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During FIRE, three major stratocumulus clearing events took place over the project region. These clearing events are analyzed using synoptic variables to determine if these clearing events can be predicted by current modeling techniques. A preliminary statistical evaluation of the correlation between satellite cloud brightness parameters and NMC global model parameters is available in Wylie, et al., 1989.
Several NCAR King Air flight missions were conducted during the Wisconsin FIRE IFO experiment in support of the University of Utah polarization lidar observations of deep cirrus cloud systems at the Wausau ground site. Data collected from four cirrus systems are included in this analysis, including those of 22 and 28 October, and 1 and 2 November. Lidar data were generally obtained at 2 min intervals in the zenith direction over observation periods that ranged from approximately 4 to 10 h, bracketing the aircraft missions. The data were processed to yield height-time (HTI) displays of lidar linear depolarization ratio sigma and relative range-normalized return power P. King Air operations consisted of a combination of rapid profiling and Lagrangian spiral descents and stacked racetrack patterns in the vicinity of the field site. From the spiral descents are constructed vertical profiles of ice particle concentration N(sub i) and ice mass content IWC derived from PMS 2-D probe imagery and, when detected, FSSP cloud droplet concentration N(sub W) and liquid water content, LWC. Aircraft flight leg data are presented for the vertical velocity W and the same ice and water cloud content parameters. In addition, aerosol particle concentrations obtained with the ASAS probe are examined, and photographs of ice particles collected in-situ on oil-coated slides are presented to illustrate ice particle habit.
The author summarizes and links together a number of papers that were presented at the Propulsion and Energetics (PEP) symposium on low temperature environment operation of turbojet engines that was held October 8 to 12, 1990. Topics covered include operational experience of ice ingestion in the turboprop engine in the 2,000 hp class, icing on helicopter turbo engines, icing test facilities, ice relevant cloud physical parameters, and low temperature and fuel problems.
The problem of electromagnetic scattering of an incident plane wave by an arbitrary configuration of obstacles was solved by Twersky. In this report, the results are extended to point source incidence corresponding to a Hertz dipole. Knowledge of the response of a fixed configuration of scatterers excited by a point source may provide insight to improve the accuracy of the values of bulk parameters for clouds which have been found using plane wave excitation.
An airborne field mill (ABFM) system was implemented on a Learjet 36A and was used to collect electric-field and microphysical data for summertime convective clouds near Cape Canaveral and the Kennedy Space Center. This system is described and the method used for calibrating it is outlined. Data from this ABFM system were used to investigate the relationship between the strengths of electric fields at the boundaries of summer maritime convective clouds and the distances from these cloud where the fields could first be detected by this system. The relationship between the electric-field strengths at the boundaries of convective clouds and selected radar-measurable parameters of these clouds were also investigated. This study shows promise that the radar volume of these clouds can be used to estimate the order of magnitude electric-field intensity. It is possible that selected remote radar measurements could be incorporated into the launch commit criteria as a means of providing greater confidence and flexibility for determining safe stand-off distances for launch vehicles from convective clouds.
The lightning frequency model developed by Baker, Christian and Latham (1995) has been refined and extended, in an effort to provide a more realistic framework from which to examine computationally the relationships that might exist between lightning frequency f (which is now being routinely measured from satellites, using NASA/MSFC devices) and a variety of cloud physical parameters, including precipitation rate, updraught speed and non-precipitating ice content. The charging mechanism incorporated into the model is the non-inductive ice-ice mechanism - involving rebounding collisions between ice crystals and growing graupel pellets - which has achieved significant field, laboratory and modelling support in recent years. Model results indicate the existence of a simple relationship between lightning frequency f and the upward flux of ice crystals into the thunderstorm anvil. It follows that, for a particular situation, one can assign a specific mass of non-precipitating ice to an individual lightning stroke. Therefore it is possible - using satellite measurements of global lightning - to estimate the atmospheric loading of ice crystals in thunderstorm anvils: a parameter of climatological importance. One can also estimate the ice crystal loading associated with more localized storm systems. Early results from this work will be presented, together with further work on the relationships between f and other thundercloud parameters.
The lightning frequency model developed by Baker, Christian and Latham (1995) has been refined and extended, in an effort to provide a more realistic framework from which to examine computationally the relationships that might exist between lightning frequency f (which is now being routinely measured from satellites, using NASA/MSFC devices) and a variety of cloud physical parameters, including precipitation rate, updraught speed and non-precipitating ice content. Model results indicate the existence of a simple relationship between lightning frequency f and the upward flux of ice crystals into the thunderstorm anvil. It follows that, for a particular situation, one can assign a specific mass of non-precipitating ice to an individual lightning stroke. Therefore it may prove possible - using satellite measurements of global lightning - to estimate the atmospheric loading of ice crystals in thunderstorm anvils: a parameter of climatological importance. Early results from this work are presented, together with further studies of the relationships between f and other thundercloud parameters.
An improved version of the Convective/Stratiform Technique (CST) and its application over Brazil are presented. Keeping the major components of traditional CST, we have modified the scheme for classing convective and stratiform rainfall and tested various schemes to eliminate non-raining cirrus clouds. The parameters of the technique are calibrated using Tropical Rainfall Measuring Mission (TRMM) multi-sensor observations, including TMI, PR and Visible Infrared Scanner (VIRS). This technique takes advantage of the high temporal sampling rate of geosynchronous infrared channel and the better instantaneous rain observation of TRMM Microwave Imager (TMI) and PR. Moreover, sparse TMI rain estimates are used to dynamically calibrate the parameters of the technique to improve its performance. The technique is applied to make rainfall estimates on various time scales and to study rainfall statistics such as the distributions of rain intensity and storm duration over a four-month period beginning January 1999. The study period coincides with the TRMM/Large-Scale Biosphere-Atmosphere experiment in Amazonia (LBA) ground validation experiment, and observations from the LBA radar are used to validate the technique. Results show the mean diurnal cycle of precipitation over the LBA area, and are compared to radar data from the Tropical Oceans and Global Atmosphere (TOGA) radar. When the larger geographic region is considered, the analysis of the mean hourly estimates revealed the pronounced effects of rivers, topography and local circulations on the rainfall.
Although dry/moist potential vorticity is a useful physical quantity for meteorological analysis, it cannot be applied to the analysis of 2D simulations. A convective vorticity vector (CVV) is introduced in this study to analyze 2D cloud-resolving simulation data associated with 2D tropical convection. The cloud model is forced by the vertical velocity, zonal wind, horizontal advection, and sea surface temperature obtained from the TOGA COARE, and is integrated for a selected 10-day period. The CVV has zonal and vertical components in the 2D x-z frame. Analysis of zonally-averaged and mass-integrated quantities shows that the correlation coefficient between the vertical component of the CVV and the sum of the cloud hydrometeor mixing ratios is 0.81, whereas the correlation coefficient between the zonal component and the sum of the mixing ratios is only 0.18. This indicates that the vertical component of the CVV is closely associated with tropical convection. The tendency equation for the vertical component of the CVV is derived and the zonally-averaged and mass-integrated tendency budgets are analyzed. The tendency of the vertical component of the CVV is determined by the interaction between the vorticity and the zonal gradient of cloud heating. The results demonstrate that the vertical component of the CVV is a cloud-linked parameter and can be used to study tropical convection.
The Atmospheric Infrared Sounder (AIRS) is a facility instrument onboard EOS Aqua. Major level 2 products are highlighted including temperature profile; water vapor profile; surface skin temperature and other surface parameters; and, cloud friction and top cloud pressure. Level 2 files and data availability are discussed.
AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best on the average from the perspective of improving Global 7 day forecast skill.
Investigation of coupling mechanisms between the troposphere and the ionosphere requires a multidisciplinary approach involving several branches of atmospheric sciences, from meteorology, atmospheric chemistry, and fulminology to aeronomy, plasma physics, and space weather. In this work, we review low frequency electromagnetic wave propagation in the Earth-ionosphere cavity from a troposphere-ionosphere coupling perspective. We discuss electromagnetic wave generation, propagation, and resonance phenomena, considering atmospheric, ionospheric and magnetospheric sources, from lightning and transient luminous events at low altitude to Alfven waves and particle precipitation related to solar and magnetospheric processes. We review in situ ionospheric processes as well as surface and space weather phenomena that drive troposphere-ionosphere dynamics. Effects of aerosols, water vapor distribution, thermodynamic parameters, and cloud charge separation and electrification processes on atmospheric electricity and electromagnetic waves are reviewed. We also briefly revisit ionospheric irregularities such as spread-F and explosive spread-F, sporadic-E, traveling ionospheric disturbances, Trimpi effect, and hiss and plasma turbulence. Regarding the role of the lower boundary of the cavity, we review transient surface phenomena, including seismic activity, earthquakes, volcanic processes and dust electrification. The role of surface and atmospheric gravity waves in ionospheric dynamics is also briefly addressed. We summarize analytical and numerical tools and techniques to model low frequency electromagnetic wave propagation and solving inverse problems and summarize in a final section a few challenging subjects that are important for a better understanding of tropospheric-ionospheric coupling mechanisms.
The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.
Nebular and central star parameters and elemental abundances of C, N, O, Ne, S, and Ar are presented for the planetary nebulae N2, N5, N43, N54, and N67 in the SMC and P2, P7, P9, P25, P33, and P40 in the LMC. The nebular chemical compositions are affected by nuclear processes in the precursor stars, which may not have been sufficiently massive to synthesize Ne, S, or Ar, which appear to be deficient with respect to their solar abundances by factors of roughly four and five for the LMC and SMC, respectively. Even after excluding nebulae formed by stars in which O apparently was destroyed by nuclear processes, O depletion in the LMC and SMC nebulae is significantly greater than in galactic planetaries. The estimated masses of the 12 remnant central stars range from 0.58 to 0.71 solar mass.
Techniques for measuring the local and global parameters that describe molecular clouds are presented and illustrated by selected results. The local parameters which characterize a given location in a cloud are gas kinetic temperature, dust temperature, total density, magnetic field strength, abundance of species i, volume cooling and heating rates for gas and dust, and the thermal and turbulent velocities. Global properties which characterize the cloud as a whole include the size expressed as a length or area, the orientation and shape, the mass, and the integrated heating and cooling rates. If the cloud as a whole is collapsing or rotating, then the collapse velocity and the rotational velocity or angular momentum are global properties. An intermediate class of parameters which shares features of local and global properties includes the column density of species i, the total column density, and the average density.
Cloud height and cloud coverage detection are important for total ozone retrieval using ultraviolet and visible scattered light. Use of the O2 A and B bands, around 761 and 687 nm, by a satellite-borne instrument of moderately high spectral resolution viewing in the nadir makes it possible to detect cloud top height and related parameters, including fractional coverage. The measured values of a satellite-borne spectrometer are convolutions of the instrument slit function and the atmospheric transmittance between cloud top and satellite. Studies here determine the optical depth between a satellite orbit and the Earth or cloud top height to high accuracy using FASCODE 3. Cloud top height and a cloud coverage parameter are determined by least squares fitting to calculated radiance ratios in the oxygen bands. A grid search method is used to search the parameter space of cloud top height and the coverage parameter to minimize an appropriate sum of squares of deviations. For this search, nonlinearity of the atmospheric transmittance (i.e., leverage based on varying amounts of saturation in the absorption spectrum) is important for distinguishing between cloud top height and fractional coverage. Using the above-mentioned method, an operational cloud detection algorithm which uses minimal computation time can be implemented.
A procedure for the retrieval of cloud vertical structure from passive microwave radiometry is demonstrated by using passive microwave radiometry observations made during the Tropical Rainfall Measuring Mission. The procedure uses a set of cloud radiative models, with each model consisting of five vertical layers, specifying a distinct cloud vertical structure in terms of the near-surface parameters. The retrieval procedure is separated into two tasks (1) retrieving a set of geophysical parameters for each cloud radiative model and (2) finding which of the cloud radiative models and its associated retrieved parameters best fit the observed geophysical conditions. It is shown that this retrieval technique can detect differences and similarities between precipitating systems.
Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.