comparing satellite and surface observations of …...paciﬁc by using both satellite and surface...

3172 VOLUME 125M O N T H L Y W E A T H E R R E V I E W

Comparing Satellite and Surface Observations of Cloud Patterns in Synoptic-ScaleCirculation Systems

NGAR-CHEUNG LAU AND MARK W. CRANE

Geophysical Fluid Dynamics Laboratory/NOAA, Princeton University, Princeton, New Jersey

(Manuscript received 14 October 1996, in final form 22 April 1997)

ABSTRACT

The propagation characteristics and spatial distributions of cloud cover associated with synoptic-scale cir-culation systems are studied using both satellite data processed by the International Satellite Cloud ClimatologyProject (ISCCP) and surface observations taken at weather stations or ships of opportunity. These two independentdatasets produce comparable climatological patterns of the preferred direction and speed of the cloud movements.Such ‘‘propagation vectors’’ based on the ISCCP products depict cloud motions at a higher altitude than thatof the corresponding movements deduced from surface synoptic reports.

By application of a similar composite procedure to the ISCCP and surface datasets, a detailed comparison ismade between the satellite and surface observations of the organization of various cloud types in midlatitudecyclones. The relationships of these cloud patterns with the concurrent atmospheric circulation are illustratedby superposing the composites of wind and geopotential height on the cloud data. Both the satellite and surfaceobservations yield well-defined cloud patterns organized about frontal zones. These cloud patterns are consistentwith the composite distributions of weather types as coded in the surface reports. Combination of findings fromthe surface reports (which provide information on the altitude of the cloud base) and those from the satelliteobservations (which offer estimates of cloud-top heights) is found to be helpful for portraying the verticaldistribution of cloud cover in various sectors of the extratropical cyclones. The ISCCP dataset underestimatesthe amount of low stratiform clouds lying under the high, optically thick cloud shield in the warm sector.Comparison between the composite results for cyclones occurring over the North Atlantic and those over theNorth American continent indicates the occurrence of larger anomalous cloud amounts in the continental systems.The more widespread cover by nimbostratus cloud in the northwestern sector of the surface low pressure centerover land is particularly noteworthy. The distinction between the cloud organization in maritime and continentalcyclones is seen to be related to the stronger, frictionally induced cross-isobaric flow over land surfaces.

Analogous composite charts are constructed for the convective disturbances occurring over the tropical westernPacific by using both satellite and surface cloud observations. Some degree of consistency is again discernibleamong the cloud patterns based on the two datasets. The ISCCP data tend to underestimate the amount ofcumulus clouds situated below the anvils at the trailing end of these convective systems.

1. Introduction

In a recent article published in Monthly Weather Re-view, Lau and Crane (1995, hereafter referred to asLC95) examined the fluctuations of cloud properties as-sociated with the passage of synoptic-scale circulationsystems in middle and low latitudes. The daily cloudobservations used in that study were derived from sat-ellite measurements processed by the International Sat-ellite Cloud Climatology Project [ISCCP; see reviewsby Schiffer and Rossow (1983) and Rossow and Schiffer(1991)]. The typical spatial distribution of cloud typeswith various optical and cloud-top characteristics duringprominent synoptic episodes was described in LC95 bycompositing selected parameters in the ISCCP dataset.

Corresponding author address: Dr. Ngar-Cheung Lau, GFDL/NOAA, Princeton University, P.O. Box 308, Princeton, NJ 08542.E-mail: [email protected]

By overlaying these satellite-derived cloud fields oncomposites of the contemporaneous atmospheric struc-ture, well-known relationships between the cloud andatmospheric circulation patterns have been confirmed.In the region of enhanced storm activity over the NorthAtlantic during winter, the representative cloud patternas deduced from our quantitative analysis of the ISCCPdata bears a considerable resemblance to that associatedwith typical midlatitude cyclones as reported in othersynoptic studies. Over the western tropical Pacific, thesummertime cloud distribution based on satellite ob-servations is in broad agreement with that observed pre-viously in tropical convective disturbances.

The evidence presented in LC95 illustrates the use-fulness of satellite data for delineating various facets ofthe atmospheric circulation. The credibility of these sat-ellite-based findings would be enhanced by verificationagainst results derived from other observational meth-ods. An obvious alternative to the satellite datasets isthe cloud observations taken from ships and surface

DECEMBER 1997 3173L A U A N D C R A N E

weather stations. An extensive effort to compile theworldwide, surface-based synoptic records of cloud typeand cloud amount for the recent decades has been un-dertaken by Hahn et al. (1994). The primary objectiveof the present study is to analyze the cloud observationsfrom sea or ground level by following essentially thesame procedures developed in LC95, and to comparethe results thus obtained with their counterparts basedon the ISCCP dataset. In addition to cross-checking theinferences on cloud organization as drawn from twoindependent data sources, it is also our intention to ex-plore the extent to which the ‘‘top-down’’ view of thecloud systems from spaceborne instruments may be aug-mented by the ‘‘bottom-up’’ perspective of these sys-tems from surface observers. Our emphasis is placed onthe propagation and spatial patterns of various cloudtypes in those regions of the northern extratropics andTropics where synoptic-scale disturbances (i.e., phe-nomena with timescales of several days) are particularlyactive.

A brief description of the datasets and data processingprocedures used in this study is given in section 2. Thetypical shape and propagation characteristics of thecloud patterns associated with midlatitude circulationsystems are examined in section 3. Satellite- and sur-face-based composite cloud patterns accompanying ex-tratropical cyclones are compared in section 4, and con-trasts between maritime and continental weather sys-tems are highlighted. Results on the cloud distributionsfor tropical disturbances are presented in section 5 usingboth ISCCP and surface data. Some discussion of thefindings of this study is then made in the concludingsection.

2. Datasets and analysis procedures

The present study makes use of the satellite productsin the C1 dataset produced by ISCCP for the 1983–90period. In particular, the daily averaged variations oftotal cloud optical thickness t and fractional cover bydifferent cloud types at individual grid points are ana-lyzed. The cloud types are classified according to var-ious thresholds of cloud-top altitude and t (see Table 1of LC95). Clouds with tops in the upper, middle, andlower troposphere are identified as ‘‘high-top,’’ ‘‘mid-dle-top,’’ and ‘‘low-top,’’ respectively. Clouds withlarge, moderate, and small values of t are referred toas ‘‘thick,’’ ‘‘medium,’’ and ‘‘thin,’’ respectively. Eachcloud type is named by using a combination of the cloudtop and t attributes (e.g., high-top/thick, low-top/thin,etc.).

Information on the structure of the atmospheric cir-culation is obtained from the daily averaged griddedanalyses of wind and geopotential height for the sameperiod. These global meteorological fields are producedby the European Centre for Medium-Range WeatherForecasts (ECMWF). A detailed documentation of thisdataset has been compiled by Trenberth (1992).

Surface observations of cloud types and cloudamounts are based on the synoptic cloud reports pro-cessed and edited by Hahn et al. (1994). This datasetconsists of 124 million reports from land stations and15 million reports from ships over the globe, and coversthe decade from 1982 through 1991. Each report con-tains information on the time and location of the ob-servation, total cloud cover, type and fraction of cloudcover at low, middle, and high altitudes, as well as acode indicating the present weather. Other supplemen-tary variables such as cloud-base altitude are also in-cluded in the report.

To facilitate comparison between the surface obser-vations and the ISCCP dataset, an elaborate processingscheme has been applied to the synoptic cloud reports.The details of this data analysis procedure are describedin the appendix. For a given set of M selected synopticcases, this procedure yields the composite patterns forthe amount of individual cloud types ct and the fre-quency of occurrence of individual weather types wt ona 2.58 (latitude) by 2.58 (longitude) grid mesh. The cloudtypes being examined include various cumuliform andstratiform clouds with bases at low, middle, and highlevels. The weather types include fog, heavy and lightrain, and heavy and light snow. The composite data areexpressed as anomalous departures from the long-termclimatology for the corresponding season and are de-noted as ANOMct and ANOMwt, for a given cloud typeand weather type, respectively. Hence the spatial dis-tributions of ANOMct and ANOMwt correspond to theanomalous cloud and weather patterns, which are rep-resentative of the M cases under consideration.

3. Propagation characteristics of extratropicalcloud fluctuations

To gain some appreciation of the typical shape andtemporal evolution of midlatitude cloud patterns asviewed from the surface, we first examine the compositeanomalous distribution of the total cloud cover accom-panying cloudy episodes detected in the western NorthAtlantic. For ease of comparison with the satellite-basedresults, the dates of occurrence of these episodes areexactly the same as the set of key dates used in LC95.As explained in our earlier study, these dates correspondto notable maxima in the time series of day-to-day fluc-tuations of cloud optical thickness t in the ISCCP da-taset for the reference site 468N, 468W. Nine such datesare selected in each of the seven cool seasons, so thatthe total number of cases M incorporated in the presentcomposite procedure is 9 3 7 5 63. The anomalouscomposite pattern (i.e., ANOM as defined in the ap-pendix) of surface observations of total cloud coverbased on the key dates (day 0) is shown in Fig. 1b. Thecorresponding patterns based on data for the day before(day 21) and the day after (day 11) the key dates arepresented in Figs. 1a and 1c, respectively. The location


FIG. 1. Composite patterns of the anomalous total cloud amount(in percent, see scale bar at bottom) based on prominent cloudy ep-isodes during the cool season at the reference site 468N, 468W. Panels(a), (b), and (c) depict the cloud distributions on the day before thekey dates, the key dates, and the day after the key dates, respectively.The location of the reference site is indicated by a solid dot in eachpanel and is labeled as P0 in (b). The positive extrema in (a) and (c)are indicated by open circles and are labeled as P21 and P11, re-spectively. All patterns have been smoothed using the nine-pointspatial filter described by Holloway (1958).

of the reference site P0 is indicated as a solid dot ineach panel.

It is evident from Fig. 1 that prominent cloudy eventsat P0 are linked to a well-organized pattern of total cloudcover over eastern North America as well as the westernand central North Atlantic. The distribution on day 0(Fig. 1b) is indicative of a wavelike phenomenon, withenhanced cloud cover along an elongated band in the

vicinity of P0, and reduced cloud cover along similarbands farther east and farther west. The typical wave-length of this system, as estimated from the distancebetween the two principal bands of negative anomaliesin cloud cover in Fig. 1b, is approximately 5000 km.These individual bands of cloud anomaly exhibit a char-acteristic orientation from the southwest to the north-east. Comparison among the three panels in Fig. 1 re-veals a distinct tendency of the system of bands to mi-grate east-northeastward with time, at a speed of ap-proximately 15 m s21. The above spatial and temporalcharacteristics of the composite charts in Fig. 1 basedon surface observations are in general agreement withthe corresponding patterns in Figs. 3a–c in LC95 basedon satellite measurements of t.

For a given reference site P0, the temporal evolutionof the composite cloud pattern may be depicted by apropagation vector computed using the following meth-od. The mean locations of the principal anomaly ofenhanced cloud cover one day before and one day afterthe key dates are estimated by noting the positive ex-trema appearing in the composite maps for day 21 andday 11 (see open circles labeled as P21 and P11 in Figs.1a and 1c, respectively). The direction of the propa-gation vector is determined by the orientation of the linesegment pointing from P21 to P11. The migration speedis obtained by dividing the distance between P21 andP11 by 2 days. The propagation ‘‘arrow’’ thus computedis then assigned to the reference point P0. The com-putation of the composite patterns and propagation ar-rows is repeated multiple times by successively treatingindividual grid boxes situated between 258 and 608N asthe reference site.

The wintertime distributions of the propagation vec-tors as determined by the above procedure are displayedin Fig. 2. Arrows based on the surface observations oftotal cloud cover are shown in red. The correspondingvectors obtained from analysis of the ISCCP data for t(as presented in Fig. 4a of LC95) are reproduced in Fig.2 using black arrows. Red and black arrows are plottedonly in grid boxes for which the sum of the compositecloud cover anomaly at P21 and at P11 (which is a mea-sure of the ‘‘temporal coherence’’ of the migratory sig-nal during the 2-day periods centered on the key dates)exceeds 16%. Arrows are not plotted over grid pointswith propagations speeds less than 2 m s21. The sparsityof propagation vectors over the eastern oceans may par-tially be attributed to the prevalence of persistent andextensive stratus decks in those regions (Warren et al.1988), which makes it difficult to discern day-to-daycloud movements by using surface reports.

Some of the characteristics of the propagation vectorsin Fig. 2 are related to the local mean wind circulationat the altitudes where the clouds are detected. For in-stance, the systematic counterclockwise turning of thevectors as they go eastward from East Asia to the west-ern North Pacific is consistent with the occurrence of awintertime stationary trough in that region. The mag-


FIG. 2. Distributions of the propagation vectors during the cool season, as computed using the ISCCP data for cloud optical thickness(black arrows) and surface synoptic reports of total cloud cover (red arrows). The scaling for these arrow patterns is given at the bottomright of the figure. The zonal and meridional components of the vectors have been smoothed using the nine-point spatial filter described byHolloway (1958). Yellow (blue) shading indicates regions where the vectors based on ISCCP observations are rotated in a clockwise(counterclockwise) fashion relative to the vectors based on surface observations by more than 58. The angular deviation between the resultsfor satellite and surface data at a given grid point is determined only when the propagation speed for both results exceed 8 m s21.

nitude and orientation of the arrows in Fig. 2 are similarto those of the climatological wind vectors at 700 or850 mb (e.g., see Fig. 2 of Blackmon et al. 1984).

At those sites where wavelike disturbances are active,such as the cyclone tracks within the 408–508N zone inthe central North Pacific and North Atlantic (e.g., seeBlackmon et al. 1977), the arrows in Fig. 2 may alter-natively be interpreted as portraying the phase propa-gation of these disturbances. The association betweenthe temporal evolution of cloud cover and movementof cyclone-scale waves is substantiated by the resem-blance between the vector fields in Fig. 2 and the phasepropagation patterns based on time-filtered data of geo-potential height [see Fig. 2 of Blackmon et al. (1984)and Fig. 8 of Wallace et al. (1988)].

Along the axes of the jet streams over the westernNorth Pacific (near 358N, 1208–1708E), the propagationspeed deduced from surface observations (red arrowsin Fig. 2) is noticeably slower than that obtained usingISCCP data (black arrows). Similar differences are also

discernible in a more limited area in the western NorthAtlantic (308–408N, near 708W). This discrepancy couldin part be attributed to the different vantage points ofthe surface observers and satellite platforms. For a spe-cific location at a given time, surface-based data tendto describe characteristics of clouds that are situated atlower altitudes than those detected by satellite sensors.Since the jet stream regions are characterized by rapidincreases in the local wind speed with height, the surfacesynoptic reports would yield comparatively slowerpropagation speeds.

In the jet stream regions over the western oceans, thepropagation arrows based on satellite data are rotatedin a counterclockwise sense relative to the arrows com-puted using surface data. In particular, blue shading inFig. 2 depicts those areas where this counterclockwiserotation exceeds 58. If we again assume that the altitudeof the wind field as inferred from surface reports istypically lower than that based on ISCCP data, the dif-ferences in the orientation of the two sets of vectors


would imply a backing of the prevalent winds withheight in vicinity of the jet streams. Such a verticalprofile of the thermal wind is indicative of the occur-rence of cold temperature advection in these regions.This inference is consistent with the climatologicalcharts of temperature advection as presented by Lau(1979, Figs. 18a and 20a).

In the North Pacific region in 458–508N, 1508E–1708W, the propagation arrows based on ISCCP obser-vations are directed mostly from west to east, whereasthe corresponding arrows for the surface dataset are ori-ented from southwest to northeast. Yellow shading isused in Fig. 2 to highlight those regions where the ar-rows for the satellite data exhibit a clockwise rotationrelative to the arrows for the surface data by more than58. The angular deviation between the two sets of arrowsin this region may in part be due to differences in thedirection of phase propagation of cyclone waves alongthe Pacific storm track at various altitudes. The verticaldependence of the propagation characteristics of syn-optic-scale fluctuations may be discerned from the re-sults presented by Blackmon (1976, Fig. 5), Blackmonet al. (1977, Fig. 2b) and Wallace et al. (1988, Fig. 8)based on time-filtered geopotential height data at dif-ferent pressure levels. These findings are consistent withthe tendency for surface lows (as would be preferentiallysampled by cloud reports taken at the surface) to migratepoleward as they evolve through the occlusion and de-cay phases over the central North Pacific. In this stageof the cyclone development, the upper-level waves (asseen by the satellite instruments from above) are oftendecoupled from the surface disturbances and continueto travel eastward.

In the North Atlantic region from 258 to 408N, andfrom 208 to 508W, there are notable discrepancies be-tween the propagation vectors based on ISCCP and sur-face reports. Differences are also seen at scattered gridpoints in the subtropical central and eastern Pacific. Theclimatological circulations in these regions are domi-nated by subtropical anticyclones, which are associatedwith much weaker wind speeds and storm intensity, andwith extensive stratiform cloud cover near the boundarylayer. The weak steering currents and long-lived mari-time stratus decks in these regions lead to considerableuncertainties in the estimation of cloud propagationcharacteristics using both datasets.

4. Cloud patterns accompanying extratropicalcyclones

We proceed to compare the satellite and surface viewsof the typical distribution of various cloud types asso-ciated with midlatitude disturbances. The ISCCP andsurface datasets are subjected to essentially the samecomposite procedure described in section 5a of LC95.For each point in a given array of 20 reference sites, aset of 63 key dates are selected by identifying the max-ima in the daily time series of cloud optical thickness

t for that point. Composites are then constructed byaveraging the pertinent ISCCP, ECWMF, and surfacecloud data over the key dates. Anomalies are computedby subtracting the corresponding climatological meansfor the northern cool season (October through March)from the composites. In our previous study, the anom-alies for a given key date were defined as departuresfrom the average over the 5-day period centered on thatkey date. For a given parameter, the set of 20 anomalouscomposite patterns thus obtained (one for each referencesite in the array) is combined to form a single chart byaligning the composite data to a common Cartesian co-ordinate system, so that the origin of this system co-incides with the reference site for each of the 20 com-posite patterns. The composite procedure in this studyentails considerable averaging in both time and space.No attempt is made to distinguish the cloud patternsoccurring in various stages of the cyclone development.These limitations should be borne in mind when com-paring our results with other studies based on individualsynoptic cases.

For the ISCCP data, the amount of a given cloud typeis determined by taking the ratio of the number of pixelssatisfying the cloud-top altitude–t criteria for the cloudtype in question versus the total number of pixels avail-able for analysis in each grid box on each day. Thisratio may be viewed as a spatial measure of the fractionof the sky covered by a particular cloud type. All sub-sequent computations of the composite and climatolog-ical patterns are then performed using the daily gridsof these ratios. Hence the ISCCP cloud amounts cor-respond to temporal averages of fractions of spatialcloud cover for individual days. On the other hand, thecloud amount based on the surface data [see Eq. (A1)]is defined as the product of the frequency of occurrenceof a certain cloud type (which is essentially a temporalmeasure) and the average fraction of cover by that cloudtype whenever it is present (a spatial measure). In com-paring the products from ISCCP and the surface reports,one must bear in mind the different procedures used inestimating the cloud amount from the two datasets.

a. Maritime systems

We first examine the cloud and circulation patternsaccompanying the maritime disturbances over the NorthAtlantic. The composite results to be presented here arebased on the same network of 20 reference sites usedpreviously by LC95 (see solid dots in Fig. 5a of thatpaper). This staggered array of ocean points is situatedeast of Nova Scotia and Newfoundland and covers theregion of 418–518N, 348–598W. The separation betweenneighboring points in this array is 58 of longitude and2.58 of latitude. This array is situated in a region char-acterized by climatological cold-air advection (see sec-tion 3) and frequent cyclogenesis. The spatial patternsof the anomalous amounts of selected cloud types fromthe ISCCP dataset (left panels) and the surface reports


(right panels) are shown in Fig. 3. Superposed on thepatterns for each cloud type are the composite anomaliesof the ECMWF analyses of the height (contours) andhorizontal vector wind (arrows) fields at 1000 mb. Theabscissa and ordinate of each panel represent the lon-gitudinal and latitudinal distances, respectively, from thecommon origin, to which the reference sites of the 20individual composite charts are aligned. The compositeprocedure has been applied to every cloud type reportedin the ISCCP and surface datasets. The specific cloudtypes in Fig. 3 are chosen for presentation by virtue ofthe large anomalous amounts appearing in the compositepatterns for these cloud types.

The satellite-based cloud patterns (left panels of Fig.3) exhibit well-defined relationships with the ambientcirculation field. Physical interpretation of such rela-tionships in terms of dynamical forcing and three-di-mensional cyclone structure has been offered in LC95.The most prominent feature in the region east of thesurface low pressure center and west of the high center(i.e., the ‘‘warm sector,’’ with predominately southerlyflow) is a cloud shield that is optically thick and has ahigh top (Fig. 3a). Near the eastern fringe of this shieldare high-top elements with lower t (Fig. 3b). The cloudcover in the cold sector to the west of the surface low,where northerly flow prevails, consists mainly of low-top/thick clouds (Fig. 3c), and, to a lesser extent, low-top/thin clouds (Fig. 3d).

The surface synoptic reports (right panels of Fig. 3)also reveal a systematic organization of the cloud typesin various sectors of the composite cyclone. The oc-currence of nimbostratus (Fig. 3e) is enhanced in a broadregion extending westward from the warm sector all theway to the west of low center. The maximum enhance-ment occurs to the east of the low and reaches an am-plitude of more than 10%. Assuming that these precip-itating nimbostratus clouds1 are optically thick, theISCCP composites indicate that the eastern two-thirdsof the nimbostratus region (which corresponds to thewarm sector of the cyclone) are mostly populated byclouds with high tops (Fig. 3a), whereas the remainingone-third to the west of the low (which corresponds tothe cold sector) consists mainly of low-top clouds (Fig.3c). The composite pattern for thick altostratus (Fig. 3f)bears some resemblance to that for high-top/mediumclouds based on ISCCP data (Fig. 3b). The positiveextrema in this pair of patterns are located near the

1 In editing the surface cloud observations, the nimbostratus cat-egory is assigned to reports with midlevel cloud type correspondingto thick altostratus or ‘‘obscured sky,’’ and with the current weathercorresponding to drizzle, rain, or snow. Nimbostratus is also assumedto be present when (a) information on middle-level clouds is missing,the low-level cloud observation indicates either no cloud or bad-weather stratus, and the current weather corresponds to drizzle, rain,or snow; or (b) information on midlevel clouds is missing, the low-level cloud type is either fair-weather stratus or stratocumulus, andthe weather type is rain or snow.

eastern edge of the cloud shields depicted in the nim-bostratus and high-top/thick composites. This spatial re-lationship implies that stratiform clouds with bases atmiddle levels (i.e., altostratus) and tops at high levelsare prevalent along the leading edge of the deep rain-clouds associated with the advancing warm front.

The composite pattern for nonprecipitating stratusclouds2 based on the surface reports (Fig. 3g) indicatesa notable increase of this cloud type in a large regionextending southwestward from the warm sector. On thecontrary, the ISCCP composite for the cloud categorywith attributes that correspond most closely to stratus(i.e., low cloud top and large optical thickness; see Fig.3c) is characterized by a decrease in this cloud type inthe warm sector. This discrepancy between the satelliteand surface views of the low stratiform cloud may inpart be due to the presence of thick or medium high-top clouds in the warm sector (see Figs. 3a,b), whichshield whatever cloud decks that might exist underneathfrom the view of the satellite sensors. It is also con-ceivable that, in situations when stratus clouds and high-top/thin clouds coexist in the warm sector, the satelliteretrieval algorithms might interpret the cloud field asbeing composed mainly of high-top/thick elements. Abetter agreement between Figs. 3c and 3g is found tothe southwest of the low center, where the low cloudsare not obscured from the satellite view by high-topclouds.

A reasonable correspondence is found between thesatellite composites of low-top/thick and low-top/thinclouds (Figs. 3c,d) and the surface-based composite forthe combined cumulus/nonprecipitating stratocumulus2

categories (Fig. 3h). Enhanced occurrence of these cloudtypes is found in the cold sectors to the northwest ofthe low center and to the southeast of the high center.Included in such clouds are open cell convective ele-ments often seen when cold air masses advance towardrelatively warmer ocean surfaces.

In a recent study, J. R. Norris (1996, personal com-munication) documented the relationships between sur-face cloud observations and vertical soundings taken atselected weather ships. His results for the midlatitudeNorth Atlantic during winter indicate that stratocumulusand cumulus occur in conjunction with cold temperatureadvection, whereas fair-weather or bad-weather stratusare associated with warm advection. These findings arein general agreement with the composite patterns pre-sented in Fig. 3.

The relative abundance of, and the spatial relation-

2 Since some stratus (St) or stratocumulus (Sc) clouds are reclas-sified as nimbostratus clouds when the current weather indicates driz-zle, rain, or snow (see footnote 1 for details), only those St or Screports in nonprecipitating weather situations are incorporated inthese two cloud categories. There is, hence, no overlap between thereports contributing to the nimbostratus composite and the reportscontributing to the St or Sc composites.


FIG. 3. Composite patterns of anomalous amounts (in percent, see stippling in each panel and scale bar at bottom)of (a) high-top/thick, (b) high-top/medium, (c) low-top/thick, and (d) low-top/thin clouds based on the ISCCP dataset,and of (e) nimbostratus, (f) thick altostratus, (g) stratus, and (h) cumulus/stratocumulus based on the surface synopticreports. Superposed on each panel are the corresponding composites of anomalous horizontal wind vector (arrows, seescale at bottom right) and geopotential height (contours; interval: 10 m) at 1000 mb, as obtained from ECMWF analyses.Solid (dashed) contours indicate positive (negative) values. The composite procedure is based on 20 reference sites inthe North Atlantic during the cool season. The ordinate (abscissa) of each panel represents latitudinal (longitudinal)displacements from the common origin, to which the composite charts for individual reference sites are aligned.


ships between the individual cloud categories consid-ered in Fig. 3 may be discerned more easily by pre-senting the composite data for all cloud types in a singlechart, as is done in Fig. 4 for (a) ISCCP data and (b)surface observations. Each 2.58 3 2.58 grid box in thecommon coordinate system used here is divided into 25square pixels. For each cloud type being considered, thepixels are filled in a randomized fashion with a colorassigned to that cloud type. The number of pixels in agrid box to be color-filled is determined according tothe magnitude of the positive composite anomaly in thatcloud type at that grid box: one pixel is filled for eachpercent of cloud amount enhancement. Negative com-posite anomalies are not indicated in these plots. Anyunfilled pixels are indicated in black. Note that the col-ors used to represent these four cloud types are differentfrom those used in LC95. As in Fig. 3, the compositeanomalies in 1000-mb height and horizontal wind aresuperposed on the pixel patterns in Figs. 4a and 4b usingcontours and arrows, respectively.

The color mosaics in Figs. 4a and 4b illustrate furtherthe similarities and differences between the cloud pat-terns based on the ISCCP and surface datasets as notedpreviously in Fig. 3. The satellite pattern (Fig. 4a) in-dicates a clear demarcation between high-top clouds(red and green pixels) in the warm sector and the low-top clouds (yellow and blue pixels) in the cold sector.On the other hand, the surface observers (Fig. 4b) reportmuch larger amounts of stratus in the warm sector, sothat the cloud cover in the latter region is characterizedby a more heterogeneous mix of cloud types. Also ev-ident from Figs. 4a and 4b is the collocation of thenimbostratus clouds north and west of the low centerwith the low-top/thick pixels in the satellite composite.

To delineate the relationships between the cloud pat-terns and the surface weather, the composite chart ofthe anomalous frequency of occurrence of four selectedweather types (see definition of ANOMwt in the appen-dix) is shown in Fig. 4c. The plotting procedure for thisdiagram is analogous to that for Figs. 4a and 4b. The25 pixels within each grid box in the common coordinatesystem are filled by the colors representing individualweather types wt at the rate of one pixel per each percentincrease in the frequency of occurrence of each wt. Su-perposed on this pixel pattern is the composite anom-alous pattern of 500-mb vertical velocity, 2v (see con-tours), as provided in the ECMWF dataset. Reports oflight snow spread over an extensive region in the north-western quadrant of the plotting domain. This weathertype is not depicted in Fig. 4c (and Fig. 5c in section4b) for the sake of clarity.

The pattern in Fig. 4c is consistent with the weatheraccompanying a typical midlatitude cyclone, with rainoccurring in the vicinity of the warm and cold fronts,and snow to the north and west of these frontal zones.The fog reports are mostly situated along the easternedge of the rainy region. The area of enhanced occur-rence of precipitation is well collocated with the max-

imum in anomalous upward velocity at 500 mb. Thecenters of anomalous descent are almost void of anyreports of precipitating weather. The good agreementbetween the contour and pixel patterns in Fig. 4c, whichare based on entirely independent data sources, affirmsthe validity of the analysis procedures adopted in thepresent study, and also demonstrates the reliability ofECMWF estimates of the vertical velocity field in mid-latitudes.

Comparison among the three panels in Fig. 4 revealsa close correspondence between precipitation reports inFig. 4c and occurrence of nimbostratus in Fig. 4b, ascan be expected from the definition of the nimbostratuscloud category (see footnote 1). It is also evident fromFigs. 4a and 4c that much of the rain in the warm sectoris coincident with high-top clouds, and the snowfall tothe northwest of the surface low is mostly associatedwith clouds with low tops. The centroid of the high-topcloud shield in Fig. 4a is shifted eastward of the centersof precipitation and ascent Fig. 4c by approximately 58of longitude. This relationship is consistent with thesynoptic experience that high clouds tend to occur inadvance of the precipitation during the passage of anextratropical cyclone. The spatial shift of the cloud cov-er relative to the center of maximum ascent is the resultof eastward advection of the high cloud elements by theupper-level jet stream.

In summary, the satellite and surface observationsoffer complementary views of the cloud organization ina typical midlatitude cyclone. By inferring the altitudesof the base and top of the prevalent clouds from thesurface reports and ISCCP data, respectively, it is fea-sible to estimate the vertical characteristics of the cloudcover in certain parts of the cyclone. For instance, thecoincidence of surface reports of nimbostratus and stra-tus with mostly high-top satellite cloud pixels in thewarm sector is indicative of the existence of either adeep cloud layer or multiple cloud decks. On the otherhand, the collocation of nimbostratus with low-top sat-ellite pixels in the northwestern quadrant of the lowpressure area implies a much shallower cloud cover inthat region. This comparative study also suggests thata one-to-one correspondence does not always exist be-tween the cloud types identified in the ISCCP dataset(based on cloud-top height and t) and the cloud typesused in surface synoptic reports (based on visual ap-pearance and cloud-base height). A case in point is thatthe nimbostratus in the warm sector can be matchedwith the satellite high-top/thick pixels, whereas the nim-bostratus to the northwest of the low center is seen tobe mostly associated with low-top/thick pixels. On theother hand, the nimbostratus cloud category has beenassigned to middle-top/thick pixels in the ISCCP da-tasets under the classification scheme of Rossow andSchiffer (1991, see their Fig. 4). In view of these com-plications, caution must be exercised in associatingcloud characteristics inferred from satellite measure-


FIG. 4. Composite patterns of the positive anomalies of the amount of selected cloud types based on (a) ISCCP dataand (b) surface observations, and of the (c) frequency of occurrence of selected surface weather types, for the referencesites in the North Atlantic during the cool season. The coordinate system used in each panel is identical to that usedin Fig. 3. In each 2.58 3 2.58 box in this system, the presence and relative abundance of a given cloud type or weathertype are depicted by plotting randomly scattered pixels with a specific color (see legends at right), at the rate of onepixel for each percent increment in cloud amount or frequency of occurrence. The arrows (see scaling at top right) andcontours (interval: 10 m) in (a) and (b) indicate the composite anomalous 1000-mb wind and geopotential height fieldsfrom the ECMWF analyses, respectively. The composite anomaly pattern for the vertical velocity, 2v (with positivevalues indicating upward motion) from the ECMWF data is shown as contours (interval: 2 3 1022 Pa s21) in (c). Solid(dashed) contours indicate positive (negative) values.


ments with specific morphological cloud types based onsurface observations.

b. Continental systems

In order to compare the cloud organization in mari-time cyclones with that occurring over land, a compositeanalysis of the ISCCP cloud data, surface cloud data,and surface weather reports has been repeated by usingan array of 20 reference sites in the eastern half of NorthAmerica. This array of land points has a similar con-figuration as the North Atlantic array used in section4a, and covers the region of 368–468N, 748–998W. Aset of 63 key dates is identified for each of these 20land sites according to the times of occurrence of larget in the time series for the site in question. These keydates are in general different from those determined forthe North Atlantic sites used in section 4a. The sub-sequent data processing procedure is identical to thatused for studying the maritime cyclones. The color mo-saics thus obtained for the North American weather sys-tems are shown in Fig. 5a for ISCCP data, Fig. 5b forsurface cloud data, and Fig. 5c for surface weather typedata. Superposed on the pixel patterns are the corre-sponding ECMWF composites of the anomalous1000-mb height and wind fields in Figs. 5a and 5b, andthe 500-mb vertical velocity in Fig. 5c.

The patterns in Figs. 5a and 5b indicate that the con-tinental cloud shields and geopotential anomalies ac-quire a more isotropic character than their counterpartsover the North Atlantic. In particular, the characteristicsouthwest-to-northeast tilt of the cloud cover and1000-mb height anomaly seen in the maritime systems(Figs. 3 and 4) is less evident in the land systems. Theless prominent horizontal tilt over North America isconsistent with the weaker time-averaged meridionalflux of westerly momentum by synoptic-scale eddies inthat region (e.g., see Fig. 7b of Blackmon et al. 1977).These geographical differences in the eddy transportproperties are related to the life cycles of eastward trav-eling synoptic disturbances in this region. The typicalevolution of such storm systems is characterized by abaroclinic growth phase (with enhanced poleward heatfluxes) near the eastern seaboard of North America, fol-lowed by a mature phase (with enhanced eddy momen-tum flux convergence) farther downstream. The com-posite amplitude of the 1000-mb height perturbationsin the continental sector is comparable to that in theoceanic sector. However, the density of color-filled cloudpixels in Figs. 5a and 5b over the continental low pres-sure center and in the region farther north and west ishigher than that in the corresponding maritime com-posites (Figs. 4a and 4b). Specifically, the surface re-ports indicate that the enhancement of total cloud covernear the low pressure center is approximately 25% forthe land composite and 10% for the ocean composite.Since the data presented here correspond to departuresfrom climatological averages (CLIMct, see appendix),

the larger anomalies in cloud cover over North Americacould in part be attributed to the lower values of CLIMct

over land as compared to those over maritime sites (seeWarren et al. 1986, 1988).

Comparison between the satellite patterns in Figs. 4aand 5a reveals that the low-top clouds to the northwestof the continental low center are characterized by rel-atively larger t. The low-top/thin clouds seen in thissector of the maritime pattern are absent from the com-posite in Fig. 5a. The population of low-top thick cloudsto the southeast of the low pressure area is noticeablyhigher in the continental composite than in the maritimecomposite.

The surface-based composites (Figs. 4b and 5b) in-dicate that the nimbostratus and stratus cloud shields inthe continental cyclone are extended farther to the northand to the west than their counterparts in the maritimecomposite. The diminished cloud cover to the northwestof the low center in the maritime pattern could in partbe related to the sparsity of surface observations in thatparticular quadrant, which corresponds approximatelyto the Labrador Peninsula and the surrounding waters.The density of cumulus/stratocumulus clouds in thesoutheastern quadrant of the continental low pressurearea is considerably higher than that in the maritimepattern. The high pressure center in the land compositeis almost void of any cloud cover, in contrast to thepresence of small amounts of cumulus/stratocumulusover the oceanic high center. The enhanced low-levelcloud cover in the warm sector of the continental systemcould be due to the transport of moisture from the Gulfof Mexico by the southerly airstream.

The distribution of weather types associated with con-tinental systems (Fig. 5c) is characterized by a higherfrequency of light rain in the warm sector, and by alower frequency of heavy snow in the cold sector whencompared with the corresponding distribution for oce-anic systems (Fig. 4c). There are also relatively morereports of fog in the land composite along the easternedge of the precipitation zone. The locations of thesefog observations correspond approximately to the Unit-ed States eastern seaboard.

The location of precipitating weather in Fig. 5c isconsistent with the distribution of vertical motion at 500mb as inferred from the ECMWF analyses (see contoursin the same panel). Comparison between the land com-posites for weather type (Fig. 5c) and for cloud type(Fig. 5a) also reveals a slight eastward shift of the cloudshield from the precipitation zone. This spatial rela-tionship has been noted in the maritime system (Fig.4).

The most salient difference in the near-surface windcirculation accompanying the maritime and continentalsystems is the much stronger cross-isobaric componentover land. This land–sea contrast is an indication of themore prominent role of friction over continental sur-faces. The nature of the cross-isobaric flow is exploredin greater detail in Fig. 6, which shows the composites


FIG. 5. As in Fig. 4 but based on 20 reference sites located in the eastern half of the North American continent.

of the geopotential height (contours), horizontal wind(arrows), and the angle (in degrees) between the actualwind vector and the geostrophic wind vector (stippling),all at the 1000-mb level. The results based on the com-bination of the 20 reference sites over the North Atlanticand North America are shown in Figs. 6a and 6b, re-spectively. For both the maritime and continental sys-

tems, the flow across the height contours is most notableto the west and northwest of the low center. The surfacewinds also exhibit a considerable cross-isobaric com-ponent in the region located at 108–208 of latitude southof the low center. In the land composite, another areaof strong ageostrophic flow is discernible just west ofthe high center. The angular deviation from geostrophy


FIG. 6. Composite patterns of the anomalous horizontal wind (arrows, see scaling at top right) andgeopotential height (contours, interval: 10 m) at 1000 mb, based on 20 reference sites in (a) North Atlanticand (b) eastern North American continent. Solid (dashed) contours indicate positive (negative) values. Theangular deviation of the 1000-mb flow from the local geostrophic wind vector is indicated by stippling (seescale bar at bottom; units: degrees).

in the above areas is approximately 208–308 over theNorth Atlantic and increases markedly to 408–508 overNorth America. It is also noteworthy that the windspeeds in the vicinity of the oceanic low (Fig. 6a) aregenerally higher than those near the continental cyclone(Fig. 6b). In examining Fig. 6, it should be borne inmind that the ageostrophic characteristics presentedtherein may be somewhat dependent on the treatment

of surface friction in the ECMWF models used for pro-ducing the wind and geopotential height analyses. Anindependent check of the ageostrophic features notedhere could be performed by constructing analogouscomposites using actual wind and pressure observationstaken at ships and surface stations.

The enhanced near-surface convergence associatedwith the strong cross-isobaric flow in the west-north-


western quadrant and the southern quadrant of the con-tinental low pressure area may account for the morefrequent occurrence of low-top thick or stratiform cloudcover in these sectors of the cyclones over land (seeyellow pixels in Figs. 5a and 5b). As noted by Carlson(1991, Section 9.1), the extensive decks of low stratusclouds often seen to the northwest of midlatitude cy-clones are associated with frictionally forced ascent inthe boundary layer, and with dynamically forced descent(mostly due to negative temperature advection) at higheraltitudes.

5. Cloud patterns accompanying tropicaldisturbances

To examine the cloud organization in prevalent trop-ical weather systems in the western Pacific, the com-posite procedure described in the previous sections hasbeen applied to the cloud and ECMWF data in thatregion for the warm season (June through September).An array of 15 reference sites extending from 118 to218N, and from 1218 to 1418E (see Fig. 5c of LC95)are used in determining the key dates for constructingthe composites. The patterns for the anomalous amountsof selected cloud types, as obtained by combining the15 individual composites in a common coordinate sys-tem, are shown using stippling in Fig. 7 for the ISCCPdata (left panels) and the surface synoptic reports (rightpanels). Superposed on the cloud patterns are compos-ites of the ECMWF data for height (contours) and wind(arrows) at 1000 mb.

The satellite composites are representative of thecloud organization in tropical convective disturbances.Some of these circulation systems are associated withthe wavelike phenomena described by Lau and Lau(1990), among others. The cloudy episodes consideredin the composite procedure may also include typhoonpassages. In their typically northwestward journeyacross the western Pacific, the tropical wave and ty-phoon disturbances are accompanied by thick cloudswith high tops in the vicinity of the low pressure center(see Fig. 7a). The deep convective towers thin out grad-ually toward the trailing edge of the system, so that theanvil-type clouds with high tops and relatively lower tprevail to the south-southeast of the low center (Fig.7b), where the outflow in the upper troposphere pref-erentially occurs. The leading edge of these systems(i.e., north of the low) is populated by low-top/thin cloudelements (Fig. 7c).

Comparison between Figs. 7a and 7d reveals that thehigh-top/thick clouds detected by the satellites are col-located with nimbostratus clouds as observed from thesurface, thus suggesting that the cloud cover near thelow center has a large vertical extent. The surface-basedcloud type that exhibits the closest spatial correspon-dence to the high-top/thin clouds (Fig. 7b) is thin al-tostratus (Fig. 7e). In particular, note the enhanced cloudamounts south of the low center in Figs. 7b and 7e. A

good match is evident between the enhanced cumulus(Fig. 7f) and low-top/thin (Fig. 7c) clouds at the north-ern (leading) edge of the system. In the region south ofthe low center, the cumulus clouds appearing in thesurface-based composite (Fig. 7f) are not evident in thesatellite composites for low-top/thin (Fig. 7c) clouds.These low clouds may be obscured from the satelliteview by the high-top anvil clouds lying aloft.

The composites of the surface reports of nonprecip-itating stratocumulus and stratus clouds (not shown) in-dicate an increase of more than 5% of these cloud typesin the vicinity of the low center. These results are con-trary to the reduction of cloudiness in that region, asinferred from the ISCCP composite of low-top/thickcloud, which has a pattern similar to Fig. 7c. The un-derestimation of low cloud amount in the satellite com-posite is again attributable to the shielding effect of thehigh-top/thick clouds above the low center (Fig. 7a).

The cloud types displayed separately in individualpanels in Fig. 7 are combined in the color mosaics inFig. 8a for ISCCP and Fig. 8b for surface data. Theanomalous frequency of light rain and heavy rain reportsis presented in Fig. 8c. Superposed on the pixel patternsare ECMWF products of anomalous 1000-mb heightand wind in Figs. 8a and 8b, and 500-mb vertical ve-locity in Fig. 8c. The procedure for filling the colorpixels is similar to that used in constructing Figs. 4 and5 for the extratropical cyclones, except that each pixelin Fig. 8 represents a one-half percent enhancement ofa certain cloud type or weather type.

The pattern in Fig. 8a illustrates more clearly thenorth–south asymmetry in the cloud-top altitude of theoptically thin clouds with respect to the low center, withvirtually all the low clouds being situated to the north,and the high clouds to the south. The low center itselfis primarily covered by high-top/thick clouds. This or-ganization is reproduced to a certain extent by the sur-face-based composite (Fig. 8b), which yields a relativelyhigher abundance of low-lying cumulus clouds under-neath the anvil clouds situated south of the low center.

The composite of weather types (Fig. 8c) indicatesthe occurrence of heavy and light rain through much ofthe low center. The broad pattern of precipitation basedon surface observations is in good agreement with theshield by high-top/thick clouds as deduced indepen-dently by the satellite dataset (Fig. 8a). The precipitationzone is also consistent with the region of ascent inferredfrom the ECMWF analyses. The extension of heavy rainto the southeast of the low center may be related to theenhanced divergent outflow at 200 mb in this quadrant(see Fig. 10c of LC95). The number of rain reports ismuch less in the regions of weak subsidence locatednear the northern and southern edges of the plottingdomain.

6. DiscussionPrevious studies on the relationships between cloud

cover and atmospheric flow patterns are often based on


FIG. 7. As in Fig. 3 but for composite patterns based on 15 reference sites in the subtropical western Pacific, and for(a) high-top/thick, (b) high-top/thin, and (c) low-top/thin clouds in the ISCCP dataset, and (d) nimbostratus, (e) thinaltostratus, and (f) cumulus in the surface reports. Note the different scale bars used for the top four panels and for thebottom two panels. Contour interval for anomalous 1000-mb height field: 5 m. Solid (dashed) contours indicate positive(negative) values.


FIG. 8. As in Fig. 4 but for composite patterns based on 15 reference sites in the subtropical westernPacific. Each color represents 0.5% increment in cloud amount or frequency of occurrence of weather types.Contour intervals for anomalous 1000-mb height and vertical velocity fields: 5 m and 2 3 1022 Pa s21. Solid(dashed) contours indicate positive (negative) values.


qualitative interpretations of the pertinent data fields.Comparisons between satellite and surface observationsof cloudiness have heretofore mostly been concernedwith climatological statistics. In LC95 and the presentpaper, special analysis tools have been designed to in-vestigate the interactions between the cloud and cir-culation fields on a more quantitative and objective ba-sis, and to compare in greater detail the satellite- andsurface-based cloud patterns associated with two spe-cific synoptic phenomena: the midlatitude cyclonewave, and the tropical convective disturbance. An over-all consistency is noted between the propagation char-acteristics and spatial structure of cloud cover as de-duced from the ISCCP products and the correspondingresults obtained using surface observations. This generalagreement among the two sets of findings lends credi-bility to the usefulness of both datasets for diagnosinga wide range of atmospheric behavior. It is demonstratedthat the complementary nature of the two datasets, withthe satellite platforms viewing the top of the cloud sys-tems from space and the surface observers examiningthe same systems from below, can provide useful in-formation on the vertical distribution of cloudiness. Sev-eral discrepancies are noted between the results basedon ISCCP and surface observations. The most strikingexample is the underrepresentation in the satellite com-posite of low-level clouds under the high cloud shieldeast of the extratropical cyclone center (compare Figs.3c and 3g). Some of these differences are evidentlyattributable to systematic biases inherent in the observ-ing techniques and data processing procedures used inproducing the datasets examined here.

The ISCCP and surface cloud observations have beencollected using radically different methodologies. More-over, the amount of various cloud types in these twodatasets has been defined by applying disparate sam-pling procedures in both the spatial and temporal do-mains. Implicit in such definitions and data reductionprocedures are many assumptions concerning the char-acteristic space scales and timescales for space and sur-face observations. For instance, the ISCCP estimates ofthe cloud amounts are based on sampling within a 3-hwindow of satellite pixels situated in square grid boxeswith dimensions of 280 km, whereas the cloud amountsentered into an individual surface synoptic report pertainto the instantaneous skycover within the field of viewof the observer (typically limited to tens of kilometers).Inspite of the dissimilarities among the information in-put from satellite and surface observations, some degreeof consistency among the results based on these twodatasets is still discernible. This level of agreement be-tween the findings from the two data sources is achievedin part by incorporating a large number of similar eventsin the composite procedure.

Pursuant to the demonstration of the applicability ofsatellite and surface cloud data products to the study ofselected circulation systems and the attendant atmo-spheric processes, it may be of interest to analyze the

interactions among the cloud and circulation fields inother meteorological features. The scope of these in-vestigations could conceivably be extended beyond themidlatitude cyclones and tropical disturbances consid-ered thus far to phenomena with a broad range of spacescales and timescales. Such circulation systems couldinclude mesoscale features in extratropical frontal zonesand low-latitude convective complexes, marine stratusdecks associated with subtropical anticyclones, propa-gating intraseasonal oscillations near the equator, tele-connection patterns in the monthly and seasonal aver-aged midlatitude flow, and variations related to the ElNino–Southern Oscillation. Some of the above phenom-ena (such as those related to mesoscale processes) wouldhave to be examined using cloud and other meteoro-logical data with high spatial and temporal resolutions(on the order of 10–30 km and several hours, respec-tively). New analysis procedures would have to be de-veloped for examining specific classes of phenomena.For instance, individual case studies (instead of com-posite analysis) are probably more suited for investi-gating the nature of subsynoptic cloud features. Sus-tained efforts to examine different modes of atmosphericvariability by the joint application of satellite cloudproducts and conventional meteorological datasets (suchas wind, temperature, and geopotential height fields)will hopefully facilitate closer interactions among theresearch communities specializing in atmospheric dy-namics and those in cloud and radiation processes.

Acknowledgments. We thank J. R. Norris for makingthe surface synoptic reports available to us, S. A. Kleinand J. M. Wallace for helpful discussions in the researchphase of this work, and A. J. Broccoli, A. D. Del Genio,S. A. Klein, J. R. Lanzante, J. R. Norris, and B. J. Sodenfor offering perceptive comments on the manuscript.

APPENDIX

Data Analysis Procedures

The surface reports are first sorted according to timeand location of observation. For a given day, surfaceobservations taken within individual grid boxes withdimensions of 2.58 of latitude by 2.58 of longitude aregrouped together. This particular size of the grid boxeshas been chosen to match the spatial resolution of theISCCP and ECMWF datasets. At each grid box, a dailytally is then taken of the available number of reportsNct of each selected cloud type ct and of the availablenumber of reports Nwt of each selected surface weathertype wt.

The cloud types ct processed in this study includecumulus (Cu), stratocumulus (Sc), stratus (St), cumu-lonimbus (Cb), fog (Fg), thin and thick altostratus (As),thin and thick altocumulus (Ac), nimbostratus (Ns), thinand thick cirrus (Ci), cirrostratus (Cs), cirrocumulus(Cc), and a special category indicating the total cloud


cover. The definitions of these cloud types in terms ofthe standard synoptic codes are given in Table 2 of Hahnet al. (1994). These individual cloud types are groupedinto three broad cloud levels cl according to the altitudeof the cloud base: Cu, Sc, St, Cb, and Fg are classifiedas low clouds; As, Ac, and Ns are regarded as middleclouds; and Ci, Cs, and Cc are treated as high clouds.

Several broad categories of weather types wt are con-sidered in this study: heavy rain [corresponding to re-ports with standard World Meteorological Organizationweather codes (ww) indicating values of 63–65 and 81–82], light rain (ww 5 14–16, 20–21, 25, 50–55, 58–62, and 80), heavy snow (ww 5 37, 39, 73–75, and 86),light snow (ww 5 22, 26, 36, 38, 70–72, 76–79, 85),and fog (ww 5 10–12, 28, and 40–49). This groupingis coarser than that used by Petty (1995), who parti-tioned the weather codes according to intensity (ex-tremely light, light, moderate/heavy, etc.), phase (liquid,snow, mixed, hail, etc.), and character (steady, showery,strong convection, etc.) of the precipitation being re-ported. Almost all weather codes contributing to lightprecipitation (rain or snow) in our study are assignedto the light or extremely light intensity classes by Petty.Similarly, heavy precipitation in our study correspondswell to the moderate/heavy intensity class in Petty’sscheme. The snow and liquid categories used in the twoclassification methods are also consistent with each oth-er.

A separate daily tally is taken of the total number ofcontributing reports for each of the three cloudclN total

levels cl, and of the total number of surface weatherobservations . Note that represents a count ofw clN Ntotal total

all available observations (including reports of clearsky) for a given cloud level. It is possible that a givensynoptic report contributes to at a certain cloudclN total

level but not to the tally at other levels. The daily sumof the Nct observations of fractional cover Fct by eachselected cloud type ct, that is, 5 S Fct, is also storedFct

in each grid box. Here the summation is taken over theavailable Nct observations for a given day. The quantity

, when divided by Nct represents the daily averagedFct

fractional cover at a given grid box by cloud type ctwhen it is present. This variable, , will be used inFct

Eq. (A1) to define the cloud amount.The end product of the data processing procedure

described above consists of daily time series of gridded,near-global arrays of , Nct, Nwt, , and forcl wF N Nct total total

each cloud or weather type, and for each cloud level.These arrays portray the spatial distributions of the oc-currence of individual cloud or weather categories dur-ing a specific day, and are hence suited for mapping ordiagnosis using various techniques developed for con-ventional meteorological fields. Inspection of the datacoverage over our regions of interest (i.e., the north-western sector of the tropical Pacific and midlatitudeNorthern Hemisphere) indicates that the average numberof contributing synoptic low-cloud (middle-cloud) re-ports in a 2.58 3 2.58 grid box ranges from 1–2 (0.5–

1) per day in the tropical and extratropical maritimesites, to 4–6 (3–4) per day in the extratropical land sites.

Following Hahn et al. (1994), the climatologicalamount CLIMct of a given cloud type ct in a given gridbox is obtained by

N FO Oct ctCLIM 5 . (A1)ct clN NO Ototal ct

Here all summations are taken over all the days in eitherthe 6-month northern cool season (October throughMarch) or the 4-month northern warm season (Junethrough September) within the 1983–90 period. Thisspecific period is chosen to match the temporal coverageof the ISCCP dataset used in LC95. The superscript clin the term in Eq. (A1) indicates the cloud levelclN total

category under which the cloud type ct in question isclassified (see details earlier in this appendix). For in-stance, for low clouds is used to determine theclN total

climatology of stratus, whereas for middle cloudsclN total

is used to compute the corresponding statistic for al-tostratus.

The definition in Eq. (A1) may be interpreted as fol-lows. Since represents the number of contributingclN total

reports of cloudiness at level cl, the ratio SNct/S clN total

[first fraction on the rhs of Eq. (A1)] is hence a measureof the mean frequency of the occurrence of cloud typect. Also recalling that is the sum of fractional cloudFct

cover reported in Nct observations in a given day, thefraction S /S Nct [second fraction on the rhs of Eq.Fct

(A1)] thus represents the long-term averaged fractionof coverage by ct when it is present. The climatologicalcloud amount is, therefore, seen to be the product ofthe mean frequency of a given cloud type and the meanfractional cover by this cloud type when it occurs.

In analogy with the definition for frequencies of in-dividual cloud types, the climatological frequency ofthe occurrence of a given weather type wt in a grid boxis computed as

NO wtCLIM 5 . (A2)wt wNO total

To ensure that the cloud- or weather-type climatol-ogies are based on sufficient data input, the above com-putations are performed only for grid boxes where

or are nonzero in at least 25% of the totalcl wN Ntotal total

number of days in seven seasons considered here. Theclimatology is regarded as missing for grid boxes thatfail to meet this criterion and no further analysis is madefor these boxes.

The typical cloud and weather patterns accompanyingselected synoptic episodes are described using a com-posite procedure. Suppose that altogether M outstandingsynoptic cases are identified, then the composite amountCOMPct of the cloud type ct and the composite fre-quency COMPwt of the weather type wt in each gridbox can be computed using formulae analogous to thosein Eq. (A1) and (A2), except that all summations are


taken over the common set of M cases only (instead ofevery day of a certain season in all years considered,as is done in evaluating the climatology). The compositevalues for a given grid box are determined only if

or are nonzero in at least 25% of the M se-cl wN Ntotal total

lected cases. Otherwise the composite cloud amount orweather type is treated as missing for the grid box inquestion. The departures of the composite data from thelong-term climatology are represented by the anomaliesANOMct 5 COMPct 2 CLIMct and ANOMwt 5 COMPwt

2 CLIMwt.

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