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At least 55 records · Page 3

The relation of radar to cloud area-time integrals and implications for rain measurements from space

The relationships between satellite-based and radar-measured area-time integrals (ATI) for convective storms are determined, and both are shown to depend on the climatological conditional mean rain rate and the ratio of the measured cloud area to the actual rain area of the storms. The GOES precipitation index of Arkin (1986) for convective storms, an area-time integral for satellite cloud areas, is shown to be related to the ATI for radar-observed rain areas. The quality of GPI-based rainfall estimates depends on how well the cloud area is related to the rain area and the size of the sampling domain. It is also noted that the use of a GOES cloud ATI in conjunction with the radar area-time integral will improve the accuracy of rainfall estimates and allow such estimates to be made in much smaller space-time domains than the 1-month and 5-deg boxes anticipated for the Tropical Rainfall Measuring Mission.

Atlas, David↗

A composite study of Florida thunderstorms, using radar, cloud-to-ground lightning, and surface winds

Two thunderstorms occurring in Florida during the summer of 1987 are studied in order to determine the location of cloud-to-ground (CG) lightning in terms of surface winds and radar reflectivity. Composites of radar, CG lightning locations, and surface winds during the development, mature, and dissipation stages of the storms are presented and analyzed. The relationship between lightning and radar reflectivity is examined. It is noted that the main CG lightning activity region is on the upshear side of the storm in the reflectivity gradient where upward motion is between the convergent gust front and reflectivity center, and lightning avoids areas of maximum reflectivity.

Watson, Andrew I.↗

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

Nguyen, L.↗

A Simple Model of Cirrus Horizontal Inhomogeneity and Cloud Fraction

A simple model of horizontal inhomogeneity and cloud fraction in cirrus clouds has been formulated on the basis that all internal horizontal inhomogeneity in the ice mixing ratio is due to variations in the cloud depth, which are assumed to be Gaussian. The use of such a model was justified by the observed relationship between the normalized variability of the ice water mixing ratio (and extinction) and the normalized variability of cloud depth. Using radar cloud depth data as input, the model reproduced well the in-cloud ice water mixing ratio histograms obtained from horizontal runs during the FIRE2 cirrus campaign. For totally overcast cases the histograms were almost Gaussian, but changed as cloud fraction decreased to exponential distributions which peaked at the lowest nonzero ice value for cloud fractions below 90%. Cloud fractions predicted by the model were always within 28% of the observed value. The predicted average ice water mixing ratios were within 34% of the observed values. This model could be used in a GCM to produce the ice mixing ratio probability distribution function and to estimate cloud fraction. It only requires basic meteorological parameters, the depth of the saturated layer and the standard deviation of cloud depth as input.

Smith, Samantha A.↗

Toward the characterization of upper tropospheric clouds using Atmospheric Infrared Sounder and Microwave Limb Sounder observations

We estimate the accuracy of cloud top altitude (Z) retrievals from the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) observing suite (ZA) on board the Earth Observing System Aqua platform. We compare ZA with coincident measurements of Z derived from the micropulse lidar and millimeter wave cloud radar at the Atmospheric Radiation Measurement (ARM) program sites of Nauru and Manus islands (ZARM) and the inferred Z from vertically resolved Microwave Limb Sounder (MLS) ice water content (IWC) retrievals. The mean difference in ZA minus ZARM plus or minus one standard deviation ranges from −2.2 to 1.6 km ± 1.0 to 4.2 km for all cases of AIRS effective cloud fraction (f A) > 0.15 at Manus Island using the cloud radar only. The range of mean values results from using different approaches to determine ZARM, day/night differences, and the magnitude of f A; the variation about the mean decreases for increasing values of f A. Analysis of ZARM from the micropulse lidar at Nauru Island for cases restricted to 0.05 ≤ f A ≤ 0.15 indicates a statistically significant improvement in ZA − ZARM over the cloud radar-derived values at Manus Island. In these cases the ZA − ZARM difference is −1.1 to 2.1 km ± 3.0 to 4.5 km. These results imply that the operational ZA is quantitatively useful for constraining cirrus altitude despite the nominal 45 km horizontal resolution. Mean differences of cloud top pressure (PCLD) inferred from coincident AIRS and MLS ice water content (IWC) retrievals depend upon the method of defining AIRS PCLD (as with the ARM comparisons) over the MLS spatial scale, the peak altitude and maximum value of MLS IWC, and f A. AIRS and MLS yield similar vertical frequency distributions when comparisons are limited to f A > 0.1 and IWC > 1.0 mg m−3. Therefore the agreement depends upon the opacity of the cloud, with decreased agreement for optically tenuous clouds. Further, the mean difference and standard deviation of AIRS and MLS PCLD are highly dependent on the MLS tangent altitude. For MLS tangent altitudes greater than 146 hPa, the strength of the limb technique, the disagreement becomes statistically significant. This implies that AIRS and MLS “agree” in a statistical sense at lower tangent altitudes and “disagree” at higher tangent altitudes. These results provide important insights on upper tropospheric cloudiness as observed by nadir-viewing AIRS and limb-viewing MLS.

Wu, Dong L.↗

Fast, Space qualified 3000 V modulator for a Cloud Profiling Radar

This paper describes the design approach for the FEM and its performance in EM and Flight configurations. This design is a simple but universal approach which allows the designers to greater flexibility and freedom in designing high swinging voltage space- qualifiable FEM.

CloudSat↗

Cloud profiling radar for the CloudSat Mission

The CloudSat Mission is a new satellite mission jointly developed by NASA, JPL, the Canadian Agency, Colorado State University, and the US AirForce to acquire a global data set of vertical cloud structure and its variability.

vertical profiling↗

Bulk ice characterization using coupled cloud, multiparameter radar, and radiative transfer models

The study demonstrates the potential utility of employing scattering-based passive microwave channels (not less than 37 GHz) to estimate the amount of ice water path that exists above rain in precipitating clouds. This methodology can be used along with lower-frequency emission-based channels to infer the columnar melt water and ice water paths. Portions of the ice column that coexist with cloud water hide the usually steep brightness temperature cooling through this region and inhibit characterization of the total ice column.

Turk, J.↗