Clouds with sun rays. Credit: Photo Gallery

Upgrading Aeolus aerosol observational capabilities towards improving air quality and NWP models

 

ADD-CROSS

Clouds with sun rays. Credit: Photo Gallery
Clouds with sun rays. Credit: Photo Gallery

ADD-CROSS assesses the impact of cross-channel assimilation on air quality and numerical weather prediction (NWP).

Last Updated

02 May 2024

Published on

30 April 2024

About

The AEOLUS mission has demonstrated its ability to measure profiles of aerosol optical properties, specifically backscatter and extinction coefficients, without relying on assumptions about the extinction-to-backscatter ratio. Both coefficients are independently measured thanks to the lidar’s high-spectral resolution capability, which allows for the separation of Mie contributions (from aerosols or hydrometeors) and Rayleigh contributions (from air molecules) in the detected signals. This capability opens up the possibility of acquiring information about the aerosol type, which is valuable for air quality models. However, AEOLUS only provides a single polarisation component of the backscattered light (parallel), thus preventing the measurement of the depolarisation ratio, which is another variable providing useful information about the aerosol type. Implementing a cross-polarized channel in EPS-AEOLUS is feasible but comes with additional cost and increased complexity.

The purpose of this study was to evaluate the benefits of adding this additional channel on weather forecasts by assimilating AEOLUS aerosol retrievals obtained with either single or both polarisation channels. This was achieved by conducting observation experiments using the CAMS model of the European Centre for Medium-range Weather Forecasts. Simulated data based on real Calipso observations were converted to AEOLUS UV wavelength and assimilated.

AOD timeseries
Figure 1: Courtesy NOA (from Final Report): Timeseries of the AOD forecasts based on the hwyt (green or AOD-IA), hx71 (red or AOD+F-IA), hx6z (grey or AOD+P-IA), hwyq (orange or AOD), hx63 (brown or AOD+F) and hx6x (magenta or AOD+P) IFS-COMPO runs along with AERONET daily mean observations acquired in Mindelo (Cabo Verde) from 4th to 30th September 2021. The model outputs (CY47R3 IFS-COMPO cycle) between T+3 and T+12 from the forecasts initialized at 00UTC and 12UTC have been averaged for the calculation of the daily means.

Objective

The specific goal of ADD-CROSS was to assess the impact of cross-channel assimilation on air quality and numerical weather prediction (NWP). The ADD-CROSS Region of Interest (RoI) included the Western Sahara and the Tropical Atlantic Ocean, capitalising on the prominent natural processes that generate non-spherical dust mineral particles and subsequently transport significant dust loads toward maritime outflow regions. Moreover, the selection of the ADD-CROSS RoI aimed to leverage the abundance of available data, particularly from the ASKOS Tropical Campaign conducted in September 2021 as part of the ESA JATAC cluster of campaigns.

Overview

Conclusions and Recommendations of the study:

The AEOLUS system has demonstrated its capability to enhance short-term weather forecasts via the assimilation of winds profiles in global models (e.g. Rennie et al., 2023). There is potential for further enhancement in NWP model-forecasting skills through the assimilation of the L2A, although this has not been attempted previously. The ADD-CROSS initiate undertook efforts to assimilate the L2A product to improve the representation of simulated aerosol fields and subsequently assess the impacts of interactive aerosols on NWP.

ADD-CROSS generated aerosol fields resembling those observed by AEOLUS over the RoI by using cross and parallel returns from CALIPSO and applying appropriate conversion factors, including spectral and depolarization-related factors. These aerosol profiles were then assimilated into the Integrated Forecasting System with Coupled Ocean-Atmosphere Processes (IFS-COMPO) to evaluate their impact on NWP. The main findings resulting from the evaluation against ASKOS and comparisons between different experiments can be summarized as follows:

  1. The consideration of interactive aerosols enhances model-forecasting skills in representing temperature fields throughout the troposphere over a forecast range of 120 hours, although there is less improvement in wind speed representation.
  2. Assimilating Aeolus total backscatter, including both perpendicular and parallel components, notably improves wind speed forecasts, especially in the upper tropospheric layers, evident in the IFS-COMPO runs 72 hours after model initialization.
  3. Assimilating Aeolus total backscatter shows a neutral impact on temperature fields across all forecast steps and pressure levels when compared against their own analysis.
  4. Assimilating Aeolus total backscatter positively impacts model forecasts of Aerosol Optical Depths (AOD), particularly under conditions associated with dust activity, as shown in Figure 1.
  5. Improved agreement between model and observations for near surface and vertically resolved temperatures is observed in areas affected by intense dust loads when Aeolus total backscatter is assimilated.
  6. The model’s response to assimilating Aeolus total backscatter is negligible for temperature, but pronounced for the wind speed, especially in its parallel component.

Overall, ADD-CROSS has demonstrated that incorporating polarization capabilities into a hypothetical ALADIN configuration scenario would significantly enhance air quality (AQ) forecasts and numerical weather prediction (NWP) by assimilating of Aeolus total backscatter retrievals (both parallel and perpendicular aerosol backscatter).

Additionally, beyond ADD-CROSS’s primary objectives, it is important to note that deploying a cross-channel will strengthen Aeolus’ observational capabilities and the scientific exploitation of its optical products in various ways, including:

  1. Improving calibration capabilities.
  2. Developing algorithms for aerosol and cloud subtype classification.
  3. Investigating aerosol-cloud interactions.
  4. Jointly implementing aerosol, cloud and wind data assimilation studies to enhance NWP, aligning with the main scientific goal of the Aeolus satellite mission.