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Kimawirkungen, einesystematische Übersicht
Klimadefinitionen und Klassifikationen
Matthias Lüdeke
Matthias Lüdeke
Klima ist die Synthese des Wetters über einen Zeitraum, der lang genug ist, um dessen statistische Eigenschaftenbestimmen zu können
(nach WMO 1979, siehe Hupfer 1996)
Matthias Lüdeke
Climate in a narrow sense is usually defined as the average weather or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system
IPCC, WG I, 2007
Matthias Lüdeke
Climate in a narrow sense is usually defined as the average weather or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system
The climate system is the highly complex system consisting of five major components: the atmosphere, the hydrosphere, the cryosphere, the land surface and the biosphere, and the interactions between them. The climate system evolves in time under the influence of its own internal dynamics and because of external forcings such as volcanic eruptions, solar variations and anthropogenic forcings such as the changing composition of the atmosphere and land use change
IPCC, WG I, 2007
Matthias Lüdeke
Climate in a narrow sense is usually defined as the average weather or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system
Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer.
IPCC, WG I, 2007
Matthias Lüdeke
Wettervariablen: Messung, Übergang zum Klima: Eigenschaften derVerteilungsfunktionen, Bsp.: Säkularstation Potsdam
Trendbestimmung: Temeratur. Bsp. - Säkularstation Potsdam, “Bootstrapping” zur Signifikanzbestimmung.
Matthias Lüdeke
FlächendeckendeGlobale Wetter- und Klimadatensätze:(interpolierteStationsdaten)
Cramer/Leemanns:
Walther-Diagramme im0.5x0.5° Raster(720x360 Gitterpunkte)T, Pr, I: klim. Monatsmittel
Climate Research Unit (Norwich, UK)
T, Pr, I: Monatsmittelüber 100 Jahre
Matthias Lüdeke
Klimaklassifikationen
(a) Effektive Klimaklassifikationen (Köppen u.a.)
(b) Genetische Klimaklassifikationen (Hendl u.a.)
(c) Statistische Klimaklassifikationen (Kropp u.a.)
Matthias Lüdeke
The Köppen climate classification is one of the most widely used climate classification systems. It was developed by Wladimir Köppen, a German climatologist, around 1900 (with several further modifications by Köppenhimself, notably in 1918 and 1936). It is based on the concept that native vegetation is the best expression of climate; thus, climate zone boundaries have been selected with vegetation distribution in mind. It combines average annual and monthly temperatures and precipitation, and the seasonality of precipitation.
http://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification
Matthias Lüdeke
* Tropical rain climates (A)
Equatorial (Af) Monsoon(Am) Savanna (Aw,As)
* Arid climates (B)
Desert (Bwh) Semi-Arid (BS..)
Matthias Lüdeke
* Temperate rain climates (C) Humid/subtropical (Cfa, Cwa) Oceanic (Cfb, Cwb, Cfc) Mediterranean (Csa, Csb)
* Boreal forest and snow climates (D)Humid continental (Df/w,a/b) · Subarctic (Df/w,c,d)·Mediterranean continental (Dsa/b) . Other cont. (Dsc/d)
* Cold snow climates (E)
alpine (ETH) polar (EF) + ET(undra)
Matthias Lüdeke
* Tropical rain climates (A) – where the mean temperature of the coldest monthexceeds +18.0°C.
* Arid climates (B) – are defined as follows on the basis of the average annualprecipitation sum R (cm) and the annual mean temperature T (°C):R < 2T + 28 (where summer rain is dominating)R < 2T +14 (where no pronounced annual cycle is observed)R < 2T (where winter rain is dominating)
* Temperate rain climates (C) – where the mean temperature of the coldest monthis between –3.0°C and +18.0°C.
* Boreal forest and snow climates (D) – are characterized by a mean temperatureof the warmest month exceeding 10.0°C and a mean temperature of the coldestmonth below –3.0°C.
* Cold snow climates (E) – are defined by a mean temperature of the warmestmonth below 10.0°C.
Matthias Lüdeke
Matthias Lüdeke
* Tropical rain climates (A)
Equatorial (Af) Monsoon(Am) Savanna (Aw,As)
Af: All twelve months have average precipitation of at least 60 mm
Am: driest month less than 60 mm, but more than (100 − [total annual precipitation in mm/25])
Aw: driest month less than 60 mm, but less than (100 − [total annual precipitation in mm/25])
Matthias Lüdeke
% Landfläche, die vom ent-sprechenden Köppen-typBedeckt ist (ohne Antarktis& Grönland), Beck et al., 2006
Distribution of Global Climate Classes (36d)Distribution of Global Climate Classes (36d)
Klima-ClusterungKohonen KarteJ. Kropp, 1999
SOMTOP vs BIOME
Biome model:Tropical dryforestSOMTOP: node17
Green:Green: Biome-ModelYellowYellow:: SOMTOPRed:Red: Coincidence
Kropp (1999)
Kropp & Schellnhuber (2007)
SOMTOP vs BIOME
Matthias Lüdeke
Genetische Klimaklassifikation nach Hendl, 1963/91
Matthias Lüdeke
Matthias Lüdeke
Vorhersage von Klimawandel-Wirkungen:
Welche Eigenschaften des zukünftigen Klimawandels können mit welcherSicherheit vorhergesagt werden?
Treiber: zukünftige anthropogene Treibhausgasemissionen (CO2, CH4, N2O etc.). - Hängen von politischen/wirtschaftlichen/sozialenEntwicklungen ab. Schwer vorherzusagen (Reflexivität: Vorhersagenüber zukünftige Entwicklungen beeinflussen diese möglicherweise!) -> plausible Szenarien (z.B. die SRES Szenarien)
Globale Strahlungsbilanz-Rechnungen -> ∆Tglobal (hohe Konvergenz seitArrhenius)
AOGCM-Rechnungen: ständige Annäherung an die Notwendigkeiten von Impact-Rechnungen
SRES, IPCC
Matthias Lüdeke
Sind Emissionen und CO2-Concentration trivial vermittelt?
Matthias Lüdeke
Matthias Lüdeke
Vorhersage von Klimawandel-Wirkungen:
Welche Eigenschaften des zukünftigen Klimawandels können mit welcherSicherheit vorhergesagt werden?
Treiber: zukünftige anthropogene Treibhausgasemissionen (CO2, CH4, N2O etc.). - Hängen von politischen/wirtschaftlichen/sozialenEntwicklungen ab. Schwer vorherzusagen (Reflexivität: Vorhersagenüber zukünftige Entwicklungen beeinflussen diese möglicherweise!) -> plausible Szenarien (z.B. die SRES Szenarien)
Globale Strahlungsbilanz-Rechnungen -> ∆Tglobal (hohe Konvergenz seitArrhenius)
AOGCM-Rechnungen: ständige Annäherung an die Notwendigkeiten von Impact-Rechnungen
Matthias Lüdeke
Stefan-Boltzmann:Langwellige Abstrahlung (mit T4), [CO2] modifiziert = Kurzwellige (Sonnen-) Einstrahlung, Albedo-modifiziert
Matthias Lüdeke
Matthias Lüdeke
AR4, WG1 (2007):
“… the global averagesurface warming following a doubling of carbondioxide concentrations. It is likely to be in the range2°C to 4.5°C with a best estimate of about 3°C, and is very unlikely to be less than 1.5°C. Values substantially higher than 4.5°C cannot be excluded, but agreement of models with observations is not as good for those values
Matthias Lüdeke
Vorhersage von Klimawandel-Wirkungen:
Welche Eigenschaften des zukünftigen Klimawandels können mit welcherSicherheit vorhergesagt werden?
Treiber: zukünftige anthropogene Treibhausgasemissionen (CO2, CH4, N2O etc.). - Hängen von politischen/wirtschaftlichen/sozialenEntwicklungen ab. Schwer vorherzusagen (Reflexivität: Vorhersagenüber zukünftige Entwicklungen beeinflussen diese möglicherweise!) -> plausible Szenarien (z.B. die SRES Szenarien)
Globale Strahlungsbilanz-Rechnungen -> ∆Tglobal (hohe Konvergenz seitArrhenius)
AOGCM-Rechnungen: ständige Annäherung an die Notwendigkeiten von Impact-Rechnungen
Matthias Lüdeke
Matthias Lüdeke
Matthias Lüdeke
Matthias Lüdeke
Matthias Lüdeke
Matthias Lüdeke