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  • Author or Editor: Anita D. Rapp x
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Anita D. Rapp, M. Lebsock, and C. Kummerow

Abstract

How to deal with the different spatial resolutions of multifrequency satellite microwave radiometer measurements is a common problem in retrievals of cloud properties and rainfall. Data convolution and deconvolution is a common approach to resampling the measurements to a single resolution. Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) measurements are resampled to the resolution of the 19-GHz field of view for use in a multifrequency optimal estimation retrieval algorithm of cloud liquid water path, total precipitable water, and wind speed. Resampling the TMI measurements is found to have a strong influence on retrievals of cloud liquid water path and a slight influence on wind speed. Beam-filling effects in the resampled brightness temperatures are shown to be responsible for the large differences between the retrievals using the TMI native resolution and resampled brightness temperatures. Synthetic retrievals are performed to test the sensitivity of the retrieved parameters to beam-filling effects in the resampling of each of the different channels. Beam-filling effects due to the convolution of the 85-GHz channels are shown to be the largest contributor to differences in retrieved cloud liquid water path. Differences in retrieved wind speeds are found to be a combination of effects from deconvolving the 10-GHz brightness temperatures and compensation effects due to the lower liquid water path being retrieved by the high-frequency channels. The influence of beam-filling effects on daily and monthly averages of cloud liquid water path is also explored. Results show that space–time averaging of cloud liquid water path cannot fully compensate for the beam-filling effects and should be considered when using cloud liquid water path data for validation or in climate studies.

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Anita D. Rapp, G. Elsaesser, and C. Kummerow

Abstract

The complicated interactions between cloud processes in the tropical hydrologic cycle and their responses to changes in environmental variables have been the focus of many recent investigations. Most studies that examine the response of the hydrologic cycle to temperature changes focus on deep convection and cirrus production, but recent results suggest that warm rain clouds may be more sensitive to temperature changes. These clouds are prevalent in the tropics and make considerable contributions to the radiation budget and to total tropical rainfall, as well as serving to moisten and precondition the atmosphere for deep convection. A change in the properties of these clouds in climate-change scenarios could have significant implications for the hydrologic cycle. Existing microwave and visible retrievals of warm rain cloud liquid water path (LWP) disagree over the range of sea surface temperatures (SST) observed in the tropical western Pacific Ocean. Although both retrieval methods show similar behavior for nonraining clouds, the two methods show very different warm-rain-cloud LWP responses to SST, both in magnitude and trend. This makes changes to the relationship between precipitation and cloud properties in changing temperature regimes difficult to interpret. A combined optimal estimation retrieval algorithm that takes advantage of the strengths of the different satellite measurements available on the Tropical Rainfall Measuring Mission (TRMM) satellite has been developed. Deconvolved TRMM Microwave Imager brightness temperatures are combined with cloud fraction from the Visible and Infrared Scanner and rainwater estimates from the TRMM precipitation radar to retrieve the cloud LWP in warm rain systems. This algorithm is novel in that it takes into account the water in the rain and estimates the LWP due to only the cloud water in a raining cloud, thus allowing investigation of the effects of precipitation on cloud properties.

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Kevin M. Smalley and Anita D. Rapp

Abstract

Cloud models show that precipitation is more likely to occur in larger shallow clouds and/or in an environment with more moisture, in part as a result of decreasing the impacts of entrainment mixing on the updrafts. However, the role of cloud size in shallow cloud precipitation onset from global satellite observations has mostly been examined with precipitation proxies from imagers and has not been systematically examined in active sensors, primarily because of sensitivity limitations of previous spaceborne active instruments. Here we use the more sensitive CloudSat/CALIPSO observations to identify and characterize the properties of individual contiguous shallow cumulus cloud objects. The objects are conditionally sampled by cloud-top height to determine the changes in precipitation likelihood with increasing cloud size and column water vapor. On average, raining shallow cumulus clouds are typically taller by a factor of 2 and have a greater horizontal extent than their nonraining counterparts. Results show that for a fixed cloud-top height the likelihood of precipitation increases with increasing cloud size and generally follows a double power-law distribution. This suggests that the smallest cloud objects are able to grow freely within the boundary layer but the largest cloud objects are limited by environmental moisture. This is supported by our results showing that, for a fixed cloud-top height and cloud size, the precipitation likelihood also increases as environmental moisture increases. These results are consistent with the hypothesis that larger clouds occurring in a wetter environment may be better able to protect their updrafts from entrainment effects, increasing their chances of raining.

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Tong Ren, Anita D. Rapp, Shaima L. Nasiri, John R. Mecikalski, and Jason Apke

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals from the Terra and Aqua satellites currently provide the largest satellite aerosol dataset for investigating relationships to meteorological phenomena, such as aerosol impact on electrification in deep convection. The usefulness of polar-orbiting satellite aerosol retrievals in lightning inference is examined by correlating MODIS AOD retrievals with lightning observations of the thunderstorms in the summers during 2002–14 over northern Alabama. Lightning flashes during the 1400–1700 local standard time peak period show weak but positive correlations with the MODIS AOD retrievals 2–4 h earlier. The correlation becomes stronger in particular meteorological conditions, including weak vertical wind shear and prevailing northerly winds over northern Alabama. Results show that the MODIS AOD retrievals are less useful in predicting enhanced lightning flash rate for lightning-producing storms than the forecasts of other meteorological variables that are more closely linked to the intensification of convective storms. However, when relatively weaker convective available potential energy (CAPE) is forecast, the probability of enhanced lightning flash rate increases in a more polluted environment, making the knowledge of aerosols more useful in lightning inference in such CAPE regimes. The aerosol enhancement of lightning, if present, may be associated with enhanced convergence in the boundary layer and secondary convection.

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