Do CMIP5 emergent constraints on the large scale atmospheric circulation work to constrain CMIP6 projections?

2020 ◽  
Author(s):  
Isla Simpson ◽  
Fances Davenport ◽  
Abdullah Al Fahad ◽  
Flavio Lehner
Keyword(s):  
Atmospheric Circulation ◽  
Large Scale ◽  
Coupled Model ◽  
Internal Variability ◽  
Stationary Waves ◽  
Projected Change ◽  
Emergent Constraints ◽  
Out Of Sample ◽  
Emergent Constraint ◽  
Large Scale Atmospheric Circulation

<p>Accurate future projections of the climate system are hindered by a number of sources of uncertainty: forcing uncertainty, internal variability and model structural uncertainty. An ``Emergent constraint'' is a technique that has been devised to reduce projection uncertainties arising from the model structural component. It consists of a statistical relationship (across a model ensemble) between a model’s representation of some aspect of the present day climate and its future projected climate change. This relationship can then be used to imply the future projected change, given the observed value of that present-day aspect. However, in order for the emergent constraint to be considered robust it must: (a) be accompanied by a physical mechanism and (b) be robust to out-of-sample testing.</p><p> </p><p>In prior Coupled Model Intercomparison Projects (CMIP), in particular CMIP5, a number of emergent constraints on the large scale atmospheric circulation were proposed, with implications for regional hydroclimate change. These include: (1) a relationship between a model’s climatological jet latitude and its future projected poleward shift in the Southern Hemisphere; (2) a relationship between a model’s future projected wintertime circulation and hydroclimate change over North America and its climatological representation of stationary waves in the North Pacific; and (3) a relationship between a model’s future projected precipitation change over California and its representation of the relationship between ENSO and California precipitation. Constraints (2) and (3) actually imply opposite constraints on California precipitation changes for the real world, which speaks to the need for a deeper understanding of these emergent constraints and a comprehensive assessment of their robustness.</p><p> </p><p>While the CMIP6 archive does not represent a true ``out-of-sample’’ test of CMIP5 emergent constraints, it does provide us with a new dataset composed of new and/or more advanced models in which to assess their robustness. This presentation will review the proposed emergent constraints on the large-scale atmospheric circulation and assess whether or not they are robust across both the CMIP5 and CMIP6 ensembles. Their potential for constraining regional hydroclimate projections will also be discussed.</p><p> </p>

Emergent constraints on the large scale atmospheric circulation and regional hydroclimate: do they still work in CMIP6 and how much can they actually constrain the future?

2021 ◽  
pp. 1-62
Author(s):  
Isla R. Simpson ◽  
Karen A. McKinnon ◽  
Frances V. Davenport ◽  
Martin Tingley ◽  
Flavio Lehner ◽  
...  
Keyword(s):  
Large Scale ◽  
Coupled Model ◽  
Internal Variability ◽  
Stationary Wave ◽  
Meridional Wind ◽  
Least Squares Regression ◽  
Enso Teleconnections ◽  
Projected Change ◽  
Out Of Sample ◽  
The Relationship

AbstractAn ‘emergent constraint’ (EC) is a statistical relationship, across a model ensemble, between a measurable aspect of the present day climate (the predictor) and an aspect of future projected climate change (the predictand). If such a relationship is robust and understood, it may provide constrained projections for the real world. Here, Coupled Model Intercomparison Project 6 (CMIP6) models are used to revisit several ECs that were proposed in prior model intercomparisons with two aims: (1) to assess whether these ECs survive the partial out-of-sample test of CMIP6 and (2) to more rigorously quantify the constrained projected change than previous studies. To achieve the latter, methods are proposed whereby uncertainties can be appropriately accounted for, including the influence of internal variability, uncertainty on the linear relationship, and the uncertainty associated with model structural differences, aside from those described by the EC. Both least squares regression and a Bayesian Hierarchical Model are used. Three ECs are assessed: (a) the relationship between Southern Hemisphere jet latitude and projected jet shift, which is found to be a robust and quantitatively useful constraint on future projections; (b) the relationship between stationary wave amplitude in the Pacific-North American sector and meridional wind changes over North America (with extensions to hydroclimate), which is found to be robust but improvements in the predictor in CMIP6 result in it no longer substantially constrains projected change in either circulation or hydroclimate; and (c) the relationship between ENSO teleconnections to California and California precipitation change, which does not appear to be robust when using historical ENSO teleconnections as the predictor.

scholarly journals Projections of northern hemisphere extratropical climate underestimate internal variability and associated uncertainty

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Christopher H. O’Reilly ◽  
Daniel J. Befort ◽  
Antje Weisheimer ◽  
Tim Woollings ◽  
Andrew Ballinger ◽  
...  
Keyword(s):  
Climate Variability ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Internal Variability ◽  
Uncertainty Range ◽  
Coupled Climate Models ◽  
Large Scale Atmospheric Circulation

AbstractInternal climate variability will play a major role in determining change on regional scales under global warming. In the extratropics, large-scale atmospheric circulation is responsible for much of observed regional climate variability, from seasonal to multidecadal timescales. However, the extratropical circulation variability on multidecadal timescales is systematically weaker in coupled climate models. Here we show that projections of future extratropical climate from coupled model simulations significantly underestimate the projected uncertainty range originating from large-scale atmospheric circulation variability. Using observational datasets and large ensembles of coupled climate models, we produce synthetic ensemble projections constrained to have variability consistent with the large-scale atmospheric circulation in observations. Compared to the raw model projections, the synthetic observationally-constrained projections exhibit an increased uncertainty in projected 21st century temperature and precipitation changes across much of the Northern extratropics. This increased uncertainty is also associated with an increase of the projected occurrence of future extreme seasons.

scholarly journals Winter hydrometeorological extreme events modulated by large scale atmospheric circulation in southern Ontario

2019 ◽  
Author(s):  
Olivier Champagne ◽  
Martin Leduc ◽  
Paulin Coulibaly ◽  
M. Altaf Arain
Keyword(s):  
Atmospheric Circulation ◽  
Extreme Events ◽  
Large Scale ◽  
Internal Variability ◽  
Southern Ontario ◽  
Future Evolution ◽  
The Past ◽  
The Future ◽  
High Flows ◽  
Large Scale Atmospheric Circulation

Abstract. Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in term of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. Rain on Snow index has been widely used but it neglects rain only events which are expected to be more frequent in the future. In this study we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model Large Ensemble (CRCM5-LE). These climate data were used as input in PRMS hydrological model to simulate the future evolution of high flows in three watersheds in Southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in northeastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10 mm and temperature higher than 5 °C were a necessary historical condition to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated to two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP) and the Atlantic Ocean (South). These hydrometeorological extreme events will be more frequent in the near future and will still be associated to the same atmospheric patterns. The future evolution of the index will be modulated by the internal variability of the climate system as higher Z500 in the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high flows generation. This study shows the values of CRCM5-LE dataset to simulate hydrometeorological extreme events in Eastern Canada and to better understand the uncertainties associated to internal variability of climate.

scholarly journals Winter hydrometeorological extreme events modulated by large-scale atmospheric circulation in southern Ontario

2020 ◽  
Vol 11 (1) ◽  
pp. 301-318 ◽  
Author(s):  
Olivier Champagne ◽  
Martin Leduc ◽  
Paulin Coulibaly ◽  
M. Altaf Arain
Keyword(s):  
Atmospheric Circulation ◽  
Extreme Events ◽  
Large Scale ◽  
Internal Variability ◽  
Southern Ontario ◽  
Future Evolution ◽  
The Past ◽  
The Future ◽  
High Flows ◽  
Large Scale Atmospheric Circulation

Abstract. Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. The rain on snow index has been widely used, but it neglects rain-only events which are expected to be more frequent in the future. In this study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model large ensemble (CRCM5-LE). These climate data were used as input in Precipitation Runoff Modelling System (PRMS) hydrological model to simulate the future evolution of high flows in three watersheds in southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in north-eastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10 mm and temperature higher than 5 ∘C were necessary historical conditions to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP regime) and the Atlantic Ocean (South regime). These hydrometeorological extreme events will still be associated with the same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal variability of the climate system, as higher Z500 on the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high-flow generation. This study shows the value of the CRCM5-LE dataset in simulating hydrometeorological extreme events in eastern Canada and better understanding the uncertainties associated with internal variability of climate.

scholarly journals Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

2017 ◽  
Vol 8 (4) ◽  
pp. 963-976 ◽  
Author(s):  
Jaak Jaagus ◽  
Mait Sepp ◽  
Toomas Tamm ◽  
Arvo Järvet ◽  
Kiira Mõisja
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
Large Scale ◽  
Regime Shifts ◽  
The Arctic ◽  
Dry Period ◽  
Snow Cover Duration ◽  
Large Scale Atmospheric Circulation

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.

scholarly journals Impact of climate change on groundwater point discharge: backflooding of karstic springs (Loiret, France)

2011 ◽  
Vol 8 (2) ◽  
pp. 2235-2262
Author(s):  
E. Joigneaux ◽  
P. Albéric ◽  
H. Pauwels ◽  
C. Pagé ◽  
L. Terray ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Groundwater Quality ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Weather Type ◽  
Future Climate Change ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Large Scale Atmospheric Circulation

Abstract. Under certain hydrological conditions it is possible for spring flow in karst systems to be reversed. When this occurs, the resulting invasion by surface water, i.e. the backflooding, represents a serious threat to groundwater quality because the surface water could well be contaminated. Here we examine the possible impact of future climate change on the occurrences of backflooding in a specific karst system, having first established the occurrence of such events in the selected study area over the past 40 yr. It would appear that backflooding has been more frequent since the 1980s, and that it is apparently linked to river flow variability on the pluri-annual scale. The avenue that we adopt here for studying recent and future variations of these events is based on a downscaling algorithm relating large-scale atmospheric circulation to local precipitation spatial patterns. The large-scale atmospheric circulation is viewed as a set of quasi-stationary and recurrent states, called weather types, and its variability as the transition between them. Based on a set of climate model projections, simulated changes in weather-type occurrence for the end of the century suggests that backflooding events can be expected to decrease in 2075–2099. If such is the case, then the potential risk for groundwater quality in the area will be greatly reduced compared to the current situation. Finally, our results also show the potential interest of the weather-type based downscaling approach for examining the impact of climate change on hydrological systems.

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