Calibration of TCCON column-averaged CO2: the first aircraft campaign over European TCCON sites

The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO2, CH4, N2O, CO and O2 are measured. CO2 is constrained with a precision better than 0.25% (1-σ). To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO2 column amounts from the TCCON instruments. The results of the campaign show that the FTS measurements are consistently biased 1.1% ± 0.2% low with respect to WMO standards, in agreement with previous TCCON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft profiles as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO2 measurements of total column concentrations provide a suitable database for the calibration and validation of nadir-viewing satellite

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 2: Variability and characteristic differences under near-pristine, biomass burning, and long-range transport conditions

Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014–Feb 2015). In a companion part 1 paper, we presented an in-depth CCN characterization based on annually as well as seasonally averaged time intervals and discuss different parametrization strategies to represent the Amazonian CCN cycling in modelling studies (M. Pöhlker et al., 2016b). The present part 2 study analyzes the aerosol and CCN variability in original time resolution and, thus, resolves aerosol advection and transformation for the following case studies, which represent the most characteristic states of the Amazonian atmosphere: 1. Near-pristine (NP) conditions, defined as the absence of detectable black carbon (< 0.01 µg m−3), showed their highest occurrence (up to 30 %) in the wet season (i.e., Mar–May). On average, the NP episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode: DAit = 70 nm, NAit = ~ 200 cm−3 vs. weaker accumulation mode: Dacc = 170 nm, Nacc = ~ 60 cm−3), a mostly organic particle composition, and relatively low hygroscopicity levels (κAit = 0.12 vs. κacc = 0.18). The NP CCN efficiency spectrum shows that the CCN population is sensitive to changes in supersaturation (S) over a wide S range. 2. Long-range transport (LRT) conditions frequently mix Saharan dust, African combustion smoke, and sea spray aerosols into the Amazonian wet season atmosphere. The LRT episodes (i.e., Feb–Apr) are characterized by an accumulation mode dominated size distribution (DAit = 80 nm, NAit = 120 cm−3 vs. Dacc = 180 nm, Nacc = 300 cm−3), a clearly increased abundance of dust and salt compounds, and relatively high hygroscopicity levels (κAit = 0.18, κacc = 0.34). The LRT CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime. 3. Biomass burning (BB) conditions dominate the Amazonian dry season. A selected characteristic BB episode shows a very strong accumulation mode (DAit = 70 nm, NAit = ~ 140 cm−3 vs. Dacc = 170 nm, Nacc = ~ 3400 cm−3), particles with very high organic fractions (> 90 %), and correspondingly low hygroscopicity levels (κAit = 0.14, κacc = 0.17). The BB CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime. 4. Mixed pollution conditions show the superposition of African (i.e., volcanic) and Amazonian (i.e., biomass burning) aerosol emissions during the dry season. The African aerosols showed a broad monomodal distribution (D = 130 nm, N = ~ 1300 cm−3), with very high sulfate fractions (20 %), and correspondingly high hygroscopicity (κAit = 0.14, κacc = 0.22). This was superimposed by fresh smoke from nearby fires with one strong mode (D = 113 nm, Nacc = ~ 2800 cm−3), an organic-dominated aerosol, and sharply decreased hygroscopicity (κAit = 0.10, κacc = 0.20). These conditions underline the rapidly changing pollution regimes with clear impacts on the aerosol and CCN properties. Overall, this study provides detailed insights into the CCN cycling in relation to aerosol-cloud interaction in the vulnerable and climate-relevant Amazon region. The detailed analysis of aerosol and CCN key properties and particularly the extracted CCN efficiency spectra with the associated fit parameters provide a basis for an in-depth analysis of aerosol-cloud interaction in the Amazon and beyond