Deep convective storms with overshooting tops (OTs) are capable of producing hazardous weather conditions such as aviation turbulence, frequent lightning, heavy rainfall, large hail, damaging wind, and tornadoes. This paper presents a new objective infrared-only satellite OT detection method called infrared window (IRW)-texture. This method uses a combination of 1) infrared window channel brightness temperature (BT) gradients, 2) an NWP tropopause temperature forecast, and 3) OT size and BT criteria defined through analysis of 450 thunderstorm events within 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) imagery. Qualitative validation of the IRW-texture and the well-documented water vapor (WV) minus IRW BT difference (BTD) technique is performed using visible channel imagery, CloudSat Cloud Profiling Radar, and/or Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud-top height for selected cases. Quantitative validation of these two techniques is obtained though comparison with OT detections from synthetic satellite imagery derived from a cloud-resolving NWP simulation. The results show that the IRW-texture method false-alarm rate ranges from 4.2% to 38.8%, depending upon the magnitude of the overshooting and algorithm quality control settings. The results also show that this method offers a significant improvement over the WV-IRW BTD technique. A 5-yr Geosynchronous Operational Environmental Satellite (GOES)-12 OT climatology shows that OTs occur frequently over the Gulf Stream and Great Plains during the nighttime hours, which underscores the importance of using a day/night infrared-only detection algorithm. GOES-12 OT detections are compared with objective Eddy Dissipation Rate Turbulence and National Lightning Detection Network observations to show the strong relationship among OTs, aviation turbulence, and cloud-to-ground lightning activity.

A comprehensive and accurate global water vapor dataset is critical to the adequate understanding of water vapor's role in the earth's climate system. To begin to satisfy this need, the authors have produced a blended dataset made up of global, 5-yr (1988-92), l°x 1° spatial resolution, atmospheric water vapor (WV) and liquid water path products. These new products consist of both the daily total column-integrated composites and a multilayered WV product at three layers (1000-700, 700-500, 500-300 mb). The analyses combine WV retrievals from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS), the Special Sensor Microwave/Imager, and radiosonde observations. The global, vertical-layered water vapor dataset was developed by slicing the blended total column water vapor using layer information from TOVS and radiosonde. Also produced was a companion, over oceans only, liquid water path dataset. Satellite observations of liquid water path are growing in importance since many of the global climate models are now either incorporating or contain liquid water as an explicit variable. The complete dataset (all three products) has been named NVAP, an acronym for National Aeronautics and Space Administration Water Vapor Project. This paper provides examples of the new dataset as well as scientific analysis of the observed annual cycle and the interannual variability of water vapor at global, hemispheric, and regional scales. A distinct global annual cycle is shown to be dominated by the Northern Hemisphere observations. Planetary-scale variations are found to relate well to recent independent estimates of tropospheric temperature variations. Maps of regional interannual variability in the 5-yr period show the effect of the 1992 ENSO and other features.

A method of remotely sensing integrated cloud liquid water over the oceans using spaceborne passive measurements from the special sensor microwave/imager (SSM/I) is described. The technique is comprised of a simple physical model that uses the 19.35‐ and 37‐GHz channels of the SSM/I. The most comprehensive validation to date of cloud liquid water estimated from satellites is presented. This is accomplished through a comparison to independent ground‐based microwave radiometer measurements of liquid water on San Nicolas Island, over the North Sea, and on Kwajalein and Saipan Islands in the western Pacific. In areas of marine stratocumulus clouds off the coast of California a further comparison is made to liquid water inferred from advanced very high resolution radiometer (AVHRR) visible reflectance measurements. The results are also compared qualitatively with near‐coincident satellite imagery and with other existing microwave methods in selected regions. These comparisons indicate that the liquid water amounts derived from the simple scheme are consistent with the ground‐based measurements for nonprecipitating cloud systems in the subtropics and middle to high latitudes. The comparison in the tropics, however, was less conclusive. Nevertheless, the retrieval method appears to have general applicability over most areas of the global oceans. An observational measure of the minimum uncertainty in the retrievals is determined in a limited number of known cloud‐free areas, where the liquid water amounts are found to have a low variability of 0.016 kg m−2. A simple sensitivity and error analysis suggests that the liquid water estimates have a theoretical relative error typically ranging from about 25% to near 40% depending on the atmospheric/surface conditions and on the amount of liquid water present in the cloud. For the global oceans as a whole the average cloud liquid water is determined to be about 0.08 kg m−2. The major conclusion of this paper is that reasonably accurate amounts of cloud liquid water can be retrieved from SSM/I observations for nonprecipitating cloud systems, particularly in areas of persistent stratocumulus clouds, with less accurate retrievals in tropical regions.

A combined active/passive modeling system that converts CloudSat observations to simulated microwave brightness temperatures (T B ) is used to assess different ice particle models under precipitating conditions. Simulation results indicate that certain ice models (e.g., low-density spheres) produce excessive scattering and implausibly low simulated T B s for stratiform precipitation events owing to excessive derived ice water paths (IWPs), while other ice models produce unphysical T B depressions due to the combined effects of elevated derived IWP and excessive particle size distribution-averaged extinction. An ensemble of nonspherical ice particle models, however, consistently produces realistic results under most circumstances and adequately captures the radiative properties of frozen hydrometeors associated with precipitation-with the possible exception of very high IWP events. Large derived IWP uncertainties exceeding 60% are also noted and may indicate IWP retrieval accuracy deficiencies using high-frequency passive microwave observations. Simulated T B uncertainties due to the ice particle model ensemble members approach 9 (5) K at 89 (157) GHz for high ice water path conditions associated with snowfall and ;2-3 (;1-2) K under typical stratiform rain conditions. These uncertainties, however, display considerable variability owing to ice water path, precipitation type, satellite zenith angle, and frequency. Comparisons between 157-GHz simulations and observations under precipitating conditions produce low biases (,1.5 K) and high correlations, but lower-frequency channels display consistent negative biases of 3-4 K in precipitating regions. Sample error correlations and covariance matrices for select microwave frequencies also show strong functional relationships with ice water path and variability depending on precipitation type.

The Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988–2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) intercalibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2, and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and the monthly mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, correcting for a CLWP bias (based on matchups to clear-sky MODIS scenes), and constructing a total (cloud + rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e., CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from −15% (e.g., global oceanic stratocumulus decks) to +5%–10% (e.g., portions of the higher latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Sciences Data and Information Services Center.

[1] Near-global analysis of 183 GHz measurements from the NOAA-15 advanced microwave sounding unit (AMSU) B was conducted to investigate the impact of cold (< 240 K at 11 mm) clouds on upper tropospheric humidity (UTH) observations and in assessing the potential for deriving cloud microphysical properties. Collocated advanced very high resolution radiometer (AVHRR) data aided in identifying clouds and isolating the ice-cloud-scattering effect. This effect was determined by subtracting the measured AMSU-B brightness temperature (T b ) from a background T b estimated using AVHRRderived cloud optical depth data. Results for December 1999 over land and ocean show that nonprecipitating cold clouds have a measurable impact on 183 GHz T b s although the average effect is rather weak (1.4 K). Cold clouds associated with precipitation had a much larger average effect (7 K); therefore only for these types of clouds is there sufficient information for potential quantitative estimation of cloud/precipitation physical properties. Nonprecipitating cold clouds bias estimates of UTH, on average, by 5% but can reach 20% for optically thick clouds. Precipitating clouds produce an 18% average bias. On the basis of these results it is recommended that UTH retrievals undergo filtering for precipitation (using combined microwave and infrared window channels) as well as for optically thick nonprecipitating cold clouds that fill a sensor's field of view, which may be screened using infrared split window techniques.

This paper describes an observational study of the relationship between the cloudy sky components of the Earth's radiation budget (ERB) and space/time coincident observations of the sea surface temperature, microwave‐derived cloud liquid water and cloud cover. The study uses two ERB data sets; Nimbus 7 narrow field‐of‐view, broadband scanning radiometer data from June 1979 to May 1980 and the Earth Radiation Budget Experiment broadband scanning data from March 1985 to February 1986. Cloud fluxes are derived from the ERB fluxes and estimates of the clear sky fluxes are described in a related paper. A new method that extends the cloud forcing analysis of ERB data is also introduced to estimate the cloud albedo. The zonally and seasonally averaged cloud flux components of the ERB are within 6 W m−2 for the two data sets. The general gross features of the global distributions of these fluxes also reproduce those reported in recent studies with the largest differences in mid‐to‐high latitude regions characterized by persistent cloud cover where the estimation of Nimbus 7 clear sky fluxes is suspect. A quantitative assessment of the impact of clouds on the greenhouse effect is given in terms of the greenhouse parameter introduced in a related study. This impact is significant, especially for deep convective clouds that form over the warmest waters of the oceans. It is also shown how the greenhouse effect of clouds increases as the liquid water path (LWP) of clouds increases in a manner analogous to that observed for water vapor. This increase is in direct contrast to many recent model studies of cloud feedback that ignore this influence. Cloud albedo data are grouped in categories corresponding to ranges of solar zenith angle. Albedos and longwave fluxes for the latitudinal ranges of these categories suggest that brighter, colder clouds exist over tropical land masses in comparison to tropical oceanic regions and vice versa for middle and high latitudes. While microphysical effects cannot be ruled out as an explanation, the general reciprocal change of albedo and longwave flux support the assertion that these differences originate from gross macrophysical differences of clouds. The albedo of clouds and the relationships between the cloud albedo and LWP are also shown to be significantly different for midlatitude oceanic clouds compared to clouds over tropical oceans. The cloud albedo differences are substantial and cannot be explained simply in terms of cloud amount effects. Based on comparison with theory, it is unlikely that realistic differences in the microphysics of clouds are large enough to explain the observations. An explanation for these differences in terms of gross macroscopic effects is proposed. The major conclusion of this study is that the largest, and hence most important, observed influence of cloud on the ERB is more consistent with macrophysical properties of clouds as opposed to microphysical properties, which have received much more attention in recent literature.

In this study, the ability of different combinations of bulk cloud microphysics and planetary boundary layer (PBL) parameterization schemes implemented in the Weather Research and Forecasting Model to realistically simulate the wide variety of cloud types associated with an extratropical cyclone is examined. An ensemble of high-resolution model simulations was constructed for this case using four microphysics and two PBL schemes characterized by different levels of complexity. Simulated cloud properties, including cloud optical thickness, cloud water path, cloud-top pressure, and radiative cloud phase, were subsequently compared to cloud data from three Moderate Resolution Imaging Spectroradiometer (MODIS) overpasses across different portions of the domain. A detailed comparison of the simulated datasets revealed that the PBL and cloud microphysics schemes both exerted a strong influence on the spatial distribution and physical properties of the simulated cloud fields. In particular, the low-level cloud properties were found to be very sensitive to the PBL scheme while the upper-level clouds were sensitive to both the microphysics and PBL schemes. Overall, the simulated cloud properties were broadly similar to the MODIS observations, with the most realistic cloud fields produced by the more sophisticated parameterization schemes.