scholarly journals Evaluation of climate model aerosol trends with ground-based observations over the last two decades – an AeroCom and CMIP6 analysis

2020 ◽  
Author(s):  
Augustin Mortier ◽  
Jonas Gliss ◽  
Michael Schulz ◽  
Keyword(s):  
Time Series ◽  
North Africa ◽  
Climate Models ◽  
Climate Model ◽  
Model Performance ◽  
Parameter Analysis ◽  
Time And Space ◽  
Regional Trends ◽  
Model Aerosol ◽  
The World

<p>This study presents a multi-parameter analysis of aerosol trends over the last two decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical composition and mass aerosol properties by using the observations of several ground-based networks. From these regional time series the aerosol trends have been derived for different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases of aerosol optical depth (AOD) are found in Europe, North America, South America and North Africa, ranging from −1.3 %/yr to −3.1 %/yr. An error and representativity analysis of the incomplete observational data has been performed using model data subsets in order to investigate how likely the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of the climate models and their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, column Angstrom exponent, sulfate and particulate matter well (except in North Africa), but show larger discrepancies for coarse mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from the one depicted by solely relying on ground based observations. Using a model with complete diagnostics (NorESM2) we find a global increase of AOD of about 0.2 %/yr between 2000 and 2014, primarily caused by an increase of the loads of organic aerosol, sulfate and black carbon.</p>

scholarly journals Evaluation of climate model aerosol trends with ground-based observations over the last two decades – an AeroCom and CMIP6 analysis

2020 ◽  
Author(s):  
Augustin Mortier ◽  
Jonas Gliss ◽  
Michael Schulz ◽  
Wenche Aas ◽  
Elisabeth Andrews ◽  
...  
Keyword(s):  
Time Series ◽  
North Africa ◽  
Climate Models ◽  
Climate Model ◽  
Model Performance ◽  
Parameter Analysis ◽  
Time And Space ◽  
Regional Trends ◽  
Model Aerosol ◽  
The World

Abstract. This study presents a multi-parameter analysis of aerosol trends over the last two decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical composition and mass aerosol properties by using the observations of several ground-based networks. From these regional time series the aerosol trends have been derived for different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases of aerosol optical depth (AOD) are found in Europe, North America, South America and North Africa, ranging from −1.3 %/yr to −3.1 %/yr. An error and representativity analysis of the incomplete observational data has been performed using model data subsets in order to investigate how likely the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of the climate models and their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, column Angstrom exponent, sulfate and particulate matter well (except in North Africa), but show larger discrepancies for coarse mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from the one depicted by solely relying on ground based observations. Using a model with complete diagnostics (NorESM2) we find a global increase of AOD of about 0.2 %/yr between 2000 and 2014, primarily caused by an increase of the loads of organic aerosol, sulfate and black carbon.

scholarly journals Evaluation of climate model aerosol trends with ground-based observations over the last 2 decades – an AeroCom and CMIP6 analysis

2020 ◽  
Vol 20 (21) ◽  
pp. 13355-13378
Author(s):  
Augustin Mortier ◽  
Jonas Gliß ◽  
Michael Schulz ◽  
Wenche Aas ◽  
Elisabeth Andrews ◽  
...  
Keyword(s):  
Time Series ◽  
North Africa ◽  
Climate Model ◽  
Model Performance ◽  
Phase Iii ◽  
Time And Space ◽  
Reanalysis Dataset ◽  
Regional Trends ◽  
Model Aerosol ◽  
The World

Abstract. This study presents a multiparameter analysis of aerosol trends over the last 2 decades at regional and global scales. Regional time series have been computed for a set of nine optical, chemical-composition and mass aerosol properties by using the observations from several ground-based networks. From these regional time series the aerosol trends have been derived for the different regions of the world. Most of the properties related to aerosol loading exhibit negative trends, both at the surface and in the total atmospheric column. Significant decreases in aerosol optical depth (AOD) are found in Europe, North America, South America, North Africa and Asia, ranging from −1.2 % yr−1 to −3.1 % yr−1. An error and representativity analysis of the spatially and temporally limited observational data has been performed using model data subsets in order to investigate how much the observed trends represent the actual trends happening in the regions over the full study period from 2000 to 2014. This analysis reveals that significant uncertainty is associated with some of the regional trends due to time and space sampling deficiencies. The set of observed regional trends has then been used for the evaluation of 10 models (6 AeroCom phase III models and 4 CMIP6 models) and the CAMS reanalysis dataset and of their skills in reproducing the aerosol trends. Model performance is found to vary depending on the parameters and the regions of the world. The models tend to capture trends in AOD, the column Ångström exponent, sulfate and particulate matter well (except in North Africa), but they show larger discrepancies for coarse-mode AOD. The rather good agreement of the trends, across different aerosol parameters between models and observations, when co-locating them in time and space, implies that global model trends, including those in poorly monitored regions, are likely correct. The models can help to provide a global picture of the aerosol trends by filling the gaps in regions not covered by observations. The calculation of aerosol trends at a global scale reveals a different picture from that depicted by solely relying on ground-based observations. Using a model with complete diagnostics (NorESM2), we find a global increase in AOD of about 0.2 % yr−1 between 2000 and 2014, primarily caused by an increase in the loads of organic aerosols, sulfate and black carbon.

scholarly journals Empirical estimate of the signal content of Holocene temperature proxy records

2019 ◽  
Vol 15 (2) ◽  
pp. 521-537 ◽  
Author(s):  
Maria Reschke ◽  
Kira Rehfeld ◽  
Thomas Laepple
Keyword(s):  
Time Series ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Correlation Structure ◽  
Past Climate ◽  
Time Uncertainty ◽  
Proxy Records ◽  
Spatial Correlation Structure ◽  
Temperature Proxy

Abstract. Proxy records from climate archives provide evidence about past climate changes, but the recorded signal is affected by non-climate-related effects as well as time uncertainty. As proxy-based climate reconstructions are frequently used to test climate models and to quantitatively infer past climate, we need to improve our understanding of the proxy record signal content as well as the uncertainties involved. In this study, we empirically estimate signal-to-noise ratios (SNRs) of temperature proxy records used in global compilations of the middle to late Holocene (last 6000 years). This is achieved through a comparison of the correlation of proxy time series from nearby sites of three compilations and model time series extracted at the proxy sites from two transient climate model simulations: a Holocene simulation of the ECHAM5/MPI-OM model and the Holocene part of the TraCE-21ka simulation. In all comparisons, we found the mean correlations of the proxy time series on centennial to millennial timescales to be low (R<0.2), even for nearby sites, which resulted in low SNR estimates. The estimated SNRs depend on the assumed time uncertainty of the proxy records, the timescale analysed, and the model simulation used. Using the spatial correlation structure of the ECHAM5/MPI-OM simulation, the estimated SNRs on centennial timescales ranged from 0.05 – assuming no time uncertainty – to 0.5 for a time uncertainty of 400 years. On millennial timescales, the estimated SNRs were generally higher. Use of the TraCE-21ka correlation structure generally resulted in lower SNR estimates than for ECHAM5/MPI-OM. As the number of available high-resolution proxy records continues to grow, a more detailed analysis of the signal content of specific proxy types should become feasible in the near future. The estimated low signal content of Holocene temperature compilations should caution against over-interpretation of these multi-proxy and multisite syntheses until further studies are able to facilitate a better characterisation of the signal content in paleoclimate records.

scholarly journals Sensitivity of the WRF-Chem (V3.6.1) model to different dust emission parametrisation: assessment in the broader Mediterranean region

2017 ◽  
Vol 10 (8) ◽  
pp. 2925-2945 ◽  
Author(s):  
Emmanouil Flaounas ◽  
Vassiliki Kotroni ◽  
Konstantinos Lagouvardos ◽  
Martina Klose ◽  
Cyrille Flamant ◽  
...  
Keyword(s):  
North Africa ◽  
Eastern Mediterranean ◽  
Dust Emission ◽  
Model Performance ◽  
Dust Particles ◽  
Dust Transport ◽  
Dust Emissions ◽  
Extinction Coefficients ◽  
Airborne Measurements ◽  
Model Aerosol

Abstract. In this study we aim to assess the WRF-Chem model capacity to reproduce dust transport over the eastern Mediterranean. For this reason, we compare the model aerosol optical depth (AOD) outputs to observations, focusing on three key regions: North Africa, the Arabian Peninsula and the eastern Mediterranean. Three sets of four simulations have been performed for the 6-month period of spring and summer 2011. Each simulation set uses a different dust emission parametrisation and for each parametrisation, the dust emissions are multiplied with various coefficients in order to tune the model performance. Our assessment approach is performed across different spatial and temporal scales using AOD observations from satellites and ground-based stations, as well as from airborne measurements of aerosol extinction coefficients over the Sahara. Assessment over the entire domain and simulation period shows that the model presents temporal and spatial variability similar to observed AODs, regardless of the applied dust emission parametrisation. On the other hand, when focusing on specific regions, the model skill varies significantly. Tuning the model performance by applying a coefficient to dust emissions may reduce the model AOD bias over a region, but may increase it in other regions. In particular, the model was shown to realistically reproduce the major dust transport events over the eastern Mediterranean, but failed to capture the regional background AOD. Further comparison of the model simulations to airborne measurements of vertical profiles of extinction coefficients over North Africa suggests that the model realistically reproduces the total atmospheric column AOD. Finally, we discuss the model results in two sensitivity tests, where we included finer dust particles (less than 1 µm) and changed accordingly the dust bins' mass fraction.

scholarly journals Emerging climate signals in the Lena River catchment: a non-parametric statistical approach

2020 ◽  
Vol 24 (5) ◽  
pp. 2817-2839
Author(s):  
Eric Pohl ◽  
Christophe Grenier ◽  
Mathieu Vrac ◽  
Masa Kageyama
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Models ◽  
Climate Model ◽  
Natural Variability ◽  
Climate Signal ◽  
Lena River ◽  
River Catchment ◽  
Model Simulations ◽  
Non Parametric

Abstract. Climate change has far-reaching implications in permafrost-underlain landscapes with respect to hydrology, ecosystems, and the population's traditional livelihoods. In the Lena River catchment, eastern Siberia, changing climatic conditions and the associated impacts are already observed or expected. However, as climate change progresses the question remains as to how far we are along this track and when these changes will constitute a significant emergence from natural variability. Here we present an approach to investigate temperature and precipitation time series from observational records, reanalysis, and an ensemble of 65 climate model simulations forced by the RCP8.5 emission scenario. We developed a novel non-parametric statistical method to identify the time of emergence (ToE) of climate change signals, i.e. the time when a climate signal permanently exceeds its natural variability. The method is based on the Hellinger distance metric that measures the similarity of probability density functions (PDFs) roughly corresponding to their geometrical overlap. Natural variability is estimated as a PDF for the earliest period common to all datasets used in the study (1901–1921) and is then compared to PDFs of target periods with moving windows of 21 years at annual and seasonal scales. The method yields dissimilarities or emergence levels ranging from 0 % to 100 % and the direction of change as a continuous time series itself. First, we showcase the method's advantage over the Kolmogorov–Smirnov metric using a synthetic dataset that resembles signals observed in the utilized climate models. Then, we focus on the Lena River catchment, where significant environmental changes are already apparent. On average, the emergence of temperature has a strong onset in the 1970s with a monotonic increase thereafter for validated reanalysis data. At the end of the reanalysis dataset (2004), temperature distributions have emerged by 50 %–60 %. Climate model projections suggest the same evolution on average and 90 % emergence by 2040. For precipitation the analysis is less conclusive because of high uncertainties in existing reanalysis datasets that also impede an evaluation of the climate models. Model projections suggest hardly any emergence by 2000 but a strong emergence thereafter, reaching 60 % by the end of the investigated period (2089). The presented ToE method provides more versatility than traditional parametric approaches and allows for a detailed temporal analysis of climate signal evolutions. An original strategy to select the most realistic model simulations based on the available observational data significantly reduces the uncertainties resulting from the spread in the 65 climate models used. The method comes as a toolbox available at https://github.com/pohleric/toe_tools (last access: 19 May 2020).

scholarly journals On the potential use of glacier and permafrost observations for verification of climate models

1997 ◽  
Vol 25 ◽  
pp. 400-406 ◽  
Author(s):  
Martin Beniston ◽  
Wilfried Haeberli ◽  
Martin Hoelzle ◽  
Alan Taylor
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Model Performance ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Model Verification ◽  
Dominant Feature

While the capability of global and regional climate models in reproducing current climate has significantly improved over the past few years, the confidence in model results for remote regions, or those where complex orography is a dominant feature, is still relatively low. This is, in part, linked to the lack of observational data for model verification and intercomparison purposes.Glacier and permafrost observations are directly related to past and present energy flux patterns at the Earth-atmosphere interface and could be used as a proxy for air temperature and precipitation, particularly of value in remote mountain regions and boreal and Arctic zones where instrumental climate records are sparse or non-existent. It is particularly important to verify climate-model performance in these regions, as this is where most general circulation models (GCMs) predict the greatest changes in air temperatures in a warmer global climate.Existing datasets from glacier and permafrost monitoring sites in remote and high altitudes are described in this paper; the data could be used in model-verification studies, as a means to improving model performance in these regions.

scholarly journals Hydroclimate variability in Scandinavia over the last millennium – insights from a climate model–proxy data comparison

2017 ◽  
Vol 13 (12) ◽  
pp. 1831-1850 ◽  
Author(s):  
Kristina Seftigen ◽  
Hugues Goosse ◽  
Francois Klein ◽  
Deliang Chen
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Model Performance ◽  
Circulation Model ◽  
Last Millennium ◽  
Atmospheric Variability ◽  
Out Of Sample ◽  
Hydroclimate Variability ◽  
Transient Simulations

Abstract. The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts–pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5–PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data–model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

scholarly journals Probabilistic Concepts in Intermediate-Complexity Climate Models: A Snapshot Attractor Picture

2015 ◽  
Vol 29 (1) ◽  
pp. 259-272 ◽  
Author(s):  
Mátyás Herein ◽  
János Márfy ◽  
Gábor Drótos ◽  
Tamás Tél
Keyword(s):  
Time Series ◽  
Climate Models ◽  
Climate Model ◽  
Initial Conditions ◽  
Internal Variability ◽  
Co2 Concentration ◽  
Ensemble Average ◽  
Climate Projections ◽  
Intermediate Complexity ◽  
The North

Abstract A time series resulting from a single initial condition is shown to be insufficient for quantifying the internal variability in a climate model, and thus one is unable to make meaningful climate projections based on it. The authors argue that the natural distribution, obtained from an ensemble of trajectories differing solely in their initial conditions, of the snapshot attractor corresponding to a particular forcing scenario should be determined in order to quantify internal variability and to characterize any instantaneous state of the system in the future. Furthermore, as a simple measure of internal variability of any particular variable of the model, the authors suggest using its instantaneous ensemble standard deviation. These points are illustrated with the intermediate-complexity climate model Planet Simulator forced by a CO2 scenario, with a 40-member ensemble. In particular, the leveling off of the time dependence of any ensemble average is shown to provide a much clearer indication of reaching a steady state than any property of single time series. Shifts in ensemble averages are indicative of climate changes. The dynamical character of such changes is illustrated by hysteresis-like curves obtained by plotting the ensemble average surface temperature versus the CO2 concentration. The internal variability is found to be the most pronounced on small geographical scales. The traditionally used 30-yr temporal averages are shown to be considerably different from the corresponding ensemble averages. Finally, the North Atlantic Oscillation (NAO) index, related to the teleconnection paradigm, is also investigated. It is found that the NAO time series strongly differs in any individual realization from each other and from the ensemble average, and climatic trends can be extracted only from the latter.

scholarly journals Empirical estimate of the signal content of Holocene temperature proxy records

2018 ◽  
Author(s):  
Maria Reschke ◽  
Kira Rehfeld ◽  
Thomas Laepple
Keyword(s):  
Time Series ◽  
Climate Models ◽  
Climate Model ◽  
Time Series Data ◽  
Series Data ◽  
Past Climate ◽  
Proxy Records ◽  
Model Time Series ◽  
Climate Model Simulations ◽  
Temperature Proxy

Abstract. Proxy records from climate archives provide evidence about past climate changes, but the recorded signal is affected by non-climate related effects as well as time uncertainty. As proxy based climate reconstructions are frequently used to test climate models and to quantitatively infer past climate, we need to improve our understanding of the proxy records’ signal content as well as the uncertainties involved. In this study, we empirically estimate signal-to-noise ratios (SNRs) of temperature proxy records used in global compilations of the mid to late Holocene. This is achieved through a comparison of proxy time series from close-by sites of three compilations and model time series data at the proxy sites from two transient Holocene climate model simulations. In all comparisons, we found the mean correlations of the proxy time series on centennial to millennial time scales to be rather low (R 

scholarly journals Hydroclimate variability in Scandinavia over the last millennium – insights from a climate model-proxy data comparison

2017 ◽  
Author(s):  
Kristina Seftigen ◽  
Hugues Goosse ◽  
Francois Klein ◽  
Deliang Chen
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Circulation Model ◽  
Global Climate Models ◽  
Last Millennium ◽  
Atmospheric Variability ◽  
Out Of Sample

Abstract. The integration of climate proxy information with General Circulation Model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavian with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produces droughts/pluvials in the region. But despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find simulated interannual components of variability to be overestimated, while the multidecadal/longer timescale components generally are too weak. Specifically, summertime moisture variability and temperature are weakly negatively associated at inter-annual timescales but positively correlated at decadal timescales, revealed from observational and proxy evidences. On this background, the CMIP5/PMIP3 simulated timescale dependent relationship between regional precipitation and temperature is considerably biased, because the short-term negative association is overestimated, and the long-term relationship is significantly underestimated. The lack of adequate understanding for mechanisms linking temperature and moisture supply on longer timescales has important implication for future projections. Weak multidecadal variability in models also implies that inference about future persistent droughts and pluvials based on the latest generation global climate models will likely underestimate the true risk of these events.

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