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Satellite Observations of an Unusual Cloud Formation near the Tropopause [Journal of the Atmospheric Sciences](Journal of the Atmospheric Sciences Via Acquire Media NewsEdge) ABSTRACT This paper describes observations of a field of deep and regular cloud formations that spans several hundreds of kilometers at the top of a midlatitude frontal system in the North Pacific storm track. Space-based imagery of the event from active and passive measurements reveals smooth, clearly defined cloud lobes approximately 10 km across and 2-4 km deep that resemble upside-down mammatus. These observations, together with theoretical arguments and prior modeling work, suggest that the lobes were part of a deepening turbulent mixed layer that formed as a consequence of strong cloud-top radiative cooling. Over the course of a day, the cloud-top formation evolved to leave behind a sheet of cumuliform cirrus that stretched hundreds of kilometers across. The potential is for such clouds to facilitate mixing across the tropopause, much as cloud-top cooling drives the entrainment of free-tropospheric air into stratocumulus-topped boundary layers. (ProQuest: ... denotes formulae omitted.) 1. Introduction As a consequence of the first and second laws of thermodynamics, all atmospheric processes are slaves to the global requirements that i) incoming and outgoing energy fluxes at the top of the atmosphere (TOA) are in approximate balance and ii) energetic transformations within the Earth's climate system spread available ra- diative energy from concentrated high-energy photons within the solar beam into a more-diffuse and/or lower- temperature thermal radiation that is radiated to space. This is accomplished either by the scattering of radiation or through its thermal absorption and emission at pro- gressively colder temperatures. Atmospheric motions provide an additional mecha- nism for transporting thermal energy to a colder state. Throughout nearly the entirety of the atmosphere's depth, air is sufficiently dense to maintain equilibrium between the internal vibrational and rotational modes of molecules that are excited by radiative absorption and the three modes of molecular translational motion that are sensed meteorologically as temperature. The con- sequence of this equilibrium is that horizontal and ver- tical radiative flux divergence sets up fluid temperature and pressure gradients that lead to some combination of turbulent and laminar atmospheric flows. Clouds are optically dense and spatially and temporally intermittent. They provide the atmosphere with an ex- ceptionally efficient means for establishing sharp pressure gradients that may ultimately lead to radiatively driven atmospheric flows. In fact, because the heating and cooling rates in clouds are so rapid compared to those of the sur- rounding clear skies, such flows often break down into turbulence. The pressure gradients that are established cannot be relaxed through laminar horizontal motions, so vertical mixing develops instead (Schmidt and Garrett 2013). One well-known example is how cloud-top radia- tive flux divergence maintains broad sheets of boundary layer clouds: cloud-top cooling accelerates condensation and contributes to the production of neg- atively buoyant air near cloud top, providing a source of energy that sustains boundary layer overturning. This paper presents a striking case of a deep and peri- odic cloud structure at the top of a large frontal system along the northwestern Pacific storm track. We argue that the formation arose as a consequence of efficient radiative cooling, which led to the development of a convectively overturning mixed layer several kilometers deep. Re- markably, the layer gives the appearance of a field of mammatus lobes, the pendulous features sometimes ob- served hanging from the base of stratiform storm clouds (Schultz et al. 2006). What stands out is the very large size of the lobes and the fact that they protrude upward from the cloud top. The suggestion is that these cloudy formations have the potential to facilitate stratospheric-tropospheric exchange through vigorous turbulent mixing. 2. Observations a. Radar and lidar observations The data used in this study are derived primarily from active measurements from the 94-GHz Cloud Profiling Radar (CPR) aboard CloudSat (Marchand et al. 2008), the two-wavelength-polarization Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Infrared Imager Radiometer (IIR) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)(Winker et al. 2009) positioned within the A-Train constellation of satellites (Stephens et al. 2002). Level 2B CloudSat geometric profile product (2B-GEOPROF) radar reflectivities are used for analysis of the spatial statistics of the cloud field. CloudSat 2B-GEOPROF lidar data (Mace et al. 2009)are used to assess cloud-top statistics. Thermodynamic vari- ables that we analyze below are part of CALIPSO level 1 ancillary data and come from meteorological reanalyses. Figure 1a shows a satellite image from 23 December 2008 of a cloud system located approximately 1000 km east of the coast of Japan between the latitudes 288 and 538N and the longitudes 1608 and 1688E. The satellite imagery is a combination of geostationary data provided by the Na- tional Centers for Environmental Prediction (NCEP) and Advanced Very High Resolution Radiometer (AVHRR; polar) imagery provided by the National Oceanic and Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship System (CLASS) [this imagery is available online through the CloudSat data processing center, the Cooperative Institute for Research in the Atmosphere (CIRA): http://www.cloudsat.cira. colostate.edu/dpcstatusQL.php]. A miniature of the cloudy portion of the system from the CPR on the CloudSat platform is visible at the bottom of the figure and covers the CloudSat-referenced segments 27, 28, and 29. The cloud system is oriented southwest to northeast and is approximately 3000 km long and 1000 km wide. Motion of the system is northeastward. Active instruments from the A-Train sampled the cloud system's width and length seven times between 0223 UTC 22 December and 1421 UTC 24 December. Figs. 1b and 1c show two other geo- stationary views of the cloud system. The overpass between 1517 and 1526 UTC (0317 and 0326 local time) by the CloudSat platform within the A-Train series of satellites offers a detailed view of the cloud system's internal structure, from north to south. Figure 2 shows CloudSat CPR radar reflectivities. The horizontal resolution is around 1.5 km, while the vertical resolution is about 500 m; the radar signal is obtained vertically every 240 m, while the altitude at each point has an uncertainty of approximately 230 m. Radar re- flectivity ranges between 220 and 20 dBZ. The upper boundary of the cloud system shown in Fig. 2 is determined by CALIOP, as taken from the CloudSat 2B-GEOPROF lidar product. Just below this upper boundary, CloudSat radar imagery shows a marked in- ternal structure that lies between 348N, 1628Eand418N, 1648E. Reflectivities in what appear to be lobes are greater than 210 dBZ, largely above the minimum detectable reflectivity factor of 229 dBZ (the calibration accuracy of the instrument CPR is 1.5 dB, while its dynamic range is 70 dB). Two additional pieces of data-data quality and CPR cloud mask-are included with radar reflectivities. These indicate good data quality, meaning that false de- tection of cloud-top lobes should not be expected. The confidence in the radar signal is reaffirmed by the re- markable correlation with the lidar backscattered signal. A closer look at this cloud-top region is shown in Fig. 3, which illustrates radar and lidar views between the alti- tudes of 8 and 14 km. Abscissas are great-circle distances in kilometers obtained from the target's coordinates, with theoriginatthesouthofthecloudsystem.Thecloudtop displays pronounced nearly regularly spaced lobes that protrude upward. The lobe boundaries are apparent from the regions where there is deeper penetration of the lidar within the cloud system and where radar reflectivities are less than 215 dBZ. The cloudy lobes are about 10 km wide and 2-3 km deep. The maximum depth extends to 4 km, for example, around the horizontal location 900 km, where the holes between the lobes extend from a higher top altitude of approximately 13.3 km down to 9.3 km. Assuming that the lobes are part of a turbulent phe- nomenon, the cell aspect ratio of 3-5 suggests high an- isotropy within a gravitationally stratified atmosphere. Cloud classification is traditionally done using the hu- man eye and visible wavelengths. The nearest tool that is available in this case is the CALIOP lidar, and we use it here to compute an ''optical'' boundary for the cloud that roughly corresponds to what might be seen by the human eye. The integrated optical depth starting at the upper boundary is given by t (z) 5 zzt ext532(z)dz,whereext532 is the extinction coefficient at 532 nm inferred from CALIOP measurements and dz 5 60 m is the vertical res- olution of CALIOP. We estimate that the depth at which t equals unity should roughly correspond to the ''visible'' upper envelope of the cloud-top formation, as indicated in Figs. 3a and 3b by a white line. The envelope also indicates a lobed pattern, although less deep and regular than in the radar returns. For example, for the abscissa 1320, a lobe has a 1.5-km vertical depth between altitudes of 11 and 12.5 km. Because the features strongly resemble the mammatus lobes that are commonly seen protruding downward from the underside of thick cirrus anvils (Schultz et al. 2006), we refer to them as mammatocumulus. What is unusual in this case is that the lobes extend upward from the cloud top. b. Meteorological context The meteorological context has been analyzed using Global Modeling and Assimilation Office (GMAO) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis fields. GMAO data (Bloom et al. 2005; Bey et al. 2001) are available with CALIPSO CAL_LID_L2_05kmCPro files and consist of diagnosed temperature, pressure, and humidity fields at the location of each 5-km CALIPSO pixel, vertically interpolated to each lidar-data altitude. Wind and potential vorticity fields are obtained from the ECMWF dataset at a horizontal grid spacing of 0.258 every 6 h and at 12 pressure levels in the troposphere (Dee et al. 2011). A pressure-to-altitude conversion is derived using CALIPSO data. It should be kept in mind that GMAO data are Gridpoint Statistical Interpolation (GSI)-derived data. The GSI system is a var- iational data assimilation system, so clouds are not explicitly considered. Thus, the temperature field does not explicitly reflect the extent to which cloud processes could have modified local thermodynamic properties, except insofar as they are reflected in more sparse atmospheric soundings. As shown in Fig. 4, the reanalysis meteorological data describe the presence of a large anticyclone (1035 hPa) in the northwestern Pacific. The cloud system is west of this anticyclone within a quite strong surface wind field, which turns clockwise around it. The meteorological fields within the cloud system evolve slowly between 1200 and 1800 UTC 23 December, implying that the meteorological data from 1200 UTC shown in Fig. 4 and later correspond approximately to the satellite imagery from 1520 UTC. Figure 5 shows the vertical profile of the GMAO thermodynamic and potential temperature fields superimposed on the coincident CloudSat re- flectivity profile of the cloud system. On the right side of Fig. 5, the rise and drop of isolines of potential and thermodynamical temperatures, respectively (including the 08C bright-band near 47.58N, 1668E), indicate that the cloud system lies along a warm front. The warm front remains evident almost 23 h later (Fig. 12) when active sensors resampled the cloud system at 1420 UTC 24 December. The great-circle distance between the two locations (i.e., their distance over Earth's surface) is 1861 km, implying an average propagation speed for the front of 22.5 m s21. ECMWF data indicate similar values for the horizontal surface wind (see Fig. 7). The frontal cloud system follows an upper-tropospheric jet with maximum winds located between 10- and 12-km alti- tude, as shown in Fig. 6. The wind direction is north- eastward (Fig. 6a), reaching 80 m s21. Figure 7 shows a vertical cross section of the wind field, where in the mammatocumulus region, the horizontal wind is be- tween 30 and 50 m s21 with positive shear. The presence of shear might account for the tilt of some of the lobes visible in Fig. 3b, particularly near the 1250- and 1350-km horizontal markers. The role of shear in the mammato- cumulus production is considered further in the discussion below. The ECMWF-diagnosed vertical wind (color shading on Fig. 7) shows consistency between the location of the cloud system and the area where negative di- vergence of the horizontal winds leads to upward motion. The top of the cloud system observed on 23 December generally lies between 12 and 13.5 km. As shown in Fig. 5, the cloud top pushes up against the tropopause, the alti- tude of which decreases northward. The examination of the reanalyzed potential vorticity field (red lines on Fig. 5) indicates no characteristic signature of a stratospheric intrusion or tropopause fold or evidence of an upper-level front like in Homeyer et al. (2011) and Luce et al. (2012). Over the mammatocumulus region, however, the tropo- pause is diagnosed to be 900 m higher than its surround- ings, reaching 13.2 km over a 100-km-wide area. Above this region, there is a volume of particularly cold air aloft, with a local temperature of 2658C. While suggestive, any inference of a correlation between this tropopause height anomaly, the locally colder temperature, and the exis- tence of the cloud-top lobes should be considered with caution. Meteorological data do not explicitly consider mesoscale cloud dynamics. c. Infrared observation The distinctive mammatocumulus cloud feature is characterized by a highly variable structure with remark- able periodicity and vertical depth in signatures from ac- tive sensors. This high ''activity'' at the top of the cloud system is also apparent in passive infrared observations from the IIR onboard the CALIPSO platform. The IIR instrument measures upward radiances at the wavelengths of 8.65, 10.6, and 12.05 mm within a 69-km swath centered on the lidar track, with a 1 km 3 1 km spatial horizontal resolution. The 2D color plot included in Fig. 6a shows brightness temperatures at 10.6 mm deduced from the IIR measurement in this 69-km swath. Blue represents the coldest brightness temperatures(205K)thatcorrespond to the top of the lobes. Red represents the highest local temperatures (230 K) and corresponds to the deepest gap between lobes. From GMAO data, the local lapse rate is close to the dry adiabatic value at these cold temperatures. The observed brightness temperature difference of 10- 20 K in the mammatocumulus region is thus consistent with the altitude depression of 1-2 km determined at vis- ible wavelengths using the lidar. A 2D color plot of Fig. 6a shows that brightness tem- peratures and cloud-top formations in the southern part of the mammatocumulus region are less organized than in the northern part, where they seem to be arranged into lines oriented northwest-southeast. These linearly orga- nized cloud formations would be oriented perpendicular to the high-altitude wind shown in Fig. 6. We notice the resemblance of this feature of cloud organization into lines to modeling studies of mammatus clouds in sheared environments (Kanak and Straka 2009) and to cirrus bands close to the jet stream (Knox et al. 2010). Where the mammatocumulus formations are organized into cloud lines, we suggest that they be termed mammato- cumulus lucullus.1 d. Cloud structure and periodicity The spectacular cloud-top formation that we de- scribe here has the remarkable feature of being spa- tially regular over a large region approximately 700 km wide. To provide an objective assessment of the characteristic spatial scales associated with this unique region, we apply signal processing techniques to the 10.6-mm thermal emission imagery signal of the cloud system, as measured by the IIR instruments on board CALIPSO. First, we use a wavelet-based tool to objectively characterize and assess the location of this area. Then, we perform a Fourier analysis to identify the dominant periodicity of the cloud-top features. The bottom-right-hand panel of Fig. 8 shows the 1D brightness temperature signal at 10.6 mm over the frontal cloud. It corresponds to the central measure- ments over the 69-km swath (i.e., on the CloudSat- CALIPSO track). We perform first a multiresolution wavelet analysis of this signal. Wavelets have been successfully applied by others for the study of cirrus dynamics and structure (Smith and Jonas 1997; Quante et al. 2002; Wang and Sassen 2008). Here, Meyer func- tions are used as the wavelet basis because of their mathematical consistency with Fourier spectral de- composition (Ferlay et al. 2006). Figure 8 shows the Meyer-based discrete multiresolution analysis of the brightness temperature signal: it is decomposed into an approximation at the chosen resolution of 256 km (top- left-hand panel of Fig. 8), and into finer and finer details at half resolutions (256, 128, 64 km, etc.) down to 2 km, twice the measurement horizontal resolution. Consequently, the brightness temperature signal plotted on the bottom-right- hand panel of Fig. 8 represents exactly the sum of the signals plotted in the nine other panels. Each detail that is extracted is smooth and well localized in frequency space. In the coarse-scale approximation of the analysis (top-left- hand panel of Fig. 8), the mammatocumulus region is characterized by temperatures colder than 220 K. Tem- perature variability is largest at spatial scales between 2 and 16 km and in horizontal locations between 800 and 1500km. Within this mammatocumulus region of high variability that has been objectively identified through wavelet analysis, we perform a Fourier transform of the IIR signal and compute the power spectrum of nine IIR 10.6-mm signals that are centered along the CloudSat-CALIPSO track and spaced by 1 km orthogonal to the track. This power spectrum is shown by the blue line in Fig. 9.For comparison, the black line illustrates the power spectrum of the IIR measurements observed within the cloudy area outside of the mammatocumulus region. Consistent with the multiresolution wavelet analysis, the energy of the brightness temperature signal is largest within the mammatocumulus portion of the cloud system and over spatial scales ranging between 2 and 50 km. What the Fourier analysis reveals in addition to the wavelet analysis is a significant variability peak at scales near 23 km. High power at this scale can be related directly to the more subjectively assessed periodicity of the cloud-top struc- tures shown in Figs. 2 and 3. Over the intermediate por- tion of the mammatocumulus power spectrum, the brightness temperature variability has the characteristic 25/3-power-law behavior that is normally associated with an energetic cascade in isotropic turbulence (Tennekes and Lumley 1972). At spatial scales larger than 20 km, the power of the brightness temperature signal shows only very weak dependence on spatial scale. Outside of the mammatocumulus region, however, a slope close to 25/3 is maintained up to scales of 100 km. Below a scale break at about 6 km, both signals have a spectral slope of ap- proximately 25. This is indicative of a scale break toward sharply increasing smoothness in cloud features at smaller scales. Figure 9 also shows the power spectra of the radar and lidar signals (red and green lines, respectively), cal- culated as a vertical average within the mammatocumulus layers. The altitudes for the calculations are between 12.2 and 12.9 km for the lidar signal and between 11.5 and 13.2 km for the radar signal. The spectrum of the 94-GHz (3200 mm) CPR signal is shifted one decade upward on Fig. 9 because it would otherwise overlay the IIR spectra inside the mammatocumulus region (there is similar sen- sitivity of the infrared and millimeter-wavelength signals to the cloud variability). The one difference is that there is a slightly more pronounced periodicity in the radar signal, with variability maxima at scales of about 23 and 18.5 km. Over the intermediate portion of the spectrum, the radar signal has a spectral slope close to 25/3 and a scale break near 6 km. Below this scale, however, the spectral slope is slightly smaller, with a value of approximately 23.5. The power spectrum of the CALIOP 0.532-mm lidar total at- tenuated backscatter signal shows a 23-km periodicity, although the signal is comparatively weak. Lidar pene- trates less deeply into cloud than thermal or radar signals, so it does not ''see'' as efficiently the deep-lobed structures that are present. At small spatial scales, the spectral slope is close to 25/3 but without any scale break. Our interpretation of these results is that the observed scale break depends on sensor wavelength, because there is a size dependence in the inertial response of cloud and precipitation particles to turbulence. Typically, short- wavelength radiation responds most strongly to the smallest particles of a hydrometeor size distribution. Longer thermal wavelengths respond most strongly to the largest cloud particles, and millimeter-wavelength radar responds most strongly to precipitation. It appears that visible, thermal, and microwave signals are all affected equally by the turbulent motions that affect both cloud and precipitation particles, regardless of particle size, but only provided that the spatial scales of the turbulence are larger than 6 km. At scales smaller than 6 km, the radar signal has higher spatial roughness than the thermal signal, and the visible wavelength signal shows no evidence of any scale break while maintaining a spectral slope of 25/3. We infer from these results that small ice particles act as efficient tracers of the smaller-scale turbulent motions to which heavy precipitation particles respond only weakly. 3. Discussion: Formation mechanisms The observed cloud-top structure is intriguing and raises the question of its formation mechanism. The meteorological data, despite its low resolution, shows broad consistency with satellite measurements. Yet an analysis of the potential vorticity field does not show any tropopause fold and any intrusion of stratospheric air into the troposphere that might lead to an upper- tropospheric increase in convection. The horizontal wind is high in the mammatocumulus area, and there is moderate wind shear (see Fig. 7) but, as we discuss later, the magnitude of shear is insufficient to explain the observed cloud structure. It is unlikely that conditions are met for the onset of Kelvin-Helmholtz instabilities and billows (Luce et al. 2012). Last, there is no apparent source of convective overshooting sufficient to generate a 700-km-wide field of 4-km-deep gravity waves. Instead, the cloud-top structure that we present looks strikingly like mammatus clouds. Mammatus clouds are among the more intriguing of atmospheric phenomena for their dramatic visual appearance, especially when the sun is low on the horizon and the contrast between pouches is at its highest and most colorful. Normally, mammatus lobes are smooth and regularly spaced, protruding downward from cloud base in visible and radar imagery (Martner 1995; Winstead et al. 2001; Schultz et al. 2006). Here we see mammatus-like struc- tures that protrude instead upward from the cloud top. To our knowledge, this is the first time ''upside-down'' mammatus has been described in observations. To examine more closely this cloud-top structure, we analyze retrievals of its properties using the Cloud- Aerosol-Water-Radiation Interactions Center's radar- lidar project (DARDAR) approach. DARDAR uses a synergetic combination of CloudSat , CALIPSO , and MODIS measurements within a variational framework (Delanoë and Hogan 2008, 2010). Cloud products have a 60-m vertical resolution at the CloudSat horizontal footprint resolution of 1.4 km. Figure 10 shows the DARDAR-estimated cloud ice water content (IWC) in milligrams per cubic meter and ice effective radius re in micrometers in the mammatocumulus region. In the up- per part of the cloud, IWC is limited to about 100 mg m23 and re is limited to about 60 mm. The highest values of IWC are seen locally inside the mammatocumulus lobes at altitudes above 12 km. The observed periodicity in IWC and effective radius is consistent with the lidar and radar profile of the cloud top. Holes in the radar profile are associated with small values of IWC # 40 mg m23 and values of re around 30 mm. The tilted characteristic of the lobes is clearly visible in the IWC spatial structure at several locations (e.g., at 1250 and 1350 km). So, what we refer to as mammatocumulus can be defined more objec- tively as high values of IWC and re concentrated into pe- riodic upward-pointing lobes, possibly tilted, where the intervening spaces contain small particles. In general, mammatus clouds have remained some- what of a puzzle. In a review article, Schultz et al. (2006) provided a history of efforts to describe mammatus and outlined a broad variety of possible explanations. The prevailing theory is that evaporative cooling plays a key role. If the air below a cirrus anvil is dry, precipitation sublimates and enhances development of negatively buoyant cloudy thermals. Numerical simulations have borne out this mechanism as providing the necessary ingredients for mammatus-like clouds, given an appro- priate set of initial conditions (Kanak and Straka 2006; Kanak et al. 2008). In the case presented here, however, sublimation of precipitation cannot be responsible for the upwardly protruding cloudy lobes that we observe. Precipitation falls down, not up. Any evaporative cooling of hydro- meteors would propel the cloudy lobes in the wrong direction. Rather, we suggest that the mammatocumulus clouds that we observe might develop instead as a con- sequence of an instability that is driven by local radiative flux divergence (Garrett et al. 2010; Schmidt and Garrett 2013), much as radiative cooling is seen as a driving force for turbulence at the tops of stratocumulus decks (Lilly 1968; Moeng et al. 1995, 1996). In the case of the large cloud frontal system seen here, the instability is created by longwave radiative cooling to space from the cloud top. Because the tops are at a high altitude and above most of the water vapor blanket that insulates Earth, this thick cloud system emits to space essentially as a blackbody with the temperature of the cloud top TCT. Thermal emission downward from the stratosphere is relatively small. Also, because the cloud is essentially a blackbody, the thermal radiation field is isotropic deeper within the cloud interior. This means that any radiative temperature contrast DT~ between the cloud top and the upper atmosphere concentrates radiative cooling to within a thin layer near cloud top, with near- zero radiative heating above and below (Fig. 11). This heating gradient is the engine for a buoyant instability. What follows is a mesoscale circulation that appears to entrain clear air from above the cloud into the cloudy interior. Mammatocumulus are simply the cloudy manifestation of the return circulation. Such radiatively driven entraining circulations have been reproduced numerically, both at cloud bottom and cloud top, and for similar atmospheric conditions to those described here (Garrett et al. 2010; Schmidt and Garrett 2013). Garrett et al. (2010) and Schmidt and Garrett (2013) showed how this problem can be viewed theoretically. Calculation of a dimensionless ''spreading number'' helps to predict the dynamic response of a cloud with finite lateral dimensions when it is heated or cooled at its boundaries: ... (1) Suppose a cloud that floats within a stably stratified clear-sky environment with characteristic buoyancy frequency N 5 [g(duy/dz)/uy]1/2, where uy is the virtual potential temperature and g is the gravitational accel- eration. Radiative flux divergence within the cloud causes a local temperature change at rate H'duy/dt over a depth of cloud h and a width of cloud L. At the top of a deep convective system with cold tops, H can be approximated by the following equation: ... (2) where T~CT is the emission temperature of the cloud top, FY5sT~4 is the downwelling thermal emission from the stratosphere with radiative temperature T~, cp is the specific heat capacity, and r is the air density. Any feed- back associated with latent heating is negligibly small at very cold temperatures (Arakawa and Schubert 1974; Heymsfield and Miloshevich 1991). The e-folding pene- tration depth for the deposition of thermal radiation into cirrus depth h is given by (e.g., Stephens et al. 1990) ... (3) where g is the thermal diffusivity factor for isotropic radiation (;1.7) (Hermann 1980), qi is the ice water mixing, and k(re) is the ice crystal size-dependent mass- specific absorptivity at thermal wavelengths. In general, low values of S , 1 are associated with weak cloud-top cooling and small cloud widths. In this case, pressure perturbations that are created by radia- tive flux divergence can be returned to equilibrium through gradual subsidence while keeping isentropic surfaces approximately flat. Through continuity, the cloud then spreads outward. However, if S . 1, laminar isentropic flows are in- sufficiently rapid to restore radiatively developed pressure gradients to equilibrium. Instead, radiative cooling sets up a gravitational instability. A mixed layer develops and lateral spreading takes the form of turbulent density currents. If the value of S is particularly large, then mammatus-like cloud features develop in the central part of the cloud base and inverted mammatus features de- velop in the central portion of the cloud top. Any potential energy that is added to the central portion of the cloud through radiative flux divergence deepens the turbulent mixed layer faster than horizontal pressure gradients can restore gravitational equilibrium through spreading at the cloud edges. The rate at which the mixed layer deepens is ... (4) or, integrated over time, ... (5) A more general form of this time dependence is given by Turner (1979), their Eq. (9.2.9), which addresses the response of a mixed layer to heating at a boundary. In Garrett et al. (2010), it was shown in numerical simula- tions how mammatus lobes are the visible, cloudy por- tion of the mixed-layer circulations. They develop from an initially quiescent cloud only if values of S are greater than about 1000. In general, such conditions are favored by clouds that are broad (meaning large values of L), dense (meaning small values of h), and for which de- position of radiant energy into the cloud is either much lower or higher than the thermal radiant flux out of the cloud (meaning large values of H). Does the case shown here satisfy the condition of S . 1000 that appears to be required to initiate mammatus-like cloud formations? The DARDAR retrievals shown in Fig. 10 suggest characteristic values for re and IWC in the cloud-top lobes of 40 mm and 100 mg m23, respectively. This im- plies an approximate value for k(re) of 0.03 m2 g21 (Knollenberg et al. 1993). The turbulent region between 900 and 1400 km in Fig. 3a has a cloud-top pressure of approximately 130 hPa and a temperature of 210 K, implying a local air density of 0.22 kg m23. Thus, from Eq. (3), thermal radiation is deposited within a cloud absorption depth of h 5 1/(1.67 3 0.03 3 0.1) ' 200 m. For the heating rate H, radiative fluxes from the CloudSat level 2 ''Fluxes and Heating Rates'' project (2B-FLXHR) lidar indicate downward and upward fluxes at the cloud top of 20 and 110 W m22 respectively. Therefore, the energetic loss rate from the cloud is ap- proximately 90 W m22, and from Eq. (2), this creates a gradient in heating of 2 176 K day 2 1 over the 200-m absorption depth. From GMAO reanalyses within the mammatocumulus region, uy is 332 K and N averages 0.56 3 1022 s21 at altitudes between 10 and 11.5 km. An estimate of the width of the turbulent mammatocumulus cloud-top region is L 5 700 km. Thus, from Eq. (1), the approximate value of S is 6000. Of course, this estimate of S is only approximate because itisbasedinpartonreanalysis estimates of thermodynamic parameters. Nonetheless, numerical simulations described in Garrett et al. (2010) suggest that this value of S is more than sufficient to be associated with a rapidly deepening mixed layer and mammatus cloud formation. Equation (5) suggests that it should take only about 2 h to develop a 2-km mixed layer similar to that which is observed, at which point, from Eq. (4), the layer would continue to deepen at a rate of about 30 cm s21. Wind shear can act as an additional contributing fac- tor for mixed-layer deepening, and moderate wind shear can even help organize mammatus lobe features into convective rolls (Kanak and Straka 2009). One way to evaluate the relative contributions of shear and buoyancy to turbulence generation is to calculate the local value of the Richardson number within the layer, as defined by Ri 5 N2/[(dU/dz)2 1 (dV/dz)2], where U and V repre- sent the horizontal wind speeds. Values of Ri . 0.25 have a static stability that is too high for shear-generated turbulence to dominate the local flow (Emanuel 1994). While we do not have direct measurements of the local wind shear in the mammatocumulus region, in- terpolated ECMWF reanalysis data from Fig. 7 provide a vertical profile of the horizontal wind speeds at 1200 UTC 23 December, 3.5 h prior to the A-Train overpass. The wind profile appears to be very steady at this loca- tion between 1200 and 1800 UTC. From this vertical profile, we obtained for [(dU/dz)2 1 (dV/dz)2] a value of around 5 3 1025 s22, with low variability within the mammatocumulus area. Compared to the observed range of values for N2, implied values for the Richardson number are approximately 0.63. This suggests that shear is very unlikely to have played a dominant role in the mixed-layer development. Regarding the aspect ratio and periodicity of the mammatocumulus lobes, there are obvious similarities here to the Rayleigh-Bénard convection that can be driven by an externally imposed vertical temperature gradient (Müller and Chlond 1996). A characteristic lobe separation of 20 km suggests that the upward component of the Bénard-like cells has a 10-km hori- zontal dimension. Lobe heights range from 1.5 to 3 km in the radar and lidar data, suggesting an aspect ratio be- tween 3 and 7. Similar aspect ratio values have been observed in the planetary boundary layer and in laboratory-scale flows (Cieszelski 1998). 4. Conclusions This study has identified an unusual cloud formation at the top of a large frontal cloud system within the North Pacific storm track. In active 94-GHz space-based radar imagery, the features bear a remarkable resemblance to mammatus clouds, with the notable exception that the cloudy lobes protrude upward rather than descending downward. We term these lobes mammatocumulus for their resemblance in shape to mammatus. The formation mechanism for mammatus clouds that is often provided is one that starts with an initial in- stability at the cloud base where air has become gravi- tationally loaded by precipitation (Kanak et al. 2008). Because they point upward, the mammatocumulus lobes that are described here cannot be due to this mechanism. Instead, an alternative explanation appears to be at play where the instability is driven by powerful longwave radiative flux divergence at cloud top. If a cold cloud is especially broad and dense, then theoretical and nu- merical arguments suggest that the rapid cloud-top ra- diative cooling will drive downward-descending clear air to create a turbulent mixed layer; cloudy features in the upwelling component of the resulting circulations re- semble mammatus lobes (Garrett et al. 2010; Schmidt and Garrett 2013). In addition to their direction, what is notable in the case described here is that the observed lobes are remarkably large, with a characteristic width of about 10 km and a height of between 1.5 and 3 km. Such clouds may be more than just a dramatic exam- ple of interactions between radiation, clouds, and at- mospheric dynamics. Figure 12 shows a CloudSat CPR transect of the frontal cloud system 1 day later as it progressed northeastward (see Fig. 1c). Mammatocumulus features continue to be evident at the frontal system top. However, there appear to be regions where the lower portion of the cloud system has entirely decayed, above which the mammatocumulus features have lingered as a cirrocumulus deck that is several hundreds of kilo- meters in horizontal extent. A full explanation for this cloud evolution might best be addressed using a numerical model. What these ob- servations suggest is that the radiative forces that ini- tially created the mammatocumulus mixed layer were long lived and that they continued to sustain cellular features long after the parent cloud had disappeared. If so, mammatocumulus clouds might ultimately be linked to an exchange of air between the troposphere and stratosphere (Holton et al. 1995). An analogous phenomenon could be mixing across a stratocumulus-topped boundary layer where cloud-top radiative cooling drives both boundary layer turbulence and cloud-top entrainment (Lilly 1968; Moeng et al. 1995). Sometimes such entrainment creates deep holes of free-tropospheric dry air that penetrate hundreds of meters into the stratocumulus interior (Gerber et al. 2005). The tops of stratocumulus tend not to be as smooth as mammatocumulus, but this may only be be- cause the feedback from latent heat release becomes negligible at very cold temperatures (Heymsfield and Miloshevich 1991). With mammatocumulus and strato- cumulus, however, a broad, dense cloud layer radiates efficiently into relatively dry air aloft. This creates tur- bulence, entrainment, and mixing along an interface between two distinct atmospheric layers. The possibility of such an exchange between the tro- posphere and stratosphere might be considered less important if the observed cloud structure were very rare, but this is almost certainly not the case. In fact, a very similar example of this cloud-top structure was seen on the same day between 1457 and 1500 UTC to the southeast of Greenland (Fig. 13). Acknowledgments. 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Hunt, and S. A. Young, 2009: Overview of the CALIPSO mission and CALIOP data processing algorithms. J. Atmos. Oceanic Technol., 26, 2310-2323, doi:10.1175/ 2009JTECHA1281.1. Winstead, N. S., J. Verlinde, S. T. Arthur, F. Jaskiewicz, M. Jensen, N. Miles, and D. Nicosia, 2001: High-resolution airborne radar observations of mammatus. Mon. Wea. Rev., 129, 159-166, doi:10.1175/1520-0493(2001)129,0159:HRAROO.2.0.CO;2. NICOLAS FERLAY Laboratoire d'Optique Atmosphérique, Université Lille 1, Sciences et Technologies, Villeneuve d'Ascq, France TIMOTHY J. GARRETT University of Utah, Salt Lake City, Utah FANNY MINVIELLE Laboratoire d'Optique Atmosphérique, Université Lille 1, Sciences et Technologies, Villeneuve d'Ascq, France (Manuscript received 13 November 2013, in final form 11 June 2014) Corresponding author address: Nicolas Ferlay, Laboratoire d'Optique Atmosphérique, bâtiment P5, Cité Scientifique, Ville- neuve d'Ascq, 59655 CEDEX, France. E-mail: [email protected] DOI: 10.1175/JAS-D-13-0361.1 (c) 2014 American Meteorological Society |