Ground-based Remote Sensing of Cirrus Clouds

Cirrus ◽  
2002 ◽  
Author(s):  
Kenneth Sassen ◽  
Gerald Mace
Keyword(s):  
Remote Sensing ◽  
Multispectral Imaging ◽  
Cirrus Clouds ◽  
Radiative Energy ◽  
Radiation Balance ◽  
Cirrus Cloud ◽  
Microphysical Properties ◽  
Research Aircraft ◽  
Cloud Modeling

Cirrus clouds have only recently been recognized as having a significant influence on weather and climate through their impact on the radiative energy budget of the atmosphere. In addition, the unique difficulties presented by the study of cirrus put them on the “back burner” of atmospheric research for much of the twentieth century. Foremost, because they inhabit the frigid upper troposphere, their inaccessibility has hampered intensive research. Other factors have included a lack of in situ instrumentation to effectively sample the clouds and environment, and basic uncertainties in the underlying physics of ice cloud formation, growth, and maintenance. Cloud systems that produced precipitation, severe weather, or hazards to aviation were deemed more worthy of research support until the mid- 1980s. Beginning at this time, however, major field research programs such as the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE; Cox et al. 1987), International Cirrus Experiment (ICE; Raschke et al. 1990), Experimental Cloud Lidar Pilot Study (ECLIPS; Platt et al. 1994), and the Atmospheric Radiation Measurement (ARM) Program (Stokes and Schwartz 1994) have concentrated on cirrus cloud research, relying heavily on ground-based remote sensing observations combined with research aircraft. What has caused this change in research emphasis is an appreciation for the potentially significant role that cirrus play in maintaining the radiation balance of the earth-atmosphere system (Liou 1986). As climate change issues were treated more seriously, it was recognized that the effects, or feedbacks, of extensive high-level ice clouds in response to global warming could be pivotal. This fortunately came at a time when new generations of meteorological instrumentation were becoming available. Beginning in the early 1970s, major advancements were made in the fields of numerical cloud modeling and cloud measurements using aircraft probes, satellite multispectral imaging, and remote sensing with lidar, short-wavelength radar, and radiometers, all greatly facilitating cirrus research. Each of these experimental approaches have their advantages and drawbacks, and it should also be noted that a successful cloud modeling effort relies on field data for establishing boundary conditions and providing case studies for validation. Although the technologies created for in situ aircraft measurements can clearly provide unique knowledge of cirrus cloud thermodynamic and microphysical properties (Dowling and Radke 1990), available probes may suffer from limitations in their response to the wide range of cirrus particles and actually sample a rather small volume of cloud during any mission.

Cirrus: A Modern Perspective

Cirrus ◽  
2002 ◽  
Author(s):  
Kenneth Sassen
Keyword(s):  
Global Warming ◽  
Multispectral Imaging ◽  
Cirrus Clouds ◽  
Radiation Balance ◽  
Cirrus Cloud ◽  
Upper Troposphere ◽  
Important Sense ◽  
Cloud Modeling ◽  
Macrophysical Properties ◽  
Measurement Capabilities

It is now understood that the cirrus clouds inhabiting the upper troposphere play a significant role in regulating the radiation balance of the earth-atmosphere system and so must be recognized as a crucial component in solving the human-induced climate change puzzle (Liou 1986). Because of their high altitudes, these cold, ice-dominated clouds act as a thermal blanket by trapping the outgoing terrestrial (infrared) radiation, but, at the same time, they can be effective at reflecting the incoming solar radiation back out to space. The balance between these two radiative processes, the greenhouse and albedo effects, respectively, determines the net impact of cirrus on our climate system. Which process dominates appears to be quite sensitive to the cloud microphysical and macrophysical properties (e.g., see Stephans et al. 1990). These properties in turn depend on the weather processes that generate cirrus, a function of geographic location, thereby complicating the global view. Of current concern is comprehending how cirrus clouds will respond, or feedback, to the effects of global warming caused by the buildup of carbon dioxide and other greenhouse gases. Would the changing atmosphere produce alterations in cirrus clouds that reinforce, or act to negate, the theoretically predicted global warming surmised from fundamental physics? One must also ask whether increasing jet aircraft traffic is creating more cirrus cloud cover, and if this traffic and agricultural activities are increasing the transport of dust and smoke particles into the upper troposphere and affecting, in a radiatively important sense, those cirrus formed naturally. Settling these issues could be pivotal to making difficult decisions on the future use of the Earth's resources. Fortunately, a new generation of meteorological instrumentation has become available. The need for these new measurement capabilities has helped to spawn and adapt instrumentation for cirrus research. Sophisticated cloud measurement capabilities using in situ probes on jet aircraft, satellite multispectral imaging, and remote sensing with lidar, short-wavelength radar, and passive radiometers, have all greatly facilitated cirrus cloud research. Major advancements have also been made in the field of numerical cloud modeling. As will be reviewed briefly here and in depth in following chapters, these developments have significantly advanced our knowledge of the characteristic properties of cirrus clouds over the past few decades.

Dynamic Processes in Cirrus Clouds: Concepts and Models

Cirrus ◽  
2002 ◽  
Author(s):  
David O’C. Starr ◽  
Markus Quante
Keyword(s):  
Cirrus Clouds ◽  
Radiative Properties ◽  
Cirrus Cloud ◽  
Early Model ◽  
Minimum Requirement ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Cloud Models ◽  
New Concepts

Advancement in the understanding of cirrus clouds and their life cycle comes through symbiotic use of models, observations, and related concepts (fig. 18.1). Models of cirrus clouds represent an integration of our knowledge of cirrus cloud properties and processes. They provide a capacity to extend knowledge and enhance understanding in ways that complement existing observational capabilities. Models can be used to develop new theories, such as parameterizations, and focus science issues and observational requirements and developments. For example, early model results of Starr and Cox (1985a) and Starr (1987b) predicted that fine cellular structure (~lkm or less) would be found in the upper part of extended stratiform cirrus clouds. This prediction was confirmed when high-frequency sensors were deployed both for active remote sensing (Sassen et al. 1990a, 1995) and later for in-situ measurements (Quante and Brown 1992; Gultepe et al. 1995; Quante et al. 1996). Sampling rates of 10Hz, or better, are now accepted as a minimum requirement for resolving cirrus cloud internal structure and circulation where 1-Hz or coarser measurements were previously used. Similarly, discrepancies between observed cloud radiative properties and calculations (theory) based on corresponding in-situ observations of cloud microphysical properties (Sassen et al. 1990b) led to the development of improved observing capabilities for small ice crystals (Arnott et al. 1994; Miloshevich and Heymsfield 1997; Lawson et al. 1998). Such sensors are now regarded as part of the standard complement when doing in-situ microphysical measurements in cirrus. At the same time, observations are absolutely essential in developing and evaluating cloud models. No cloud modeler wants to apply a model or theory too far beyond the limits of what can be observationally confirmed, at least in gross terms. The third aspect of this triad is concepts. Although models and observations can lead to predictions or diagnosis of unexpected relationships, they are each limited by the concepts that were used in their design and/or implementation. In the end, new concepts arising from analogy to other phenomena and/or from synergistic integration of existing knowledge can lead to new understanding, new models, new instruments, and new sampling strategies (fig. 18.1). Chapter 17 focuses on observations of internal cloud circulation and structure.

scholarly journals Aerosol optical and microphysical retrievals from a hybrid multiwavelength lidar data set – DISCOVER-AQ 2011

2014 ◽  
Vol 7 (9) ◽  
pp. 3095-3112 ◽  
Author(s):  
P. Sawamura ◽  
D. Müller ◽  
R. M. Hoff ◽  
C. A. Hostetler ◽  
R. A. Ferrare ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
Index Of Refraction ◽  
High Spectral Resolution ◽  
Lidar Data ◽  
Data Set ◽  
Microphysical Properties ◽  
Lidar Measurements ◽  
Multiwavelength Lidar

Abstract. Retrievals of aerosol microphysical properties (effective radius, volume and surface-area concentrations) and aerosol optical properties (complex index of refraction and single-scattering albedo) were obtained from a hybrid multiwavelength lidar data set for the first time. In July 2011, in the Baltimore–Washington DC region, synergistic profiling of optical and microphysical properties of aerosols with both airborne (in situ and remote sensing) and ground-based remote sensing systems was performed during the first deployment of DISCOVER-AQ. The hybrid multiwavelength lidar data set combines ground-based elastic backscatter lidar measurements at 355 nm with airborne High-Spectral-Resolution Lidar (HSRL) measurements at 532 nm and elastic backscatter lidar measurements at 1064 nm that were obtained less than 5 km apart from each other. This was the first study in which optical and microphysical retrievals from lidar were obtained during the day and directly compared to AERONET and in situ measurements for 11 cases. Good agreement was observed between lidar and AERONET retrievals. Larger discrepancies were observed between lidar retrievals and in situ measurements obtained by the aircraft and aerosol hygroscopic effects are believed to be the main factor in such discrepancies.

scholarly journals Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI

2017 ◽  
Vol 10 (11) ◽  
pp. 4317-4339 ◽  
Author(s):  
Johan Strandgren ◽  
Jennifer Fricker ◽  
Luca Bugliaro
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Cirrus Clouds ◽  
Cirrus Cloud ◽  
Retrieval Error ◽  
Water Path ◽  
Retrieval Accuracy ◽  
Ice Water Path ◽  
Retrieval Errors ◽  
Ice Water

Abstract. Cirrus clouds remain one of the key uncertainties in atmospheric research. To better understand the properties and physical processes of cirrus clouds, accurate large-scale observations from satellites are required. Artificial neural networks (ANNs) have proved to be a useful tool for cirrus cloud remote sensing. Since physics is not modelled explicitly in ANNs, a thorough characterisation of the networks is necessary. In this paper the CiPS (Cirrus Properties from SEVIRI) algorithm is characterised using the space-borne lidar CALIOP. CiPS is composed of a set of ANNs for the cirrus cloud detection, opacity identification and the corresponding cloud top height, ice optical thickness and ice water path retrieval from the imager SEVIRI aboard the geostationary Meteosat Second Generation satellites. First, the retrieval accuracy is characterised with respect to different land surface types. The retrieval works best over water and vegetated surfaces, whereas a surface covered by permanent snow and ice or barren reduces the cirrus detection ability and increases the retrieval errors for the ice optical thickness and ice water path if the cirrus cloud is thin (optical thickness less than approx. 0.3). Second, the retrieval accuracy is characterised with respect to the vertical arrangement of liquid, ice clouds and aerosol layers as derived from CALIOP lidar data. The CiPS retrievals show little interference from liquid water clouds and aerosol layers below an observed cirrus cloud. A liquid water cloud vertically close or adjacent to the cirrus clearly increases the average retrieval errors for the optical thickness and ice water path, respectively, only for thin cirrus clouds with an optical thickness below 0.3 or ice water path below 5.0 g m−2. For the cloud top height retrieval, only aerosol layers affect the retrieval error, with an increased positive bias when the cirrus is at low altitudes. Third, the CiPS retrieval error is characterised with respect to the properties of the investigated cirrus cloud (ice optical thickness and cloud top height). On average CiPS can retrieve the cirrus cloud top height with a relative error around 8 % and no bias and the ice optical thickness with a relative error around 50 % and bias around ±10 % for the most common combinations of cloud top height and ice optical thickness. Similarities with physically based retrieval methods are evident, which implies that even though the retrieval methods differ in the implementation of physics in the model, the retrievals behave similarly due to physical constraints. Finally, we also show that the ANN retrievals have a low sensitivity to radiometric noise in the SEVIRI observations. For optical thickness and ice water path the relative uncertainty due to noise is less than 10 % down to sub-visual cirrus. For the cloud top height retrieval the uncertainty due to noise is around 100 m for all cloud top heights.

scholarly journals Improvement of airborne retrievals of cloud droplet number concentration of trade wind cumulus using a synergetic approach

2019 ◽  
Vol 12 (3) ◽  
pp. 1635-1658 ◽  
Author(s):  
Kevin Wolf ◽  
André Ehrlich ◽  
Marek Jacob ◽  
Susanne Crewell ◽  
Martin Wirth ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Cloud Base ◽  
Trade Wind ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Research Aircraft ◽  
Cloud Droplet Number Concentration

Abstract. In situ measurements of cloud droplet number concentration N are limited by the sampled cloud volume. Satellite retrievals of N suffer from inherent uncertainties, spatial averaging, and retrieval problems arising from the commonly assumed strictly adiabatic vertical profiles of cloud properties. To improve retrievals of N it is suggested in this paper to use a synergetic combination of passive and active airborne remote sensing measurement, to reduce the uncertainty of N retrievals, and to bridge the gap between in situ cloud sampling and global averaging. For this purpose, spectral solar radiation measurements above shallow trade wind cumulus were combined with passive microwave and active radar and lidar observations carried out during the second Next Generation Remote Sensing for Validation Studies (NARVAL-II) campaign with the High Altitude and Long Range Research Aircraft (HALO) in August 2016. The common technique to retrieve N is refined by including combined measurements and retrievals of cloud optical thickness τ, liquid water path (LWP), cloud droplet effective radius reff, and cloud base and top altitude. Three approaches are tested and applied to synthetic measurements and two cloud scenarios observed during NARVAL-II. Using the new combined retrieval technique, errors in N due to the adiabatic assumption have been reduced significantly.

scholarly journals Factors that influence surface PM<sub>2.5</sub> values inferred from satellite observations: perspective gained for the US Baltimore–Washington metropolitan area during DISCOVER-AQ

2014 ◽  
Vol 14 (4) ◽  
pp. 2139-2153 ◽  
Author(s):  
S. Crumeyrolle ◽  
G. Chen ◽  
L. Ziemba ◽  
A. Beyersdorf ◽  
L. Thornhill ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Metropolitan Area ◽  
Scattering Coefficient ◽  
Data Set ◽  
Ambient Relative Humidity ◽  
Microphysical Properties ◽  
The Us ◽  
Dry Conditions ◽  
The Impact

Abstract. During the NASA DISCOVER-AQ campaign over the US Baltimore, MD–Washington, D.C., metropolitan area in July 2011, the NASA P-3B aircraft performed extensive profiling of aerosol optical, chemical, and microphysical properties. These in situ profiles were coincident with ground-based remote sensing (AERONET) and in situ (PM2.5) measurements. Here, we use this data set to study the correlation between the PM2.5 observations at the surface and the column integrated measurements. Aerosol optical depth (AOD550 nm) calculated with the extinction (550 nm) measured during the in situ profiles was found to be strongly correlated with the volume of aerosols present in the boundary layer (BL). Despite the strong correlation, some variability remains, and we find that the presence of aerosol layers above the BL (in the buffer layer – BuL) introduces significant uncertainties in PM2.5 estimates based on column-integrated measurements (overestimation of PM2.5 by a factor of 5). This suggests that the use of active remote sensing techniques would dramatically improve air quality retrievals. Indeed, the relationship between the AOD550 nm and the PM2.5 is strongly improved by accounting for the aerosol present in and above the BL (i.e., integrating the aerosol loading from the surface to the top of the BuL). Since more than 15% of the AOD values observed during DISCOVER-AQ are dominated by aerosol water uptake, the f(RH)amb (ratio of scattering coefficient at ambient relative humidity (RH) to scattering coefficient at low RH; see Sect. 3.2) is used to study the impact of the aerosol hygroscopicity on the PM2.5 retrievals. The results indicate that PM2.5 can be predicted within a factor up to 2 even when the vertical variability of the f(RH)amb is assumed to be negligible. Moreover, f(RH = 80%) and RH measurements performed at the ground may be used to estimate the f(RH)amb during dry conditions (RHBL < 55%).

Numerical modeling of mesospheric mountain wave propagation observed in Southern Argentina during the SOUTHTRAC campaign

2020 ◽  
Author(s):  
Tyler Mixa ◽  
Andreas Dörnbrack ◽  
Bernd Kaifler ◽  
Markus Rapp
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Numerical Models ◽  
Airborne Lidar ◽  
Tierra Del Fuego ◽  
Polar Night ◽  
Research Aircraft ◽  
Complex Propagation ◽  
The Antarctic

&lt;p&gt;We present numerical simulations of a deep orographic gravity wave (GW) event observed by the ALIMA airborne lidar on 11-12 September 2019 over Southern Argentina. The measurements are taken from the 2019 SOUTHTRAC Campaign, employing a comprehensive suite of remote sensing and in-situ instruments onboard the HALO research aircraft to study the stratospheric GW hotspot over Tierra del Fuego and the Antarctic Peninsula. Wind conditions on 11-12 September exhibit local and large-scale directional shear from the ground to the polar night jet, creating a complex propagation environment supporting multiple orientations of GW propagation and strong potential for local GW breaking and secondary GW generation. Using high resolution numerical models, we simulate the 3D evolution of the orographic GW field to analyze&lt;span&gt; the remote sensing and in-situ measurements from the event.&lt;/span&gt;&lt;/p&gt;

scholarly journals Freezing thresholds and cirrus cloud formation mechanisms inferred from in situ measurements of relative humidity

2003 ◽  
Vol 3 (5) ◽  
pp. 1791-1806 ◽  
Author(s):  
W. Haag ◽  
B. Kärcher ◽  
J. Ström ◽  
A. Minikin ◽  
U. Lohmann ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate Model ◽  
In Situ Measurements ◽  
Cirrus Clouds ◽  
Formation Mechanisms ◽  
Cirrus Cloud ◽  
Homogeneous Freezing

Abstract. Factors controlling the microphysical link between distributions of relative humidity above ice saturation in the upper troposphere and lowermost stratosphere and cirrus clouds are examined with the help of microphysical trajectory simulations. Our findings are related to results from aircraft measurements and global model studies. We suggest that the relative humidities at which ice crystals form in the atmosphere can be inferred from in situ measurements of water vapor and temperature close to, but outside of, cirrus clouds. The comparison with concomitant measurements performed inside cirrus clouds provides a clue to freezing mechanisms active in cirrus. The analysis of field data taken at northern and southern midlatitudes in fall 2000 reveals distinct differences in cirrus cloud freezing thresholds. Homogeneous freezing is found to be the most likely mechanism by which cirrus form at southern hemisphere midlatitudes. The results provide evidence for the existence of heterogeneous freezing in cirrus in parts of the polluted northern hemisphere, but do not suggest that cirrus clouds in this region form exclusively on heterogeneous ice nuclei, thereby emphasizing the crucial importance of homogeneous freezing. The key features of distributions of upper tropospheric relative humidity simulated by a global climate model are shown to be in general agreement with both, microphysical simulations and field observations, delineating a feasible method to include and validate ice supersaturation in other large-scale atmospheric models, in particular chemistry-transport and weather forecast models.

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