Band 3 (A. Illingworth, A. v. Lammeren, F. H. Berger, 2000)
Anthony Illingworth, Andre van Lammeren and Franz H. Berger, 2000:
Quantification of the Synergy Aspects of the Earth Radiation Mission
(ISBN 3-86005-262-4)
EXECUTIVE SUMMARY
The representation of clouds is one of the chief sources of uncertainty in numerical models used for forecasting weather and climate. The first step in gaining confidence in such models is to verify that they are correctly representing the current climate. At present we have limited data on the global characteristics of clouds and in particular virtually no information on the vertical structure of clouds and the quantity of ice within such clouds. Because of the value such data would have in the validation of climate models ESA is planning an Earth Radiation Mission (ERM) which would involve flying a nadir pointing radar and lidar in low earth orbit together with a multispectral imager and a broad band radiometer. This study is to consider how the output of these four instruments can be combined to retrieve the best representation of cloud characteristics such as profiles of cloud water (and ice) content, cloud particle size and radiative fluxes which can then be compared with the model representation of such clouds. The radar and lidar are active instruments and provide profiles of backscatter signals but the lidar is subject to attenuation, so this study addresses how such signals can be combined. The active instruments have a narrow swath, so the multispectral imager is designed to provide a broader swath and provide a context in which to place the profiles derived from the active instruments. The broad band radiometer provides a top of the atmosphere constraint for the vertical profiles of radiative fluxes computed from the vertical profiles of cloud characteristics. Chapter two (UR) considers various aspects of the synergy between radar and lidar and concludes:1.A dual wavelength (94 GHz and 215 Ghz) radar would have some advantages over the lidar because it is virtually unaffected by attenuation and the ratio of the reflectivities can provide a robust estimate of ice particle size for particles down to 25 microns for sufficiently high signal to noise ratio. An optimum package would be to combine this with a lidar.
2.Attenuation by ice clouds of a spaceborne lidar at a height of 4 km has been estimated from mid-latitude radar data to be over 10 dB on 53% of the time and constitutes a severe problem.
3.If the active instruments are embarked upon separate satellites then the inhomogeneity of the ice clouds leads to an error in the backscatter ratio which increases with the footprint separation of the instruments so that for both dual wavelength radar and radar/lidar at a separation of 5km the error is 2.5 dB for an along track integration of 1km and 2 dB for 10 km integration.
4.There is a very powerful synergy of the radar and lidar for identifying layers of super-cooled clouds from space. A lidar backscatter of 4x 10-5 sr-1m-1v which decreases by twenty-fold after 300 m penetration and is not accompanied by any increase in radar reflectivity efficiently identifies such layers; they are present on 30% of occasions when there is cloud colder than -10°C, and their mean horizontal extent is at least 20 km.
5.It is shown that the spaceborne active instruments will be able to provide invaluable statis-tics on global cloud overlap. Analysis of data over Chilbolton shows that the universally assumption of maximum random overlap whereby layers within vertically continuous cloud are maximally overlapped is incorrect; although adjacent layers are nearly maximally over-lapped, but when the vertical separation is 4km overlap is essentially random. A mathematical expression which could be used by modellers is derived to express this change from maxi-mum to random with increased separation of layers within vertically continuous clouds.
6.Powerful retrievals of ice cloud characteristics would available if an invariant parameter could be derived from their size spectra; an analogous invariant for liquid water clouds is total number concentration. No ice cloud invariants have been found.
7.The relationship between radar reflectivity (Z) and ice water content (IWC) is central to most retrievals. It is shown that the large published scatter is misleading; optimum relation-ships are proposed for 35 and 94 GHz which vary only slightly for realistic assumption of the variation of ice density with particle size. In addition temperature dependent IWC-Z relation-ships are proposed which should reduce random errors for individual IWC from observed Z to about 50%.
8.Theoretical calculations of the lidar ratio relating extinction to backscatter show that for ice spheres this varies between about 10 and 30 for spheres of uniform density and also for polycrystalline spheres.
9.The errors in the use of empirical relations between radar reflectivity (Z) and optical atten-uation (a) are presented and their use in constraining algorithms for correcting lidar attenua-tion are introduced.
In Chapter three the work of KNMI is presented and it is concluded that:
10.A new algorithm which retrieves cloud particle size and water content from simultaneous radar and lidar backscatter profiles is presented. This algorithm corrects for lidar attenuation (see point 2) and multiple scattering and is stable even when the cloud attenuation is signi-ficant (t up to 4-5).
11.In-situ aircraft validation of the radar-lidar retrieval above are extremely encouraging but further comparisons are needed over various cloud types and measurement situations. The retrievals would also benefit from further study into the nature of the relationships between ice cloud particle area and mass under different circumstances.
12.The results of the lidar/radar inversion have been successfully used to predict the down-welling thermal 10 micron surface fluxes. In general, though, this can only be carried out when both the lidar and radar ‘see’ the entire cloud.
13.Comparisons between passive AVHRR retrievals and in-situ validation are rather good for simple single-level cloud situation. However, this is generally not the case for multi-level clouds or semi-transparent clouds. This situation can be improved using the information that active instruments would provide.
14.A ground based cloud liquid water path (LWP) algorithm using combined cloud emissivity observations with the active instruments is presented. The results agree with inde-pendent microwave LWP measurements. The procedure may also be applicable to ERM type space-based observations.
15.1-D radiative transfer calculations demonstrate that the TOA and surface fluxes are most sensitive to cloud properties when the optical depths are less than five; in this regime the ERM measurements of ice cloud would be particularly valuable. Aerosols would be most important in the clear skies and the visible, but can still significantly influence fluxes if the optical depth of the cloud is < 5.
In chapter four the work TUD using radiative transfer schemes to determine cloud optical and microphysical properties from the ERM imager is presented and it is concluded:
16.Comparison of two different radiative transfer schemes (SBDART and Streamer) shows comparable results for water clouds, but needs more detailed intercomparisons, especially of individual parameterizations.
17.Need of additional information about ice cloud properties, which must be more realized within radiative transfer schemes.
18.Possible determination of cloud optical depth using spectral bands with wavelength less then 1 mm and of cloud effective droplet radius / ice crystal size using spectral bands with mid IR channels. [Leads to need to combine active and passive inferred cloud properties].
19.Using two spectral solar bands, the most convenient band combination is visible (approx. 0.6 mm) and mid IR at 1.6 mm despite of ambiguous solutions for thin clouds with small par-ticles. [Again - Synergy is recommended].
20.Accuracy very sensitive to surface characteristics, like the reflectance (need of improved bi-directional reflectance function - BDRF knowledge).
21.Concerning radiant fluxes at top of atmosphere and at surface, cloud optical depth must be accurately defined within the range of 1 to 20 of optical depth.
22.For a cloud type discrimination using terrestrial IR bands, the most convenient results can be inferred using three window bands: at 8.7, 11 and 12 mm.