Earth and Life Institute Georges Lemaître Centre for Earth and Climate Research Université catholique de Louvain, Belgium Speleothems and Climate Models Qiuzhen YIN Summer School on Speleothem Science, Oxford, 23-29 August 2015
Outline Climate system Climate forcings Astronomical parameters and insolation Climate models Applications of climate modelling in paleoclimate (including speleothem) research
Climate system: Atmosphere, hydrosphere, cryosphere, biosphere, lithosphere, and their interactions. (IPCC, 2007)
External forcing Climate forcings Solar radiation (solar output, interplanetary medium, astronomical theory) In models, depending on their characteristic time scale, some components are kept constant (not interactively coupled to the other components of the climate model) and as such also called forcings (sometimes referred to as internal forcings): Volcanic eruptions, plate tectonics Human-induced changes (eg. CO2 increase, land surface change) Ice sheets Carbon cycle Vegetation Ocean circulation If interactive, these are acting as feedbacks.
Astronomical parameters and characteristics of insolation
Trenberth et al. (2009)
Latitudinal-seasonal distribution of insolation (Wm -2 ) at the top of the atmosphere Daily insolation at present-day (Berger, 1978)
Berger (1978) 400ka, 100ka 19ka, 23ka 41ka
Insolation from North to South For a given day, variations for each latitude are in phase, Berger and Pestiaux, 1984. in Milankovitch and Climate (Berger et al eds.)
Insolation from January to December For a given latitude, variations are out of phase by ~2 ka from one month to the next. Berger and Pestiaux, 1984. in Milankovitch and Climate (Berger et al eds.)
Daily insolation (irradiance, Wm-2) is mainly a function of precession. Insolation integrated over any time interval (irradiation, Jm-2) is only a function of obliquity. Summer irradiation Obliquity Insolation at summer solstice Precession Berger et al., 2010, QSR
Total annual irradiation Anti-phase between high and low latitudes; Obliquity signal vanishes at 44 N and 44 S where the only signal is from eccentricity despite very small variation. Berger et al., 2010, QSR
Latitudinal insolation gradient: a function of eccentricity/precession or obliquity depending on season Austral winter (May-September) Austral summer (October-April) Yin, 2013, Nature
Climate models a mathematical representation of the climate system based on physical, biological and chemical principles; attempt to simulate the many processes that produce climate; a simplification of the real climate system.
Model development Physical, chemical, biological principles Uncertainties Approximations, parameterizations Numerical resolution Uncertainties Climate forcings Boundary conditions Inital conditions Climate model Results
A simplified representation of part of the domain of a 3-D climate model Figure source: Goosse et al, http://www.climate.be/textbook
Type of models EBMs: Energy Balance Models EMICs: Earth system Models of Intermediate Complexity GCMs: General Circulation Models Long+many simulations; Less computer resources More details; More computer resources All the model types can produce useful information on the behavior of the climate system. There is no perfect model. The best type of model to use depends on the scientific objective and question. Figure source: Goosse et al, http://www.climate.be/textbook
Model Validation and Evaluation A model is an approximation of the real world, so it will never match the observations exactly. It might have a good match at some places but a poor match at other places. Validation of a model is related to the purpose of model use and can only be partial. Some classical simulations to test climate models: Simulate the climate of recent decades Paleoclimate simulations (eg. last millennium, Holocene, LGM) Idealised test cases (eg. double CO2 experiments, water hosing experiments) Braconnot et al., 2012. Evaluation of climate models using palaeoclimatic data. Nature Clim Change 2, 417 424. Evaluation of climate simulations against paleo data shows that models reproduce the direction and large scale patterns of past changes in climate, but tend to underestimate the magnitude of regional changes. The improvement in data-model comparison requires the efforts of both data and model communities.
Reasons of Climate Modeling All models are wrong, but some models are useful. George Box Test the robustness of prevailing theory (eg. greenhouse warming, Milankovitch theory) Improve our knowledge of the most important characteristics of the climate system and of the causes of climate variations Explain past and present climate changes Predict future climate Direct field data collection Improve climatic interpretation of proxy records
Applications of Climate Modeling in Paleoclimate Research Example 1: Modeling the relative roles of insolation, CO 2 and astronomical parameters on interglacial climate Example 2: Model confirms and explains millennial-scale changes in speleothems Example 3: Combined climate-isotope modelling and climate-stalagmite modeling improve the climatic interpretation of stalagmite
CO2 China loess EDC T (oc) (ppmv) Interglacial diversity in time and space 280 240 MIS-1 5 7 9 11 MBE 13 15 17 19 CO2 Concentration Loulergue et al., 2008 200 4 0-4 -8 Antarctica temperature Jouzel et al., 2007 3 LR04 3.5 4 4.5 5 Fed/FeT (%) Global ice volume /deep-sea temperature Lisiecki and Raymo, 2005 30 25 20 East Asian summer monsoon Guo et al., 2009 15 0 100 200 300 400 500 600 700 800 Time (kyr BP)
Earth system Model of Intermediate complexity: LOVECLIM Goosse et al., 2010
Simulate peak interglacial climate in response to insolation and CO 2 MIS-1 5.5 7.5 9.3 11.3 13.1 15.1 17 19 21.3 6 123 239 329 405 501 575 696 780 858 12 127 242 335 409 506 579 693 788 Lisiecki and Raymo, 2005 Berger, 1978 262 287 262 298 282 240 250 251 235 865 Luthi et al., 2008
Modeling study separating the individual impact of insolation and CO 2 on the climates of the last nine interglacials shows that: CO 2 is dominant in southern high latitudes and global annual mean surface temperature, leading to clear MBE there. Insolation is dominant in northern high latitudes temperature, in monsoon precipitation and in vegetation, leading to no clear MBE. Yin and Berger, 2012, Clim Dyn
Different manifestation of MBE in proxy records MBE clear MBE not clear Number color: SST; Monsoon; Warmth; Vegetation 16 39 35 21 18 13 31 12 10 11 28 30 29 9 6 5 7 17 37 22 8 2 3 1 4 1 27 23 24 36 20 19 39 15 25 14 33 32 34 26 38
Transient simulations with time-varying insolation to investigate the impacts of precession and obliquity Dash horizontal line: Pre-Industrial level obliquity precession Yin and Berger, 2015, QSR Data: Berger, 1978
Regression Coefficient Regression Coefficient Regression Coefficient Precession VS. Obliquity Annual temperature Precession and obliquity have different weight on precipitation and temperature at different latitudes, partly explaining interglacial regional diversity in intensity, duration and phasing. Yin and Berger, 2015, QSR JJA temperature Annual precipitation
δ 18 O (%0) Precession control on NH and SH monsoon variations evidence from speleothem records Green: China speleothem δ 18 O (Wang et al, 2001, 2008; Cheng et al., 2009) Blue: Brazil speleothem δ 18 O (Cruz et al., 2005) Red: precession (Berger, 1978) Time (Ka BP) Speleothem records confirms the reliability of climate model in simulating monsoon dynamics at the astronomical time scale.
Example 2: Model confirms and explains millennial-scale changes in speleothems Abrupt changes during Heinrich stadial 3 and Greenland interstadials 3/4 Lewis et al., 2011, EPSL
The 8.2 ka event (Cheng et al., 2009, Geology) An abrupt cooling of 5-8 C in Greenland Intensification of zonal wind speed over Central America Weakening of the Asian monsoon Strengthening of the South American monsoon
Results from water-hosing experiments using the GFDL atmosphere-ocean coupled model (Zhang and Delworth, 2005) Annual sea surface temperature anomaly Abrupt changes discovered in different proxy records are in agreement with model results, demonstrating the reliability of climate model in reproducing global interconnection in rapid climate changes through ocean and atmosphere processes. Annual Precipitation (color shading) and sea level pressure (contour line) anomaly Summer precipitation (color shading) and wind (vector) anomaly
Example 3: Combined climate-isotope modelling and climate-stalagmite modelling help to improve the climatic interpretation of stalagmite
Summary Climate system is very complex. A small perturbation in forcings or in one component may lead to changes in the whole system. Climate model is a simplification of the real climate system. Uncertainties exist in model development and in experiment setup, therefore they exist in model results. High quality observations/reconstructions are necessary to test model results and to improve model performance. Climate models are very helpful for understanding proxy records. The best model to use depends on research objective. In paleoclimate study, modelling proxy becomes more and more necessary to allow direct comparison between proxy data and model results.