DETECTION OF ICE CLOUDS BY RADAR AND LIDAR ANDCOMPARISON WITH OPERATIONAL NWP MODELS.

Anthony J. Illingworth and Robin J HoganJCMM, Department of Meteorology, University of Reading, UK

1. INTRODUCTION

Satel l i te missions are planned in which a l idar and aradar will be flown together for the first time. In thisnote we analyse observations with a ground based radarand lidar at Chilbolton in the UK to answer thefollowing questions.

a) What is the sensitivity required by a spaceborneinstrument so that all radiatively significant ice cloudswill be detected? Is the lidar more sensitive to tenuousclouds than the radar?

b) Cloud base and cloud top detection.Do spaceborne radar and lidar provide reliable detectionof the top and base of ice clouds and is this a functionof the instrument sensitivity? How often is radar cloudbase lower because of fall streaks?

c) Embarking the radar and lidar on different platforms.Can the radar and lidar be embarked upon differentsatellite platforms without prejudicing the mainobjectives? Is it still possible to use the backscatterratio to derive ice particle size? What is the spatial scaleof cirrus cloud inhomogeneity?

Comparisons of observations with the values of cloudparameters held in the ECMWF operational model havebeen made to address the following questions:

d) Cloud overlap.All models assume maximum-random overlap in thevertical. What is the true sub-grid scale overlap?

e) Comparison of fractional cloud cover.How do the values of fiactional cloud cover inf-erredfrom the ground based observations compare with thosein the model?

Finally, tor a future spaceborne mission:

f) Spaceborne use of 215 and94GHz radars.Can the ratio of reflectivities measured at these twowavelengths provide an estimate of ice particle size?

Corresponding author address: AnthonyJCMM, Dept of Meteorology, UnivReading RG6 688, UK.e-mail : A.J. I l l insworth @readins. ac.uk.

I l l ingworth,of Reading,

The data used in this study were gathered over theperiod October 1998 to January 1999 using a verticallypointing radar and lidar. The 94GHz radar used had asensitivity of -52.5dB.2 at a range of lkm and-32.5dB2 at a range of 1Okm with a range resolution of120m for a 2 minute integration t ime. The cal ibrat ionto ldB is achieved by comparing the simultaneous94GHz and 3GHz returns for Rayleigh scattering targetsuch as drizzle'. the 3GLIZ radar was calibrated to 0.5dBusing the redundancy of polarisation parameters inheavy rain. The lidar had a sensitivity of 2 x l0-7 m-rsr-t The ground based instruments are more sensitivethan the spaceborne instruments proposed by ESA(-35dBZ for the radar and 8 l0-7 m-r sr-r for the lidar)so it is possible to check the effect of changing thespaceborne instrument sensitivity. Because the radarresponds to the sixth power of the particle size and thelidar approximately to the second power, there has beenmuch concern and debate over the following aspects:i) Will the radar miss many thin but radiativelysignificant clouds which are only sensed by the lidar?ii) Will the presence of larger particles falling belowcloud base mean that the radar persistently detects acloud base lower then that inferred from the lidar?

2. COINCIDENCE OF ECHOES FROM RADAR ANDLIDAR.

A comparison of the radar and lidar returns (see figurel) reveals that it is in fact extremely rare for a clouddetected by the lidar not to be seen by the radar. Theconverse is of course very common when the lidarsignal is completely ext inguished by optical ly denseclouds. Clouds were identified by returns that weremore than three pixels thick to reject anomalous echoes.For the three month data set with the full 'ground-based' sensit ivi t ies, only 3.9Vo of the clouds detectedby the radar were not seen by the radar. For the'spaceborne' sensitivity this value drops to 2.l%o; thisreduction arises because, when degrading theinstruments to spaceborne sensitivity, the lidar losesmore signal than the radar. However, the averageoptical depth of the clouds seen only by the lidar is only0.05 (assuming an extinction to backscatter ratio ofl4). If we consider that only clouds with an opticaldepth above 0.05 are likely to be radiatively significantthen the fraction of clouds seen by the lidar but not thelidar is reduced to l.5Vo tor the ground-basedsensitivities, and to only l7o for the spacebornesensit ivi t ies. I t would be interesting to extend suchstudies to the tropics where high altitude cirruscomposed of very small crystals may be moreextensive.

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Figure 4: An examole of cloud radar data used to derive the cloud cover mask. from I I December 1998.

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Detection of cloud by radar and lidar. The cloud detected only by the lidar is shown in red.

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3. CLOUD BASE AND CLOUD TOP DETECTION OFICE CLOUDS.

Forty five hours of data from 6 different days wereidentified when the lidar had an unobstructed view ofthe base of an ice cloud. Figure 2 shows the radar andlidar returns and the derived values of cloud base forthe 19 December and indicates that cloud bases fromthe two instruments agree to within 100m. The lowerpanel compares cloud base differences using the fullground-based sensitivity with the spacebornesensitivity and shows that derived cloud base dependsupon sensit ivi ty. The lower sensit ivi ty of thespaceborne lidar is responsible for the difference of thetwo traces.

For the full 'ground based' instrument sensitivity it isfound that 80Vo of the time the cloud base agrees towithin 200m and 967o of the time to within 400m. Forspaceborne sensitivities these vaiues become l37o and95Vo. We conclude that there is a diff'erence in thecloud base measured by radar and lidar but it is usuallyless than 200m and is not really of great concern, whenwe consider that for typical lapse rates in thetroposphere, a change in cloud base of 500mcorresponds to a change in long-wave emission of onlyabout l0 W m-2.

4.EMBARKING A RADAR AND LIDAR ONDIFFERENT PLATFORMS

A powerful synergy of the radar and lidar instrumentscould be to use the ratio of the basckscattered signals toprovide an estimate of the ice particle size. If this is tobe possible it is important that the footprints of theradar and lidar are sampling ice cloud with similarcharacteristics.

An analysis of the spatial variability of ice clouds hasbeen carried out in order to investigate the effect ofseparating the footprints of the two instruments. Thetime series of retlectivity from the vertically pointingradar was converted into spatial variability using themean wind speed, and then a power law of the form:

E=Eoktswas tjtted to the Fourier spectra of these data, where Eis the power spectral density and k is the wave number.A typical best fit was of the form E = 2 x 10-5 p -z t6dBZ2 m (where k is in m-' ) . Synthetic cloud f leldswere generated by calculat ing the inverse two-dimensional Fourier transform of synthetic matricescontaining wave amplitudes consistent with the energyat the various scales indicated by this one dimensionspectrum. The phase of each wave component of thematrix was random so that each cloudfield wasdifferent. The domains were square and measured25.6km on a side with a resolut ion of 100m. We shallconsider a l-second averaging time for the spaceborneradar and l idar to achieve suff icient sensit ivi ty, whichresults in a pixel length of 7km. The eff'ect of footprintseparation has been simulated using 64 synthetic cloudflelds. The footprint of the lidar was taken as l00m andthat of the radar to be 700m with both instruments

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Figure 3: The effect of separating the radar and lidarfootprints on the radar/lidar backscatter ratio for iceclouds.

having a Gaussian beam pattern. Calculation of theradar backscatter is relatively straightforward, but tocalculate the lidar backscatter the radar reflectivity fieldwas transformed to an optical extinction using anempirical relationship from Hogan and illingworth(1999). The swaths of the spaceborne radar and lidarwere offset by up to l0km in the direction parallel tothe satellite motion. The result of the mean fractionerror in the backscatter ratio as a function of theseparation distance is displayed in figure 3. Note thateven when the centres of the footprints are both co-located there is an error in the backscatter ratio becausethe radar footprint is larger than that of the lidar, but theRMS vale of this error is only 0.2dB or less than 5Voand so can be neglected. When the footprint separationreaches 3km the RMS error is 2.3d8 or JjVo whichcould give an appreciable error in the derived sizes. Inpractice the errors will be worse than this, because ofthe difficulty of correcting the lidar attenuation andalso because of temporal evolution and advection of thecloud i f there is a t ime delay between the passage ofthe two instruments on separate platfbrms.

5. CLOUD OVERLAP.

The assumed overlap of cloud fraction in a verticalstack of grid boxes has a considerable influence on themodel performance. Two extreme assumptions are thatthe cloud at each level is maximally overlapped or thatat each level the overlap is random. It is now commonpractice to assume that vert ical ly continuously cloudis maximally overlapped but that clouds separated bycloud free grid boxes are randomly overlapped.

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Figure 4 shows an example of cloud radar data togetherwith the cloud mask derived from the radar data. Theboxes superposed over the cloud mask are for one hourand 360m in the vert ical and the derived cioud fract ionis the fract ion of such a box which is judged to containcloud. The rectangular box highl ighted in the upperpart of tigure 2 demonstrates that although adjacentlevels may well be maximally overlapped, there is atendency for the overlap to be come more random as theseparation of the levels increases.

The complete data set has been analysed and theoverlap parameter, o, calculated as a function of theseparation of the levels and plotted in f igure 5, wherecr=l implies maximal overlap and q,=0 is for randomoverlap. For vert ical ly non-continuous cloud therandom assumption is confirmed, but 1or verticallycontinuous cloud as the level separation increases thereis a change from maximum to random overlap whichoccurs with an e-folding distance of about l .68km.These results suggest that the overlap assumption inmodels should be adjusted. A future spaceborne radarand lidar would provide global statistics on this degreeof overlap.

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Figure 5: The overlap parameter versus level separationfor vertically continuous and non-continuous cloud,using boxes 360m in height and I hour in duration. Avalue of unity indicates maximum overlap and a valueof zero indicates random overlap.

6. COMPARISON OF THE FRACTIONAL CLOUDCOVER WITH THE ECMWF MODEL,

The method of deriving fractional cloud cover describedin the previous section has been adapted slightly toderive the vertical profile of fractional cloud cover overChilbolton and compare it with the ECMWF modelrepresentation for the enite three month period data set.The lidar was used to derive cloud base when lightdrizzle was falling from the cloud to avoid difficultieswhen the radar echo extended to the ground. Thecomparisons of fractional cloud cover were made forhourly periods at the heights of the grid boxes in theECMWF model. Rainfall can cause attenuation of the94GHz radar, so periods when the rainfall rate exceeded0.5mm/hr were excluded from the analysis. A typicalten day period of observations of fractional cloud coverand model representations is shown in figure 6. Theoverall agreement is very encouraging. However themean profiles in figure 7 do show some disagreements.Although the frequency of occurrence of any cloud is

Figure 6: Comparison of observed and ECMWF modelcloud fiaction at Chilbolton for a ten-day period inI 998.

0 0.2 0.4 06 0.8 1Frequency of occurrence

0 02 0.4 06 0.8Amount when present

Figure 7: Cloud fraction climatology split inro (a) thefrequency that the grid-box mean cloud fraction wasgreater than 0.05, and (b) the mean cloud amount whengreater than 0.05.

generally well predicted, the amount when present istoo low in the model below 6km and too high above6km. The disagreement below 6km arises because, incontrast to the model, the observations cannotmeaningful ly dist inguish precipitat ing snowfl akes fromnon-precipitating ice crystals. If model snow fluxesbelow 0.05mm/hr were reclassified as clouds, thenthere was very good agreement of the amount whenpresent below 6km. Examination of the lidarobservations suggests that such low fluxes of snowfallreally are associated with optically thick clouds. Theradiation scheme in the model is interpreting suchregions as cloud-free and this could be a source oferTor.

The difference in cloud amount when present above6km seems to be associated with very tenuous iceclouds which may be below the sensit ivi ty of the radar.However, removal of such low ice water content cloudsfrom the model still leaves an apparent modeloverestimate of cloud fraction by up to a factor of twofor these high altitude ice clouds.

7, SPACEBORNE USE OF 215 AND 94GHZRADARS.

Hogan and Illingworth (2000) have shown rhatsimultaneous observations of ref lect ivi ty with 35 and94GHz ground based radars can be used to provide anestimate of ice part icle size. The large part icles Mie

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scatter at the higher tiequency and so there is ameasurable reduction of reflectivity at 94GHz. Atground level the use of frequencies higher than 94GHzis not possible because of the attenuation by the highlevels of absolute humidity. Hogan and Illingworth(1999) show that from space this restr ict ion is muchless severe because the satellite is looking down at iceclouds through cold dry atmosphere and, for example,the total two-way attenuation looking vertically downthrough a standard tropical atmosphere to the freezinglevel at 2l5GHz is only ldB. Figure 8 displays thepredicted values of dual wavelength ratio as a functionof the median volume diameter for an exponentialdistribution of ice particles. They recommend thefrequency pair Zl5GHz and 79 or 94GHz. If the dualwavelength ratio can be measured to ldB then it shouldbe possible to estimate median diameters down to aboutl50pm. The sensitivity of a spaceborne radar at2l5GHz should not be a major restriction. Although thetransmitted power from available tubes may be 12dBlower atZlSGHz than 94GHz, this is offset by the l4dBincrease in sensitivity due to increased scatteringeff iciency.

0 0.5 1 1.5 2Median volume diameter Do (mm)

Figure 8: Dual wavelength ratio of reflectivity as afunction of median volume diameter for ice particleswith an exponential distribution.

8. CONCLUSIONS.

Based on an analysis of three months of simultaneousground based radar and lidar observations we draw thefol lowing conclusions :

a) Radar and lidar Sensitivity.

For the proposed spaceborne sensitivities of -35dBZfbr the radar and 8 10-? m-' sr-' fbr the lidar then theradar fails to detect only l7o of the radiativelysignif icant ice clouds sensed by the l idar.

b) Cloud base and cloud top detection for ice clouds.

For the proposed spaceborne sensitivities we concludethat the cloud base sensed with radar and lidar agree towithin 200m tor 737o of the time, and to within 400mtor 95Vo of the time. These differences are notsignificant when estimating the radiative properties ofclouds. The agreement can be improved if the lidarsensi t iv i ty is increased.

c) Embarking the radar and lidar on different platforms.

Because of the inhomogeneity of ice clouds if the lidarand radar footprints are separated by 3km, then the rootmean square error in the radar/lidar backscatter ratiowill be at least lOVa; this could compromise the use ofsuch a parameter to estimate ice particle size.

d) Cloud overlap.

Although the use of maximum-random overlap is usedby nearly all models, the radar data shows thatvertically continuous clouds are only maximallyoverlapped for small vertical separations. When theseparation reaches 4km the cloud overlap is essentiallyrandom.

e) Comparison of fractional cloud cover.

The vertical profiles of fractional cloud cover predictedby the ECMWF operational model are in very goodagreement with those measured. The modeldistinguishes between ice clouds and snow, but ifoccasions when the snow flux in the model is less than0.05mm/hr are classified as clouds then theimprovement is even better. The lidar indicates thatsuch low snow fluxes are associated with optically thickclouds and so the model really should consider them asclouds from a radiation point of view. There is still atendency for the model to overestimate ice cloudfraction above 6km by about a factor of two.

f) Dual wavelength radar.

The use of a dual frequency radar operating at 215 and94GHz appears to have great potential for providing anestimate of the size of ice particles. We suggest the thattechnological chal lenge of developing such a systemwarrants further research.

Acknowledgements:We acknowledge the support of ESTEC under contract10568/NUNB adn NERC GR3/8765. We thankChristian Jakob of ECMWF for the model data.

References:Hogan R.J and A.J. I l l ingworth (1999): The potentialof spaceborne dual-wavelength radar to make globalmeasurements of cirrus clouds. J Atmos and OceanTechnol . 16.518-531.

Hogan R.J. and A.J.I l l ingworth (2000): Measuringcrystal size in cirrus using 35 and 94GHz radars. JAtmos and Ocean Technol. 17.21-37.

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