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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ClimatologyLecture 1: What is climate?
What should be learned in climatology?
(b) theoretical/analytical study (c) experiment & numerical modeling
Aspects: Formation, structure, evolution, interaction, and feedback
What the weather might be up to tomorrow?
Is the coming rainy season normal? Ancient civilizations appealed to the gods of the sky
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
This is much better
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.
TheophrastusAristotles student, 287 BCBook of Signs (served as the definitive weather book for 2,000 years!)
Climate, a tract or region of the earth (clime in many poems)
in ancient Greece
klima in German & Norwegian
ora in Latin
It advanced little after ancient Greece until the Renaissance
(Gustav Coriolis 19)
(The Bergen School)
1920:(polar front theory)(Bjerknes, Solberg, Bergeron)
(The Chicago School-Dynamical meteorology era)
1950von NeumannW. Nielsen J. Charney(NWP)
1960TIROS-1Advanced TIROS (NOAA series) GOES and GMS(especially )
Image of a cyclone from TIROS1
Journal of the Atmospheric Sciences: Vol. 35, No. 3, pp. 414432.The Life Cycles of Some Nonlinear Baroclinic WavesAdrian J. Simmons and Brian J. Hoskins
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
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.
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.
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 52N to 72N) 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.
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.
Source: IPCC TAR (2001) Summary for Policy Makers
Source: IPCC AR4 (2007) Summary for Policy Makers
--(A statistical ensemble of states of the atmosphere-ocean-land system during a time period several decades long. )
(multiple scale)WMO()30(1951-1980)IPCC1961-1990 (anomaly;)
Can climate change occur over short time period?
By definition, NO!
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?
Source: IPCC AR4 (2007) Scientific basis
Hard wall adds nonlinear response
in initial x,v lead to
motion is bounded
Two dimensional Lorenz attractor for simple model of the weather
A butterfly !
Internal forcings: reacts of interactions to a subsystem