We investigated the importance of spectral range and angular resolution for
aerosol retrieval from multiangle photopolarimetric measurements over land.
For this purpose, we use an extensive set of simulated measurements for
different spectral ranges and angular resolutions and subsets of real
measurements of the airborne Research Scanning Polarimeter (RSP) carried out
during the PODEX and SEAC

The radiative impact caused by aerosols is widely considered to be one of the
largest uncertainties in the radiative forcing of the Earth
climate

RSP provides measurements of a ground scene at

In this paper we apply an extended version of the SRON aerosol retrieval
algorithm

In order to exploit the full spectral range of RSP, we extend the SRON aerosol retrieval algorithm to be capable to cope with spectrally dependent refractive indices. The paper is organized as follows: Sect. 2 describes the data used in the paper, Sect. 3 describes the retrieval method, Sect. 4 shows the results based on synthetic measurements and Sect. 5 shows the results based on RSP measurements. Finally, Sect. 6 concludes the paper.

Information of used RSP measurements

The RSP data used in the paper are obtained during the PODEX (Polarimeter
Definition Experiment) campaign and the SEAC

Measurements of individual ground pixel and effective

For both campaigns, we focus on measurements of the RSP bands at

Here, information on temperature, pressure and relative humidity profiles in
atmosphere is interpolated to a particular date, time and location of the RSP
measurements using NCEP reanalysis data

Imaginary (left panel) and real parts (right panel) of the
refractive index as a function of wavelength. Data taken
from

In the PODEX and SEAC

For RSP shortwave infrared bands, gaseous absorption need to be taken into
account. The absorption in RSP

The optical properties of aerosols depend on the size, shape and type of
aerosols. There is sufficient evidence that mixtures of spheroids allow
rather accurate fitting of measured spectral and angular dependencies of
observed intensity and polarization

Comparison between accounting for (top panel, for

For the characterization of surface reflection, the Rahman–Pinty–Verstraete
model (RPV)

We solve the vector radiative transfer equation in the Earth atmosphere using
the method as described
by

The aim of aerosol retrieval is to convert observed measurements into
information about physical properties of aerosols, i.e.,

The results of mean absolute errors of aerosol optical depth
(

Additionally, the complex refractive index

Comparison between retrieved and true values of aerosol optical
depth (

In total, for coarse mode aerosols there are eight state vector elements of
which two correspond to size (

Parameters of fine and coarse modes used in lookup table retrieval.

Parameters of RPV model and the modified Fresnel model used in lookup table retrieval.

To retrieve the state vector

One example of RSP measurements and the corresponding fit results
for DOLP in retrieval. Triangle symbols denote the RSP measurements and solid
lines with plus are fits using the forward model in Sect.

To obtain an appropriate first guess state vector for the iterative retrieval
procedure, we perform a retrieval using a lookup table based on 48 aerosol
modes for the fine mode and

Comparison between the retrieved AOD of RSP measurements and AERONET
at

For surface reflectance, the parameters of the RPV model used for generating
the lookup table at each wavelength are shown in Table

First, we perform our investigations on a set of

Comparison between the retrieved fine and coarse modes effective
radius (

Parameters of RPV model and the modified Fresnel model used in synthetic retrieval.

Comparison between retrieved single scattering albedo (SSA) and
composed refractive index of RSP measurements and those provided by AERONET
at

Retrieved AOD mean absolute error dependence on number of viewing angles for different spectral ranges of RSP data.

The forward model as described in Sect.

We first test the effect of spectral variation of the refractive index in the
retrieval. A measurement configuration is used with a wavelength range of

To investigate the importance of spectral range and angular resolution, we
investigate retrieval errors on

Figure

Figure

We applied our algorithm described above to RSP data over land close
(distance

For the aerosol properties from the AERONET inversion product it should be
noted that the corresponding accuracies are less well quantified and expected
to be similar or larger than those of the RSP retrievals. So, for SSA,
refractive index and effective radius, the results presented below should be
considered as a comparison rather than a validation. Apart from this, AERONET
retrieves one refractive index whereas we retrieve refractive indices for
both the fine and coarse mode. To get a general impression on the agreement
between AERONET and RSP retrieval, we compose a refractive index

In our RSP retrieval, we use five viewing angles which are evenly sampled
within the available range of each measurement and consider cases that passed
a goodness of fit criterion under

Figure

In Fig.

Figure

The retrieved center heights

Figure

In this paper we performed aerosol retrievals over land from multiangle photopolarimetric measurements produced synthetically and obtained by the airborne RSP instrument. We adjusted the SRON aerosol retrieval algorithm to cope with spectrally dependent refractive indices so that it can be applied to all RSP spectral channels.

We investigated the capability of different retrieval setups with varying
spectral ranges and angular resolutions by considering

For retrievals from real RSP measurements, the retrieved AOD
agrees well with AERONET products. The correlation coefficients are

We wish to thank two anonymous reviewers, Matteo Ottaviani, Thibaut Lurton,
and Michael Garay for their interest and valuable comments which have led to
several improvements. The RSP data from the SEAC