scholarly journals The Key Role of Coupled Chemistry–Climate Interactions in Tropical Stratospheric Temperature Variability

2020 ◽  
Vol 33 (17) ◽  
pp. 7619-7629
Author(s):  
Simchan Yook ◽  
David W. J. Thompson ◽  
Susan Solomon ◽  
Seo-Yeon Kim
Keyword(s):  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Stratospheric Temperature ◽  
Climate Interactions ◽  
Free Running ◽  
Polar Stratosphere ◽  
Fully Coupled ◽  
Do So

AbstractThe purpose of this study is to quantify the effects of coupled chemistry–climate interactions on the amplitude and structure of stratospheric temperature variability. To do so, the authors examine two simulations run on version 4 of the Whole Atmosphere Coupled Climate Model (WACCM): a “free-running” simulation that includes fully coupled chemistry–climate interactions and a “specified chemistry” version of the model forced with prescribed climatological-mean chemical composition. The results indicate that the inclusion of coupled chemistry–climate interactions increases the internal variability of temperature by a factor of ~2 in the lower tropical stratosphere and—to a lesser extent—in the Southern Hemisphere polar stratosphere. The increased temperature variability in the lower tropical stratosphere is associated with dynamically driven ozone–temperature feedbacks that are only included in the coupled chemistry simulation. The results highlight the fundamental role of two-way feedbacks between the atmospheric circulation and chemistry in driving climate variability in the lower stratosphere.

scholarly journals Cross-validation of bias-corrected climate simulations is misleading

2018 ◽  
Vol 22 (9) ◽  
pp. 4867-4873 ◽  
Author(s):  
Douglas Maraun ◽  
Martin Widmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Cross Validation ◽  
Climate Model ◽  
False Negative ◽  
Internal Variability ◽  
Validation Period ◽  
Climate Simulations ◽  
Free Running ◽  
The Difference

Abstract. We demonstrate both analytically and with a modelling example that cross-validation of free-running bias-corrected climate change simulations against observations is misleading. The underlying reasoning is as follows: a cross-validation can have in principle two outcomes. A negative (in the sense of not rejecting a null hypothesis), if the residual bias in the validation period after bias correction vanishes; and a positive, if the residual bias in the validation period after bias correction is large. It can be shown analytically that the residual bias depends solely on the difference between the simulated and observed change between calibration and validation periods. This change, however, depends mainly on the realizations of internal variability in the observations and climate model. As a consequence, the outcome of a cross-validation is also dominated by internal variability, and does not allow for any conclusion about the sensibility of a bias correction. In particular, a sensible bias correction may be rejected (false positive) and a non-sensible bias correction may be accepted (false negative). We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations against observations. Instead, one should evaluate non-calibrated temporal, spatial and process-based aspects.

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 Global modeling of fungal spores with the EMAC chemistryclimate model: uncertainties in emission parametrizations and observations

2019 ◽  
Author(s):  
Meryem Tanarhte ◽  
Sara Bacer ◽  
Susannah M. Burrows ◽  
J. Alex Huffman ◽  
Kyle M. Pierce ◽  
...  
Keyword(s):  
Urban Areas ◽  
Climate Model ◽  
Strong Dependence ◽  
Fungal Spores ◽  
Fungal Spore ◽  
Specific Humidity ◽  
Area Index ◽  
Climate Interactions

Abstract. Primary biological aerosol particles (PBAPs) may impact human health and aerosol-cloud-climate interactions. The role of PBAPs in the earth system is associated with large uncertainties, for example of source estimates and the atmospheric lifetime. We used a chemistry-climate model to simulate PBAPs in the atmosphere including bacteria and fungal spores. Three fungal spore emission parameterizations have been evaluated against an updated set of spore counts synthesized from observations reported in the literature. The comparison indicates an optimal fit for the emission parameterization proposed by Heald and Spracklen (2009) and adapted by Hoose et al. (2010) for particle sizes of 5 µm or 3 µm, although the model still overpredicts PBAP concentrations in some locations. The correlations between the spore count observations and meteorological parameters simulated by the model show a strong dependence on the leaf area index in non-urban areas and the specific humidity in urban areas. Additional evaluation was performed by comparing our combined bacteria and fungal spore simulations to a global dataset of fluorescent biological aerosol particle (FBAP) concentrations. The model predicts the total sum of measured PBAP concentrations relatively well, typically within a factor of two of FBAP. Further, the modeled fungal spore results deviate from the FBAP concentrations when used as a rough proxy for spores, depending on the particle size used in the parametrization. Uncertainties related to technical aspects of the FBAP and direct-counting spore measurements challenge the ability to further refine quantitative comparison on this scale. Additional long-term data of better quality are needed to improve emission parameterizations.

A Gaussian process emulator for simulating ice sheet-climate interactions on a multi-million year timescale

2020 ◽  
Author(s):  
Jonas Van Breedam ◽  
Philippe Huybrechts ◽  
Michel Crucifix
Keyword(s):  
Gaussian Process ◽  
Climate Model ◽  
Ice Sheet ◽  
Climate System ◽  
Lapse Rate ◽  
Coupled Models ◽  
Climate Interactions ◽  
Coupling Time ◽  
Fully Coupled ◽  
Gaussian Process Emulator

<p>Fully coupled state-of-the-art Atmosphere-Ocean General Circulation Models are the best tool to investigate feedbacks between the different components of the climate system on a decadal to centennial timescale. On millennial to multi-millennial timescales, Earth System Models of Intermediate Complexity are used to explore the feedbacks in the climate system between the ice sheets, the atmosphere and the ocean. Those fully coupled models, even at coarser resolution, are computationally very expensive and other techniques have been proposed to simulate ice sheet-climate interactions on a million-year timescale. The asynchronous coupling technique proposes to run a climate model for a few decades and subsequently an ice sheet model for a few millennia. Another, more efficient method is the use of a matrix look-up table where climate model runs are performed for end-members and intermediate climatic states are linearly interpolated.</p><p>In this study, a novel coupling approach is presented where a Gaussian Process emulator applied to the climate model HadSM3 is coupled to the ice sheet model AISMPALEO. We have tested the sensitivity of the formulation of the ice sheet parameter and of the coupling time to the evolution of the ice sheet over time. Additionally, we used different lapse rate adjustments between the relatively coarse climate model and the much finer ice sheet model topography. It is shown that the ice sheet evolution over a million year timescale is strongly sensitive to the choice of the coupling time and to the implementation of the lapse rate adjustment. With the new coupling procedure, we provide a more realistic and computationally efficient framework for ice sheet-climate interactions on a multi-million year timescale.</p><p> </p>

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 Development and basic evaluation of a prognostic aerosol scheme (v1) in the CNRM Climate Model CNRM-CM6

2015 ◽  
Vol 8 (3) ◽  
pp. 501-531 ◽  
Author(s):  
M. Michou ◽  
P. Nabat ◽  
D. Saint-Martin
Keyword(s):  
Climate Model ◽  
Correlation Coefficients ◽  
Internal Variability ◽  
Forecast Model ◽  
Data Sets ◽  
Deep Blue ◽  
Free Running ◽  
Aerosol Module ◽  
The Impact ◽  
Climate Studies

Abstract. We have implemented a prognostic aerosol scheme (v1) in CNRM-CM6, the climate model of CNRM-GAME and CERFACS, based upon the GEMS/MACC aerosol module of the ECMWF operational forecast model. This scheme describes the physical evolution of the five main types of aerosols, namely black carbon, organic matter, sulfate, desert dust and sea salt. In this work, we describe the characteristics of our implementation, for instance, taking into consideration a different dust scheme or boosting biomass burning emissions by a factor of 2, as well as the evaluation performed on simulation output. The simulations consist of time slice simulations for 2004 conditions and transient runs over the 1993–2012 period, and are either free-running or nudged towards the ERA-Interim Reanalysis. Evaluation data sets include several satellite instrument AOD (aerosol optical depth) products (i.e., MODIS Aqua classic and Deep-Blue products, MISR and CALIOP products), as well as ground-based AERONET data and the derived AERONET climatology, MAC-v1. The uncertainty of aerosol-type seasonal AOD due to model internal variability is low over large parts of the globe, and the characteristics of a nudged simulation reflect those of a free-running simulation. In contrast, the impact of the new dust scheme is large, with modelled dust AODs from simulations with the new dust scheme close to observations. Overall patterns and seasonal cycles of the total AOD are well depicted with, however, a systematic low bias over oceans. The comparison to the fractional MAC-v1 AOD climatology shows disagreements mostly over continents, while that to AERONET sites outlines the capability of the model to reproduce monthly climatologies under very diverse dominant aerosol types. Here again, underestimation of the total AOD appears in several cases, sometimes linked to insufficient efficiency of the aerosol transport away from the aerosol sources. Analysis of monthly time series at 166 AERONET sites shows, in general, correlation coefficients higher than 0.5 and lower model variance than observed. A large interannual variability can also be seen in the CALIOP vertical profiles over certain regions of the world. Overall, this prognostic aerosol scheme appears promising for aerosol-climate studies. There is room, however, for implementing more complex parameterisations in relation to aerosols.

scholarly journals The coupled atmosphere–chemistry–ocean model SOCOL-MPIOM

2014 ◽  
Vol 7 (5) ◽  
pp. 2157-2179 ◽  
Author(s):  
S. Muthers ◽  
J. G. Anet ◽  
A. Stenke ◽  
C. C. Raible ◽  
E. Rozanov ◽  
...  
Keyword(s):  
Climate Model ◽  
Land Use Changes ◽  
Surface Air Temperature ◽  
Polar Vortex ◽  
Ocean Model ◽  
Boreal Winter ◽  
Data Sets ◽  
Polar Regions ◽  
Stratospheric Temperature ◽  
Climate Interactions

Abstract. The newly developed atmosphere–ocean–chemistry–climate model SOCOL-MPIOM is presented by demonstrating the influence of chemistry–climate interactions on the climate state and the variability. Therefore, we compare pre-industrial control simulations with (CHEM) and without (NOCHEM) interactive chemistry. In general, the influence of the chemistry on the mean state and the variability is small and mainly restricted to the stratosphere and mesosphere. The atmospheric dynamics mainly differ in polar regions, with slightly stronger polar vortices in the austral and boreal winter, respectively. The strengthening of the vortex is related to larger stratospheric temperature gradients, which are attributed to a parameterisation of the absorption of ozone and oxygen in different wavelength intervals, which is considered in the version with interactive chemistry only. A second reason for the temperature differences between CHEM and NOCHEM is related to diurnal variations in the ozone concentrations in the higher atmosphere, which are missing in NOCHEM. Furthermore, stratospheric water vapour concentrations substantially differ between the two experiments, but their effect on temperature is small. In both setups, the simulated intensity and variability of the northern polar vortex is inside the range of present-day observations. Additionally, the performance of SOCOL-MPIOM under changing external forcings is assessed for the period 1600–2000 using an ensemble of simulations. In the industrial period from 1850 onward SOCOL-MPIOM overestimates the global mean surface air temperature increase in comparison to observational data sets. Sensitivity simulations show that this overestimation can be attributed to a combination of factors: the solar forcing reconstruction, the simulated ozone changes, and incomplete aerosol effects and land use changes.

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 Climate versus emission drivers of methane lifetime from 1860–2100

2012 ◽  
Vol 12 (7) ◽  
pp. 18067-18105 ◽  
Author(s):  
J. G. John ◽  
A. M. Fiore ◽  
V. Naik ◽  
L. W. Horowitz ◽  
J. P. Dunne
Keyword(s):  
Climate Warming ◽  
Climate Model ◽  
Climate Forcing ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Atmospheric Methane ◽  
Future Evolution ◽  
The Individual ◽  
Future Work ◽  
Fully Coupled

Abstract. With a more-than-doubling in the atmospheric abundance of the potent greenhouse gas methane (CH4) since preindustrial times, and indications of renewed growth following a leveling off in recent years, questions arise as to future trends and resulting climate and public health impacts from continued growth without mitigation. Changes in atmospheric methane lifetime are determined by factors which regulate the abundance of OH, the primary methane removal mechanism, including changes in CH4 itself. We investigate the role of emissions of short-lived species and climate in determining the evolution of tropospheric methane lifetime in a suite of historical (1860–2005) and Representative Concentration Pathway (RCP) simulations (2006–2100), conducted with the Geophysical Fluid Dynamics Laboratory (GFDL) fully coupled chemistry-climate model (CM3). From preindustrial to present, CM3 simulates an overall 5% increase in CH4 lifetime due to a doubling of the methane burden which offsets coincident increases in nitrogen oxide (NOx) emissions. Over the last two decades, however, the methane lifetime declines steadily, coinciding with the most rapid climate warming and observed slow-down in CH4 growth rates, reflecting a possible negative feedback through the CH4 sink. The aerosol indirect effect plays a significant role in the CM3 climate and thus in the future evolution of the methane lifetime, due to the rapid projected decline of aerosols under all four RCPs. In all scenarios, the methane lifetime decreases (by 5–13%) except for the most extreme warming case (RCP8.5), where it increases by 4% due to the near-doubling of the CH4 abundance, reflecting a positive feedback on the climate system. In the RCP4.5 scenario changes in short-lived climate forcing agents reinforce climate warming and enhance OH, leading to a more-than-doubling of the decrease in methane lifetime from 2006 to 2100 relative to a simulation in which only well-mixed greenhouse gases are allowed to change along the RCP4.5 scenario (13% vs. 5%) Future work should include process-based studies to better understand and elucidate the individual mechanisms controlling methane lifetime.

scholarly journals Investigating the Roles of External Forcing and Ocean Circulation on the Atlantic Multidecadal SST Variability in a Large Ensemble Climate Model Hierarchy

2021 ◽  
pp. 1-51
Author(s):  
Lisa N. Murphy ◽  
Jeremy M. Klavans ◽  
Amy C. Clement ◽  
Mark A. Cane
Keyword(s):  
Spatial Pattern ◽  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Model ◽  
Time History ◽  
Internal Variability ◽  
External Forcing ◽  
Large Ensemble ◽  
The North

AbstractThis paper attempts to enhance our understanding of the causes of Atlantic Multidecadal Variability, the AMV. Following the literature, we define the AMV as the SST averaged over the North Atlantic basin, linearly detrended and low-pass filtered. There is an ongoing debate about the drivers of the AMV, which include internal variability generated from the ocean or atmosphere (or both), and external radiative forcing. We test the role of these factors in explaining the time history, variance, and spatial pattern of the AMV using a 41-member ensemble from a fully coupled version of CESM and a 10-member ensemble of the CESM atmosphere coupled to a slab ocean. The large ensemble allows us to isolate the role of external forcing versus internal variability, and the model differences allow us to isolate the role of coupled ocean circulation. Both with and without coupled ocean circulation, external forcing explains more than half of the variance of the observed AMV time series, indicating its important role in simulating the 20th century AMV phases. In this model the net effect of ocean processes is to reduce the variance of the AMV. Dynamical ocean coupling also reduces the ability of the model to simulate the characteristic spatial pattern of the AMV, but forcing has little impact on the pattern. Historical forcing improves the time history and variance of the AMV simulation, whilst the more realistic ocean representation reduces the variance below that observed and lowers the correlation with observations.

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