scholarly journals Intrinsic versus Forced Variation in Coupled Climate Model Simulations over the Arctic during the Twentieth Century*

2007 ◽  
Vol 20 (6) ◽  
pp. 1093-1107 ◽  
Author(s):  
Muyin Wang ◽  
James E. Overland ◽  
Vladimir Kattsov ◽  
John E. Walsh ◽  
Xiangdong Zhang ◽  
...  

Abstract There were two major multiyear, Arctic-wide (60°–90°N) warm anomalies (>0.7°C) in land surface air temperature (LSAT) during the twentieth century, between 1920 and 1950 and again at the end of the century after 1979. Reproducing this decadal and longer variability in coupled general circulation models (GCMs) is a critical test for understanding processes in the Arctic climate system and increasing the confidence in the Intergovernmental Panel on Climate Change (IPCC) model projections. This study evaluated 63 realizations generated by 20 coupled GCMs made available for the IPCC Fourth Assessment for their twentieth-century climate in coupled models (20C3M) and corresponding control runs (PIcntrl). Warm anomalies in the Arctic during the last two decades are reproduced by all ensemble members, with considerable variability in amplitude among models. In contrast, only eight models generated warm anomaly amplitude of at least two-thirds of the observed midcentury warm event in at least one realization, but not its timing. The durations of the midcentury warm events in all the models are decadal, while that of the observed was interdecadal. The variance of the control runs in nine models was comparable with the variance in the observations. The random timing of midcentury warm anomalies in 20C3M simulations and the similar variance of the control runs in about half of the models suggest that the observed midcentury warm period is consistent with intrinsic climate variability. Five models were considered to compare somewhat favorably to Arctic observations in both matching the variance of the observed temperature record in their control runs and representing the decadal mean temperature anomaly amplitude in their 20C3M simulations. Seven additional models could be given further consideration. Results support selecting a subset of GCMs when making predictions for future climate by using performance criteria based on comparison with retrospective data.

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  

<p>Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.</p>


2011 ◽  
Vol 24 (22) ◽  
pp. 5935-5950 ◽  
Author(s):  
Elinor R. Martin ◽  
Courtney Schumacher

Abstract A census of 19 coupled and 12 uncoupled model runs from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) shows that all models have the ability to simulate the location and height of the Caribbean low-level jet (CLLJ); however, the observed semiannual cycle of the CLLJ magnitude was a challenge for the models to reproduce. In particular, model means failed to capture the strong July CLLJ peak as a result of the lack of westward and southward expansion of the North Atlantic subtropical high (NASH) between May and July. The NASH was also found to be too strong, particularly during the first 6 months of the year in the coupled model runs, which led to increased meridional sea level pressure gradients across the southern Caribbean and, hence, an overly strong CLLJ. The ability of the models to simulate the correlation between the CLLJ and regional precipitation varied based on season and region. During summer months, the negative correlation between the CLLJ and Caribbean precipitation anomalies was reproduced in the majority of models, with uncoupled models outperforming coupled models. The positive correlation between the CLLJ and the central U.S. precipitation during February was more challenging for the models, with the uncoupled models failing to reproduce a significant relationship. This may be a result of overactive convective parameterizations raining out too much moisture in the Caribbean meaning less is available for transport northward, or due to incorrect moisture fluxes over the Gulf of Mexico. The representation of the CLLJ in general circulation models has important consequences for accurate predictions and projections of future climate in the Caribbean and surrounding regions.


1997 ◽  
Vol 1 (2) ◽  
pp. 217-226 ◽  
Author(s):  
W. J. Shuttleworth ◽  
Z.-L. Yang ◽  
M. A. Arain

Abstract. Aggregation rules are derived for calculating the effective value of parameters that determine the exchange of momentum and energy between the land surface and the atmosphere at the length scales used in General Circulation Models (GCMs). The derivation involves starting from theories that link parameters relevant at grid scale and patch scale, and then imposing the limitations necessarily present when models are operated in a free-standing, predictive mode. The application of these rules is illustrated by example for the case of the Biosphere-Atmosphere Transfer Scheme (BATS). Remotely sensed global maps of land cover classes at 1 km x 1 km pixel scale for North America, South America, and Africa are used with these new aggregation rules to calculate area-average values of parameters for the 3° x 3° grid mesh used in the National Center for Atmospheric Research Community Climate Model. There are significant differences between the parameters calculated using aggregation rules and the values selected on the basis of the dominant vegetation cover in each grid, this being the selection procedure conventionally applied with BATS.


2009 ◽  
Vol 16 (4) ◽  
pp. 453-473 ◽  
Author(s):  
J. Boucharel ◽  
B. Dewitte ◽  
B. Garel ◽  
Y. du Penhoat

Abstract. El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability in the Pacific, having socio-economic impacts on surrounding regions. ENSO exhibits significant modulation on decadal to inter-decadal time scales which is related to changes in its characteristics (onset, amplitude, frequency, propagation, and predictability). Some of these characteristics tend to be overlooked in ENSO studies, such as its asymmetry (the number and amplitude of warm and cold events are not equal) and the deviation of its statistics from those of the Gaussian distribution. These properties could be related to the ability of the current generation of coupled models to predict ENSO and its modulation. Here, ENSO's non-Gaussian nature and asymmetry are diagnosed from in situ data and a variety of models (from intermediate complexity models to full-physics coupled general circulation models (CGCMs)) using robust statistical tools initially designed for financial mathematics studies. In particular α-stable laws are used as theoretical background material to measure (and quantify) the non-Gaussian character of ENSO time series and to estimate the skill of ``naïve'' statistical models in producing deviation from Gaussian laws and asymmetry. The former are based on non-stationary processes dominated by abrupt changes in mean state and empirical variance. It is shown that the α-stable character of ENSO may result from the presence of climate shifts in the time series. Also, cool (warm) periods are associated with ENSO statistics having a stronger (weaker) tendency towards Gaussianity and lower (greater) asymmetry. This supports the hypothesis of ENSO being rectified by changes in mean state through nonlinear processes. The relationship between changes in mean state and nonlinearity (skewness) is further investigated both in the Zebiak and Cane (1987)'s model and the models of the Intergovernmental Panel for Climate Change (IPCC). Whereas there is a clear relationship in all models between ENSO asymmetry (as measured by skewness or nonlinear advection) and changes in mean state, they exhibit a variety of behaviour with regard to α-stability. This suggests that the dynamics associated with climate shifts and the occurrence of extreme events involve higher-order statistical moments that cannot be accounted for solely by nonlinear advection.


2011 ◽  
Vol 24 (24) ◽  
pp. 6528-6539 ◽  
Author(s):  
Robert J. Allen ◽  
Charles S. Zender

Abstract Throughout much of the latter half of the twentieth century, the dominant mode of Northern Hemisphere (NH) extratropical wintertime circulation variability—the Arctic Oscillation (AO)—exhibited a positive trend, with decreasing high-latitude sea level pressure (SLP) and increasing midlatitude SLP. General circulation models (GCMs) show that this trend is related to several factors, including North Atlantic SSTs, greenhouse gas/ozone-induced stratospheric cooling, and warming of the Indo-Pacific warm pool. Over the last approximately two decades, however, the AO has been decreasing, with 2009/10 featuring the most negative AO since 1900. Observational and idealized modeling studies suggest that snow cover, particularly over Eurasia, may be important. An observed snow–AO mechanism also exists, involving the vertical propagation of a Rossby wave train into the stratosphere, which induces a negative AO response that couples to the troposphere. Similar to other GCMs, the authors show that transient simulations with the Community Atmosphere Model, version 3 (CAM3) yield a snow–AO relationship inconsistent with observations and dissimilar AO trends. However, Eurasian snow cover and its interannual variability are significantly underestimated. When the albedo effects of snow cover are prescribed in CAM3 (CAM PS) using satellite-based snow cover fraction data, a snow–AO relationship similar to observations develops. Furthermore, the late-twentieth-century increase in the AO, and particularly the recent decrease, is reproduced by CAM PS. The authors therefore conclude that snow cover has helped force the observed AO trends and that it may play an important role in future AO trends.


Author(s):  
Richard A. Betts ◽  
Matthew Collins ◽  
Deborah L. Hemming ◽  
Chris D. Jones ◽  
Jason A. Lowe ◽  
...  

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) assessed a range of scenarios of future greenhouse-gas emissions without policies to specifically reduce emissions, and concluded that these would lead to an increase in global mean temperatures of between 1.6°C and 6.9°C by the end of the twenty-first century, relative to pre-industrial. While much political attention is focused on the potential for global warming of 2°C relative to pre-industrial, the AR4 projections clearly suggest that much greater levels of warming are possible by the end of the twenty-first century in the absence of mitigation. The centre of the range of AR4-projected global warming was approximately 4°C. The higher end of the projected warming was associated with the higher emissions scenarios and models, which included stronger carbon-cycle feedbacks. The highest emissions scenario considered in the AR4 (scenario A1FI) was not examined with complex general circulation models (GCMs) in the AR4, and similarly the uncertainties in climate–carbon-cycle feedbacks were not included in the main set of GCMs. Consequently, the projections of warming for A1FI and/or with different strengths of carbon-cycle feedbacks are often not included in a wider discussion of the AR4 conclusions. While it is still too early to say whether any particular scenario is being tracked by current emissions, A1FI is considered to be as plausible as other non-mitigation scenarios and cannot be ruled out. (A1FI is a part of the A1 family of scenarios, with ‘FI’ standing for ‘fossil intensive’. This is sometimes erroneously written as A1F1, with number 1 instead of letter I.) This paper presents simulations of climate change with an ensemble of GCMs driven by the A1FI scenario, and also assesses the implications of carbon-cycle feedbacks for the climate-change projections. Using these GCM projections along with simple climate-model projections, including uncertainties in carbon-cycle feedbacks, and also comparing against other model projections from the IPCC, our best estimate is that the A1FI emissions scenario would lead to a warming of 4°C relative to pre-industrial during the 2070s. If carbon-cycle feedbacks are stronger, which appears less likely but still credible, then 4°C warming could be reached by the early 2060s in projections that are consistent with the IPCC’s ‘likely range’.


2006 ◽  
Vol 19 (17) ◽  
pp. 4397-4417 ◽  
Author(s):  
N. H. Saji ◽  
S-P. Xie ◽  
T. Yamagata

Abstract The twentieth-century simulations using by 17 coupled ocean–atmosphere general circulation models (CGCMs) submitted to the Intergovernmental Panel on Climate Change’s Fourth Assessment Report (IPCC AR4) are evaluated for their skill in reproducing the observed modes of Indian Ocean (IO) climate variability. Most models successfully capture the IO’s delayed, basinwide warming response a few months after El Niño–Southern Oscillation (ENSO) peaks in the Pacific. ENSO’s oceanic teleconnection into the IO, by coastal waves through the Indonesian archipelago, is poorly simulated in these models, with significant shifts in the turning latitude of radiating Rossby waves. In observations, ENSO forces, by the atmospheric bridge mechanism, strong ocean Rossby waves that induce anomalies of SST, atmospheric convection, and tropical cyclones in a thermocline dome over the southwestern tropical IO. While the southwestern IO thermocline dome is simulated in nearly all of the models, this ocean Rossby wave response to ENSO is present only in a few of the models examined, suggesting difficulties in simulating ENSO’s teleconnection in surface wind. A majority of the models display an equatorial zonal mode of the Bjerknes feedback with spatial structures and seasonality similar to the Indian Ocean dipole (IOD) in observations. This success appears to be due to their skills in simulating the mean state of the equatorial IO. Corroborating the role of the Bjerknes feedback in the IOD, the thermocline depth, SST, precipitation, and zonal wind are mutually positively correlated in these models, as in observations. The IOD–ENSO correlation during boreal fall ranges from −0.43 to 0.74 in the different models, suggesting that ENSO is one, but not the only, trigger for the IOD.


2016 ◽  
Vol 97 (12) ◽  
pp. 2305-2328 ◽  
Author(s):  
Paquita Zuidema ◽  
Ping Chang ◽  
Brian Medeiros ◽  
Ben P. Kirtman ◽  
Roberto Mechoso ◽  
...  

Abstract Well-known problems trouble coupled general circulation models of the eastern Atlantic and Pacific Ocean basins. Model climates are significantly more symmetric about the equator than is observed. Model sea surface temperatures are biased warm south and southeast of the equator, and the atmosphere is too rainy within a band south of the equator. Near-coastal eastern equatorial SSTs are too warm, producing a zonal SST gradient in the Atlantic opposite in sign to that observed. The U.S. Climate Variability and Predictability Program (CLIVAR) Eastern Tropical Ocean Synthesis Working Group (WG) has pursued an updated assessment of coupled model SST biases, focusing on the surface energy balance components, on regional error sources from clouds, deep convection, winds, and ocean eddies; on the sensitivity to model resolution; and on remote impacts. Motivated by the assessment, the WG makes the following recommendations: 1) encourage identification of the specific parameterizations contributing to the biases in individual models, as these can be model dependent; 2) restrict multimodel intercomparisons to specific processes; 3) encourage development of high-resolution coupled models with a concurrent emphasis on parameterization development of finer-scale ocean and atmosphere features, including low clouds; 4) encourage further availability of all surface flux components from buoys, for longer continuous time periods, in persistently cloudy regions; and 5) focus on the eastern basin coastal oceanic upwelling regions, where further opportunities for observational–modeling synergism exist.


2014 ◽  
Vol 11 (5) ◽  
pp. 6715-6754 ◽  
Author(s):  
W. Zhang ◽  
C. Jansson ◽  
P. A. Miller ◽  
B. Smith ◽  
P. Samuelsson

Abstract. Continued warming of the Arctic will likely accelerate terrestrial carbon (C) cycling by increasing both uptake and release of C. There are still large uncertainties in modelling Arctic terrestrial ecosystems as a source or sink of C. Most modelling studies assessing or projecting the future fate of C exchange with the atmosphere are based an either stand-alone process-based models or coupled climate–C cycle general circulation models, in either case disregarding biogeophysical feedbacks of land surface changes to the atmosphere. To understand how biogeophysical feedbacks will impact on both climate and C budget over Arctic terrestrial ecosystems, we apply the regional Earth system model RCA-GUESS over the CORDEX-Arctic domain. The model is forced with lateral boundary conditions from an GCMs CMIP5 climate projection under the RCP 8.5 scenario. We perform two simulations with or without interactive vegetation dynamics respectively to assess the impacts of biogeophysical feedbacks. Both simulations indicate that Arctic terrestrial ecosystems will continue to sequester C with an increased uptake rate until 2060s–2070s, after which the C budget will return to a weak C sink as increased soil respiration and biomass burning outpaces increased net primary productivity. The additional C sinks arising from biogeophysical feedbacks are considerable, around 8.5 Gt C, accounting for 22% of the total C sinks, of which 83.5% are located in areas of Arctic tundra. Two opposing feedback mechanisms, mediated by albedo and evapotranspiration changes respectively, contribute to this response. Albedo feedback dominates over winter and spring season, amplifying the near-surface warming by up to 1.35 K in spring, while evapotranspiration feedback dominates over summer exerting the evaporative cooling by up to 0.81 K. Such feedbacks stimulate vegetation growth with an earlier onset of growing-season, leading to compositional changes in woody plants and vegetation redistribution.


2014 ◽  
Vol 11 (19) ◽  
pp. 5503-5519 ◽  
Author(s):  
W. Zhang ◽  
C. Jansson ◽  
P. A. Miller ◽  
B. Smith ◽  
P. Samuelsson

Abstract. Continued warming of the Arctic will likely accelerate terrestrial carbon (C) cycling by increasing both uptake and release of C. Yet, there are still large uncertainties in modelling Arctic terrestrial ecosystems as a source or sink of C. Most modelling studies assessing or projecting the future fate of C exchange with the atmosphere are based on either stand-alone process-based models or coupled climate–C cycle general circulation models, and often disregard biogeophysical feedbacks of land-surface changes to the atmosphere. To understand how biogeophysical feedbacks might impact on both climate and the C budget in Arctic terrestrial ecosystems, we apply the regional Earth system model RCA-GUESS over the CORDEX-Arctic domain. The model is forced with lateral boundary conditions from an EC-Earth CMIP5 climate projection under the representative concentration pathway (RCP) 8.5 scenario. We perform two simulations, with or without interactive vegetation dynamics respectively, to assess the impacts of biogeophysical feedbacks. Both simulations indicate that Arctic terrestrial ecosystems will continue to sequester C with an increased uptake rate until the 2060–2070s, after which the C budget will return to a weak C sink as increased soil respiration and biomass burning outpaces increased net primary productivity. The additional C sinks arising from biogeophysical feedbacks are approximately 8.5 Gt C, accounting for 22% of the total C sinks, of which 83.5% are located in areas of extant Arctic tundra. Two opposing feedback mechanisms, mediated by albedo and evapotranspiration changes respectively, contribute to this response. The albedo feedback dominates in the winter and spring seasons, amplifying the near-surface warming by up to 1.35 °C in spring, while the evapotranspiration feedback dominates in the summer months, and leads to a cooling of up to 0.81 °C. Such feedbacks stimulate vegetation growth due to an earlier onset of the growing season, leading to compositional changes in woody plants and vegetation redistribution.


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