic airmass back trajectories using HYSPLIT. Though authors made broad comments on the usefulness and issues of back trajectory analysis, this section did not add more to the association of CO-q. Page 32, Line 1-4: This point is interesting, but needs more clarity and supporting evidence.
There are several studies discussed the radiative implications of aerosols on water vapor and diurnal evolution of boundary layer over the continental locations. How does BB aerosols influence the CO-q association? I wonder whether diabatic heating due to absorbing aerosols has any effect on the elevated layers of water vapour. Moreover, photochemical oxidations and chemical reactions involving CH4 and OH can also affect the concentration of CO and water vapour. Though the strength of these mechanisms may not be adequate enough to explain the observed CO-q association, it is better to mention these possibilities in the discussion for the sake of completion.
Figure 2 is interesting. Authors mentioned that the humidity datasets (aircraft, COMA, WISPER) differ for measurements within the PBL and rapidly changing aircraft conditions. I still not able to understand why only PBL humidity measured from the three instruments differ? What is the problem with PBL humidity and why aircraft is more stable (fewer ascents/descents) in the free troposphere compared to PBL. What is the rationale for omitting the PBL data is not clear? Is it possible to screen the data close to clouds?
Page 11, Line 7-8: What is the rationale for selecting PBL height as 2 km? How do authors measure the PBL height (Page 12, Line 5)?
Page 13, Line 8-10: To assess the possibility of the hygroscopic growth of aerosols on the AOD versus q relationship, authors have to provide the ranges of relative humidity.
Page 25, line 29: replace “continental boundary layer over land” with “continental boundary layer” (or boundary layer over land).
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RC2: 'Review of Pistone et al.', Anonymous Referee #2, 29 Mar 2021
In this study, the authors investigate the possible origin of the elevated moisture that characterises biomass-burning aerosol plumes transported from southern Africa to the south-eastern Atlantic Ocean. The authors find robust relationships between carbon monoxide (used as a marker of combustion sources) and specific humidity in ORACLES aircraft data and reanalyses and free-running models. They demonstrate that aircraft measurements are very probably real and that models simulate specific humidity sufficiently well for the analysis. They then use the models over land to track the source of the relationship, which they attribute to convection over the source regions of the biomass-burning aerosol. The moisture cannot originate from the fires themselves, which emit too small an amount of water to explain the measured enhancement.
The manuscript is very well written and follows a very clear reasoning. Figures support the discussion well. The paper makes a convincing case that elevated moisture and carbon monoxide are, to a large degree and despite their correlation, two independent quantities transported in the same air mass.
My only main comment is to clarify the conclusion of the paper. In the conclusion section (Page 34 line 32 to page 35 line 4), and also – I think - at the end of the abstract (Page 2, lines 8-9), the authors call for more research on the effects of elevated water vapour on radiation and clouds. I am not sure why. I can see two direct implications of the results:
- In that region, biomass-burning aerosols are transported in moist layers. That moisture modifies their aerosol optical depth and single-scattering albedo through hygroscopic growth, but such impacts are captured by aircraft and satellite retrievals.
- The transported air layer would be moist even without fires. In other words, the elevated water vapour is part of the natural atmosphere and is not an external perturbation. Of course, it will have its own radiative effects and influence aerosol-cloud interactions by supplying moisture, but those impacts seem clearly identified, as discussed from Page 2 line 22 to Page 3 line 5.
In that context, what are the outstanding questions?
Other comments
- Page 3, lines 28-31: These two statements suggest that aerosols need to be present for water vapour to influence clouds and have a radiative impact. Obviously, there is no need for aerosols for water vapour to interact with radiation. And lines 7-9 on the same page suggest that water vapour alone can exert radiative effects that are sufficiently strong to affect clouds. So I would suggest rewriting those statements.
- Page 8, line 13: I have never been sure of what aerosols do in the MERRA reanalysis. The MERRA papers say that GOCART is "radiatively coupled" to GEOS5 in that reanalysis, but does that then mean that aerosols affect heating rates?
- Page 12, line 7: "lower correlation than the other flights" – than the other routine flight? The flight on 20 September has an even lower correlation.
- Page 12, line 18: I suggest clarifying that statement by echoing the statement made on page 20, lines 7-10, which is clearer on the assumption made: that because air masses are transported from the continent, one can reasonably extend the confidence gained over ocean to the continent.
- Caption of Figure 12: "Each parameter has a distinct diurnal cycle except CO at 650hPa." What does that mean?
- Page 25, lines 1-4: Are those daily variations in CO emissions represented in MERRA2? If not, that might explain why the daily cycle of CO is flatter than other variables on Figure 12.
- Page 27, line 4: What is meant by "background CO is used"? Doesn’t the model simulate CO from emissions?
Technical comments
- Page 2, lines 31-32: Suggest rewriting to "the cloud liquid water path response to aerosol (via aerosol indirect effects) was much stronger".
- Page 3, line 7: The brackets in "(as was described by Adebiyi et al., 2015)" seem unnecessary.
- Page 8, line 25, and Page 9, lines 4, 7, and 8: Is CAMS the Copernicus Atmosphere Monitoring Service Reanalysis (Inness et al. (2019) https://doi.org/10.5194/acp-19-3515-2019) or a typo for CAM5? Probably the former. Incidentally, the CAMS dataset could be an additional dataset in which to look at CO-q correlations. In fact, given its close link to ERA-5, CAMS may be a better dataset to do so than MERRA2.
- Figure 9: The black dashed line that marks the African shoreline is not very visible. Could mark its position with an arrow on the x-axis?
- Page 23, line 23: Repeated word "the"
Kristina Pistone et al.
Data sets
ORACLES 2016 archival dataset for P-3 observations ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V1
ORACLES 2017 archival dataset for P-3 observations ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V1
ORACLES 2018 archival dataset for P-3 observations ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V1
Kristina Pistone et al.
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