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Climatology Lecture 1: What is climate?

Climatology Lecture 1: What is climate?. What should be learned in climatology?. 氣候學研究. Nature phenomena Observations: qualitative & quantitative descriptions Interpretation: (a) data diagnosis

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Climatology Lecture 1: What is climate?

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  1. ClimatologyLecture 1: What is climate? What should be learned in climatology?

  2. 氣候學研究 • Nature phenomena • Observations: qualitative & quantitative descriptions • Interpretation: (a) data diagnosis (b) theoretical/analytical study (c) experiment & numerical modeling Aspects: Formation, structure, evolution, interaction, and feedback • Application: forecast-error-modification

  3. What the weather might be up to tomorrow? Is the coming rainy season normal? Ancient civilizations appealed to the gods of the sky History(1) Egyptians looked to Ra, the sun god, Greeks sought out the all-powerful Zeus, and in Ancient Nordic people, there was Thor, the god of thunder and lightning. Aztecs use human sacrifice to satisfy the rain god, Tlaloc(He who makes things sprout). Native American and Australian aborigines performed rain dances. Those who were able to predict the weather/climate and seemed to influence its production were held in highest esteem. modern wizards

  4. Tlaloc

  5. This is much better

  6. History(1) Climatology is the study of atmosphere and its phenomena (Meteorology and Climate). It is a natural science due to the use of scientific instruments to make observations. Aristotle（340 BC），Meteorologica，和天氣與氣候相關的知識。包括天文學、地理學、以及化學。研究雲、雨、雪、風、雹、雷、和颶風等自然現象。” meteoros”希臘字意指在高空中。Meteorology研究由高空掉落以及在空氣中各種現象。 Theophrastus（Aristotle’s student, 287 BC），Book of Signs (served as the definitive weather book for 2,000 years!)，第一本天氣預報的書，利用與天氣變化有關的訊息來預報天氣。 Climate, a tract or region of the earth (clime in many poems) κλιμα in ancient Greece klima in German & Norwegian ora in Latin localitin Italian

  7. History(2) It advanced little after ancient Greece until the Renaissance 意大利天文學家 伽利略(16世紀)：溫度計。 意大利數學及物理學家 托里賽利(17世紀)：水銀氣壓計。 法國數學及哲學家 帕斯卡和笛卡兒(17世紀)：氣壓隨高度變化。 英國科學家 霍克(17世紀)：風速計。 德國物理學家 華氏(18世紀)：定華氏溫標。 法國化學家 查爾斯(18世紀)：溫度與固定體積空氣的關係。 瑞典天文學家 攝氏(18世紀)：定攝氏溫標。 美國科學家富蘭克林(18世紀)：放風箏入雷暴證明閃電來源。 瑞士地質及氣象學家 笛紹高斯(18世紀)：毛髮濕度計。 溫度，氣壓，風速風向，濕度，閃電等氣象參數的度量，及其與天氣現象間之關係開始被建立

  8. history(3) 英國氣象學家 哈德里(18世紀)：解釋地球旋轉如何影響赤道的風向。 1821年天氣圖被繪製（天氣現象） 法國物理學家 科氏(Gustav Coriolis 19世紀)：數學證明地球旋轉對大氣運動的影響。 1842年電報系統發展，長程通訊對氣象事業發展影響深遠 1869年等壓線的繪製（現代天氣圖） 挪威學派 (The Bergen School) 1920年氣團與鋒面的概念開始建立:極鋒理論(polar front theory)，近代天氣學的開端(Bjerknes, Solberg, Bergeron) ⊿

  9. ⊿

  10. Vilhelm F. K. Bjerknes(1862-1951) Jacob A.B. Bjerknes(1897-1975) BJERKNES FAMILY • Pioneers in modern meteorology and climate research • Born on the 14th March, 1862 in Oslo (Christiania), Vilhelm Frimann Koren Bjerknes was destined for a career in science. He obtained a Master’s degree in mathematics and physics in Kristiania 1888 and continued his studies in Paris and Bonn, where his work together with HeinrichHertz on electrical resonance resulted in a doctoral thesis in 1892. • While he was professor at the University of Stockholm (1895-1906), Vilhelm Bjerknes worked out a synthesis of hydrodynamics and thermodynamics, which was applicable to large-scale circulation in the atmosphere and the oceans. Based on his theorems, he published a programatic paper in 1904 on “The problem of weather forecasting as a problem in mechanics and physics” (Meteorologische Zeitschrift, Wien 21:1-7) where he postulated the procedure now know as numerical weather forecasting. Once at the Geophysical Institute in Bergen (1917-1926), he laid the foundations of the Bergen School of Meteorology. Bjerknes established a network of weather observations in Norway that collected data that would be of great importance in their later work. Together with his son Jacob, also an acknowledged meteorologist, he put forward the acclaimed “polar front theory”. In analogy with WWI battlefronts, the meteorological “fronts” form the boundaries between cold and warm air masses and their theories and models suggested that weather activity is concentrated in these relatively narrow zones, where mid-latitude cyclones were proposed to form, live, and decay. Today, practically all weather forecasting is based on Bjerknes principles described in his paper of 1904 and made possible thanks to the enormous computer capabilities of today. The work by Bjerknes marked a turning point in atmospheric science and remains remarkably unaltered to this day. • Further, Vilhelm and Jacob Bjerknes conducted several studies of the ocean circulation, air-sea exchange, and climate variability that laid the basis for modern research on climate change and the role of the ocean in the climate system. Jacob Bjerknes carried out pioneer studies on the North Atlantic Oscillation (NAO), by describing its major features and how it influences the currents and temperature conditions in the North Atlantic. Nowadays the vision provided by the Bjerknes family has been taken further by simulating climate variability in models that couple the atmosphere, land, and oceans, in an attempt to estimate the response of the climate system to driving forces. • The Centre is named is thus named as a tribute to their efforts. • (BCCR: Bjerknes Center for Climate Research, Norway)

  11. history(4) 芝加哥學派(The Chicago School-Dynamical meteorology era) 1940年氣球探空、雷達、氣象飛機，西風噴流，羅士培波(Rossby waves:西風帶長波)，WMO成立 現代氣象科學的蓬勃發展 1950年von Neumann，W. Nielsen， J. Charney，發明高速電子計算機，建立準地轉理論（長波與氣旋鋒面），數值天氣預報(NWP) 1960年氣象衛星（TIROS-1），Advanced TIROS (NOAA series) ，GOES and GMS，進行全球監測(especially 熱帶海洋氣象)，都卜勒雷達 1970年全球氣候與環境變遷，聖嬰與南方震盪(ENSO)，南極臭氧洞，全球暖化 1980年剖風儀、雙偏振都卜勒雷達、複雜衛星系統、超大快速電子計算機

  12. NEXT

  13. Image of a cyclone from TIROS1

  14. history（5）20世紀氣候學發展的十大成就 • 20~30年代, 三大氣壓震盪,北大西洋震盪(NAO),北太平洋震盪(NPO),南方震盪(SO); Walker (1932) • 30年代, 大氣長波理論-羅士比波, Rossby (1939) • 40~50年代, 時間平均環流之長波預測, Namias (1953) • 60年代, 赤道東西向沃克環流, Bjerknes (1969) • 70年代, 溫室效應(doubling CO2), Manabe (1975) • 80年代, 月平均環流預測, Miyakoda (1986) • 80~90年代, ENSO預測, Cane and Zebiak (1986) • 80~90年代, ENSO理論, Suarez (1988), Battisti (1989) • 90年代, 溫鹽環流, Brocker , Delworth (1993) • 90年代, 季平均環流預測, Madden-Julian Oscillation(Madden 1994), Ming Ji (1994)

  15. Carl-Gustav Rossby: Long waves in the westerly

  16. Early days of NWP

  17. Jule Charney’s influence on modern Meteorology/long waves vs polar front (1982, BAMS)

  18. 極鋒理論在北半球溫帶氣旋之理想生命周期的連續天氣示意圖。在其生命期，系統由於動力作用向東移。極鋒理論在北半球溫帶氣旋之理想生命周期的連續天氣示意圖。在其生命期，系統由於動力作用向東移。

  19. Journal of the Atmospheric Sciences: Vol. 35, No. 3, pp. 414–432.The Life Cycles of Some Nonlinear Baroclinic WavesAdrian J. Simmons and Brian J. Hoskins

  20. Chaos Theory混沌理論 • Predictability problem：可預報度問題

  21. 20世紀氣候學發展的十大成就 • 20~30年代, 三大氣壓震盪,北大西洋震盪(NAO),北太平洋震盪(NPO),南方震盪(SO); Walker (1932) • 30年代, 大氣長波理論-羅士比波, Rossby (1939) • 40~50年代, 時間平均環流之長波預測, Namias (1953) • 60年代, 赤道東西向沃克環流, Bjerknes (1969) • 70年代, 溫室效應(doubling CO2), Manabe (1975) • 80年代, 月平均環流預測, Miyakoda (1986) • 80~90年代, ENSO預測, Cane and Zebiak (1986) • 80~90年代, ENSO理論, Suarez (1988), Battisti (1989) • 90年代, 溫鹽環流, Brocker , Delworth (1993) • 90年代, 季平均環流預測, Madden-Julian Oscillation(Madden 1994), Ming Ji (1994)

  22. 大氣海洋交互作用-聖嬰與南方震盪ENSO

  23. Walker circulation-an equatorial belt circulation The term “Walker circulation” was first defined by Bjerknes (1969) to describe an exchange of air in the zonal plane for the equatorial belt from South America to the western Pacific. Bjerknes considered this circulation to be part of the global Southern Oscillation phenomenon defined earlier in the statistical sense by Sir Gilbert Walker (1923, 1924, 1928). Bjerknes also postulated that the gradient of ocean surface temperature along the equator was the cause of the Walker circulation. Newell et al. (1974) later expanded this concept by considering circulations in zonal planes circumscribing the entire globe at any tropical latitude. Chervin and Druyan 1984 MWR

  24. Sea surface temperature anomaly map

  25. Walker’s southern oscillation (Bjerknes 1969)

  26. Journal of the Atmospheric Sciences: Vol. 32, No. 1, pp. 3–15. • The Effects of Doubling the CO2 Concentration on the climate of a General Circulation Model • Syukuro Manabe and Richard T. WetheraldGeophysical Fluid Dynamics Laboratory/NOAA, Princeton University, Princeton, N.J. 08540 • (Manuscript received 6 June 1974, in final form 8 August 1974) ABSTRACT An attempt is made to estimate the temperature changes resulting from doubling the present CO2 concentration by the use of a simplified three-dimensional general circulation model. This model contains the following simplications: a limited computational domain, an idealized topography, no heat transport by ocean currents, and fixed cloudiness. Despite these limitations, the results from this computation yield some indication of how the increase of CO2 concentration may affect the distribution of temperature in the atmosphere. It is shown that the CO2 increase raises the temperature of the model troposphere, whereas it lowers that of the model stratosphere. The tropospheric warming is somewhat larger than that expected from a radiative-convective equilibrium model. In particular, the increase of surface temperature in higher latitudes is magnified due to the recession of the snow boundary and the thermal stability of the lower troposphere which limits convective beating to the lowest layer.It is also shown that the doubling of carbon dioxide significantly increases the intensity of the hydrologic cycle of the model.

  27. Monthly Weather Review: Vol. 114, No. 12, pp. 2363–2401. • One-Month Forecast Experiments—without Anomaly Boundary Forcings • K. Miyakoda, J. Sirutis, and J. PloshayGeophysical Fluid Dynamics Laboratory/N0AA, Princeton University, Princeton, NJ 08542 • (Manuscript received 17 August 1985, in final form 19 May 1986) ABSTRACT A series of one-month forecasts were carried out for eight January cases, using a particular prediction model and prescribing climatological sea-surface temperature as the boundary condition. Each forecast is a stochastic prediction that consists of three individual integrations. These forecasts start with observed initial conditions derived from datasets of three meteorological centers. The forecast skill was assessed with respect to time means of variables based on the ensemble average of three forecasts. The time or space filter is essential to suppress unpredictable components of atmospheric variabilities and thereby to make an attempt at extending the limit of predictability. The circulation patterns of the three individual integrations tend to be similar to each other on the one-month time scale, implying that forecasts for the 10 day (or 20 day) means are not fully stochastic. The overall results indicate that the 10-day mean height prognoses resemble observations very well in the first ten days, and then start to lose similarity to real states, and yet there is some recognizable skill in the last ten days of the month. The main interests in this study are the feasibility of one-month forecasts, the adequacy of initial conditions produced by a particular data assimilation, and the growth of stochastic uncertainty. An outstanding problem turns out to be a considerable degree of systematic error included in the prediction model, which is now known to be “climate drift.” Forecast errors are largely due to the model's systematic bias. Thus, forecast skill scores are substantially raised if the final prognoses are adjusted for the model's known climatic drift.

  28. Oscillation of the thermohaline circulation • Journal of Climate: Vol. 6, No. 11, pp. 1993–2011. • Interdecadal Variations of the Thermohaline Circulation in a Coupled Ocean-Atmosphere Model • T. Delworth, S. Manabe, and R.J. StoufferGeophysical Fluid Dynamics Laboratory/N0AA, Princeton University, Princeton, New Jersey • (Manuscript received 5 September 1992, in final form 26 February 1993) ABSTRACT A fully coupled ocean-atmosphere model is shown to have irregular oscillations of the thermohaline circulation in the North Atlantic Ocean with a time scale of approximately 50 years. The irregular oscillation appears to be driven by density anomalies in the sinking region of the thermohaline circulation (approximately 52°N to 72°N) combined with much smaller density anomalies of opposite sign in the broad, rising region.The spatial pattern of sea surface temperature anomalies associated with this irregular oscillation bears an encouraging resemblance to a pattern of observed interdecadal variability in the North Atlantic. The anomalies of sea surface temperature induce model surface air temperature anomalies over the northern North Atlantic, Arctic, and northwestern Europe.

  29. 氣候科學的最新發展 • 大氣與海洋的交互作用：季風和聖嬰現象的研究，並延伸至短期氣候變化的預測，這方面的研究關連到大氣科學家與海洋學家的合力研究。 • 數值模擬：模擬天氣及氣候預報，利用電腦自動計算結果經人為詮釋進行預報。這方面的研究關連到大氣科學家，應用數學家及電子計算機專家的合作。 • 空氣污染問題：熱島效應,全球增溫,南極臭氧洞等。這方面的研究關連到大氣科學家與化學家的通力合作。 • 探討地球氣候變遷的歷史：這方面的研究牽涉到大氣科學家，地球化學家，地質學家,海洋學家,及冰河學家們的合作。探討百年甚至千年氣候變化的原因與未來之可能趨勢，並討論因應對策。

  30. 氣候變遷 UK The contribution to each winter's total precipitation made from "heavy" precipitation days, indicated by red (below average) and blue (above average) bars. A black smoothing line to highlight decadal variations has been overlaid.

  31. Source: IPCC TAR (2001) Summary for Policy Makers

  32. Source: IPCC AR4 (2007) Summary for Policy Makers

  33. What is climate (A.S. Monin)? 在長達數十年期間，大氣-海洋-陸地系統狀態的統計系集」(A statistical ensemble of states of the atmosphere-ocean-land system during a time period several decades long. )。 三個重點: 統計系集、數十年及大氣-海洋-陸地系統

  34. 統計系集 氣候是由許多隨機過程所組成的，無法以數學函數準確地描述它在任何時刻的確切狀態(無論是過去或未來)。但是，它也可能具有某些可以被偵測到的統計特性。最明顯的例子是四季變化。地球自轉軸相對於黃道面的傾斜角（約23.5度）以及地球繞太陽公轉，是造成四季的主要原因之一。如果，上述的天文因素是影響四季的唯一因子，我們就可準確的預測世界各地的四季變化。但是，各地的四季變化還受到緯度、高度、海陸分布、地形、大氣內部動力甚至人為因素等的影響。已知及未知的隨機過程不斷地塑造地球氣候，令我們無法預知每一天的確切溫度。

  35. 統計系集 所幸經過許多觀測，我們仍可歸納出各地的四季變化的主要特徵，而且發現它仍是受到上述天文因素的影響。每一季節的長期平均溫度可以從許多年的資料計算出來，我們因此知道冷暖氣候的空間分布。分析多年資料之後，我們同時也發現冬季之後是春季、夏季、秋季，再回到到冬季，亦即季節與季幫之間有極高的相關性(red noise)。這個循環每年不停地運作，此一季節變化的長期平均特性，就是Monin所說的統計系集。由以上討論，我們知道，氣候是大氣-海洋-陸地系統的統計特性，而非任何時刻的確切狀態。

  36. 數十年 氣候具有多重時間尺度(multiple scale)的特性。氣候學要闡述的是變化較緩慢的部份，因此必須作某種篩選以便濾除氣候系統中變化較快的部份。最常用的方法即時間平均。但是，對於應取多長的時間來計算氣候特性的系集平均有許多不同的看法。WMO(世界氣象組織)將之定義為30年(1951-1980)。IPCC則取1961-1990 ，再以此為參考點，探討氣候在其他時間的相對變化(anomaly;距平)。 Can climate change occur over short time period? By definition, NO!

  37. What is climatology? Study the statistical properties of the atmospheric variables: means, variability, max, min., etc. Weather or climate? Did it rain yesterday at Taipei? When does Bombay enter the rainy season? Was last winter colder than normal?

  38. 大氣-海洋-陸地系統 • Monin定義的氣候系統，只包含了大氣、海洋、陸地三大分量，明確地指出氣候變化的表徵雖然主要呈現在描述大氣的氣象變數上，此表徵實際上是三大氣候次系統歷經交互作用後的產物。 • 近年來更再細分之以考慮生物的影響。地球氣候系統則包括大氣圈、水圈、冰雪圈、岩石圈及生物圈。這些次系統彼此之間又息息相關，不斷地進行交互作用。=>Rising of Earth System Science • 五大氣候次系統，以大氣圈變化最快。次系統之間的交互作用的結果也最快呈現於大氣圈。

  39. Subsystems in Earth Climate System • Atmosphere: Nitrogen (78.1% volume mixing ratio) and oxygen (20.9%), together with a number of trace gases (argon 0.93%, helium, ozone, and carbon dioxide 0.035%). It also contains clouds and aerosols. • Hydrosphere: Liquid surface and subterranean water (oceans, seas, rivers, fresh water lakes, underground water etc.) • Cryosphere: Snow,ice, and permafrost at and beneath the surface of the earth and ocean. • Lithosphere: The upper layer of the solid Earth, both continent and ocean, comprising all crustal rocks and the cold part of the uppermost mantle (volcanic activity is generally excluded). • Biosphere: ecosystems and living organisms in the atmosphere, on land or in the oceans, including derived dead organic matter, such as litter, soil organic matter and oceanic detritus.

  40. 複雜程度不斷增加的氣候科學 Source: IPCC AR4 (2007) Scientific basis

  41. (非線性)交互作用暗示固有的不可預測性(Intrinsic unpredictability) • The laws of momentum conservation here lead to intrinsic nonlinearity (Navier-Stokes equations). Here u is the velocity of a parcel of air or fluid. ↑↑↑↑↑↑ Nonlinearity

  42. 混沌現象: Impossibility of knowing initial conditions with perfect precision Hard wall adds nonlinear response Slight differences in initial x,v lead to very different trajectories – still, motion is bounded

  43. But, trajectories are confined to ``attractors’’ – average behavior can be well defined !=> bounded system Two dimensional Lorenz attractor for simple model of the weather

  44. A butterfly !

  45. External forcings Internal forcings: reacts of interactions to a subsystem response

  46. End of Lecture 1

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