Can we measure from satellites the cloud effects on the atmospheric radiation budget?

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1 Can we measure from satellites the cloud effects on the atmospheric radiation budget? Ehrhard Raschke University of Hamburg Institute of Meteorology Abstract Clouds modify all radiation budget components within the atmosphere and at their upper and lower boundary. Can regional and global changes of these effects be attributed to changes of the climate as they are visible in various cloud properties and can they be monitored from space? In this paper are discussed primarily two major data sets, of the International Satellite Cloud Climatology Project (ISCCP) and of the GEWEX Surface Radiation Budget (SRB) Project, which are describing global and regional fields of all radiation budget components. We in particular compare their results as obtained for the time period July 1983 to October 1995 and can show that both data sets still contain various systematic errors stemming from different ancillary data, which are needed in the procedures, but also from the computation itself. It must be concluded, that at the present state these data are well suited for first studies of global radiation fields and the relation to observed cloud pattern, but the still cannot be used for analyses of global or regional time series. Introduction The Problem Already very early studies of the radiation budget of our planet (see e.g. Peixoto & Oort, 1992, and Kiehl & Trenberth, 1999) have shown, that clouds modify decisively the energy transfer by electromagnetic radiation within the atmosphere. Their related physical and chemical properties depend on various dynamical and chemical processes, where in particular the availability of atmospheric water vapor and also the presence and properties of aerosols play a role. During the past 5 to 10 years there were numerous suggestions relating observations of cloud field changes to external forcings by cosmic rays or by aerosols and also to internal forcings by the atmospheric dynamics and possibly also the influence of changes in the heat exchanges over continental surfaces as caused by different land use. Modelers use now in their numerical tools for weather analyses and forecasts and also for climate investigations cloud characteristics of increasing complexity. The results of such simulations need a thorough comparison with observations. However observations of radiative transfer characteristics of clouds are extremely difficult due to the high variability of them in space and time. Therefore it is also intended to determine with highest possible accuracy and long-term stability the radiation budget parameters at both boundaries of the atmosphere and experimentally at different levels within it, and afterwards estimate the effect of clouds on them which often has been also called the cloud radiative forcing. How can we measure such quantities directly from space and how can we derive them from various ancillary data which are obtained from both satellite-borne, ground-based and also various in-situ measurements within the atmosphere? In principle satellites can measure only upward radiances upwelling from Earth to space. These contain the required information on the radiation budget at TOA, on various cloud properties and also on surface properties (e.g.: sea surface temperature). Various ancillary data are required to compute the desired quantities. In Table 1 are reproduced all those quantities and their sources which were used in the ISCCP to extract various cloud characteristics from satellite-borne radiances. This cloud information enters also (later) the algorithms used in ISCCP and in the GEWEX-SRB to compute radiation fields.

2 Table 1: Variables to be used in the cloud retrieval from the ISCCP radiance data (from Rossow & Zhang, 2004, private communication) Variables Cloud Cover, Optical Thickness, Top Temperature by Type Cloud Particle Size Cloud Vertical Structure Atmospheric Temperature and Tropospheric Humidity Atmospheric Humidity (Upper Troposphere, Stratosphere) Atmospheric Composition Stratospheric Total Ozone Stratospheric Ozone Profiles Stratospheric Aerosols Tropospheric Aerosols Snow cover Sea Ice cover Diurnal Cycle of Air Temperature over Land Surface Skin Temperature and Visible Reflectance Surface Spectral Albedo and Emissivity by Type Data set of variables ISCCP satellite radiances ISCCP-based Climatology Combined ISCCP-Rawinsonde Climatology TOVS, Oort Climatology for filling SAGE Climatology Actual record from Various Sources TOMS, TOVS for filling SAGE Climatology SAGE Baseline Current-day Climatology NOAA product NSIDC product Climatology based on surface weather reports and NCEP reanalysis From ISCCP retrievals GISS GCM reconstruction by surface type and season How can we estimate the effect of clouds on the radiative energy transfer at given levels? There are basically two ways: (1) One is using spatially and temporally high resolved information on the upward radiation fluxes at TOA and some ancillary information to determine statistically for a short timeperiod (e.g. 1 month) the radiation field at clear skies. The difference between the monthly (or shorter period) average of the all-sky and clear sky radiation flux density at TOA is then called the cloud effect or cloud radiative forcing. Early attempts of such analyses date back to the first radiation budget studies with satellite data (e.g. Raschke, 1972). In general it was found that clouds enhance considerably the albedo of our planet, but reduce somewhat less the emission of thermal radiation to space. (2) The other method computes directly the up- and downward fluxes of solar and terrestrial radiation within the climate system up to its top simultaneously for clear and cloudy sky at each time step (about 3h and less) from the data described in Table 1 and various others. Basic details on ISCCP are given in Zhang et al., 2004, and in Stackhouse et al., 2004. This method computes directly and at all desired levels the cloud effects on the radiation fields within the climate system. It is recently applied by other groups for similar purposes. In the following section a few results as obtained by the ISCCP for a five year period are described. A more detailed summary of results are given in Raschke et al., 2005, and Raschke and Ohmura (2005). The next section contains an error study inter-comparing the results of both projects. Radiation climatology from ISCCP data The project ISCCP has originally been initiated by the Radiation Commission of IAMAP in 1980. It became later a component of the GEWEX with the major goal to extract information from operational imaging data of meteorological satellites on cloud field characteristics, which are important for climate research and diagnostics,. Various details on this project are documented in Rossow and Duenas (2004) and Zhang et al. (2004) and in several earlier papers mentioned there. The core work for ISCCP is being done at the Goddard Institute for Space Studies in New York in cooperation with operational agencies for satellite data in the US, in Europe and in Japan.

3 The SRB has been defined with the specific task to determine the radiation budget components at the surface using primarily the required information on the atmosphere and on the relevant surface properties from satellite data. Various details are documented in Stackhouse et al. (2004) and in references mentioned there. This work is performed at the NASA Langley Research Center in Hampton, VA., and is closely related to other large projects to determine the planetary radiation budget from various specific satellite measurements (e.g. the project CERES = Clouds and Earth s Radiant Energy System, see Wielicki et al., 1996). In the following figures 1 to 4 we show a few results, radiation products and the effect of clouds on them, which were obtained from the ISCCP data sets for the 5-year period January 1991 to December 1995. More results, in particular seasonal values, are described in Raschke et al., 2005. Here we define the cloud effect of any quantity as the difference between its value at all (clear and cloudy) and at clear conditions, as ISCCP computes both values simultaneously at each time step. Thus positive values should be interpreted as an enlargement by clouds, and vice versa. We will show later, that these quantities described in the following figures contain serious uncertainties, which however may have a small impact on the general areal pattern as shown here. The radiation budget of the earth-atmosphere system (Fig. 1; left panel), as shown in the right panel of Fig. 1, is most effectively reduced over areas of low (warm) and intensively reflecting clouds layers. The cloud effect is relatively small over high convective cold cloud surfaces and over the icy polar regions. Of particular interest for the reader should be the maximum cooling over southern China, which primarily is due to a strong prominence of middle-high cloud fields. Fig. 1: Planetary Radiation Budget and Cloud Effect on it, as computed from ISCCP data sets of the period January 1991 to December 1995. The radiation budget at the surface (Fig. 2; left panel) is strongly reduced by clouds over tropical and subtropical regions and the mid-latitude storm tracks as well. The aforementioned dominance of midlevel clouds over China causes also a considerable reduction of the radiation budget at the surface. Fig. 2: Radiation Budget at the surface and cloud effects on it, as computed from ISCCP data sets of the period January 1991 to December 1995.

4 The ISCCP data set allows also for estimates of the total vertical radiative flux divergence and - as Zhang et al. (2004) also could show of rough vertical profiles of this quantities. We show here only figures of the solar and infrared (terrestrial) components of this interesting quantity. The solar component can reach values of up to 100 Wm -2 (Fig. 3; left panel) in the tropics, where however the contribution of clouds (i.e. the cloud effect: Fig. 3, right panel) is relatively small, since clouds reduce considerably the amount of solar radiation reaching the lower tropospheric moist layers. A small minimum occurs over the Highland of Tibet due to its thinner atmosphere, where however clouds can considerably enhance the absorption. Fig. 3: Solar Radiative Flux Divergence within the atmosphere and cloud effect on it, as computed from ISCCP data sets of the period January 1991 to December 1995. In the infrared terrestrial heat radiation the vertical flux divergence is everywhere over the globe negative, documenting that the earth looses energy back to space. This cooling is in particular high (Fig. 4; right panel blue areas) over regions of dominantly low cloud fields and also over the midlatitude storm tracks. It is considerably reduced over the tropical and optically very dense cloud fields at both sides of the equator. The atmospheric cooling over Tibet is again very small and is reduced dominantly by clouds. Fig. 4: Divergence of terrestrial radiation within the atmosphere and cloud effect on it, as computed from ISCCP data sets of the period January 1991 to December 1995. In the following Fig. 5 (next page) we compare the cloud effect on the solar and infrared radiative flux divergence (maps on the right hand side) with maps of the cover with high, middle and low clouds during the same period. Cloud influence differently the vertical solar and terrestrial radiative flux divergence within the atmosphere. High convective systems with low surface temperatures reduce the cooling to space while low clouds enhance it. On the other side the low clouds enhance also the absorption of solar radiation.

5 high Cloud effect on vertical divergence solar middle terrestrial low Raschke et al, 2005; Int. Journ. Clim. Fig. 5: Comparison of ISCCP cloud fields (annual averages 1991 to 1995) with cloud effects on the vertical divergence of the same period. Parameter ANN DJF MAM JJA SON TOA: terrestrial cloud effect + 25 + 25 + 26 + 25 + 25 TOA: solar cloud effect - 50-53 - 46-50 - 50 TOA: total cloud effect - 24-28 - 20-22 - 26 SFC : terrestrial cloud effect + 30 + 31 + 30 + 28 + 30 SFC : solar cloud effect - 52-57 - 49-50 - 53 SFC : total cloud effect - 23-26 - 20-21 - 24 Cloud effect on terrestrial divergence - 4.3-5.4-3.5-3.2-5.3 Cloud effect on solar divergence + 3.0 + 3.3 + 2.7 + 2.7 + 3.2 Cloud effect on total divergence - 1.3-2.1-0.8-0.5-2.1 Table 2: Global annual and seasonal averages for the period 1991 to 1995 of cloud effects on the radiation budget and on the divergence in the atmosphere. Negative values mean at TOA losses to space, or at the surface (SFC) losses into the atmosphere. Global annual and seasonal means of the cloud effect on various radiation quantities are summarized in the Table 2. They were computed from the ISCCP data and agree in sign but not in magnitude also with those obtained at the TOA only from data of the Earth Radiation Budget Experiment (ERBE) which are +32 Wm -2, -49 Wm -2, -17 Wm -2, +15% for the outgoing terrestrial radiation, for the absorbed solar radiation, for the planetary radiation balance and for the planetary albedo, respectively. These differences between the ISCCP and ERBE results are due to different spatial and temporal sampling and possibly due to different uncertainties in the identification of clouds. The seasonal global averages of the cloud effect remain quite stable during all seasons, while related maps show large changes over several regions (see Raschke and Ohmura, 2005).

6 A short assessment Zhang et al., 2004, estimated the uncertainty ranges for various radiation fluxes within the atmosphere to be of the order of 15 to 25 Wm -2, as summarized in Table 3. Such values are considered useless for climate change observations (see Ohring et al., 2003), where values of about 1-5 Wm -2 are recommended with a stability of about 1/5 to 1/10 over periods of 10 years. Therefore the already existing data sets must be assessed thoroughly with respect to internal error sources which can be avoided. solar TOA 11 Wm -2 (7 Wm -2 ) terrestrial - 1 Wm -2 (4 Wm -2 ) SFC 10-15 Wm -2 (10 Wm -2 ) 3 Wm -2 10-15 Wm -2 (15 Wm -2 ) 12 Wm -2 (20 Wm -2 ) DIV 20 25 Wm -2 10 20 Wm -2 Table 3: Estimates of biases (and standard deviation) of regional uncertainty ranges for upward radiation fluxes at TOA and down- and upward radiation fluxes at the surface, made by Zhang and Rossow (1995) with regional monthly averages. The estimates for the divergence within the atmosphere are based on these numbers. Therefore we performed a comparison of radiation fields computed within the two projects ISCCP and SRB, where we considered only monthly averages over very broad latitudinal zones of both hemispheres: 0-30, 30-60, 60-75 and 75-90. These zones are representative for almost similar climate conditions in the tropics and subtropics, in the middle latitudes and in sub-polar and polar regions. We can show here only a few samples. Fig. 6: Differences between zonal monthly (July 1983 to October 1995) averages of the downward solar radiation at TOA as computed for the ISCCP and GEWEX-SRB radiation climatologies.

7 The differences between values of the incoming solar radiation at TOA, Fig. 6, show, that ISCCP values are in most cases higher than those of the SRB. This difference is primarily caused by a much larger threshold of about 11 for the angle above horizon during sunrise and sunset in the SRB than in the ISCCP (0.005 ). In particular over regions with generally low sun, these differences are becoming large. The SRB does also not consider the leap-year, which causes a four-year periodicity in these differences. In fact also the many climate models participating in the Atmospheric Model Intercomparison Project (AMIP) and in related actions for the IPCC deviate considerably (up to 2 percent) in the values for the regional climate forcing by the Sun. Fig. 7: Comparison between zonal monthly (July 1983 to October 1995) values of the planetary radiation budget and the cloud effect on it, as computed by the projects ISCCP (ordinate) and GEWEX-SRB (abscissa). The planetary radiation budget values (Fig. 7) agree quite well within a range of ±10 Wm -2, since apparently some errors in their components compensate. The disagreement increases towards highest negative values, which occur over both sub-polar regions. The cloud effect values are uncertain within a similar order of magnitude, although the correlation within each latitude belt appears high. The downward solar radiation at ground, as shown in Fig. 8, disagree within a range of ca. ±10 Wm -2 over the tropical and mid-latitude belts. However at higher latitudes the SRB, due to the constraints at lower heights of the sun, computes much smaller values for the insolation. The oscillations in these differences are partly due to the seasonal dependence of the various input data, and also partly due to the fact, that SRB does not consider the leap year. These disagreements may largely be reduced, when both projects agree to use the same insolation. Then a comparative study of the transmittance of both model atmospheres or solar radiation might be useful to uncover other error sources.

8 Fig. 8: Differences between monthly (July 1983 to October 1996) zonal averages of downward solar radiation at ground, computed within the projects SRB and ISCCP. Fig. 9: Differences between monthly (1991-1995) zonal averages of the cloud effect o downward solar radiation, as computed by the projects ISCCP (ordinate) and GEWEX-SRB (abscissa). Clouds generally increase the downward atmospheric radiation. We see in Fig. 9, that also here both models show systematic differences of 8 to up to 12 Wm -2. These might in particular been caused by different assumptions on the cloud bottom altitude and temperature, which taken in both projects from climatological estimates. An improvement should be expected when direct measurements are available from lidar and cloud radar onboard of satellites. The ratio of the emission at the surface, as computed by both algorithms, back into the atmosphere shows /Fig. 10) clearly that the ISCCP data over both poles is much warmer and over the southern mid-latitudes is colder, respectively, than in the SRB data. ISCCP also shows a small degrees of the temperature in the tropics and subtropics, which seems to be caused by its retrieval algorithm.

9 Fig. 10: Ratio between monthly (July 1983 to October 1995) zonal averages of the emission at surface, as computed by the projects ISCCP and GEWEX-SRB. Fig. 11: Comparison between monthly (July 1983 to October 1995) zonal averages of the vertical radiative flux divergence within the atmosphere, as computed by the projects ISCCP (ordinate) and GEWEX-SRB (abscissa). The total radiative flux divergence within the atmosphere (Fig. 11) is negative due to the fact, that the climate system receives its energy solely from the Sun. Both data sets agree between about ±20 Wm -2, since apparently some errors are cancelled out (= good results for the wrong reason). The cloud effect on the divergence is higher in the ISCCP, except for the zone between 30 and 60 S. Conclusions In this report we could demonstrate that operational satellite measurements of upwelling short- and longwave radiation at TOA can be used to estimate the radiative energy fluxes at all levels of the atmosphere. However this requires a large set of ancillary data on the states of the atmosphere and of the ground. Additional rules must be used to consider also specific radiative transfer characteristics,

10 such as the angular dependence of the reflectance and emittance at ground, or the cloud properties. All input data require careful quality control to avoid misinterpretations of the results as they might be caused by erroneous spurious trends in the input. This quality control must already begin with the satellite radiances. Direct measurements of the cloud effect are not possible, however crude estimates for the radiative fluxes at TOA are possible with statistical means and require an accurate cloud identification. There are still various systematic error sources within the at present larges data sets for a radiation climatology. The SRB data set seems to underestimate the incoming solar radiation by more than 2.5 Wm -2, and causes even systematic errors of much higher magnitude over high-latitude regions. Its atmosphere and clouds seem to be optically thicker for solar radiation, while the ISCCP data seem to underestimate the absorption in the atmosphere. On the other side the surface temperatures in the ISCCP for polar regions are too high, while they decrease with time over the tropical and subtropical zones. Thus a complete revision of this ancillary data set is required. There are (not shown here) various other uncertainties in this data causing unexpected month-to-month variations and other irregularities. Therefore it is recommended here and will be discussed in forth-coming workshops arranged within the GEWEX to revise completely both data sets and combine them with the new and earlier data sets of measured radiation budget components at TOA. Also a close cooperation with climate modelers should reduce the uncertainties in computed quantities of the radiation budget in models. This more critical assessment should not overlook the enormous progress, which has been made in this field. Now we are able to study global and regional fields of all components of he radiation budget at TOA, at ground and within the atmosphere and to explain their spatial pattern and variation with time. These should also be reproduced in models for the present climate. Considerable improvements are only possible improving the retrieval of cloud characteristics with the more advanced techniques than the ISCCP and SRB could use. It must be concluded, that at the present state these data are well suited for first studies of global radiation fields and the relation to observed cloud pattern, but the still cannot be used for analyses of global or regional time series. This study was possible due the often overseen facts, that the EUMETSAT and related other space organizations and also various individuals provided continued support to the ISCCP with data, ideas and active research. References Kiehl, J. T., and Trenberth, K. E., 1997: Earth's annual global mean energy budget. Bull. Amer. Meteor. Soc., 78: 197-199. Ohring, G., B. Wielicki, R. Spencer, B, Emery, R, Datla, ed., 2004: Satellite Instrument Calibration for Measuring Global Climate Change. NISTIR 7047, available from the US Department of Commerce, Technology Administration Peixoto J. and A. Oort, 1992: Physical Climatology, American Institute of Physics, 520 pp Raschke, E., A. Ohmura, W. Rossow, Y. Zhang, C. Stubenrauch, M. Kottek, M. Wild, 2005: Cloud effects on the radiation budget based on ISCCP data (1991-1995), Int. Jour. Climatol., 25, 1103-1125. Raschke E., 1972: Die Strahlungsbilanz des Systems Erde-Atmosphäre neuere Ergebnisse von Satellitenmessungen. Zeitschr. f. Geophys., 38, 967-1000. Raschke, E., A. Ohmura, 2005: The Radiation Budget of the Climate System. in (ed.) M. Hantel, Landolt- Börnstein V/6, Meteorology, Springer Rossow, W. B., E. N. Duenas, 2004: The International Satellite Cloud Climatology Project (ISCCP) Website. Bull. Amer. Meteor. Soc., 85, 167-172. Stackhouse Jr., P.W., S.K. Gupta, S.J. Cox, J.C. Mikovitz, T. Zhang, M. Chiacchio, 2004: 12-year Surface Radiation Budget Data Set. GEWEX News Wielicki, B.A., B.R. Barkstrom, E.F. Harrison, R.B. Lee, G.L. Smith and J.E. Cooper, 1996: Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System experiment. Bulletin of the American Meteorological Society, 77: 853-868. Zhang, Y., W.B. Rossow, A.A. Lacis, V. Olivas, M.I. Mishchenko, 2004: Calculation of radiative fluxes from the surface to top of the atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data. J. Geophys. Res., 109D, D19105, 27 pp.