Current state of the global operational aerosol multi-model ensemble: An update from the International Cooperative for Aerosol Prediction (ICAP)

Since the first International Cooperative for Aerosol Prediction (ICAP) multi-model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP-MME over 2012-2017, with a focus on June 2016-May 2017. Evaluated with ground-based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate-resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP-MME AOD consensus remains the overall top-scoring and most consistent performer among all models in terms of root-mean-square error (RMSE), bias and correlation for total, fine- and coarse-mode AODs as well as dust AOD; this is similar to the first ICAP-MME study. Further, over the years, the performance of ICAP-MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP-MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP-MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012-2017 suggests a general tendency for model improvements in fine-mode AOD, especially over Asia. No significant improvement in coarse-mode AOD is found overall for this time period.

Observations of the Interaction and Transport of Fine Mode Aerosols with Cloud and/or Fog in Northeast Asia from Aerosol Robotic Network (AERONET) and Satellite Remote Sensing

Analysis of sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (>1.0 in mid-visible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological co-variation with atmospheric stability and convergence. The new development of Aerosol Robotic network (AERONET) Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the Spectral Deconvolution Algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter-summer period, comparisons of AERONET L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.

Observation-based study on aerosol optical depth and particle size in partly cloudy regions

This study seeks to help better understand aerosol-cloud interactions by examining statistical relationships between aerosol properties and nearby low-altitude cloudiness using satellite data. The analysis of a global dataset of MODIS (Moderate Resolution Imaging Spectroradiometer) observations reveals that the positive correlation between cloudiness and aerosol optical depth (AOD) reported in earlier studies is strong throughout the globe and during both winter and summer. Typically, AOD is 30-50% higher on cloudier-than-average days than on less cloudy days. A combination of satellite observations and MERRA-2 global reanalysis data reveals that the correlation between cloud cover and AOD is strong for all aerosol types considered: sulfate, dust, carbon, and sea salt. The observations also indicate that in the presence of nearby clouds, aerosol size distributions tend to shift toward smaller particles over large regions of the Earth. This is consistent with a greater cloud-related increase in the AOD of fine mode than of coarse mode particles. The greater increase in fine mode AOD implies that the cloudiness-AOD correlation does not come predominantly from cloud detection uncertainties. Additionally, the results show that aerosol particle size increases near clouds even in regions where it decreases with increasing cloudiness. This suggests that the decrease with cloudiness comes mainly from changes in large-scale environment, rather than from clouds increasing the number or the size of fine mode aerosols. Finally, combining different aerosol retrieval algorithms demonstrated that quality assessment flags based on local variability can help identifying when the observed aerosol populations are affected by surrounding clouds.

Modified angström exponent for the characterization of submicrometer aerosols

The classical Angström exponent is an operationally robust optical parameter that contains size information on all optically active aerosols in the field of view of a sunphotometer. Assuming that the optical effects of a typical (radius) size distribution can be approximated by separate submicrometer and supermicrometer components, we show that one can exploit the spectral curvature information in the measured optical depth to permit a direct estimation of a fine-mode (submicrometer) Angström exponent (alpha(f)) as well as the optical fraction of fine-mode particles (eta). Simple expressions that enable the estimation of these parameters are presented and tested by use of simulations and measurements.

Comparison of columnar water-vapor measurements from solar transmittance methods

In the fall of 1997 the Atmospheric Radiation Measurement program conducted a study of water-vapor-abundance-measurement at its southern Great Plains site. The large number of instruments included four solar radiometers to measure the columnar water vapor (CWV) by measuring solar transmittance in the 0.94-mum water-vapor absorption band. At first, no attempt was made to standardize our procedures to the same radiative transfer model and its underlying water-vapor spectroscopy. In the second round of comparison we used the same line-by-line code (which includes recently corrected H(2)O spectroscopy) to retrieve CWV from all four solar radiometers, thus decreasing the mean CWV by 8-13%. The remaining spread of 8% is an indication of the other-than-model uncertainties involved in the retrieval.