臺灣博碩士論文加值系統

高光譜紅外輻射儀以及掩星技術之觀測皆提供大量的大氣觀測，而先前研究指出此兩種觀測擁有互補之性質。來自高光譜紅外線觀測的溫度反演，在高對流層以及低平流層之區域常有較大的誤差，而掩星觀測在此高度則是擁有相對較高的準確度。因此，若結合掩星以及高光譜之觀測，則可能改善原單以紅外線反演得到的溫度與溼度垂直剖面。此研究提出一項同時使用掩星折射率以及紅外線亮溫之反演演算法，用於溫度以及溼度的垂直剖面反演。使用此研究中提出之反演法所得到的溫度剖面，在 100 百帕到 300 百帕之間，其均方根差之降低大約為 24%(0.36K;與再分析場比較時)與35%(0.66K;與探空感測比較時)。在高對流層對於溫度反演有所改進之外，溼度的反演上亦有改善，在100 百帕以下的平均均方根差之降低最大高達 43%(0.57g/kg)。研究中提出的演算法所得到的反演產品，與再分析場以及探空氣球觀測之各項比較後，其溼度反演之準確度於每項實驗皆優於單以紅外亮溫反演的產品，而其溫度反演則是在高層對流層上之改善最為顯著。

Hyperspectral infrared spectrometers and the radio occultation (RO) technique have become crucial for observing the atmosphere, and past studies showed that these two types of observations have complementary characteristics. Temperature retrievals from infrared sounders, such as the Atmospheric InfraRed Sounder (AIRS), tend to have higher error in the upper troposphere. In contrast, radio occultation measurements have a high vertical resolution, are highly accurate for temperature estimates in the upper troposphere and lower stratosphere, and can potentially be used to improve radiance-based temperature estimates. This study presents a physical-statistical algorithm which uses RO-derived refractivity and spectrometer radiances simultaneously to estimate temperature and humidity vertical profiles, demonstrated with measurements from FORMOSAT-3/COSMIC and AIRS. Comparison of simultaneously derived profiles and AIRS-alone derived profiles showed that the impact of RO observations to be most apparent in the upper troposphere between 100 hPa and 300hPa, where it reduced the root-mean-square difference of estimated temperature with a minimum reduction of 24\% (0.36 K) and a maximum of 35\% (0.66 K). In addition to having improved temperature profile retrievals in the upper troposphere, the humidity retrievals were also improved; the average root-mean-square difference below 100 hPa was reduced up to 43\% (0.57 g/kg) in comparison to radiosondes. In comparison to different reanalysis datasets and radiosonde soundings, the humidity profiles retrieved using the proposed algorithm were overall better than the infrared-only retrievals in all of the comparisons, and the temperature profiles improved upon the infrared-only most notably in the upper troposphere.

1 Introduction 1
2 Background 4
2.1 Characteristics of Hyperspectral Radiances Retrievals . . . . . . . 4
2.2 Characteristics of Radio Occultation Refractivity Retrievals . . . . 6
2.3 Comparison of Refractivity Retrievals and Radiance Retrievals . . 8
3 Methodology 11
3.1 Retrieval Method Using Infrared Radiance . . . . . . . . . . . . . 11
3.1.1 Retrieval in Empirical Orthogonal Function Space . . . . 14
3.2 Retrieval Method Using Radio Occultation Refractivity and In-
frared Radiance . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.3 Forward Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3.1 Radiance Forward Model . . . . . . . . . . . . . . . . . . 16
3.3.2 Refractivity Forward Model . . . . . . . . . . . . . . . . 16
3.4 Jacobian of the Forward Models . . . . . . . . . . . . . . . . . . 20
3.4.1 Jacobian of the Radiance Forward Model: Weight Functions 20
3.4.2 Jacobian of the Refractivity Forward Model . . . . . . . . 21
3.5 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.5.1 Observation Datasets . . . . . . . . . . . . . . . . . . . . 24
3.5.2 Reference Datasets . . . . . . . . . . . . . . . . . . . . . 25
iii3.5.3 Auxiliary Datasets Used in the Retrieval . . . . . . . . . . 26
3.5.4 Collocation for Observations and Reference Datasets . . . 26
4 Experiments and Preliminary Results 29
4.1 Evaluation of Retrieval Profiles with Reanalyses and Radiosonde
Soundings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.2 Effect of Moisture on Retrieval Accuracy . . . . . . . . . . . . . 34
4.3 Impact of Boundary Layer Refractivity on Retrieval Performance . 37
5 Conclusion 58
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