scholarly journals Comparison of retrieved Noctilucent cloud particle properties from Odin tomography scans and model simulations

2016 ◽  
Author(s):  
Linda Megner ◽  
Ole M. Christensen ◽  
Bodil Karlsson ◽  
Susanne Benze ◽  
Victor I. Fomichev
Keyword(s):  
Imaging System ◽  
Mass Density ◽  
Scattered Light ◽  
Measurement Techniques ◽  
Retrieval Algorithm ◽  
Atmospheric Conditions ◽  
Noctilucent Cloud ◽  
Remote Imaging ◽  
Satellite Retrieval ◽  
Cloud Properties

Abstract. Mesospheric ice particles, known as Noctilucent clouds or Polar Mesospheric Clouds, have long been observed by rocket instruments and satellites, while models have been used to simulate ice particle growth and cloud properties. However, the fact that different measurement techniques are sensitive to different parts of the ice particle distribution makes it difficult to compare retrieved parameters such as ice particle radius or particle number density from different experiments. In this work we investigate the accuracy of satellite retrieval based on scattered light and how this affects derived cloud properties. We run the retrieval algorithm on modelled cloud distributions and compare the results to the properties of the original distributions. We find that ice mass density is accurately retrieved whereas mean radius often is overestimated and high number densities generally are underestimated. The reason is that the retrieval algorithm assumes a Gaussian size distribution, whereas the modelled size distributions often are multimodal. Once we know the limits of the satellite retrieval we proceed to compare the properties retrieved from the modelled cloud distributions to those observed by the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) instrument on the Odin satellite. We find that a model with a stationary atmosphere, as given by average atmospheric conditions, does not yield cloud properties that are in agreement with the observations, whereas a model with realistic temperature and vertical wind variations does. This indicates that average atmospheric conditions are insufficient to understand the process of Noctilucent cloud growth and that a realistic atmospheric variability is crucial for cloud formation and growth. Further, the agreement between results from the model – when set up with a realistically variable atmosphere – and the observations suggests that our understanding of the growth process itself is reasonable.

scholarly journals Comparison of retrieved noctilucent cloud particle properties from Odin tomography scans and model simulations

2016 ◽  
Vol 16 (23) ◽  
pp. 15135-15146 ◽  
Author(s):  
Linda Megner ◽  
Ole M. Christensen ◽  
Bodil Karlsson ◽  
Susanne Benze ◽  
Victor I. Fomichev
Keyword(s):  
Imaging System ◽  
Mass Density ◽  
Scattered Light ◽  
Measurement Techniques ◽  
Retrieval Algorithm ◽  
Atmospheric Conditions ◽  
Noctilucent Cloud ◽  
Remote Imaging ◽  
Satellite Retrieval ◽  
Cloud Properties

Abstract. Mesospheric ice particles, known as noctilucent clouds or polar mesospheric clouds, have long been observed by rocket instruments, satellites and ground-based remote sensing, while models have been used to simulate ice particle growth and cloud properties. However, the fact that different measurement techniques are sensitive to different parts of the ice particle distribution makes it difficult to compare retrieved parameters such as ice particle radius or ice concentration from different experiments. In this work we investigate the accuracy of satellite retrieval based on scattered light and how this affects derived cloud properties. We apply the retrieval algorithm on spectral signals calculated from modelled cloud distributions and compare the results to the properties of the original distributions. We find that ice mass density is accurately retrieved whereas mean radius is often overestimated and high ice concentrations are generally underestimated. The reason is partly that measurements based on scattered light are insensitive to the smaller particles and partly that the retrieval algorithm assumes a Gaussian size distribution. Once we know the limits of the satellite retrieval we proceed to compare the properties retrieved from the modelled cloud distributions to those observed by the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) instrument on the Odin satellite. We find that a model with a stationary atmosphere, as given by average atmospheric conditions, does not yield cloud properties that are in agreement with the observations, whereas a model with realistic temperature and vertical wind variations does. This indicates that average atmospheric conditions are insufficient to understand the process of noctilucent cloud growth and that a realistic atmospheric variability is crucial for cloud formation and growth. Further, the agreement between results from the model, when set up with a realistically variable atmosphere, and the observations suggests that our understanding of the growth process itself is reasonable.

scholarly journals A Fast Retrieval of Cloud Parameters Using a Triplet of Wavelengths of Oxygen Dimer Band around 477 nm

2021 ◽  
Vol 13 (1) ◽  
pp. 152
Author(s):  
Haklim Choi ◽  
Xiong Liu ◽  
Gonzalo Gonzalez Abad ◽  
Jongjin Seo ◽  
Kwang-Mog Lee ◽  
...  
Keyword(s):  
Scattered Light ◽  
Trace Gas ◽  
Retrieval Algorithm ◽  
The Novel ◽  
Cloud Parameters ◽  
Retrieval Scheme ◽  
The Difference ◽  
The Look ◽  
Time Required ◽  
Cloud Top Pressure

Clouds act as a major reflector that changes the amount of sunlight reflected to space. Change in radiance intensity due to the presence of clouds interrupts the retrieval of trace gas or aerosol properties from satellite data. In this paper, we developed a fast and robust algorithm, named the fast cloud retrieval algorithm, using a triplet of wavelengths (469, 477, and 485 nm) of the O2–O2 absorption band around 477 nm (CLDTO4) to derive the cloud information such as cloud top pressure (CTP) and cloud fraction (CF) for the Geostationary Environment Monitoring Spectrometer (GEMS). The novel algorithm is based on the fact that the difference in the optical path through which light passes with regard to the altitude of clouds causes a change in radiance due to the absorption of O2–O2 at the three selected wavelengths. To reduce the time required for algorithm calculations, the look-up table (LUT) method was applied. The LUT was pre-constructed for various conditions of geometry using Vectorized Linearized Discrete Ordinate Radiative Transfer (VLIDORT) to consider the polarization of the scattered light. The GEMS was launched in February 2020, but the observed data of GEMS have not yet been widely released. To evaluate the performance of the algorithm, the retrieved CTP and CF using observational data from the Global Ozone Monitoring Experiment-2 (GOME-2), which cover the spectral range of GEMS, were compared with the results of the Fast Retrieval Scheme for Clouds from the Oxygen A band (FRESCO) algorithm, which is based on the O2 A-band. There was good agreement between the results, despite small discrepancies for low clouds.

scholarly journals Growth of nucleation mode particles in the summertime Arctic: a case study

2016 ◽  
Vol 16 (12) ◽  
pp. 7663-7679 ◽  
Author(s):  
Megan D. Willis ◽  
Julia Burkart ◽  
Jennie L. Thomas ◽  
Franziska Köllner ◽  
Johannes Schneider ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Methanesulfonic Acid ◽  
Lower Troposphere ◽  
Atmospheric Conditions ◽  
Aerosol Formation ◽  
Radiative Balance ◽  
Nucleation Mode ◽  
Cloud Properties ◽  
Marine Influence

Abstract. The summertime Arctic lower troposphere is a relatively pristine background aerosol environment dominated by nucleation and Aitken mode particles. Understanding the mechanisms that control the formation and growth of aerosol is crucial for our ability to predict cloud properties and therefore radiative balance and climate. We present an analysis of an aerosol growth event observed in the Canadian Arctic Archipelago during summer as part of the NETCARE project. Under stable and clean atmospheric conditions, with low inversion heights, carbon monoxide less than 80 ppbv, and black carbon less than 5 ng m−3, we observe growth of small particles,  <  20 nm in diameter, into sizes above 50 nm. Aerosol growth was correlated with the presence of organic species, trimethylamine, and methanesulfonic acid (MSA) in particles ∼ 80 nm and larger, where the organics are similar to those previously observed in marine settings. MSA-to-sulfate ratios as high as 0.15 were observed during aerosol growth, suggesting an important marine influence. The organic-rich aerosol contributes significantly to particles active as cloud condensation nuclei (CCN, supersaturation  =  0.6 %), which are elevated in concentration during aerosol growth above background levels of ∼ 100 to ∼ 220 cm−3. Results from this case study highlight the potential importance of secondary organic aerosol formation and its role in growing nucleation mode aerosol into CCN-active sizes in this remote marine environment.

scholarly journals Uncertainties of ground-based microwave radiometer retrievals in zenith and off-zenith observations under snow conditions

2017 ◽  
Vol 10 (1) ◽  
pp. 155-165 ◽  
Author(s):  
Wengang Zhang ◽  
Guirong Xu ◽  
Yuanyuan Liu ◽  
Guopao Yan ◽  
Dejun Li ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Microwave Radiometer ◽  
Retrieval Algorithm ◽  
Mean Square ◽  
Atmospheric Conditions ◽  
Vapor Density ◽  
Heavy Snowfall ◽  
Snow Conditions ◽  
The Impact ◽  
Mean Square Errors

Abstract. This paper is to investigate the uncertainties of microwave radiometer (MWR) retrievals in snow conditions and also explore the discrepancies of MWR retrievals in zenith and off-zenith observations. The MWR retrievals were averaged in a ±15 min period centered at sounding times of 00:00 and 12:00 UTC and compared with radiosonde observations (RAOBs). In general, the MWR retrievals have a better correlation with RAOB profiles in off-zenith observations than in zenith observations, and the biases (MWR observations minus RAOBs) and root mean square errors (RMSEs) between MWR and RAOB are also clearly reduced in off-zenith observations. The biases of temperature, relative humidity, and vapor density decrease from 4.6 K, 9 %, and 1.43 g m−3 in zenith observations to −0.6 K, −2 %, and 0.10 g m−3 in off-zenith observations, respectively. The discrepancies between MWR retrievals and RAOB profiles by altitude present the same situation. Cases studies show that the impact of snow on accuracies of MWR retrievals is more serious in heavy snowfall than in light snowfall, but off-zenith observation can mitigate the impact of snowfall. The MWR measurements become less accurate in snowfall mainly due to the retrieval algorithm, which does not consider the effect of snow, and the accumulated snow on the top of the radome increases the signal noise of MWR measurements. As the snowfall drops away by gravity on the sides of the radome, the off-zenith observations are more representative of the atmospheric conditions for RAOBs.

Simulations of Föhn in Antarctica with WRF for the Antarctic Mesoscale Prediction System AMPS

2021 ◽  
Author(s):  
Amélie Kirchgaessner ◽  
John King ◽  
Alan Gadian ◽  
Phil Anderson
Keyword(s):  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Prediction System ◽  
Atmospheric Conditions ◽  
Ice Shelf ◽  
Cloud Properties ◽  
Surface Melt ◽  
Mixed Phase Clouds ◽  
The Antarctic

&lt;p&gt;We examine the representation of F&amp;#246;hn events across the Antarctic Peninsula Mountains during 2011 as they were observed in measurements by an Automatic Weather Station, and in simulations with the Weather Research and Forecasting Model (WRF) as run for the Antarctic Mesoscale Prediction System (AMPS). On the Larsen Ice Shelf (LIS) in the lee of this mountain range F&amp;#246;hn winds are thought to provide the atmospheric conditions for significant warming over the ice shelf thus leading to the initial firn densification and subsequently providing the melt water for hydrofracturing. This process has led to the dramatic collapse of huge parts of the LIS in 1995 and 2002 respectively.&lt;/p&gt;&lt;p&gt;Measurements obtained at a crest AWS on the Avery Plateau (AV), and the analysis of conditions upstream using the Froude number help to put observations at CP into a wider context. We find that, while the model generally simulates meteorological parameters very well, and shows good skills in capturing the occurrence, frequency and duration of F&amp;#246;hn events realistically, it underestimates the temperature increase and the humidity decrease during the F&amp;#246;hn significantly, and may thus underestimate the contribution of F&amp;#246;hn to driving surface melt on the LIS.&lt;/p&gt;&lt;p&gt;Our results indicate that the misrepresentation of cloud properties and particularly the absence of mixed phase clouds in AMPS, affects the quality of weather simulation under normal conditions to some extent, and to a larger extent the model&amp;#8217;s capability to simulate the strength of F&amp;#246;hn conditions - and thus their contribution to driving surface melt on the LIS - adequately. Most importantly our data show that F&amp;#246;hn conditions can raise the air temperature to above freezing, and thus trigger melt/sublimation even in winter.&lt;/p&gt;

Synthetic Wavelength Holography: Snapshot Non-Line-of-Sight Imaging with High-Resolution and Wide Field of View

2020 ◽  
Author(s):  
Florian Willomitzer ◽  
Prasanna Rangarajan ◽  
Fengqiang Li ◽  
Muralidhar Balaji ◽  
Marc Christensen ◽  
...  
Keyword(s):  
High Resolution ◽  
Imaging System ◽  
Scattered Light ◽  
Field Of View ◽  
Line Of Sight ◽  
Wide Field ◽  
Navigation Systems ◽  
Small Probe ◽  
Wide Field Of View ◽  
Non Line Of Sight

Abstract The presence of a scattering medium in the imaging path between an object and an observer is known to severely limit the visual acuity of the imaging system. We present an approach to circumvent the deleterious effects of scattering, by exploiting spectral correlations in scattered wavefronts. Our Synthetic Wavelength Holography (SWH) method is able to recover a holographic representation of hidden targets with high resolution over a wide field of view. The complete object field is recorded in a snapshot-fashion, by monitoring the scattered light return in a small probe area. This unique combination of attributes opens up a plethora of new Non-Line-of-Sight imaging applications ranging from medical imaging and forensics, to early-warning navigation systems and reconnaissance. Adapting the findings of this work to other wave phenomena will help unlock a wider gamut of applications beyond those envisioned in this paper.

scholarly journals Validation of ozone profile retrievals derived from the OMPS LP version 2.5 algorithm against correlative satellite measurements

2018 ◽  
Vol 11 (5) ◽  
pp. 2837-2861 ◽  
Author(s):  
Natalya A. Kramarova ◽  
Pawan K. Bhartia ◽  
Glen Jaross ◽  
Leslie Moy ◽  
Philippe Xu ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Infrared Imaging ◽  
Imaging System ◽  
Thermal Sensitivity ◽  
Retrieval Algorithm ◽  
Ozone Profile ◽  
Mean Differences ◽  
The Stability ◽  
Cloud Tops ◽  
Spectral Ranges

Abstract. The Limb Profiler (LP) is a part of the Ozone Mapping and Profiler Suite launched on board of the Suomi NPP satellite in October 2011. The LP measures solar radiation scattered from the atmospheric limb in ultraviolet and visible spectral ranges between the surface and 80 km. These measurements of scattered solar radiances allow for the retrieval of ozone profiles from cloud tops up to 55 km. The LP started operational observations in April 2012. In this study we evaluate more than 5.5 years of ozone profile measurements from the OMPS LP processed with the new NASA GSFC version 2.5 retrieval algorithm. We provide a brief description of the key changes that had been implemented in this new algorithm, including a pointing correction, new cloud height detection, explicit aerosol correction and a reduction of the number of wavelengths used in the retrievals. The OMPS LP ozone retrievals have been compared with independent satellite profile measurements obtained from the Aura Microwave Limb Sounder (MLS), Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Odin Optical Spectrograph and InfraRed Imaging System (OSIRIS). We document observed biases and seasonal differences and evaluate the stability of the version 2.5 ozone record over 5.5 years. Our analysis indicates that the mean differences between LP and correlative measurements are well within required ±10 % between 18 and 42 km. In the upper stratosphere and lower mesosphere (> 43 km) LP tends to have a negative bias. We find larger biases in the lower stratosphere and upper troposphere, but LP ozone retrievals have significantly improved in version 2.5 compared to version 2 due to the implemented aerosol correction. In the northern high latitudes we observe larger biases between 20 and 32 km due to the remaining thermal sensitivity issue. Our analysis shows that LP ozone retrievals agree well with the correlative satellite observations in characterizing vertical, spatial and temporal ozone distribution associated with natural processes, like the seasonal cycle and quasi-biennial oscillations. We found a small positive drift ∼ 0.5 % yr−1 in the LP ozone record against MLS and OSIRIS that is more pronounced at altitudes above 35 km. This pattern in the relative drift is consistent with a possible 100 m drift in the LP sensor pointing detected by one of our altitude-resolving methods.

scholarly journals Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

2017 ◽  
Vol 10 (9) ◽  
pp. 3215-3230 ◽  
Author(s):  
André Ehrlich ◽  
Eike Bierwirth ◽  
Larysa Istomina ◽  
Manfred Wendisch
Keyword(s):  
Remote Sensing ◽  
Grain Size ◽  
Sea Ice ◽  
Optical Thickness ◽  
Liquid Water ◽  
Retrieval Algorithm ◽  
Continuous Transition ◽  
Cloud Properties ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

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