scholarly journals Cross-Seasonal Relationship between the Boreal Autumn SAM and Winter Precipitation in the Northern Hemisphere in CMIP5

2016 ◽  
Vol 29 (18) ◽  
pp. 6617-6636 ◽  
Author(s):  
Ting Liu ◽  
Jianping Li ◽  
Juan Feng ◽  
Xiaofan Wang ◽  
Yang Li
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Decisive Role ◽  
Winter Precipitation ◽  
Systematic Evaluation ◽  
Cmip5 Models ◽  
Type I ◽  
Sst Variability ◽  
Ocean Atmosphere ◽  
The Cross

Abstract Recent work suggests that the boreal autumn Southern Hemisphere annular mode (SAM) favors a tripole pattern of winter precipitation anomalies in the Northern Hemisphere. This study focuses on the abilities of climate models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to reproduce the physical processes involved in this observed cross-seasonal connection. A systematic evaluation suggested that 16 out of 25 models were essentially capable of reproducing this cross-seasonal connection. Two categories of models were selected to explore the underlying reasons for these successful simulations. Models that successfully simulated the cross-seasonal relationship were placed in the type-I category, and these performed well in reproducing the related physical mechanism, known as the “coupled ocean–atmosphere bridge,” in terms of the SST variability associated with the SAM and response of the meridional circulation to these SST anomalies. In contrast, the type-II category of models showed poor performance in representing the related processes and associated feedbacks, and the model biases compromised the performance of the simulated cross-seasonal relationship. These results demonstrate that the capability of the CMIP5 models to reproduce SST variability associated with the boreal autumn SAM and related coupled ocean–atmosphere bridge process plays a decisive role in the successful simulation of the cross-seasonal relationship.

Evaluation of snow albedo feedback simulated by CMIP6 coupled climate models

2020 ◽  
Author(s):  
jiangling hu ◽  
duoying ji
Keyword(s):  
Climate Change ◽  
Northern Hemisphere ◽  
Land Surface ◽  
Climate Models ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Simulation Research ◽  
Albedo Feedback ◽  
Snow Albedo ◽  
Autumn And Winter

<p>As the land surface warms, a subsequent reduction in snow and ice cover reveals a less reflective surface that absorbs more solar radiation, which further enhances the initial warming. This positive feedback climate mechanism is the snow albedo feedback (SAF), which will exacerbate climate warming and is the second largest contributor to Arctic amplification. Snow albedo feedback will increase the sensitivity of climate change in the northern hemisphere, which affects the accuracy of climate models in simulation research of climate change, and further affects the credibility of future climate prediction results.</p><p>Using the latest generation of climate models from CMIP6 (Coupled Model Intercomparison Project Version 6), we analyze seasonal cycle snow albedo feedback in Northern Hemisphere extratropics. We find that the strongest SAF strength is in spring (mean: -1.34 %K<sup>-1</sup>), second strongest is autumn (mean: -1.01 %K<sup>-1</sup>), the weakest is in summer (mean: -0.18 %K<sup>-1</sup>). Except summer, the SAF strength is approximately 0.15% K<sup>-1</sup> larger than CMIP5 models in the other three seasons. The spread of spring SAF strength (range: -1.09 to -1.37% K<sup>-1</sup>) is larger than CMIP5 models. Oppositely, the spread of summer SAF strength (range: 0.20 to -0.56% K<sup>-1</sup>) is smaller than CMIP5 models. When compared with CMIP5 models, the spread of autumn and winter SAF strength have not changed much.</p>

scholarly journals 21st century changes in snow water equivalent over Northern Hemisphere landmasses due to increasing temperature, projected with the CMIP5 models

2015 ◽  
Vol 9 (2) ◽  
pp. 2135-2166 ◽  
Author(s):  
H. X. Shi ◽  
C. H. Wang
Keyword(s):  
Northern Hemisphere ◽  
21St Century ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
The Tibetan Plateau ◽  
High Latitudes ◽  
Snow Water ◽  
Increasing Temperature

Abstract. Changes in snow water equivalent (SWE) over Northern Hemisphere (NH) landmasses are investigated for the early (2016–2035), middle (2046–2065) and late (2080–2099) 21st century using twenty global climate models, which are from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The results show that, relative to the 1986–2005 mean, the multi-model ensemble projects a significant decrease in SWE for most regions, particularly over the Tibetan Plateau and western North America, but an increase in eastern Siberia. Seasonal SWE projections show an overall decreasing trend, with the greatest reduction in spring, which is linked to the stronger inverse partial correlation between the SWE and increasing temperature. Moreover, zonal mean annual SWE exhibits significant reductions in three Representative Concentration Pathways (RCP), a stronger linear relationship between SWE and temperature at mid–high latitudes suggests the reduction in SWE there is related to rising temperature. However, the rate of reduction in SWE declines gradually during the 21st century, indicating that the temperature may reach a threshold value that decreases the rate of SWE reduction. A large reduction in zonal maximum SWE (ZMSWE) between 30° and 40° N is evident in all 21st century for the three RCPs, while RCP8.5 alone indicates a further reduction at high latitudes in the late period of the century. This pattern implies that ZMSWE is affected not only by a terrain factor but also by the increasing temperature. In summary, our results show both a decreasing trend in SWE in the 21st century and a decline in the rate of SWE reduction over the 21st century despite rising temperatures.

A new method for studying the extratropical response to tropical precipitation anomalies and its role in improving projections of Northern Hemisphere climate variability

2020 ◽  
Author(s):  
Natasha Senior ◽  
Manoj Joshi ◽  
Adrian Matthews ◽  
Pranab Deb
Keyword(s):  
Climate Variability ◽  
Northern Hemisphere ◽  
Geopotential Height ◽  
Climate Models ◽  
Linear Response Theory ◽  
Teleconnection Pattern ◽  
Cmip5 Models ◽  
Boreal Winter ◽  
Response Functions ◽  
Tropical Precipitation

<p>Intensification of extreme precipitation and weather events are some of the projections under a 2°C average global temperature increase scenario. Rossby wave trains may be triggered by anomalous tropical precipitation through the interaction of the associated upper level divergent wind and the vorticity gradients of the subtropical jet streams. In this way, anomalous tropical precipitation can influence weather patterns in the Northern Hemisphere. Owing to the quasi-linearity of this teleconnection pattern, it may be studied statistically as a series of signal-response functions. Here the anomalous precipitation events are treated as input forcings and the resulting geopotential height anomalies are the output signals. Through calculating the response functions we are able to realistically capture the 250 hPa geopotential height response to a step-like change in precipitation over the Maritime Continent or the eastern Indian Ocean during the boreal winter. When examining these responses using the same forcing for a selection of CMIP5 models, we find that there is a large inter-model spread, owing to differences in the model basic state. Since these teleconnection patterns are not faithfully represented in climate models, this can obscure our ability to develop realistic projections of atmospheric circulation and extreme weather. We discuss the potential of the linear response theory method to provide improved projections for Northern Hemisphere climate variability.</p>

scholarly journals Hydrological droughts in the southern Andes (40–45°S) from an ensemble experiment using CMIP5 and CMIP6 models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rodrigo Aguayo ◽  
Jorge León-Muñoz ◽  
René Garreaud ◽  
Aldo Montecinos
Keyword(s):  
Climate Models ◽  
Physicochemical Characteristics ◽  
Climate Impact ◽  
Economic Consequences ◽  
Cmip5 Models ◽  
Southern Andes ◽  
Weap Model ◽  
Coastal System ◽  
Hydrological Droughts ◽  
Impacts Of Climate Change

AbstractThe decrease in freshwater input to the coastal system of the Southern Andes (40–45°S) during the last decades has altered the physicochemical characteristics of the coastal water column, causing significant environmental, social and economic consequences. Considering these impacts, the objectives were to analyze historical severe droughts and their climate drivers, and to evaluate the hydrological impacts of climate change in the intermediate future (2040–2070). Hydrological modelling was performed in the Puelo River basin (41°S) using the Water Evaluation and Planning (WEAP) model. The hydrological response and its uncertainty were compared using different combinations of CMIP projects (n = 2), climate models (n = 5), scenarios (n = 3) and univariate statistical downscaling methods (n = 3). The 90 scenarios projected increases in the duration, hydrological deficit and frequency of severe droughts of varying duration (1 to 6 months). The three downscaling methodologies converged to similar results, with no significant differences between them. In contrast, the hydroclimatic projections obtained with the CMIP6 and CMIP5 models found significant climatic (greater trends in summer and autumn) and hydrological (longer droughts) differences. It is recommended that future climate impact assessments adapt the new simulations as more CMIP6 models become available.

scholarly journals Climate Drift in the CMIP5 Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8597-8615 ◽  
Author(s):  
Alexander Sen Gupta ◽  
Nicolas C. Jourdain ◽  
Jaclyn N. Brown ◽  
Didier Monselesan
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Deep Ocean ◽  
Internal Variability ◽  
Correction Method ◽  
Physical Models ◽  
Cmip5 Models ◽  
Steric Sea Level ◽  
Biogeochemical Models ◽  
The Difference

Abstract Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.

Evaluating temperature extremes in CMIP6 simulations using statistically proper evaluation methods

2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Model Evaluation ◽  
Climate Models ◽  
Climate Model ◽  
Mean Squared Error ◽  
Surface Air Temperature ◽  
Cmip5 Models ◽  
Model Output ◽  
Intergovernmental Panel ◽  
Near Surface

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>

EL NINO EFFECTS ON THE ARCTIC STRATOSPHERE ACCORDING TO CMIP5 MODELS AND REANALYSIS

2021 ◽  
pp. 5-23
Author(s):  
M. A. Kolennikova ◽  
◽  
P. N. Vargin ◽  
D. Yu. Gushchina ◽  
◽  
...  
Keyword(s):  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Reanalysis Data ◽  
The Arctic ◽  
Cmip5 Models ◽  
Composite Analysis ◽  
Central Pacific ◽  
Coupled Climate Models

The response of the Arctic stratosphere to El Nio is studied with account of its Eastern and Central Pacific types for the period of 1950-2005. The study is based on the regression and composite analysis using the simulations with six CMIP5 coupled climate models and reanalysis data.

scholarly journals Pliocene Model Intercomparison Project (PlioMIP): experimental design and boundary conditions (Experiment 2)

2011 ◽  
Vol 4 (3) ◽  
pp. 571-577 ◽  
Author(s):  
A. M. Haywood ◽  
H. J. Dowsett ◽  
M. M. Robinson ◽  
D. K. Stoll ◽  
A. M. Dolan ◽  
...  
Keyword(s):  
Experimental Design ◽  
Boundary Conditions ◽  
Initial Phase ◽  
Climate Models ◽  
Model Development ◽  
Warm Period ◽  
Model Intercomparison ◽  
Ocean Atmosphere ◽  
Intercomparison Project ◽  
Fully Coupled

Abstract. The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere-only climate models. The second (Experiment 2) utilises fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.

Interannual Tropical Pacific Sea Surface Temperatures and Their Relation to Preceding Sea Level Pressures in the NCAR CCSM2

2006 ◽  
Vol 19 (6) ◽  
pp. 998-1012 ◽  
Author(s):  
Bruce T. Anderson ◽  
Eric Maloney
Keyword(s):  
Sea Level ◽  
Tropical Pacific ◽  
Equatorial Pacific ◽  
Sea Surface ◽  
Boreal Winter ◽  
Atmospheric Variability ◽  
Climate System Model ◽  
Sst Variability ◽  
Ocean Atmosphere ◽  
Sst Anomalies

Abstract This paper describes aspects of tropical interannual ocean/atmosphere variability in the NCAR Community Climate System Model Version 2.0 (CCSM2). The CCSM2 tropical Pacific Ocean/atmosphere system exhibits much stronger biennial variability than is observed. However, a canonical correlation analysis technique decomposes the simulated boreal winter tropical Pacific sea surface temperature (SST) variability into two modes, both of which are related to atmospheric variability during the preceding boreal winter. The first mode of ocean/atmosphere variability is related to the strong biennial oscillation in which La Niña–related sea level pressure (SLP) conditions precede El Niño–like SST conditions the following winter. The second mode of variability indicates that boreal winter tropical Pacific SST anomalies can also be initiated by SLP anomalies over the subtropical central and eastern North Pacific 12 months earlier. The evolution of both modes is characterized by recharge/discharge within the equatorial subsurface temperature field. For the first mode of variability, this recharge/discharge produces a lag between the basin-average equatorial Pacific isotherm depth anomalies and the isotherm–slope anomalies, equatorial SSTs, and wind stress fields. Significant anomalies are present up to a year before the boreal winter SLP variations and two years prior to the boreal winter ENSO-like events. For the second canonical factor pattern, the recharge/discharge mechanism is induced concurrent with the boreal winter SLP pattern approximately one year prior to the ENSO-like events, when isotherms initially deepen and change their slope across the basin. A rapid deepening of the isotherms in the eastern equatorial Pacific and a warming of the overlying SST anomalies then occurs during the subsequent 12 months.

scholarly journals Achieving realistic Arctic-midlatitude teleconnections in a climate model through stochastic process representation

2021 ◽  
Author(s):  
Kristian Strommen ◽  
Stephan Juricke
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
Stochastic Perturbations ◽  
Model Studies ◽  
Process Representation ◽  
Arctic Sea ◽  
Ocean Atmosphere ◽  
Winter Circulation

Abstract. The extent to which interannual variability in Arctic sea ice influences the midlatitude circulation has been extensively debated. While observational data supports the existence of a teleconnection between November sea ice in the Barents-Kara region and the subsequent winter circulation, climate models do not consistently reproduce such a link, with only very weak inter-model consensus. We show, using the EC-Earth3 climate model, that while a deterministic ensemble of coupled simulations shows no evidence of such a teleconnection, the inclusion of stochastic parameterizations to the ocean and sea ice component of EC-Earth3 results in the emergence of a robust teleconnection comparable in magnitude to that observed. We show that this can be accounted for entirely by an improved ice-ocean-atmosphere coupling due to the stochastic perturbations. In particular, the inconsistent signal in existing climate model studies may be due to model biases in surface coupling, with stochastic parameterizations being one possible remedy.

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