Efficient single-scattering lookup table for lidar and polarimeter phytoplankton studies.

Coupled atmosphere and ocean remote sensing retrievals of aerosol, cloud, and oceanic phytoplankton microphysical properties, such as those carried out by the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, involve single-scattering calculations that are time consuming. Lookup tables (LUTs) exist to speed up these calculations for aerosol and water droplets in the atmosphere. In our new Lorenz-Mie lookup table, we tabulate single scattering by an ensemble of coated isotropic spheres representing oceanic phytoplankton at wavelengths from 0.355 µm. The lookup table covers phytoplankton particles with radii in the range of 0.15-100 µm at an increase of up to 104 in computational speed compared to single-scattering calculations. The allowed complex refractive indices range from 1.05 to 1.24 for the shell's real part, from 10-7 to 0.3 for the shell's imaginary part, from 0 to 0.001 for the core's imaginary part, and equal to 1.02 for the core's real part. We show that we precisely compute inherent optical properties for the phytoplankton size distributions ranging up to 5 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.355 to 1.065 µm and find that all the inherent optical properties of interest agree with the single-scattering calculations to within 1% for 99.9% of cases. We also provide an example of using the lookup table to reproduce the phytoplankton optical datasets listed in the PANGAEA database for synthetic hyperspectral algorithm development. The table together with C++, Fortran, MATLAB, and Python codes to apply different complex refractive indices and phytoplankton size distributions is freely available online.

Efficient single-scattering look-up table for lidar and polarimeter water cloud studies.

Combined lidar and polarimeter retrievals of aerosol, cloud, and ocean microphysical properties involve single-scattering cloud calculations that are time consuming. We create a look-up table to speed up these calculations for water droplets in the atmosphere. In our new Lorenz-Mie look-up table we tabulate the light scattering by an ensemble of homogeneous isotropic spheres at wavelengths starting from 0.35 µm. The look-up table covers liquid water cloud particles with radii in the range of 0.001-500 µm while gaining an increase of up to 104 in computational speed. The covered complex refractive indices range from 1.25 to 1.36 for the real part and from 0 to 0.001 for the imaginary part. We show that we can precisely compute inherent optical properties for the particle size distributions ranging up to 100 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.35 to 2.3 µm and find that the elements of the normalized scattering matrix as well as the asymmetry parameter, the absorption, backscatter, extinction, and scattering coefficients are precise to within 1% for 96.7%-100% of cases depending on the inherent optical property. We also provide an example of using the look-up table with in situ measurements to determine agreement with remote sensing. The table together with C++, Fortran, MATLAB, and Python codes to interpolate the complex refractive index and apply different particle size distributions are freely available online.

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast - Part 1: Analysis of Aerosols, Gases, and Wet Deposition Chemistry.

The Western North Atlantic Ocean (WNAO) and adjoining East Coast of North America are of great importance for atmospheric research and have been extensively studied for several decades. This broad region exhibits complex meteorological features and a wide range of conditions associated with gas and particulate species from many sources regionally and other continents. As Part 1 of a 2-part paper series, this work characterizes quantities associated with atmospheric chemistry, including gases, aerosols, and wet deposition, by analyzing available satellite observations, ground-based data, model simulations, and reanalysis products. Part 2 provides insight into the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, properties, and precipitation over the WNAO domain. Key results include spatial and seasonal differences in composition along the North American East Coast and over the WNAO associated with varying sources of smoke and dust and meteorological drivers such as temperature, moisture, and precipitation. Spatial and seasonal variations of tropospheric carbon monoxide and ozone highlight different pathways toward the accumulation of these species in the troposphere. Spatial distributions of speciated aerosol optical depth and vertical profiles of aerosol mass mixing ratios show a clear seasonal cycle highlighting the influence of different sources in addition to the impact of intercontinental transport. Analysis of long-term climate model simulations of aerosol species and satellite observations of carbon monoxide confirm that there has been a significant decline in recent decades among anthropogenic constituents owing to regulatory activities.

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics.

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

Vertical Profiles of Droplet Size Distributions Derived from Cloud-Side Observations by the Research Scanning Polarimeter: Tests on Simulated Data.

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances with high angular resolution. It allows for accurate characterization of liquid water cloud droplet sizes using the rainbow structure in the polarized reflectance. RSP's observations also provide constraints on the cumulus cloud's 2D cross section, yielding estimates of its geometric shape. In this study for the first time we evaluate the possibility to retrieve vertical profiles of microphysical characteristics along the cloud side by combining these micro- and macrophysical retrieval methods. First we constrain cloud's geometric shape, then for each point on the bright side of its surface we collect data from different scans to obtain the multi-angle polarized reflectance at that point. The rainbow structures of the reflectances from multiple points yield the corresponding droplet size distributions (DSDs), which are then combined into vertical profiles. We present the results of testing the proposed profiling algorithm on simulated data obtained using large eddy simulations and 3D radiative transfer computations. The virtual RSP measurements were used for retrieval of DSD profiles, which then were compared to the actual data from the LES-model output. A cumulus congestus cloud was selected for these tests in preparation for analysis of real measurements made during the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). We demonstrate that the use of the non-parametric Rainbow Fourier Transform (RFT) allows for adequate retrieval of the complex altitude-dependent bimodal structure of cloud DSDs.

Intercomparison of airborne multi-angle polarimeter observations from the Polarimeter Definition Experiment.

In early 2013, three airborne polarimeters were flown on the high altitude NASA ER-2 aircraft in California for the Polarimeter Definition Experiment (PODEX). PODEX supported the pre-formulation NASA Aerosol-Cloud-Ecosystem (ACE) mission, which calls for an imaging polarimeter in polar orbit (among other instruments) for the remote sensing of aerosols, oceans, and clouds. Several polarimeter concepts exist as airborne prototypes, some of which were deployed during PODEX as a capabilities test. Two of those instruments to date have successfully produced Level 1 (georegistered, calibrated radiance and polarization) data from that campaign: the Airborne Multiangle Spectropolarimetric Imager (AirMSPI) and the Research Scanning Polarimeter (RSP). We compared georegistered observations of a variety of scene types by these instruments to test whether Level 1 products agreed within stated uncertainties. Initial comparisons found radiometric agreement, but polarimetric biases beyond measurement uncertainties. After subsequent updates to calibration, georegistration, and the measurement uncertainty models, observations from the instruments now largely agree within stated uncertainties. However, the 470 nm reflectance channels have a roughly +6% bias of AirMSPI relative to RSP, beyond expected measurement uncertainties. We also find that observations of dark (ocean) scenes, where polarimetric uncertainty is expected to be largest, do not agree within stated polarimetric uncertainties. Otherwise, AirMSPI and RSP observations are consistent within measurement uncertainty expectations, providing credibility for the subsequent creation of Level 2 (geophysical product) data from these instruments, and comparison thereof. The techniques used in this work can also form a methodological basis for other intercomparisons, for example, of the data gathered during the recent Aerosol Characterization from Polarimeter and Lidar (ACEPOL) field campaign, carried out in October and November of 2017 with four polarimeters (including AirMSPI and RSP).

Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives.

The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.

On averaging aspect ratios and distortion parameters over ice crystal population ensembles for estimating effective scattering asymmetry parameters.

The use of ensemble-average values of aspect ratio and distortion parameter of hexagonal ice prisms for the estimation of ensemble-average scattering asymmetry parameters is evaluated. Using crystal aspect ratios greater than unity generally leads to ensemble-average values of aspect ratio that are inconsistent with the ensemble-average asymmetry parameters. When a definition of aspect ratio is used that limits the aspect ratio to below unity (α≤1) for both hexagonal plates and columns, the effective asymmetry parameters calculated using ensemble-average aspect ratios are generally consistent with ensemble-average asymmetry parameters, especially if aspect ratios are geometrically averaged. Ensemble-average distortion parameters generally also yield effective asymmetry parameters that are largely consistent with ensemble-average asymmetry parameters. In the case of mixtures of plates and columns, it is recommended to geometrically average the α≤1 aspect ratios and to subsequently calculate the effective asymmetry parameter using a column or plate geometry when the contribution by columns to a given mixture's total projected area is greater or lower than 50%, respectively. In addition, we show that ensemble-average aspect ratios, distortion parameters and asymmetry parameters can generally be retrieved accurately from simulated multi-directional polarization measurements based on mixtures of varying columns and plates. However, such retrievals tend to be somewhat biased toward yielding column-like aspect ratios. Furthermore, generally large retrieval errors can occur for mixtures with approximately equal contributions of columns and plates and for ensembles with strong contributions of thin plates.

Passive remote sensing of aerosol layer height using near-UV multi-angle polarization measurements.

We demonstrate that multi-angle polarization measurements in the near-UV and blue part of the spectrum are very well suited for passive remote sensing of aerosol layer height. For this purpose we use simulated measurements with different set-ups (different wavelength ranges, with and without polarization, different polarimetric accuracies) as well as airborne measurements from the Research Scanning Polarimeter (RSP) obtained over the continental USA. We find good agreement of the retrieved aerosol layer height from RSP with measurements from the Cloud Physics Lidar (CPL) showing a mean absolute difference of less than 1 km. Furthermore, we found that the information on aerosol layer height is provided for large part by the multi-angle polarization measurements with high accuracy rather than the multi-angle intensity measurements. The information on aerosol layer height is significantly decreased when the shortest RSP wavelength (410 nm) is excluded from the retrieval and is virtually absent when 550 nm is used as shortest wavelength.

Vertical variation of ice particle size in convective cloud tops.

A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops (dre /dz) from airborne shortwave reflectance measurements and lidar. Values of dre /dz are about -6 µm/km for cloud tops below the homogeneous freezing level, increasing to near 0 µm/km above the estimated level of neutral buoyancy. Retrieved dre /dz compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present, and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud-top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.

Analysis of fine-mode aerosol retrieval capabilities by different passive remote sensing instrument designs.

Remote sensing of aerosol optical properties is difficult, but multi-angle, multi-spectral, polarimetric instruments have the potential to retrieve sufficient information about aerosols that they can be used to improve global climate models. However, the complexity of these instruments means that it is difficult to intuitively understand the relationship between instrument design and retrieval success. We apply a Bayesian statistical technique that relates instrument characteristics to the information contained in an observation. Using realistic simulations of fine size mode dominated spherical aerosols, we investigate three instrument designs. Two of these represent instruments currently in orbit: the Multiangle Imaging SpectroRadiometer (MISR) and the POLarization and Directionality of the Earths Reflectances (POLDER). The third is the Aerosol Polarimetry Sensor (APS), which failed to reach orbit during recent launch, but represents a viable design for future instruments. The results show fundamental differences between the three, and offer suggestions for future instrument design and the optimal retrieval strategy for current instruments. Generally, our results agree with previous validation efforts of POLDER and airborne prototypes of APS, but show that the MISR aerosol optical thickness uncertainty characterization is possibly underestimated.

Efficient vector radiative transfer calculations in vertically inhomogeneous cloudy atmospheres.

Accurate radiative transfer calculations in cloudy atmospheres are generally time consuming, limiting their practical use in satellite remote sensing applications. We present a model to efficiently calculate the radiative transfer of polarized light in atmospheres that contain homogeneous cloud layers. This model combines the Gauss-Seidel method, which is efficient for inhomogeneous cloudless atmospheres, with the doubling method, which is efficient for homogeneous cloud layers. Additionally to reduce the computational effort for radiative transfer calculations in absorption bands, the cloud reflection and transmission matrices are interpolated over the absorption and scattering optical thicknesses within the cloud layer. We demonstrate that the proposed radiative transfer model in combination with this interpolation technique is efficient for the simulation of satellite measurements for inhomogeneous atmospheres containing one homogeneous cloud layer. For example, the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) measurements in the oxygen A band (758-773 nm) and the Hartley-Huggins ozone band (295-335 nm) with a spectral resolution of 0.4 nm can be simulated for these atmospheres within 1 min on a 2.8 GHz PC with an accuracy better than 0.1%.