scholarly journals A flexible three-dimensional stratocumulus, cumulus and cirrus cloud generator (3DCLOUD) based on drastically simplified atmospheric equations and Fourier transform framework

2014 ◽  
Vol 7 (1) ◽  
pp. 295-337 ◽  
Author(s):  
F. Szczap ◽  
Y. Gour ◽  
T. Fauchez ◽  
C. Cornet ◽  
T. Faure ◽  
...  

Abstract. The 3DCLOUD algorithm for generating stochastic three-dimensional (3-D) cloud fields is described in this paper. The generated outputs are 3-D optical depth (τ) for stratocumulus and cumulus fields and 3-D ice water content (IWC) for cirrus clouds. This model is designed to generate cloud fields that share some statistical properties observed in real clouds such as the inhomogeneity parameter ρ (standard deviation normalized by the mean of the studied quantity), the Fourier spectral slope β close to −5/3 between the smallest scale of the simulation to the outer Lout (where the spectrum becomes flat). Firstly, 3DCLOUD assimilates meteorological profiles (humidity, pressure, temperature and wind velocity). The cloud coverage C, defined by the user, can also be assimilated, but only for stratocumulus and cumulus regime. 3DCLOUD solves drastically simplified basic atmospheric equations, in order to simulate 3-D cloud structures of liquid or ice water content. Secondly, Fourier filtering method is used to constrain intensity of ρ, β, Lout and mean of τ or IWC of these 3-D cloud structures. 3DCLOUD model was developed to run on a personnel computer under Matlab environment with the Matlab statistics toolbox. It is used to study 3-D interactions between cloudy atmosphere and radiation.

2014 ◽  
Vol 7 (4) ◽  
pp. 1779-1801 ◽  
Author(s):  
F. Szczap ◽  
Y. Gour ◽  
T. Fauchez ◽  
C. Cornet ◽  
T. Faure ◽  
...  

Abstract. The 3DCLOUD algorithm for generating stochastic three-dimensional (3-D) cloud fields is described in this paper. The generated outputs are 3-D optical depth (τ) for stratocumulus and cumulus fields and 3-D ice water content (IWC) for cirrus clouds. This model is designed to generate cloud fields that share some statistical properties observed in real clouds such as the inhomogeneity parameter ρ (standard deviation normalized by the mean of the studied quantity), the Fourier spectral slope β close to −5/3 between the smallest scale of the simulation to the outer Lout (where the spectrum becomes flat). Firstly, 3DCLOUD assimilates meteorological profiles (humidity, pressure, temperature and wind velocity). The cloud coverage C, defined by the user, can also be assimilated, but only for stratocumulus and cumulus regime. 3DCLOUD solves drastically simplified basic atmospheric equations, in order to simulate 3-D cloud structures of liquid or ice water content. Secondly, the Fourier filtering method is used to constrain the intensity of ρ, β, Lout and the mean of τ or IWC of these 3-D cloud structures. The 3DCLOUD model was developed to run on a personal computer under Matlab environment with the Matlab statistics toolbox. It is used to study 3-D interactions between cloudy atmosphere and radiation.


2013 ◽  
Vol 13 (23) ◽  
pp. 12043-12058 ◽  
Author(s):  
M. S. Johnston ◽  
S. Eliasson ◽  
P. Eriksson ◽  
R. M. Forbes ◽  
K. Wyser ◽  
...  

Abstract. An earlier method to determine the mean response of upper-tropospheric water to localised deep convective systems (DC systems) is improved and applied to the EC-Earth climate model. Following Zelinka and Hartmann (2009), several fields related to moist processes and radiation from various satellites are composited with respect to the local maxima in rain rate to determine their spatio-temporal evolution with deep convection in the central Pacific Ocean. Major improvements to the earlier study are the isolation of DC systems in time so as to prevent multiple sampling of the same event, and a revised definition of the mean background state that allows for better characterisation of the DC-system-induced anomalies. The observed DC systems in this study propagate westward at ~4 m s−1. Both the upper-tropospheric relative humidity and the outgoing longwave radiation are substantially perturbed over a broad horizontal extent and for periods >30 h. The cloud fraction anomaly is fairly constant with height but small maximum can be seen around 200 hPa. The cloud ice water content anomaly is mostly confined to pressures greater than 150 hPa and reaches its maximum around 450 hPa, a few hours after the peak convection. Consistent with the large increase in upper-tropospheric cloud ice water content, albedo increases dramatically and persists about 30 h after peak convection. Applying the compositing technique to EC-Earth allows an assessment of the model representation of DC systems. The model captures the large-scale responses, most notably for outgoing longwave radiation, but there are a number of important differences. DC systems appear to propagate eastward in the model, suggesting a strong link to Kelvin waves instead of equatorial Rossby waves. The diurnal cycle in the model is more pronounced and appears to trigger new convection further to the west each time. Finally, the modelled ice water content anomaly peaks at pressures greater than 500 hPa and in the upper troposphere between 250 hPa and 500 hPa, there is less ice than the observations and it does not persist as long after peak convection. The modelled upper-tropospheric cloud fraction anomaly, however, is of a comparable magnitude and exhibits a similar longevity as the observations.


2015 ◽  
Vol 54 (10) ◽  
pp. 2087-2097 ◽  
Author(s):  
Sujan Khanal ◽  
Zhien Wang

AbstractRemote sensing and in situ measurements made during the Colorado Airborne Multiphase Cloud Study, 2010–2011 (CAMPS) with instruments aboard the University of Wyoming King Air aircraft are used to evaluate lidar–radar-retrieved cloud ice water content (IWC). The collocated remote sensing and in situ measurements provide a unique dataset for evaluation studies. Near-flight-level IWC retrieval is compared with an in situ probe: the Colorado closed-path tunable diode laser hygrometer (CLH). Statistical analysis showed that the mean radar–lidar IWC is within 26% of the mean in situ measurements for pure ice clouds and within 9% for liquid-topped mixed-phase clouds. Considering their different measurement techniques and different sample volumes, the comparison shows a statistically good agreement and is close to the measurement uncertainty of the CLH, which is around 20%. It is shown that ice cloud microphysics including ice crystal shape and orientation has a significant impact on IWC retrievals. These results indicate that the vertical profile of the retrieved lidar–radar IWC can be reliably combined with the flight-level measurements made by the in situ probes to provide a more complete picture of the cloud microphysics.


Author(s):  
Allyson Rugg ◽  
Julie Haggerty ◽  
Alain Protat

AbstractHigh ice water content (HIWC; defined herein as at least 1.0 g m−3) conditions are often found in the anvils of convective systems and can cause engine damage and/or failure in aircraft. We use ice water content (IWC) retrievals from satellite-borne radar and lidar (CloudSat and CALIOP) to provide the first analysis of global HIWC frequency using 11 years of data (2007 to 2017). Results show HIWC is generally present in 1 to 2% of CloudSat and CALIOP IWC retrievals between flight levels 270 (27,000 ft or 8.230 km) and 420 (FL420; 42,000 ft or 12.801 km) in areas with frequent convection. Similar rates of HIWC are found over midlatitude oceans at relatively low altitudes (below FL270). Possible non-convective mechanisms for the formation of this low-level HIWC are discussed, as are the uncertainties suggesting the results at these low altitudes are an overestimation of the true threat of HIWC to aircraft engines. The satellite IWC retrievals are also used to validate a HIWC diagnostic tool which provides storm-scale statistics on HIWC over the Contiguous United States (CONUS) during the summer convective season (May through August, 2012 to 2019). Results over the CONUS suggest HIWC over the Great Plains is highest in June, when a point in the region is under HIWC conditions about 25 hours out of 30 days on average. The mean area-equivalent diameters of HIWC conditions in some areas of the Great Plains exceeds 350 km and the conditions can persist for 4 to 5 hours.


2007 ◽  
Vol 112 (D10) ◽  
Author(s):  
Sean M. Davis ◽  
Linnea M. Avallone ◽  
Elliot M. Weinstock ◽  
Cynthia H. Twohy ◽  
Jessica B. Smith ◽  
...  

2015 ◽  
Vol 8 (1) ◽  
pp. 211-224 ◽  
Author(s):  
T. D. Thornberry ◽  
A. W. Rollins ◽  
R. S. Gao ◽  
L. A. Watts ◽  
S. J. Ciciora ◽  
...  

Abstract. The recently developed NOAA Water instrument is a two-channel, closed-path, tunable diode laser absorption spectrometer designed for the measurement of upper troposphere/lower stratosphere water vapor and enhanced total water (vapor + inertially enhanced condensed phase) from the NASA Global Hawk unmanned aircraft system (UAS) or other high-altitude research aircraft. The instrument utilizes wavelength-modulated spectroscopy with second harmonic detection near 2694 nm to achieve high precision with a 79 cm double-pass optical path. The detection cells are operated under constant temperature, pressure, and flow conditions to maintain a constant sensitivity to H2O independent of the ambient sampling environment. An onboard calibration system is used to perform periodic in situ calibrations to verify the stability of the instrument sensitivity during flight. For the water vapor channel, ambient air is sampled perpendicular to the flow past the aircraft in order to reject cloud particles, while the total water channel uses a heated, forward-facing inlet to sample both water vapor and cloud particles. The total water inlet operates subisokinetically, thereby inertially enhancing cloud particle number in the sample flow and affording increased cloud water content sensitivity. The NOAA Water instrument was flown for the first time during the second deployment of the Airborne Tropical TRopopause EXperiment (ATTREX) in February–March 2013 on the NASA Global Hawk UAS. The instrument demonstrated a typical in-flight precision (1 s, 1σ) of better than 0.17 parts per million (ppm, 10−6 mol mol−1), with an overall H2O vapor measurement uncertainty of 5% ± 0.23 ppm. The inertial enhancement for cirrus cloud particle sampling under ATTREX flight conditions ranged from 33 to 48 for ice particles larger than 8 μm in diameter, depending primarily on aircraft altitude. The resulting ice water content detection limit (2σ) was 0.023–0.013 ppm, corresponding to approximately 2 μg m−3, with an estimated overall uncertainty of 20%.


2018 ◽  
Vol 11 (7) ◽  
pp. 4015-4031 ◽  
Author(s):  
Armin Afchine ◽  
Christian Rolf ◽  
Anja Costa ◽  
Nicole Spelten ◽  
Martin Riese ◽  
...  

Abstract. The ice water content (IWC) of cirrus clouds is an essential parameter determining their radiative properties and thus is important for climate simulations. Therefore, for a reliable measurement of IWC on board research aircraft, it is important to carefully design the ice crystal sampling and measuring devices. During the ML-CIRRUS field campaign in 2014 with the German Gulfstream GV HALO (High Altitude and Long Range Research Aircraft), IWC was recorded by three closed-path total water together with one gas-phase water instrument. The hygrometers were supplied by inlets mounted on the roof of the aircraft fuselage. Simultaneously, the IWC is determined by a cloud particle spectrometer attached under an aircraft wing. Two more examples of simultaneous IWC measurements by hygrometers and cloud spectrometers are presented, but the inlets of the hygrometers were mounted at the fuselage side (M-55 Geophysica, StratoClim campaign 2017) and bottom (NASA WB57, MacPex campaign 2011). This combination of instruments and inlet positions provides the opportunity to experimentally study the influence of the ice particle sampling position on the IWC with the approach of comparative measurements. As expected from theory and shown by computational fluid dynamics (CFD) calculations, we found that the IWCs provided by the roof inlets deviate from those measured under the aircraft wing. As a result of the inlet position in the shadow zone behind the aircraft cockpit, ice particle populations with mean mass sizes larger than about 25 µm radius are subject to losses, which lead to strongly underestimated IWCs. On the other hand, cloud populations with mean mass sizes smaller than about 12 µm are dominated by particle enrichment and thus overestimated IWCs. In the range of mean mass sizes between 12 and 25 µm, both enrichment and losses of ice crystals can occur, depending on whether the ice crystal mass peak of the size distribution – in these cases bimodal – is on the smaller or larger mass mode. The resulting deviations of the IWC reach factors of up to 10 or even more for losses as well as for enrichment. Since the mean mass size of ice crystals increases with temperature, losses are more pronounced at higher temperatures, while at lower temperatures IWC is more affected by enrichment. In contrast, in the cases where the hygrometer inlets were mounted at the fuselage side or bottom, the agreement of IWCs is most frequently within a factor of 2.5 or better – due to less disturbed ice particle sampling, as expected from theory – independently of the mean ice crystal sizes. The rather large scatter between IWC measurements reflects, for example, cirrus cloud inhomogeneities and instrument uncertainties as well as slight sampling biases which might also occur on the side or bottom of the fuselage and under the wing. However, this scatter is in the range of other studies and represent the current best possible IWC recording on fast-flying aircraft.


2011 ◽  
Vol 50 (9) ◽  
pp. 1952-1969 ◽  
Author(s):  
Thorwald H. M. Stein ◽  
Julien Delanoë ◽  
Robin J. Hogan

AbstractThe A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.


2014 ◽  
Vol 7 (8) ◽  
pp. 8271-8309 ◽  
Author(s):  
T. D. Thornberry ◽  
A. W. Rollins ◽  
R. S. Gao ◽  
L. A. Watts ◽  
S. J. Ciciora ◽  
...  

Abstract. The recently developed NOAA Water instrument is a two-channel, closed-path, tunable diode laser absorption spectrometer designed for the measurement of water vapor and enhanced total water (vapor + inertially enhanced condensed-phase) in the upper troposphere/lower stratosphere from the NASA Global Hawk unmanned aircraft system (UAS) or other high-altitude research aircraft. The instrument utilizes wavelength-modulated spectroscopy with second harmonic detection near 2694 nm to achieve high precision with a 79 cm double-pass optical path. The detection cells are operated under constant temperature, pressure and flow conditions to maintain a constant sensitivity to H2O independent of the ambient sampling environment. An on-board calibration system is used to perform periodic in situ calibrations to verify the stability of the instrument sensitivity during flight. For the water vapor channel, ambient air is sampled perpendicular to the flow past the aircraft in order to reject cloud particles, while the total water channel uses a heated, forward-facing inlet to sample both water vapor and cloud particles. The total water inlet operates subisokinetically, thereby inertially enhancing cloud particle number in the sample flow and affording increased cloud water content sensitivity. The NOAA Water instrument was flown for the first time during the second deployment of the Airborne Tropical TRopopause EXperiment (ATTREX) in February–March 2013 on board the Global Hawk UAS. The instrument demonstrated a typical in-flight precision (1 s, 1σ) of better than 0.17 parts per million (ppm, 10−6 mol mol−1), with an overall H2O vapor measurement uncertainty of 5% ± 0.23 ppm. The inertial enhancement for cirrus cloud particle sampling under ATTREX flight conditions ranged from 33–48 for ice particles larger than 8 μm in diameter, depending primarily on aircraft altitude. The resulting ice water content detection limit (2σ) was 0.023–0.013 ppm, corresponding to approximately 2 μg m−3, with an estimated overall uncertainty of 20%.


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