使用衛星資料評析全球預報模式之 雲參數特性

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姓名

林祐乾(Yu-Chien Lin) 查詢紙本館藏

畢業系所

遙測科技碩士學位學程

論文名稱

使用衛星資料評析全球預報模式之雲參數特性

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摘要(中)

現今的天氣預報，十分仰賴數值天氣模式的資訊，因此，為了評估其可信度，必須對模式進行精確性分析。隨著衛星資料應用的與時俱進，其高時空解析度以及不受天候影響的優點，近年來成為驗證模式的工具之一。本研究即使用衛星資料，針對三個全球預報系統(Central Weather Bureau Global Forecast System；CWB GFS, National Center for Environmental Prediction Final Operational Global Analysis data；NCEP FNL, European Center for Medium Range Weather Forecasting (ECMWF) ERA-interim)之模擬衛星觀測，以及針對CWB GFS的雲參數特性，利用實際衛星資料進行評析。
於評估的時間與空間區間中，首先進行亮度溫度評估，此部分工作使用Community Radiative Transfer Model (CRTM)將模式輸出之地球物理量，正演成衛星所觀測到的亮溫，並與地球同步衛星所觀測到的亮溫進行分析。初步結果顯示，CWB GFS與NECP FNL表現非常相似，但高層薄雲的模擬可能較少或低估，而ERA-interim則在模擬雲頂溫度有最低溫約220K的閾值限制。
另外一方面，也進行了雲參數(即Cloud Fraction (CF)、Cloud Top Pressure (CTP)及Cloud Optical Thickness(COT))的特性評估，使用Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP)，進行模式與MODIS雲產品比較。分析結果顯示CWB GFS的高雲、薄雲太少，中層雲出現頻率過高且低雲有較大的低估，在非洲及澳洲沙漠區域的雲模擬次數過高，整體而言原因來自厚雲出現頻率過高、薄雲低估。評析總雲量平均的結果發現，沿岸處雲量高估、南海地區雲量高估，ITCZ (Intertropical Convergence Zone)下沉區雲量較為低估。

摘要(英)

The accurate cloud information is critical in the NWP (Numerical Weather Prediction) models, which might associate with improved forecast skills. Nowadays, meteorological satellites provide wide spatial coverage with multi channels’ spectrum of reflectance and/or radiances. Satellite-retrieved products are assumed to be a useful proxy data sets to evaluate the NWP model’s performance other than geophysical parameters. In this study, the evaluation of clouds in NWP models based on comparisons of observed and simulated climatologies of BT (Brightness temperature) and cloud fraction.
We adopt model analysis field during in the whole month of January in 2011. We would like to firstly use fast Community Radiative Transfer Model (CRTM) to evaluate Central Weather Bureau Global Forecast System (CWB GFS), National Center for Environmental Prediction Final Operational Global Analysis data (NCEP FNL), European Center for Medium Range Weather Forecasting (ERA-interim) model from calculated brightness temperature against to MTSAT-2. The initial results show that CWB GFS and NECP FNL perform very similar and both of them might underestimate the high level cloud. ERA-interim has threshold at the 220K region.
We secondly use Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) to evaluate CWB GFS cloud properties, and use the simulated cloud features to compare with MODIS level 3 cloud products. The results show that total cloud fraction perform well, but some overestimate at coastal region, some underestimate at ITCZ region. For cloud occurrence analysis, the results show some overestimate in Africa and Australia. Therefore, we try to combine the cloud top pressure and cloud optical thickness for further analysis. The overall results show model has various degree of error. These errors include an underestimation of optically thin clouds, high level cloud and low-level cloud; an overestimation clouds in middle levels and thick cloud. The reason might be caused by the cumulus parameterization scheme or ice water content scheme and so on.

關鍵字(中)

★ 雲參數特性

關鍵字(英)

★ COSP
★ CRTM
★ Cloud properties
★ Brightness temperature
★ CWB GFS
★ NCEP FNL,ERA-interim

論文目次

摘要 I
Abstract VII
致謝 IX
目錄 X
表目錄 XI
圖目錄 XII
第一章緒論 1
1.1　前言 1
1.2　文獻回顧 2
1.3　研究動機與目的 11
第二章分析及評估方法 17
2.1 實驗流程設計 17
2.2 Community Radiative Transfer Model (CRTM) 20
2.3 Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) 22
2.3.1雲滴等效粒徑 (effective radius of cloud droplet) 26
2.3.2雲光學厚度 (cloud optical depth) 27
2.3.3雲量 (cloud fraction) 27
2.3.4雲長波發射率 (cloud longwave emissivity) 28
2.4 CWB GFS雲參數與MODIS雲產品之時空匹配 29
第三章資料介紹 32
3.1　衛星資料 32
3.1.1 MODIS CDR雲產品 32
3.1.2　MTSAT-2 亮溫觀測資料 33
3.2　 NWP 模式資料 35
3.2.1 CWB GFS 35
3.2.2 NCEP FNL 36
3.2.3 ERA-interim 37
第四章結果與討論 39
4.1 大氣窗區亮度溫度分析 39
4.2 數值模式雲特性分析 44
第五章結論與未來展望 55
5.1 結論 55
5.2 未來展望 57
參考文獻 58

參考文獻

林孟岳，2016: Assessment of the NWP Model Physical Fields from Radiative Quantity，國立中央大學大氣物理研究所碩士論文，1-93。
莊耀中，2006: MODIS和NOAA衛星資料反演之大氣溫濕度剖線在夏季午後對流前兆分析之應用，國立中央大學太空科學研究所碩士論文，1-92。
Ban-Weiss, G. A., Jin, L., Bauer, S. E., Bennartz, R., Liu, X., Zhang, K., …& Jiang, J. H. (2014). Evaluating clouds, aerosols, and their interactions in three global climate models using satellite simulators and observations. Journal of Geophysical Research: Atmospheres, 119(18).
Barnes, W. L., Pagano, T. S., & Salomonson, V. V. (1998). Prelaunch characteristics of the moderate resolution imaging spectroradiometer (MODIS) on EOS-AM1. IEEE Transactions on Geoscience and Remote Sensing, 36(4), 1088-1100.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J. L., Klein, S. A., ... & John, V. O. (2011). COSP: Satellite simulation software for model assessment. Bulletin of the American Meteorological Society, 92(8), 1023-1043.
Businger, J. A., J. C. Wyngaard, Y. Izumi, and E. F. Bradley, 1971: Flux-profile relationships in the atmospheric surface layer, J. Atmos. Sci, 28, 181-1894-701.
Chahine, M. T., Pagano, T. S., Aumann, H. H., Atlas, R., Barnet, C., Blaisdell, J., ... & Gautier, C. (2006). AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bulletin of the American Meteorological Society, 87(7), 911-926.
Clough, S.A., M.W. Shephard, E.J. Mlawer, J.S. Delamere, M.J. Iacono, K. Cady-Pereira, S. Boukabara, and P.D. Brown, 2005: Atmospheric radiative transfer modeling: A summary of the AER codes. J. Quant. Spectrosc. Radiat. Transfer., 91, 233-244.
Ebert, E. E., & Curry, J. A. (1992). A parameterization of ice cloud optical properties for climate models. Journal of Geophysical Research: Atmospheres, 97(D4), 3831-3836.
Ek, M., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesocale Eta Model. J. Geophys. Res., 108, 8851
Evan, A. T., Heidinger A. K., & Vimont, D. J. (2007). Arguments against a physical long-term trend in global ISCCP cloud amounts. Geophysical Research Letters, 34(4).
Franklin, C. N., Sun, Z., Bi, D., Dix, M., Yan, H., & Bodas-Salcedo, A. (2013). Evaluation of clouds in ACCESS using the satellite situlatior package COSP: Regime-sorted tropical cloud properties. Journal of Geophysical Research: Atmospheres, 118(12), 6663-6679.
Han, J., and H.-L. Pan, 2011: Revision of convection and vertical diffuseion schemes in thr NCEP Global Forecast System. Wea. Forecasting,26,520-533.
Haynes, J. M., Marchand, R. T., Luo, Z., Bodas-Salcedo, A., & Stephens, G. L. (2007). A multipurpose radar simulation package: QuickBeam, B. Am. Meteorol. Soc., 88, 1723–1727.
Harshvardhan, Randall, D. A., & Corsetti, T. G. (1989). Earth radiation budget and cloudiness simulations with a general circulation model. Journal of the Atmospheric Sciences, 46(13), 1922-1942.
Heymsfield, A. J., & McFarquhar, G. M. (1996). High albedos of cirrus in the tropical Pacific warm pool: Microphysical interpretations from CEPEX and from Kwajalein, Marshall Islands. Journal of the atmospheric sciences, 53(17), 2424-2451.
Holz, R. E., Ackerman, S. A., Nagle, F. W., Frey, R., Dutcher, S., Kuehn, R. E., ... & Baum, B. (2008). Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation using CALIOP. Journal of Geophysical Research: Atmospheres, 113(D8).
Hou, Y., S. Moorthi,. K. Campana, 2002: Parameterization of solar radiation transfer in the NCEP models. NCEP Office Note, 441.
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote sensing of environment, 83(1-2), 195-213.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, M.W. Shephard, S.A. Clough, and W.D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103
Kiehl, J. T., & Trenberth, K. E. (1997). Earth′s annual global mean energy budget. Bulletin of the American Meteorological Society, 78(2), 197-208.
Kiehl, J. T., Hack, J. J., Bonan, G. B., Boville, B. A., Williamson, D. L., & Rasch, P. J. (1998). The national center for atmospheric research community climate model: CCM3. Journal of Climate, 11(6), 1131-1149.
King, M. D., Menzel, W. P., Kaufman, Y. J., Tanré, D., Gao, B. C., Platnick, S., ... & Hubanks, P. A. (2003). Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS. IEEE Transactions on Geoscience and Remote Sensing, 41(2), 442-458.
Kottayil, A., John, V. O., Buehler, S. A., & Mohanakumar, K. (2016). Evaluating the diurnal cycle of upper tropospheric humidity in two different climate models using satellite observations. Remote Sensing, 8(4), 325.
Lacis, A. A., & Hansen, J. (1974). A parameterization for the absorption of solar radiation in the earth′s atmosphere. Journal of the atmospheric sciences, 31(1), 118-133.
Li, J.-L., 1994:On shallow cumulus parameterization scheme for large-scale planetary boundary layers, Ph.D. thesis, University of Wisconsin-Madison, pp203.
Liang, X. M., Ignatov, A., & Kihai, Y. (2009). Implementation of the Community Radiative Transfer Model in Advanced Clear-Sky Processor for Oceans and validation against nighttime AVHRR radiances. Journal of Geophysical Research: Atmospheres, 114(D6).
Liu, C.-Y., Li, J., Weisz, E., Schmit, T. J., Ackerman, S. A., & Huang, H. L. (2008). Synergistic use of AIRS and MODIS radiance measurements for atmospheric profiling. Geophysical Research Letters, 35(21).
Liu, C.-Y., Liu, G. R., Lin, T. H., Liu, C. C., Ren, H., & Young, C. C. (2014). Using surface stations to improve sounding retrievals from hyperspectral infrared instruments. IEEE Transactions on Geoscience and Remote Sensing, 52(11), 6957-6963.
Luo, S., Sun, Z., Zheng, X., Rikus, L., & Franklin, C. (2016). Evaluation of ACCESS model cloud properties over the Southern Ocean area using multiple- satellite products. Quarterly Journal of the Royal Meteorological Society, 142(694), 160-171.
McFeeters, R. F.,Palma-Harris, C., & Fleming, H. P. (2001). Solid-phase microextraction (SPME) technique for measurement of generation of fresh cucumber flavor compounds. Journal of agricultural and food chemistry, 49(9), 4203-4207.
Palmer, T. N., G. Shutts, and R. Swinbank, 1986: Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parameterization. Quart. J. Roy. Meteor. Soc., 112, 1001-1039.
Pan, and W.-S. Wu, 1995: Implementing a mass flux convective parameterization package for the NMC Medium-Range Forecast model. NMC Office Note 409, 40pp
Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., & Miller, H. L. (2007). IPCC fourth assessment report: climate change 2007 (AR4).
Randel, D. L., Greenwald, T. J., Vonder Haar, T. H., Stephens, G. L., Ringerud, M. A., & Combs, C. L. (1996). A new global water vapor dataset. Bulletin of the American Meteorological Society, 77(6), 1233-1246.
Rossow, W. B., & Schiffer, R. A. (1999). Advances in understanding clouds from ISCCP. Bulletin of the American Meteorological Society, 80(11), 2261-2287.
Schaaf, C. B., Gao, F., Strahler, A. H., Lucht, W., Li, X., Tsang, T., ... & Lewis, P. (2002). First operational BRDF, albedo nadir reflectance products from MODIS. Remote sensing of Environment, 83(1), 135-148.
Schneider, S. H., & Dickinson, R. E. (1974). Climate modeling. Reviews of Geophysics, 12(3), 447-493.
Stephens, G. L., & Kummerow, C. D. (2007). The remote sensing of clouds and precipitation from space: A review. Journal of the Atmospheric Sciences, 64(11), 3742-3765.
Sun, Z., & Rikus, L. (2004). Validating model clouds and their optical properties using geostationary satellite imagery. Monthly weather review, 132(8), 2006-2020.
Tanré, D.,Kaufman, Y. J., Remer, L. A., Vermote, E. F., Chu, A., & Holben, B. N. (1997). Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. Journal of Geophysical Research: Atmospheres, 102(D14), 17051-17067.
Teixeira, J., Waliser, D., Ferraro, R., Gleckler, P., Lee, T., & Potter, G. (2014). Satellite observations for CMIP5: The genesis of Obs4MIPs. Bulletin of the American Meteorological Society, 95(9), 1329-1334.
Tiedtke, M., 1989: A Comprehensive Mass Flux Scheme for Cumulus Parameterization in Large-Scale Models. Monthly Weather Review, 117, 1779-1800.
Troen, I., and L. Mahrt, 1986: A simple model of the atmospheric boundary layer: Sensivity to surface evaporation. Bound. Layer Meteor., 37, 129-148.
Tsuang B-J, Tu C-Y, Arpe K, 2001: Lake parameterization for climate models. Max-Planck-Institute for Meteorology Rept.,316, p 72.
Tsuang et al., 2009: A more accurate scheme for calculating Earth’s skin temperature. Climate Dynamics, 32, 251-272.
Tu C-Y, Tsuang B-J, 2005: Cool-skin simulation by a one-column ocean model. Geophys Res Lett, 32: L22602. doi:10.1029/2005 GL024252.
Wylie, D. P., & Menzel, W. P. (1999). Eight years of high cloud statistics using HIRS. Journal of Climate, 12(1), 170-184.
Xu, K. M., & Randall, D. A. (1996). A semiempirical cloudiness parameterization for use in climate models. Journal of the atmospheric sciences, 53(21), 3084-3102.
Zhang, M. H., Lin, W. Y., Klein, S. A., Bacmeister, J. T., Bony, S., Cederwall, R. T., ... & Minnis, P. (2005). Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements. Journal of Geophysical Research: Atmospheres, 110(D15).
Zhao and F. H. Carr, 1997: A prognostic cloud scheme for operational NWP models. Mon. Wea. Rev., 125, 1931–1953.

指導教授

劉千義(Chian-Yi Liu)

審核日期

2018-1-31

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