SATELLITE OBSERVATIONS OF CLOUD RADIATIVE FORCING FOR THE AFRICAN TROPICAL CONVECTIVE REGION

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1 SATELLITE OBSERVATIONS OF CLOUD RADIATIVE FORCING FOR THE AFRICAN TROPICAL CONVECTIVE REGION J. M. Futyan, J. E. Russell and J. E. Harries Space and Atmospheric Physics Group, Blackett Laboratory, Imperial College, London, SW7 2BZ, UK ABSTRACT Analysis of ERBE-like fluxes from the Clouds and the Earth s Radiant Energy System (CERES) instrument on the TERRA satellite reveals a high degree of cancellation between the monthly mean longwave (LW) and shortwave (SW) cloud radiative forcing (CRF) in the African tropical convective region. The behaviour found is similar to that seen previously in the Pacific warm pool region, but only in the large scale area average. Significant seasonal and spatial variations in net CRF occur within the African convective region. Further analysis indicates the importance of both clear sky (surface) and cloud effects and highlights the limitations of monthly mean gridded data for this kind of study, particularly with regard to unresolved higher frequency variations in the cloud field, indicating the need for studies using higher time resolution data. The Geostationary Earth Radiation Budget (GERB) Experiment on board Meteosat-8 provides accurate broadband fluxes at timescales comparable to those at which convective systems develop. We show how these data, in conjunction with cloud type identification from the Spinning Enhanced Visible and Infrared Imager (SEVIRI, also on Meteosat-8), can be used to achieve better separation of the effects of convective cloud systems from other factors influencing the radiation budget in the region, and so can be used to produce a more accurate estimate of the convective cloud forcing at monthly timescales. 1 INTRODUCTION The concept of cloud radiative forcing provides a means of quantifying the effect of clouds on the Earth s radiation budget. The longwave component (LWCRF, Equation 1a) measures the reduction in the emission of thermal radiation to space due to the presence of cloud, and the shortwave part (SWCRF, Equation 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). LW CRF = OLR clear OLR cloudy (1a) SW CRF = F ref clear F ref cloudy (1b) Here 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.

2 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 (Ramanthan et al., 1989; Harrison et al., 1990). Monthly average longwave forcings reach their maximum values of W m 2 in the convectively disturbed regions of the tropics; however this heating effect is nearly cancelled by a correspondingly large shortwave forcing. These observations led to debate as to the cause of this behaviour, Kiehl (1994) suggests that the near cancellation observed is a coincidence of the height of the tropical tropopause and the typical albedos of optically thick high clouds. More recently, Hartmann et al. (2001) have suggested that this behaviour may be indicative of feedbacks in the climate system influencing the ensemble of cloud types associated with convection. Near cancellation between LW- 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 which exist for other regions do not necessarily find a similar degree of cancellation. In the present work, the radiative effects of convective clouds in the Atlantic and African convective regions are investigated and the observed behaviour compared with that seen in the Pacific warm pool region using ERBE-like (ES-4, edition 2) data from CERES (Clouds and the Earth s Radiant Energy System) on TERRA (Wielicki et al., 1996). Preliminary comparisons with data from GERB are presented, and a method to produce more accurate estimates of the convective cloud forcing using combined GERB and SEVIRI data is proposed. 2 COMPARISON WITH THE PACIFIC WARM POOL REGION 2.1 METHOD Previous studies have used two measures to quantify the degree of cancellation between the LW- and SWCRF: net CRF=LWCRF+SWCRF, and the cloud forcing ratio, R = SW CRF/LW CRF. Clearly perfect cancellation is implied by net CRF=0, or R = 1.0. As in Futyan et al. (2004), the region of study is defined to consist of all grid-boxes with LWCRF greater than 30 Wm 2, rather than as a fixed geographic region. This avoid problems associated with the migration of the Inter- Tropical Convergence Zone (ITCZ) and inclusion of areas dominated by non convective cloud formations such as the stratocumulus deck off the west coast of southern Africa. The Pacific convective region is defined to contain all grid-boxes satisfying the above LWCRF condition, within 20 S-20 N, E. For the Atlantic, the LWCRF limit is applied to grid-boxes within 20 S-20 N, 40 W-20 E with surface flag ocean, and for the African region the area of interest is 30 S-20 N, 30 W-50 E, for surface types land and desert. 2.2 RESULTS Figure 1 shows the annual mean frequency distribution of the 2.5 degree grid-box scale values of the cloud forcing ratio R for these three regions. The narrow sharply peaked distribution for the Pacific region indicates a high degree on cancellation (values of R close to 1.0) throughout the convective region in all months, consistent with the results of previous studies. Over African land regions, the modal value is the same as in the Pacific region (R = 1.1), but the broader distribution implies significatively more variability in this region. Over the Atlantic, the distribution is again broader, and is shifted towards higher R values, peaking at R 1.3 (SWCRF 30% larger than LWCRF). Futyan et al. (2004) showed that the increased spread of R found in these regions is in part due to seasonal chances in the balance between the LW and SW cloud forcings (Figure 2). In particular, in the Atlantic region, the SW forcing increases noticeably in the summer months, while the LWCRF remains relatively constant, resulting in a negative net CRF greater than 20 W m 2 between May and September. This is similar to the behaviour found by Hartmann et al. (2001) for the east Pacific ITCZ region in July and August using ERBE data.

3 Figure 1: Fractional frequency distributions of grid-box values of R for the Pacific, African, and Atlantic convective regions from CERES data. Averaged for all months of 2001 & These seasonal variations in the degree of cancellation over African land and the Atlantic only account for part for the greater widths of the annual mean distributions in these regions. Spatial variability in the balance between the LW and SWCRF in individual months is also found to be larger in these regions than in the Pacific warm pool (Figure 3 shows an example of this for July 2001). 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. Figure 2: Seasonal variations in the area averaged value of R (calculated as SW CRF /LW CRF ) for the Pacific, Atlantic and African convective regions for Mar-Dec 2000 and Jan-Dec 2001 & 2002 for CERES data. Reproduced from Futyan et al. (2004) Because the cloud forcing is defined as the difference in flux between clear and cloudy conditions its magnitude is dependant on factors influencing the energy balance under clear sky conditions, i.e. properties of the surface and atmosphere in the corresponding clear scene. The same cloud will produce a smaller SWCRF (and hence lower R) over a bright desert surface than over a darker surface such as ocean. Over Africa, there is a sharp gradient in surface albedo moving from the bright Sahara desert, south across the Sahel into darker vegetated regions. If the convective region extends over the southern edge of the Sahara desert, the SW forcing is suppressed due to the reduced albedo contrast, and positive values of net CRF (R < 1) are found as can be seen in Figure 3. However, the band of large negative net CRF seen along the southern coast of West Africa in Figure 3 (and throughout the summer) cannot be explained by surface albedo effects. These grid-boxes have highly negative net CRF, with magnitudes larger than 50 W m 2 and clearly do not demonstrate the near cancellation found in other areas.

4 Figure 3: Contour-plots of net CRF for Jul 2001 for the Pacific and African/ Atlantic convective regions for CERES data. The 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 is filled with a grid pattern The plot of the stratocumulus fraction shown in Figure 4 helps to explain the high values of net CRF found in this region. In the summer months, low cloud, for which the SWCRF dominates, extends up over the coast of Africa. Occasional high cloud systems propagate over this region during the month, resulting in its inclusion in the convective region defined using a LWCRF threshold (Futyan et al., 2004), but for the remainder of the month, the radiative effects of these low clouds dominate and hence skew the mean net CRF towards negative values. To separate the radiative effects of these different regimes requires the use of radiation budget data at timescales shorter than the monthly average. Figure 4: Monthly mean fractional coverage of stratocumulus cloud for the African/ Atlantic region in Jul The boxes show the regions within which the LWCRF limit is applied in the previous analysis. 3 PRELIMINARY RESULTS FROM GERB AND SEVIRI GERB produces accurate broadband measurements of the radiation budget components at 15 minute time intervals, and hence provides an ideal tool for studies requiring this data at high temporal resolution. In particular, by exploiting the synergy with SEVIRI to identify and classify cloud in the GERB image, studies of cloud forcing by cloud type become possible. Firstly the analysis described above is repeated for monthly mean fluxes derived from GERB for April 2004, and the results compared with those from CERES data in previous Aprils. Secondly, a method using SEVIRI cloud type identification to produce a more accurate estimation of the monthly mean convective cloud forcing in the region is proposed.

5 3.1 MONTHLY MEAN CLOUD FORCING FROM GERB AND SEVIRI METHOD Before the cloud forcing can be calculated, estimates of the monthly mean clear and all sky flux are required. For GERB, the excellent temporal sampling means that the all sky mean flux can be calculated as a simple average of the observed data. However, for the clear sky flux, forming an accurately sampled mean is not a straightforward task; some of the complexities and possible solutions for GERB data are discussed in Russell et al. (2004) (this proceedings). The approach followed here is to use a SEVIRI based cloud identification (combined RMIB and MPEF flags (Russell et al., 2004)), and hence to produce a monthly time-step clear sky mean flux at each footprint in the GERB field of view. Missing time-steps are then filled using a diurnal model. In the longwave this diurnal filling is achieved via linear interpolation over ocean, and a half-sine model is fitted over land. Unlike in the ERBE-like processing used for the CERES data discussed above (Young et al., 1998), this is not forced to peak at local noon. This additional flexibility is possible due to the larger number of observations of a particular region during the course of a day available from GERB. In the shortwave, the flux data are converted to albedo before averaging over the month. Missing daylight timesteps are filled by fitting directional models (DRMs) of the variation of albedo with solar zenith angle derived from CERES on TRMM (Loeb et al., 2003). These are consistent with the angular models (ADMs) used for radiance to flux conversion for GERB data. The monthly average all sky and clear sky flux estimates are then used to calculate the cloud forcings and ratio R as described in Section RESULTS Figure 5 shows the LW, SW and net CRF for April 2004 from GERB, and for April 2002 for ERBE-like data from CERES on TERRA. There is a significant amount of missing data in the Atlantic convective region in the SWCRF plot. This relates to there being too few clear sky observations in this region during daylight over the course of the month to obtain a GERB footprint scale estimate of the clear sky flux. It should be noted however that spatial and/or temporal regriding or resolution enhanced GERB products can be used to enhance data quantities (Russell et al., 2004). In general similar patterns and magnitudes are found in the results from the two instruments. The SWCRF is comparable for the convective region, although larger values are found in the stratocumulus region for GERB than for CERES. This may be due to interannual variability in the cloud cover in this region. However, differences could also be due to the much better sampling of the strong diurnal cycle of cloud cover in this area from GERB than from the sun-synchronous orbit of TERRA. GERB also measures lower LWCRF, and hence more negative net CRF (or higher R) for the convective region, especially over land. This is unlikely to be due to interannual variability given the high level of year to year repeatability seen in Figure. 2. Figure 6 shows the average values of the LW and SW over the convective regions defined previously, and their ratio, for the years 2000 to Averages are calculated for points where a valid estimate of both the LW and SW forcing is available. The estimate for the Atlantic region in 2004 may be biased by the amount of missing data. As mentioned, the LWCRF for the African land region found in 2004 from GERB is lower than that found by CERES in previous years, while the SWCRF is comparable, resulting in a more negative net forcing and higher R. For the Atlantic the behaviour found is similar in all years. Once fully validated, GERB data will provide the most accurately sampled estimate of the monthly mean cloud forcings in this region. While it is interesting to note qualitatively the generally high level of agreement between the two instruments, as validation of GERB data is ongoing it would be inappropriate to speculate as to the causes of the quantitative differences found here.

6 Figure 5: LW, SW and net CRF for April 2004 (top) from GERB data, and for April 2002 (below) from CERES data. The convective region selected by a LWCRF threshold of 30W m 2 is highlighted by cross-hatching. Missing data is filled with a grid pattern 3.2 USING SEVIRI CLOUD TYPE DATA FOR ENHANCED CLOUD FORCING ESTIMATES The strong synergy between GERB and SEVIRI, and their high temporal resolution, allows a more complete separation of the radiative effects of different cloud types than is possible for the approach used above. Multi-channel imager data from SEVIRI can be used to identify the cloud type (classified according to height, optical depth etc) at each SEVIRI pixel for each repeat cycle. This data can then be used to classify a GERB footprint as either convective, non-convective or clear. i As before, the cloud forcing is the difference between the observed flux in a footprint Fobs, and the clear sky esi timate for that footprint, Fclear. The difference is that rather than first averaging the flux estimates over time, and subsequently taking the difference, the subtraction is performed on the instantaneous data. The convective cloud forcing (convcrf ) can then be defined to be equal to the observed forcing if the footprint is flagged as convective, and zero otherwise, and similarly for the non-convective cloud forcing (Equation 2). These quantities can then be averaged over time to give the mean value at each footprint. Their sum will give an estimate of the overall cloud forcing, while separately they provide an estimate of the relative importance of high and low clouds to the radiation budget of the region. convcrf convcrf = = i i Fobs Fclear 0 if flag is convective cloud otherwise (2) The cloud analysis image product is a cloud type classification produced operationally by the EUMETSAT Meteorological Products Extraction Facility (MPEF) at the 3x3 SEVIRI pixel scale, every three hours. Here, we use this product is used to provide a simple flag for the presence of convective or high clouds in a GERB footprint, and hence demonstrate the method proposed above for the 11:45 time-step. Figure 7 shows the monthly time-step mean SW cloud forcing for 11:45 UTC for April 2004, together with estimates of the convective and non convective cloud forcings. The monthly time-step mean albedo was combined with the

7 Atlantic region African land region CERES LW CERES SW GERB LW GERB SW 'R' for the African and Atlantic Convective regions CERES- land 1 CERES - ocean 0.8 GERB - land 0.6 GERB - ocean Figure 6: Bar charts of the area average LW and SWCRF, and ratio R for the African and Atlantic convective regions for the month of April from 2000 to Data from 2000 to 2003 are from CERES on TERRA, and for 2004 are from GERB instantaneous incoming solar flux to estimate the clear sky SW reflected flux on each day. The region selected as convective using a 30W m 2 threshold on the monthly mean LWCRF is shown in cross-hatching for comparison. As expected, the convective (or high) cloud forcing dominates in the region previously defined as convective using the LWCRF limit, but also makes a non-negligible contribution to the SW forcing outside this region. As all types of high cloud are included in this convective flag, non zero convcrf is also found in regions not necessarily associated with convective activity e.g. in mid-latitudes (30 40o ). Low or non-convective cloud forcing dominates in the expected regions, for example contributing all of the observed cloud forcing over the stratocumulus region. It is also apparent however, that, according to this definition, low clouds do contribute to the SWCRF within the region previously defined to be convective. This approach makes it possible to separate out the contribution of these clouds to the mean cloud forcing. Figure 7: (left) SWCRF for 11:45 UTC for April 2004 from GERB data, (centre) convective or high cloud forcing, (right) low or non convective cloud forcing as defined above.

8 4 SUMMARY Analysis of ERBE-like data from CERES on TERRA reveals interesting similarities and differences between the radiative effects of convective clouds in the tropical western Pacific, African and Atlantic regions. Despite the obvious differences in surface type (albedo), diurnal cycle and sources of convective instability, the area-averaged degree of cancellation between the LW and SW cloud forcings in the Pacific warm pool and African convective regions is similar. Over the Atlantic region, however, the SW forcing tends to dominate, producing net cloud forcings of greater than 20W m 2 in the summer months. However, significantly more seasonal and spatial variability in the degree of cancellation is observed in the African region than in the western tropical Pacific. This variability has been shown to relate partially to the variability of the surface albedo over Africa, with low values of R occurring where cloud extends over the Sahara, and partially to spatial structure in the cloud field. Some of the observed structure in the cloud forcing is found to relate to the inclusion of the radiative effects of low clouds which are present in some regions during the course of the month. To fully separate the effects of different cloud types on the monthly mean radiation budget, requires screening by cloud type at higher time-resolutions, for example by combination of GERB fluxes with a cloud type retrieval from SEVIRI. The feasibility and benefits of this method are demonstrated using data for a single time-step during April Non-negligible contributions to the convective cloud forcing are found outside of the region selected using monthly mean data, and significant contributions to the SW forcing within this region are attributed to low clouds. These results indicate the usefulness of this approach for estimation of the mean cloud forcing by cloud type. Use of this approach will also allow study of the cloud forcing over this region at higher temporal resolution, more comparable to those on which convective systems develop, providing insight into how the monthly mean behaviour arises. Preliminary results for the monthly mean cloud forcings measured by GERB over the African and Atlantic regions for April 2004 show generally good agreement in terms of both spatial patterns and magnitudes with the results for previous years from CERES data. Once fully validated GERB data is available, such comparisons will provide a useful tool to understand the strengths and limitations of the two datasets. References Futyan, J. M., J. E. Russell, and J. E. Harries, 2004: Cloud Radiative Forcing in Pacific, African and Atlantic Tropical Convective Regions. J. Climate, In Press. Harrison, E. F., P. Minnis, B. R. Barkstrom, V. Ramanathan, R. D. Cess, and G. G. Gibson, 1990: Seasonal Variation of Cloud Radiative Forcing Derived From the Earth Radiation Budget Experiment. J. Geophys. Res., 95, Hartmann, D. L., L. A. Moy, and Q. Fu, 2001: Tropical Convection and the Energy Balance at the Top of the Atmosphere. J. Climate, 14, Kiehl, J. T., 1994: On the Observed Near Cancellation between Longwave and Shortwave Cloud Forcing in Tropical Regions. J. Climate, 7, Loeb, N. G., N. Manalo-Smith, S. Kato, W. F. Miller, S. K. Gupta, P. Minnis, and B. A. Wielicki, 2003: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth s Radiant Energy System instrument on the Tropical Rainfall Measuring Mission Satellite. Part I: Methodology. J. Appl. Meteor, 42, Ramanthan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud- Radiative Forcing and Climate: Results from the Earth Radiation Budget Experiment. Science, 243, Russell, J. E., J. M. Futyan, et al.: 2004, Stratagies for determining clear sky fluxes from GERB data. Proceedings: The 2004 EUMETSAT Meteorological Satellite Data Users Conference, EUMETSAT. Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. L. III, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth s Radiant Energy System (CERES): An Earth Observing System Experiment. Bull. Am. Meteorol. Soc., 77, 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. Meteorol., 37,