التفاصيل البيبلوغرافية
| العنوان: |
Retrieving UV-VIS Spectral Single-scattering Albedo of Absorbing Aerosols above Clouds from Synergy of ORACLES Airborne and A-train Sensors. |
| المؤلفون: |
Jethva, Hiren T.1,2 hiren.t.jethva@nasa.gov, Torres, Omar2, Ferrare, Richard Anthony3, Burton, Sharon P.3, Cook, Anthony L.3, Harper, David B.3, Hostetler, Chris A.3, Redemann, Jens4, Kayetha, Vinay5, LeBlanc, Samuel6, Pistone, Kristina6, Mitchell, Logan4, Flynn, Connor J.4 |
| المصدر: |
Atmospheric Measurement Techniques Discussions. 8/7/2023, p1-48. 48p. |
| مصطلحات موضوعية: |
*AEROSOLS, *ALBEDO, *RADIATIVE forcing, *SPECTRAL reflectance, *OCEAN color, *CLOUDINESS, *MICROPHYSICS, *ICE clouds |
| الشركة/الكيان: |
UNITED States. National Aeronautics & Space Administration |
| مستخلص: |
Inadequate knowledge about the complex microphysical and optical processes of the aerosol-cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In the satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from OMI and MODIS sensors of NASA's A-train satellites to retrieve 1) SSA of light-absorbing aerosols lofted over the clouds, and 2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosols scenes using the 'color ratio' algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High-spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) Sunphotometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean, and synergize them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354-388 nm) and VIS-near-IR (470-860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of ground-based AERONET over land, the retrieved spectral SSAs from the satellites, on average, were found to be higher overall by ~0.01-0.02--a positive bias still within the uncertainties involved in all these inversion datasets. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20%, 1 km, and 10%, respectively, produce an error in the retrieved SSA by 0.017 (0.01), 0.008 (0.001), and 0.03 (0.005) at 388 (470) nm. The development of the proposed aerosol-cloud algorithm implies a possible synergy of CALIOP lidar and OMI-MODIS passive sensors to deduce a global product of ACAOD and SSA. The availability of such global dataset can help constrain the climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
Full Text Finder