Reflectivity and rain rate in and below drizzling stratocumulus

Environmental Research Letters, 2008

Marine stratocumuli make a major contribution to Earth's radiation budget. Drizzle in such clouds can greatly affect their albedo, lifetime and fractional coverage, so drizzle rate prediction is important. Here we examine a question: does a drizzle rate (R) depend on cloud depth (H) and/or drop number concentration n in a simple way? This question was raised empirically in several recent publications and an approximate H 3 /n dependence was observed. Here we suggest a simple explanation for H 3 scaling from viewing the drizzle rate as a sedimenting volume fraction (f) of water drops (radius r) in air, i.e. R = f u(r), where u is the fall speed of droplets at the cloud base. Both R and u have units of speed. In our picture, drizzle drops begin from condensation growth on the way up and continue with accretion on the way down. The ascent contributes H (f ∝ H) and the descent H 2 (u ∝ r ∝ f H) to the drizzle rate. A more precise scaling formula is also derived and may serve as a guide for parameterization in global climate models. The number concentration dependence is also discussed and a plausibility argument is given for the observed n −1 dependence of the drizzle rate. Our results suggest that deeper stratocumuli have shorter washout times.

Journal of Applied Meteorology, 1997

Raindrop images obtained on research flights of the NCAR Electra aircraft in the Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) are analyzed. The drop size distributions, based on the images obtained in 6-s samples (about 750 m of flight track), are used to calculate both radar reflectivity Z and rain rate R. Airborne radar data from the NOAA P-3 aircraft flying in coordination with the Electra are used to categorize the particle-image data according to whether the drop images were obtained in regions of convective or stratiform precipitation. Within stratiform precipitation, the same rain rate could be produced by a drop spectrum dominated by numerous small drops (lower reflectivity) or by a few large drops (higher reflectivity). The reflectivity values varied by as much as 9 dB for a given rain rate. Reflectivity data from the airborne radar and flight-level data reveal that the stratiform regions often contain fallstreaks of about 0.1-2 km in horizontal dimension. The fallstreaks are associated with large-drop spectra and local maxima in reflectivity up to approximately 40 dBZ and in rain rates up to 25 mm h Ϫ1. The fallstreaks extend downward from the melting band and bend with the low-level wind shear, but do not usually reach the surface. Thus, although relatively more uniform than convective regions, stratiform regions can be variable in reflectivity and rain rate at fine spatial scales in both the horizontal and vertical directions. Stratiform regions are therefore best characterized by their ensemble properties rather than the values of individual high-resolution measurements. The variability of stratiform drop size spectra arises primarily from the occurrence of fallstreaks and the discontinuous nature of regions favoring aggregation of snow crystals, and it implies that Z-R distributions associated with convective and stratiform precipitation are not statistically distinct. Thus, separate Z-R relations for convective and stratiform precipitation are not justified, and techniques to distinguish between convective and stratiform precipitation based solely on the characteristics of drop size distributions are not likely to be accurate. The variability of the drop size spectra in tropical precipitation makes an exponential fit to the Z-R relation sensitive to the spatial scale over which Z and R are determined. This sensitivity can be avoided by using a probability-matched Z-R relation. The probability-matched Z-R relation for all the raindrop image data from the Electra collected between altitudes of 2.7 and 3.3 km in TOGA COARE is similar to the Z-R relation obtained at the sea surface in the Global Atmospheric Research Program Atlantic Tropical Experiment.

Atmospheric Measurement Techniques, 2013

This empirical study demonstrates the feasibility of using 89-GHz Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) passive microwave brightness temperature data to detect heavily drizzling cells within subtropical marine stratocumulus. For the purpose of this paper, we define heavily drizzling cells as areas ≥ 6 km × 4 km with C-band Z > 0 dBZ; equivalent to > 0.084 mm h −1 . A binary heavy drizzle product is described that can be used to determine areal and feature statistics of drizzle cells within the major marine stratocumulus regions. Current satellite liquid water path (LWP) and cloud radar products capable of detecting drizzle are either lacking in resolution (AMSR-E LWP), diurnal coverage (MODIS LWP), or spatial coverage (CloudSat). The AMSR-E 89-GHz data set at 6 km × 4 km spatial resolution is sufficient for resolving individual heavily drizzling cells. Radiant emission at 89 GHz by liquid-water cloud and precipitation particles from drizzling cells in marine stratocumulus regions yields local maxima in brightness temperature against an otherwise cloud-free background brightness temperature. The background brightness temperature is primarily constrained by column-integrated water vapor for moderate sea surface temperatures. Clouds containing ice are screened out. Once heavily drizzling pixels are identified, connected pixels are grouped into discrete drizzle cell features. The identified drizzle cells are used in turn to determine several spatial statistics for each satellite scene, including drizzle cell number and size distribution. The identification of heavily drizzling cells within marine stratocumulus regions with satellite data facilitates analysis of seasonal and regional drizzle cell occurrence and the interrelation between drizzle and changes in cloud fraction.

Journal of the Atmospheric Sciences, 2005

In situ and radar data from the second field study of the Dynamics and Chemistry of Marine Stratocumulus (DYCOMS-II) have been used to study drizzle in stratocumulus. Measurements indicate that drizzle is prevalent. During five of seven analyzed flights precipitation was evident at the surface, and on roughly a third of the flights mean surface rates approached or exceeded 0.5 mm day Ϫ1 . Additional analysis of the structure and variability of drizzle indicates that the macroscopic (flight averaged) mean drizzle rates at cloud base scale with H 3 /N where H is the flight-averaged cloud depth and N the flight-averaged cloud droplet number concentration. To a lesser extent flight-to-flight variability in the mean drizzle rate also scales well with differences in the 11-and 4-m brightness temperatures, and the cloud-top effective radius. The structure of stratocumulus boundary layers with precipitation reaching the surface is also investigated, and a general picture emerges of large flight-averaged drizzle rates being manifested primarily through the emergence of intense pockets of precipitation. The characteristics of the drizzle spectrum in precipitating versus nonprecipitating regions of a particular cloud layer were mostly distinguished by the number of drizzle drops present, rather than a change in size of the median drizzle drop, or the breadth of the drizzle spectrum.

The problem of the production of warm rain by collision and coalescence has been studied for over half a century and several processes have been suggested to explain the observed production, which is more rapid than generally possible with models. A straightforward scenario in relatively shallow maritime cumulus clouds is one where cloud drops simply grow by condensation and coalescence, with no appeal to enhancement due to entrainment or turbulence or indeed the presence of giant and ultragiant aerosols that may exist in the boundary layer. However, it is difficult in a field experiment to measure the concentrations of aerosols and the time evolution of the droplet size distribution or reflectivity in individual clouds. The Rain in Cumulus Over the Ocean (RICO) field experiment overcame some of these difficulties due to the abundance of clouds and the statistical sampling strategy at all significant altitudes. In this article, we present the results of the rate of increase in the radar reflectivity in a couple of cases. Comparisons with a cloud model strongly suggest that the development of warm rain can be explained using the observed aerosol distribution alone. Sensitivity studies suggested that giant and ultragiant aerosols were unimportant for the production of rain in these clouds.

Journal of Applied Meteorology, 1997

Raindrop images obtained on research flights of the NCAR Electra aircraft in the Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) are analyzed. The drop size distributions, based on the images obtained in 6-s samples (about 750 m of flight track), are used to calculate both radar reflectivity Z and rain rate R. Airborne radar data from the NOAA P-3 aircraft flying in coordination with the Electra are used to categorize the particle-image data according to whether the drop images were obtained in regions of convective or stratiform precipitation.

Journal of Geophysical Research, 2008

1] This paper focuses on the relation between local sea surface temperature (SST) and convective precipitation fraction and stratiform rainfall area from radar observations of precipitation, using data from the Kwajalein atoll ground-based radar as well as the precipitation radar on board the TRMM satellite. We find that the fraction of convective precipitation increases with SST at a rate of about 6 to 12%/K and the area of stratiform rainfall normalized by total precipitation decreases with SST at rates between À5 and À28%/K. These relations are observed to hold for different regions over the tropical oceans and also for different periods of time. Correlations are robust to outliers and to undersampled precipitation regions. Kwajalein results are relatively insensitive to the parameters in the stratiform-convective classification algorithm. Quantitative differences between the results obtained using the two different radars could be explained by the smoothing in the reflectivity of convective regions due to the relatively large pixel size of the TRMM precipitation radar compared to the size of the convective clouds. Although a dependence on temperature such as the one documented is consistent with an increase in the efficiency of convective precipitation (and therefore consistent with one of the mechanisms invoked to explain the original Iris effect observations) this is but one step in studying the possibility of a climate feedback. Further work is required to clarify the particular mechanism involved. Citation: Rondanelli, R., and R. S. Lindzen (2008), Observed variations in convective precipitation fraction and stratiform area with sea surface temperature,

Journal of Applied Meteorology and Climatology, 2011

Satellite observations are used to deduce the relationship between cloud water and precipitation water for low-latitude shallow marine clouds. The specific sensors that facilitate the analysis are the collocated CloudSat profiling radar and the Moderate Resolution Imaging Spectroradiometer (MODIS). The separation of the cloud water and precipitation water signals relies on the relative insensitivity of MODIS to the presence of precipitation water in conjunction with estimates of the path-integrated attenuation of the CloudSat radar beam while explicitly accounting for the effect of precipitation water on the observed MODIS optical depth. Variations in the precipitation water path are shown to be associated with both the cloud water path and the cloud effective radius, suggesting both macrophysical and microphysical controls on the production of precipitation water. The method outlined here is used to place broad bounds on the mean relationship between the precipitation water path an...

Journal of Geophysical Research, 2000

The discrimination of convective from stratiform tropical oceanic rains by conventional radar-based textural methods is problematic because of the small size and modest horizontal reflectivity gradients of the oceanic convective cells. In this work the vertical air motion measured by an aircraft gust probe is used as a discriminator which is independent of the textural methods. A threshold draft magnitude of •1 m s -1 separates the two rain types. Simultaneous airborne in situ observations of drop size distributions (DSD) made during the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) were used to compute Z, R, and other integral parameters. The data were quality controlled to minimize misclassifications. The convective and stratiform rains, observed just below the melting level but adjusted to surface air density, are characterized by power law Z-R relations (Z = 129R 1'38 (convective) and 224R TM (stratiform)). However, at R < 10 mm h -1, the convective population is essentially coincident with the small-drop size, small-Z portion of the stratiform population. Tokay and Short [1996] found a similar result when their algorithm did not separate the rain types unambiguously at R < 10 mm h -1. The physical reasons for the wide variability of the drop size spectra and Z-R points in stratiform rain and their overlap with that of convective rain are proposed. The subtle distinctions in the microphysical properties and the Z-R relations by rain type could not be found by Yuter and Houze (YH) using the same airborne DSD data set as that in this work and a radar-based textural classification algorithm.

Journal of Geophysical Research, 1999

Time histories of the characteristics of the drop size distribution of surface disdrometer measurements collected at Kapingamarangi Atoll were partitioned for several storms using rain rate R, reflectivity factor Z, and median diameter of the distribution of water content D 0. This partitioning produced physically based systematic variations of the drop size distribution (DSD) and Z-R relations in accord with the precipitation types viewed simultaneously by a collocated radar wind profiler. These variations encompass the complete range of scatter around the mean Z-R relations previously reported by Tokay and Short [ 1996] for convective and stratiform rain and demonstrate that the scatter is not random. The systematic time or space variations are also consistent with the structure of mesoscale convective complexes with a sequence of convective, transition, and stratiforrn rain described by various authors. There is a distinct inverse relation between the coefficient A and the exponent of the Z-R relations which has been obscured in prior work because of the lack of proper discrimination of the rain types. Contrary to previous practice it is evident that there is also a distinct difference in the DSD and the Z-R relations between the initial convective and the trailing transition zones. The previously reported Z-R relation for convective rain is primarily representative of the transition rain that was included in the convective class. The failure of present algorithms to distinguish between the initial convective and the trailing transition rains causes an erroneous apportionment of the diabatic heating and cooling and defeats the primary intent of discriminating stratiform from convective rains.

Journal of Hydrometeorology, 2008

Recent studies using vertically pointing S-band profiling radars showed that coastal winter storms in California and Oregon frequently do not display a melting-layer radar bright band and inferred that these nonbrightband (NBB) periods are characterized by raindrop size spectra that differ markedly from those of brightband (BB) periods. Two coastal sites in northern California were revisited in the winter of 2003/04 in this study, which extends the earlier work by augmenting the profiling radar observations with collocated raindrop disdrometers to measure drop size distributions (DSD) at the surface. The disdrometer observations are analyzed for more than 320 h of nonconvective rainfall. The new measurements confirm the earlier inferences that NBB rainfall periods are characterized by greater concentrations of small drops and smaller concentrations of large drops than BB periods. Compared with their BB counterparts, NBB periods had mean values that were 40% smaller for mean-volume diameter, 32% smaller for rain intensity, 87% larger for total drop concentration, and 81% larger (steeper) for slope of the exponential DSDs. The differences are statistically significant. Liquid water contents differ very little, however, for the two rain types. Disdrometer-based relations between radar reflectivity (Z ) and rainfall intensity (R) at the site in the Coast Range Mountains were Z ϭ 168R 1.58 for BB periods and Z ϭ 44R 1.91 for NBB. The much lower coefficient, which is characteristic of NBB rainfall, is poorly represented by the Z-R equations most commonly applied to data from the operational network of Weather Surveillance Radar-1988 Doppler (WSR-88D) units, which underestimate rain accumulations by a factor of 2 or more when applied to nonconvective NBB situations. Based on the observed DSDs, it is also concluded that polarimetric scanning radars may have some limited ability to distinguish between regions of BB and NBB rainfall using differential reflectivity. However, differential-phase estimations of rain intensity are not useful for NBB rain, because the drops are too small and nearly spherical. On average, the profiler-measured echo tops were 3.2 km lower in NBB periods than during BB periods, and they extended only about 1 km above the 0°C altitude. The findings are consistent with the concept that precipitation processes during BB periods are dominated by ice processes in deep cloud layers associated with synoptic-scale forcing, whereas the more restrained growth of hydrometeors in NBB periods is primarily the result of orographically forced condensation and coalescence processes in much shallower clouds. FIG. 1. Map of the Sonoma County area of northern California showing the primary observing sites for this study. Cazadero (CZD) as at 475 m MSL in the Coast Range Mountains; Bodega Bay (BBY) and Fort Ross (FRS) are near sea level on the coastline. The city of San Francisco is approximately 75 km southeast of CZD.

Journal of Applied Meteorology, 1999

The motivation for this research is to move in the direction of improved algorithms for the remote sensing of rainfall, which are crucial for meso-and large-scale circulation studies and climate applications through better determinations of precipitation type and latent heating profiles. Toward this end a comparison between two independent techniques, designed to classify precipitation type from 1) a disdrometer and 2) a 915-MHz wind profiler, is presented, based on simultaneous measurements collected at the same site during the Intensive Observing Period of the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. Disdrometer-derived quantities such as differences in drop size distribution parameters, particularly the intercept parameter N 0 and rainfall rate, were used to classify rainfall as stratiform or convective. At the same time, profiler-derived quantities, namely, Doppler velocity, equivalent reflectivity, and spectral width, from Doppler spectra were used to classify precipitation type in four categories: shallow convective, deep convective, mixed convective-stratiform, and stratiform.

Journal of Geophysical Research, 1990

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) for January 1979, over the North Atlantic Ocean (40ø-60øN). Concurrent analysis of the SMMR data with the U.S. Air Force 3-Dimensional Nephanalysis (3DNEPH) allows the interpretation of the SMMR-derived liquid water paths and precipitation characteristics in terms of cloud type, cloud fraction, and cloud height. Combining the initialized analyses from the European Center for Medium-Range Weather Forecasting (ECMWF) with the 3DNEPH enables vertical temperature and humidity profiles to be incorporated into the retrievals. The interpretation and presentation of our results are guided by their implications for the parameterization of liquid water content of layer clouds in largescale atmospheric models. The average liquid water paths for middle and low clouds were determined to be 115 and 102 g m '2, respectively, with a maximum value of 1070 g m '2. A comparison of the SMMR-derived values of the liquid water path with the adiabatic liquid water path determined from the 3DNEPH cloud data and the ECMWF temperature profiles indicated that these clouds were for the most part substantially diluted by a combination of precipitation, freezing, and entrainment. Analysis of the liquid water path as a function of temperature showed that clouds with average temperature below 246 K had little liquid water and were inferred to be predominantly crystalline. There was little evidence that cloud liquid water path increases with temperature for cloudiness on a large scale, suggesting that cloud thickness plays the dominant role in determining cloud liquid water path. A total of 8.5% and 4.4% of the total middle and low clouds, respectively, were determined to be raining. Liquid water paths of 350 g m '2 and 500 g m '2 for middle and low clouds, respectively, were determined to be average thresholds for the onset of precipitation. Maximum rain rates for these clouds were determined to be 7 mm h 4. The autoconversion of cloud water to rain water was determined to occur at a rate of 0.001 s 4. INTRODUCHON A current goal in atmospheric modeling is the parameterization of cloud liquid water content so that it can be directly employed in the determination of precipitation and radiative transfer. Both diagnostic [e.g., Harshvardhan et al., 1989] and prognostic [e.g., Sundqvist, 1978] parameterizations have been proposed. The verification of modeled liquid water content requires observations of cloud water content on a large scale, which over most of the globe can only be provided by satellite. Over oceanic regions, satellite microwave measurements

Geophysical Research Letters, 2007

Results of analysis of CloudSat radar data collected during the first three months of operation are described. It is shown that the global tropical oceans (30N-30S) predominantly favor clouds with tops in two layers centered at about 2 and 12 km. Precipitating clouds occur primarily in three modes, a shallow mode that is the most frequent type, as well as a middle and deep mode. Regional features are also discussed. The Indian and western Pacific Oceans exhibit more predominantly high clouds and deeper precipitation features than the eastern Pacific and Atlantic. The occurrence of a mid-level mode of cloudiness and precipitation is shown to vary regionally, being particularly significant in the western Pacific. For all regions examined, precipitating clouds are observed to be deeper than nonprecipitating clouds. Over the global tropical oceans, 18% of the clouds detected by CloudSat produce precipitation.

Atmospheric Chemistry and Physics, 2010

Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003-2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that Cloud-Sat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP∼h 9 ) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP∼h 2 ) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Z max >−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h∼LWP 1/2 ). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20 • S, 85 • W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20 • S, 75 • W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.