Search

In this work, we present the results of an observing system simulation experiment (OSSE) in which we investigate the emergence of a surface reflectance-dependent bias in retrieved column-averaged dry-air mole fractions of methane (XCH4). Our focus is on single-band type retrievals in the short-wave infrared (SWIR) at 2.3 µm. This particular bias manifests as artificial gradients in XCH4 fields that relate to surface features on the ground and can, for example, cause erroneous estimates of methane source emission rates. We find that even for near-ideal conditions (that being a perfectly calibrated instrument, perfect knowledge of meteorology and trace gas vertical distributions, and an absence of clouds and aerosols) a surface reflectance-related bias appears in the retrieved XCH4. While the magnitude of the bias is much lower than is observed in e.g. real data from the TROPOspheric Monitoring Instrument (TROPOMI), the overall qualitative shape is strikingly similar. When we study a more realistic scenario by considering synthetic measurements that are affected by aerosols, the surface bias increases in magnitude roughly by a factor of 10. We hold all other properties of the synthetic measurements fixed, and thus can make the following statements about these surface biases from the 2.3 µm absorption band. First, the bias already appears in the near-perfect scenario, meaning that its origin is likely fundamental to XCH4 retrievals from this particular absorption band, and using an optimal estimation-type retrieval approach. Second, the magnitude of the bias increases significantly when aerosols are encountered. As aerosols give rise to a magnification of the bias, we have implemented a retrieval configuration in which the retrieval algorithm knows the true aerosol abundance profiles along with their optical properties. With this configuration, the surface bias returns mostly to the level first seen when synthetic measurements were not affected by aerosols. The results we present in this work should be considered for new missions where XCH4 is a target quantity and the design relies on the 2.3 µm absorption band. Since the surface bias will likely emerge, it is crucial that a validation approach is planned which sufficiently samples the needed range of surface reflectance in areas of near-uniform methane concentrations in order to capture the bias and thus correct for it. [ABSTRACT FROM AUTHOR]

In this study, we present aerosol level-2 retrieval results from ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON (NL) and took place October-November 2017 over the western part of the United States. We perform aerosol retrievals using the SRON multimode algorithm on SPEX airborne L1C data, the Research Scanning Polarimeter (RSP) L1 data, and the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI) L1B2 data. The AERONET data and the High Spectral Resolution Lidar-2 (HSRL2) data are used to validate polarimeter retrieved/diagnostics aerosol properties. The polarimeter retrievals are based on SRON 5-mode approaches. Other multimode (from 6 to 10 modes) tests show similar performances with the 5-mode approach.Validations with AERONET show that SPEX, RSP, and AirMSPI retrievals achieve similar performances on aerosol optical thickness (AOT) and they agree well with AERONET. Here, we also show that AirMSPI-AERONET based on the SRON algorithm compares well with that based on the JPL algorithm. The Angstrom Exponent is compared between SPEX-AERONET and RSP-AERONET when AOT>0.1. Validations with HSRL2 are performed on two days. One day with low aerosol (AOD in range 0.02-0.14) and one day with measurements of an inhomogeneous smoke plume with high AOD (including AOD values > 1.0). Considering the data collocations among instruments, we compare SPEX-HSRL2, RSP-HSRL2, and SPEX-RSP for these two cases. SPEX and RSP both compare well to HSRL2 for AOT, backscatter coefficients, and depolarization ratio. [ABSTRACT FROM AUTHOR]

There is growing consensus in the aerosol remote sensing community that Multi-Angle Photo-polarimetric (MAP) measurements are essential to unambiguously determine all aerosol properties relevant to quantify and understand the impact of aerosols on climate and air quality. This presentation will discuss the advanced algorithm development for aerosol and cloud retrieval from MAP instruments. This includes aerosol and cloud retrieval from the PARASOL mission (2004-2013) and its validation, estimation the Direct Radiative Effect of Aerosols (DREA) using PARASOL and other A-Train sensors, use of Neural Network techniques for cloud retrievals, and aerosol retrieval from airborne MAP instruments. Further, we will discuss the development of the SPEXone instrument for the NASA PACE mission (launch 2022) and its aerosol retrieval capabilities. SPEXone is a high accuracy MAP with 5 viewing angles with hyperspectral capability, that is expected to provide aerosol properties with unprecedented detail and accuracy. On the PACE mission SPEXone will be used in synergy with the Hyper-Angular Rainbow Polarimeter-2 (HARP-2) and the Ocean Color Instrument (OCI). [ABSTRACT FROM AUTHOR]