scholarly journals AMOC Trends From 1850 to 2100 At Interannual To Multi-Decadal Time Scales Corroborated By Changes In Salinity Budget

2022 ◽  
Author(s):  
Delphine Lobelle ◽  
Florian Sévellec ◽  
Claudie Beaulieu ◽  
Valerie Livina ◽  
Eleanor Frajka-Williams
Keyword(s):  
Numerical Models ◽  
Coupled Model ◽  
Future Trend ◽  
Meridional Overturning Circulation ◽  
Future Climate ◽  
Historical Period ◽  
Intrinsic Variability ◽  
Maximum Probability ◽  
Salinity Transport ◽  
Business As Usual

Abstract The Atlantic Meridional Overturning Circulation (AMOC) is a key player in the global coupled ocean-atmosphere climate system. To characterise the potential of an AMOC slowdown, a past and future trend probability analysis is applied using 16 models from the Coupled Model Intercomparison Project Phase 5. We determine the probability of AMOC annual to multidecadal trends under the historical period and two future climate scenarios (`business-as-usual’ scenario - RCP8.5 and `stabilisation’ scenario - RCP4.5). We show that the probability of a AMOC decline in model data shifts outside its range of intrinsic variability (determined from the pre-industrial control runs) for sustained 5-year trend or longer. This suggests that interannual AMOC events are not significantly affected by future climate scenario, and so potentially neither by anthropogenic forcing. Furthermore, under the ‘business-as-usual’ scenario the probability of a 20-year decline remains high (87\%) until 2100, however in a ‘stabilisation’ scenario the trend probability recovers its pre-industrial values by 2100. A 20-year unique event is identified from 1995 to 2015, marked by simultaneous unique features in the AMOC and salinity transport that are not replicated over any other 20-year period within the 250 years studied. These features include the maximum probability and magnitude of an `intense’ AMOC decline, and a sustained 20-year decline in subpolar salinity transport caused by internal oceanic processes (as opposed to external atmospheric forcing). This work therefore highlights the potential use of direct salinity transport observations, and ensemble mean numerical models to represent and understand changes in past, present, and future AMOC.

scholarly journals Response of microbial decomposition to spin-up explains CMIP5 soil carbon range until 2100

2014 ◽  
Vol 7 (6) ◽  
pp. 2683-2692 ◽  
Author(s):  
J.-F. Exbrayat ◽  
A. J. Pitman ◽  
G. Abramowitz
Keyword(s):  
Soil Carbon ◽  
Carbon Storage ◽  
Land Surface ◽  
Coupled Model ◽  
Surface Fluxes ◽  
Cmip5 Models ◽  
Historical Period ◽  
Microbial Decomposition ◽  
Transient Simulations ◽  
Business As Usual

Abstract. Soil carbon storage simulated by the Coupled Model Intercomparison Project (CMIP5) models varies 6-fold for the present day. Here, we confirm earlier work showing that this range already exists at the beginning of the CMIP5 historical simulations. We additionally show that this range is largely determined by the response of microbial decomposition during each model's spin-up procedure from initialization to equilibration. The 6-fold range in soil carbon, once established prior to the beginning of the historical period (and prior to the beginning of a CMIP5 simulation), is then maintained through the present and to 2100 almost unchanged even under a strong business-as-usual emissions scenario. We therefore highlight that a commonly ignored part of CMIP5 analyses – the land surface state achieved through the spin-up procedure – can be important for determining future carbon storage and land surface fluxes. We identify the need to better constrain the outcome of the spin-up procedure as an important step in reducing uncertainty in both projected soil carbon and land surface fluxes in CMIP5 transient simulations.

scholarly journals Historically-based run-time bias corrections substantially improve model projections of 100 years of future climate change

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Gerhard Krinner ◽  
Viatcheslav Kharin ◽  
Romain Roehrig ◽  
John Scinocca ◽  
Francis Codron
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Climate Impact ◽  
Future Climate ◽  
Future Climate Change ◽  
Historical Period ◽  
Underlying Assumption ◽  
Bias Corrections

Abstract Climate models and/or their output are usually bias-corrected for climate impact studies. The underlying assumption of these corrections is that climate biases are essentially stationary between historical and future climate states. Under very strong climate change, the validity of this assumption is uncertain, so the practical benefit of bias corrections remains an open question. Here, this issue is addressed in the context of bias correcting the climate models themselves. Employing the ARPEGE, LMDZ and CanAM4 atmospheric models, we undertook experiments in which one centre’s atmospheric model takes another centre’s coupled model as observations during the historical period, to define the bias correction, and as the reference under future projections of strong climate change, to evaluate its impact. This allows testing of the stationarity assumption directly from the historical through future periods for three different models. These experiments provide evidence for the validity of the new bias-corrected model approach. In particular, temperature, wind and pressure biases are reduced by 40–60% and, with few exceptions, more than 50% of the improvement obtained over the historical period is on average preserved after 100 years of strong climate change. Below 3 °C global average surface temperature increase, these corrections globally retain 80% of their benefit.

scholarly journals Large-Scale Atlantic Salinity Changes over the Last Half-Century: A Model–Observation Comparison

2008 ◽  
Vol 21 (8) ◽  
pp. 1698-1720 ◽  
Author(s):  
Anne Pardaens ◽  
Michael Vellinga ◽  
Peili Wu ◽  
Bruce Ingleby
Keyword(s):  
Large Scale ◽  
Hydrological Cycle ◽  
Coupled Model ◽  
Internal Variability ◽  
Meridional Overturning Circulation ◽  
Historical Period ◽  
Substantial Part ◽  
Freshwater Transport ◽  
Northern Atlantic ◽  
Hadley Centre

Abstract Large-scale freshening of the northern Atlantic, and concurrent salinity increases in the low-latitude Atlantic upper layers, have been widely reported for the second half of the twentieth century. The role of anthropogenic and/or unforced variability processes in these changes, and the potential for the high-latitude freshening to slow the Atlantic meridional overturning circulation (MOC), have been the subject of debate. These issues are investigated by comparing observed and simulated changes, using the Third Hadley Centre Coupled Model (HadCM3). This analysis suggests that a substantial part of the observed trends could be related to multidecadal variability of the MOC. Using an SST-derived proxy for historical MOC changes, in conjunction with model internal variability relationships, suggests that much of the observed evolution of northern Atlantic freshwater content can be explained as being driven by unforced MOC variability. HadCM3 simulations with “external” historical time-varying forcings show anthropogenically forced increases in the main hydrological cycle over the Atlantic: an increase in net precipitation at high latitudes and in net evaporation in the subtropics. In the northern Atlantic the freshening from additional surface freshwater is counteracted by changes in ocean freshwater transport. A similar ocean compensation is absent at lower latitudes, where there is decreasing freshwater content. It is suggested that in the recent historical period this externally forced trend is likely to have led to anomalies exceeding the unforced variability range.

scholarly journals A bias-corrected CMIP6 global dataset for dynamical downscaling of future climate, 1979–2100

2021 ◽  
Author(s):  
Zhongfeng Xu ◽  
Ying Han ◽  
Chi-Yung Tam ◽  
Zong-Liang Yang ◽  
Congbin Fu
Keyword(s):  
Large Scale ◽  
Dynamical Downscaling ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Future Climate ◽  
Atmospheric Environment ◽  
Historical Period ◽  
Important Approach ◽  
Corrected Data ◽  
Mean Climate

Abstract Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical downscaling simulations are often degraded by biases in the large-scale forcing itself. Here, we construct a set of bias-corrected global dataset based on 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5). The bias-corrected data have an ERA5-based mean climate and interannual variance, but with a nonlinear trend from the mean of 18 CMIP6 models. The dataset spans the historical period of 1979–2014 and future scenarios (SSP245 and SSP585) of 2015–2100 with a horizontal resolution of 1.25° × 1.25° and 6-hourly intervals. Our evaluation suggests that the bias-corrected data shows clearly better quality than individual CMIP6 models evaluated in terms of climatological mean, interannual variance and extreme events. The presented dataset will be useful for the dynamical downscaling projections of future climate, atmospheric environment, hydrology, agriculture, wind power, etc.

scholarly journals Intrinsic Variability of the Atlantic Meridional Overturning Circulation at Interannual-to-Multidecadal Time Scales

2015 ◽  
Vol 45 (7) ◽  
pp. 1929-1946 ◽  
Author(s):  
Sandy Grégorio ◽  
Thierry Penduff ◽  
Guillaume Sérazin ◽  
Jean-Marc Molines ◽  
Bernard Barnier ◽  
...  
Keyword(s):  
Time Scales ◽  
Gulf Stream ◽  
Atlantic Meridional Overturning Circulation ◽  
Meridional Overturning Circulation ◽  
Global Ocean ◽  
Intrinsic Variability ◽  
Meridional Heat Transport ◽  
Overturning Circulation ◽  
Spectral Peaks ◽  
Meridional Overturning

AbstractThe low-frequency variability of the Atlantic meridional overturning circulation (AMOC) is investigated from 2, ¼°, and ° global ocean–sea ice simulations, with a specific focus on its internally generated (i.e., “intrinsic”) component. A 327-yr climatological ¼° simulation, driven by a repeated seasonal cycle (i.e., a forcing devoid of interannual time scales), is shown to spontaneously generate a significant fraction R of the interannual-to-decadal AMOC variance obtained in a 50-yr “fully forced” hindcast (with reanalyzed atmospheric forcing including interannual time scales). This intrinsic variance fraction R slightly depends on whether AMOCs are computed in geopotential or density coordinates, and on the period considered in the climatological simulation, but the following features are quite robust when mesoscale eddies are simulated (at both ¼° and ° resolutions); R barely exceeds 5%–10% in the subpolar gyre but reaches 30%–50% at 34°S, up to 20%–40% near 25°N, and 40%–60% near the Gulf Stream. About 25% of the meridional heat transport interannual variability is attributed to intrinsic processes at 34°S and near the Gulf Stream. Fourier and wavelet spectra, built from the 327-yr ¼° climatological simulation, further indicate that spectral peaks of intrinsic AMOC variability (i) are found at specific frequencies ranging from interannual to multidecadal, (ii) often extend over the whole meridional scale of gyres, (iii) stochastically change throughout these 327 yr, and (iv) sometimes match the spectral peaks found in the fully forced hindcast in the North Atlantic. Intrinsic AMOC variability is also detected at multidecadal time scales, with a marked meridional coherence between 35°S and 25°N (15–30 yr periods) and throughout the whole basin (50–90-yr periods).

scholarly journals Atlantic Meridional Overturning Circulation (AMOC) in CMIP5 Models: RCP and Historical Simulations

2013 ◽  
Vol 26 (18) ◽  
pp. 7187-7197 ◽  
Author(s):  
Wei Cheng ◽  
John C. H. Chiang ◽  
Dongxiao Zhang
Keyword(s):  
North Atlantic ◽  
Coupled Model ◽  
Meridional Overturning Circulation ◽  
First Century ◽  
Model Intercomparison ◽  
The North ◽  
Intercomparison Project ◽  
Meridional Overturning ◽  
The North Atlantic ◽  
Twenty First Century

Abstract The Atlantic meridional overturning circulation (AMOC) simulated by 10 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical (1850–2005) and future climate is examined. The historical simulations of the AMOC mean state are more closely matched to observations than those of phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similarly to CMIP3, all models predict a weakening of the AMOC in the twenty-first century, though the degree of weakening varies considerably among the models. Under the representative concentration pathway 4.5 (RCP4.5) scenario, the weakening by year 2100 is 5%–40% of the individual model's historical mean state; under RCP8.5, the weakening increases to 15%–60% over the same period. RCP4.5 leads to the stabilization of the AMOC in the second half of the twenty-first century and a slower (then weakening rate) but steady recovery thereafter, while RCP8.5 gives rise to a continuous weakening of the AMOC throughout the twenty-first century. In the CMIP5 historical simulations, all but one model exhibit a weak downward trend [ranging from −0.1 to −1.8 Sverdrup (Sv) century−1; 1 Sv ≡ 106 m3 s−1] over the twentieth century. Additionally, the multimodel ensemble–mean AMOC exhibits multidecadal variability with a ~60-yr periodicity and a peak-to-peak amplitude of ~1 Sv; all individual models project consistently onto this multidecadal mode. This multidecadal variability is significantly correlated with similar variations in the net surface shortwave radiative flux in the North Atlantic and with surface freshwater flux variations in the subpolar latitudes. Potential drivers for the twentieth-century multimodel AMOC variability, including external climate forcing and the North Atlantic Oscillation (NAO), and the implication of these results on the North Atlantic SST variability are discussed.

scholarly journals Numerical Simulation Study on Distribution of Bubble in Flow near Aerator Based on CFD-PBM Coupled Model in Tunnel

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Jiaming Lei ◽  
Jianmin Zhang ◽  
Lifang Zhang
Keyword(s):  
Size Distribution ◽  
Bubble Size ◽  
Numerical Models ◽  
Coupled Model ◽  
Bubble Size Distribution ◽  
Balance Model ◽  
Main Process ◽  
Air Bubbles ◽  
Air Concentration ◽  
Aerated Flow

The aerator can reduce erosion by mixing a large amount of air into the water in the solid wall area. The effectiveness of erosion reduction is mainly based on air concentration and its bubble size distribution. However, simultaneous simulation of the air concentration and its bubble size distribution in numerical simulations is still a hot and difficult area of research. Aiming at the downstream aerated flow of hydraulic aeration facilities, several numerical models, such as VOF, mixture, Euler, and Population Balance Model (PBM), are compared and verified by experiments. The results show that the CFD-PBM coupled model performs well compared to other conventional multiphase models. It can not only obtain the evolution law of the bubble distribution downstream of the aerator but also accurately simulate the recombination and evolution process of bubble aggregation and breakage. The Sauter mean diameter of the air bubbles in the aerated flow decreases along the way and eventually reaches a stable value. The bubble breakage is the main process in the development of the bubbles. It reveals the aeration law that the small air bubbles are closer to the bottom plate, while the large bubbles float up along the aerated flow, which provides a powerful support for the basic research on the mechanism of aeration and erosion reduction.

scholarly journals Projections of Cold Air Outbreaks In CMIP6 Earth System Models

2021 ◽  
Author(s):  
Erik T. Smith ◽  
Scott Sheridan
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Coupled Model ◽  
Meridional Overturning Circulation ◽  
Cold Air ◽  
Complex Processes ◽  
The North ◽  
Meridional Overturning ◽  
Earth System Models ◽  
Cold Air Outbreaks

Abstract Historical and future simulated temperature data from five climate models in the Coupled Model Intercomparing Project Phase 6 (CMIP6) are used to understand how climate change might alter cold air outbreaks (CAOs) in the future. Three different Shared Socioeconomic Pathways (SSPs), SSP 1 – 2.6, SSP 2 – 4.5, and SSP 5 – 8.5 are examined to identify potential fluctuations in CAOs across the globe between 2015 and 2054. Though CAOs may remain persistent or even increase in some regions through 2040, all five climate models show CAOs disappearing by 2054 based on current climate percentiles. Climate models were able to accurately simulate the spatial distribution and trends of historical CAOs, but there were large errors in the simulated interannual frequency of CAOs in the North Atlantic and North Pacific. Fluctuations in complex processes, such as Atlantic Meridional Overturning Circulation, may be contributing to each model’s inability to simulate historical CAOs in these regions.

scholarly journals PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
Author(s):  
P. B. Holden ◽  
N. R. Edwards ◽  
P. H. Garthwaite ◽  
K. Fraedrich ◽  
F. Lunkeit ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Coupled Model ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate Impacts ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Data ◽  
Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

scholarly journals An Efficient GPU Implementation of a Coupled Overland-Sewer Hydraulic Model with Pollutant Transport

Hydrology ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 146
Author(s):  
Javier Fernández-Pato ◽  
Pilar García-Navarro
Keyword(s):  
Water Flow ◽  
Numerical Models ◽  
Global Analysis ◽  
Coupled Model ◽  
Pollutant Transport ◽  
Pollutant Dispersion ◽  
Quality Analysis ◽  
Storm Events ◽  
Graphic Processing Units ◽  
Intense Storm

Numerical simulation of flows that consider interaction between overland and drainage networks has become a practical tool to prevent and mitigate flood situations in urban environments, especially when dealing with intense storm events, where the limited capacity of the sewer systems can be a trigger for flooding. Additionally, in order to prevent any kind of pollutant dispersion through the drainage network, it is very interesting to have a certain monitorization or control over the quality of the water that flows in both domains. In this sense, the addition of a pollutant transport component to both surface and sewer hydraulic models would benefit the global analysis of the combined water flow. On the other hand, when considering a realistic large domain with complex topography or streets structure, a fine spatial discretization is mandatory. Hence the number of grid cells is usually very large and, therefore, it is necessary to use parallelization techniques for the calculation, the use of Graphic Processing Units (GPU) being one of the most efficient due to the leveraging of thousands of processors within a single device. In this work, an efficient GPU-based 2D shallow water flow solver (RiverFlow2D-GPU) is fully coupled with EPA’s Storm Water Management Model (SWMM). Both models are able to develop a transient water quality analysis taking into account several pollutants. The coupled model, referred to as RiverFlow2D-GPU UD (Urban Drainge) is applied to three real-world cases, covering the most common hydraulic situations in urban hydrology/hydraulics. A UK Environmental Agency test case is used as model validation, showing a good agreement between RiverFlow2D-GPU UD and the rest of the numerical models considered. The efficiency of the model is proven in two more complex domains, leading to a >100x faster simulations compared with the traditional CPU computation.

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