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Cloud Radiative Forcing in Pacific, African, and Atlantic Tropical Convective Regions J. M. FUTYAN, J. E. RUSSELL,
AND
J. E. HARRIES
Blackett Laboratory, Imperial College, London, United Kingdom (Manuscript received 22 October 2003, in final form 2 February 2004) ABSTRACT The high degree of cancellation between longwave (LW) and shortwave (SW) cloud radiative forcing (CRF) observed in the Pacific warm pool region has generally been assumed to be a property of all convective regions in the Tropics. Analysis of the (Earth Radiation Budget Experiment) ERBE-like data from the Clouds and the Earth’s Radiant Energy System (CERES) instrument on the Terra satellite reveals that a similar degree of cancellation occurs over the African convective region at monthly and longer time scales, but only in the area average. In the Atlantic intertropical convergence zone (ITCZ), the degree of cancellation is lower, particularly during the summer months, where the area-average SW forcing typically exceeds the LW forcing by more than 20 W m 22 . This behavior is similar to that found previously for the eastern Pacific ITCZ region, which is consistent with the similarity in dynamics between these two regions. Over Africa, substantial seasonal and spatial variations in net CRF occur, with significant departures from cancellation within the convective region. These are explained here by a combination of surface albedo and cloud effects. In particular the large negative values of net CRF found in the summer months result from the inclusion of the radiative effects of low cloud present during the course of the month in the monthly mean cloud forcings. This work highlights the limitations of monthly mean radiation budget data for studies of rapidly evolving processes such as convection, indicating the need for studies at a higher time resolution.
1. Introduction The concept of cloud radiative forcing (CRF) provides a means of quantifying the effect of clouds on the earth’s radiation budget. The longwave (LW) component [LWCRF, Eq. (1a)] measures the reduction in the emission of thermal radiation to space due to the presence of clouds, and the shortwave (SW) part [SWCRF, Eq. (1b)] quantifies the increase in the reflection of solar radiation. The balance between these two counteracting effects on the overall energy balance determines the sign and magnitude of the net cloud forcing (net CRF): LWCRF 5 OLR clear 2 OLR cloudy ,
(1a)
ref SWCRF 5 F clear 2 F ref cloudy ,
(1b)
where OLR is outgoing longwave radiation flux, and F ref is the reflected solar flux. The subscripts ‘‘clear’’ and ‘‘cloudy’’ refer to clear-sky (cloud free) and cloudy (all sky) conditions. Results from the Earth Radiation Budget Experiment (ERBE) revealed a high degree of cancellation between the longwave and shortwave cloud forcings in tropical convective regions (Ramanathan et al. 1989; Harrison Corresponding author address: Mrs. J. M. Futyan, Space and Atmospheric Physics Group, Blackett Laboratory, Imperial College, London SW7 2BP, United Kingdom. E-mail:
[email protected]
q 2004 American Meteorological Society
et al. 1990). Monthly average longwave forcings reach their maximum values of 50–100 W m 22 in the convectively disturbed regions of the Tropics; however, this heating effect is nearly cancelled by a correspondingly large shortwave forcing. Kiehl and Ramanathan (1990) demonstrated that the net CRF was within 610 W m 22 , the approximate gridbox-scale uncertainty for ERBE monthly mean data, throughout the Indonesian region. These observations provoked interest in why this cancellation occurs. Kiehl (1994) suggests that the near cancellation observed is simply a coincidence. He argues that if the dominant cloud type determining both the LWCRF and SWCRF is assumed to be optically thick high cloud with albedo similar to that typically observed, the cloud-top height required for cancellation is found to be close to that of the tropical tropopause. In fact, there is a distribution of cloud types of varying optical depth and height associated with convection, which individually cause net forcing ranging from positive to highly negative. The observed near cancellation corresponds to an average over this ensemble (Jensen et al. 1994; Hartmann et al. 2001; Cess et al. 2001). Hartmann et al. (2001) suggested that this behavior may be indicative of feedbacks in the climate system influencing the ensemble structure and proposed a simple mechanism based on energy balance between convective and neighboring nonconvective regions. According to this mechanism, if the net flux into the convective
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region at the top of atmosphere were smaller than that into an adjacent nonconvective region, then the convective region would lose energy relative to the nonconvective region. This is proposed to result in changes in the strength of the overturning circulation between these regions, which in turn alters the cloud properties (albedo) and hence CRF in the convective column, driving the net flux back toward that in the nonconvective region. If the nonconvective region is predominately clear sky and has low net CRF then so will the convective region. The mechanism breaks down if ocean heat transports in or out of either region mean the two are not in equilibrium. The validity of this mechanism and of some of the simplifying assumptions made by Hartmann et al. (2001) have been disputed (Chou and Lindzen 2002). Zero net forcing has also been used as an observational constraint in several studies into potential cloud– climate feedback processes (Ramanathan and Collins 1991; Pierrehumbert 1995; Fu et al. 2002), while other proposed feedbacks rely on changes in the distribution of cloud types associated with convection (Chou and Neelin 1999; Lindzen et al. 2001). Clearly, to understand the validity of these assumptions requires an understanding of where, how, and why cancellation occurs in the current climate. Near cancellation between LWCRF and SWCRF has been assumed to be a generic property of all tropical convective regions, over both land and ocean (e.g., Kiehl 1994). However the majority of regional-scale studies have concentrated on the western tropical Pacific warm pool region, and those that exist for other regions do not necessarily find a similar degree of cancellation. For example, using ERBE data, Rajeevan and Srinivasan (2000) found negative net forcings as large as 230 W m 22 over the northern part of the Indian monsoon region (08–308N, 608–1208E) in the northern summer. This is suggested to be due to the frequent occurrence of very high optical depth clouds in this region. Hartmann et al. (2001) also found negative net forcings greater than 220 W m 22 in the eastern Pacific tropical convergence zone (7.58–158N, 1008–1408W) during July and August. The International Satellite Cloud Climatology Project (ISCCP) data imply the occurrence of more mid- and low-level clouds and a higher proportion of optically thick to optically thin high cloud in this region than in the western tropical Pacific, which is consistent with the observed differences in CRF. It should be noted that the negative net CRF found in this region is not inconsistent with Hartmann et al.’s proposed feedback process. In the present work, the radiative effects of convective clouds in the Atlantic and African convective regions are investigated and the observed behavior is compared with that seen in the Pacific warm pool region. This study was carried out in preparation for a more detailed analysis of the radiative effects of convective clouds in the African and Atlantic regions combining high time
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resolution data from the two new instruments on the Meteosat-8 satellite, the Geostationary Earth Radiation Budget (GERB) radiometer and Spinning Enhanced Visible and Infrared Imager (SEVIRI). We find that on average a similar degree of cancellation is found over African land regions to that seen in the Pacific, but larger seasonal and spatial variability also occurs. Part of this spatial structure is attributed to albedo variations of the underlying land surface, and part to structure in the cloud field. In particular, regions of large negative monthly mean net forcing are found to be associated with the predominance of bright low cloud on some days during the course of the month. Over the Atlantic, the behavior found is more similar to that found in the eastern Pacific, with a lower degree of cancellation related to lower LWCRF. Our ability to interpret the observed differences between regions is limited by the use of data averaged over much longer time periods than those on which convective systems develop, highlighting the need for studies at a higher time resolution. 2. Methodology Previous studies have used two measures to quantify the degree of cancellation between LWCRF and SWCRF: net CRF 5 LWCRF 1 SWCRF, and the cloud forcing ratio, R 5 2SWCRF/LWCRF. Clearly perfect cancellation is implied by net CRF 5 0, or R 5 1.0. The net CRF has the advantage of providing directly the actual energy difference caused by the presence of clouds for the surface–atmosphere column, but its use to quantify the degree of cancellation is limited by its dependance on cloud fraction. As net CRF is proportional to the fraction of the region covered by cloud, the value found can depend on the size of the region chosen for averaging. It is therefore not the most useful measure of the degree of cancellation when comparing two regions that may be of different size or have differing levels of cloudiness. This problem is removed by the use of the ratio, R, although the value of R only has meaning in regions where clouds are present, and may be misleading where the LWCRF is small. In this study, R will be used to quantify the degree of cancellation, but values of net CRF will also be discussed. Previous studies have tended to define a region of study using a fixed latitude–longitude box within which the analysis is performed (Kiehl and Ramanathan 1990; Rajeevan and Srinivasan 2000; Hartmann et al. 2001). However, this approach was found to be problematic for the comparison between regions performed in this study, due to the proximity of other cloud regimes (such as the stratocumulus deck off the west coast of southern Africa) to the area of active convection in the African– Atlantic region, and because of the large seasonal migration of the intertropical convergence zone (ITCZ) in this region. While a fixed box within the convective area could be selected for each region and season, the results found depend strongly on the fairly arbitrary
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FIG. 1. Monthly mean fractional coverage of (left) deep convective and (right) cirrus cloud in the Pacific region for Jan 2001. The box marked shows the region within which the LWCRF limit is applied, and the area covered by cross hatching indicates the grid boxes selected.
choice of area included. To avoid this, the convective region was defined to consist of all grid boxes with LWCRF greater than 30 W m 22 within a latitude–longitude range large enough to include the entire convective area. High monthly mean LWCRF indicates the regular occurrence of high clouds during the course of the month and so acts as a tracer for frequent convective activity. The cutoff value of 30 W m 22 was chosen based on the typical cloud forcing values found for a region known to lie entirely within the stratocumulus deck (a region of cool SST and subsidence, dominated by low cloud cover), and is similar to the value of 35 W m 22 that Tian and Ramanathan (2002) found marked the edge of the region with large fractional coverage of high cloud (in the climatological average) over the tropical Pacific. The LWCRF threshold is applied separately to each region in each month, allowing for seasonal changes in the location of strongest convection. This approach (of preselecting convective regions) is similar to that of Allan et al. (2002), who used regions of strong mean ascent to trace the location of convection. In the following, the Pacific convective region is defined to contain all grid boxes satisfying the above LWCRF condition, within 208S–208N, 1108E–1808. For the Atlantic, the LWCRF limit is applied to grid boxes within 208S–208N, 408W–208E with surface flag ‘‘ocean,’’ and for the African region the area of interest is 308S–208N, 308W–508E, for surface types ‘‘land’’ and ‘‘desert.’’ Using spatial maps of the monthly mean distribution of cloud cover from the ISCCP D2 dataset, we can investigate the suitability of the convective regions selected using this method. Figures 1 and 2 show the distribution of deep convective [optically thick (optical depth t greater than 23) high cloud] and cirrus [thin (t , 3.6) high cloud] for the example month of January 2001 for the Pacific and African–Atlantic regions, re-
spectively. Grid boxes with cirrus cloud fraction greater than 10% or deep convective fraction greater than 2% are shaded, and the region selected by the LWCRF limit is highlighted by cross hatching. An ideal method would select all grid boxes within which convection or associated cloud cover occurs, and exclude all regions dominated by low nonconvective clouds. Here, all grid boxes with substantial coverage of deep convective and cirrostratus cloud (intermediate optical depth high cloud, not shown) are included for all three regions in January 2001 (similar results are found for other months). However, the LWCRF limit imposed excludes grid boxes with significant coverage of cirrus cloud around the edge of the convective regions. In particular, for the African region during the winter months (December–February), the excluded grid boxes cover an extensive area, and can be shown to contain predominately the thinnest cirrus cloud (t , 1.3). Thin cirrus forms by two mechanisms: outflow from convective anvils, and large-scale uplift independent from convection (Jensen et al. 1996). Given the concentration of the excluded cirrus around the active convective region, it seems likely to be related to convective activity and arguably should be included in the region selected. As thin high cloud tends to have larger LWCRF than SWCRF, and hence R , 1 (Hartmann et al. 2001; Jensen et al. 1994), its exclusion would be expected to cause a high bias in the values of R calculated here. Nevertheless, 30 W m 22 is still considered an appropriate cutoff as adjusting the LWCRF limit to include more of this cirrus would also result in the inclusion of significantly more grid boxes with large fractional coverage of low cloud, not associated with convection, particularly for the African land and Atlantic regions. SWCRF dominates for low cloud, hence its inclusion would bias the value of R high.
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FIG. 2. Same as in Fig. 1, but for the African–Atlantic region. Note only grid boxes for which the data have surface type flag ocean are included in the Atlantic convective region, and only those with land or desert flags in the African region. The two boxes show the area of interest in each case.
The value of 30 W m 22 chosen to select the convective region provides a reasonable balance between these two effects, and represents as good a separation of convective and nonconvective areas as is possible using monthly mean data. In fact, sensitivity testing indicates that the area-average value of R does not depend strongly on the precise value of the LWCRF limit used. The difference between the value of R found using a LWCRF limit of either 20 or 40 W m 22 and that found using a cutoff at 30 W m 22 is generally less than 0.05, with the lowest sensitivity in the Pacific region. Slightly larger increases in R occur in the Atlantic region when the limit is reduced to 20 W m 22 , presumably due to the radiative effects of including more stratocumulus cloud. Results are presented either as area-weighted averages over the convective region, or as frequency distributions of the individual gridbox values. To produce the distributions, the data is binned (at 10 W m 22 intervals for LWCRF and SWCRF, and at 0.1 intervals for R) and the percentage of convective grid boxes in each bin determined. Grid boxes within the convective region for which no estimate of the clear-sky flux is available are simply excluded from the analysis. In general the number of such grid boxes is small and unlikely to affect the area-average values or distributions presented below. Months with substantial missing data are included, but will be flagged as such. 3. Data The radiation budget quantities presented here are calculated from monthly mean ERBE-like fluxes from the Clouds and the Earth’s Radiant Energy System (CERES) instrument (Wielicki et al. 1996) on board the Terra satellite (ES-4 dataset, edition 2). These data
have been processed using the ERBE scene identification process, angular models and temporal interpolation scheme (Barkstrom et al. 1989; Young et al. 1998), to provide a dataset that is as consistent with the ERBE data as possible. More accurate flux estimates from CERES, using new angular models and an enhanced temporal interpolation scheme involving the use of geostationary satellite data (Young et al. 1998; Wielicki et al. 1996) are planned, but were not available at the time of writing, and would be less directly comparable to the results of previous studies based on ERBE and ERBE-like data. The ERBE mission was designed to provide accurate estimates of monthly mean fluxes, using the precessing orbit of the Earth Radiation Budget Satellite (ERBS) to sample all local times over the course of a month, thus building up coverage of the mean diurnal cycle. Following the failure of CERES on the Tropical Rainfall Measuring Mission satellite (TRMM), CERES data are obtained from a single sun-synchronous satellite (Terra) with an equator crossing time of 10:30 A.M. This limited sampling of the diurnal cycle results in biases in the monthly mean fluxes measured by Terra, the impacts of which are discussed in section 5b. At the gridbox scale (2.58 3 2.58), rms errors in net CRF are of the order of 610 W m 22 and (for forcings typical of convective regions) are ø60.2 for R (Harrison et al. 1990; Young et al. 1998). These errors are reduced by spatial and temporal averaging. Cloud parameters are obtained from the ISCCP D series datasets (Rossow and Schiffer 1999). These data contain 3-hourly (D1) or monthly mean (D2) fractional coverage of each of the ISCCP cloud types (defined by height and optical depth limits) for daylight hours, gridded at the same spatial resolution as the CERES data.
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FIG. 3. Fractional frequency distributions of gridbox values of (left) R, (middle) LWCRF, and (right) SWCRF for the Pacific, African, and Atlantic convective regions. Averaged for all months of 2001 and 2002.
4. Results a. Analysis of CERES data Figure 3 shows the annual mean frequency distributions for gridbox-scale values of R, LWCRF, and SWCRF for the Pacific warm pool, African land, and Atlantic convective regions defined previously. Over the Pacific the distribution of R values is sharply peaked around a modal value of 1.1, indicating a fairly high degree of cancellation throughout the convective region. This is consistent with the results found by Kiehl and Ramanathan (1990) for the Indonesian region (108S– 108N, 1108–1608E) using ERBE. Over African land regions, the modal value is the same as in the Pacific region, but the distribution is much broader, with an excess of regions for which R , 1 (positive net CRF) and a small tail of high R (large negative net CRF) values. Over the Atlantic, the distribution is broader than that for the Pacific, and is shifted toward higher R values, peaking at R ø 1.3 (SWCRF 30% larger than LWCRF). The lower average degree of cancellation observed for the Atlantic region results from the fact that although
the SWCRF for this region is similar to that in the other two regions, the LWCRF is lower (both in terms of typical and peak values). It should be noted that, as LWCRF is the denominator in R, a smaller LWCRF implies that a smaller imbalance in net CRF is required to produce a given deviation of R from one. However, even in terms of net CRF, the degree of cancellation is lower for the Atlantic. Over the African land region, there is a deficit of grid boxes with the very highest LWCRF and an excess with low SWCRF, relative to the Pacific warm pool region. Figure 4 shows the seasonal and interannual variations in the area-average value of R (i.e., the ratio of the area-average monthly mean SWCRF and LWCRF) for the three convective regions. A similar degree of cancellation occurs (in the area average) for the Pacific and African regions in most months, with R ø 1.1, although significantly lower values of R (ø0.85, equivalent to positive net CRF of ø10 W m 22 ) are seen over African land regions in the spring. The most substantial departures from cancellation occur for the Atlantic ITCZ region in northern summer. From May to September the area-average value of R is greater than 1.4, which cor-
FIG. 4. Seasonal variations in the area averaged value of R (calculated as 2SWCRF / LWCRF ) for the Pacific, Atlantic, and African convective regions for Mar–Dec 2000 and Jan– Dec 2001 and 2002. Results for all three years are shown to demonstrate the high level of repeatability in the seasonal cycle. The larger variability seen for the Atlantic may relate to the inclusion of fewer grid boxes in the convective region [ø40–90 grid boxes per month (fewer in summer), compared to ø100 for Africa, and ø300 for the Pacific]. It should also be noted that, the value of R for Jan and Nov 2001 and Feb, Oct, and Nov 2002 for the African region may be unreliable due to relatively large amounts of missing data within the convective region.
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FIG. 5. Contour plot of net CRF for Jul 2001. The two boxes show the regions within which the LWCRF limit is applied, and the convective region selected by this threshold is highlighted by cross hatching. Missing data are filled with a grid pattern.
responds to net CRF greater than 20 W m 22 . This is similar to the behavior found by Hartmann et al. (2001) for the east Pacific ITCZ region in July and August using ERBE data. In the Pacific warm pool region, the mean LWCRF and SWCRF vary synchronously through the year, with the SWCRF always a few watts per meter squared larger in magnitude than the LWCRF, hence R is essentially constant at ø1.1. The seasonal variations in the areaaverage value of R over Africa and the Atlantic are due to month to month variations in the SWCRF while the LWCRF remains relatively constant. The seasonal variations in the degree of cancellation over African land and the Atlantic apparent in Fig. 4 account in part for the greater widths of the annual mean distributions in these regions seen in Fig. 3. However, inspection of the individual monthly distributions for the three regions show that these are also broader for the African and Atlantic regions than for the Pacific. This larger spatial variability is most notable for the African land region where it can, in part, be explained by the larger variability in surface albedo found over Africa compared to the predominantly oceanic Pacific region. As cloud forcing is defined as the difference in flux between clear and cloudy conditions its magnitude is dependant on the properties of the corresponding clear scene (i.e., of the surface and atmospheric profile in the clear region); the same cloud will produce a smaller SWCRF (and hence lower R) over a bright desert surface than over the darker ocean. As can be seen in Fig. 5, positive values of net CRF (R , 1) are found where
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the convective region extends over the southern edge of the Sahara Desert (a similar effect is seen for the Kalahari Desert in the winter months). Comparison of the spatial variations in net CRF with those in the total outgoing (emitted LW 1 reflected SW) clear-sky flux reveal common features of similar magnitude, confirming the importance of surface effects. However, features in the net CRF plots are clearly modulated by cloud effects and cannot all be explained in this manner. In particular, the band of large negative net CRF seen along the southern coast of West Africa in Fig. 5 (and throughout the summer) cannot be explained by surface effects. These grid boxes have highly negative net CRF, with magnitudes larger than 50 W m 22 and clearly do not demonstrate the near cancellation found in other areas. It should also be noted that given the higher surface albedo throughout the African region, the clouds must be brighter here than in the Pacific to achieve the same SWCRF (as it is the albedo contrast that is important). Therefore, the similarity in the distributions of SWCRF in Fig. 3 between the Pacific warm pool and African land regions actually imply a difference in the cloud properties between these regions. This makes the observed similarity in the overall radiative effects of these clouds all the more surprising. b. Further analysis using ISCCP data Using the ISCCP D2 data to compare the spatial distribution of deep convective and cirrus cloud over the Pacific with that of net CRF, reveals a correlation between regions with high-fractional cover of optically thick high cloud and those with more negative net CRF (higher R). Similarly, values of R , 1 (positive net CRF) occur where there is a lack of active convection, and thin cirrus cloud dominates. Thus, the small spread of R values seen in the Pacific region is associated with the existence of locations where convection is relatively favored or suppressed. This is what would be expected from modeling of the radiative effects of individual cloud types (Jensen et al. 1994; Hartmann et al. 2001), and supports the idea that cancellation occurs only in the average over the ensemble of cloud types. Within each grid box, a mixture of cloud types occurs during the course of the month, and this ensemble produces R ø 1 (hence the sharply peaked distribution seen in Fig. 3); the fact that deviations from this are correlated with changes in the relative proportions of the different cloud types indicates that cancellation is indeed due to a balance between the effects of clouds, which individually have very different radiative properties. This correlation is less apparent over Africa. However, ISCCP cloud maps do reveal a predominance of high thin (cirrus) cloud and lack of active convection (optically thick cloud) over the desert regions neighboring the convective region (e.g., along the southern edge of the Sahara during spring/summer). The lack of
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FIG. 7. ‘‘Daily’’ mean high cloud cover averaged over region A (defined in Fig. 6) and for an identically sized region within the Pacific warm pool (58–108N, 1408–1608E) for all days of Jul 2001. Means are produced as an average over all daylight hours of ISCCP D1 data and measure the combined coverage of deep convective, cirrostratus, and cirrus cloud types. FIG. 6. Monthly mean fractional coverage of stratocumulus cloud for the African–Atlantic region in Jul 2001. As in Fig. 1, cross hatching is used to highlight the convective region. The area defined as region A (Fig. 7) is also marked.
active convection over the desert is not surprising considering the limited moisture supply (source of latent heat), and suggests that the cloud cover results primarily from the spreading of anvil cloud from the neighboring convective region. The positive net CRF seen over the desert regions is likely to relate to a combination of this cloud effect and the surface albedo effect discussed previously. The low mean values of R seen in the spring over African land regions (Fig. 4) result from the inclusion of a relatively large number of such grid boxes, with high surface albedo and suppressed convection, in the region selected for analysis. These effects are also responsible for the excess of grid boxes with R , 1 found over the African land region compared to the Pacific region (Fig. 3). Figure 6 shows the monthly mean occurrence of stratocumulus clouds as defined in the ISCCP D series datasets (cloud top below 680 hPa, 3.6 , t , 23) for July 2001. A region of bright low cloud extends over the coast of West Africa in the region marked A in this plot. The time series of daily average high (cloud top above 440 hPa) cloud amount averaged over region A, shown in Fig. 7, demonstrates why it is included in the convective region selected using the LWCRF threshold, despite the substantial coverage of low clouds. The high cloud responsible for the relatively large LWCRF found in this region is not present consistently through the month, in fact, substantial coverage only occurs on a few days during the month. The intermittent nature of the convection observed in region A is consistent with the expected banded cloud structure of a
typical West African monsoon climatology (Barry and Chorley 1998, 267–268), and with the pattern of occurrence of mesoscale convective systems during the Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) field campaign (Martin and Schreiner 1981). In any convective region, the strength and amount of convective activity and hence the proportion of high cloud cover at a particular location will vary from day to day. Figure 7 provides a comparison of the variability in high cloud cover typical of the warm pool region and that found in region A. It is clear that in this warm pool region there is more high cloud present than in region A, with coverage only dropping below 20% on 2 days in the month. In region A high cloud cover greater than 20% is achieved on less than half the days in the month. In itself, this lower fractional coverage of high clouds would not affect the value of R found. However, on days when the high cloud fraction is less than 20% the low cloud fraction measured by ISCCP is ;40% in region A, compared to typical values of less than 10% in the Pacific region. It should be noted that, while low cloud is present throughout the month in both regions, the fraction measurable by satellites varies depending on the proportion of the field of view obscured by higher clouds. If coverage is calculated as a proportion of the unobscured part of the field of view, typical low cloud fractions are ;25% in the Pacific warm pool and ;60% in region A. On days when the high cloud cover is small, the influence of the substantial amount of low cloud present in region A, which is predominantly (;75%) moderately optically thick (and hence bright) stratocumulus cloud, is felt at the top of the atmosphere, producing a significantly negative net cloud forcing. In the Pacific the coverage of low clouds is relatively small, even on days when convection is suppressed, so
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the monthly mean cloud forcings provide a reasonably accurate estimate of the radiative effects of high convective clouds. By contrast, in region A, the fractional coverage of low cloud on days with little or no convective activity is comparable to (or greater than) the fraction of high cloud occurring on convectively active days. Hence the monthly mean forcings calculated for region A arise from a fairly equally weighted average over the radiative effects of these two distinct cloud regimes. It is clear that this region is not dominated by convective cloud cover throughout the month, and hence the monthly mean forcings would not be expected to be representative of those for convective clouds. The lack of cancellation between the monthly mean LWCRF and SWCRF seen in Fig. 5 for region A, therefore does not necessarily imply a difference in the structure of the convective ensemble in this region, although this might be expected on the basis of differences in local dynamics and forcings as discussed in section 5a. This example demonstrates the limitations of gridded monthly mean data for this kind of study. Convective systems form, develop, and decay on time scales of the order of 1 day and on spatial scales smaller than the ø280 km 3 280 km grid boxes used here (Machado and Rossow 1993). Thus, it is not possible to fully separate the effects of the convective cloud ensemble from other factors influencing the radiation balance in the region using these large-scale monthly mean data. This problem is clearly not unique to this coastal region of Africa. Region A simply provides a particularly good example of this limitation of monthly mean data. Unless almost all of the cloud occurring in a grid box during the course of a month is produced by convection, the monthly mean forcing will not be representative of the radiative effects of convective cloud systems. The large negative values of net CRF found in the northern part of the Indian monsoon region by Rajeevan and Srinivasan (2000) may also be attributable to this type of effect. Their results indicate that the clouds to the north of the monsoon region are on average brighter, but also lower than those farther south. Using ISCCP data, they find that the region of most negative net CRF corresponds to an area with high monthly mean coverage of optically thick high clouds. However, their results are also consistent with the presence of a mixture of this high cloud and bright low or midlevel cloud in this region. This is supported by Yu et al. (2001) who found maximum coverage of optically thick midlevel cloud (ISCCP cloud-type nimbostratus) over this part of eastern China. 5. Discussion In this work, we have addressed two issues. First, interesting similarities and differences between the radiative effects of convective clouds for the Pacific warm pool, African land, and tropical Atlantic convective regions have been found, the implications of which are
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discussed in section 5a. Second, this work has shown that some of the effects seen in the monthly mean forcings relate to shorter time-scale variations in the cloud field that are not resolved, highlighting the limitations of available radiation budget data for studies of rapidly evolving cloud systems. In section 5b, we discuss the effects of known uncertainties and sampling issues associated with the monthly mean data used here on the results presented. a. Similarities and differences between regions In the area average, the degree of cancellation is surprisingly similar for the African and Pacific regions, given the differences in the diurnal cycle and processes driving convective activity in these regions. Over land, convective activity peaks in the late afternoon or early evening in response to the peak in solar heating of the land surface (Duvel 1989), whereas convective activity is observed to peak in the early morning [around 0600 local standard time (LST)] for maritime regions (Hendon and Woodberry 1993; Yang and Slingo 2001; Soden 2000). The diurnal cycle is important in itself as the mean cloud forcings will depend on the time of day of maximum cloud cover (cloud present at night produces no SWCRF, but still affects the emission of thermal radiation to space), but also because it reflects differences in the development, and hence possibly the structure, of the convective ensemble. In the summer months, the dynamics of the African region are strongly influenced by the monsoon circulation (Barry and Chorley 1998), which would be expected to impact on the ensemble structure. As was noted previously, the differences in the surface properties (and hence clear-sky fluxes) between the regions mean that different cloud properties are required in the two regions to achieve the same radiative forcing. More substantial differences in the radiative effects observed for these two regions are apparent at smaller spatial scales, and for individual months, the causes of which have been discussed. However, when the behavior is considered at larger time and space scales, these differences average out, leading to the general similarity observed. Over the Atlantic, a lower degree of cancellation is observed, corresponding to lower LWCRF. Lower LWCRF is consistent with the lower-tropopause height and cooler sea surface temperatures (SSTs) found in this region than in the Pacific warm pool (Johnson et al. 1999). The lower LWCRF found is also consistent with the results of Gu and Zhang (2002), who find that nondeep clouds form a larger fraction of the total cloud ensemble over the Atlantic ITCZ than in the Pacific warm pool or African land region. In the Atlantic, warm SSTs are confined to a much smaller area than in the warm pool region; there are larger SST gradients and much stronger low-level convergence drives the convective activity (Gu and Zhang
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2002). The dynamical situation is more similar to that in the eastern Pacific ITCZ region, where Hartmann et al. (2001) found a similar lack of cancellation. ISCCP data also reveal similar differences between the average cloud ensembles in the Atlantic and Pacific convective regions to those found by Hartmann et al. between the eastern and western tropical Pacific. Within their proposed feedback mechanism, Hartmann et al. suggest that the negative net CRF found in the eastern Pacific ITCZ can be explained either by interactions with subsiding regions where there is extensive stratocumulus cover, and hence negative net CRF, or by ocean heat transports into the convective area. Both these ideas are equally applicable to the Atlantic region. However, the lower degree of cancellation and the seasonal variability in R observed for the Atlantic region could also be due to inclusion of varying amounts of low nonconvective cloud within the convective region. The difficulty in isolating the effects of convective cloud systems using monthly mean data makes it hard to determine the significance of the differences between the mean radiative forcings found in this region and those found in the warm pool region, and hence we cannot confidently attribute them to differences in dynamics or local conditions. This study also suggests that interesting seasonal variations (Fig. 4) in the radiative effects of convective clouds over the African and Atlantic region occur, which may be related to seasonal changes in dynamics or local forcings. However, our ability to interpret and attribute these changes is limited by the use of radiation budget data, which poorly resolve these rapidly evolving systems. Further analysis using high time resolution data will help to understand the causes of the variability observed, and the extent to which it is associated with changes in the convective ensemble. b. Sampling issues associated with monthly mean data from low-earth-orbiting satellites The limited diurnal sampling possible from Terra’s sun-synchronous orbit results in global mean bias errors of up to 26 W m 22 in the SW all-sky flux and of the order of 1 W m 22 in the LW all-sky flux (Young et al. 1998). In tropical convective areas, where there is a strong diurnal cycle of cloudiness, the errors introduced may be even larger. These bias errors, combined with an estimated 4 W m 22 overestimation of the clear-sky LW flux due to scene identification errors (Wong et al. 2000), suggest that the absolute values of net CRF given here may be up to 9 W m 22 too high. (For typical values of area-average LWCRF and SWCRF for the Pacific warm pool region, this constitutes an underestimate of ø0.15 of the value of R.) These bias errors are clearly important in determining the absolute values of fluxes and forcings, and hence in quantifying the extent to which cancellation between LWCRF and SWCRF actually occurs. Bias errors would
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TABLE 1. Area-average values of R for each of the three convective regions (selected using LWCRF . 30 W m22 ) for Mar 2000, based on the CERES instruments on both Terra and TRMM.
Terra TRMM
Pacific
Atlantic
Africa
1.10 1.18
1.24 1.30
1.04 1.10
be expected to be less important when performing a comparison between regions using a single dataset, as all regions are subject to the same error sources. While generally true, this assumption must be made with some caution in this case, due to differences in the diurnal cycle of cloudiness and phasing of convective activity between regions (Yang and Slingo 2001). This may result in differences in the magnitude of the bias errors between regions, thus producing a residual interregional bias. Estimates of these interregional biases are not available; however, comparison between the fluxes and forcings found using the 1 month of concurrent ERBE-like data from the CERES instruments on TRMM and Terra (March 2000) suggests that there is not a significant difference in the bias errors produced by Terra’s limited diurnal sampling between the regions considered here. TRMM’s precessing orbit provides very different (although still imperfect) diurnal sampling to that achieved by Terra, hence different diurnal sampling errors are expected. As can be seen in Table 1, values of R found from CERES on TRMM are higher than those found from Terra during the same month, which is consistent with the expected sense of Terra’s sampling bias, but all three regions are affected almost equally. Although data for a single month do not allow a full investigation of this effect, these results indicate that any interregional bias in the value of R introduced by Terra’s sampling pattern is small, and will not dramatically affect the conclusions reached here. Estimates of the degree of cancellation from monthly mean data from low-earth-orbiting satellites are limited not only by errors in the mean fluxes due to poor sampling of the diurnal cycle, but also by their inability to resolve higher time resolution changes in the cloud field. Cloud forcings calculated from monthly mean gridded data average together the effects of all clouds occurring within the spatial extent of a grid box during the course of the month. To make accurate observations of the radiative effects of individual cloud systems, even in terms of the monthly average cloud forcings associated with a particular category of cloud, requires the use of radiation budget data that can resolve those individual systems. 6. Summary Analysis of the radiative effects of convective clouds in the tropical western Pacific, African, and Atlantic regions, using ERBE-like data from CERES Terra, re-
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veals a surprising similarity in the area-averaged degree of cancellation between the LW and SW cloud forcings in the Pacific warm pool and African convective regions. Despite the obvious differences in surface type (albedo), diurnal cycle, and sources of convective instability, the average impact of the convective cloud ensemble on the top of atmosphere radiation budget at large time and space scales is essentially the same for the two regions. However, larger variability is observed within the African region, and values of the radiative forcing ratio, R, substantially different from one are observed within the convective region. This variability has been shown to relate partially to the variability of the surface albedo over Africa, and partially to spatial structure in the cloud field. In particular, the excess of regions with R , 1 (positive net CRF) corresponds to the inclusion of desert areas, with high surface albedo and suppressed active convection, within the convective region selected. The occurrence of monthly mean R values k1 (large negative net CRF) can be related to the inclusion of significant amounts of bright low cloud within the convective region, due to variability in the cloud field at shorter time scales. The resulting monthly mean forcing quantities (net CRF ø250 W m 22 ) include the effects of this low, nonconvective cloud and are therefore not purely representative of the radiative effects of the convective clouds that do occur in the region. The behavior observed for the Atlantic ITCZ region is more similar to that found in the eastern Pacific, where a lower degree of cancellation occurs than is found in the warm pool region. This is suggested to relate to differences in the cloud ensemble caused by differences in the dynamical forcings between these regions. These data allow some useful insights into the radiative impacts of convective cloud in the three regions chosen for analysis; however, this study also highlights the limitations of monthly mean radiation data for understanding the effects of cloud systems which exist on much shorter time scales. Thus, while the mean comparison presented here can be considered robust, it is difficult to come to firm conclusions regarding the smaller scale and seasonal variations, or to attribute the differences seen to differences in the convective ensemble between regions. To fully understand these effects requires study using radiation budget data with daily or better time resolution. The feedback process proposed by Hartmann et al. (2001) is expected to act at the time and space scales at which individual convective systems systems develop (i.e., at the mesoscale and on time scales of the order of a day of less). If such a feedback exists, we would therefore expect the cancellation of LWCRF and SWCRF to occur for the spatially and temporally averaged radiative effects of individual convective systems over their lifetime, and not just for the monthly mean ensemble. Observations to confirm or refute this are therefore required to further investigate the validity of such proposals. In any case, an understanding of the
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Soden, B. J., 2000: The diurnal cycle of convection, clouds, and water vapor in the tropical upper troposphere. Geophys. Res. Lett., 27, 2173–2176. Tian, B., and V. Ramanathan, 2002: Role of tropical clouds in surface and atmospheric energy budget. J. Climate, 15, 296–305. Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee III, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System experiment. Bull. Amer. Meteor. Soc., 77, 853–868. Wong, T., D. F. Young, M. Haeffelin, and S. Weckmann, 2000: Validation of the CERES/TRMM ERBE-like monthly mean clearsky longwave dataset and the effects of the 1998 ENSO event. J. Climate, 13, 4256–4267. Yang, G. Y., and J. Slingo, 2001: The diurnal cycle in the Tropics. Mon. Wea. Rev., 129, 784–801. Young, D. F., P. Minnis, D. R. Doelling, G. G. Gibson, and T. Wong, 1998: Temporal interpolation methods for the Clouds and the Earth’s Radiant Energy System (CERES) experiment. J. Appl. Meteor., 37, 572–590. Yu, R., Y. Yu, and M. Zhang, 2001: Comparing cloud radiative properties between the Eastern China and Indian monsoon region. Adv. Atmos. Sci., 18, 1090–1102.
