scholarly journals Northern high-latitude climate change between the mid and late Holocene – Part 1: Proxy data evidence

2009 ◽  
Vol 5 (4) ◽  
pp. 1819-1852 ◽  
Author(s):  
H. S. Sundqvist ◽  
Q. Zhang ◽  
A. Moberg ◽  
K. Holmgren ◽  
H. Körnich ◽  
...  
Keyword(s):  
Climate Model ◽  
Cold Season ◽  
High Latitudes ◽  
Proxy Data ◽  
Summer Insolation ◽  
Temperature And Precipitation ◽  
Northern High Latitude ◽  
Quantitative Understanding ◽  
Climate Model Simulations ◽  
Using Data

Abstract. In this paper we try to develop a quantitative understanding of the absolute change in climate between the mid-Holocene ~6000 yr BP (6 ka) and the preindustrial period ~1750 AD (0 ka) in the northern high latitudes. This has been performed using available quantitative reconstructions of temperature and precipitation from proxy data. The main reason for comparing these two periods is that the summer insolation in the northern high latitudes was higher at 6 ka than 0 ka due to orbital forcing. Another reason is that it gives us the opportunity to quantitatively compare results from proxy data with results from several climate model simulations for the same periods by using data from the Palaeoclimate Modelling Intercomparison Project. Another aim has been to try and quantify the uncertainties in the proxy data reconstructions. The reconstructions indicate that the northern high latitudes were 0.96±0.42°C warmer in summer, 1.71±1.70°C warmer in winter and 2.02±0.72 warmer in the annual mean temperature at 6 ka compared to 0 ka. The warmer climate in summer around 6 ka BP was most likely directly related to the higher summer insolation whereas the warmer climate in annual mean and winter temperature may possibly be explained by internal physical mechanisms such as heat stored in the oceans during summer and released during the cold season or by changes in the vegetation causing albedo changes that may affect seasonal temperatures differentially. For the future there is a great need to reduce the errors of the predictions as well as improving our understanding of how a proxys respond to changes in environmental variables.

scholarly journals Climate change between the mid and late Holocene in northern high latitudes – Part 1: Survey of temperature and precipitation proxy data

2010 ◽  
Vol 6 (5) ◽  
pp. 591-608 ◽  
Author(s):  
H. S. Sundqvist ◽  
Q. Zhang ◽  
A. Moberg ◽  
K. Holmgren ◽  
H. Körnich ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Arctic Region ◽  
High Latitudes ◽  
Proxy Data ◽  
Atlantic Sector ◽  
Proxy Records ◽  
Temperature And Precipitation ◽  
Calibration Uncertainty ◽  
Reconstructed Temperature

Abstract. We undertake a study in two parts, where the overall aim is to quantitatively compare results from climate proxy data with results from several climate model simulations from the Paleoclimate Modelling Intercomparison Project for the mid-Holocene period and the pre-industrial, conditions for the pan-arctic region, north of 60° N. In this first paper, we survey the available published local temperature and precipitation proxy records. We also discuss and quantifiy some uncertainties in the estimated difference in climate between the two periods as recorded in the available data. The spatial distribution of available published local proxies has a marked geographical bias towards land areas surrounding the North Atlantic sector, especially Fennoscandia. The majority of the reconstructions are terrestrial, and there is a large over-representation towards summer temperature records. The available reconstructions indicate that the northern high latitudes were warmer in both summer, winter and the in annual mean temperature at the mid-Holocene (6000 BP ± 500 yrs) compared to the pre-industrial period (1500 AD ± 500 yrs). For usage in the model-data comparisons (in Part 1), we estimate the calibration uncertainty and also the internal variability in the proxy records, to derive a combined minimum uncertainty in the reconstructed temperature change between the two periods. Often, the calibration uncertainty alone, at a certain site, exceeds the actual reconstructed climate change at the site level. In high-density regions, however, neighbouring records can be merged into a composite record to increase the signal-to-noise ratio. The challenge of producing reliable inferred climate reconstructions for the Holocene cannot be underestimated, considering the fact that the estimated temperature and precipitation fluctuations during this period are in magnitude similar to, or lower than, the uncertainties the reconstructions. We advocate a more widespread practice of archiving proxy records as most of the potentially available reconstructions are not published in digital form.

scholarly journals Greenland temperature and precipitation over the last 20 000 years using data assimilation

2020 ◽  
Vol 16 (4) ◽  
pp. 1325-1346
Author(s):  
Jessica A. Badgeley ◽  
Eric J. Steig ◽  
Gregory J. Hakim ◽  
Tyler J. Fudge
Keyword(s):  
Data Assimilation ◽  
Spatial Patterns ◽  
Climate Model ◽  
Ice Core ◽  
Ice Sheet ◽  
Proxy Data ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations ◽  
Paleoclimate Data

Abstract. Reconstructions of past temperature and precipitation are fundamental to modeling the Greenland Ice Sheet and assessing its sensitivity to climate. Paleoclimate information is sourced from proxy records and climate-model simulations; however, the former are spatially incomplete while the latter are sensitive to model dynamics and boundary conditions. Efforts to combine these sources of information to reconstruct spatial patterns of Greenland climate over glacial–interglacial cycles have been limited by assumptions of fixed spatial patterns and a restricted use of proxy data. We avoid these limitations by using paleoclimate data assimilation to create independent reconstructions of mean-annual temperature and precipitation for the last 20 000 years. Our method uses oxygen isotope ratios of ice and accumulation rates from long ice-core records and extends this information to all locations across Greenland using spatial relationships derived from a transient climate-model simulation. Standard evaluation metrics for this method show that our results capture climate at locations without ice-core records. Our results differ from previous work in the reconstructed spatial pattern of temperature change during abrupt climate transitions; this indicates a need for additional proxy data and additional transient climate-model simulations. We investigate the relationship between precipitation and temperature, finding that it is frequency dependent and spatially variable, suggesting that thermodynamic scaling methods commonly used in ice-sheet modeling are overly simplistic. Our results demonstrate that paleoclimate data assimilation is a useful tool for reconstructing the spatial and temporal patterns of past climate on timescales relevant to ice sheets.

scholarly journals Emerging Anthropogenic Influences on the Southcentral Alaska Temperature and Precipitation Extremes and Related Fires in 2019

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 82
Author(s):  
Uma S. Bhatt ◽  
Rick T. Lader ◽  
John E. Walsh ◽  
Peter A. Bieniek ◽  
Richard Thoman ◽  
...  
Keyword(s):  
Climate Model ◽  
Simulation Analysis ◽  
Historical Context ◽  
Fire Risk ◽  
Internal Variability ◽  
Fire Season ◽  
Temperature And Precipitation ◽  
Southcentral Alaska ◽  
Meteorological Observations ◽  
Climate Model Simulations

The late-season extreme fire activity in Southcentral Alaska during 2019 was highly unusual and consequential. Firefighting operations had to be extended by a month in 2019 due to the extreme conditions of hot summer temperature and prolonged drought. The ongoing fires created poor air quality in the region containing most of Alaska’s population, leading to substantial impacts to public health. Suppression costs totaled over $70 million for Southcentral Alaska. This study’s main goals are to place the 2019 season into historical context, provide an attribution analysis, and assess future changes in wildfire risk in the region. The primary tools are meteorological observations and climate model simulations from the NCAR CESM Large Ensemble (LENS). The 2019 fire season in Southcentral Alaska included the hottest and driest June–August season over the 1979–2019 period. The LENS simulation analysis suggests that the anthropogenic signal of increased fire risk had not yet emerged in 2019 because of the CESM’s internal variability, but that the anthropogenic signal will emerge by the 2040–2080 period. The effect of warming temperatures dominates the effect of enhanced precipitation in the trend towards increased fire risk.

scholarly journals The DeepMIP contribution to PMIP4: methodologies for selection, compilation and analysis of latest Paleocene and early Eocene climate proxy data, incorporating version 0.1 of the DeepMIP database

2019 ◽  
Vol 12 (7) ◽  
pp. 3149-3206 ◽  
Author(s):  
Christopher J. Hollis ◽  
Tom Dunkley Jones ◽  
Eleni Anagnostou ◽  
Peter K. Bijl ◽  
Margot J. Cramwinckel ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Early Eocene ◽  
Proxy Data ◽  
Time Model ◽  
Deep Time ◽  
Climate Proxy ◽  
Early Eocene Climatic Optimum ◽  
Climate Model Simulations ◽  
Atmospheric Co2 Concentrations

Abstract. The early Eocene (56 to 48 million years ago) is inferred to have been the most recent time that Earth's atmospheric CO2 concentrations exceeded 1000 ppm. Global mean temperatures were also substantially warmer than those of the present day. As such, the study of early Eocene climate provides insight into how a super-warm Earth system behaves and offers an opportunity to evaluate climate models under conditions of high greenhouse gas forcing. The Deep Time Model Intercomparison Project (DeepMIP) is a systematic model–model and model–data intercomparison of three early Paleogene time slices: latest Paleocene, Paleocene–Eocene thermal maximum (PETM) and early Eocene climatic optimum (EECO). A previous article outlined the model experimental design for climate model simulations. In this article, we outline the methodologies to be used for the compilation and analysis of climate proxy data, primarily proxies for temperature and CO2. This paper establishes the protocols for a concerted and coordinated effort to compile the climate proxy records across a wide geographic range. The resulting climate “atlas” will be used to constrain and evaluate climate models for the three selected time intervals and provide insights into the mechanisms that control these warm climate states. We provide version 0.1 of this database, in anticipation that this will be expanded in subsequent publications.

Quantifying uncertainty in projections of future European climate: a multi-model multi-method approach

2020 ◽  
Author(s):  
Lukas Brunner ◽  
Carol McSweeney ◽  
Daniel Befort ◽  
Chris O'Reilly ◽  
Ben Booth ◽  
...  
Keyword(s):  
Climate Model ◽  
Probability Distributions ◽  
Internal Variability ◽  
Precipitation Change ◽  
Future Climate Change ◽  
Climate Projections ◽  
Temperature And Precipitation ◽  
European Climate ◽  
Climate Model Simulations ◽  
Quantifying Uncertainty

<p>Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. Different approaches to constrain, filter, or weight climate model simulations into probabilistic projections have been proposed to provide such estimates. Here six methods are applied to European climate projections using a consistent framework in order to allow a quantitative comparison.  Focus is given to summer temperature and precipitation change in three different spatial regimes in Europe in the period 2041-2060 relative to 1995-2014. The analysis draws on projections from several large initial condition ensembles, the CMIP5 multi-model ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5.  <br>The methods included are diverse in their approach to quantifying uncertainty, and include those which apply weighting schemes based on baseline performance and inter-model relationships, so-called ASK (Allen, Stott and Kettleborough) techniques which use optimal fingerprinting to scale the scale the response to external forcings, to those found in observations and Bayesian approaches to estimating probability distributions. Some of the key differences between methods are the uncertainties covered, the treatment of internal variability, and variables and regions used to inform the methods. In spite of these considerable methodological differences, the median projection from the multi-model methods agree on a statistically significant increase in temperature by mid-century by about 2.5°C in the European average. The estimates of spread, in contrast, differ substantially between methods. Part of this large difference in the spread reflects the fact that different methods attempt to capture different sources of uncertainty, and some are more comprehensive in this respect than others. This study, therefore, highlights the importance of providing clear context about how different methods affect the distribution of projections, particularly the in the upper and lower percentiles that are of interest to 'risk averse' stakeholders. Methods find less agreement in precipitation change with most methods indicating a slight increase in northern Europe and a drying in the central and Mediterranean regions, but with considerably different amplitudes. Further work is needed to understand how the underlying differences between methods lead to such diverse results for precipitation. </p>

scholarly journals Joint bias correction of temperature and precipitation in climate model simulations

2014 ◽  
Vol 119 (23) ◽  
pp. 13,153-13,162 ◽  
Author(s):  
Chao Li ◽  
Eva Sinha ◽  
Daniel E. Horton ◽  
Noah S. Diffenbaugh ◽  
Anna M. Michalak
Keyword(s):  
Bias Correction ◽  
Climate Model ◽  
Model Simulations ◽  
Temperature And Precipitation ◽  
Climate Model Simulations

PMIP4/CMIP6 last interglacial simulations using three different versions of MIROC: importance of vegetation

2021 ◽  
Author(s):  
Ryouta O'ishi ◽  
Wing-Le Chan ◽  
Ayako Abe-Ouchi ◽  
Sam Sherriff-Tadano ◽  
Rumi Ohgaito ◽  
...  
Keyword(s):  
Feedback Mechanism ◽  
Climate Feedback ◽  
High Latitudes ◽  
Last Interglacial ◽  
Proxy Data ◽  
Area Index ◽  
Vegetation Feedback ◽  
Temperature Changes ◽  
Northern High Latitude ◽  
Series Of Experiments

<p>We carry out three sets of last interglacial (LIG) experiments, named lig127k, and of pre-industrial experiments, named piControl, both as part of PMIP4/CMIP6 using three versions of the MIROC model: MIROC4m, MIROC4m-LPJ, and MIROC-ES2L. The results are compared with reconstructions from climate proxy data. All models show summer warming over northern high-latitude land, reflecting the differences between the distributions of the LIG and present-day solar irradiance. Globally averaged temperature changes are −0.94 K (MIROC4m), −0.39 K (MIROC4m-LPJ), and −0.43 K (MIROC-ES2L).<br>Only MIROC4m-LPJ, which includes dynamical vegetation feedback from the change in vegetation distribution, shows annual mean warming signals at northern high latitudes, as indicated by proxy data. In contrast, the latest Earth system model (ESM) of MIROC, MIROC-ES2L, which considers only a partial vegetation effect through the leaf area index, shows no change or even annual cooling over large parts of the Northern Hemisphere. Results from the series of experiments show that the inclusion of full vegetation feedback is necessary for the reproduction of the strong annual warming over land at northern high latitudes. The LIG experimental results show that the warming predicted by models is still underestimated, even with dynamical vegetation, compared to reconstructions from proxy data, suggesting that further investigation and improvement to the climate feedback mechanism are needed.</p>

scholarly journals Perturbing a Weather Generator using change factors derived from Regional Climate Model simulations

2011 ◽  
Vol 18 (4) ◽  
pp. 503-511 ◽  
Author(s):  
P. D. Jones ◽  
C. Harpham ◽  
C. M. Goodess ◽  
C. G. Kilsby
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Study Data ◽  
Distant Future ◽  
Change Factors ◽  
Unseen Data ◽  
Climate Model Simulations ◽  
Using Data

Abstract. The purpose of this paper is to provide a method for perturbing Weather Generators (WGs) for future decades and to assess its effectiveness. Here the procedure is applied to the WG implemented within the UKCP09 package and assessed using data from a Regional Climate Model (RCM) simulation which provides a significant "climate change" between a control run period and a distant future. The WG is normally calibrated on observed data. For this study, data from an RCM control period (1961–1990) was used, then perturbed using the procedure. Because only monthly differences between the RCM control and scenario periods are used to perturb the WG, the direct daily RCM scenario may be considered as unseen data to assess how well the perturbation procedure reproduces the direct RCM simulations for the future.

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