scholarly journals Imprints of climate forcings in global gridded temperature data

2015 ◽  
Vol 6 (2) ◽  
pp. 2339-2381 ◽  
Author(s):  
J. Mikšovský ◽  
E. Holtanová ◽  
P. Pišoft
Keyword(s):  
20Th Century ◽  
Southern Oscillation ◽  
Internal Variability ◽  
Atlantic Multidecadal Oscillation ◽  
Near Surface ◽  
Explanatory Variables ◽  
Teleconnection Patterns ◽  
Internal Climate Variability ◽  
Volcanic Forcing ◽  
Climate Forcings

Abstract. Monthly near-surface temperature anomalies from several gridded datasets (GISTEMP, Berkeley Earth, MLOST, HadCRUT4, 20th Century Reanalysis) were investigated and compared with regard to the presence of components attributable to external climate forcings (anthropogenic, solar and volcanic) and to major internal climate variability modes (El Niño/Southern Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation and variability characterized by the Trans-Polar Index). Multiple linear regression was used to separate components related to individual explanatory variables in local monthly temperatures as well as in their global means, over the 1901–2010 period. Strong correlations of temperature and anthropogenic forcing were confirmed for most of the globe, whereas only weaker and mostly statistically insignificant connections to solar activity were indicated. Imprints of volcanic forcing were found to be largely insignificant in the local temperatures, in contrast to the clear volcanic signature in their global averages. An attention was also paid to the manifestations of short-term time shifts in the responses to the forcings, and to differences in the spatial fingerprints detected from individual temperature datasets: it is shown that although the resemblance of the response patterns is usually strong, some regional contrasts appear. Noteworthy differences from the other datasets were found especially for the 20th Century Reanalysis, particularly for the components attributable to anthropogenic and volcanic forcing over land, but also in some of the teleconnection patterns related to the internal variability modes.

scholarly journals Imprints of climate forcings in global gridded temperature data

2016 ◽  
Vol 7 (1) ◽  
pp. 231-249 ◽  
Author(s):  
Jiří Mikšovský ◽  
Eva Holtanová ◽  
Petr Pišoft
Keyword(s):  
Climate Variability ◽  
20Th Century ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Temperature Data ◽  
Data Sets ◽  
Near Surface ◽  
Anthropogenic Forcing ◽  
Internal Climate Variability ◽  
Climate Forcings

Abstract. Monthly near-surface temperature anomalies from several gridded data sets (GISTEMP, Berkeley Earth, MLOST, HadCRUT4, 20th Century Reanalysis) were investigated and compared with regard to the presence of components attributable to external climate forcings (associated with anthropogenic greenhouse gases, as well as solar and volcanic activity) and to major internal climate variability modes (El Niño/Southern Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation and variability characterized by the Trans-Polar Index). Multiple linear regression was used to separate components related to individual explanatory variables in local monthly temperatures as well as in their global means, over the 1901–2010 period. Strong correlations of temperature and anthropogenic forcing were confirmed for most of the globe, whereas only weaker and mostly statistically insignificant connections to solar activity were indicated. Imprints of volcanic forcing were found to be largely insignificant in the local temperatures, in contrast to the clear volcanic signature in their global averages. Attention was also paid to the manifestations of short-term time shifts in the responses to the forcings, and to differences in the spatial fingerprints detected from individual temperature data sets. It is shown that although the resemblance of the response patterns is usually strong, some regional contrasts appear. Noteworthy differences from the other data sets were found especially for the 20th Century Reanalysis, particularly for the components attributable to anthropogenic forcing over land, but also in the response to volcanism and in some of the teleconnection patterns related to the internal climate variability modes.

scholarly journals Teleconnections and relationship between ENSO and SAM in reconstructions and models over the past millennium

2019 ◽  
Author(s):  
Christoph Dätwyler ◽  
Martin Grosjean ◽  
Nathan J. Steiger ◽  
Raphael Neukom
Keyword(s):  
Climate Model ◽  
Southern Oscillation ◽  
Negative Temperature ◽  
Internal Variability ◽  
Southern Annular Mode ◽  
Teleconnection Patterns ◽  
Modes Of Variability ◽  
Proxy Records ◽  
Climate Model Simulations ◽  
Instrumental Records

Abstract. The climate of the Southern Hemisphere (SH) is strongly influenced by variations in the El Niño-Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). Due to the temporally very limited instrumental records in most parts of the SH, very little is known about the relationship between these two key modes of variability and its stability over time. Here, we use proxy-based reconstructions and climate model simulations to quantify changes in tropical-extratropical SH teleconnections as represented by the correlation between the ENSO and SAM indices. Reconstructions indicate mostly negative correlations back to around 1400 CE confirming the pattern seen in the instrumental record over the last few decades. An ensemble of last millennium simulations of the model CESM1 confirms this pattern with very stable ensemble mean correlations around −0.3. Individual forced simulations, the pre-industrial control run and the proxy-based reconstructions indicate intermittent periods of positive correlations and particularly strong negative correlations. The fluctuations of the ENSO-SAM correlations are not significantly related to solar nor volcanic forcing in both proxy and model data, indicating that they are driven by internal variability in the climate system. Pseudoproxy experiments indicate that the currently available proxy records are able to reproduce the tropical-extratropical teleconnection patterns back to around 1600 CE. We analyse the spatial temperature and sea level pressure patterns during periods of positive and particularly strong negative teleconnections in the CESM model. Results indicate no consistent pattern during periods where the ENSO-SAM teleconnection changes its sign. However, periods of very strong negative SH teleconnections are associated with negative temperature anomalies across large fractions of the extra-tropical Pacific and a strengthening of the Aleutian Low.

scholarly journals Wind speed stilling and its recovery due to internal climate variability

2021 ◽  
Vol 12 (4) ◽  
pp. 1239-1251
Author(s):  
Jan Wohland ◽  
Doris Folini ◽  
Bryn Pickering
Keyword(s):  
Wind Speed ◽  
Climate Variability ◽  
Internal Variability ◽  
Systematic Investigation ◽  
Max Planck ◽  
Near Surface ◽  
Climate Conditions ◽  
Wind Speeds ◽  
Internal Climate Variability ◽  
Long Run

Abstract. Near-surface winds affect many processes on planet Earth, ranging from fundamental biological mechanisms such as pollination to man-made infrastructure that is designed to resist or harness wind. The observed systematic wind speed decline up to around 2010 (stilling) and its subsequent recovery have therefore attracted much attention. While this sequence of downward and upwards trends and good connections to well-established modes of climate variability suggest that stilling could be a manifestation of multidecadal climate variability, a systematic investigation is currently lacking. Here, we use the Max Planck Institute Grand Ensemble (MPI-GE) to decompose internal variability from forced changes in wind speeds. We report that wind speed changes resembling observed stilling and its recovery are well in line with internal climate variability, both under current and future climate conditions. Moreover, internal climate variability outweighs forced changes in wind speeds on 20-year timescales by 1 order of magnitude, despite the fact that smaller, forced changes become relevant in the long run as they represent alterations of mean states. In this regard, we reveal that land use change plays a pivotal role in explaining MPI-GE ensemble-mean wind changes in the representative concentration pathways 2.6, 4.5, and 8.5. Our results demonstrate that multidecadal wind speed variability is of greater relevance than forced changes over the 21st century, in particular for wind-related infrastructure like wind energy.

Trends and Variability in Airmass Frequencies: Indicators of a Changing Climate

2020 ◽  
Vol 33 (19) ◽  
pp. 8603-8617
Author(s):  
Cameron C. Lee
Keyword(s):  
Southern Oscillation ◽  
Weather Conditions ◽  
Atlantic Multidecadal Oscillation ◽  
Global Scale ◽  
Temperature Record ◽  
Near Surface ◽  
Air Masses ◽  
Global Mean Temperature ◽  
Climate Indicators ◽  
Two Indices

AbstractRecent international efforts at communicating climate change have begun using the notion of a climate indicator—a climate-related metric that can be used to track changes in the Earth system over time. Based upon a recently developed global-scale classification of daily air masses, this research examines the trends and variability in the frequencies of these air masses and then utilizes them to develop two nontraditional climate indicators: a warm/cool index (WCI) and a global extremes index (GEI). Results show that both indices trend significantly upward over the 40-yr period of record, indicating an increase in warm-based air masses (WCI) and extreme air masses (GEI). The two indices also exhibit a moderate (GEI) to strong (WCI) association with the global mean temperature record, multiple near-surface climate variables, and other existing climate indicators over that same time, showing promise as global indicators. Shorter-term variability in these indices also show a linear relationship between the WCI and changes in the Atlantic multidecadal oscillation and a nonlinear relationship between GEI and El Niño–Southern Oscillation. While many published climate indicators are based upon a single variable, and/or are regional in scope, the two indices presented herein are unique in that they are representative of the trends in the multivariate (and extreme, in the case of the GEI) weather conditions that are experienced near Earth’s surface, while also being global in scope.

Separating Internal Variability from the Externally Forced Climate Response

2015 ◽  
Vol 28 (20) ◽  
pp. 8184-8202 ◽  
Author(s):  
Leela M. Frankcombe ◽  
Matthew H. England ◽  
Michael E. Mann ◽  
Byron A. Steinman
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Low Frequency ◽  
Internal Variability ◽  
Atlantic Multidecadal Oscillation ◽  
Ensemble Member ◽  
Internal Climate Variability ◽  
Climate Simulations ◽  
Scaling Methods ◽  
Synthetic Time Series

Abstract Separating low-frequency internal variability of the climate system from the forced signal is essential to better understand anthropogenic climate change as well as internal climate variability. Here both synthetic time series and the historical simulations from phase 5 of CMIP (CMIP5) are used to examine several methods of performing this separation. Linear detrending, as is commonly used in studies of low-frequency climate variability, is found to introduce large biases in both amplitude and phase of the estimated internal variability. Using estimates of the forced signal obtained from ensembles of climate simulations can reduce these biases, particularly when the forced signal is scaled to match the historical time series of each ensemble member. These so-called scaling methods also provide estimates of model sensitivities to different types of external forcing. Applying the methods to observations of the Atlantic multidecadal oscillation leads to different estimates of the phase of this mode of variability in recent decades.

scholarly journals Evaluation of Leading Modes of Climate Variability in the CMIP Archives

2020 ◽  
Vol 33 (13) ◽  
pp. 5527-5545 ◽  
Author(s):  
John T. Fasullo ◽  
A. S. Phillips ◽  
C. Deser
Keyword(s):  
Climate Variability ◽  
Southern Oscillation ◽  
Internal Variability ◽  
Intrinsic Variability ◽  
Annular Modes ◽  
Internal Climate Variability ◽  
The North ◽  
The Pacific ◽  
The North Atlantic Oscillation ◽  
Modes Of Climate Variability

AbstractThe adequate simulation of internal climate variability is key for our understanding of climate as it underpins efforts to attribute historical events, predict on seasonal and decadal time scales, and isolate the effects of climate change. Here the skill of models in reproducing observed modes of climate variability is assessed, both across and within the CMIP3, CMIP5, and CMIP6 archives, in order to document model capabilities, progress across ensembles, and persisting biases. A focus is given to the well-observed tropical and extratropical modes that exhibit small intrinsic variability relative to model structural uncertainty. These include El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the North Atlantic Oscillation (NAO), and the northern and southern annular modes (NAM and SAM). Significant improvements are identified in models’ representation of many modes. Canonical biases, which involve both amplitudes and patterns, are generally reduced across model generations. For example, biases in ENSO-related equatorial Pacific sea surface temperature, which extend too far westward, and associated atmospheric teleconnections, which are too weak, are reduced. Stronger tropical expression of the PDO in successive CMIP generations has characterized their improvement, with some CMIP6 models generating patterns that lie within the range of observed estimates. For the NAO, NAM, and SAM, pattern correlations with observations are generally higher than for other modes and slight improvements are identified across successive model generations. For ENSO and PDO spectra and extratropical modes, changes are small compared to internal variability, precluding definitive statements regarding improvement.

scholarly journals How large does a large ensemble need to be?

2020 ◽  
Vol 11 (4) ◽  
pp. 885-901
Author(s):  
Sebastian Milinski ◽  
Nicola Maher ◽  
Dirk Olonscheck
Keyword(s):  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Forced Response ◽  
Ensemble Size ◽  
Max Planck ◽  
Large Ensemble ◽  
Acceptable Error ◽  
Near Surface ◽  
Temperature And Precipitation

Abstract. Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool for quantifying the forced response and internal variability in various components of the climate system. However, there is no consensus on the ideal or even sufficient ensemble size for a large ensemble. Here, we introduce an objective method to estimate the required ensemble size that can be applied to any given application and demonstrate its use on the examples of global mean near-surface air temperature, local temperature and precipitation, and variability in the El Niño–Southern Oscillation (ENSO) region and central United States for the Max Planck Institute Grand Ensemble (MPI-GE). Estimating the required ensemble size is relevant not only for designing or choosing a large ensemble but also for designing targeted sensitivity experiments with a model. Where possible, we base our estimate of the required ensemble size on the pre-industrial control simulation, which is available for every model. We show that more ensemble members are needed to quantify variability than the forced response, with the largest ensemble sizes needed to detect changes in internal variability itself. Finally, we highlight that the required ensemble size depends on both the acceptable error to the user and the studied quantity.

scholarly journals Modeling of severe persistent droughts over eastern China during the last millennium

2014 ◽  
Vol 10 (3) ◽  
pp. 1079-1091 ◽  
Author(s):  
Y. Peng ◽  
C. Shen ◽  
H. Cheng ◽  
Y. Xu
Keyword(s):  
Southern Oscillation ◽  
Asian Summer Monsoon ◽  
Eastern China ◽  
Volcanic Eruptions ◽  
Internal Variability ◽  
Last Millennium ◽  
Proxy Data ◽  
Monsoon Variability ◽  
Primary Driver ◽  
Climate Forcings

Abstract. We use proxy data and modeled data from 1000 year model simulations with a variety of climate forcings to examine the occurrence of severe event of persistent drought over eastern China during the last millennium and diagnose the mechanisms. Results show that the model was able to roughly simulate most of these droughts over the study area during the last millennium such as those that occurred during the periods of 1123–1152, 1197–1223, 1353–1363, 1428–1449, 1479–1513, and 1632–1645. Our analyses suggest that these six well-captured droughts may caused by the East Asian summer monsoon (EASM) weakening. Study on the wavelet transform and spectral analysis reveals these events occurred all at the statistically significant 15–35-year timescale. A modeled data intercomparison suggests the possibility that solar activity may be the primary driver in the occurrence of the 1129–1144, 1354–1365, 1466–1491 and 1631–1648 droughts as identified by the model. However another possibility that these events may be related to internal variability cannot be excluded. Although the El Niño–Southern Oscillation (ENSO) plays an important role in monsoon variability, a temporally consistent relationship between the droughts and SST pattern in the Pacific Ocean could not be found either in the modeled or proxy data. Our analyses also indicate that large volcanic eruptions play a role as an amplifier in the drought of 1631–1648 and caused the droughts of 1830–1853 and 1958–1976, which was identified by the model.

scholarly journals Variability of extreme precipitation over Europe and its relationships with teleconnection patterns

2013 ◽  
Vol 10 (10) ◽  
pp. 12331-12371 ◽  
Author(s):  
A. Casanueva ◽  
C. Rodríguez-Puebla ◽  
M. D. Frías ◽  
N. González-Reviriego
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Southern Oscillation ◽  
Global Climate ◽  
Atlantic Multidecadal Oscillation ◽  
Physical Factors ◽  
Teleconnection Patterns ◽  
The North ◽  
The North Atlantic Oscillation

Abstract. A growing interest in extreme precipitation has spread through the scientific community due to the effects of global climate change on the hydrological cycle and their threat on natural systems more than averaged climatic values. Understanding the variability of hydrological indices and their association to atmospheric processes could help to project the frequency and severity of extremes. This paper evaluates the trend of three precipitation extremes: the number of consecutive dry/wet days (CDD/CWD) and the quotient of the precipitation in days where daily precipitation exceeds the 95th percentile of the reference period and the total amount of precipitation (or contribution of very wet days, R95pTOT). The aim of this study is twofold. First, extreme indicators are compared against accumulated precipitation (RR) over Europe in terms of trends using non-parametric approaches. Second, we analyse the geographic opposite trends found over different parts of Europe by considering their relationships with large-scale processes, using different teleconnection patterns. The study is accomplished for the four seasons using the gridded E-OBS dataset developed within the EU ENSEMBLES project. Different patterns of variability were found for CWD and CDD in winter and summer, with north-south and east–west configurations, respectively. We consider physical factors to understand the extremes variability by linking large-scale processes and hydrological extremes. Opposite association with the North Atlantic Oscillation in winter and summer, and the relationships with the Scandinavian, East Atlantic patterns and El Niño/Southern Oscillation events in spring and autumn gave insight into the trend differences. Significant relationships were found between the Atlantic Multidecadal Oscillation and very extreme precipitation (R95pTOT) during the whole year. The largest extreme anomalies were analysed by composite maps using atmospheric variables and sea surface temperature. The association of extreme precipitation indices and large-scale variables found in this work could pave the way of new possibilities for the projection of extremes in downscaling techniques.

Nonlinear components in global climate teleconnections

2020 ◽  
Author(s):  
Jiří Mikšovský
Keyword(s):  
Long Range ◽  
Target Location ◽  
Southern Oscillation ◽  
Global Climate ◽  
Internal Variability ◽  
Atlantic Multidecadal Oscillation ◽  
Surrogate Data ◽  
Oscillatory Behavior ◽  
Climate System ◽  
Nonlinear Components

<p>Among the sources of temporal variability in the climate system, an important role belongs to internal variability modes – phenomena with oscillatory behavior ranging from predominantly sub-annual (e.g. North Atlantic Oscillation) or inter-annual (e.g. Southern Oscillation) to decadal or multidecadal variations (e.g. Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation). These oscillations manifest themselves not only within their particular geographical areas of origin, but their effects are typically also transmitted through long-range teleconnections, affecting weather and climate patterns worldwide. Analysis of these relationships is often done assuming their linearity – but rarely is such assumption explicitly verified.</p><p>In this presentation, presence and magnitude of nonlinear components in long-range teleconnections associated with selected climate variability modes are studied through various time series analysis methods. Several nonlinearity-quantifying statistics, ranging from simple measures of asymmetry in the regression coefficients to outcomes of more formal surrogate data-based tests, are employed to investigate the teleconnection-related responses of local temperatures across the globe. It is shown that substantial variations exist in degree of manifested nonlinearity, subject to both the target location and type of the variability mode(s) considered. Potential of individual nonlinearity-sensitive techniques for more realistic capture of the teleconnection-related response patterns is also discussed, with an ultimate goal of construction of a more accurate model of variability transfer in the climate system.</p>

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