Assessment of NAAPS-RA performance in Maritime Southeast Asia during CAMP²Ex

Abstract

Abstract. Monitoring and modeling aerosol particle life cycle in Southeast Asia (SEA) is challenged by high cloud cover, complex meteorology, and the wide range of aerosol species, sources, and transformations found throughout the region. Satellite observations are limited, and there are few in situ observations of aerosol extinction profiles, aerosol properties, and environmental conditions. Therefore, accurate aerosol model outputs are crucial for the region. This work evaluates the Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA) aerosol optical thickness (AOT) and light extinction products using airborne aerosol and meteorological measurements from the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) conducted in 2019 during the SEA southwest monsoon biomass burning season. Modeled AOTs and extinction coefficients are compared to those retrieved with a high spectral resolution lidar (HSRL-2). Agreement between simulated and retrieved AOT (R2= 0.78, relative bias =-5 %, normalized root mean square error (NRMSE) = 48 %) and aerosol extinction coefficients (R2= 0.80, 0.81, and 0.42; relative bias = 3 %, −6 %, and −7 %; NRMSE = 47 %, 53 %, and 118 % for altitudes between 40–500, 500–1500, and >1500 m, respectively) is quite good considering the challenging environment and few opportunities for assimilations of AOT from satellites during the campaign. Modeled relative humidities (RHs) are negatively biased at all altitudes (absolute bias =-5 %, −8 %, and −3 % for altitudes <500 500–1500 and >1500 m, respectively), motivating interest in the role of RH errors in AOT and extinction simulations. Interestingly, NAAPS-RA AOT and extinction agreement with the HSRL-2 does not change significantly (i.e., NRMSE values do not all decrease) when RHs from dropsondes are substituted into the model, yet biases all move in a positive direction. Further exploration suggests changes in modeled extinction are more sensitive to the actual magnitude of both the extinction coefficients and the dropsonde RHs being substituted into the model as opposed to the absolute differences between simulated and measured RHs. Finally, four case studies examine how model errors in RH and the hygroscopic growth parameter, γ, affect simulations of extinction in the mixed layer (ML). We find NAAPS-RA overestimates the hygroscopicity of (i) smoke particles from biomass burning in the Maritime Continent (MC) and (ii) anthropogenic emissions transported from East Asia. This work mainly provides insight into the relationship between errors in modeled RH and simulations of AOT and extinction in a humid and tropical environment influenced by a myriad of meteorological conditions and particle types. These results can be interpreted and addressed by the modeling community as part of the effort to better understand, quantify, and forecast atmospheric conditions in SEA.

Dropsonde observations during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment

“…A subset of ACTIVATE studies have classified wintertime flights into whether they qualify as a “cold air outbreak” 6 , 10 , 11 , for which dropsonde data are used along with published criteria requiring knowledge of the vertical thermodynamic structure of the atmosphere 12 . As demonstrated by another recent campaign investigating aerosol-cloud interactions (CAMP 2 Ex), dropsonde data such as vertically-resolved relative humidity can be used for model simulations of aerosol extinction and aerosol optical thickness 13 and for assistance in interpreting remote sensing data from HSRL-2 and RSP deployed on the King Air. Investigations and analyses of ACTIVATE observations will show how dropsonde data are useful for assessments and improvements in remote sensing algorithms for geophysical variables such as wind speed, mixed layer height, and aerosol-related parameters.…”

An evaluation of biomass burning aerosol mass, extinction, and size distribution in GEOS using observations from CAMP2Ex

“…Except for a decrease in the extinction at the top of the PBL in GEOS 5.22 and a small increase in extinction in all GEOS runs, there is little change in the representation of extinction through correcting the relative humidity. This is not limited to GEOS as minimal improvement occurred through correcting RH biases in the Navy Aerosol Analysis and Prediction System Reanalysis (NAAPS-RA) (Edwards et al, 2022). These results suggest that the discrepancy in ambient extinction is a result of model treatment of particle hygroscopicity and less dependent on aerosol concentration (i.e., loading) or relative humidity.…”

“…Here, we make use of the NASA Langley Aerosol Research Group Experiment (LARGE) suite of instruments, particle size distribution from a fast integrated mobility spectrometer (FIMS; Kulkarni and Wang, 2006;Wang et al, 2017), and aerosol scattering profiles from the second-generation High Spectral Resolution Lidar (HSRL2) (Burton et al, 2018) as summarized in Table 1. Additional details including spatial and temporal resolution of the observations can be found in Edwards et al (2022). Chemical composition of the non-refractory submicron aerosol was provided by the LARGE high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS, Aerodyne Research, Inc.), while the optics array included nephelometers (TSI Inc., model 3563) and a particle soot absorption photometer (PSAP, Radiance Research) that provided scattering and absorption coefficients at three wavelengths, respectively.…”

An emerging aerosol climatology via remote sensing over Metro Manila, the Philippines

“…Previous studies have used NAAPS data for an overview of aerosol sources in specific regions of interest (Ross et al, 2018;Foth et al, 2019;Markowicz et al, 2021;Harenda et al, 2022;Mims III, 2022). More recent studies show the need to improve aerosol representation in NAAPS (Edwards et al, 2022), so we will use NAAPS qualitatively, together with MERRA-2 compositional AOD data and back trajectories, for an overview of aerosol sources that may contribute to extreme events with high AOD from AERONET.…”