Rotational Raman scattering in the Earth's atmosphere ... - SRON

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108 Chapter 5 Figure 5.4: Same as Fig. 5.3, but retrieval noise (e x ) as function of noise floor (η).
Retrieval of cloud properties from NUV, VIS and NIR 109 retrieval sensitivity, and thus in the degree of regularization of the inversion problem, arise solely from differences in the information that is present in the measurement. For this purpose we consider the retrieval noise e x,i in Fig. 5.4 together with the retrieval sensitivity shown in Fig. 5.3. In general, a higher retrieval sensitivity cannot automatically be associated with more information present in the measurement. It indicates a weaker regularization of the inversion and one has to make sure that a higher retrieval sensitivity is not accompanied by an enhanced retrieval error of the cloud parameters. In our case, Fig. 5.4 shows that the retrieval noise e x,i for the different cloud parameters is of the same order of magnitude when we compare the different spectral windows. Only for the retrieval of cloud top pressure from the NIR window with a retrieval sensitivity close to one for the full range of noise floor values we achieve significantly lower retrieval errors. Overall, the small variations of the retrieval noise anti-correlate with the retrieval sensitivity. Thus for a higher retrieval sensitivity we obtain a somewhat lower retrieval noise and vice versa. This clearly demonstrates that the variation of the retrieval sensitivities C i in Fig. 5.3 adequately reflects the retrieval capability of the different spectral windows. Summarized, for fully clouded scenes it is possible to retrieve all three cloud parameters, p c , f c , and τ c from the NUV window with sensitivities C i >0.5 up to reasonable noise levels (< 0.8%). Of the three windows, the VIS window is most sensitive to additional random-like spectral biases on the measurement: here the sensitivity to cloud top pressure retrieval for high clouds and to cloud optical thickness for thick clouds rapidly diminishes when the noise level increases to > 0.5%. For low clouds though, the VIS window provides a similar performance as the NUV window. The retrieval of cloud top pressure from NIR window appears unaffected by noise floors up to 1.5%. The cloud optical thickness on the other hand (and to a lesser degree the cloud fraction retrieval) is highly sensitive to random-like biases. To investigate the retrieval capabilities of the NUV, VIS and NIR windows in further detail we choose a noise floor η = 0.1% and study the information on the cloud parameters as a function of cloud fraction. Fig. 5.5 shows the sensitivity C pc , C fc , C τc and C As , as function of f c . For the NUV window all three cloud parameters can be retrieved with a high sensitivity, i.e. C pc , C fc , C τc > 0.7 down to low cloud fractions of f c ≈ 0.2, for all scenarios. Here the differences between low and high cloud and optically thick and thin cloud are small. The situation differs for the VIS window where cloud top pressure retrieval shows a low retrieval sensitivity, e.g. C pc ≤0.45 for the high cloud scenario. As mentioned earlier this results from the weak O 2 -O 2 absorption coefficient at higher tropospheric altitudes. Finally, the NIR window provides highest sensitivity C pc ≈ 1 for the retrieval of p c for all cloud fractions. However it has its shortcoming in the retrieval of cloud optical thickness. For the optical thick cloud only a very low sensitivity is achieved of about C τc = 0.1 and also for the optically thin cloud the sensitivity does not exceed a value of 0.5 for cloud fractions f c < 0.5. In all three spectral windows the Lambertian surface albedo can only be extracted from the measurement when the cloud fraction is low. This holds for all cases that are studied in this paper and therefore the retrieval sensitives C As are hereafter not shown. Furthermore, we studied the retrieval noise e x for the scenarios in Fig. 5.5 (not shown). Similar to Fig. 5.3 we found that the dependence of the retrieval noise on cloud fraction allows us also in this case to use the retrieval sensitivity to investigate cloud information in the measurement. This holds for the other scenarios in the remainder of this study as
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VRIJE UNIVERSITEIT Rotational Raman
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Contents 1 Introduction 1 1.1 Obser
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1 Introduction 1.1 Observing skylig
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Introduction 3 Extracting the wealt
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Introduction 5 and Spurr, 1997, Vou
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Introduction 7 energy: E rot (v,J)
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Introduction 9 Figure 1.4: Probabil
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Introduction 11 scattered radiance
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Introduction 13 approximation in wh
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Introduction 15 scattering have bee
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2 A doubling-adding method to inclu
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A doubling-adding method to include
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40 Chapter 3 nm with a spectral res
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42 Chapter 3 contributions of lower
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44 Chapter 3 if we use the effectiv
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46 Chapter 3 This in turn results i
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48 Chapter 3 This may be shown in a
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50 Chapter 3 The forward and adjoin
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52 Chapter 3 Here, ∆ = diag [1, 1
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54 Chapter 3 Figure 3.3: Relative R
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56 Chapter 3 biases the simulation
Page 64 and 65: 58 Chapter 3 3.4.2 Approximation me
Page 66 and 67: 60 Chapter 3 where I ram,app and I
Page 68 and 69: 62 Chapter 3 3.5 Simulation of pola
Page 70 and 71: 64 Chapter 3 Figure 3.10: Relative
Page 72 and 73: 66 Chapter 3 dependence on the vert
Page 74 and 75: 68 Chapter 3 Figure 3.13: Same as F
Page 76 and 77: 70 Chapter 3 3.6 Summary A vector r
Page 78 and 79: 72 Chapter 3 where λ is the wavele
Page 80 and 81: 74 Chapter 3 where S l is the expan
Page 82 and 83: 76 Chapter 3 3.C Appendix: Evaluati
Page 85 and 86: 4 Accurate modeling of spectral fin
Page 87 and 88: Accurate modeling of spectral fine-
Page 103 and 104: 5 Retrieval of cloud properties fro
Page 105 and 106: Retrieval of cloud properties from
Page 113: Retrieval of cloud properties from
Page 125 and 126: References Aben, I., F. Helderman,
Page 127 and 128: References 121 Ellery, A., D. Wynn-
Page 129 and 130: References 123 Lacis, A. A., J. Cho
Page 131 and 132: References 125 Schulz, F., K. Stamn
Page 133 and 134: Summary A spectrum of sunlight that
Page 135 and 136: Summary 129 Earth radiance spectrum
Page 137 and 138: Samenvatting Het door de aardatmosf
Page 139 and 140: Samenvatting 133 met een vector-mod
Page 141: List of publications Peer-reviewed
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