Plane-parallel Radiative Transfer Model Research Articles

An assessment of the impact of Indian summer monsoon droughts on atmospheric aerosols and associated radiative forcing at a semi-arid station in peninsular India

A continuing increase in droughts/floods in Asian monsoon regions and worsening air quality due to aerosols are the two biggest threats to the health and well being of over 60% of the world's population. This study focuses on in-situ observations of atmospheric aerosols and their impact on shortwave direct aerosol radiative forcing (SDARF) during the southwest monsoon season (June–September) from 2015 to 2020 over a semi-arid station in Southern India. The Standardized precipitation index (SPI) is used to identify the droughts and normal monsoon years. Based on the SPI index, 2015, 2016, and 2018 were considered the drought monsoon years, while 2017, 2019, and 2020 were chosen as the normal monsoon years. During the drought monsoon years (normal monsoon years), the monthly mean black carbon (BC) was 1.17 ± 0.25 (0.72 ± 0.18), 1.02 ± 0.31 (0.64 ± 0.17), 1.02 ± 0.38 (0.74 ± 0.28), and 1.28 ± 0.35 μg/m3 (0.88 ± 0.21 μg/m3), for June, July, August and September respectively. The lower BC concentration during the normal monsoon years is mainly due to the enhanced wet-removal rates by high rainfall over the measurement location. In July, there was a high ventilation coefficient (VC) and low concentration of BC, while in September, low VC, and a high concentration of BC was observed in both the drought and the normal monsoon years. In addition, a plane-parallel radiative transfer model was used to estimate shortwave direct aerosol radiative forcing for composite and without BC at various surfaces, including the surface (SUF), atmosphere (ATM), and top of the atmosphere (TOA). During the drought monsoon years (normal monsoon years), the estimated monthly mean ATM forcing was 17.6 ± 2.4 (13.9 ± 2.1), 17.5 ± 7.5 (12.7 ± 4.4), 17.2 ± 4.0 (13.5 ± 1.9), and 17.4 ± 2.8 Wm−2 (14.6 ± 0.7 Wm−2) for June, July, August, and September, respectively. During the drought monsoon years, the estimated BC forcing was substantially larger (8.8 ± 2.6 Wm−2) than that of normal monsoon years (6.0 ± 1.5 Wm−2). It indicates the important role of absorbing BC aerosols during the drought monsoon years in introducing additional heat to the lower atmosphere, particularly over peninsular India.

Estimating bias in the OCO-2 retrieval algorithm caused by 3-D radiation scattering from unresolved boundary layer clouds

Abstract. Due to the complexity of the multiple scattering problem for shortwave radiative transfer in Earth's atmosphere, operational physical retrieval algorithms commonly use a plane parallel radiative transfer model (RTM). This so-called one-dimensional (1-D) assumption allows practical retrieval algorithms to be implemented. In order to understand the impacts of this assumption for low altitude, unresolved clouds observed by OCO-2, the three-dimensional (3-D) radiative transfer model SHDOM is used to generate synthetic observations which are then processed by the operational retrieval algorithm based on a 1-D RTM. Simulations are performed over three realistic surface spectral albedos, corresponding to snow, vegetation, and bare soil. The results show that the existing cloud screening algorithm has difficulty identifying sub-field of view (FOV), unresolved clouds that fill less than half of the FOV. The unresolved clouds introduce a bias in the retrieved CO2 concentration, as quantified by the dry air mole fraction (XCO2). The biases are relatively small (less than 1 ppm) when the albedo at 2.1 μm is high, which is common over bare land surfaces. For cases with low 2.1 μm albedo, such as snow, the bias becomes much larger, up to 5 ppm. These results indicate that the XCO2 retrieval appears robust to 3-D scattering effects from unresolved low level clouds when the short wave infrared surface albedo is large, but for darker surfaces these clouds can introduce significant biases.

The Dependence of the Ice-Albedo Feedback on Atmospheric Properties

Ice-albedo feedback is a potentially important destabilizing effect for the climate of terrestrial planets. It is based on the positive feedback between decreasing surface temperatures, an increase of snow and ice cover, and an associated increase in planetary albedo, which then further decreases surface temperature. A recent study shows that for M stars, the strength of the ice-albedo feedback is reduced due to the strong spectral dependence of stellar radiation and snow/ice albedos; that is, M stars primarily emit in the near IR, where the snow and ice albedo is low, and less in the visible, where the snow/ice albedo is high. This study investigates the influence of the atmosphere (in terms of surface pressure and atmospheric composition) on this feedback, since an atmosphere was neglected in previous studies. A plane-parallel radiative transfer model was used for the calculation of planetary albedos. We varied CO₂ partial pressures as well as the H₂O, CH₄, and O₃ content in the atmosphere for planets orbiting Sun-like and M type stars. Results suggest that, for planets around M stars, the ice-albedo effect is significantly reduced, compared to planets around Sun-like stars. Including the effects of an atmosphere further suppresses the sensitivity to the ice-albedo effect. Atmospheric key properties such as surface pressure, but also the abundance of radiative trace gases, can considerably change the strength of the ice-albedo feedback. For dense CO₂ atmospheres of the order of a few to tens of bar, atmospheric rather than surface properties begin to dominate the planetary radiation budget. At high CO₂ pressures, the ice-albedo feedback is strongly reduced for planets around M stars. The presence of trace amounts of H₂O and CH₄ in the atmosphere also weakens the ice-albedo effect for both stellar types considered. For planets around Sun-like stars, O₃ could also lead to a very strong decrease of the ice-albedo feedback at high CO₂ pressures.

A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm

Abstract. The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studies. In this paper, the uncertainties in the cloud water path (CWP) retrievals derived with the cloud physical properties retrieval algorithm (CPP) of the climate monitoring satellite application facility (CM SAF) are investigated. To this end, a numerical simulator of MSG-SEVIRI observations has been developed that calculates the reflectances at 0.64 and 1.63 μm for a wide range of cloud parameter values, satellite viewing geometries and surface albedos using a plane-parallel radiative transfer model. The reflectances thus obtained are used as input to CPP, and the retrieved values of CWP are compared to the original input of the simulator. Cloud parameters considered in this paper refer to e.g. sub-pixel broken clouds and the simultaneous occurrence of ice and liquid water clouds within one pixel. These configurations are not represented in the CPP algorithm and as such the associated retrieval uncertainties are potentially substantial. It is shown that the CWP retrievals are very sensitive to the assumptions made in the CPP code. The CWP retrieval errors are generally small for unbroken single-layer clouds with COT > 10, with retrieval errors of ~3% for liquid water clouds to ~10% for ice clouds. In a multi-layer cloud, when both liquid water and ice clouds are present in a pixel, the CWP retrieval errors increase dramatically; depending on the cloud, this can lead to uncertainties of 40–80%. CWP retrievals also become more uncertain when the cloud does not cover the entire pixel, leading to errors of ~50% for cloud fractions of 0.75 and even larger errors for smaller cloud fractions. Thus, the satellite retrieval of cloud physical properties of broken clouds as well as multi-layer clouds is complicated by inherent difficulties, and the proper interpretation of such retrievals requires extra care.

Study of distinctive regional features of surface solar radiation in North and East China

Solar radiation is an important energy source for plants on the earth and also a major component of the global energy balance. Variations in solar radiation incident at the earth’s surface profoundly affect the human and terrestrial environment, including the climate change. To provide useful information for predicting the future climate change in China, distinctive regional features in spatial and temporal variations of the surface solar radiation (SSR) and corresponding attributions (such as cloud and aerosol) are analyzed based on SSR observations and other meteorological measurements in North and East China from 1961 to 2007. Multiple models, such as the plane-parallel radiative transfer model, empirical and statistical models, and correlation and regression analysis methods are used in the study. The results are given as follows. (1) During 1961–2007, the total SSR in North China went through a process from quickly “dimming” to slowly “dimming”, while in East China, a significant transition from “dimming” to “brightening” occurred. Although there are some differences between the two regional variation trends, long-term variations in SSR in the two regions are basically consistent with the observation worldwide. (2) Between the 1960s and 1980s, in both North and East China, aerosols played a critical role in the radiation dimming. However, after 1989, different variation trends of SSR occurred in North and East China, indicating that aerosols were not the dominant factor. (3) Cloud cover contributed less to the variation of SSR in North China, but was the major attribution in East China and played a promoting role in the reversal of SSR from dimming to brightening, especially in the “remarkable brightening” period, with its contribution as high as 70%.

Effects of atmospheric water and surface wind on passive microwave retrievals of sea ice concentration: a simulation study

The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors were examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water (CLW), water vapour (WV) and surface wind on the microwave signatures. A plane parallel radiative transfer model was used to compute brightness temperatures at SSM/I frequencies over surfaces that contained open water, first‐year (FY) ice, multi‐year (MY) ice and their combinations. Synthetic retrievals were performed using the NASA Team (NT) algorithm for the estimation of sea ice concentrations. Our results show that if the satellite sensor's field of view is filled with only FY ice, the retrieval is hardly affected by the atmospheric conditions because of the high contrast between emission signals from the FY ice surface and the atmosphere. Pure MY ice concentration is generally underestimated because of the low MY ice surface emissivity, which results in the enhancement of emission signals from the atmosphere. In marginal ice areas, the atmospheric and surface effects tend to degrade the accuracy at low sea ice concentrations. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. Moreover, strong surface wind appears to be more important than atmospheric water in contributing to the retrieval errors of total ice concentrations over marginal ice zones.

On the potential of sub-mm passive MW observations from geostationary satellites to retrieve heavy precipitation over the Mediterranean Area

Abstract. The general interest in the potential use of the mm and sub-mm frequencies up to 425 GHz resolution from geostationary orbit is increasing due to the fact that the frequent time sampling and the comparable spatial resolution relative to the "classical" (≤89 GHz) microwave frequencies would allow the monitoring of precipitating intense events for the assimilation of rain in now-casting weather prediction models. In this paper, we use the simulation of a heavy precipitating event in front of the coast of Crete island (Greece) performed by the University of Wisconsin - Non-hydrostatic Modeling System (UW-NMS) cloud resolving model in conjunction with a 3D-adjusted plane parallel radiative transfer model to simulate the upwelling brightness temperatures (TB's) at mm and sub-mm frequencies. To study the potential use of high frequencies, we first analyze the relationships of the simulated TB's with the microphysical properties of the UW-NMS simulated precipitating clouds, and then explore the capability of a Bayesian algorithm for the retrieval of surface rain rate, rain and ice water paths at such frequencies.

Laboratory measurements of spectral reflection from ice clouds of various habits

Spectral light from 550 to 650 nm reflected from the surface of an ice cloud produced in a temperature-controlled column is measured at seven different angles between 16.7 degrees and 29.9 degrees . Cloud optical depth (tau) is determined from the extinction of a 670 nm laser and is corrected for forward scattering using a Monte Carlo ray-tracing algorithm. Reflection measurements are compared to expectations from a plane-parallel radiative transfer model with input parameters based on the measured tau and a phase function for the observed ice crystal types. The plane-parallel radiative transfer model can be used to interpret the measured reflection for tau less than about 0.4 for this particular experiment, ideal for providing a validation data set to assist with the development of satellite bidirectional remote sensing.

Linearization of vector radiative transfer with respect to aerosol properties and its use in satellite remote sensing

We present a plane parallel radiative transfer model for polarized light that provides the intensity vector field as well as analytical derivatives of the four Stokes parameters at the top of the atmosphere with respect to physical properties of spherical aerosols. The linearization consists of two steps: (1) calculation of the derivatives of the four Stokes parameters at the top of the atmosphere with respect to scattering coefficient, extinction coefficient, and expansion coefficients of the scattering phase matrix. These derivatives are calculated employing the forward‐adjoint perturbation theory. General expressions are presented that can be applied for the linearization of any vector radiative transfer model that calculates the internal radiation field in the model atmosphere. (2) The second step is calculation of the derivatives of the scattering coefficient, extinction coefficient, and the expansion coefficients of the scattering phase matrix, with respect to the real and imaginary part of the refractive index, and parameters describing the size distribution (e.g., effective radius, effective variance). These derivatives are analytically calculated following Mie theory. The use of the developed linearized radiative transfer model for the retrieval of aerosol properties is demonstrated using synthetic measurements of intensity and polarization of the Global Ozone Monitoring Experiment‐2 (GOME‐2). Here it is shown that an iterative retrieval approach based on the linearized radiative transfer model is suited to solve the nonlinear aerosol retrieval problem, and additionally allows a solid error analysis.

AMSU-B Observations of Mixed-Phase Clouds over Land

Abstract Measurements from passive microwave satellite instruments such as the Advanced Microwave Sounding Unit B (AMSU-B) are sensitive to both liquid and ice cloud particles. Radiative transfer modeling is exploited to simulate the response of the AMSU-B instrument to mixed-phase clouds over land. The plane-parallel radiative transfer model employed for the study accounts for scattering and absorption from cloud ice as well as absorption and emission from trace gases and cloud liquid. The radiative effects of mixed-phase clouds on AMSU-B window channels (i.e., 89 and 150 GHz) and water vapor line channels (i.e., 183 ± 1, 3, and 7 GHz) are studied. Sensitivities to noncloud parameters, including surface temperature, surface emissivity, and atmospheric temperature and water vapor profiles, are also quantified. Modeling results indicate that both cloud phases generally have significant radiative effects and that the 150- and 183 ± 7-GHz channels are typically the most sensitive channels to integrated cloud properties (i.e., liquid water path and ice water path). However, results also indicate that AMSU-B measurements alone are probably insufficient for retrieving all mixed-phase cloud properties of interest. These results are supported by comparisons of AMSU-B observations of a mixed-phase cloud over the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) site with corresponding calculated clear-sky values.

Single-Scattering Properties of Mixed-Phase Arctic Clouds at Solar Wavelengths: Impacts on Radiative Transfer

In situ observations of the sizes, shapes, and phases of Arctic clouds were obtained during the First International Satellite Cloud Climatology Project Regional Experiment (FIRE) Arctic Clouds Experiment (ACE). These particle distributions were then combined with a library of single-scattering properties, calculated using Mie theory and improved geometric ray optics, to determine the corresponding single-scattering properties (single-scattering albedo v 0, phase function, and asymmetry parameter g) at solar wavelengths. During FIRE-ACE, mixed-phase clouds, where both water and ice were detected in 30 s of flight track, corresponding to 3.0-km horizontal extent, were observed in 33% of clouds. Because supercooled water drops generally dominate mass contents of these mixed-phase clouds, there is no statistically significant difference in the distributions of single-scattering properties of mixed-phase clouds compared to liquid-phase clouds, whereas those of ice crystals differ significantly. The average g for all mixed-phase clouds at visible wavelengths is 0.8556.005, similar to 0.8636.007 computed for water clouds, but higher than 0.7676.007 computed for ice clouds. Differences in g and v 0 between mixedand ice-phase clouds for near-infrared bands are also noted, whereas they are similar for mixed- and liquidphase clouds. Single-scattering properties computed using observations of mixed-phase clouds differ by more than 10% on average from those computed using a parameterization that describes the average fraction of water and ice in mixed-phase clouds. Simulations using a plane-parallel radiative transfer model show that these differences can cause top of the atmosphere albedos to vary between 6% and 100% depending on wavelength. However, when single-scattering properties are computed from observations over all phases (mixed, ice, and liquid), and average albedos are compared against those determined using the parameterized scattering properties, there is a difference of only 2% at visible wavelengths. Since observations show that the occurrence of phases is clustered, largescale averages may not be representative of mixed-phase cloud climatic effects.

A three-dimensional radiative transfer model to interpret ranging scatterometer measurements from a pine forest

This paper addresses the propagation of microwaves in forested media. It interprets the vertical distribution of backscatter acquired by a ranging scatterometer in a pine forest at X band (9.5 GHz) and vertical incidence by means of modelling. A plane parallel radiative transfer model for the forest canopy exhibits a large discrepancy between the measured and estimated distribution. This is attributed to failure to represent the horizontal heterogeneity in the forest. Taking into account the height variability of the trees significantly improves the estimated distribution at the top of the canopy but the backscatter from the lower layers and the ground is still underestimated. To deal with this, a fully three-dimensional (3D) radiative transfer model is developed. By modelling precisely the propagation of the wave through the medium, the 3D approach allows accurate estimation of the ground backscatter and slightly improves the estimated backscatter from the lower layers. It is demonstrated that 3D modelling is required to estimate accurately the vertical distribution of backscatter, total backscatter and the height of the centre of backscatter in the experimental data. These results have implications for the interpretation of more general measurements scenarios, especially as regards forest height measurement by radar interferometry.

Characterization of plumes on top of deep convective storm using AVHRR imagery and radiative transfer simulations

Cirrus clouds often form on top of intense convective storms and influence the radiation exchange at the top of the atmosphere. From time to time these cirrus assume a typical plume form, whose origin is yet to be clearly explained. Investigation on plume's structure and composition is necessary using satellite observations and radiative transfer modeling, since in situ measurements are generally not available for the storm's extreme scenarios. Plumes of ice crystals produce a significant increase of cloud top reflectivity in channel 3 (3.55–3.93 μm) of National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR), due to the small size of the crystals (of the order of the channel wavelength). AVHRR measurements over a severe storm are compared with radiative transfer simulations through a 1-D, plane-parallel radiative transfer model (RTM). The hydrometeor vertical distribution of a cumulonimbus tower is assumed, composed of a water droplet layer underlying an ice crystal layer. The presence of the plume on top of the cumulonimbus is simulated by an ice crystal layer whose optical depth and ice crystal size and habit are varied. The results of the comparisons show that channel 3 conveys relevant information on the ice crystal size and habit.

Use of Passive Microwave Observations in a Radar Rainfall-Profiling Algorithm

Abstract A physically based methodology to incorporate passive microwave observations in a “rain-profiling algorithm” is developed for space- or airborne radars at frequencies exhibiting attenuation. The rain-profiling algorithm deploys a formulation for reflectivity attenuation correction that is mathematically equivalent to that of Hitschfeld and Bordan. In this formulation, the reflectivity–hydrometeor content (or rainfall rate) and reflectivity–attenuation relationships are expressed as a function of one variable in the drop size distribution parameterization, namely, the multiplicative factor in a normalized gamma distribution. The multiplicative factor parameter, mean cloud water content, and one parameter describing the precipitation phase are estimated in a Bayesian framework. This involves the minimization of differences between the 10-, 19-, 37-, and 85-GHz brightness temperature values predicted by a plane-parallel multilayer radiative transfer model and those observed by space- or airborne rad...

A simple new radiative transfer model for simulating the effect of cirrus clouds in the microwave spectral region

The upwelling atmospheric radiation in the millimeter wave spectral range is influenced by the presence of cirrus clouds. A plane parallel radiative transfer model which can take into account the effect of multiple scattering by ice particles in the cirrus has been developed and is used to simulate the brightness temperatures as they would be measured by a satellite instrument. The model uses an iterative procedure to solve the radiative transfer equation. The formulation of the model is such that it can easily be adapted to treat the full specific intensity vector instead of just the scalar total intensity. A convergence test for the model is explained and two cirrus cloud scenarios are simulated. The results illustrate the linearity of microwave radiative transfer for not too strong cirrus clouds in this frequency region.

A linearized vector radiative transfer model for atmospheric trace gas retrieval

We present a plane parallel radiative transfer model for polarized light, that provides the intensity vector as well as the derivatives of the four Stokes parameters with respect to atmospheric trace gas profiles. These derivatives are essential for retrieval of height resolved trace gas information from satellite measurements of backscattered sunlight. The model uses the Gauss–Seidel iteration technique for solving the radiative transfer equation. For the first time, the forward-adjoint radiative perturbation theory is applied for the linearization of a radiative transfer model including polarization. The accuracy of the model is better than 0.025% for all four Stokes parameters and better than 0.03% for the derivatives.

Dust Scattering of Emission Lines in HiiRegions. I. Plane‐parallel Models and Application to the Orion Nebula (M42)

I present a comprehensive plane-parallel radiative transfer model for the scattering by dust of emission lines in a blister H II region on the surface of a molecular cloud. The effects of dust in the molecular cloud, within the H II region, and in a layer of overlying neutral material are all included. The spectral intensity and polarization profiles of the scattered lines are calculated, as well as the effective albedo of the scattering. Analytical, semianalytical and Monte Carlo numerical techniques are used, as appropriate. The model is applied in detail to observations of the [O III] λ5007 Å line in the inner Orion Nebula. It is shown that the observations are consistent with a backscattering origin for the broad redshifted component that is seen in this line, as well as in lines of other ionized species. High-resolution spectropolarimetry of the emission line would provide a conclusive test of the scattering model. Model fits suggest that the optical depth of dust between the ionization front and the [O III] emitting region is in the range 0.5-1.0 in the visible. Foreground scattering in the neutral lid that overlies the nebula is shown to have little effect on the line profile, although it could account for some of the unexplained broadening seen in all optical lines.

Surface Solar Radiation Flux and Cloud Radiative Forcing for the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP): A Satellite, Surface Observations, and Radiative Transfer Model Study

Abstract This study presents surface solar radiation flux and cloud radiative forcing results obtained by using a combination of satellite and surface observations interpreted by means of a simple plane-parallel radiative transfer model called 2001. This model, a revised version of a model initially introduced by Gautier et al., relates calibrated radiance observations from space to incoming surface solar flux. After a description of the model, an evaluation is presented by comparison with a more complex model that the authors have developed, the Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART) based on the discrete ordinate model of Stamnes et al. This evaluation demonstrates this model’s accuracy for instantaneous surface flux when used to retrieve daily (and monthly) surface solar flux. Limitations related to its lack of treatment of the bidirectional reflectance properties of clouds are also discussed and quantified by comparison with SBDART for instantaneous surface solar flux retri...

A new spherical model for computing the radiation field available for photolysis and heating at twilight

Accurate computation of atmospheric photodissociation and heating rates is needed in photo-chemical models. These quantities are proportional to the mean intensity of the solar radiation penetrating to various levels in the atmosphere. For large solar zenith angles a solution of the radiative transfer equation valid for a spherical atmosphere is required in order to obtain accurate values of the mean intensity. Such a solution based on a perturbation technique combined with the discrete Ordinate method is presented. Mean intensity calculations are carried out for various solar zenith angles. We compare these results with calculations from a plane parallel radiative transfer model in order to assess the importance of using correct geometry around sunrise and sunset. This comparison shows, in agreement with previous investigations, that for solar zenith angles less than 90° adequate solutions are obtained for plane parallel geometry as long as spherical geometry is used to compute the direct beam attenuation; but for solar zenith angles greater than 90° this “pseudo-spherical” plane parallel approximation overestimates the mean intensity. At 400 nm this overestimation is as much as 30% between 10 and 30 km for a solar zenith angle of 98°, while at 300 nm it is about 20% between 40 and 60 km for a solar zenith angle of 96°. The assumption of isotropic rather than Rayleigh (molecular) scattering may lead to an incorrect assessment of the radiation field available for photolysis and heating. Thus, at 450 nm isotroplc scattering leads to an underestimation of the mean intensity of a few percent when the Sun is above the horizon increasing to as much as 15% when the Sun is below the horizon. Model computations of zenith sky intensities agree well with twilight observations of Umkehr curves including the location of the minimum point (second Umkehr).

A Component Decomposition Model for Evaluating Atmospheric Effects in Remote Sensing

A radiance value of a target pixel recorded by a remote sensor can be decomposed into three components: (1) attenuated target signature, (2) pure atmospheric radiation, and (3) the contribution made by the ground through the atmospheric scattering process. Given the meteorological and optical parameters of a layer-structured atmosphere, its transmittance and radiance distribution can be accurately calculated with a plane-parallel radiative transfer model. For a uniform surface, the ground contribution can be obtained by comparing radiances for an atmosphere over a black but nonemitting surface and the same atmosphere with an underlying ground of given albedo or temperature. For an inhomogeneous surface, the first two components remain the same as long as the surface is a plane. The third may be estimated using the locally averaged top-of-atmosphere radiance. An atmospheric point spread function is calculated by a Monte Carlo approach and is used for retrieving the ground signature through a deconvolution procedure.