Estimates Of Ice Water Content Research Articles

WIVERN: A New Satellite Concept to Provide Global In-Cloud Winds, Precipitation, and Cloud Properties

AbstractThis paper presents a conically scanning spaceborne Dopplerized 94-GHz radar Earth science mission concept: Wind Velocity Radar Nephoscope (WIVERN). WIVERN aims to provide global measurements of in-cloud winds using the Doppler-shifted radar returns from hydrometeors. The conically scanning radar could provide wind data with daily revisits poleward of 50°, 50-km horizontal resolution, and approximately 1-km vertical resolution. The measured winds, when assimilated into weather forecasts and provided they are representative of the larger-scale mean flow, should lead to further improvements in the accuracy and effectiveness of forecasts of severe weather and better focusing of activities to limit damage and loss of life. It should also be possible to characterize the more variable winds associated with local convection. Polarization diversity would be used to enable high wind speeds to be unambiguously observed; analysis indicates that artifacts associated with polarization diversity are rare and can be identified. Winds should be measurable down to 1 km above the ocean surface and 2 km over land. The potential impact of the WIVERN winds on reducing forecast errors is estimated by comparison with the known positive impact of cloud motion and aircraft winds. The main thrust of WIVERN is observing in-cloud winds, but WIVERN should also provide global estimates of ice water content, cloud cover, and vertical distribution, continuing the data series started by CloudSat with the conical scan giving increased coverage. As with CloudSat, estimates of rainfall and snowfall rates should be possible. These nonwind products may also have a positive impact when assimilated into weather forecasts.

Using in situ estimates of ice water content, volume extinction coefficient, and the total solar optical depth obtained during the tropical ACTIVE campaign to test an ensemble model of cirrus ice crystals

AbstractAn ensemble model of cirrus ice crystals combined with a parametrized particle size distribution function (PSD) is used to predict the ice water content (IWC), column‐integrated IWC (ice water path, IWP), volume extinction coefficient, and the total solar optical depth, for five tropical cirrus cases. The PSD is estimated from the IWC and in‐cloud temperature, and comparisons are presented between the ensemble model predictions and in situ estimates of these microphysical and macrophysical quantities. The in situ estimates were obtained during the Aerosol and Chemical Transport In tropical conVection (ACTIVE) campaign between November–December 2005 and January–February 2006, based at Darwin, Australia. The microphysical instrumentation deployed on the Airborne Australia Egrett research aircraft were the SPEC Cloud Particle Imaging (CPI) probe, Cloud and Aerosol Spectrometer (CAS) and Cloud Imaging Probe (CIP). The CPI was used to measure ice crystal size from about 5 to 1800 μm, ice crystal number concentration, and to estimate ice crystal shape, IWC, IWP, volume extinction coefficient and the total solar optical depth. The CIP instrument was also used to measure ice crystal size from about 25 to 1550 μm, ice crystal number concentration and to estimate IWC. For all flights the limited CPI shape recognition algorithm recorded that about 80% or greater of the ice crystal populations were composed of small irregular or ‘quasi‐spherical’ ice crystals. The CPI‐ and CIP‐estimated IWC distributions are compared against each other and it is shown that the distributions are not significantly different at the 95% level of confidence. The CPI‐estimated averaged IWC ranged between approximately 5.3 and 98.2 mg m−3. The CPI‐estimated IWP and total solar optical depth ranged between ∼1.0 ± 0.5 and 35.0 ± 17 g m−2 and between 0.1 ± 0.05 and 1.46 ± 0.73, respectively.To predict the IWC and IWP, an ensemble model effective density‐size relationship is derived, and it is shown that the uncertainty in the model predictions are generally within the uncertainty of the CPI estimates for all cases considered. It is also demonstrated that, when the CPI‐estimated total solar optical depth is greater than unity, the ensemble model combined with the PSD scheme predicts an uncertainty in the volume extinction coefficient and total solar optical depth that is within the CPI experimental range of uncertainty. However, for total solar optical depths much less than unity, the ensemble model combined with the PSD scheme does not generally predict an uncertainty in the volume extinction coefficient and total solar optical depth that is within the lower range of the CPI uncertainty; the physical reason for this is further explored.The paper demonstrates that there is predictive value in combining an ensemble model of ice crystals with a universal PSD scheme to predict the microphysical and macrophysical properties of importance to radiative transfer through tropical cirrus. Moreover, in the case of very low IWC tropical cirrus, further characterization of the PSD is required using a number of in situ instruments. Copyright © Royal Meteorological Society and Crown Copyright, 2011

Testing an ensemble model of cirrus ice crystals using midlatitude in situ estimates of ice water content, volume extinction coefficient and the total solar optical depth

In this paper an ensemble model of cirrus ice crystals is tested against midlatitude in situ estimates of ice water content, volume extinction coefficient and the total solar optical depth. During the Winter of 2005 and Spring 2006 the FAAM (Facility for Airborne Atmospheric Measurements) BAE-146 G-LUXE aircraft flew three flights as part of the CAESAR (Cirrus and Anvils: European Satellite and Airborne Radiation measurements project) campaign of flying in cirrus around the UK. The suite of microphysical instrumentation onboard the aircraft included the PMS 2D-C probe and the Stratton Park Engineering Company (SPEC) cloud particle imager (CPI). The campaign characterized cirrus properties such as ice water content, volume extinction coefficient, ice crystal geometric shape and ice crystal effective dimension. Cirrus cloud temperatures ranged approximately between 215 and 240 K. From the CPI instrument 60–80% of the ice crystal habits were estimated to be either indeterminate or ‘irregular’ (though such irregular crystals could be composed of pristine components) of some form with hexagonal columns and hexagonal plates accounting for generally much less than 3% of the ice crystal population. The CPI estimated integrated ice water content ranged between 5±2 and 45±22 gm −2, whilst the CPI estimate of the total solar optical depth was found to lie between 0.2±0.1 and 1.0±0.5. The CPI estimate of the mean ice crystal effective dimension was found to range between about 59±9 and 90±75 μm. The particle size distribution (PSD) function was estimated using a PSD scheme that requires as input the in situ estimated IWC and measured in-cloud temperature. The CPI estimates of the bulk and microphysical properties of the midlatitude cirrus are used to test whether an ensemble model of cirrus ice crystals together with a PSD scheme can predict CPI in situ estimates to within the experimental uncertainty. This paper demonstrates that the ensemble model coupled with a PSD scheme can predict the ice water content and the integrated ice water content to generally well within the experimental uncertainty if a varying density with respect to size is assumed. The ensemble model together with a PSD scheme is also shown to predict the CPI estimated volume extinction coefficient and the derived total solar optical depth to generally well within the experimental uncertainty. The paper demonstrates that an ensemble model of cirrus combined with a PSD scheme can predict the radiative properties of cirrus without the need to invoke the concept of an ice crystal effective dimension.

Snow Size Distribution Parameterization for Midlatitude and Tropical Ice Clouds

Abstract Many microphysical process rates involving snow are proportional to moments of the snow particle size distribution (PSD), and in this study a moment estimation parameterization applicable to both midlatitude and tropical ice clouds is proposed. To this end aircraft snow PSD data were analyzed from tropical anvils [Tropical Rainfall Measuring Mission/Kwajelein Experiment (TRMM/KWAJEX), Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE)] and midlatitude stratiform cloud [First International Satellite Cloud Climatology Project Research Experiment (FIRE), Atmospheric Radiation Measurement Program (ARM)]. For half of the dataset, moments of the PSDs are computed and a parameterization is generated for estimating other PSD moments when the second moment (proportional to the ice water content when particle mass is proportional to size squared) and temperature are known. Subsequently the parameterization was tested with the other half of the dataset to facilitate an independent comparison. The parameterization for estimating moments can be applied to midlatitude or tropical clouds without requiring prior knowledge of the regime of interest. Rescaling of the tropical and midlatitude size distributions is presented along with fits to allow the user to recreate realistic PSDs given estimates of ice water content and temperature. The effects of using different time averaging were investigated and were found not to be adverse. Finally, the merits of a single-moment snow microphysics versus multimoment representations are discussed, and speculation on the physical differences between the rescaled size distributions from the Tropics and midlatitudes is presented.

The Role of Spaceborne Millimeter-Wave Radar in the Global Monitoring of Ice Cloud

The purpose of this paper is to assess the potential of a spaceborne 94-GHz radar for providing useful measurements of the vertical distribution and water content of ice clouds on a global scale. Calculations of longwave (LW) fluxes for a number of model ice clouds are performed. These are used to determine the minimum cloud optical depth that will cause changes in the outgoing longwave radiation or flux divergence within a cloud layer greater than 10 W m −2 , and in surface downward LW flux greater than 5 W m −2 , compared to the clear-sky value. These optical depth values are used as the definition of a radiatively significant cloud. Different thresholds of radiative significance are calculated for each of the three radiation parameters and also for tropical and midlatitude cirrus clouds. Extensive observational datasets of ice crystal size spectra from midlatitude and tropical cirrus are then used to assess the capability of a radar to meet these measurement requirements. A radar with a threshold of −30 dBZ should detect 99% (92%) of radiatively significant clouds in the midlatitudes (Tropics). This detection efficiency may be reduced significantly for tropical clouds at very low temperatures (−80°C). The LW flux calculations are also used to establish the required accuracy within which the optical depth should be known in order to estimate LW fluxes or flux divergence to within specified limits of accuracy. Accuracy requirements are also expressed in terms of ice water content (IWC) because of the need to validate cloud parameterization schemes in general circulation models (GCMs). Estimates of IWC derived using radar alone and also using additional information to define the mean crystal size are considered. With crystal size information available, the IWC for samples with a horizontal scale of 1-2 km may be obtained with a bias of less than 8%. For IWC larger than 0.01 g m −3 , the random error is in the range +50% to −35%, whereas for a value of 0.001 g m −3 the random error increases to between +80% and −45%. This level of accuracy also represents the best that may be achieved for estimates of the cloud optical depth and meets the requirements derived from LW flux calculations. In the absence of independent particle size information, the random error is within the range +85% to −55% for IWC greater than 0.01 g m −3 . For the same IWC range, the estimated bias is less than ±15%. This accuracy is sufficient to provide useful constraints on GCM cloud parameterization schemes.