GOES 12 observations of convective storm variability andevolution during the Tropical Composition, Cloudsand Climate Coupling Experiment field program

Kristopher M. Bedka1 and Patrick Minnis2

Received 18 September 2009; revised 11 March 2010; accepted 5 April 2010; published 3 September 2010.

[1] This study characterizes convective clouds that occurred during the TropicalComposition, Clouds and Climate Coupling Experiment as observed within GOES imagery.Overshooting deep convective cloud tops (OT) that penetrate through the tropicaltropopause layer and into the stratosphere are of particular interest in this study. The resultsshow that there were clear differences in the areal coverage of anvil cloud, deep convection,and OT activity over land and water and also throughout the diurnal cycle. The offshorewaters of Panama, northwest Colombia, and El Salvador were the most active regions forOT‐producing convection. A cloud object tracking system is used to monitor the durationand areal coverage of convective cloud complexes as well as the time evolution of theircloud‐top microphysical properties. The mean lifetime for these complexes is 5 hours, withsome existing for longer than 16 hours. Deep convection is found within the anvil cloudduring 60% of the storm lifetime and covered 24% of the anvil cloud. The cloud‐top heightand optical depth at the storm core followed a reasonable pattern, with maximum valuesoccurring 20% into the storm lifetime. The values in the surrounding anvil cloud peaked ata relative age of 20%–50% before decreasing as the convective cloud complex decayed.Ice particle diameter decreased with distance from the core but generally increased withstorm age. These results, which characterize the average convective system during theexperiment, should be valuable for formulating and validating convective cloud processmodels.

Citation: Bedka, K. M., and P. Minnis (2010), GOES 12 observations of convective storm variability and evolution during theTropical Composition, Clouds and Climate Coupling Experiment field program, J. Geophys. Res., 115, D00J13,doi:10.1029/2009JD013227.

1. Introduction

[2] Recent observations have shown that stratosphericwater vapor (WV) has been increasing over at least the lasthalf century [Oltmans et al., 2000; Rosenlof et al., 2001], sounderstanding its sources and sinks is crucial for climatechange studies. The 2007 Tropical Composition, Clouds andClimate Coupling Experiment (TC4) in Costa Rica wasdesigned to address a number of questions related to theinteractions among convection, clouds, and humidity in thetropical tropopause layer (TTL) and lower stratosphere [Toonet al., 2010]. Changes in water vapor within the TTL can playan important role in modulating the climate since water vaporis the most powerful greenhouse gas in the atmosphere.Understanding how water behaves in the TTL is one key tobetter understanding the impacts of greenhouse gases onglobal climate change.

[3] Overshooting deep convective cloud tops that penetratethrough the TTL and into the stratosphere have been recog-nized as a significant source of lower stratospheric watervapor. For example, by analyzing aircraft measurements,Dessler [2002] demonstrated that up to 60% of the watervapor crossing the 380 K potential temperature surface at∼17 km was detrained above 15 km. In a later studyemploying airborne measurements, Corti et al. [2008]showed that ice particles from overshooting tops reached ashigh as 18.8 km. Gettelman et al. [2002] used satellite data toestimate that overshooting tops cover ∼0.5% of the tropicsand penetrate up to 1.5 km into the stratosphere. Setvak et al.[2008] employed satellite radiances to show that midlatitudedeep convective clouds also inject some of their water vaporinto stratosphere. These and other empirical results are con-sistent with a variety of modeling studies [e.g., Wang, 2003;Jensen et al., 2007; Chemel et al., 2009] that estimate themoisture balance of the TTL and lower stratosphere in thepresence of overshooting convection.[4] The water vapor and ice crystals introduced into the

TTL by overshooting convection are thought to be respon-sible for the thin, often subvisible, cirrus above 14 km in thetropics [e.g., Wang et al., 1996; Liu, 2007]. These clouds,

1Science Systems and Applications Inc., Hampton, Virginia, USA.2NASA Langley Research Center, Hampton, Virginia, USA.

Copyright 2010 by the American Geophysical Union.0148‐0227/10/2009JD013227

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which are characterized as having very small ice crystals [e.g.,Wang et al., 1996], are thought to form from a combination ofeffects including the direct injection of ice crystals and, moreindirectly, convective generated gravity wave pulses cloudsabove the main convective cloud tops [Garrett et al., 2006].Fujita [1982] described these clouds as “above anvil cirrusplumes” and/or “jumping cirrus.” Wang [2007] used a cloudmodel to show that breaking gravity waves atop a deepconvective storm can cause some water vapor to detach fromthe storm cloud and remain in the stratosphere. This watervapor can condense to form a cloud at levels up to 3 km abovethe anvil [Levizzani and Setvák, 1996]. The above anvil cirrusplumes can extend over 100 km away from the overshootingtop (OT) source region (see Figure 1). However, the mech-anisms that maintain these thin TTL clouds remain elusive.[5] It has been shown by many researchers [e.g., Short and

Wallace, 1980; Minnis and Harrison, 1984; Alcala andDessler, 2002; Liu and Zipser, 2005; Liu et al., 2008] thatthe deepest convection over tropical land areas peaks duringthe late afternoon and, over ocean, during the 6 hours afterlocal midnight. Because TC4 was designed to examine theinteractions of convection and the TTL, but was limitedlogistically to flights only during daytime, the aircraft mea-surements did not sample the complete diurnal cycle. Mostflights ended at or before 1600 LT, with only one missionextending to 1700 LT [Toon et al., 2010]. In addition tomissing a large portion of the diurnal cycle of convection, theaircraft also sampled only a small portion of each stormsystem that was encountered during the flights. To fill in thediurnal cycle and provide a large‐scale characterization of theconvection over the TC4 domain, it is necessary to employgeostationary satellite measurements. Although they do notprovide the fine detail available from the in situ and remotesensing measurements aboard the aircraft, satellite measure-ments can be used to infer much about the context and broaderimplications of the aircraft data. P. Minnis et al. (Cloudproperties determined from GOES and MODIS data duringTC4, submitted to Journal of Geophysical Research, 2010a)provided a general overview of the clouds observed from

geostationary satellites during TC4, but did not focus spe-cifically on the properties of the convective systems (e.g.,areal coverage, OT activity, cloud‐top height and micro-physical variability) over the diurnal cycles or lifetimes ofdeep convection. Such information is important for obtaininga more comprehensive picture of TTL‐convection interac-tions and for guiding modeling studies of tropical convection.[6] The purpose of this paper is to characterize convective

clouds that developed during the TC4 experiment as observedby the Twelfth Geostationary Operational EnvironmentalSatellite (GOES 12). We seek to determine (1) the locationsof frequent OT activity throughout the diurnal cycle, (2) thediurnal variability of anvil cloud, deep convective cloud, andOT areal coverage, (3) the characteristic size and durationof individual thunderstorm complexes, and (4) the temporalevolution and spatial variability of satellite‐derived cloud‐topproperties throughout the lifetime of a convective cloudcomplex. A technique exploiting the water vapor and infraredwindow bands of GOES 12 [Setvak et al., 2007] is used hereto detect OTs as this method provides a direct inferenceof moisture present in the TTL. The following sectionsdescribe the data sets and methodology used to conduct thisstudy in addition to the primary results.

2. Data and Methodology

[7] Signatures in multispectral weather satellite imageryindicate the presence of OTs and moisture transport intothe TTL. OTs exhibit a lumpy or “cauliflower” texturedappearance in visible and near‐infrared channel imagery asthey can be up to 2 km higher than the surrounding anvilcloud [Heymsfield et al., 1991]. OTs are also inferred throughthe presence of a small cluster of very cold brightness tem-peratures (BTs) in the ∼11 mm infrared window (IRW)region. OTs continue to cool at a rate of 7–9 K km−1 as theyascend into the lower stratosphere, causing them to be sig-nificantly colder than the surrounding anvil cloud tempera-ture [Negri, 1982; Adler et al., 1983; Bedka et al., 2010].[8] The WV‐IRW brightness temperature difference

(BTD) technique, which employs the difference between the6 and 7 mmWVabsorption channel BTminus the 11mm IRWchannel BT, has been described extensively for objectivedetection of OT clouds [Fritz and Laszlo, 1993; Ackerman,1996; Schmetz et al., 1997; Setvak et al., 2007; Martinet al., 2008]. Generally, the BTD between these two chan-nels results in a value below zero, since the WV channelweighting function usually peaks at higher altitudes and atlower temperatures than that of the IRW channel. Positivevalues of this BTD have been shown to identify OTs. Thereasons for this correlation are that (1) the atmospheric tem-perature profile warms with height in the lower stratosphere,(2) water vapor is forced into the lower stratosphere at levelsabove the physical cloud top by the overshooting stormupdraft, (3) this water vapor emits at the warmer stratospherictemperature whereas emission in the IR window channeloriginates from the colder physical cloud top, and (4) posi-tive differences between the warmer WV and colder IRWBTs can therefore reveal where overshooting is occurring.The aforementioned literature describing the WV‐IRW BTDmethod indicates that the required WV‐IRW BTD thresh-old for OT detection can vary depending upon satelliteinstrument spatial resolution and spectral channel coverage,

Figure 1. A three‐channel composite of GOES 8 visible,water vapor, and infrared window imagery across the U.S.Great Plains showing a row of thunderstorms with anvil topplumes (indicated by white arrows) at 0015 UTC on 6 May2002. From Wang [2007].

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intensity of the convective updraft, stratospheric lapse rate,and water vapor residence time in the stratosphere. For 4 kmGOES imagery, a BTD value ≥1 K is shown to relate to thepresence of overshooting [Martin et al., 2008], whereas alarger value (2–3 K) is a better indicator of overshootingfor higher‐resolution imagers [Setvak et al., 2007]. The 1 Kcriterion is used in this study for objective OT identification.[9] An example of the WV‐IRW BTD OT detection

product is provided by Figure 2 for a storm that occurredduring the TC4 experiment at 1324 UTC on 24 July 2007.An OT is evident in the GOES 12 visible channel image

(Figure 2a) at the center of the convective cloud (∼6.9°N,86.5°W) and is detected by the WV‐IRW BTD method(Figure 2b). The Cloud Physics Lidar (CPL) instrumentaboard the NASA ER‐2 aircraft observed this cloud atapproximately the same time of the GOES image. The CPLcloud‐top height retrieval verifies the presence of this OTwhich has a peak height that extends ∼0.6 km above thesurrounding thick cirrus anvil cloud (Figure 2c). After reviewof all aircraft observations during the entire TC4 experiment,it has been determined that this was the only OT simulta-neously observed by both GOES and research aircraft so it is

Figure 2. (a) Contrast‐enhanced GOES 12 1 km visible channel image on 24 July 2007 at 1324 UTC fea-turing a convective cloud complexwith an overshooting top. (b)Water vapor (WV)‐infrared window (IRW)brightness temperature difference (BTD)‐based overshooting deep convective cloud‐top (OT) detec-tions (red) with the flight track of the ER‐2 aircraft (blue squares) overlaid atop the visible image fromFigure 2a. The beginning of the ER‐2 flight segment is at 1321 UTC in the northwest of the image and endsat 1327 UTC in the southeast. The aircraft positions are plotted at ∼15 s intervals. (c) ER‐2 cloud physicslidar (CPL) cloud‐top height retrievals from 1321 to 1327 UTC for the highest CPL cloud layer. The over-shooting top highlighted in Figure 2a and detected in Figure 2b is evident in the CPL retrieval.

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not possible validate OT detection accuracy in a compre-hensive manner during TC4.

2.1. Data

[10] To characterize the diurnal variability of the convec-tive clouds, data from half hourly, 4 kmGOES 12 imagery areanalyzed over a subregion of the greater TC4 experimentsatellite domain (Minnis et al., submitted manuscript, 2010a)extending from 3°N to 18°N latitude and 77°W to 92°Wlongitude. The 22 day time period, 18 July–8 August 2007,

analyzed in this study encompasses all of the TC4 tropicalflight days. The 10.7 mm IRW channel pixel BTs are used to(1) determine anvil cloud and deep convective cloud domainfractional coverage and (2) define cloud objects that aretracked from the time of first storm detection until decay. Thecorresponding 6.5 mmWV channel BTs are used to computethe WV‐IRW BTD, which defines OT locations for thisstudy. The GOES 12 data used in this study were provided bythe University of Wisconsin‐Madison Space Science andEngineering Center.[11] Cloud properties retrieved from the daytime GOES 12

imagery are used to characterize the micro‐ and macro-physical variations of convection during TC4. The param-eters of interest are the cloud‐top height Zt, optical depthCOD, ice crystal effective diameterDe, and the ice water pathIWP. Their values were retrieved by Minnis et al. (submittedmanuscript, 2010a) using the visible‐infrared‐shortwave‐infrared technique (VIST), a variant of the four‐channelmethod of P. Minnis et al. (CERES Edition‐2 cloud propertyretrievals using TRMM VIRS and Terra and Aqua MODISdata, part I: Algorithms, submitted to IEEE Transactions onGeoscience and Remote Sensing, 2010b). The postexperi-ment retrievals were used here. Since the VIST uses the3.9 mm channel to retrieve De, the values represent the icecrystal sizes only in the upper part of the clouds. The IWPwascomputed as a function of De and COD. The method ofMinnis et al. [2008] was used to estimate cloud‐top heightfrom IRW BT for optically thick clouds.[12] It is beyond the scope of this paper to validate theVIST

microphysical products used in this study, but previousstudies have investigated the relative accuracy of VIST rel-ative to aircraft and spaceborne observations. Garrett et al.[2005] show good agreement between VIST De and aircraftobservations within a thick convective cirrus anvil cloud.Waliser et al. [2009] show that VIST retrievals of IWP arecomparable to those retrieved via CloudSat Cloud ProfilingRadar data. Mace et al. [2005] and Minnis et al. (submittedmanuscript, 2010b) show good agreement in microphysicalproperties for thin cirrus. More details of the retrievals andtheir errors can be found in the work of Smith et al. [2008],Chang et al. [2010], Yost et al. [2010], and Minnis et al. (sub-mitted manuscript, 2010a).

2.2. Methodology

[13] Before we begin the discussion of the methodology,we will review and introduce acronyms and terminology thatwill be used throughout the remainder of this paper. Figure 3provides a schematic that illustrates the cloud types thatwould be identified through the use of the following criteria:(1) anvil cloud (AC), pixel with an IRW BT ≤ 230 and IRWBT > 215 K; (2) anvil cloud object (AC object), a contiguousarea of at least 50 pixels with IRW BTs ≤ 225 K; (3) deepconvection (DC), pixel with an IRW BT ≤ 215 K; (4) deepconvection object (DC object), a contiguous area of at least25 pixels with IRW BTs ≤ 215 K; (5) extremely deep con-vection (extreme DC), pixel with an IRW BT ≤ 200 K;(6) overshooting top (OT), pixels with a WV‐IRW BTD ≥1 K; and (7) convective cloud complex, a generic term used torefer to a region of deep convective cloud in a satellite image.[14] The satellite‐observed characteristics of convection

present during the TC4 experiment are investigated in three

Figure 3. (top) GOES 12 1 km resolution visible channelimage at 1315 UTC on 31 July 2007. The purple, magenta,blue, and green contours define pixels that meet the anvilcloud (AC), AC object, deep convection (DC), and OT cri-teria, respectively. No extreme DC are present at this time.(bottom) Color‐enhanced GOES 12 4 km resolution IRWbrightness temperature (BT) imagery from the same time andwith the same contour definitions as Figure 3 (top). The BTrange associated with the color enhancement is provided atthe bottom.

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ways. The first analysis involves determining the fractionalcoverage of AC, DC, and OT over the TC4 subdomaindescribed in the previous section. The purpose of this analysisis to characterize the spatial extent of DC and AC as well as toexamine the diurnal and spatial cloud variability during TC4.The total numbers of AC, DC, and OT pixels are computedfor each of the 48 images and the fractional coverage iscomputed by dividing these values by the total number ofGOES 12 pixels in the domain. The areal coverage of extremeDC pixels is used to help interpret the AC and DC arealcoverage results. A 1 km terrain map is interpolated to the4 km GOES 12 resolution and navigation and is used toseparate land and ocean to understand differences in con-vective activity over these two surfaces. The 215 K BT cri-terion used to define DC was also used by Fu et al. [1990],Zhang [1993], and Martin et al. [2008]. Rickenbach et al.[2008] experimented with IRW BT values ranging from240 to 220 K to define AC using GOES 12 observa-tions collected during the Cirrus Regional Study of TropicalAnvils and Cirrus Layers‐Florida Area Cirrus Experiment(CRYSTAL‐FACE). They show that the areal coverageof clouds that meet a given BT criterion increases withincreasing BT, but the timing of maximum areal coveragedoes not change significantly when the BT criteria wereadjusted by ±5 K. Nasiri et al. [2002] used a 230 K thresholdas the basis for radiative transfer calculations used to modelthe microphysical properties of cirrus clouds.[15] For the second analysis, convective cloud complexes

are defined as coherent “objects”within the IRW imagery andare objectively tracked to determine cloud complex lifetime,duration of DC, and maximum cloud areal coverage. TheWarning Decision and Support System, Integrated Informa-tion (WDSS‐II [Lakshmanan et al., 2007]) is the tool usedhere to define and track these objects. The component ofWDSS‐II used in this study employs a hierarchical K meansclustering method to identify objects at a user specifiedminimum spatial scale and BT range. Motion estimatesare obtained by maximizing the correlation of translatedobjects to the images at previous time periods, and smoothedover time using a Kalman filter [Lakshmanan et al., 2003].Objects are matched across frames by greedy optimization ofprojected position error and longevity. Lakshmanan et al.[2009] and Lakshmanan and Smith [2010] provide detaileddescriptions of the WDSS‐II object definition and trackingmethodology.[16] Objects are assigned an identification (ID) number by

WDSS‐II and object properties associated with this IDnumber are tracked from the time of first object detection untildecay. It is possible that within the same convective cloudcomplex, one region of DCmay be decaying and warm whileanother is developing nearby. Since a 215 K threshold is usedto define DC objects, theWDSS‐II systemwould define thesetwo DC regions as separate objects with differing ID numb-ers, even though the two objects may have some relation toand interaction with each other. We handle this by trackingthe entire AC as an object, which helps to maintain the timeseries throughout the lifetime of the convective cloud com-plex. Though the definition of an AC object may seeminconsistent with the AC definition (215–230 K) used in theaforementioned domain areal coverage analysis, the authors’experience with satellite imagery of convective clouds and

use of the WDSS‐II indicates that a warmer threshold wouldoften cause AC from distant convection to merge, producingunnaturally large objects that do not represent a single con-vective cloud complex. When two or more DC objects arefound within one larger AC object at the same time, the arealcoverage and duration of the two DC objects are combined.[17] The third component of this analysis involves analysis

of the temporal evolution and spatial variability of the VISTcloud properties for individual convective cloud complexes.The analysis begins with finding the location of the minimumIRW BT in the AC object, which is considered the “core” ofthe convection. Only the coldest object BT is considered ifmore than one DC object is found within an AC object. Themean cloud‐top height, ice crystal effective diameter, icewater path, and optical depth are computed in a 3 × 3 pixelbox surrounding the core. These values, rather than singlepixel values at the core areas, are recorded for the 0 km radiusdata point. The next step is to analyze the cloud properties atincreasing radii from the core. The mean cloud properties arecomputed within 10 kmwide concentric rings at 10 km radiusintervals from the core out to a 100 km radius. For example,the first ring would include pixels at a distance between 5 and15 km, the second would include those from 15 to 25 km,continuing out to 100 km.[18] We repeat the above process for each image where the

AC object is present in the imagery. As anAC object can existfor a wide range of time periods (1–12 or more hours), thetime of each image where the object is present is normalizedto a number between 0 and 10, with 0 corresponding to thetime of first detection and 10 corresponding to the last imagebefore convection decay. For an object with a lifetime of6 images, the VIST properties from the first image areassigned to time bin 0 and those from the last image areassigned bin 10. The four remaining images are assignedto bins, 2, 4, 6, and 8 as the object had lived 20%, 40%, 60%,and 80% of its lifetime at each of these intervals, respectively.If an object is present for longer than eleven 30 min images(i.e., 5 hours), then VIST properties from multiple imagescould be assigned to the same bin. In this case, the data areaveraged so that one data point resides in each bin. Includedin this analysis are AC objects with a duration of ≥3 hoursthat existed at solar zenith angles ≤76°. The 76° criteria limitsthis to a “daytime‐only” analysis and is found to minimizebiases in low‐light conditions within the VIST algorithm.These criteria limit our sample size to 127 out of the 877 total(to be described later) AC objects. After the object lifetimeis normalized, the average properties of all 127 objects arecomputed at each of the 11 time intervals and the 11 radiito form a composite that shows cloud temporal evolutionand spatial variability throughout the convective complexlifetime.

3. Results and Discussion

3.1. Distribution and Areal Coverage of DeepConvection

[19] The average diurnal variations in the domainwidefractional coverage of AC, DC, extreme DC, and OT areshown in Figure 4. Over land, the AC, DC, and OT pixelsoccupy the maximum area within an hour of 1800 LT.Extreme DC and OT activity peaks at 1715 LT and the areal

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Figure 4. Fractional coverage of AC, DC, extreme DC, and OT pixels over (top) water and (bottom) landwithin the Tropical Composition, Clouds and Climate Coupling Experiment (TC4) domain over the fullduration of the 18 July–8 August 2007 study period. The black (shaded) lines correspond to data rangeson the left (right) y axis. Symbols plotted atop the lines are defined within the legend. Note the differencein y‐axis scale between the top and bottom.

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expansion of DC continues for an hour until 1815 LT. As theDC weakens, the cloud tops warm, but convectively inducedmomentum still causes the AC to expand further until itreaches its peak extent 1 hour later, on average. The patternof OT activity mirrors that of the DC rather than the extremeDC, as an OT can have an IRW BT > 200 K. A secondarymaximum in extreme DC occurs between 1900 and 2100 LTwhile DC is seemingly dissipating. This will be examined inmore detail below.[20] Over water, there is a clear maximum in extreme DC

and OT activity during the night and early morning hours.The pattern shown by the OT line would suggest thatdevelopment of strong convection occurs near 0000 LT andincreases in coverage through 0600 LT. As the convec-tion continues to develop, the DC expands to peak area near0900 LT. After the DC dissipates after 0900 LT, the con-vectively induced momentum continues to expand the cloudwhile it decays and warms into the BT range classified as AC.The AC area peak lags that of the DC by 5 hours, which islonger the lag observed over land (2 hours). The increasein convection activity in coastal regions over land during theearly afternoon is likely producing AC over the offshorewaters. This fact, in combination with the still expanding anddissipating AC over water, may be biasing the peak toward alater time than would occur in the absence of a convectivelyactive land region.[21] Though the criteria chosen to identify AC and DC in

this study have been used to analyze these cloud types inprevious studies, Figure 5 shows the impact of varied BTthresholds on the AC and DC areal coverage results duringTC4. As expected, when colder BT criteria are used, the arealcoverage of DC and AC generally decreases. The clear sep-aration in time of peakAC andDC coverage suggests that twodifferent cloud types are being identified. The timing of peakcoverage remains very consistent regardless of BT criteriaover land (Figure 5, top). Over water, peak coverage of ACand DC is earlier when colder BT criteria are used (Figure 5,bottom). This result is similar to that of Rickenbach et al.[2008] for CRYSTAL‐FACE who found that clouds withwarmer BTs reached their maximum area 1–2 hours after thepeak areal coverage of colder cloud regions due to anvil cloudexpansion. Nevertheless, despite this variability, the resultsproduced by a change in the AC and DC BT criteria do notcontradict the primary results from Figure 4, namely theexistence of a daytime DC peak over land and nighttime DCpeak over water.[22] Figure 6 shows the locations of OT detections during

the afternoon, evening, early morning, and late morninghours, which facilitates interpretation of the patterns shown inFigure 4. During the afternoon, Figure 6a shows that OTactivity is most concentrated throughout the entirety of thePanama landmass and over interior regions of Costa Rica andNicaragua. A significant concentration of OT activity is alsopresent in the waters north of Honduras. This is caused by aseries of tropical waves that moved from east to west acrossthe northern portion of this domain during TC4. During theevening hours, OT activity was concentrated over northwestNicaragua and the interior of Panama. The afternoon con-vection over Costa Rica and Panama mostly dissipated ormoved westward along their Pacific coasts. The presence ofconvection with large areas of cold BT along the coastlinescauses the areal coverage of extremely DC over land to

increase during the 1900–2100 LT time period though thetotal number OTs decreased (see Figure 4).[23] During the early morning, OTs were abundant in the

offshore and coastal regions of Colombia, Panama, and ElSalvador. Analysis of animated GOES 12 IRW imagery (notshown; available online at http://angler.larc.nasa.gov/tc4/)reveals that strong convection that initially formed overnorthwest Colombia moved westward throughout the morn-ing hours, triggering new development off the coasts ofPanama. A similar trend is observed near El Salvador whereconvection that moves westward off of northwest Nicaraguahelps to initiate vigorous new development in the offshorewaters. During late morning, the convective clouds nearPanama continue to move westward and maintain theirintensity while those off of El Salvador mostly dissipate.[24] Analysis shows that 54.4% (68.1%) of land (water)

OTs was present during the 9 P.M. to 9 A.M. LT period. TheOT occurrences are proportionately distributed over land andocean; 17.8% of the total OT activity occurred over land,which covers 20.4% of the domain. The greatest areal cov-erage of OTs over the study domain was present on 4 Augustand the lowest coverage was present on 24 July.[25] These results are generally consistent with previous

studies that show, over tropical oceans, a broad midafternoonmaximum in relatively weak convective cloud tops overocean is accompanied by a second broad maximum in themost intense convection during the early morning hours [e.g.,Minnis andHarrison, 1984; Liu and Zipser, 2005]. The peaksin the AC, DC, and OT over land between 1600 and 1900 LTare typical of most land areas [e.g., Minnis and Harrison,1984; Liu and Zipser, 2005]. However, the late night maxi-mum in extreme DC and secondary maxima in OT andextreme DC over land during the early morning hours areatypical. According to Figure 6, the greatest concentrationover land, during early morning, is found over the Panama‐Columbia border region. Liu et al. [2008] found an earlymorning peak in precipitation over the same region indicatingthe extreme DC maximum at that time is not unusual.

3.2. Storm Object Analysis

[26] The analysis will now transition to the characterizationof cloud objects defined and tracked by the WDSS‐II.Figure 7 shows GOES 12 visible imagery from 31 July 2007for a convective cloud complex west of Costa Rica. Thiscomplex is of special interest to the TC4 experiment as theeastern portion of the cirrus anvil was well sampled by theNASA DC‐8 and ER‐2 aircraft. In the central portion ofthe domain in Figure 7a, an OT is apparent in a region ofenhanced texture surrounded by a smoother anvil cloud.Extending to the east of the OT is an above‐anvil cirrusplume. As noted in the Introduction, an above‐anvil cirrusplume indicates the presence of water vapor in the TTL orstratosphere that has condensed to form a cirrus cloud. Theplume extended ∼100 km across the top of the convectivecloud complex by 1345 UTC (see Figure 7c). The plumecould still be seen in the 1415 UTC image (not shown) butno later due to a combination of plume dissipation and areduction in visible channel image texture with decreasingsolar zenith angle.[27] Figure 8 (bottom) shows that the OT signatures seen in

Figure 7, including the plume‐producing system, are wellcaptured by the WV‐IRW texture method. Though Bedka

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Figure 5. (top) Sensitivity of AC (black lines) and DC (shaded lines) areal coverage over water to changesin the IRWBT range used to define these cloud types. Symbols plotted atop the lines are used to differentiateresults from different BT ranges, which are defined within the legend. (bottom) Same as Figure 5 (top), butfor land regions.

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et al. [2010] and other aforementioned WV‐IRW BTDreferences show that this method can overdiagnose the spatialcoverage of OTs, the results shown here and in Figure 2bindicate that detections are isolated to the OT regions.[28] AC and DC cloud objects are also well defined in this

example. The 1245 UTC panel shows two distinct DC areasin the northern object separated by a narrow area of warmercloud (see Figure 8, middle). By 1315 UTC, the twoDC areasmerge, though the area defined by WDSS‐II does not extendas far west as the cold cloud area shown in the IRW imagery.At 1345 UTC, the two anvil cloud objects come closertogether and later merge into one larger object by 1415 UTC(not shown).[29] This AC object was tracked byWDSS‐II for a 16 hour

period. Figure 9 shows the minimum IRW BT within thisobject throughout its lifetime. After the first 2 hours wherethe convective cloud complex intensified, the minimum BThovered near 195K for a period of 7 hours. OTswere detectedwithin this object for 10 consecutive hours. During the first8 hours of existence, the areal coverage of the AC and DCcontinued to expand, reaching a peak near 1500 UTC. Themerger between the northern and southern AC objects in the

1345–1415UTC time frame is evident in this plot. The resultshere would indicate that two other mergers later occurred at1645 and 1815 UTC. Animated IRW imagery (not shown)indicates that the increases in AC and DC areas are alsocaused by new convective initiation within the bounds ofthe AC object, which provided a new influx of cold cloudtops. Warming cloud tops and decreasing areal coverage after1900 UTC indicate that the convective cloud complex isdecaying rapidly.[30] Since the results have shown that the WDSS‐II can

accurately monitor the evolution of convective cloud com-plexes for long time periods, WDSS‐II is applied to 30 minimagery over the full duration of the TC4 experiment. Wefocus on AC objects that exist longer than 30 min and con-tain a DC object at least once during their lifetime. A totalof 877 AC objects met this criteria and are included in thefollowing analyses. Figure 10 shows that the lifetime of the31 July object described above was in the 95th percentile ofall objects tracked by WDSS‐II. The mean lifetime of ACobjects is 5 hours and those objects contained DC objects for3 hours (60%) of this time (not shown). Figure 10 also showsthat the 31 July convective cloud complex was quite large

Figure 6. Locations of WV‐IRW‐based OT detections over land (blue) and water (cyan) during the(a) afternoon (1315–1815 LT), (b) evening (1845–2345 LT), (c) early morning (0015–0515 LT), and(d) late morning (0545–1045 LT) over the full duration of the 18 July–8 August 2007 study period. Eachplotted symbol corresponds to one detected OT occurrence.

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relative to other complexes that developed during TC4.The mean of the maximum areal coverage of AC objectsis 13,900 km2 and the mean of the maximum coverage ofDC objects is 3345 km2, indicating that DC covers 24% of amature convective cloud complex (not shown). Based uponthe areal coverage of the WV‐IRW BTD OT detections,it is determined that OT pixels represent only 0.15% of aconvective cloud complex. It is important to note here that

these results are based on the anvil cloud being defined by a225 K BT. In reality, semitransparent anvil cloud along theperiphery of a storm complex can spread and add a significantamount of areal coverage to the anvil cloud statistics, therebyreducing the mean coverage of deep convection and OTpixels.

3.3. Deep Convective Cloud and Anvil Microphysics

[31] Areal coverage of the convective cloud complexesconstitutes only one aspect of the convective cloud lifetime.The ice water budget of the clouds and its impact on theradiation budget are important characteristics of the convec-tion that need to be understood if they are to be properlymodeled. The influence on the radiation budget can computedusing the De , COD, and the cloud‐top temperature or Zt ,while the ice water variations can be monitored using IWP.[32] Figure 11 shows the mean variations of each of those

parameters for 127 daytime‐only AC objects as functions ofthe relative age of the system and the distance from the core ofthe storm using the approach described earlier. The cloud‐topheight (Figure 11a) of the core drops by ∼0.8 km during theaverage complex’s lifetime, from 15.8 km to 15.0 km. Thisdecrease with age extends 100 km from the storm center,but diminishes to a magnitude of less than 0.3 km at ∼75 kmfrom the storm center. The decrease is not monotonic with thepeak heights occurring around 20% into life of the system.[33] The mean COD (Figure 11b) of the core is at a max-

imum of ∼95 for the first half of its existence and drops by∼40% as it decays. Overall, the average COD varies non-monotonically, with mean maximum values occurring duringthe first 50% of the lifetime to a distance of 70 km from thecore. Beyond 70 km, the youngest and oldest clouds havethe greatest COD, which are about half of the core values. ThemeanDe (Figure 11c) at the core is smallest early in the stormlife but generally increases with age. Within the first 20 kmradius, De drops by 1–3 mm regardless of age. At distancesbetween 30 and 60 km from the center, De is a maximumabout 60% through the average storm’s life. It is lowest for thenew anvil at this distance range. IWP peaks ∼40% though thestorm life when COD and De are near or at their peak values(Figure 11d). IWP drops by a factor of 2 at 100 km from thecenter at the time of peak storm intensity. When the stormdecays, the IWP is lowest and the drop with distance is muchless pronounced due to the decreased COD and the homo-geneity of De.[34] When cores penetrate the TTL, the cloud properties

tend to be more extreme. For OT clouds, the mean values ofCOD, De, and Zt are 104.6, 84.8 mm, and 16.3 km, respec-tively (not shown). These values can be compared to 83.2,80.5 mm, and 15.7 km for cores that are not classified ashaving OTs, respectively. By definition, the cloud top ishigher within an OT than in a typical non‐OT anvil cloud.The increased COD is due in part to the greater thickness andreflects the intensity of the convection, but it also reflects theage of the convection since the cores are less vigorous withage as seen in Figure 8b.[35] When an object can be identified with the WDSS‐II,

the core is still growing, reaching its peak at 20%–40% into itslifetime. This peak is defined by maxima in all parametersexceptDe. The rise and fall of Zt follows the growth and decayof the convective cloud complex (Figure 11a). The anvilcontinues to build vertically until the system is in middle age.

Figure 7. (top) GOES 12 IRW imagery, (middle) WarningDecision and Support System, Integrated Information(WDSS‐II) objects, and (bottom) WV‐IRW BTD‐basedOT detections at (left) 1245, (middle) 1315, and (right)1345 UTC on 31 July 2007. The regions colored blue (red)in the middle row represent AC (DC) objects.

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Its top then drops to lower altitudes at a faster pace than that ofthe growth stage. The initially smaller particles at the top ofthe core may be due to the rapid rise of the younger particlesin the relatively dry environment above the cloud, whereas,the droplets and ice crystals ascending within the alreadyformed convective core are in a moister environment wherethey can grow to larger sizes (Figure 11c). This might explainwhy the anvil contains significantly smaller particles early inits existence, but rapidly accumulates large ice crystals as theconvection proceeds. The slower rate of decrease in De withincreasing radius as the system decays could also be due tothe greater abundance of moisture in the surrounding envi-ronment compared to the initial stages. It is not clear whyDe increases with distance beyond ∼60 km for the youngerclouds. Perhaps, there is some influence of other systemsoverlapping the younger anvils.

4. Summary and Conclusions

[36] This study characterizes the convective cloud com-plexes that occurred during the TC4 field program asobserved within GOES 12 imagery. There were clear differ-ences in the areal coverage of AC, DC, and OT activity over

land and water and also throughout the diurnal cycle. OTdetections from the WV‐IRW BTD method were used todetermine where this activity is most frequent across a subsetof the TC4 domain.[37] As would be expected, convection over interior land

regions increased in areal coverage during the 1315–1815 LTperiod in conjunction with strong solar heating of a humidtropical air mass. The northern coast and offshore waters ofHonduras were particularly active during the 1315–2345 LTperiod. Northwest Nicaragua and El Salvador also showeda convective maximum within the 1845–2345 LT period.Convection developed and moved across the offshore watersand coastal areas of these two nations during the earlymorning hours, producing a distinct regional maximum inOT activity. The offshore waters of Panama, northwestColombia, and El Salvador were the most active regions forOT‐producing clouds. The greatest areal coverage of OTactivity over the study domain was present on 4 August.[38] A large convective cloud complex that occurred on

31 July was examined in detail in this paper as the AC fromthis complex was well sampled by TC4 research aircraft.The 1 km visible channel imagery showed the presence ofan above‐anvil cirrus plume that was evident for a 1.5 hour

Figure 8. (top) Minimum IRW BT throughout the lifetime of the convective cloud complex shown inFigure 5. Asterisks denote the times that OTs were detected within the AC object. (bottom) Areal cover-age of AC and DC for the same object.

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period. This plume was connected to a persistent OT area thatserved to inject water vapor into the TTL and/or stratospherethat condensed to form a cloud. This large convectivecloud complex was detected and tracked for 16 hours bythe WDSS‐II system. The AC from this complex covered

a ∼65,000 km2 area, making it one of the largest and mostlong‐lived of those detected during the TC4 experiment. OTswere found within this complex for 10 consecutive hours.[39] A total of 877AC objects were detected and tracked by

WDSS‐II throughout the duration of the TC4 experiment.

Figure 9. (top) Maximum anvil and deep convective cloud object areal coverage for cloud complexestracked by the WDSS‐II. (bottom) Lifetime of AC (black bars) and duration of DC (shaded bars) trackedby the WDSS‐II.

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The mean lifetime for these objects is 5 hours with AC at itsgreatest horizontal extent covering a mean area of 13,900 km2.DC is found within the AC during 60% of the storm lifetimeand covers 24% of the total AC area at the time of stormmaturity. As most observed OTs are ≤15 km in diameter,they only occupy 0.15% of the AC, on average. The arealcoverage proportions of DC and OT are likely a bit too highbecause a relatively cold 225 K BT threshold is used to definethe spatial extent of the anvil cloud.[40] The microphysical properties of convective cloud

complexes were determined only for clouds that developed

and decayed during sunlit conditions. On average, theyfollowed a reasonable pattern with maximum values of Ztand COD occurring at the core roughly at a time corre-sponding to 20% of the system’s lifetime. The values in theAC surrounding the core peaked at relative age of 20%–50% before decreasing as the convective system decayed.De decreased in size with distance from the center of the corebut generally increased in size with cloud age. These results,which characterize the average convective cloud complexduring the experiment, should be valuable for formulatingand validating convective cloud process models.

Figure 10. Temporal and spatial variability of the mean (a) cloud‐top height, (b) cloud optical depth,(c) ice particle diameter, and (d) ice water path for a composite of 127 daytime AC objects tracked duringthe TC4 field experiment.

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[41] The results presented here indicate that the diurnalcycles of convective clouds and OTs are quite consistent withclimatology, not only over the experiment area, but also overthe Tropics, in general. Thus, the TC4 aircraft measurements,when taken as a whole, should be representative of tropicalconvective clouds. However, because they were confined todaylight flights, they did not sample most of the clouds thatproduce OTs, the main source for TTL moisture. Never-theless, at least, two daytime convective cloud complexes(24 July and 31 July) were sampled by the aircraft and shouldprovide the basis for good case studies.[42] It is clear that the satellite imagery is critical for

learning the behavior of these convective cloud complexes.By bringing the knowledge gained from the satellite analysestogether with the TC4 in situ data and numerical cloud pro-cess models, it should be possible to make some importantstrides in understanding deep convection over the tropics andits interaction with the TTL.

[43] Acknowledgments. This research was supported by the NASARadiation Science Program TC4 project, the NASA Applied Sciences Pro-gram, and the Department of Energy Atmospheric Radiation MeasurementProgram through interagency agreement DE‐AI02‐07ER64546. The authorsthank Kirk Ayers for processing the TC4 VIST microphysical retrievals and

the University of Wisconsin Space Science and Engineering Center forproviding the GOES 12 data and McIDAS software support.

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