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In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm developed by SRON Netherlands Institute for Space Research is extended with a bi-directional reflection distribution function (BRDF) for snow surfaces. The capability of the extended algorithm is validated with both synthetic measurements and real satellite measurements from the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL), and a comparison has been made to retrievals with the baseline RemoTAP (without a snow kernel). For retrievals with real PARASOL observations, we use pixels over Aerosol Robotic Network (AERONET) stations for validation and we use the MODIS snow cover products to identify pixels over snow. We evaluate the retrieved aerosol optical thickness (AOT) at 550 nm (τ550) , single-scattering albedo (SSA) at 550 nm (ω550) and Ångström exponent (AE) for 440–870 nm (AE440-870). The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover >75 %. According to the real-data experiment, we find that the retrieval algorithm has difficulty in fitting the PARASOL 1020 nm band, where snow reflectance is significantly lower than that for the visible bands. When we perform a four-band retrieval (490, 565, 670, 865 nm) with the extended RemoTAP, we obtain a good retrieval result for τ550 , ω550 and AE440-870. Therefore, the four-band retrieval with the extended RemoTAP is recommended for aerosol retrieval over snow. [ABSTRACT FROM AUTHOR]

The University of Maryland, Baltimore County (UMBC) Hyper-Angular Rainbow Polarimeter (HARP2) will be on board NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in January 2024. In this study we systematically evaluate the retrievability and uncertainty of aerosol and ocean parameters from HARP2 multi-angle polarimeter (MAP) measurements. To reduce the computational demand of MAP-based retrievals and maximize data processing throughput, we developed improved neural network (NN) forward models for spaceborne HARP2 measurements over a coupled atmosphere and ocean system within the FastMAPOL retrieval algorithm. To this end, a cascading retrieval scheme is implemented in FastMAPOL, which leverages a series of NN models of varying size, speed, and accuracy to optimize performance. Two sets of NN models are used for reflectance and polarization, respectively. A full day of global synthetic HARP2 data was generated and used to test various retrieval parameters including aerosol microphysical and optical properties, aerosol layer height, ocean surface wind speed, and ocean chlorophyll a concentration. To assess retrieval quality, pixel-wise retrieval uncertainties were derived from error propagation and evaluated against the difference between the retrieval parameters and truth based on a Monte Carlo method. We found that the fine-mode aerosol properties can be retrieved well from the HARP2 data, though the coarse-mode aerosol properties are more uncertain. Larger uncertainties are associated with a reduced number of available viewing angles, which typically occur near the scan edge of the HARP2 instrument. Results of the performance assessment demonstrate that the algorithm is a viable approach for operational application to HARP2 data after the PACE launch. [ABSTRACT FROM AUTHOR]

The Directional Polarization Camera (DPC) onboard the Chinese Gaofen-5 satellite, launched in May 2018, has similar specifications as the POLDER-3 instrument. The SRON Remote Sensing of Trace gas and Aerosol Products (RemoTAP) full retrieval algorithm is applied to DPC measurements to retrieve aerosol properties including the total Aerosol Optical Depth (AOD), the fine/coarse mode AOD and the SSA (Single Scattering Albedo). Measurements of the global ground-based AERONET network between December 2019 and April 2020 have been used for the validation of the DPC retrievals. According to the average Fine Mode Fraction (FMF) of the selected AERONET stations, the stations are divided into urban stations (FMF ≥ 0.5) and dust stations (FMF < 0.5). For the total AOD validation, DPC retrievals show better performance over urban stations than over dust stations, with average biases of 0.055 and 0.106, and RMSEs of 0.151 and 0.228, respectively. Regarding the fine mode AOD, the retrieval also performs better over urban stations. Compared with the total AOD validation, both the relatively lower bias (0.021 and 0.065) and the higher Gfrac (Fraction of Good retrieval, 63.8% and 47.3%, respectively) further indicate that DPC performs better when fine mode aerosols dominate. For the land SSA validation, most of our SSA retrievals (~71%) show differences with AERONET SSA retrievals lower than 0.05. Case studies over fire spots and dust over northern China demonstrate the encouraging application potential of DPC aerosol products. The difference between fine and coarse AOD can provide more aerosol source information compared with the total AOD alone. Since the SSA retrievals are particularly sensitive to absorbing fine particles, they can be easily used in the tracking of biomass burning aerosol. [ABSTRACT FROM AUTHOR]

We present a top-down approach for aerosol emission estimation from Spectropolarimeter for Planetary Exploration (SPEXone) polarimetric retrievals related to the aerosol amount, size, and absorption using a fixed-lag ensemble Kalman smoother (LETKS) in combination with the ECHAM-HAM model. We assess the system by performing observing system simulation experiments (OSSEs) in order to evaluate the ability of the future multi-angle polarimeter instrument, SPEXone, as well as a satellite with near-perfect global coverage. In our OSSEs, the nature run (NAT) is a simulation by the global climate aerosol model ECHAM-HAM with altered aerosol emissions. The control (CTL) and the data assimilation (DAS) experiments are composed of an ensemble of ECHAM-HAM simulations, where the default aerosol emissions are perturbed with factors taken from a Gaussian distribution. Synthetic observations, specifically aerosol optical depth at 550 nm (AOD 550), Ångström exponent from 550 to 865 nm (AE 550–865), and single-scattering albedo at 550 nm (SSA 550) are assimilated in order to estimate the aerosol emission fluxes of desert dust (DU), sea salt (SS), organic carbon (OC), black carbon (BC), and sulfate (SO 4), along with the emission fluxes of two SO 4 precursor gases (SO 2 , DMS). The prior emission global relative mean absolute error (MAE) before the assimilation ranges from 33 % to 117 %. Depending on the species, the assimilated observations sampled using the satellite with near-perfect global coverage reduce this error to equal to or lower than 5 %. Despite its limited coverage, the SPEXone sampling shows similar results, with somewhat larger errors for DU and SS (both having a MAE equal to 11 %). Further, experiments show that doubling the measurement error increases the global relative MAE up to 22 % for DU and SS. In addition, our results reveal that when the wind of DAS uses a different reanalysis dataset (ERA5 instead of ERA-Interim) to the NAT, the estimated SS emissions are negatively affected the most, while other aerosol species are negatively affected to a smaller extent. If the DAS uses dust or sea salt emission parametrizations that are very different from the NAT, posterior emissions can still be successfully estimated, but this experiment revealed that the source location is important for the estimation of dust emissions. This work suggests that the upcoming SPEXone sensor will provide observations related to aerosol amount, size, and absorption with sufficient coverage and accuracy in order to estimate aerosol emissions. [ABSTRACT FROM AUTHOR]

We present a top-down approach for aerosol emission estimation from SPEXone polarimetric retrievals related to the aerosol amount, size, and absorption using a fixed-lag ensemble Kalman smoother (LETKS) in combination with the ECHAM-HAM model. We assess the system by performing Observing System Simulation Experiments (OSSEs), in order to evaluate the ability of the future multi-angle polarimeter instrument, SPEXone, as well as a satellite with near perfect global coverage. In our OSSEs, the Nature Run (NAT) is a simulation by the global climate aerosol model ECHAM-HAM with altered aerosol emissions. The Control (CTL) and the data assimilation (DAS) experiments are composed of an ensemble of ECHAM-HAM simulations, where the default aerosol emissions are perturbed with factors taken from a Gaussian distribution. Synthetic observations, specifically Aerosol Optical Depth at 550 nm (AOD550), Angstrom Exponent from 550 nm to 865 nm (AE550-865) and Single Scattering Albedo at 550 nm (SSA550) are assimilated in order to estimate the aerosol emission fluxes of desert dust (DU), sea salt (SS), organic carbon (OC), black carbon (BC) and sulphate (SO4), along with the emission fluxes of two SO4 precursor gases (SO2, DMS). The synthetic observations are sampled from the NAT according to two satellite observing systems, with different spatial coverages. The first is the sensor SPEXone, a hyperspectral multi-angle polarimeter with a narrow swath (~100 km), that will be a part of the NASA PACE mission. The second is an idealized sensor that can retrieve observations over the whole globe even under cloudy conditions. The prior emission global relative Mean Absolute Error (MAE) before the assimilation ranges from 33 % to 117 %. Depending on the species, the assimilated observations sampled using the idealized sensor, reduce this error to equal to or lower than 5 %. Despite its limited coverage, the SPEXone sampling bares similar results, with somewhat larger errors for DU and SS (both having a MAE equal to 11 %). Further, experiments show that doubling the measurement error, increases the global relative MAE to 22 % for DU and SS. The emission estimation of the other species is not affected as much by these changes. In addition, the role of biased meteorology on emission estimation was quantified by using two different datasets (ERA-5 and ERA-interim) to nudge the U and V wind components of the model. The results reveal that when the wind of DAS uses a different reanalysis dataset than the NAT the estimated SS emissions are negatively affected the most, while the estimated emissions of DU, OC, BC and SO2 are negatively affected to a smaller extent. If the DAS uses dust or sea salt emission parametrisations that are very different from the NAT, posterior emissions can still be successfully estimated but this experiment revealed that the source location is important for the estimation of dust emissions. This work suggests that the upcoming SPEXone sensor will provide observations related to aerosol amount, size and absorption with sufficient coverage and accuracy, in order to estimate aerosol emissions. [ABSTRACT FROM AUTHOR]

This study presents an investigation of aerosol microphysical retrievals from high spectral resolution lidar (HSRL) measurements. Firstly, retrievals are presented for synthetically generated lidar measurements, followed by an application of the retrieval algorithm to real lidar measurements. Here, we perform the investigation for an aerosol state vector that is typically used in multi-angle polarimeter (MAP) retrievals, so that the results can be interpreted in relation to a potential combination of lidar and MAP measurements. These state vectors correspond to a bimodal size distribution, where column number, effective radius, and effective variance of both modes are treated as fit parameters, alongside the complex refractive index and particle shape. The focus is primarily on a lidar configuration based on that of the High Spectral Resolution Lidar-2 (HSRL-2), which participated in the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined project between NASA and SRON (Netherlands Institute for Space Research). The measurement campaign took place between October and November 2017, over the western region of the USA. Six different instruments were mounted on the aeroplane: four MAPs and two lidar instruments, HSRL-2 and the Cloud Physics Lidar (CPL). Most of the flights were carried out over land, passing over scenes with a low aerosol load. One of the flights passed over a prescribed forest fire in Arizona on 9 November, with a relatively higher aerosol optical depth (AOD), and it is the data from this flight that are focussed on in this study. A retrieval of the aerosol microphysical properties of the smoke plume mixture was attempted with the data from HSRL-2 and compared with a retrieval from the MAPs carried out in previous work pertaining to the ACEPOL data. The synthetic HSRL-2 retrievals resulted for the fine mode in a mean absolute error (MAE) of 0.038 (0.025) µm for the effective radius (with a mean truth value of 0.195 µm), 0.052 (0.037) for the real refractive index, 0.010 (7.20×10-3) for the imaginary part of the refractive index, 0.109 (0.071) for the spherical fraction, and 0.054 (0.039) for the AOD at 532 nm, where the retrievals inside brackets indicate the MAE for noise-free retrievals. For the coarse mode, we find the MAE is 0.459 (0.254) µm for the effective radius (with a mean truth value of 1.970 µm), 0.085 (0.075) for the real refractive index, 2.06×10-4 (1.90×10-4) for the imaginary component, 0.120 (0.090) for the spherical fraction, and 0.051 (0.039) for the AOD. A study of the sensitivity of retrievals to the choice of prior and first guess showed that, on average, the retrieval errors increase when the prior deviates too much from the truth value. These experiments revealed that the measurements primarily contain information on the size and shape of the aerosol, along with the column number. Some information on the real component of the refractive index is also present, with the measurements providing little on absorption or on the effective variance of the aerosol distribution, as both of these were shown to depend heavily on the choice of prior. Retrievals using the HSRL-2 smoke-plume data yielded, for the fine mode, an effective radius of 0.107 µm , a real refractive index of 1.561, an imaginary component of refractive index of 0.010, a spherical fraction of 0.719, and an AOD at 532 nm of 0.505. Additionally, the single-scattering albedo (SSA) from the HSRL-2 retrievals was 0.940. Overall, these results are in good agreement with those from the Spectropolarimeter for Planetary Exploration (SPEX) and Research Scanning Polarimeter (RSP) retrievals. [ABSTRACT FROM AUTHOR]

NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in the time frame of late 2022 to early 2023, will carry the Ocean Color Instrument (OCI), a hyperspectral scanning radiometer, and two multiangle polarimeters (MAPs), the UMBC Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the SRON Spectro-Polarimeter for Planetary EXploration one (SPEXone). One purpose of the PACE MAPs is to better characterize aerosol properties, which can then be used to improve atmospheric correction for the retrieval of ocean color in coastal waters. Though this is theoretically promising, the use of MAP data in the atmospheric correction of colocated hyperspectral ocean color measurements have not yet been well demonstrated. In this work, we performed aerosol retrievals using the MAP measurements from the Research Scanning Polarimeter (RSP) and demonstrate its application to the atmospheric correction of hyperspectral radiometric measurements from SPEX airborne. Both measurements were collected on the same aircraft from the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign in 2017. Two cases over ocean with small aerosol loading (aerosol optical depth ∼0.04) are identified including colocated RSP and SPEX airborne measurements and Aerosol Robotic Network (AERONET) ground-based observations. The aerosol retrievals are performed and compared with two options: one uses reflectance measurement only and the other uses both reflectance and polarization. It is demonstrated that polarization information helps reduce the uncertainties of aerosol microphysical and optical properties. The retrieved aerosol properties are then used to compute the contribution of atmosphere and ocean surface for atmospheric correction over the discrete bands from RSP measurements and the hyperspectral SPEX airborne measurements. The water-leaving signals determined this way are compared with both AERONET and Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color products for performance analysis. The results and lessons learned from this work will provide a basis to fully exploit the information from the unique combination of sensors on PACE for aerosol characterization and ocean ecosystem research. [ABSTRACT FROM AUTHOR]

In the fall of 2017, an airborne field campaign was conducted from the NASA Armstrong Flight Research Center in Palmdale, California, to advance the remote sensing of aerosols and clouds with multi-angle polarimeters (MAP) and lidars. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign was jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON). Six instruments were deployed on the ER-2 high-altitude aircraft. Four were MAPs: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary EXploration (SPEX airborne), and the Research Scanning Polarimeter (RSP). The remainder were lidars, including the Cloud Physics Lidar (CPL) and the High Spectral Resolution Lidar 2 (HSRL-2). The southern California base of ACEPOL enabled observation of a wide variety of scene types, including urban, desert, forest, coastal ocean, and agricultural areas, with clear, cloudy, polluted, and pristine atmospheric conditions. Flights were performed in coordination with satellite overpasses and ground-based observations, including the Ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI), sun photometers, and a surface reflectance spectrometer. ACEPOL is a resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. Data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion. They are freely available to the public. The DOI for the primary database is 10.5067/SUBORBITAL/ACEPOL2017/DATA001 (ACEPOL Science Team, 2017), while for AirMSPI it is 10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006 and 10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006 (ACEPOL AirMSPI 75 Science Team, 2017a, b). GroundMSPI data are at 10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009 (GroundMSPI Science Team, 2017). Table 3 lists further details of these archives. This paper describes ACEPOL for potential data users and also provides an outline of requirements for future field missions with similar objectives. [ABSTRACT FROM AUTHOR]

In this paper, we present aerosol retrieval results from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, which was a joint initiative between NASA and SRON – the Netherlands Institute for Space Research. The campaign took place in October–November 2017 over the western part of the United States. During ACEPOL six different instruments were deployed on the NASA ER-2 high-altitude aircraft, including four multi-angle polarimeters (MAPs): SPEX airborne, the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), and the Research Scanning Polarimeter (RSP). Also, two lidars participated: the High Spectral Resolution Lidar-2 (HSRL-2) and the Cloud Physics Lidar (CPL). Flights were conducted mainly for scenes with low aerosol load over land, but some cases with higher AOD were also observed. We perform aerosol retrievals from SPEX airborne, RSP (410–865 nm range only), and AirMSPI using the SRON aerosol retrieval algorithm and compare the results against AERONET (AErosol RObotic NETwork) and HSRL-2 measurements (for SPEX airborne and RSP). All three MAPs compare well against AERONET for the aerosol optical depth (AOD), with a mean absolute error (MAE) between 0.014 and 0.024 at 440 nm. For the fine-mode effective radius the MAE ranges between 0.021 and 0.028 µm. For the comparison with HSRL-2 we focus on a day with low AOD (0.02–0.14 at 532 nm) over the California Central Valley, Arizona, and Nevada (26 October) as well as a flight with high AOD (including measurements with AOD>1.0 at 532 nm) over a prescribed forest fire in Arizona (9 November). For the day with low AOD the MAEs in AOD (at 532 nm) with HSRL-2 are 0.014 and 0.022 for SPEX and RSP, respectively, showing the capability of MAPs to provide accurate AOD retrievals for the challenging case of low AOD over land. For the retrievals over the smoke plume a reasonable agreement in AOD between the MAPs and HSRL-2 was also found (MAE 0.088 and 0.079 for SPEX and RSP, respectively), despite the fact that the comparison is hampered by large spatial variability in AOD throughout the smoke plume. A good comparison is also found between the MAPs and HSRL-2 for the aerosol depolarization ratio (a measure of particle sphericity), with an MAE of 0.023 and 0.016 for SPEX and RSP, respectively. Finally, SPEX and RSP agree very well for the retrieved microphysical and optical properties of the smoke plume. [ABSTRACT FROM AUTHOR]

Highlights • We introduce the SPEXone instrument for the NASA PACE mission. • We demonstrate that SPEXone has high capability for aerosol retrieval. • Polarimetric accuracy is the most important factor determining capability for aerosol retrieval. • Having many spectral measurements, it is sufficient to measure at a small number (5) of viewing angles for aerosol retrieval. • On the PACE mission, retrieval capability will be further enhanced by combining with HARP-2 and OCI. Abstract SPEXone is a Multi-Angle Polarimeter instrument that is baselined to fly on the NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission, to be launched in 2022. It will perform hyper-spectral measurements of radiance and polarization in the spectral range 385–770 nm at 5 viewing angles (± 57 o , ± 20 o , 0 o ) with high accuracy (0.003) on the Degree of Linear Polarization (DoLP). Based on linear error analysis and retrievals on synthetic data, we conclude that SPEXone has the capability to significantly advance the accuracy of retrievals of optical and microphysical aerosol properties compared to past, present, and planned satellite instruments, as required for better quantification of the effect of aerosols on climate. The products that SPEXone will provide are Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), Aerosol Layer Height (ALH), effective radius, effective variance, complex refractive index, particle number column for both the fine and coarse mode as well as a shape parameter for the coarse mode. PACE will carry two other instrument: the Ocean Color Instrument (OCI) which is the main instrument and the Hyper-Angular Rainbow Polarimeter-2 (HARP-2). The synergistic use of SPEXone with these instruments will further increase retrieval accuracy, in particular for coarse mode parameters and absorption, and will provide unprecedented capability for aerosol above cloud retrievals. [ABSTRACT FROM AUTHOR]

For aerosol retrieval from multi-angle polarimetric (MAP) measurements over the ocean it is important to accurately account for the contribution of the ocean-body to the top-of-atmosphere signal, especially for wavelengths <500 nm. Performing online radiative transfer calculations in the coupled atmosphere ocean system is too time consuming for operational retrieval algorithms. Therefore, mostly lookup-tables of the ocean body reflection matrix are used to represent the lower boundary in an atmospheric radiative transfer model. For hyperspectral measurements such as those from Spectro-Polarimeter for Planetary Exploration (SPEXone) on the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission, also the use of look-up tables is unfeasible because they will become too big. In this paper, we propose a new method for aerosol retrieval over ocean from MAP measurements using a neural network (NN) to model the ocean body reflection matrix. We apply the NN approach to synthetic SPEXone measurements and also to real data collected by SPEX airborne during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We conclude that the NN approach is well capable for aerosol retrievals over ocean, introducing no significant error on the retrieved aerosol properties [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]

• PCF suite is the first dedicated satellite sensor for PM 2.5 remote sensing. • The principle of PCF composed by DPC and POSP are described. • Retrievals of aerosols and PM 2.5 by PMRS model are investigated. • The errors propagation from aerosols to PM 2.5 retrievals are discussed. Focusing on satellite remote sensing of fine particulate matter PM 2.5 from space, the polarization crossfire (PCF) strategy has been developed, which includes the PCF satellite suite and the particulate matter remote sensing (PMRS) model. Expected to be the first dedicated satellite sensor for PM 2.5 remote sensing globally, the PCF suite is composed by the Particulate Observing Scanning Polarimeter (POSP) and the Directional Polarimetric Camera (DPC) together, and will be launched on board the Chinese GaoFen-5(02) satellite in 2021. Since the cross-track polarimetric measurements of POSP fully cover the multi-viewing swath of DPC, the sophisticated joint measurements could be obtained from the PCF suite in the range of 380–2250 nm including intensity and polarization, by the means of pixel matching and the cross calibration from POSP to DPC. Based on the optimal estimation inversion framework and synthetic data of PCF, the retrieval performances of key aerosol parameters are systematically investigated and assessed for the PM 2.5 estimation by the PMRS model. For the design of inversion strategy for PCF, we firstly test the retrievals of aerosol optical depth (AOD), fine mode fraction (FMF), aerosol layer height (H) and the fine-mode real part of complex refractive index (m r f) simultaneously with surface parameters from the synthetic PCF data, and then the columnar volume-to-extinction ratio of fine particulates (VE f), the aerosol effective density (ρ f) and the hygroscopic growth factor of fine-mode particles (f (RH)) are further obtained by the corresponding empirical relationship. The propagation errors from aerosol parameters to PM 2.5 retrieval are investigated with the key procedures of PMRS model. In addition, the influences of improving calibration accuracy of PCF on PM 2.5 retrievals are discussed, as well as the retrieval feasibility of PM 10 by PCF strategy. [ABSTRACT FROM AUTHOR]