A multi-axis differential optical absorption spectroscopy aerosol profile retrieval algorithm for high-altitude measurements: application to measurements at Schneefernerhaus (UFS), Germany

Abstract

We present a new aerosol extinction profile retrieval algorithm for multi-axis differential optical absorption spectrometer (MAX-DOAS) measurements at high-altitude sites. The algorithm is based on the lookup table method. It is applied to retrieve aerosol extinction profiles from the longterm MAX-DOAS measurements (February 2012 to February 2016) at the Environmental Research Station Schneefernerhaus (UFS), Germany (47.417 • N, 10.980 • E), which is located near the summit of Zugspitze at an altitude of 2650 m. The lookup table consists of simulated O 4 differential slant column densities (DSCDs) corresponding to numerous possible aerosol extinction profiles. The sensitivities of O 4 absorption to several parameters were investigated for the design and parameterization of the lookup table. In the retrieval, simulated O 4 DSCDs for each possible profile are derived by interpolating the lookup table to the observation geometries. The cost functions are calculated for each aerosol profile in the lookup table based on the simulated O 4 DSCDs, the O 4 DSCD observations, and the measurement uncertainties. Valid profiles are selected from all the possible profiles according to the cost function, and the optimal solution is defined as the weighted mean of all the valid profiles. A comprehensive error analysis is performed to better estimate the total uncertainty. Based on the assumption that the lookup table covers all possible profiles under clear-sky conditions, we determined a set of O 4 DSCD scaling factors for differ-ent elevation angles and wavelengths. The profiles retrieved from synthetic measurement data can reproduce the synthetic profile. The results also show that the retrieval is insensitive to measurement noise, indicating the retrieval is robust and stable. The aerosol optical depths (AODs) retrieved from the long-term measurements were compared to coinciding and co-located sun photometer observations. High correlation coefficients (R) of 0.733 and 0.798 are found for measurements at 360 and 477 nm, respectively. However, especially in summer, the sun photometer AODs are systematically higher than the MAX-DOAS retrievals by a factor of ∼ 2. The discrepancy might be related to the limited measurement range of the MAX-DOAS and is probably also related to the decreased sensitivity of the MAX-DOAS measurements at higher altitudes. The MAX-DOAS measurements indicate the aerosol extinction decreases with increasing altitude during all seasons, which agrees with the co-located ceilometer measurements. Our results also show maximum AOD and maximum Ångström exponent in summer, which is consistent with observations at an AERONET station located ∼ 43 km from the UFS.

MAX-DOAS measurements of tropospheric NO<sub>2</sub> and HCHO in Munich and the comparison to OMI and TROPOMI satellite observations

“…Spaceborne observations are indispensable tools to monitor the spatiotemporal distribution of atmospheric pollutants like NO 2 and HCHO on a global scale (Burrows et al, 1999;Bovensmann et al, 1999;Callies et al, 2000;Levelt et al, 2006;Veefkind et al, 2012). Vertical column densities (VCDs), representing concentrations integrated over vertical atmospheric columns, derived from spectral radiances provide deeper insights into atmospheric dynamics, as well as anthropogenic and natural emissions (Beirle et al, 2003(Beirle et al, , 2004Wenig et al, 2003;Richter et al, 2005;Zhang et al, 2007;van der A et al, 2008). However, the accuracy of satellite retrievals strongly depends on a number of assumptions about the surface albedo, cloud and aerosol optical properties, and the vertical distribution of trace gases.…”

Stacking Machine Learning Models Empowered High Time-Height-Resolved Ozone Profiling from the Ground to the Stratopause Based on MAX-DOAS Observation

“…The conventional OE algorithm heavily depends on prior information, thereby introducing substantial uncertainties when incorrect prior information is employed. Wang et al 46 addressed this limitation by employing a parametrized lookup table, resulting in more resilient and consistent retrievals of aerosol profiles. The ML model is also capable of retrieving aerosol profiles with high efficiency and accuracy.…”

Ground-based vertical profile observations of atmospheric composition on the Tibetan Plateau (2017–2019)

“…A sequential zenith spectrum, estimated from interpolation of two zenith spectra recorded before and after an elevation sequence, was selected as Frauenhofer reference spectrum. The retrieval configuring settings followed Xing et al (2020Xing et al ( , 2021, and the configurations used in CINDI intercomparison campaign as well (Roscoe et al, 2010;Kreher et al, 2019;Wang et al, 2020) (details are listed in Table 1). Fig.…”