scholarly journals A multi-wavelength classification method for polar stratospheric cloud types using infrared limb spectra

Author(s):  
R. Spang ◽  
L. Hoffmann ◽  
M. Höpfner ◽  
S. Griessbach ◽  
R. Müller ◽  
...  

Abstract. The MIPAS instrument onboard the ESA Envisat satellite operated from July 2002 until April 2012. The infrared limb emission measurements represent a unique dataset of day and night observations of polar stratospheric clouds (PSCs) up to both poles. Cloud detection sensitivity is comparable to spaceborne lidars, and it is possible to classify different cloud types from the spectral measurements in different atmospheric windows regions. Here we present a new PSC classification scheme based on the combination of a well-established two-colour ratio method and multiple 2D brightness temperature difference probability density functions. The method is a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption. The method has been tested in conjunction with a database of radiative transfer model calculations of realistic PSC particle size distributions, geometries, and composition. The Bayesian classifier distinguishes between solid particles of ice and nitric acid trihydrate (NAT), as well as liquid droplets of super-cooled ternary solution (STS). The classification results are compared to coincident measurements from the space borne lidar CALIOP instrument over the temporal overlap of both satellite missions (June 2006 to March 2012). Both datasets show a good agreement for the specific PSC classes, although the viewing geometries, vertical and horizontal resolution are quite different. Discrepancies are observed for the MIPAS ice class. The Bayesian classifier for MIPAS identifies substantially more ice clouds in the southern hemisphere polar vortex than CALIOP. This disagreement is attributed in parts to the difference in the sensitivity on mixed-type clouds. Ice seems to dominate the spectral behaviour in the limb infrared spectra and may cause an overestimation in ice occurrence compared to the real fraction of ice within the PSC area in the polar vortex. The entire MIPAS measurement period was processed with the new classification approach. Examples like the detection of the Antarctic NAT belt during early winter, and its possible link to mountain wave events over the Antarctic Peninsula, which are observed by the AIRS instrument, are highlighting the importance of a climatology of in total 9 southern and 10 northern hemisphere winters. The new dataset is valuable both for detailed process studies, and for comparisons with and improvements of the PSC parameterisations used in chemistry transport and climate models.

2016 ◽  
Vol 9 (8) ◽  
pp. 3619-3639 ◽  
Author(s):  
Reinhold Spang ◽  
Lars Hoffmann ◽  
Michael Höpfner ◽  
Sabine Griessbach ◽  
Rolf Müller ◽  
...  

Abstract. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument on board the ESA Envisat satellite operated from July 2002 until April 2012. The infrared limb emission measurements represent a unique dataset of daytime and night-time observations of polar stratospheric clouds (PSCs) up to both poles. Cloud detection sensitivity is comparable to space-borne lidars, and it is possible to classify different cloud types from the spectral measurements in different atmospheric windows regions. Here we present a new infrared PSC classification scheme based on the combination of a well-established two-colour ratio method and multiple 2-D brightness temperature difference probability density functions. The method is a simple probabilistic classifier based on Bayes' theorem with a strong independence assumption. The method has been tested in conjunction with a database of radiative transfer model calculations of realistic PSC particle size distributions, geometries, and composition. The Bayesian classifier distinguishes between solid particles of ice and nitric acid trihydrate (NAT), as well as liquid droplets of super-cooled ternary solution (STS). The classification results are compared to coincident measurements from the space-borne lidar Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument over the temporal overlap of both satellite missions (June 2006–March 2012). Both datasets show a good agreement for the specific PSC classes, although the viewing geometries and the vertical and horizontal resolution are quite different. Discrepancies are observed between the CALIOP and the MIPAS ice class. The Bayesian classifier for MIPAS identifies substantially more ice clouds in the Southern Hemisphere polar vortex than CALIOP. This disagreement is attributed in part to the difference in the sensitivity on mixed-type clouds. Ice seems to dominate the spectral behaviour in the limb infrared spectra and may cause an overestimation in ice occurrence compared to the real fraction of ice within the PSC area in the polar vortex. The entire MIPAS measurement period was processed with the new classification approach. Examples like the detection of the Antarctic NAT belt during early winter, and its possible link to mountain wave events over the Antarctic Peninsula, which are observed by the Atmospheric Infrared Sounder (AIRS) instrument, highlight the importance of a climatology of 9 Southern Hemisphere and 10 Northern Hemisphere winters in total. The new dataset is valuable both for detailed process studies, and for comparisons with and improvements of the PSC parameterizations used in chemistry transport and climate models.


2014 ◽  
Vol 7 (5) ◽  
pp. 4623-4657
Author(s):  
M. Mech ◽  
E. Orlandi ◽  
S. Crewell ◽  
F. Ament ◽  
L. Hirsch ◽  
...  

Abstract. An advanced package of microwave remote sensing instrumentation has been developed for the operation on the new German High Altitude LOng range research aircraft (HALO). The HALO Microwave Package, HAMP, consists of two nadir looking instruments: a cloud radar at 36 GHz and a suite of passive microwave radiometers with 26 frequencies in different bands between 22.24 and 183.31 ± 12.5 GHz. We present a description of HAMP's instrumentation together with an illustration of its potential. To demonstrate this potential synthetic measurements for the implemented passive microwave frequencies and the cloud radar based on cloud resolving and radiative transfer model calculations were performed. These illustrate the advantage of HAMP's chosen frequency coverage, which allows for improved detection of hydrometeors both via the emission and scattering of radiation. Regression algorithms compare HAMP retrieval with standard satellite instruments from polar orbiters and show its advantages particularly for the lower atmosphere with a reduced root mean square error by 5 and 15% for temperature and humidity, respectively. HAMP's main advantage is the high spatial resolution of about 1 km which is illustrated by first measurements from test flights. Together these qualities make it an exciting tool for gaining better understanding of cloud processes, testing retrieval algorithms, defining future satellite instrument specifications, and validating platforms after they have been placed in orbit.


2008 ◽  
Vol 8 (5) ◽  
pp. 17467-17493 ◽  
Author(s):  
S. Kazadzis ◽  
A. Bais ◽  
A. Arola ◽  
N. Krotkov ◽  
N. Kouremeti ◽  
...  

Abstract. We have compared spectral ultraviolet overpass irradiances from the Ozone Monitoring Instruments (OMI) against ground-based Brewer measurements at Thessaloniki, Greece from September 2004 to December 2007. It is demonstrated that OMI overestimates UV irradiances by 30%, 17% and 13% for 305 nm, 324 nm, and 380 nm respectively and 20% for erythemally weighted irradiance. The bias between OMI and Brewer increases with increasing aerosol absorption optical thickness. We present methodologies that can be applied for correcting this bias based on experimental results derived from the comparison period and also theoretical approaches using radiative transfer model calculations. All correction approaches minimize the bias and the standard deviation of the ratio OMI versus Brewer ratio. According to the results, the best correction approach suggests that the OMI UV product has to be multiplied by a correction factor CA(λ) are in the order of 0.8, 0.88 and 0.9 for 305 nm, 324 nm and 380 nm respectively. Limitations and possibilities for applying such methodologies in a global scale are also discussed.


2016 ◽  
Author(s):  
Ghislain Picard ◽  
Quentin Libois ◽  
Laurent Arnaud

Abstract. Ice is a highly transparent material in the visible. According to the most widely used database (Warren and Brandt, 2008; IA2008), the ice absorption coefficient reaches values lower than 10−3 m−1 around 400 nm. These values were obtained from a radiance profile measured in a single snow layer at Dome C in Antarctica. We reproduced this experiment using a fiber optics inserted in the snow to record 56 profiles from which 70 homogeneous layers were identified. Applying the same estimation method on every layer yields 70 ice absorption spectra with a significant variability and overall larger than IA2008 by one order of magnitude. We devise another estimation method based on Bayesian inference. It reduces the statistical variability and confirms the higher absorption, around 2 × 10−2 m−1 near the minimum at 440 nm. We explore potential instrumental artifacts by developing a 3D radiative transfer model able to explicitly account for the presence of the fiber in the snow. The simulation results show that the radiance profile is indeed perturbed by the fiber intrusion but the error on the ice absorption estimate is not larger than a factor 2. This is insufficient to explain the difference between our new estimate and IA2008. Nevertheless, considering the number of profiles acquired for this study and other estimates from the Antarctic Muon and Neutrino Detector Array (AMANDA), we estimate that ice absorption values around 10−2 m−1 at the minimum are more likely than under 10−3 m−1. We provide a new estimate in the range 400–600 nm for future modeling of snow, cloud, and sea-ice optical properties. Most importantly we recommend that modeling studies take into account the large uncertainty of the ice absorption coefficient in the visible.


2021 ◽  
Author(s):  
Megan Stretton ◽  
William Morrison ◽  
Robin Hogan ◽  
Sue Grimmond

<p>The heterogenous structure of cities impacts radiative exchanges (e.g. albedo and heat storage). Numerical weather prediction (NWP) models often characterise the urban structure with an infinite street canyon – but this does not capture the three-dimensional urban form. SPARTACUS-Urban (SU) - a fast, multi-layer radiative transfer model designed for NWP - is evaluated using the explicit Discrete Anisotropic Radiative Transfer (DART) model for shortwave fluxes across several model domains – from a regular array of cubes to real cities .</p><p>SU agrees with DART (errors < 5.5% for all variables) when the SU assumptions of building distribution are fulfilled (e.g. randomly distribution). For real-world areas with pitched roofs, SU underestimates the albedo (< 10%) and shortwave transmission to the surface (< 15%), and overestimates wall-plus-roof absorption (9-27%), with errors increasing with solar zenith angle. SU should be beneficial to weather and climate models, as it allows more realistic urban form (cf. most schemes) without large increases in computational cost.</p>


2005 ◽  
Vol 5 (6) ◽  
pp. 1721-1730 ◽  
Author(s):  
A. Fotiadi ◽  
N. Hatzianastassiou ◽  
C. Matsoukas ◽  
K. G. Pavlakis ◽  
E. Drakakis ◽  
...  

Abstract. A decadal-scale trend in the tropical radiative energy budget has been observed recently by satellites, which however is not reproduced by climate models. In the present study, we have computed the outgoing shortwave radiation (OSR) at the top of atmosphere (TOA) at 2.5° longitude-latitude resolution and on a mean monthly basis for the 17-year period 1984-2000, by using a deterministic solar radiative transfer model and cloud climatological data from the International Satellite Cloud Climatology Project (ISCCP) D2 database. Anomaly time series for the mean monthly pixel-level OSR fluxes, as well as for the key physical parameters, were constructed. A significant decreasing trend in OSR anomalies, starting mainly from the late 1980s, was found in tropical and subtropical regions (30° S-30° N), indicating a decadal increase in solar planetary heating equal to 1.9±0.3Wm-2/decade, reproducing well the features recorded by satellite observations, in contrast to climate model results. This increase in solar planetary heating, however, is accompanied by a similar increase in planetary cooling, due to increased outgoing longwave radiation, so that there is no change in net radiation. The model computed OSR trend is in good agreement with the corresponding linear decadal decrease of 2.5±0.4Wm-2/decade in tropical mean OSR anomalies derived from ERBE S-10N non-scanner data (edition 2). An attempt was made to identify the physical processes responsible for the decreasing trend in tropical mean OSR. A detailed correlation analysis using pixel-level anomalies of model computed OSR flux and ISCCP cloud cover over the entire tropical and subtropical region (30° S-30° N), gave a correlation coefficient of 0.79, indicating that decreasing cloud cover is the main reason for the tropical OSR trend. According to the ISCCP-D2 data derived from the combined visible/infrared (VIS/IR) analysis, the tropical cloud cover has decreased by 6.6±0.2% per decade, in relative terms. A detailed analysis of the inter-annual and long-term variability of the various parameters determining the OSR at TOA, has shown that the most important contribution to the observed OSR trend comes from a decrease in low-level cloud cover over the period 1984-2000, followed by decreases in middle and high-level cloud cover. Note, however, that there still remain some uncertainties associated with the existence and magnitude of trends in ISCCP-D2 cloud amounts. Opposite but small trends are introduced by increases in cloud scattering optical depth of low and middle clouds.


2018 ◽  
Vol 176 ◽  
pp. 08008
Author(s):  
Daniela Viviana Vlăduţescu ◽  
Stephen E. Schwartz ◽  
Dong Huang

Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.


2007 ◽  
Vol 20 (17) ◽  
pp. 4459-4475 ◽  
Author(s):  
C. J. Stubenrauch ◽  
F. Eddounia ◽  
J. M. Edwards ◽  
A. Macke

Abstract Combined simultaneous satellite observations are used to evaluate the performance of parameterizations of the microphysical and optical properties of cirrus clouds used for radiative flux computations in climate models. Atmospheric and cirrus properties retrieved from Television and Infrared Observation Satellite (TIROS-N) Operational Vertical Sounder (TOVS) observations are given as input to the radiative transfer model developed for the Met Office climate model to simulate radiative fluxes at the top of the atmosphere (TOA). Simulated cirrus shortwave (SW) albedos are then compared to those retrieved from collocated Scanner for Radiation Budget (ScaRaB) observations. For the retrieval, special care has been given to angular direction models. Three parameterizations of cirrus ice crystal optical properties are represented in the Met Office radiative transfer model. These parameterizations are based on different physical approximations and different hypotheses on crystal habit. One parameterization assumes pristine ice crystals and two ice crystal aggregates. By relating the cirrus ice water path (IWP) retrieved from the effective infrared emissivity to the cirrus SW albedo, differences between the parameterizations are amplified. This study shows that pristine crystals seem to be plausible only for cirrus with IWP less than 30 g m−2. For larger IWP, ice crystal aggregates lead to cirrus SW albedos in better agreement with the observations. The data also indicate that climate models should allow the cirrus effective ice crystal diameter (De) to increase with IWP, especially in the range up to 30 g m−2. For cirrus with IWP less than 20 g m−2, this would lead to SW albedos that are about 0.02 higher than the ones of a constant De of 55 μm.


2018 ◽  
Vol 57 (3) ◽  
pp. 493-515 ◽  
Author(s):  
S. K. Mukkavilli ◽  
A. A. Prasad ◽  
R. A. Taylor ◽  
A. Troccoli ◽  
M. J. Kay

AbstractDirect normal irradiance (DNI) is the main input for concentrating solar power (CSP) technologies—an important component in future energy scenarios. DNI forecast accuracy is sensitive to radiative transfer schemes (RTSs) and microphysics in numerical weather prediction (NWP) models. Additionally, NWP models have large regional aerosol uncertainties. Dust aerosols can significantly attenuate DNI in extreme cases, with marked consequences for applications such as CSP. To date, studies have not compared the skill of different physical parameterization schemes for predicting hourly DNI under varying aerosol conditions over Australia. The authors address this gap by aiming to provide the first Weather and Forecasting (WRF) Model DNI benchmarks for Australia as baselines for assessing future aerosol-assimilated models. Annual and day-ahead simulations against ground measurements at selected sites focusing on an extreme dust event are run. Model biases are assessed for five shortwave RTSs at 30- and 10-km grid resolutions, along with the Thompson aerosol-aware scheme in three different microphysics configurations: no aerosols, fixed optical properties, and monthly climatologies. From the annual simulation, the best schemes were the Rapid Radiative Transfer Model for global climate models (RRTMG), followed by the new Goddard and Dudhia schemes, despite the relative simplicity of the latter. These top three RTSs all had 1.4–70.8 W m−2 lower mean absolute error than persistence. RRTMG with monthly aerosol climatologies was the best combination. The extreme dust event had large DNI mean bias overpredictions (up to 4.6 times), compared to background aerosol results. Dust storm–aware DNI forecasts could benefit from RRTMG with high-resolution aerosol inputs.


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