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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Infrared Radiative Forcing and Atmospheric Lifetimes of Trace Species Based on Observations from UARS

Observations from instruments on the Upper Atmosphere Research Satellite (UARS) have been used to constrain calculations of infrared radiative forcing by CH4, CCl2F2 and N2O, and to determine lifetimes Of CCl2F2 and N2O- Radiative forcing is calculated as a change in net infrared flux at the tropopause that results from an increase in trace gas amount from pre-industrial (1750) to contemporary (1992) times. Latitudinal and seasonal variations are considered explicitly, using distributions of trace gases and temperature in the stratosphere from UARS measurements and seasonally averaged cloud statistics from the International Satellite Cloud Climatology Project. Top-of-atmosphere fluxes calculated for the contemporary period are in good agreement with satellite measurements from the Earth Radiation Budget Experiment. Globally averaged values of the radiative forcing are 0.536, 0.125, and 0.108 W m-2 for CH4, CCl2F2, and N2O, respectively. The largest forcing occurs near subtropical latitudes during summer, predominantly as a result of the combination of cloud-free skies and a high, cold tropopause. Clouds are found to play a significant role in regulating infrared forcing, reducing the magnitude of the forcing by 30-40% compared to the case of clear skies. The vertical profile of CCl2F2 is important in determining its radiative forcing; use of a height-independent mixing ratio in the stratosphere leads to an over prediction of the forcing by 10%. The impact of stratospheric profiles on radiative forcing by CH4 and N2O is less than 2%. UARS-based distributions of CCl2F2 and N2O are used also to determine global destruction rates and instantaneous lifetimes of these gases. Rates of photolytic destruction in the stratosphere are calculated using solar ultraviolet irradiances measured on UARS and a line-by-line model of absorption in the oxygen Schumann-Runge bands. Lifetimes are 114 +/- 22 and 118 +/- 25 years for CCl2F2 and N2O, respectively.

Minschwaner, K.↗
NASA NTRS1993

The 5-6 December 1991 FIRE IFO 2 jet stream cirrus case study: The influence of volcanic aerosols

In presenting an overview of the cirrus clouds comprehensively studied by ground-based and airborne sensors from Coffeyville, KS, during the 5-6 Dec. 1992 Project FIRE (First International Satellite Cloud Climatology Project Regional Experiment) IFO II case study period, evidence is provided that volcanic aerosols from the June 1991 Pinatubo eruptions significantly influenced the formation and maintenance of the cirrus. Following the local appearance of a spur of stratospheric volcanic debris from the subtropics, a series of jet streaks subsequently conditioned the troposphere through tropopause foldings with sulfur-based particles that became effective cirrus cloud-forming nuclei. Aerosol and ozone measurements suggest a complicated history of stratospheric-tropospheric exchanges embedded within the upper level flow, and cirrus cloud formation was noted to occur locally at the boundaries of stratospheric aerosol-enriched layers that became humidified through diffusion, precipitation, or advective processes. Apparent cirrus cloud alterations include abnormally high ice crystal concentrations (up to approximately 600 l(sup -1), small but complex radial ice crystal types, and relatively large haze particles in cirrus uncinus cell heads at temperatures between -40 to -50 C. Implications for volcanic-cirrus cloud climate effects, and usual (non-volcanic aerosol) jet stream cirrus cloud formation are discussed.

Sassen, Kenneth↗
NASA NTRS1993

Cloud fields derived from satellite and surface data during FIRE cirrus phase 2

The interpretation of surface and aircraft measurements of cloud properties taken during field programs must take into account the large-scale cloud and meteorological conditions. Cloud properties are also required at scales beyond the point and line data taken from ground and aircraft platforms. Satellite data can provide a quantitative description of these large-scale cloud properties. When derived from geostationary satellite data, the cloud fields constitute a unique source for evaluating the development and demise of a cloud system. Satellites, however, can only see the tops of clouds, so that cloud layers below the uppermost cloud deck may remain undetected resulting in a incomplete depiction of the cloud system. Some multilayer clouds are amenable to detection from satellites. Many, especially in midlatitude cyclonic systems, can only be observed from the surface. A combination of surface and satellite cloud observations should be the most complete quantification of large-scale cloudiness if there are sufficient surface measurements. During the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Phase 2 (FIRE-2) Cirrus Intensive Field Observation (IFO) period (November 13 - December 7, 1991) conducted at Coffeyville, Kansas, cirrus observations were taken in a variety of conditions. The IFO area was selected for a variety of reasons including the relatively dense network of surface weather stations and special surface instrumentation sites. Thus, the FIRE-2 IFO presents an excellent opportunity to combine cloud observations from surface and satellite observations. This paper presents an analysis of cloud properties on a mesoscale grid using satellite cloud property retrievals, surface observer data, and rawinsonde temperature and humidity profiles.

Minnis, Patrick↗
NASA NTRS2000

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Aires, F.↗
NASA NTRS1990

Stratocumulus cloud height variations determined from surface and satellite observations

Determination of cloud-top heights from satellite-inferred cloud-top temperatures is a relatively straightforward procedure for a well-behaved troposphere. The assumption of a monotonically decreasing temperature with increasing altitude is commonly used to assign a height to a given cloud-top temperature. In the hybrid bispectral threshold method, or HBTM, Minnis et al. (1987) assume that the lapse rate for the troposphere is -6.5/Kkm and that the surface temperature which calibrated this lapse rate is the 24 hour mean of the observed or modeled clear-sky, equivalent blackbody temperature. The International Satellite Cloud Climatology Project (ISCCP) algorithm (Rossow et al., 1988) attempts a more realistic assignment of height by utilizing interpolations of analyzed temperature fields from the National Meteorological Center (NMC) to determine the temperature at a given level over the region of interest. Neither these nor other techniques have been tested to any useful extent. The First ISCCP Regional Experiment (FIRE) Intensive Field Observations (IFO) provide an excellent opportunity to assess satellite-derived cloud height results because of the availability of both direct and indirect cloud-top altitude data of known accuracy. The variations of cloud-top altitude during the Marine Stratocumulus IFO (MSIFO, June 29 to July 19, 1987) derived from surface, aircraft, and satellite data are examined.

Minnis, Patrick↗
NASA NTRS1986

Planning for the utilization of the PCDS in studying the interaction of clouds (ISCCP-C data) and the Earth radiation budget (ERBE data)

The Pilot Climate Data System (PCDS) affords an opportunity to analyze data from different but highly complementary data sets. Two of these highly complementary data sets supported by the PCDS are the International Satellite Cloud Climatology Project (ISCCP) and the Earth Radiation Budget Experiment (ERBE). Both data set sponsors are aware of the utility of one data set to the other, and both projects utilize gridded data on a 2.5 deg by 2.5 deg grid. The ISCCP data have been collected since July 1983, and the NOAA-9 data for ERBE have been collected for more than a year. Therefore, there is a good chance to use these temporally overlapping data sets to investigate hypothesized relationships. Changes in cloudiness affect both cloud albedo feedback (shortwave) and the greenhouse effect (longwave). The relative importance of the effects of clouds on albedo versus outgoing longwave radiation (OLR) in determining the radiation balance has long been a matter of controversy. Now, however, changes in cloud amount as observed by the ISCCPO can be correlated to corresponding changes in the albedo and changes in the OLR from ERBE. Monthly means can be utilized in all instances.

Jacobowitz, H.↗
NASA NTRS1994

Global shortwave energy budget at the earth's surface from ERBE observations

A method is proposed to compute the net solar (shortwave) irradiance at the earth's surface from Earth Radiation Budget Experiment (ERBE) data in the S4 format. The S4 data are monthly averaged broadband planetary albedo collected at selected times during the day. Net surface shortwave irradiance is obtained from the shortwave irradiance incident at the top of the atmosphere (known) by subtracting both the shortwave energy flux reflected by the earth-atmosphere system (measured) and the energy flux absorbed by the atmosphere (modeled). Precalculated atmospheric- and surface-dependent functions that characterize scattering and absorption in the atmosphere are used, which makes the method easily applicable and computationally efficient. Four surface types are distinguished, namely, ocean, vegetation, desert, and snow/ice. Over the tropical Pacific Ocean, the estimates based on ERBE data compare well with those obtained from International Satellite Cloud Climatology Project (ISCCP) B3 data. For the 9 months analyzed the linear correlation coefficient and the standard difference between the two datasets are 0.95 and 14 W/sq m (about 6% of the average shortwave irradiance), respectively, and the bias is 15 W/sq m (higher ERBE values). The bias, a strong function of ISCCP satellite viewing zenith angle, is mostly in the ISCCP-based estimates. Over snow/ice, vegetation, and desert no comparison is made with other satellite-based estimates, but theoretical calculations using the discrete ordinate method suggest that over highly reflective surfaces (snow/ice, desert) the model, which accounts crudely for multiple reflection between the surface and clouds, may substantially overestimate the absorbed solar energy flux at the surface, especially when clouds are optically thick. The monthly surface shortwave irradiance fields produced for 1986 exhibit the main features characteristic of the earth's climate. As found in other studies, our values are generally higher than Esbensen and Kushnir's by as much as 80 W/sq m in the tropical oceans. A cloud parameter, defined as the difference between clear-sky and actual irradiances normalized to top-of-atmosphere clear-sky irradiance, is also examined. This parameter, minimally affected by sun zenith angle, is higher in the midlatitude regions of storm tracks than in the intertropical convergence zone (ITCZ), suggesting that, on average, the higher cloud coverage in midlatitudes is more effective at reducing surface shortwave irradiance than opaque, convective, yet sparser clouds in the ITCZ. Surface albedo estimates are realistic, generally not exceeding 0.06 in the ocean, as high as 0.9 in polar regions, and reaching 0.5 in the Sahara and Arabian deserts.

Breon, Francois-Marie↗
NASA NTRS2011

Subsurface Emission Effects in AMSR-E Measurements: Implications for Land Surface Microwave Emissivity Retrieval

An analysis of land surface microwave emission time series shows that the characteristic diurnal signature associated with subsurface emission in sandy deserts carry over to arid and semi-arid region worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (AMSR-E) measurements. The AMSR-E orbit has equator crossing times near 01:30 and 13 :30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. AMSR-E measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from AMSR-E, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions

Galantowicz, John F.↗
NASA NTRS2015

External Influences on Modeled and Observed Cloud Trends

Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.

clouds (meteorology)↗
NASA NTRS1993

Analysis of the tropospheric water distribution during FIRE 2

The Penn State/NCAR mesoscale model, as adapted for use at ARC, was used as a testbed for the development and validation of cloud models for use in General Circulation Models (GCM's). This modeling approach also allows us to intercompare the predictions of the various cloud schemes within the same dynamical framework. The use of the PSU/NCAR mesoscale model also allows us to compare our results with FIRE-II (First International Satellite Cloud Climatology Project Regional Experiment) observations, instead of climate statistics. Though a promising approach, our work to date revealed several difficulties. First, the model by design is limited in spatial coverage and is only run for 12 to 48 hours at a time. Hence the quality of the simulation will depend heavily on the initial conditions. The poor quality of upper-tropospheric measurements of water vapor is well known and the situation is particularly bad for mid-latitude winter since the coupling with the surface is less direct than in summer so that relying on the model to spin-up a reasonable moisture field is not always successful. Though one of the most common atmospheric constituents, water vapor is relatively difficult to measure accurately, especially operationally over large areas. The standard NWS sondes have little sensitivity at the low temperatures where cirrus form and the data from the GOES 6.7 micron channel is difficult to quantify. For this reason, the goals of FIRE Cirrus II included characterizing the three-dimensional distribution of water vapor and clouds. In studying the data from FIRE Cirrus II, it was found that no single special observation technique provides accurate regional distributions of water vapor. The Raman lidar provides accurate measurements, but only at the Hub, for levels up to 10 km, and during nighttime hours. The CLASS sondes are more sensitive to moisture at low temperatures than are the NWS sondes, but the four stations only cover an area of two hundred kilometers on a side. The aircraft give the most accurate measurements of water vapor, but are limited in spatial and temporal coverage. This problem is partly alleviated by the use of the MAPS analyses, a four-dimensional data assimilation system that combines the previous 3-hour forecast with the available observations, but its upper-level moisture analyses are sometimes deficient because of the vapor measurement problem. An attempt was made to create a consistent four-dimensional description of the water vapor distribution during the second IFO by subjectively combining data from a variety of sources, including MAPS analyses, CLASS sondes, SPECTRE sondes, NWS sondes, GOES satellite analyses, radars, lidars, and microwave radiometers.

Westphal, Douglas L.↗
NASA NTRS1994

Microphysical modeling of cirrus. 1: Comparison with 1986 FIRE IFO measurements

We have used a one-dimensional model of cirrus formation to study the development of cirrus clouds during the 1986 First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) intensive field observations (IFO). The cirrus model includes microphysical, dynamical, and radiative processes. Sulfate aerosols, solution drops, ice crystals, and water vapor are all treated as interactive elements in the model. Ice crystal size distributions are fully resolved based on calculations of homogeneous freezing nucleation, growth by water vapor deposition, evaporation, coagulation, and vertical transport. We have focused on the cirrus observed on November 1, 1986. Vertical wind speed for the one-dimensional simulation is taken from a mesoscale model simulation for the appropriate time period. The mesoscale model simulation suggested that strong upward motions over Wyoming and subsequent horizontal transport of upper level moisture were responsible for the cirrus observed over Wisconsin on this date. We assumed that our one-dimensional model could be used to represent a vertical column moving from Wyoming to Wisconsin over a period of several hours. Ice crystal nucleation occurs in our model in the 8 to 10-km region as a result of the strong updrafts (and cooling) early in the simulation. Growth, coagulation, and sedimentation of these ice crystals result in a broad cloud region (5-10 km thick) with an optical depth of 1-2 after a few hours, in agreement with the FIRE measurements. Comparison with aircraft microphysical measurements made over Wisconsin indicates that the simulation generated reasonable ice water content, but the predicted ice number densities are too low, especially for radii less than about 50 microns. Sensitivity tests suggest that better agreement between simulated and observed microphysical properties is achieved if the nucleation rate is higher or stronger vertical mixing (perhaps associated with multidimensional motions) is present.

Jensen, Eric J.↗
NASA NTRS1994

Influence of ocean surface conditions on atmospheric vertical thermodynamic structure and deep convection

The authors analyze the influence of Sea Surface Temperature (SST) and surface wind divergence on atmospheric thermodynamic structure and the resulting effects on the occurrence of deep convection using National Meteorological Center radiosonde data and International Satellite Cloud Climatology Program data for July 1983-July 1985. The onset of deep convection requires not only the existence of positive convective available potential energy (CAPE), but also an unstable planetary boundary layer (PBL). A stable PBL is observed to suppress deep convection even when CAPE is positive. Variations of SST have a major effect on CAPE, but surface wind divergence can also affect deep convection by changing the lapse rate in the lower troposphere and humidity in the PBL. Specifically, when SST is greater than or equal to 28 C, CAPE is always positive, and surface wind divergence does not qualitatively change the buoyancy profile above the PBL. Strong surface wind divergence, however, stabilizes the PBL so as to suppress the initiation of deep convection. In warm SST regions, CAPE is greater than 0 regardless of assumptions about condensate loading, although the pseudoadiabatic limit is more consistent with the observed deep convection than the reversible moist-adiabatic limit under these circumstances. When SST is less than 27 C, CAPE is usually negative and inhibits convection, but strong surface wind convergence can destabilize the inversion layer and moisten the PBL enough to make the atmosphere neutrally stable in the mean. As a result, deep convection is generally enhanced either when SST is greater than or equal to 28 C in the absence of strong surface wind divergence or when strong surface wind convergence occurs even if SST is less than 27 C. The anomalous suppression of deep convection in the warm area of the equatorial west Pacific lying between the intertropical convergence zone (ITCZ) and south Pacific convergence zone (SPCZ) is probably caused by dryness in the PBL and an inversion in that area. The seasonal cycles of deep convection and surface wind divergence are in phase with the maximum solar radiation and lead SST for one to three months in the central Pacific. The change of PBL relative humidity plays a critical role in the changeover to convective instability in this case. The seasonal change of deep convection and associated clouds seems not to have important effects on the seasonal change of local SST in the central Pacific.

Fu, Rong↗
NASA NTRS2007

Comparison of Different Global Information Sources Used in Surface Radiative Flux Calculation: Radiative Properties of the Surface

Direct estimates of surface radiative fluxes that resolve regional and weather-scale variabilty over the whole globe with reasonable accuracy have only become possible with the advent of extensive global, mostly satellite, datasets within the past couple of decades. The accuracy of these fluxes, estimated to be about 10-15 W per square meter is largely limited by the accuracy of the input datasets. The leading uncertainties in the surface fluxes are no longer predominantly induced by clouds but are now as much associated with uncertainties in the surface and near-surface atmospheric properties. This study presents a fuller, more quantitative evaluation of the uncertainties for the surface albedo and emissivity and surface skin temperatures by comparing the main available global datasets from the Moderate-Resolution Imaging Spectroradiometer product, the NASA Global Energy and Water Cycle Experiment Surface Radiation Budget project, the European Centre for Medium-Range Weather Forecasts, the National Aeronautics and Space Administration, the National Centers for Environmental Prediction, the International Satellite Cloud Climatology Project (ISCCP), the Laboratoire de Meteorologie Dynamique, NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer project, NOAA Optimum Interpolation Sea Surface Temperature Analysis and the Tropical Rainfall Measuring Mission (TRMM) Microwave Image project. The datasets are, in practice, treated as an ensemble of realizations of the actual climate such that their differences represent an estimate of the uncertainty in their measurements because we do not possess global truth datasets for these quantities. The results are globally representative and may be taken as a generalization of our previous ISCCP-based uncertainty estimates for the input datasets. Surface properties have the primary role in determining the surface upward shortwave (SW) and longwave (LW) flux. From this study, the following conclusions are obtained. Although land surface albedos in the near near-infrared remain poorly constrained (highly uncertain), they do not cause too much error in total surface SW fluxes; the more subtle regional and seasonal variations associated with vegetation and snow are still on doubt. The uncertainty of the broadband black-sky SW albedo for land surface from this study is about 7%, which can easily induce 5-10 W per square meter uncertainty in (upwelling) surface SW flux estimates. Even though available surface (broadband) LW emissivity datasets differ significantly (3%-5% uncertainty), this disagreement is confined to wavelengths greater than 20 micrometers so that there is little practical effect (1-3 W per square meters) on the surface upwelling LW fluxes. The surface skin temperature is one of two leading factors that cause problems with surface LW fluxes. Even though the differences among the various datasets are generally only 2-4 K, this can easily cause 10-15 W per square meter uncertainty in calculated surface (upwelling) LW fluxes. Significant improvements could be obtained for surface LW flux calculations by improving the retrievals of (in order of decreasing importance): (1) surface skin temperature, (2) surface air and near-surface-layer temperature, (3) column precipitable water amount and (4) broadband emissivity. And for surface SW fluxes, improvements could be obtained (excluding improved cloud treatment) by improving the retrievals of (1) aerosols (from our sensitivity studies but not discussed in this work), and (2) surface (black-sky) albedo, of which, NIR part of the spectrum has much larger uncertainty.

Zhang, Yuanchong↗
NASA NTRS1981

Cloud cover archiving on a global scale - A discussion of principles

Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.

Henderson-Sellers, A.↗
NASA NTRS1982

Key scientific questions and the role of satellites

Some of the research opportunities that are available from geostationary satellite data, especially from MONEX during the Global Weather Experiment are described. In addition, the International Cloud Climatology Program is described and the use of satellite imagery in studying mesoscale convection complexes is discussed. Finally, information derived from satellite data on ocean winds is examined.

Bierly, E. W.↗
NASA NTRS1982

Soviet National Middle Atmosphere Program

Soviet national MAP program comprises seven projects: lower thermosphere (structure and dynamics); high latitude energetic sources and their effect on the structure and dynamics of the upper atmosphere under conditions of the polar night; climate of the stratosphere and mesosphere (effects of various energetic sources on its formation); winter variability in the lower ionosphere; noctilucent clouds (climatology, dynamics, nature, and genesis); wave processes and structure and dynamics of the stratosphere and mesosphere; and dynamics of the ozone layer.

Danilov, A. D.↗
NASA NTRS1987

The application of time series models to cloud field morphology analysis

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Chin, Roland T.↗
NASA NTRS1987

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Seze, G.↗