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A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 [micro]m, whereas liquid water is more absorbing than ice from 16 to 25 txm. MIXCRA retrievals are only valid for optically thin ([[tau].sub.visible]

Commercial aircraft now provide over 130,000 meteorological observations per day, including temperature, winds, and in some cases, humidity, vertical wind gust, or eddy dissipation rate (turbulence). The temperature and wind data are used in most operational numerical weather prediction models at NCEP and at other centers worldwide. At nonsynoptic times, these data are often the primary source of upper-air information over the United States. Even at synoptic times, these data are critical in depicting the atmosphere along oceanic air routes. A Web site [http://acweb. fsl.noaa.gov/] has been developed that gives selected users access to these data. Because the data are proprietary to the airlines, real-time access is restricted to entities such as government agencies and nonprofit research institutions (although sample past data are available to all). Data can be displayed in a variety of ways and can be downloaded for local processing. These data are described here, and examples of how they have been useful in weather forecasting and numerical weather prediction are shown.

The summertime intraseasonal oscillation (ISO) is an important component of the south Asian monsoon. Lagged regressions of intraseasonally filtered (25-80 days) outgoing longwave radiation (OLR) reveal that centers of convection move both northward and eastward from the central equatorial Indian Ocean subsequent to the initiation of an ISO. Eastward movement of convection is also seen at Indian subcontinent latitudes (10 [degrees]-20 [degrees] N). Based on the regression results, the summertime ISO convection signal appears as a band tilting northwestward with latitude and stretching from the equator to about 20 [degrees] N. Viewed along any meridian, convection appears to propagate northward while equatorial convection propagates to the east. To examine the robustness of the connection between eastward and northward movement, individual ISOs are categorized and composited relative to the strength of the large-scale eastward component of convection in the central equatorial Indian Ocean. It is found that the majority of ISOs that exhibit northward movement onto the Indian subcontinent (42 out of 54 ISOs, or 78%) also exhibit eastward movement into the western Pacific Ocean. It is also found that when convection in the central Indian Ocean is not followed within 10-20 days by convection in the western Pacific Ocean (12 out of 54 ISOs, or 22%), the independent northward movement of convection in the Indian Ocean region is somewhat stunted. The link between the eastward and northward movement of convection is consistent with an interpretation of the summertime ISO in terms of propagating equatorial modes. The northward moving portion of convection is forced by surface frictional convergence into the low pressure center of the Rossby cell that is excited by equatorial ISO convection. A similar convergence pattern is seen for the northern winter ISO, but it does not generate poleward movement due to relatively cool SSTs underlying the surface convergence. (Manuscript received 20 February 2001, in final form 13 August 2001)

Meteorological data from over 2800 automated environmental monitoring stations in the western United States are collected, processed, archived, integrated, and disseminated as part of the MesoWest program. MesoWest depends upon voluntary access to provisional observations from environmental monitoring stations installed and maintained by federal, state, and local agencies and commercial firms. In many cases, collection and transmission of these observations are facilitated by NWS forecast offices, government laboratories, and universities. MesoWest augments the Automated Surface Observing System (ASOS) network maintained by the NWS, Federal Aviation Administration, and Department of Defense. MesoWest increases the coverage of observations in remote locations and helps capture many of the local and mesoscale weather phenomena that impact the public. The primary goal of MesoWest is to improve timely access to automated observations for NWS forecasters at offices throughout the western United States. In addition, integration of the observations into analyses of surface conditions at high spatial and temporal resolution provides additional tools for nowcasts and forecast verification. MesoWest observations are being used for many other applications, including input to operational and research models and research and education on weather processes in the western United States.

The objective of this study was to develop a method to provide estimates of daily global radiation as input for the Crop Growth Monitoring System of the European Union, from meteorological observations transmitted via the Global Telecommunication System for locations where sunshine duration observations are not available and hence the Angstrom, or any other sunshine duration based method, cannot be applied. A simple method to estimate global radiation from mean daytime cloud cover and maximum and minimum temperature has been tested. The test was executed for various locations in Europe, ranging from Finland to Italy. Average RMSE and MBE for the comparison between observed and estimated global radiation for the tested locations using the proposed method is 2.48 and -0.25 MJ [m.sup.-2] [d.sup.-1], respectively.

The impact of observational errors on objective analyses is investigated with mathematical analyses, analytical examples, and real data experiments. Cases with observational errors at one or more stations are considered. It is found that in the presence of observational errors, the analysis error in an objective analysis scheme generally consists of two parts: the signal fitting error and the noise contamination error. Although every objective analysis scheme has its own procedure(s) to control the two errors, the procedures to suppress the noise contamination error in one and two dimensions are shown to be relatively ineffective. It is shown that the extension of an objective analysis method to more dimensions significantly reduces the noise contamination. based on these results, higher dimensional versions of the least squares polynomial fitting (LSPF) methods and the Barnes scheme are examined. In both analytic and real data experiments, the 3D and 4D LSPF methods and the 3D Barnes scheme show an enhanced ability to filter observational noise.

One of the most significant impediments to progress in forecasting weather over North America is the relative paucity of routine observations over data-sparse regions adjacent to the United States. Prospectus Development Team Seven was convened to consider ways to promote research that seeks to determine implementations of observing systems that are optimal for weather prediction in the United States. An 'optimal' measurement system is considered to be one that maximizes the ratio of societal benefit to overall cost. The thrust of the conclusions is that existing means of estimating the value of current observing systems and the potential benefits of new or proposed observing systems are underutilized. At the same time, no rational way exists for comparing the cost of observations across the spectrum of federal agencies responsible for measuring the atmosphere and ocean. The authors suggest that a rational procedure for configuring an observation system that is optimal for weather prediction would consist of the following steps. 1) Identify specific forecast problems arising from insufficient data. Examples might include hurricane landfall and intensity forecasts, 24-h forecasts of intense extratropical cyclones affecting the West Coast and Alaska, and medium-range forecasts of severe weather for all of North America. 2) Use contemporary modeling techniques, such as observing system simulation experiments, ensemble forecasting, and model adjoint-derived sensitivities, to delineate measurement requirements for each specific forecasting problem and identify candidate observing systems and data assimilation techniques that could be brought to bear on each problem. 3) Estimate the incremental forecast improvements that could plausibly result from the added or reconfigured data and the societal benefits that would accrue from such improvements. 4) Estimate the overall cost (to the nation, not to specific federal agencies) of obtaining the data by the various candidate techniques and the benefits that are projected to result. 5) Use standard cost-benefit analysis as a basis for deciding the optimal deployment of measuring systems. The authors believe that a rational approach to atmospheric measurement is critical to further improvements in weather prediction and that such improvements might very well be made within the current budget of routine observations, integrated across all of the responsible federal agencies. This document outlines a proposed strategy for rationalizing atmosphere observations in aid of weather prediction in the United States. The paper begins with a summary of recommendations.

A neural network-based retrieval technique is developed to infer vapor, liquid and ice columns using two- and three-channel microwave radiometers. Neural network-based inverse scattering methods are capable of merging various data streams in order to retrieve microphysical properties of clouds and precipitation. The method is calibrated using National Oceanic and Atmospheric Administration (NOAA) results in a cloud-free condition. The performance of two- and three-channel neural network-based techniques is verified by independent NOAA estimates. The estimates of vapor and liquid agree with NOAA values. In the presence of ice, the liquid estimates deviated from NOAA's estimates. One of the major contributions of the three-channel radiometer is the estimation of ice in a winter cloud. The three-channel radiometer not only improves estimates of vapor and liquid, but also retrieves the ice column. Passive remote sensing can be ameliorated with the help of active remote sensing methods. The three-channel radiometer is used for estimating columnar contents of vapor, liquid, and ice in a cloud. It is shown that vertical profiles of median size diameter, number concentration, liquid water content, and ice water content can be inferred by combining radar reflectivity and radiometer observations. The combined remote sensor method is applied to Winter Icing and Storms Project (WISP) data to obtain detailed microphysical properties of clouds and precipitation. We also derived Z- Ice Water Content (IWC) and Z- Liquid Water Content (LWC) relationships and they are consistent with the earlier results.

With the advent of the microwave radiometer, passive remote sensing of clouds and precipitation has become an indispensable tool in a variety of meteorological and oceanographical applications. There is wide interest in the quantitative retrieval of water vapor, cloud liquid, and ice using brightness temperature observations in scientific studies such as earth's radiation budget and microphysical processes of winter and summer clouds. Emission and scattering characteristics of hydrometeors depend on the frequency of observation. Thus, a multifrequency radiometer has the capability of profiling cloud microphysics. Sensitivities of vapor, liquid, and ice with respect to 20.6, 31.65 and 90 GHz brightness temperatures are studied. For the model studies, the atmosphere is characterized by vapor density and temperature profiles and layers of liquid and ice components. A parameterized radiative transfer model is used to quantify radiation emanating from the atmosphere. It is shown that downwelling scattering of radiation by an ice layer results in enhancement at 90 GHz brightness temperature. Once absorptive components such as vapor and liquid are estimated accurately, then it is shown that the ice water path can be retrieved using ground-based three-channel radiometer observations. In this paper we developed two- and three-channel neural network-based inversion models. Success of a neural network-based approach is demonstrated using a simulated time series of vapor, liquid, and ice. Performance of the standard explicit inversion model is compared with an iterative inversion model. In Part II of this paper, actual radiometer, and radar field measurements are utilized to show practical applicability of the inverse models.

An ATR72 commuter aircraft crashed near Roselawn, Indiana, on 31 October 1994 killing all 68 people on board. Available weather data, including those from a Next Generation Radar, a radar wind profiler, a Geostationary Operational Environmental Satellite, and pilot reports of icing have been examined in combination with analysis fields from the Rapid Update Cycle model and forecast fields from the Pennsylvania State University/National Center for Atmospheric Research MM5 numerical model. Synthesis of this information provides a relatively complete and consistent picture of the ambient meteorological conditions in the region of the ATR72 holding pattern at [approximately]3.1 km above mean sea level. Of particular interest is the evidence that these conditions favored the development of supercooled drizzle drops within a strong frontal zone, as indicated by cloud-top temperatures of -10 [degrees] to -15 [degrees] C, weak radar reflectivity, and strong, vertical wind shear within the cloud and warm front.

A database for study of the impact of Doppler wind lidar data on numerical weather prediction in Observation System Simulation Experiments was created. Five Doppler wind lidar scenarios, TIROS Operational Vertical Sounder, Advanced TIROS Operational Vertical Sounder, Advanced Scatterometer, and all conventional observation types with a realistic distribution in time and space have been successfully simulated. A 30-day run of the ECMWF forecast model was used as a physically sound reference state. This 'true' atmospheric state was sampled at the observation positions and times. The simulated true variables were mapped onto the 'measured' variables, and a mix of random and gross errors with realistic statistical characteristics was added. The simulated observations were validated by comparison with existing data where available.

Results of an intercomparison study under the Atmospheric Model Intercomparison Project (AMIP) to assess the abilities of 29 global climate models (GCMs) in simulating various aspects of regional and hydrologic processes in response to observed sea surface temperature and sea ice boundary forcings are presented. The authors find that the models generally portray an earthlike climate to approximately 10%-20% of the global land surface temperature (= 14.8 [degrees] C) and global precipitation (= 2.3 mm [day.sup.-1]). While a majority of the models have a reasonable global water budget, about a quarter of the models show significant errors in the total global water balance. While the model frequency distributions of heavy precipitation associated with deep convection are in reasonable agreement with observations, a systematic underestimate of the frequency of occurrence of light precipitation events (< 1 mm [day.sup.-1]) is present in almost all the AMIP models, especially over continental desert regions and over tropical and subtropical oceanic regions contiguous to the west coasts of continents where low-level stratocumulus clouds tend to occur. This discrepancy is presumably related to the crude treatment of moist processes, especially those related to low clouds and nonconvective precipitation in the models. Another common problem in the global rainfall distribution is the presence of spectral rain or spurious gridpoint-scale heavy rain. The artificial anchoring of rainfall to topographic features in the Maritime Continent appears to be a generic problem in many GCMs. Models differ substantially in the magnitude of the rainfall amount over the eastern Pacific ITCZ for all seasons. The simulated boreal summer rainfall distributions have large variability over the Indian subcontinent and the Bay of Bengal. The northward migration of the monsoon convective zones are not well simulated. In particular, the East Asian monsoon rainband over the subtropical western Pacific is ill-defined or absent in all models. On the interannual timescale, the models show reasonable skills in simulating the fluctuations of the Southern Oscillation and the eastward migration of the major equatorial precipitation zone during ENSO. Most models show useful rainfall prediction skill in the Tropics associated with ENSO-related SST forcing. However, the models do not show any useful skill for extratropical rainfall prediction from specified anomalous global SST forcing. Overall, the models depict a reasonably realistic annual cycle of water balance over regions where long-term local moisture balance is maintained - that is, (P-E) [approximately equal to] 0 - over large interior land regions in the extratropics. In regions of strong dynamic control - that is, (P-E) >> 0 - such as the tropical western Pacific, monsoon regions, and the ITCZ, the intermodel variability is very large. The simulated water balance over large river basins has been validated against hydrographic fiver discharge data using a river-routing model. Results show that while the model ensemble mean runoffs are consistent with the climatological observed fiver discharge for the Amazon and Mississippi, the intermodel variability is substantial. The models yield even more divergent results over other world fiver basins. These results suggest that while some GCMs may have moderate capability in capturing some aspects of the climatological variation of runoff, it is premature to use them for climate studies related to continental-scale water balance. A ranking of the AMIP models and some possible implications based on the above performance are also presented.

Designs and implementation are proceeding for a Global Ocean Observing System (GOOS) and a Global Climate Observing System (GCOS). The initial design for the ocean component of the GCOS, which is also the climate module of the GOOS, was completed in 1995 by the Ocean Observing System Development Panel (OOSDP). This design for an ocean observing system for climate aims to provide ocean observations leading to gridded products, analyses, forecasts, indexes, assessments, and other items needed to detect, monitor, understand, and predict climate variations and change. A summary of the OOSDP report is presented here, beginning with the rationale for such a system and the series of specific goals and subgoals used to focus the design. The instruments, platforms, transmission systems, or processing required to observe the climate variables or quantifiable aspects of the climate system to meet these subgoals are identified. These observing system elements are divided into three categories: 1) elements of existing operational systems, 2) those that should be added now to complete the initial observing system, or 3) elements perhaps not now readily attainable but that should be added to the system at the earliest feasible time. Future research and development likely needed for further development of the system are also identified in the report. The elements needed for each subgoal are ranked as to feasibility (i.e., routine, systematic, timely, and cost-effective characteristics) versus their impact on attaining the subgoal. Priorities among the various subgoals are presented based on the panel's perception of where the immediate and important issues lie. This then provides the basis for an incremental approach to implementation, leading to a coherent conceptual design.

A numerical scheme was developed to couple a multilayer canopy radiation model, a photosynthesis model for [C.sub.3] species, and a leaf stomatal conductance model with a single-leaf energy balance equation. This coupled leaf and canopy model was used to simulate the responses of a horizontally uniform forest canopy to its ambient microenvironment, using micrometeorological data collected from field measurements in a forest canopy. Emphasis was placed on issues associated with modeling the transient responses of plant leaves. For example, thermal storage was found to be important in modeling transience of leaf temperature, which in turn influenced the transient heating or cooling of the atmosphere by plant leaves. In addition, modification of the Ball-Berry leaf stomatal conductance model, using an exponential formula with an empirical time lag, yielded more realistic transient leaf stomatal conductances, which were important for estimating evaporation and C[O.sub.2] assimilation.

In an earlier work, the authors introduced an objective forecast model for a 24-h prediction of the number of daily forest fires based on a 2-day lag autoregressive model. The meteorological inputs required for this model (temperature and geopotential height at 850 and 700 hPa and dewpoint at 850 hPa) may be predicted by a medium-range numerical weather forecast model such as that of the European Centre for Medium-Range Weather Forecasts. These predicted meteorological elements may be used to extend the range of daily forest fire forecasting. Since the forest fire forecast model is based on a categorization (type of day), an error in the meteorological predictions may not be an error in the predictive model. A meteorological error will only imply error for the model if it produces a change in the type of day (category). The forecast range for the number of forest fires per day has been extended to five days with this new model. Moreover, assuming that the weather forecast is perfect, a validation of the prediction model for forest fires is carried out.

Comparisons have been made between in situ aircraft measurements of integrated liquid water and retrievals of integrated liquid water path (LWP) from algorithms using SSM/I brightness temperatures. The aircraft measurements were made over the North Atlantic Ocean during the winter of 1992. Six case studies are presented from which trends in the LWP algorithms are discussed. SSM/I liquid water path validation has previously only been performed through comparisons with measurements from upward-looking radiometers or with calculations from radiative transfer models. The case studies presented here reflect an alternative technique for validation. Aircraft-derived liquid water paths ranged from 0.01 to 0.09 kg [m.sup.-2] for the six cases presented. The SSM/I algorithms investigated predicted LWP to within [+ or -]0.02-0.03 kg [m.sup.-2], provided one accounted for systematic biases in the retrievals. These biases were systematic in the range [+ or -]0.06 kg [m.sup.-2] and were presumably caused by latitudinal and seasonal influences inherent in the algorithms. Algorithms based on radiative transfer models appeared to perform better than the statistically based algorithms.

This work examines the use of standard meteorological information to describe the attenuation of sunlight associated with cloudy skies. Datasets consisting of broadband ultraviolet and total spectrally integrated solar irradiance are available for Chicago over the period April-October 1993. A series of regression models seeks to explain variability in the measured irradiances using fractional cloudiness, cloud-ceiling altitude, and visibility as independent variables. Fractional cloud cover alone can explain 39%-51% of the variance in the radiation data. Regression models that combine all three independent variables can increase the explained variance to 61%-77%, depending on local time and spectral region. Comparison of broadband ultraviolet irradiances with simultaneous total solar irradiances indicates that cloudy skies provide less attenuation in the former dataset.

Variable choices of instrumentation, sensor exposure position, location and averaging methodology considerably influenced the results as suggested by the data obtained from combined San Joaquin Valley Air Quality Study and Atmospheric Utility Signatures, Predictions and Experiments study. Large differences in hourly wind speed averages obtained in the studies are discussed.

Study of around 270 meteorological soundings launched during 1991 and 1992 in the Madrid basin to analyse mixed-layer (ML) height evolution shows that the synoptic conditions exert a strong influence on the daily ML evolution, type of mixing and maximum height. The diurnal variability of the mechanical mixing heights is found to be smaller than the ML evolution. Demonstration of the relationship between the ML evolution and the synoptic-scale phenomenon is given.

The daytime planetary boundary layer (PBL) consists of two sublayers, the lower sublayer and upper sublayer. Observations performed over the Ina Valley in Japan indicated that the lower sublayer was formed due to turbulent mixing and had maximum height of one thousand meters from the surface. The upper sublayer was formed due to local subsidence and showed stable stratification during daytime. The PBL heating rate was more in the valley bottom and less over the mountains. Thermal cross-valley circulation lasted until early afternoon.

The collocation of the Weather Forecast Office and the Desert Research Institute in Reno, Nevada, has fostered a National Weather Service (NWS)-University collaborative effort that provided meteorological forecasting and research support to an experimental aeronautics endeavor. The Earthwinds transglobal ballooning project is an attempt to complete the first nonstop global circumnavigation flight by a lighter-than-air craft, with launch from Stead airfield in Reno. This article describes the cooperative efforts of the Earthwinds operations staff, the NWS office, the Desert Research Institute, and the atmospheric technology industry. Activities included the use of global and regional forecasts, evaluation of local wind and temperature diurnal cycles, numerical simulation of balloon launch trajectories, and onboard atmospheric instrumentation.

Analysis of radar and rain gauge data by window probability matching method enables the calculation of sets of radar measured reflectivity-rain intensity relationships for different types of rainfall. Analysis of the three-dimensional reflectivity enables the determination of various classification criteria including horizontal radial reflectivity gradients, cloud depth, brightband fraction and the height of the freezing level.

Consistent wind model is an atmospheric transport model that incorporates mass continuity into meteorological field, transforming it to a new grid system. The model is developed with map coordinates and uses the compressive continuity parameter in incorporating the map scale factor. The adjustability of the wind components are computed as functions of spatial function in the model.

Major nighttime and daytime differences were evident from field comparisons of net radiation estimated by a single-dome Fritschen-type pyrgeometer with blade sensing surfaces and that calculated from a pair of Eppley pyranometers and an Eppley pyrgeometer. The responsiveness of estimates of the net pyrradiometer was more in the shortwave band than in the longwave band.

Theoretical bases and elaborate polynomial expressions relevant to various naturally occurring drop size distributions for more precise parameterizations of the specific attenuation at horizontal and vertical polarizations from five to 25 GHZ, and for the specific polarization propagation differential phase shift PhiDP from three to 13 GHZ, have been established. The radar parameters can be predicted properly if only two of the three parameters, rainfall rate, R, rainwater content, W, and mass-weighted mean drop diameter, Dm, are specified and information on drop size distribution is insufficient.

The supply of consistent definitions of effective datadensity, used in satellite soundings and objective data analysis, is essential as existing definitions based on the Backus-Gilbert spread functions are inaccurate. The sensitivity of retrievals is shown using the model resolution function, which has sidelobes. The smoothing of the function's trace components results in estimates that do not change with coordinate systems or units, and that are more reliable.

The Lidar In-Space Technology Experiment (LITE) is being developed by NASA/Langley Research Center for a series of flights on the space shuttle beginning in 1994. Employing a three-wavelength Nd: YAG laser and a 1-m-diameter telescope, the system is a test-bed for the development of technology required for future operational spaceborne lidars. The system has been designed to observe clouds, tropospheric and stratospheric aerosols, characteristics of the planetary boundary layer, and stratospheric density and temperature perturbations with much greater resolution than is available from current orbiting sensors. In addition to providing unique datasets on these phenomena, the data obtained will be useful in improving retrieval algorithms currently in use. Observations of clouds and the planetary boundary layer will aid in the development of global climate model (GCM) parameterizations. This article briefly describes the LITE program and discusses the types of scientific investigations planned for the first flight.

A procedure is presented which can be used to create, from many years of available past weather data, a Reference Year consisting in 8760 hourly values of a few chosen meteorological quantities. Such 'year' corresponds to a 'typical' year for the considered locality, regarding both the occurrence and the persistence of different meteorological situations, in all months. This approach is a modification of the procedure used in the production of Test Reference Years or of Design Reference Years. In this approach, the frequency distributions relative to single months in the database are compared with the long-term frequency distribution of all the months 'with the same name.' Furthermore, the correlation between subsequent daily values is taken into account.

Comparison of ground-based and radar-measured hail kinetic energy patterns of eight hailstorms are made. Horizontal shifts in the radar patterns are made in order to obtain 0.9 correlation with the ground data. Such a shift is consistent with existing storm kinematic models. Microphysical and storm dynamics affect agreement between the two data sets. Hailstone melting and spectral shapes are also studied. The former is more evident in supercell than in single-cell or multicell storms.

Despite significant progress in the Tropical Ocean-Global Atmosphere (TOGA) program, a number of major hurdles remain before the primary objective, prediction of the variability of the coupled ocean-atmosphere system on time scales of months to years, can be achieved. Foremost among these hurdles is understanding the physics that maintains and perturbs the western Pacific warm pool, the region of the warmest sea surface temperature in the open oceans, which coexists with the largest annual precipitation and latent heat release in the atmosphere. Even though it is believed that the warm pool is a 'center of action' for the El Nino-Southern Oscillation (ENSO) phenomena in the ocean and the atmosphere, successful simulation of the warm pool has remained an elusive goal. To gain a clear understanding of global climate change, the ENSO phenomenon, and the intraseasonal variability of the coupled atmosphere-ocean system, it is clear that a better specification of the coupling of the ocean and the atmosphere is required. An observational and modeling program, the TOGA Coupled Ocean-Atmosphere Response Experiment (TOGA COARE), has been designed to work toward this goal. The scientific goals of COARE are to describe and understand: 1) the principal processes responsible for the coupling of the ocean and the atmosphere in the western Pacific warm-pool system; 2) the principal atmospheric processes that organize convection in the warm-pool region; 3) the oceanic response to combined buoyancy and wind-stress forcing in the western Pacific warm-pool region; and 4) the multiple-scale interactions that extend the oceanic and atmospheric influence of the western Pacific warm-pool system to other regions and vice versa. To carry out the goals of TOGA COARE, three components of a major field experiment have been defined: interface, atmospheric, and oceanographic. An intensive observation period (IOP), embedded in a period of enhanced meteorological and oceanographic monitoring, will occur from November 1992 through February 1993 in the western Pacific region bordered by 10 degrees N, 10 degrees S, 140 degrees E, and the date line. The experimental design calls for a complex set of oceanographic and meteorological observations from a variety of platforms that will carry out remote and in situ measurements. The focus of the observational effort will be in an intensive flux array (IFA) centered at 2 degrees S and 156 degrees E. The resulting high-quality dataset is required for the calculation of the interfacial fluxes of heat, momentum, and moisture, and to provide ground truth for a wide range of remotely sensed variables for the calibration of satellite-derived algorithms. The ultimate objective of the COARE dataset is to improve air-sea interaction and boundary-layer parameterizations in models of the ocean and the atmosphere, and to validate coupled models.

Cloud-properties can be effectively retrieved using the multispectral, multiresolution technique (MSMR). The MSMR method combines High-Resolution Infrared Radiation Sounder (HIRS) sounding channel data and Advanced Very High-Resolution Radiometer (AVHRR) imaging data to determine mid- to high-level cloud properties. AVHRR data are studied to obtain cloud reflectances and emittances with HIRS pixels and AVHRR pixel radiance are determined through the cloud-top temperature from the HIRS data.