scholarly journals Exploring seasonal accumulation bias in a west central Greenland ice core with observed and reanalyzed data

2014 ◽  
Vol 60 (224) ◽  
pp. 1065-1074 ◽  
Author(s):  
Stacy E. Porter ◽  
Ellen Mosley-Thompson
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Ice Core ◽  
The North ◽  
West Central ◽  
Circulation Patterns ◽  
Winter Circulation ◽  
History Of ◽  
Summer Maximum ◽  
The North Atlantic Oscillation

AbstractThe seasonality of accumulation in west central Greenland is investigated to determine whether a summer bias exists in a multi-century ice core recovered from Crawford Point (CP). Such a bias would negatively affect the ice core’s potential for reconstructing the history of winter circulation patterns including the North Atlantic Oscillation. An automatic weather station (AWS) installed at the CP site in 1995 records sub-daily surface heights and affords a unique opportunity to assess the seasonal distribution of accumulation and test the performance of five gridded reanalysis datasets and a regional climate model. Simulated accumulation compares remarkably well with in situ measurements from both the AWS and CP ice core, demonstrating their potential to accurately represent accumulation in this region. Seasonal accumulation exhibits no summer maximum, indicating that any concurrent precipitation maximum is likely offset by melt and/or sublimation effects. The lack of a strong seasonal accumulation bias implies that the CP ice core is well suited for future investigations of the history of winter circulation patterns.

scholarly journals Accelerating changes in ice mass within Greenland, and the ice sheet’s sensitivity to atmospheric forcing

2019 ◽  
Vol 116 (6) ◽  
pp. 1934-1939 ◽  
Author(s):  
Michael Bevis ◽  
Christopher Harig ◽  
Shfaqat A. Khan ◽  
Abel Brown ◽  
Frederik J. Simons ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Climate Model ◽  
Regional Climate ◽  
Atmospheric Forcing ◽  
Surface Mass ◽  
The North ◽  
Global Positioning ◽  
The North Atlantic Oscillation ◽  
Gravity Recovery ◽  
Gps Observations

From early 2003 to mid-2013, the total mass of ice in Greenland declined at a progressively increasing rate. In mid-2013, an abrupt reversal occurred, and very little net ice loss occurred in the next 12–18 months. Gravity Recovery and Climate Experiment (GRACE) and global positioning system (GPS) observations reveal that the spatial patterns of the sustained acceleration and the abrupt deceleration in mass loss are similar. The strongest accelerations tracked the phase of the North Atlantic Oscillation (NAO). The negative phase of the NAO enhances summertime warming and insolation while reducing snowfall, especially in west Greenland, driving surface mass balance (SMB) more negative, as illustrated using the regional climate model MAR. The spatial pattern of accelerating mass changes reflects the geography of NAO-driven shifts in atmospheric forcing and the ice sheet’s sensitivity to that forcing. We infer that southwest Greenland will become a major future contributor to sea level rise.

scholarly journals Mid-to-late Holocene Temperature Evolution and Atmospheric Dynamics over Europe in Regional Model Simulations

2016 ◽  
Author(s):  
Emmanuele Russo ◽  
Ulrich Cubasch
Keyword(s):  
Late Holocene ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climatic Conditions ◽  
Modes Of Variability ◽  
The North ◽  
Climate Reconstructions ◽  
The North Atlantic Oscillation ◽  
Almost All

Abstract. The improvement in resolution of climate models is always been mentioned as one of the most important factors when investigating past climatic conditions especially in order to evaluate and compare the results against proxy data. In this paper we present for the first time a set of high resolution simulations for different time slices of mid-to-late Holocene performed over Europe using a Regional Climate Model. Through a validation against a new pollen-based climate reconstructions dataset, covering almost all of Europe, we test the model performances for paleoclimatic applications and investigate the response of temperature to variations in the seasonal cycle of insolation, with the aim of clarifying earlier debated uncertainties, giving physically plausible interpretations of both the pollen data and the model results. The results reinforce previous findings showing that summertime temperatures were driven mainly by changes in insolation and that the model is too sensitive to such changes over Southern Europe, resulting in drier and warmer conditions. In winter, instead, the model does not reproduce correctly the same amplitude of changes, even if it captures the main pattern of the pollen dataset over most of the domain for the time periods under investigation. Through the analysis of variations in atmospheric circulation we suggest that, even though in some areas the discrepancies between the two datasets are most likely due to high pollen uncertanties, in general the model seems to underestimate the changes in the amplitude of the North Atlantic Oscillation, overestimating the contribution of secondary modes of variability

Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for Central Europe

2020 ◽  
Author(s):  
Andrea Böhnisch ◽  
Ralf Ludwig ◽  
Martin Leduc
Keyword(s):  
North Atlantic ◽  
Climate Model ◽  
Regional Climate ◽  
Internal Variability ◽  
Single Model ◽  
Large Ensemble ◽  
Central European ◽  
The North ◽  
Temperature And Precipitation ◽  
The North Atlantic Oscillation

<p>The ClimEx-project ("Climate change and hydrological extreme events"; www.climex-project.org) provides a single-model initial-condition ensemble that is unprecedented in terms of size, resolution and domain coverage: 50 members of the Canadian Earth System Model version 2 (CanESM2 Large Ensemble, 2.8° spatial resolution) are downscaled using the Canadian Regional Climate Model version 5 (CRCM5 Large Ensemble, 0.11° spatial and up to hourly temporal resolution) over two domains, Europe and northeastern North America. The high-resolution climate information serves as input for hydrological simulations to investigate the impact of internal variability and climate change on hydrometeorological extremes.</p><p>This study evaluates the downscaling of a teleconnection which affects northern hemisphere climate variability, the North Atlantic Oscillation (NAO), within the nested single-model large ensemble of the ClimEx project. The overall goal of this study is to assess whether the range of NAO internal variability is represented consistently between the driving global climate model (GCM, i.e., the CanESM2) and the nested regional climate model (RCM, i.e., the CRCM5).</p><p>The NAO pressure dipole is quantified in the CanESM2-LE; responses of mean surface air temperature and total precipitation sum to changes in the NAO index are evaluated within a Central European domain in both the CanESM2-LE and the CRCM5-LE. NAO–response relationships are expressed via Pearson correlation coefficients and the change per unit index change for historical (1981–2010) and future (2070–2099) winters.</p><p>Results show that statistically robust NAO patterns are found in the CanESM2-LE under current forcing conditions, and reproductions of the NAO flow pattern present in the CanESM2-LE produce plausible temperature and precipitation responses in the high-resolution CRCM5-LE. The NAO–response relationship is more strongly evolved in the CRCM5-LE than in the CanESM2-LE, but the inter-member spread shows no significant differences: thus internal variability expressed as inter-member spread can be seen as being represented consistently between the GCM and RCM. NAO–response relationships weaken in the future period in both the CanESM2-LE and CRCM5-LE, suggesting that the NAO influence on Central European temperature and precipitation decreases.</p><p>The results stress the advantages of a single-model ensemble regarding the evaluation of internal variability. They also strengthen the validity of the nested ensemble for further impact modelling using RCM data only, since important large-scale teleconnections present in the driving GCM propagate properly to the fine scale dynamics in the RCM.</p>

Applying machine learning for drought prediction using a large ensemble of climate simulations

2021 ◽  
Author(s):  
Elizaveta Felsche ◽  
Ralf Ludwig
Keyword(s):  
Machine Learning ◽  
Regional Climate Model ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
North Atlantic Oscillation Index ◽  
Climate Model ◽  
Regional Climate ◽  
The North ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

<p>There is strong scientific and social interest to understand the factors leading to extreme events in order to improve the management of risks associated with hazards like droughts. Recent events like the summer 2018 drought in Germany already had severe und unexpected impacts, e.g. forest fires and crop failures; in order to increase preparedness robust prediction tools are  urgently required. In this study, machine learning methods are applied to predict the occurrence of a drought with lead times of one to three months. The approach takes into account a list of thirty atmospheric and soil variables<strong> </strong>as predictor input parameters from a single regional climate model initial condition large ensemble (CRCM5-LE). The data was produced the context of the ClimEx project by Ouranos with the Canadian Regional Climate Model (CRCM5) driven by 50 members of the Canadian Earth System Model (CanESM2) for the Bavarian and Quebec domains.</p><p>Drought occurrence was defined using the Standardized Precipitation Index. The training and test datasets were chosen from the current climatology (1955-2005) for the Munich and Lisbon subdomain within the CRCM5-LE. The best performing machine learning algorithms managed to obtain a correct classification of drought or no drought for a lead time of one month for around 60 % of the events of each class for the both domains. Explainable AI methods like feature importance and shapley values were applied to gain a better understanding of the trained algorithms. Physical variables like the North Atlantic Oscillation Index and air pressure one month before the event proved to be of high importance for the prediction. The study showed that better accuracies can be obtained for the Lisbon domain, due to the stronger influence of the North Atlantic Oscillation Index on Portugal’s climate.</p>

scholarly journals Observed and Modeled Greenland Ice Sheet Snow Accumulation, 1958–2003, and Links with Regional Climate Forcing

2006 ◽  
Vol 19 (3) ◽  
pp. 344-358 ◽  
Author(s):  
Edward Hanna ◽  
Joe McConnell ◽  
Sarah Das ◽  
John Cappelen ◽  
Ag Stephens
Keyword(s):  
Regional Climate ◽  
Ice Core ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Absolute Amount ◽  
High Accumulation ◽  
The North ◽  
Meteorological Modeling ◽  
The North Atlantic Oscillation

Abstract Annual and monthly snow accumulation for the Greenland Ice Sheet was derived from ECMWF forecasts [mainly 40-yr ECMWR Re-Analysis (ERA-40)] and further meteorological modeling. Modeled accumulation was validated using 58 ice core accumulation datasets across the ice sheet and was found to be 95% of the observed accumulation on average, with a mean correlation of 0.53 between modeled and observed. Many of the ice core datasets are new and are presented here for the first time. Central and northern interior parts of the ice sheet were found to be ∼10%–30% too dry in ERA-40, in line with earlier ECMWF analysis, although too much (>50% locally) snow accumulation was modeled for interior southern parts of Greenland. Nevertheless, 47 of 58 sites show significant correlation in temporal variability of modeled with observed accumulation. The model also captures the absolute amount of snow accumulation at several sites, most notably Das1 and Das2 in southeast Greenland. Mean modeled accumulation over the ice sheet was 0.279 (standard deviation 0.034) m yr−1 for 1958–2003 with no significant trend for either the ice sheet or any of the core sites. Unusually high accumulation in southeast Greenland in 2002/03 leads the authors to study meteorological synoptic forcing patterns and comment on the prospect of enhanced climate variability leading to more such events as a result of global warming. There is good agreement between precipitation measured at coastal meteorological stations in southern Greenland and accumulation modeled for adjacent regions of the ice sheet. There is no significant persistent relation between the North Atlantic Oscillation index and whole or southern Greenland accumulation.

scholarly journals Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central Europe

2020 ◽  
Vol 11 (3) ◽  
pp. 617-640 ◽  
Author(s):  
Andrea Böhnisch ◽  
Ralf Ludwig ◽  
Martin Leduc
Keyword(s):  
Regional Climate Model ◽  
North Atlantic ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Internal Variability ◽  
Single Model ◽  
Central European ◽  
The North ◽  
The North Atlantic Oscillation

Abstract. Central European weather and climate are closely related to atmospheric mass advection triggered by the North Atlantic Oscillation (NAO), which is a relevant index for quantifying internal climate variability on multi-annual timescales. It remains unclear, however, how large-scale circulation variability affects local climate characteristics when downscaled using a regional climate model. In this study, 50 members of a single-model initial-condition large ensemble (LE) of a nested regional climate model are analyzed for a NAO–climate relationship. The overall goal of the study is to assess whether the range of NAO internal variability is represented consistently between the driving global climate model (GCM; the Canadian Earth System Model version 2 – CanESM2) and the nested regional climate model (RCM; the Canadian Regional Climate Model version 5 – CRCM5). Responses of mean surface air temperature and total precipitation to changes in the NAO index value are examined in a central European domain in both CanESM2-LE and CRCM5-LE via Pearson correlation coefficients and the change per unit index change for historical (1981–2010) and future (2070–2099) winters. Results show that statistically robust NAO patterns are found in the CanESM2-LE under current forcing conditions. NAO flow pattern reproductions in the CanESM2-LE trigger responses in the high-resolution CRCM5-LE that are comparable to reanalysis data. NAO–response relationships weaken in the future period, but their inter-member spread shows no significant change. The results stress the value of single-model ensembles for the evaluation of internal variability by pointing out the large differences of NAO–response relationships among individual members. They also strengthen the validity of the nested ensemble for further impact modeling using RCM data only, since important large-scale teleconnections present in the driving data propagate properly to the fine-scale dynamics in the RCM.

scholarly journals Impact of precipitation intermittency on NAO-temperature signals in proxy records

2013 ◽  
Vol 9 (2) ◽  
pp. 871-886 ◽  
Author(s):  
M. Casado ◽  
P. Ortega ◽  
V. Masson-Delmotte ◽  
C. Risi ◽  
D. Swingedouw ◽  
...  
Keyword(s):  
General Circulation ◽  
Ice Core ◽  
Circulation Model ◽  
Ice Cores ◽  
Stable Isotope Ratio ◽  
Global Network ◽  
Temporal Correlations ◽  
The North ◽  
The North Atlantic Oscillation ◽  
The Impact

Abstract. In mid and high latitudes, the stable isotope ratio in precipitation is driven by changes in temperature, which control atmospheric distillation. This relationship forms the basis for many continental paleoclimatic reconstructions using direct (e.g. ice cores) or indirect (e.g. tree ring cellulose, speleothem calcite) archives of past precipitation. However, the archiving process is inherently biased by intermittency of precipitation. Here, we use two sets of atmospheric reanalyses (NCEP (National Centers for Environmental Prediction) and ERA-interim) to quantify this precipitation intermittency bias, by comparing seasonal (winter and summer) temperatures estimated with and without precipitation weighting. We show that this bias reaches up to 10 °C and has large interannual variability. We then assess the impact of precipitation intermittency on the strength and stability of temporal correlations between seasonal temperatures and the North Atlantic Oscillation (NAO). Precipitation weighting reduces the correlation between winter NAO and temperature in some areas (e.g. Québec, South-East USA, East Greenland, East Siberia, Mediterranean sector) but does not alter the main patterns of correlation. The correlations between NAO, δ18O in precipitation, temperature and precipitation weighted temperature are investigated using outputs of an atmospheric general circulation model enabled with stable isotopes and nudged using reanalyses (LMDZiso (Laboratoire de Météorologie Dynamique Zoom)). In winter, LMDZiso shows similar correlation values between the NAO and both the precipitation weighted temperature and δ18O in precipitation, thus suggesting limited impacts of moisture origin. Correlations of comparable magnitude are obtained for the available observational evidence (GNIP (Global Network of Isotopes in Precipitation) and Greenland ice core data). Our findings support the use of archives of past δ18O for NAO reconstructions.

scholarly journals Temperature seasonality in the North American continental interior during the early Eocene climatic optimum

2018 ◽  
Author(s):  
Ethan G. Hyland ◽  
Katharine W. Huntington ◽  
Nathan D. Sheldon ◽  
Tammo Reichgelt
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Early Eocene ◽  
Early Eocene Climatic Optimum ◽  
The North ◽  
Annual Range ◽  
Climatic Optimum ◽  
Temperature Records ◽  
Model Ensembles ◽  
Continental Interior

Abstract. Paleogene greenhouse climate equability has long been a paradox in paleoclimate research. However, recent developments in proxy and modeling methods have suggested that strong seasonality may be a feature of at least some greenhouse periods. Here we present the first multi-proxy record of seasonal temperatures during the Paleogene from paleofloras, paleosol geochemistry, and carbonate clumped isotope thermometry in the Green River Basin (Wyoming, USA). These combined temperature records allow for the reconstruction of past seasonality in the continental interior, which shows that temperatures were warmer in all seasons during the peak early Eocene climatic optimum and that the mean annual range of temperature was high, similar to the modern value (~ 26 °C). Proxy data and downscaled Eocene regional climate model results suggest amplified seasonality during greenhouse events. Increased seasonality reconstructed for the early Eocene is similar in scope to the higher seasonal range predicted by downscaled climate model ensembles for future high-CO2 emissions scenarios. Overall, these data and model comparisons have substantial implications for understanding greenhouse climates in general, and may be important for predicting future seasonal climate regimes and their impacts in continental regions.

scholarly journals The Community Firn Model (CFM) v1.0

2020 ◽  
Author(s):  
C. Max Stevens ◽  
Vincent Verjans ◽  
Jessica M.D. Lundin ◽  
Emma C. Kahle ◽  
Annika N. Horlings ◽  
...  
Keyword(s):  
Climate Model ◽  
Noble Gas ◽  
Regional Climate ◽  
Ice Core ◽  
Ice Cores ◽  
Elevation Change ◽  
Model Framework ◽  
Modular Model ◽  
Surface Elevation Change ◽  
Air Diffusion

Abstract. Models that simulate evolution of polar firn are important for several applications in glaciology, including converting ice-sheet elevation-change measurements to mass change and interpreting climate records in ice cores. We have developed the Community Firn Model (CFM), an open-source, modular model framework designed to simulate numerous physical processes in firn. The modules include firn densification, heat transport, meltwater percolation and refreezing, water-isotope diffusion, and firn-air diffusion. The CFM is designed so that new modules can be added with ease. In this paper, we first describe the CFM and its modules. We then demonstrate the CFM's usefulness in two model applications that utilize two of its novel aspects. The CFM currently has the ability to run any of 13 previously published firn-densification models, and in the first application we compare those models' results when they are forced with regional climate model outputs for Summit, Greenland. The results show that the models do not agree well (spread greater than 10 %) when predicting depth-integrated porosity, firn age, or trend in surface-elevation change trend. In the second application, we show that the CFM's coupled firn-air and firn-densification models can simulate noble-gas records from an ice core better than a firn-air model alone.

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