Pre-industrial Control Run Research Articles

Changing effects of external forcing on Atlantic–Pacific interactions

Abstract. Recent studies have highlighted the increasingly dominant role of external forcing in driving Atlantic and Pacific Ocean variability during the second half of the 20th century. This paper provides insights into the underlying mechanisms driving interactions between modes of variability over the two basins. We define a set of possible drivers of these interactions and apply causal discovery to reanalysis data, two ensembles of pacemaker simulations where sea surface temperatures in either the tropical Pacific or the North Atlantic are nudged to observations, and a pre-industrial control run. We also utilize large-ensemble means of historical simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to quantify the effect of external forcing and improve the understanding of its impact. A causal analysis of the historical time series between 1950 and 2014 identifies a regime switch in the interactions between major modes of Atlantic and Pacific climate variability in both reanalysis and pacemaker simulations. A sliding window causal analysis reveals a decaying El Niño–Southern Oscillation (ENSO) effect on the Atlantic as the North Atlantic fluctuates towards an anomalously warm state. The causal networks also demonstrate that external forcing contributed to strengthening the Atlantic's negative-sign effect on ENSO since the mid-1980s, where warming tropical Atlantic sea surface temperatures induce a La Niña-like cooling in the equatorial Pacific during the following season through an intensification of the Pacific Walker circulation. The strengthening of this effect is not detected when the historical external forcing signal is removed in the Pacific pacemaker ensemble. The analysis of the pre-industrial control run supports the notion that the Atlantic and Pacific modes of natural climate variability exert contrasting impacts on each other even in the absence of anthropogenic forcing. The interactions are shown to be modulated by the (multi)decadal states of temperature anomalies of both basins with stronger connections when these states are “out of phase”. We show that causal discovery can detect previously documented connections and provides important potential for a deeper understanding of the mechanisms driving changes in regional and global climate variability.

MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

Abstract. Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability.

Water-Mass Coordinates Isolate the Historical Ocean Warming Signal

Abstract Persistent warming and water cycle change due to anthropogenic climate change modifies the temperature and salinity distribution of the ocean over time. This “forced” signal of temperature and salinity change is often masked by the background internal variability of the climate system. Analyzing temperature and salinity change in water-mass-based coordinate systems has been proposed as an alternative to traditional Eulerian (e.g., fixed-depth, zonally averaged) coordinate systems. The impact of internal variability is thought to be reduced in water-mass coordinates, enabling a cleaner separation of the forced signal from background variability—or a higher “signal-to-noise” ratio. Building on previous analyses comparing Eulerian and water-mass-based one-dimensional coordinates, here we recast two-dimensional coordinate systems—temperature–salinity (T–S), latitude–longitude, and latitude–depth—onto a directly comparable equal-volume framework. We compare the internal variability, or “noise” in temperature and salinity between these remapped two-dimensional coordinate systems in a 500-yr preindustrial control run from a CMIP6 climate model. We find that the median internal variability is lowest (and roughly equivalent) in T–S and latitude–depth space, compared with latitude–longitude coordinates. A large proportion of variability in T–S and latitude–depth space can be attributed to processes that operate over a time scale greater than 10 years. Overall, the signal-to-noise ratio in T–S coordinates is roughly comparable to latitude–depth coordinates, but is greater in regions of high historical temperature change. Conversely, latitude–depth coordinates have greater signal-to-noise ratio in regions of historical salinity change. Thus, we conclude that the climatic temperature change signal can be more robustly identified in water-mass coordinates. Significance Statement Changes in ocean temperature and salinity are driven both by human-induced climate change and by modes of natural variability in the climate system, such as El Niño–Southern Oscillation. It can be difficult to isolate the human-induced “signal” of climate change from the natural fluctuations or “noise” in the climate system. Water-mass-based methods, which “follow” a parcel of water around the ocean, have been thought to improve on “Eulerian” (i.e., analyses performed at fixed latitude, longitude, and depth) frames of reference as they are less impacted by the noise. However, it is difficult to cleanly compare between water-mass-based methods and Eulerian methods. Here, we aim to quantify the extent to which water-mass-based frameworks improve on Eulerian frameworks in isolating the climate signal from the noise. We recast water-mass and Eulerian methods onto an equivalent grid, enabling a clean comparison between them, and find that doing so increases the signal-to-noise ratio in water-mass-based coordinates in regions of ocean warming. These results emphasize the utility of water-mass-based methods in analyzing long-term climatic temperature change in the ocean.

Record-breaking statistics detect islands of cooling in a sea of warming

Abstract. Record-breaking statistics are combined here with a geographic mode of exploration to introduce a record-breaking map. We examine time series of sea surface temperature (SST) values and show that high SST records have been broken far more frequently than the expected rate for a trend-free random variable (TFRV) over the vast majority of oceans (83 % of the grid cells). This, together with the asymmetry between high and low records and their deviation from a TFRV, indicates SST warming over most oceans, obtained using a distribution-independent, robust, and simple-to-use method. The spatial patterns of this warming are coherent and reveal islands of cooling, such as the “cold blob” in the North Atlantic and a surprising elliptical area in the Southern Ocean, near the Ross Sea gyre, not previously reported. The method was also applied to evaluate a global climate model (GCM), which reproduced the observed records during the study period. The distribution of records from the GCM pre-industrial (PI) control run samples was similar to the one from a TFRV, suggesting that the contribution of a suitably constrained internal variability to the observed record-breaking trends is negligible. Future forecasts show striking SST trends, with even more frequent high records and less frequent low records.

Decadal climate predictions with the Canadian Earth System Model version 5 (CanESM5)

Abstract. The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 retrospective decadal forecasts (or hindcasts) is integrated for 10 years from realistic initial states once a year during 1961 to the present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from pre-industrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skillfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be potentially skillful on decadal timescales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land.

The role of interannual ENSO events in decadal timescale transitions of the Interdecadal Pacific Oscillation

The build-up of decadal timescale upper ocean heat content in the off-equatorial western tropical Pacific can provide necessary conditions for interannual El Niño/Southern Oscillation (ENSO) events to contribute to decadal timescale transitions of tropical Pacific SSTs to the opposite phase of the Interdecadal Pacific Oscillation (IPO). This can be viewed as a corollary to subseasonal westerly wind burst events contributing to El Niño interannual timescale transitions. A long pre-industrial control run with CESM1 is analyzed to show that there is a greater chance of ENSO activity to contribute to an IPO transition when off-equatorial western Pacific Ocean heat content reaches either a maximum (for El Niño to contribute to a transition to positive IPO) or minimum (for La Niña to contribute to a transition to negative IPO) as seen in observations. If above a necessary ocean heat content threshold, the convergence associated with westerly anomaly near-equatorial surface winds associated with El Niño activity can draw that heat content equatorward to sustain anomalously warm western and central Pacific SSTs. These are associated with positive precipitation and convective heating anomalies, a Gill-type response and wind stress curl anomalies that continue to feed warm water into the near-equatorial western Pacific. These conditions then sustain the decadal-timescale transition to positive IPO (with the opposite sign for transition to negative IPO). Associated central equatorial Pacific convective heating anomalies produce SLP and wind stress anomalies in the North and South Pacific that can excite westward-propagating off-equatorial oceanic Rossby waves to contribute to the western Pacific thermocline depth and consequent heat content anomalies.

Understanding the combined effects of global warming and anthropogenic aerosol forcing on the South Asian monsoon

There is growing evidence of the influence of northern hemisphere (NH) anthropogenic aerosols (AA) on the observed regional climate change over Asia in the recent few decades. While the radiative effects of AA can regionally offset the greenhouse gas (GHG) forcing, their combined impacts on the South Asian monsoon (SAM) are not adequately understood. The present study examines the individual and combined effects of GHG and AA forcing on the SAM precipitation response, based on numerical experiments conducted using the IITM Earth System Model version2 (IITM-ESMv2). We performed the following three sets of 50-year simulations based on the CMIP6 forcing (a) AER: where the atmospheric CO2 concentration is fixed to the pre-industrial level (i.e., year 1850) and AA levels correspond to the year 2005 (b) GHG: CO2 concentration corresponds to the year 2005 and AA levels correspond to the year 1850 (c) COMB: Both CO2 concentration and AA levels correspond to the year 2005. The three experiments are compared against the pre-industrial control (PICTL) run of the IITM-ESMv2. An intensification of SAM precipitation is noted in GHG relative to PICTL, whereas AER exhibits a decrease of SAM precipitation and weakening of monsoon circulation in response to the AA forcing. The results show that absorption of shortwave radiation above the atmospheric boundary layer over the Asian region creates surface radiation deficit and stabilizes the lower troposphere, leading to a slowdown of monsoonal winds, reduced evaporation over the Indian Ocean and decreased moisture convergence over South and Southeast Asia. A striking finding from our analysis is the reinforced suppression of SAM precipitation and organized monsoon convection in COMB, which results from an enhanced inter-hemispheric asymmetry in radiative forcing under the combined influence of the elevated CO2 and AA forcing. Furthermore, both the AER and COMB experiments reveal a widespread suppression of large-scale organized monsoon convective activity on sub-seasonal time-scales over South and Southeast Asia.

On the role of increased CO2 concentrations in enhancing the temporal clustering of heavy precipitation events across Europe

This study examines the response of the clustering behavior in heavy precipitation events across Europe to increasing atmospheric CO2 concentrations. We focus on four large-scale climate modes [Arctic Oscillation (AO), North Atlantic Oscillation (NAO), East Atlantic (EA) pattern, and Scandinavia pattern (SCAND)] that have been found to play a significant role in controlling the occurrence of these events. We use a peak over threshold (POT) method to define daily heavy precipitation events and Cox regression as the modeling framework. We consider three experiments from the Coupled Model Intercomparison Project Phase 5 (CMIP5): (1) pre-industrial control run experiments (PI-control); (2) a 1%/year increase in CO2 from the CO2 concentration in PI control to quadrupling (1pctCO2); and (3) an instantaneous quadrupling of CO2, then holding it fixed (abrupt4 × CO2). We measure the effects of CO2 by examining whether the Cox regression coefficients in the CO2 experiments are significantly different from those in the PI control. We find that (1) the increases in CO2 are unlikely to lead to changes in the spatial patterns of relationships between climate modes and heavy precipitation; (2) the increases in CO2 are likely to lead to a strengthening of the relationship between the AO/SCAND and the occurrence of heavy precipitation events, while increases in CO2 have weaker effects on the role of NAO and EA; (3) the response to an abrupt increase in CO2 is generally stronger compared to a more gradual one; (4) the responses of the integrated vapor transport and 500-mb geopotential height to increasing CO2 provide a physical mechanism to explain the enhanced relationship between climate modes and clustering of heavy precipitation events.

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

AbstractStochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

The Australian Earth System Model: ACCESS-ESM1.5

The Australian Community Climate and Earth System Simulator (ACCESS) has been extended to include land and ocean carbon cycle components to form an Earth System Model (ESM). The current version, ACCESS-ESM1.5, has been mainly developed to enable Australia to participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6) with an ESM version. Here we describe the model components and changes to the previous version, ACCESS-ESM1. We use the 500-year pre-industrial control run to highlight the stability of the physical climate and the carbon cycle. The long spin-up, negligible drift in temperature and small pre-industrial net carbon fluxes (0.02 and 0.08 PgC year−1 for land and ocean respectively) highlight the suitability of ACCESS-ESM1.5 to explore modes of variability in the climate system and coupling to the carbon cycle. The physical climate and carbon cycle for the present day have been evaluated using the CMIP6 historical simulation by comparing against observations and ACCESS-ESM1. Although there is generally little change in the climate simulation from the earlier model, many aspects of the carbon simulation are improved. An assessment of the climate response to CO2 forcing indicates that ACCESS-ESM1.5 has an equilibrium climate sensitivity of 3.87°C.

Attribution of Global Monsoon Response to the Last Glacial Maximum Forcings

Abstract Investigation of global monsoon (GM) responses to external forcings is instrumental for understanding its formation mechanism and projected future changes. Coupled climate model experiments are performed to assess how the individual and full Last Glacial Maximum (LGM) forcings change GM precipitation. Under the full LGM forcing, the annual and local summer-mean GM precipitation are reduced by 8.5% and 10.8%, respectively, compared to the results in the preindustrial control run; and the reduction of Northern Hemisphere (NH) summer monsoon (NHSM) precipitation is twice as large as its Southern Hemisphere (SH) counterpart (SHSM). The NH–SH asymmetric response is mainly caused by the monsoon circulation change–induced moisture convergence rather than the reduction of moisture content, but the root cause is the continental ice sheet forcing. The NHSM precipitation changes dramatically differ among various single-forcing experiments, while this is not the case for their SH counterparts. The moisture budget analysis indicates the NHSM is dynamically oriented, but SHSM is thermodynamically oriented. The markedly different NHSM circulation changes are caused by different forcing-induced sea surface temperature (SST) patterns, including the North Atlantic cooling pattern forced by the continental ice sheet, the mega–La Niña–like pattern resulting from the greenhouse gas forcing, and the Indian Ocean dipole–like SST pattern caused by the land–sea configuration forcing. Moreover, the distinctive change of “monsoonality” in the Australian–Indonesian monsoon is predominantly forced by the exposure of the land shelf, which enhances precipitation during early summer (November–December) but weakens it in the rest of the year.

Mitigation of Global Cooling by Stratospheric Chemistry Feedbacks in a Simulation of the Last Glacial Maximum

AbstractThe impact of changes in the stratospheric ozone profile in the Last Glacial Maximum simulation under reduced atmospheric CO2 concentrations and different orbital elements is investigated using an Earth System Model. For this, simulations including an interactive atmospheric chemistry scheme is compared with simulations using the prescribed ozone profile for a preindustrial control run of the fifth Coupled Model Intercomparison Project (CMIP5). The contribution of the interactive chemistry reveals a significant warming of zonal mean surface temperature, +0.5 K (approximately 20%) in the tropics and up to +1.6 K in high latitudes. In the tropics, this mitigation of global cooling is related to longwave radiative feedbacks associated with circulation‐driven increases in the lower stratospheric ozone and in the stratospheric water vapor, and related decrease in cirrus clouds. The mechanisms are of opposite sign to and consistent with those obtained by increased CO2 simulations. In high latitude, the stronger mitigation of cooling is associated with sea ice retreat, which has the same sign to and is consistent with our previous paleoclimate simulation of the mid‐Holocene (CO2 concentration of 280 ppm and orbital element change) including interactive chemistry. Most previous Last Glacial Maximum simulations with the prescribed ozone profile exhibited cold bias in the tropics compared with geological proxy data, whereas this bias is reduced in our simulations through the use of the interactive ozone chemistry , although a warmer bias in the midlatitude is enhanced. We recommend climate models to include ozone profiles that are consistent with CO2 concentrations and solar forcing.

Three types of Indian Ocean Basin modes

The persistence of the Indian Ocean Basin Mode (IOBM) from March to August is important for the prediction of Asian summer monsoon. Based on the observational data and the pre-industrial control run outputs of the Community Climate System Model, version 4 (CCSM4), the IOBM is categorized into three types: the first type can persist until August; the second type transforms from the positive (negative) IOBM into the negative (positive) Indian Ocean Dipole Mode (IODM), accompanied by the El Nino-to-La Nina (La Nina-to-El Nino) transition in the boreal summer; the third type transforms from the positive (negative) IOBM into the positive (negative) IODM in early summer. It is discovered that aside from the influence of anomalous Walker Circulation resulted from the phase transition of ENSO, the persistence of Australia high anomaly (AHA) over the southeastern tropical Indian Ocean (TIO) and the west of Australia from March to May is favorable for the positive (negative) IOBM transformation into the positive (negative) IODM in the boreal summer. The stronger equatorially asymmetric sea surface temperature anomalies (SSTAs) in the boreal spring are the main mechanism for the persistence of IOBM, because the asymmetric atmospheric responses to the stronger equatorially asymmetric SSTAs in the TIO confine the AHA to the east of Australia from May to August. This result indicates a possibility of predicting summer atmospheric circulation based on the equatorial symmetry of SSTAs in the TIO in spring.

The influence of internal climate variability on heatwave frequency trends

Understanding what drives changes in heatwaves is imperative for all systems impacted by extreme heat. We examine short- (13 yr) and long-term (56 yr) heatwave frequency trends in a 21‐member ensemble of a global climate model (Community Earth System Model; CESM), where each member is driven by identical anthropogenic forcings. To estimate changes dominantly due to internal climate variability, trends were calculated in the corresponding pre-industrial control run. We find that short-term trends in heatwave frequency are not robust indicators of long-term change. Additionally, we find that a lack of a long-term trend is possible, although improbable, under historical anthropogenic forcing over many regions. All long-term trends become unprecedented against internal variability when commencing in 2015 or later, and corresponding short-term trends by 2030, while the length of trend required to represent regional long-term changes is dependent on a given realization. Lastly, within ten years of a short-term decline, 95% of regional heatwave frequency trends have reverted to increases. This suggests that observed short-term changes of decreasing heatwave frequency could recover to increasing trends within the next decade. The results of this study are specific to CESM and the ‘business as usual’ scenario, and may differ under other representations of internal variability, or be less striking when a scenario with lower anthropogenic forcing is employed.

Aerosol forcing of extreme summer drought over North China

The frequency of extreme summer drought has been increasing in North China during the past sixty years, which has caused serious water shortages. It remains unclear whether anthropogenic forcing has contributed to the increasing extreme droughts. Using the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) re-analysis data and Coupled Model Intercomparison Project Phase 5 (CMIP5) model simulations with various combinations of historical forcings, the authors investigated the driving mechanism behind the observed changes. Metrological drought is usually measured by precipitation anomalies, which show lower fidelity in current climate models compared to large-scale circulation patterns. Based on NCEP/NCAR re-analysis, a linear relationship is firstly established between the weakest regional average 850 hPa southerly winds and extreme summer drought. This meridional winds index (MWI) is then used as a proxy for attribution of extreme North China drought using CMIP5 outputs. Examination of the CMIP5 simulations reveals that the probability of the extreme summer droughts with the first percentile of MWI for 1850–2004 under anthropogenic forcing has increased by 100%, on average, relative to a pre-industrial control run. The more frequent occurrence of extremely weak MWIs or drought over North China is ascribed from weakened climate and East Asian summer monsoon (EASM) circulation due to the direct cooling effect from increased aerosol.

Characterizing unforced multi-decadal variability of ENSO: a case study with the GFDL CM2.1 coupled GCM

Large multi-decadal fluctuations of El Nino-Southern Oscillation (ENSO) variability simulated in a 4000-year pre-industrial control run of GFDL CM2.1 have received considerable attention due to implications for constraining the causes of past and future changes in ENSO. We evaluated the mechanisms of this low-frequency ENSO modulation through analysis of the extreme epochs of CM2.1 as well as through the use of a linearized intermediate-complexity model of the tropical Pacific, which produces reasonable emulations of observed ENSO variability. We demonstrate that the low-frequency ENSO modulation can be represented by the simplest model of a linear, stationary process, even in the highly nonlinear CM2.1. These results indicate that CM2.1’s ENSO modulation is driven by transient processes that operate at interannual or shorter time scales. Nonlinearities and/or multiplicative noise in CM2.1 likely exaggerate the ENSO modulation by contributing to the overly active ENSO variability. In contrast, simulations with the linear model suggest that intrinsically-generated tropical Pacific decadal mean state changes do not contribute to the extreme-ENSO epochs in CM2.1. Rather, these decadal mean state changes actually serve to damp the intrinsically-generated ENSO modulation, primarily by stabilizing the ENSO mode during strong-ENSO epochs. Like most coupled General Circulation Models, CM2.1 suffers from large biases in its ENSO simulation, including ENSO variance that is nearly twice that seen in the last 50 years of observations. We find that CM2.1’s overly strong ENSO variance directly contributes to its strong multi-decadal modulation through broadening the distribution of epochal variance, which increases like the square of the long-term variance. These results suggest that the true spectrum of unforced ENSO modulation is likely substantially narrower than that in CM2.1. However, relative changes in ENSO modulation are similar between CM2.1, the linear model tuned to CM2.1, and the linear model tuned to observations, underscoring previous findings that relative changes in ENSO variance can robustly be compared across models and observations.

Method for reconstructing nonlinear modes with adaptive structure from multidimensional data.

We present a detailed description of a new approach for the extraction of principal nonlinear dynamical modes (NDMs) from high-dimensional data. The method of NDMs allows the joint reconstruction of hidden scalar time series underlying the observational variability together with a transformation mapping these time series to the physical space. Special Bayesian prior restrictions on the solution properties provide an efficient recognition of spatial patterns evolving in time and characterized by clearly separated time scales. In particular, we focus on adaptive properties of the NDMs and demonstrate for model examples of different complexities that, depending on the data properties, the obtained NDMs may have either substantially nonlinear or linear structures. It is shown that even linear NDMs give us more information about the internal system dynamics than the traditional empirical orthogonal function decomposition. The performance of the method is demonstrated on two examples. First, this approach is successfully tested on a low-dimensional problem to decode a chaotic signal from nonlinearly entangled time series with noise. Then, it is applied to the analysis of 250-year preindustrial control run of the INMCM4.0 global climate model. There, a set of principal modes of different nonlinearities is found capturing the internal model variability on the time scales from annual to multidecadal.

Complementary constraints from carbon (13C) and nitrogen (15N) isotopes on the glacial ocean's soft‐tissue biological pump

AbstractA three‐dimensional, process‐based model of the ocean's carbon and nitrogen cycles, including 13C and 15N isotopes, is used to explore effects of idealized changes in the soft‐tissue biological pump. Results are presented from one preindustrial control run (piCtrl) and six simulations of the Last Glacial Maximum (LGM) with increasing values of the spatially constant maximum phytoplankton growth rate μmax, which accelerates biological nutrient utilization mimicking iron fertilization. The default LGM simulation, without increasing μmax and with a shallower and weaker Atlantic Meridional Overturning Circulation and increased sea ice cover, leads to 280 Pg more respired organic carbon (Corg) storage in the deep ocean with respect to piCtrl. Dissolved oxygen concentrations in the colder glacial thermocline increase, which reduces water column denitrification and, with delay, nitrogen fixation, thus increasing the ocean's fixed nitrogen inventory and decreasing δ15NNO3 almost everywhere. This simulation already fits sediment reconstructions of carbon and nitrogen isotopes relatively well, but it overestimates deep ocean δ13CDIC and underestimates δ15NNO3 at high latitudes. Increasing μmax enhances Corg and lowers deep ocean δ13CDIC, improving the agreement with sediment data. In the model's Antarctic and North Pacific Oceans modest increases in μmax result in higher δ15NNO3 due to enhanced local nutrient utilization, improving the agreement with reconstructions there. Models with moderately increased μmax fit both isotope data best, whereas large increases in nutrient utilization are inconsistent with nitrogen isotopes although they still fit the carbon isotopes reasonably well. The best fitting models reproduce major features of the glacial δ13CDIC, δ15N, and oxygen reconstructions while simulating increased Corg by 510–670 Pg compared with the preindustrial ocean. These results are consistent with the idea that the soft‐tissue pump was more efficient during the LGM. Both circulation and biological nutrient utilization could contribute. However, these conclusions are preliminary given our idealized experiments, which do not consider changes in benthic denitrification and spatially inhomogenous changes in aeolian iron fluxes. The analysis illustrates interactions between the carbon and nitrogen cycles as well as the complementary constraints provided by their isotopes. Whereas carbon isotopes are sensitive to circulation changes and indicate well the three‐dimensional Corg distribution, nitrogen isotopes are more sensitive to biological nutrient utilization.

Abyssal Ocean Warming and Salinification after Weddell Polynyas in the GFDL CM2G Coupled Climate Model

AbstractThe role of Weddell Sea polynyas in establishing deep-ocean properties is explored in the NOAA Geophysical Fluid Dynamics Laboratory’s (GFDL) coupled climate model CM2G. Using statistical composite analysis of over 30 polynya events that occur in a 2000-yr-long preindustrial control run, the temperature, salinity, and water mass changes associated with the composite event are quantified. For the time period following the composite polynya cessation, termed the “recovery,” warming between 0.002° and 0.019°C decade−1 occurs below 4200 m in the Southern Ocean basins. Temperature and salinity changes are strongest in the Southern Ocean and the South Atlantic near the polynya formation region. Comparison of the model results with abyssal temperature observations reveals that the 1970s Weddell Polynya recovery could account for 10% ± 8% of the recent warming in the abyssal Southern Ocean. For individual Southern Ocean basins, this percentage is as little as 6% ± 11% or as much as 34% ± 13%.

Global monsoon change during the Last Glacial Maximum: a multi-model study

Change of global monsoon (GM) during the Last Glacial Maximum (LGM) is investigated using results from the multi-model ensemble of seven coupled climate models participated in the Coupled Model Intercomparison Project Phase 5. The GM changes during LGM are identified by comparison of the results from the pre-industrial control run and the LGM run. The results show (1) the annual mean GM precipitation and GM domain are reduced by about 10 and 5 %, respectively; (2) the monsoon intensity (demonstrated by the local summer–minus–winter precipitation) is also weakened over most monsoon regions except Australian monsoon; (3) the monsoon precipitation is reduced more during the local summer than winter; (4) distinct from all other regional monsoons, the Australian monsoon is strengthened and the monsoon area is enlarged. Four major factors contribute to these changes. The lower greenhouse gas concentration and the presence of the ice sheets decrease air temperature and water vapor content, resulting in a general weakening of the GM precipitation and reduction of GM domain. The reduced hemispheric difference in seasonal variation of insolation may contribute to the weakened GM intensity. The changed land–ocean configuration in the vicinity of the Maritime Continent, along with the presence of the ice sheets and lower greenhouse gas concentration, result in strengthened land–ocean and North–South hemispheric thermal contrasts, leading to the unique strengthened Australian monsoon. Although some of the results are consistent with the proxy data, uncertainties remain in different models. More comparison is needed between proxy data and model experiments to better understand the changes of the GM during the LGM.