Estimating Central Equatorial Pacific SST Variability over the Past Millennium. Part I: Methodology and Validation

2013 ◽  
Vol 26 (7) ◽  
pp. 2302-2328 ◽  
Author(s):  
Julien Emile-Geay ◽  
Kimberly M. Cobb ◽  
Michael E. Mann ◽  
Andrew T. Wittenberg
Keyword(s):  
General Circulation ◽  
Low Frequency ◽  
General Circulation Models ◽  
Performance Assessments ◽  
The Past ◽  
Proxy Records ◽  
Sst Variability ◽  
Predictive Skill ◽  
Climate Signals ◽  
Past Millennium

Abstract Constraining the low-frequency (LF) behavior of general circulation models (GCMs) requires reliable observational estimates of LF variability. This two-part paper presents multiproxy reconstructions of Niño-3.4 sea surface temperature over the last millennium, applying two techniques [composite plus scale (CPS) and hybrid regularized expectation maximization (RegEM) truncated total least squares (TTLS)] to a network of tropical, high-resolution proxy records. This first part presents the data and methodology before evaluating their predictive skill using frozen network analysis (FNA) and pseudoproxy experiments. The FNA results suggest that about half of the Niño-3.4 variance can be reconstructed back to A.D. 1000, but they show little LF skill during certain intervals. More variance can be reconstructed in the interannual band where climate signals are strongest, but this band is affected by dating uncertainties (which are not formally addressed here). The CPS reliably estimates interannual variability, while LF fluctuations are more faithfully reconstructed with RegEM, albeit with inevitable variance loss. The RegEM approach is also tested on representative pseudoproxy networks derived from two millennium-long integrations of a coupled GCM. The pseudoproxy study confirms that reconstruction skill is significant in both the interannual and LF bands, provided that sufficient variance is exhibited in the target Niño-3.4 index. It also suggests that FNA severely underestimates LF skill, even when LF variability is strong, resulting in overly pessimistic performance assessments. The centennial-scale variance of the historical Niño-3.4 index falls somewhere between the two model simulations, suggesting that the network and methodology presented here would be able to capture the leading LF variations in Niño-3.4 for much of the past millennium, with the caveats noted above.

Comparison of isotopic signatures in speleothem records and model simulations for the past millennium

2020 ◽  
Author(s):  
Janica Buehler ◽  
Moritz Kirschner ◽  
Carla Roesch ◽  
Max D. Holloway ◽  
Louise Sime ◽  
...  
Keyword(s):  
Climate Variability ◽  
Time Scales ◽  
General Circulation ◽  
General Circulation Models ◽  
Global Changes ◽  
Climate Change Scenarios ◽  
The Past ◽  
Proxy Records ◽  
Parameter Constraints ◽  
Past Millennium

<p>Global changes in climate, especially in mean temperature, receive increasing public as well as scientific attention under the current warming trend. However, the probability of extreme events and their societal impact is also governed by changes in climate variability. Improving the understanding of changes in both and their relationship is crucial for projecting reliable climate change scenarios. Model-data comparisons between general circulation models and speleothem paleoclimate archives, with δ<sup>18</sup>O as a temperature and precipitation proxy, have been suggested to test and validate the capability of different climate models.</p><p>Speleothems are precisely date-able and provide well preserved (semi-)continuous climate signals in the lower and mid-latitudes, providing a suitable archive to assess a model’s capability to simulate climate variability on time scales longer than those observable. However, the δ<sup>18</sup>O measured in speleothem calcite does not directly represent temperature or precipitation but results from multivariate, non-linear processes on top of the dominant meteoric controls on δ<sup>18</sup>O in precipitation.</p><p>Here, we evaluate correlations and networks between different records and power spectral densities across a speleothem database for the past millennium (850-2000CE), testing for representativity of individual records for the time period. Similarity measures are applied to proxy records and to the local climate variables obtained from three isotope-enabled HadCM3 simulations to evaluate simulation biases across different parameters and to distinguish main climate drivers for individual records or regions. The proxy records show strong damping of variability on shorter time scales compared to simulations down-sampled to record-resolution, acting like simple filter processes with realistic time scales for karst transit times.</p><p>Based on the evidence from proxies and models for the past 1000 years, we test for realistic parameter constraints and sufficient complexity of a speleothem proxy system model to represent low-latitude changes in climate variability on interannual to centennial timescales.</p>

scholarly journals Estimating Central Equatorial Pacific SST Variability over the Past Millennium. Part II: Reconstructions and Implications

2013 ◽  
Vol 26 (7) ◽  
pp. 2329-2352 ◽  
Author(s):  
Julien Emile-Geay ◽  
Kimberly M. Cobb ◽  
Michael E. Mann ◽  
Andrew T. Wittenberg
Keyword(s):  
Time Scales ◽  
Radiative Forcing ◽  
General Circulation ◽  
Tropical Pacific ◽  
Wavelet Coherence ◽  
The Past ◽  
Sst Variability ◽  
Wavelet Coherence Analysis ◽  
Past Millennium ◽  
The Tropical Pacific

Abstract Reducing the uncertainties surrounding the impacts of anthropogenic climate change requires vetting general circulation models (GCMs) against long records of past natural climate variability. This is particularly challenging in the tropical Pacific Ocean, where short, sparse instrumental data preclude GCM validation on multidecadal to centennial time scales. This two-part paper demonstrates the application of two statistical methodologies to a network of accurately dated tropical climate records to reconstruct sea surface temperature (SST) variability in the Niño-3.4 region over the past millennium. While Part I described the methods and established their validity and limitations, this paper presents several reconstructions of Niño-3.4, analyzes their sensitivity to procedural choices and input data, and compares them to climate forcing time series and previously published tropical Pacific SST reconstructions. The reconstructions herein show remarkably similar behavior at decadal to multidecadal scales, but diverge markedly on centennial scales. The amplitude of centennial variability in each reconstruction scales with the magnitude of the A.D. 1860–1995 trend in the target dataset’s Niño-3.4 index, with Extended Reconstructed SST, version 3 (ERSSTv3) > the Second Hadley Centre SST dataset (HadSST2) > Kaplan SST; these discrepancies constitute a major source of uncertainty in reconstructing preinstrumental Niño-3.4 SST. Despite inevitable variance losses, the reconstructed multidecadal variability exceeds that simulated by a state-of-the-art GCM (forced and unforced) over the past millennium, while reconstructed centennial variability is incompatible with constant boundary conditions. Wavelet coherence analysis reveals a robust antiphasing between solar forcing and Niño-3.4 SST on bicentennial time scales, but not on shorter time scales. Implications for GCM representations of the tropical Pacific climate response to radiative forcing are then discussed.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

An applied mathematics perspective on stochastic modelling for climate

2008 ◽  
Vol 366 (1875) ◽  
pp. 2427-2453 ◽  
Author(s):  
Andrew J Majda ◽  
Christian Franzke ◽  
Boualem Khouider
Keyword(s):  
Stochastic Model ◽  
General Circulation ◽  
Applied Mathematics ◽  
Low Frequency ◽  
Lattice Models ◽  
Stochastic Modelling ◽  
General Circulation Models ◽  
Teleconnection Patterns ◽  
Slowing Down ◽  
Low Dimensional

Systematic strategies from applied mathematics for stochastic modelling in climate are reviewed here. One of the topics discussed is the stochastic modelling of mid-latitude low-frequency variability through a few teleconnection patterns, including the central role and physical mechanisms responsible for multiplicative noise. A new low-dimensional stochastic model is developed here, which mimics key features of atmospheric general circulation models, to test the fidelity of stochastic mode reduction procedures. The second topic discussed here is the systematic design of stochastic lattice models to capture irregular and highly intermittent features that are not resolved by a deterministic parametrization. A recent applied mathematics design principle for stochastic column modelling with intermittency is illustrated in an idealized setting for deep tropical convection; the practical effect of this stochastic model in both slowing down convectively coupled waves and increasing their fluctuations is presented here.

scholarly journals An Assessment of GCM Skill in Simulating Persistence across Multiple Time Scales

2011 ◽  
Vol 24 (14) ◽  
pp. 3609-3623 ◽  
Author(s):  
Fiona Johnson ◽  
Seth Westra ◽  
Ashish Sharma ◽  
Andrew J. Pitman
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
Large Scale ◽  
Low Frequency ◽  
General Circulation Models ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Max Planck ◽  
Reservoir Storage ◽  
Low Frequency Variability

Abstract Climate change impact studies for water resource applications, such as the development of projections of reservoir yields or the assessment of likely frequency and amplitude of drought under a future climate, require that the year-to-year persistence in a range of hydrological variables such as catchment average rainfall be properly represented. This persistence is often attributable to low-frequency variability in the global sea surface temperature (SST) field and other large-scale climate variables through a complex sequence of teleconnections. To evaluate the capacity of general circulation models (GCMs) to accurately represent this low-frequency variability, a set of wavelet-based skill measures has been developed to compare GCM performance in representing interannual variability with the observed global SST data, as well as to assess the extent to which this variability is imparted in precipitation and surface pressure anomaly fields. A validation of the derived skill measures is performed using GCM precipitation as an input in a reservoir storage context, with the accuracy of reservoir storage estimates shown to be improved by using GCM outputs that correctly represent the observed low-frequency variability. Significant differences in the performance of different GCMs is demonstrated, suggesting that judicious selection of models is required if the climate impact assessment is sensitive to low-frequency variability. The two GCMs that were found to exhibit the most appropriate representation of global low-frequency variability for individual variables assessed were the Istituto Nazionale di Geofisica e Vulcanologia (INGV) ECHAM4 and L’Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL CM4); when considering all three variables, the Max Planck Institute (MPI) ECHAM5 performed well. Importantly, models that represented interannual variability well for SST also performed well for the other two variables, while models that performed poorly for SST also had consistently low skill across the remaining variables.

scholarly journals Multidecadal to Centennial Variability of the AMOC: HadCM3 and a Perturbed Physics Ensemble

2013 ◽  
Vol 26 (7) ◽  
pp. 2390-2407 ◽  
Author(s):  
Laura Jackson ◽  
Michael Vellinga
Keyword(s):  
General Circulation ◽  
Low Frequency ◽  
Coupled Model ◽  
General Circulation Models ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Equatorial Atlantic ◽  
Small Ensemble ◽  
Background Climate ◽  
Perturbed Physics

Abstract Multidecadal to centennial variability of the Atlantic meridional overturning circulation (AMOC) is investigated in a multi-thousand-year simulation of the third version of the Hadley Centre Coupled Model (HadCM3) and in an ensemble of general circulation models (GCMs) based on HadCM3 with perturbed physics. Large changes in the AMOC in the standard HadCM3 are strongly related to salinity anomalies in the deep-water formation regions, with anomalies arriving via two pathways. The first is from a coupled feedback in the equatorial Atlantic Ocean, described previously by Vellinga and Wu, and the second is from variability in the Arctic Ocean, possibly driven by stochastic sea level pressure. The low-frequency variability of the AMOC in HadCM3 is well predicted from salinity anomalies from these two pathways. The sensitivity of these processes to model physics is investigated using a small ensemble based on HadCM3 where parameters relating to physical processes are varied. The AMOC responds consistently to the salinity anomalies in the ensemble members. However, 1) the timing of the response depends on the background climate state and 2) some ensemble members have significantly larger AMOC and salinity variability than in standard HadCM3 simulations. In this small ensemble, the presence and strength of multidecadal to centennial AMOC variability is associated with the variability of salinity exported from the Arctic, with little multidecadal to centennial variability of either in the coldest members. This demonstrates how the background climate state can alter the frequency and strength of AMOC variability and is a first step toward understanding how AMOC variability differs within a multimodel context.

The Advent of Climate Science

2020 ◽  
Author(s):  
Deborah R. Coen
Keyword(s):  
Research Program ◽  
General Circulation ◽  
Modern Science ◽  
Climate Science ◽  
General Circulation Models ◽  
World War ◽  
The Past ◽  
Measurement And Analysis ◽  
History Of ◽  
Definition Of

The advent of climate science can be defined as the historical emergence of a research program to study climate according to a modern definition of climate. Climate in this sense: (1) refers not simply to the average state of the atmosphere but also to its variability; (2) is multiscalar, concerned with phenomena ranging from the very small and fast to the very large and slow; and (3) is understood to be influenced by the oceans, lithosphere, cryosphere, and biosphere. Most accounts of the history of climate science to date have focused on the development of computerized general circulation models since World War Two. However, following this definition, the advent of climate science occurred well before the computer age. This entry therefore seeks to dispel the image of climate science as a recent invention and as the preserve of an exclusive, North American elite. The historical roots of today’s knowledge of climate change stretch surprisingly far back into the past and clear across the world, though the geographic focus here is on Europe and North America. The modern science of climate emerged out of interactions between learned and vernacular knowledge traditions, and has simultaneously appropriated and undermined traditional and indigenous forms of climate knowledge. Important precedents emerged in the 17th and 18th centuries, and it was in the late 19th century that a modern science of climate coalesced into a coordinated research program in part through the unification of divergent knowledge traditions around standardized techniques of measurement and analysis.

scholarly journals Spatiotemporal Trends and Attribution of Drought across China from 1901–2100

2020 ◽  
Vol 12 (2) ◽  
pp. 477
Author(s):  
Yongxia Ding ◽  
Shouzhang Peng
Keyword(s):  
Adverse Effects ◽  
General Circulation ◽  
Potential Evapotranspiration ◽  
Northern China ◽  
General Circulation Models ◽  
Research Unit ◽  
Mitigation Strategies ◽  
Climatic Research Unit ◽  
The Past ◽  
Spatiotemporal Trends

Investigating long-term drought trends is of great importance in coping with the adverse effects of global warming. However, little attention has been focused on studying the detailed spatial variability and attribution of drought variation in China. In this study, we first generated a 1 km resolution monthly climate dataset for the period 1901–2100 across China using the delta spatial downscaling method to assess the variability of the Standardized Precipitation Evaporation Index (SPEI). We then developed a simple approach to quantifying the contributions of water supply (precipitation) and demand (potential evapotranspiration, PET) on SPEI variability, according to the meaning of the differentiating SPEI equation. The results indicated that the delta framework could accurately downscale and correct low-spatial-resolution monthly temperatures and precipitation from the Climatic Research Unit and general circulation models (GCMs). Of the 27 GCMs analyzed, the BNU-ESM, CESM1-CAM5, and GFDL-ESM2M were found to be the most accurate in modeling future temperatures and precipitation. We also found that, compared with the past (1901–2017), the climate in the future (2018–2100) will tend toward significant droughts, although both periods showed a high spatial heterogeneity across China. Moreover, the proportion of areas with significantly decreasing SPEI trends was far greater than the proportion of those with increasing trends in most cases, especially for northwestern and northern China. Finally, the proposed approach to quantifying precipitation and PET contributions performed well according to logical evaluations. The percentage contributions of precipitation and PET on SPEI variability varied with study periods, representative concentration pathway scenarios, trend directions, and geographic spaces. In the past, PET contributions for significant downward trends and precipitation contributions for significantly upward trends accounted for 95% and 72%, while their future contributions were 57 ± 22%–149 ± 20% and 95 ± 27%–190 ± 58%, respectively. Overall, our results provide detailed insights for planning flexible adaptation and mitigation strategies to cope with the adverse effects of climate drought across China.

Possible pathways to a Dansgaard-Oeschger (DO) PMIP protocol

2021 ◽  
Author(s):  
Irene Malmierca-Vallet ◽  
Louise C. Sime ◽  
Paul J. Valdes
Keyword(s):  
General Circulation ◽  
Climate Changes ◽  
General Circulation Models ◽  
Ice Age ◽  
Climate Change Projections ◽  
The Past ◽  
External Perturbations ◽  
Mis 3 ◽  
Last Ice Age ◽  
Earth System Models

<p>The DO events of the last ice age represent one of the best studied abrupt climate transitions, yet we still lack a comprehensive explanation for them. There is uncertainty whether current IPCC-relevant models can effectively represent the processes that cause DO events. Current Earth system models (ESMs) seem overly stable against external perturbations and incapable of reproducing most abrupt climate changes of the past (Valdes, 2011). If this holds true, this could noticeably influence their capability to predict future abrupt transitions, with significant consequences for the delivery of precise climate change projections.  In this task, the objectives of this study are (1) to cross compare existing simulations that show spontaneous DO-type oscillations using a common set of diagnostics so we can compare the mechanisms and the characteristics of the oscillations, and (2) to formulate possible pathways to a DO PMIP protocol that could help investigate cold-period instabilities through a range of insolation-, freshwater-, GHG-, and NH ice sheet-related forcings, as well as evaluating the possibility of spontaneous internal oscillations.</p><p>Although most abrupt DO events happened during MIS3, only few studies investigate DO events in coupled general circulation models under MIS 3 conditions (e.g., Kawamura et al., 2017; Zhang and Prange, 2020). Here, we thus propose that the MIS3 period could be the focus of such a DO-event modelling protocol. More specific sensitivity experiments performed under MIS 3 boundary conditions are needed in order to (1) better understand the mechanisms behind millennial-scale climate variability, (2) explore AMOC variability under intermediate glacial conditions, and (3) help answer the question: “are models too stable?”.</p>

scholarly journals Probabilistic Multimodel Regional Temperature Change Projections

2006 ◽  
Vol 19 (17) ◽  
pp. 4326-4343 ◽  
Author(s):  
Arthur M. Greene ◽  
Lisa Goddard ◽  
Upmanu Lall
Keyword(s):  
Temperature Change ◽  
General Circulation ◽  
General Circulation Models ◽  
Probability Models ◽  
Intergovernmental Panel ◽  
Predictive Skill ◽  
Validation Measure ◽  
Emissions Scenarios ◽  
Regional Temperature ◽  
Bayesian Linear Model

Abstract Regional temperature change projections for the twenty-first century are generated using a multimodel ensemble of atmosphere–ocean general circulation models. The models are assigned coefficients jointly, using a Bayesian linear model fitted to regional observations and simulations of the climate of the twentieth century. Probability models with varying degrees of complexity are explored, and a selection is made based on Bayesian deviance statistics, coefficient properties, and a classical cross-validation measure utilizing temporally averaged data. The model selected is shown to be superior in predictive skill to a naïve model consisting of the unweighted mean of the underlying atmosphere–ocean GCM (AOGCM) simulations, although the skill differential varies regionally. Temperature projections for the A2 and B1 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios are presented.

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