scholarly journals Influence of solar variability, CO<sub>2</sub> and orbital forcing during the last millennium in the IPSLCM4 model

2010 ◽  
Vol 6 (2) ◽  
pp. 421-460
Author(s):  
J. Servonnat ◽  
P. Yiou ◽  
M. Khodri ◽  
D. Swingedouw ◽  
S. Denvil
Keyword(s):  
Climate Model ◽  
Internal Variability ◽  
Temperature Reconstruction ◽  
Temperature Variability ◽  
Ice Age ◽  
Last Millennium ◽  
Orbital Forcing ◽  
Temperature Reconstructions ◽  
Temperature Signal ◽  
The Impact

Abstract. Studying the climate of the last millennium gives the possibility to deal with a relatively well-documented climate essentially driven by natural forcings. We have performed two simulations with the IPSLCM4 climate model to evaluate the impact of Total Solar Irradiance (TSI), CO2 and orbital forcing on secular temperature variability during the preindustrial part of the last millennium. The Northern Hemisphere (NH) temperature of the simulation reproduces the amplitude of the NH temperature reconstructions over the last millennium. Using a linear statistical decomposition we evaluated that TSI and CO2 have similar contributions to secular temperature variability between 1425 and 1850 AD. They generate a temperature minimum comparable to the Little Ice Age shown by the temperature reconstructions. Solar forcing explains ~80% of the NH temperature variability during the first part of the millennium (1000–1425 AD) including the Medieval Climate Anomaly (MCA). It is responsible for a warm period which occurs two centuries later than in the reconstructions. This mismatch implies that the secular variability during the MCA is not fully explained by the response of the model to the TSI reconstruction. With a signal-noise ratio (SNR) estimate we found that the temperature signal of the forced simulation is significantly different from internal variability over area wider than ~5.106 km2, i.e. approximately the extent of Europe. Orbital forcing plays a significant role in latitudes higher than 65° N in summer and supports the conclusions of a recent study on an Arctic temperature reconstruction over past two millennia. The forced variability represents at least half of the temperature signal on only ~30% of the surface of the globe. The study of the SNR and local impacts of the forcings suggests that individual temperature reconstructions taken from random location around the Globe are potentially weakly affected by a linear response to external forcings.

scholarly journals Influence of solar variability, CO<sub>2</sub> and orbital forcing between 1000 and 1850 AD in the IPSLCM4 model

2010 ◽  
Vol 6 (4) ◽  
pp. 445-460 ◽  
Author(s):  
J. Servonnat ◽  
P. Yiou ◽  
M. Khodri ◽  
D. Swingedouw ◽  
S. Denvil
Keyword(s):  
Climate Model ◽  
Internal Variability ◽  
Temperature Reconstruction ◽  
Temperature Variability ◽  
Ice Age ◽  
Last Millennium ◽  
Orbital Forcing ◽  
Temperature Reconstructions ◽  
Temperature Signal ◽  
The Impact

Abstract. Studying the climate of the last millennium gives the possibility to deal with a relatively well-documented climate essentially driven by natural forcings. We have performed two simulations with the IPSLCM4 climate model to evaluate the impact of Total Solar Irradiance (TSI), CO2 and orbital forcing on secular temperature variability during the preindustrial part of the last millennium. The Northern Hemisphere (NH) temperature of the simulation reproduces the amplitude of the NH temperature reconstructions over the last millennium. Using a linear statistical decomposition we evaluated that TSI and CO2 have similar contributions to secular temperature variability between 1425 and 1850 AD. They generate a temperature minimum comparable to the Little Ice Age shown by the temperature reconstructions. Solar forcing explains ~80% of the NH temperature variability during the first part of the millennium (1000–1425 AD) including the Medieval Climate Anomaly (MCA). It is responsible for a warm period which occurs two centuries later than in the reconstructions. This mismatch implies that the secular variability during the MCA is not fully explained by the response of the model to the TSI reconstruction. With a signal-noise ratio (SNR) estimate we found that the temperature signal of the forced simulation is significantly different from internal variability over area wider than ~5.106 km2, i.e. approximately the extent of Europe. Orbital forcing plays a significant role in latitudes higher than 65° N in summer and supports the conclusions of a recent study on an Arctic temperature reconstruction over past two millennia. The forced variability represents at least half of the temperature signal on only ~30% of the surface of the globe. This study suggests that regional reconstructions of the temperature between 1000 and 1850 AD are likely to show weak signatures of solar, CO2 and orbital forcings compared to internal variability.

scholarly journals 1200 years of warm-season temperature variability in central Scandinavia inferred from tree-ring density

2016 ◽  
Vol 12 (6) ◽  
pp. 1297-1312 ◽  
Author(s):  
Peng Zhang ◽  
Hans W. Linderholm ◽  
Björn E. Gunnarson ◽  
Jesper Björklund ◽  
Deliang Chen
Keyword(s):  
Tree Ring ◽  
Regional Differences ◽  
Low Frequency ◽  
Warm Season ◽  
Local Environment ◽  
Temperature Variability ◽  
Ice Age ◽  
Last Millennium ◽  
Ring Density ◽  
Temperature Reconstructions

Abstract. Despite the emergence of new high-resolution temperature reconstructions around the world, only a few cover the Medieval Climate Anomaly (MCA). Here we present C-Scan, a new Scots pine tree-ring density-based reconstruction of warm-season (April–September) temperatures for central Scandinavia back to 850 CE, extending the previous reconstruction by 250 years. C-Scan is based on samples collected in a confined mountain region, adjusted for their differences in altitude and local environment, and standardised using the new RSFi algorithm to preserve low-frequency signals. In C-Scan, the warm peak of MCA occurs ca. 1000–1100 CE, and the Little Ice Age (LIA) between 1550 and 1900 CE. Moreover, during the last millennium the coldest decades are found around 1600 CE, and the warmest 10 and 30 years occur in the most recent century. By comparing C-Scan with other millennium-long temperature reconstructions from Fennoscandia, regional differences in multi-decadal temperature variability, especially during the warm period of the last millennium are revealed. Although these differences could be due to methodological reasons, they may indicate asynchronous warming patterns across Fennoscandia. Further investigation of these regional differences and the reasons and mechanisms behind them are needed.

scholarly journals A 368-year maximum temperature reconstruction based on tree-ring data in the northwestern Sichuan Plateau (NWSP), China

2016 ◽  
Vol 12 (7) ◽  
pp. 1485-1498 ◽  
Author(s):  
Liangjun Zhu ◽  
Yuandong Zhang ◽  
Zongshan Li ◽  
Binde Guo ◽  
Xiaochun Wang
Keyword(s):  
Tree Ring ◽  
Land Surface ◽  
Temperature Reconstruction ◽  
Temperature Variability ◽  
Ice Age ◽  
Maximum Temperature ◽  
Tree Ring Data ◽  
The Mean ◽  
Extreme Cold ◽  
The 19Th Century

Abstract. We present a reconstruction of July–August mean maximum temperature variability based on a chronology of tree-ring widths over the period AD 1646–2013 in the northern part of the northwestern Sichuan Plateau (NWSP), China. A regression model explains 37.1 % of the variance of July–August mean maximum temperature during the calibration period from 1954 to 2012. Compared with nearby temperature reconstructions and gridded land surface temperature data, our temperature reconstruction had high spatial representativeness. Seven major cold periods were identified (1708–1711, 1765–1769, 1818–1821, 1824–1828, 1832–1836, 1839–1842, and 1869–1877), and three major warm periods occurred in 1655–1668, 1719–1730, and 1858–1859 from this reconstruction. The typical Little Ice Age climate can also be well represented in our reconstruction and clearly ended with climatic amelioration at the late of the 19th century. The 17th and 19th centuries were cold with more extreme cold years, while the 18th and 20th centuries were warm with less extreme cold years. Moreover, the 20th century rapid warming was not obvious in the NWSP mean maximum temperature reconstruction, which implied that mean maximum temperature might play an important and different role in global change as unique temperature indicators. Multi-taper method (MTM) spectral analysis revealed significant periodicities of 170-, 49–114-, 25–32-, 5.7-, 4.6–4.7-, 3.0–3.1-, 2.5-, and 2.1–2.3-year quasi-cycles at a 95 % confidence level in our reconstruction. Overall, the mean maximum temperature variability in the NWSP may be associated with global land–sea atmospheric circulation (e.g., ENSO, PDO, or AMO) as well as solar and volcanic forcing.

scholarly journals Understanding drivers of glacier-length variability over the last millennium

2021 ◽  
Vol 15 (3) ◽  
pp. 1645-1662
Author(s):  
Alan Huston ◽  
Nicholas Siler ◽  
Gerard H. Roe ◽  
Erin Pettit ◽  
Nathan J. Steiger
Keyword(s):  
Climate Variability ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Internal Variability ◽  
Forced Response ◽  
Last Millennium ◽  
External Forcing ◽  
Climate History ◽  
Temperature And Precipitation ◽  
Glacier Length

Abstract. Changes in glacier length reflect the integrated response to local fluctuations in temperature and precipitation resulting from both external forcing (e.g., volcanic eruptions or anthropogenic CO2) and internal climate variability. In order to interpret the climate history reflected in the glacier moraine record, the influence of both sources of climate variability must therefore be considered. Here we study the last millennium of glacier-length variability across the globe using a simple dynamic glacier model, which we force with temperature and precipitation time series from a 13-member ensemble of simulations from a global climate model. The ensemble allows us to quantify the contributions to glacier-length variability from external forcing (given by the ensemble mean) and internal variability (given by the ensemble spread). Within this framework, we find that internal variability is the predominant source of length fluctuations for glaciers with a shorter response time (less than a few decades). However, for glaciers with longer response timescales (more than a few decades) external forcing has a greater influence than internal variability. We further find that external forcing also dominates when the response of glaciers from widely separated regions is averaged. Single-forcing simulations indicate that, for this climate model, most of the forced response over the last millennium, pre-anthropogenic warming, has been driven by global-scale temperature change associated with volcanic aerosols.

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

scholarly journals Simulated climate variability in the region of Rapa Nui during the last millennium

2011 ◽  
Vol 7 (1) ◽  
pp. 381-395 ◽  
Author(s):  
C. Junk ◽  
M. Claussen
Keyword(s):  
Large Scale ◽  
Vegetation Change ◽  
Climate Model ◽  
Volcanic Eruptions ◽  
Easter Island ◽  
Ice Age ◽  
Vegetation Changes ◽  
Last Millennium ◽  
Climate Data ◽  
Climatic Fluctuations

Abstract. Easter Island, an isolated island in the Southeast Pacific, was settled by the Polynesians probably between 600 and 1200 AD and discovered by the Europeans in 1722 AD. While the Polynesians presumably found a profuse palm woodland on Easter Island, the Europeans faced a landscape dominated by grassland. Scientists have examined potential anthropogenic, biological and climatic induced vegetation changes on Easter Island. Here, we analyze observational climate data for the last decades and climate model results for the period 800–1750 AD to explore potential causes for a climatic-induced vegetation change. A direct influence of the ENSO phenomenon on the climatic parameters of Easter Island could not be found in the model simulations. Furthermore, strong climatic trends from a warm Medieval Period to a Little Ice Age or rapid climatic fluctuations due to large volcanic eruptions were not verifiable for the Easter Island region, although they are detectable in the simulations for many regions world wide. Hence we tentatively conclude that large-scale climate changes in the oceanic region around Easter Island might be too small to explain strong vegetation changes on the island over the last millennium.

scholarly journals Exploring the uncertainties in the aviation soot–cirrus effect

2021 ◽  
Vol 21 (23) ◽  
pp. 17267-17289
Author(s):  
Mattia Righi ◽  
Johannes Hendricks ◽  
Christof Gerhard Beer
Keyword(s):  
Radiative Forcing ◽  
Climate Model ◽  
Internal Variability ◽  
Reanalysis Data ◽  
Ice Nucleation ◽  
Cirrus Clouds ◽  
Model Studies ◽  
Model Dynamics ◽  
Analogous Model ◽  
The Impact

Abstract. A global aerosol–climate model, including a two-moment cloud microphysical scheme and a parametrization for aerosol-induced ice formation in cirrus clouds, is applied in order to quantify the impact of aviation soot on natural cirrus clouds. Several sensitivity experiments are performed to assess the uncertainties in this effect related to (i) the assumptions on the ice nucleation abilities of aviation soot, (ii) the representation of vertical updrafts in the model, and (iii) the use of reanalysis data to relax the model dynamics (the so-called nudging technique). Based on the results of the model simulations, a radiative forcing from the aviation soot–cirrus effect in the range of −35 to 13 mW m−2 is quantified, depending on the assumed critical saturation ratio for ice nucleation and active fraction of aviation soot but with a confidence level below 95 % in several cases. Simple idealized experiments with prescribed vertical velocities further show that the uncertainties on this aspect of the model dynamics are critical for the investigated effect and could potentially add a factor of about 2 of further uncertainty to the model estimates of the resulting radiative forcing. The use of the nudging technique to relax model dynamics is proved essential in order to identify a statistically significant signal from the model internal variability, while simulations performed in free-running mode and with prescribed sea-surface temperatures and sea-ice concentrations are shown to be unable to provide robust estimates of the investigated effect. A comparison with analogous model studies on the aviation soot–cirrus effect show a very large model diversity, with a conspicuous lack of consensus across the various estimates, which points to the need for more in-depth analyses on the roots of such discrepancies.

scholarly journals Chemistry–climate interactions of aerosol nitrate from lightning

2017 ◽  
Vol 17 (2) ◽  
pp. 1125-1142 ◽  
Author(s):  
Holger Tost
Keyword(s):  
Climate Model ◽  
Statistical Significance ◽  
Aerosol Particles ◽  
Internal Variability ◽  
Aerosol Size Distribution ◽  
Upper Troposphere ◽  
Uncertainty Range ◽  
Mixing Ratios ◽  
Microphysical Properties ◽  
The Impact

Abstract. Lightning represents one of the dominant emission sources for NOx in the troposphere. The direct release of oxidised nitrogen in the upper troposphere does not only affect ozone formation, but also chemical and microphysical properties of aerosol particles in this region. This study investigates the direct impact of LNOx emissions on upper-tropospheric nitrate using a global chemistry climate model. The simulation results show a substantial influence of the lightning emissions on the mixing ratios of nitrate aerosol in the upper troposphere of more than 50 %. In addition to the impact on nitrate, lightning substantially affects the oxidising capacity of the atmosphere with substantial implications for gas-phase sulfate formation and new particle formation in the upper troposphere. In conjunction with the condensation of nitrates, substantial differences in the aerosol size distribution occur in the upper troposphere as a consequence of lightning. This has implications for the extinction properties of the aerosol particles and for the cloud optical properties. While the extinction is generally slightly enhanced due to the LNOx emissions, the response of the clouds is ambiguous due to compensating effects in both liquid and ice clouds. Resulting shortwave flux perturbations are of   ∼ −100 mW m−2 as determined from several sensitivity scenarios, but an uncertainty range of almost 50 % has to be defined due to the large internal variability of the system and the uncertainties in the multitude of involved processes. Despite the clear statistical significance of the influence of lightning on the nitrate concentrations, the robustness of the findings gradually decreases towards the determination of the radiative flux perturbations.

scholarly journals Large-scale temperature response to external forcing in simulations and reconstructions of the last millennium

2013 ◽  
Vol 9 (1) ◽  
pp. 393-421 ◽  
Author(s):  
L. Fernández-Donado ◽  
J. F. González-Rouco ◽  
C. C. Raible ◽  
C. M. Ammann ◽  
D. Barriopedro ◽  
...  
Keyword(s):  
Internal Variability ◽  
Ice Age ◽  
Future Climate Change ◽  
Last Millennium ◽  
External Forcing ◽  
Transient Climate Response ◽  
Temperature Changes ◽  
Model Simulations ◽  
Major Player ◽  
Intercomparison Project

Abstract. Understanding natural climate variability and its driving factors is crucial to assessing future climate change. Therefore, comparing proxy-based climate reconstructions with forcing factors as well as comparing these with paleoclimate model simulations is key to gaining insights into the relative roles of internal versus forced variability. A review of the state of modelling of the climate of the last millennium prior to the CMIP5–PMIP3 (Coupled Model Intercomparison Project Phase 5–Paleoclimate Modelling Intercomparison Project Phase 3) coordinated effort is presented and compared to the available temperature reconstructions. Simulations and reconstructions broadly agree on reproducing the major temperature changes and suggest an overall linear response to external forcing on multidecadal or longer timescales. Internal variability is found to have an important influence at hemispheric and global scales. The spatial distribution of simulated temperature changes during the transition from the Medieval Climate Anomaly to the Little Ice Age disagrees with that found in the reconstructions. Thus, either internal variability is a possible major player in shaping temperature changes through the millennium or the model simulations have problems realistically representing the response pattern to external forcing. A last millennium transient climate response (LMTCR) is defined to provide a quantitative framework for analysing the consistency between simulated and reconstructed climate. Beyond an overall agreement between simulated and reconstructed LMTCR ranges, this analysis is able to single out specific discrepancies between some reconstructions and the ensemble of simulations. The disagreement is found in the cases where the reconstructions show reduced covariability with external forcings or when they present high rates of temperature change.

scholarly journals On the Choice of Ensemble Mean for Estimating the Forced Signal in the Presence of Internal Variability

2018 ◽  
Vol 31 (14) ◽  
pp. 5681-5693 ◽  
Author(s):  
Leela M. Frankcombe ◽  
Matthew H. England ◽  
Jules B. Kajtar ◽  
Michael E. Mann ◽  
Byron A. Steinman
Keyword(s):  
Regional Differences ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Single Model ◽  
Sea Level Pressure ◽  
Model Simulations ◽  
Ensemble Mean ◽  
Climate Model Simulations ◽  
The Impact

Abstract In this paper we examine various options for the calculation of the forced signal in climate model simulations, and the impact these choices have on the estimates of internal variability. We find that an ensemble mean of runs from a single climate model [a single model ensemble mean (SMEM)] provides a good estimate of the true forced signal even for models with very few ensemble members. In cases where only a single member is available for a given model, however, the SMEM from other models is in general out-performed by the scaled ensemble mean from all available climate model simulations [the multimodel ensemble mean (MMEM)]. The scaled MMEM may therefore be used as an estimate of the forced signal for observations. The MMEM method, however, leads to increasing errors further into the future, as the different rates of warming in the models causes their trajectories to diverge. We therefore apply the SMEM method to those models with a sufficient number of ensemble members to estimate the change in the amplitude of internal variability under a future forcing scenario. In line with previous results, we find that on average the surface air temperature variability decreases at higher latitudes, particularly over the ocean along the sea ice margins, while variability in precipitation increases on average, particularly at high latitudes. Variability in sea level pressure decreases on average in the Southern Hemisphere, while in the Northern Hemisphere there are regional differences.

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