The Value of Initialization on Decadal Timescales: State-Dependent Predictability in the CESM Decadal Prediction Large Ensemble

2020 ◽  
Vol 33 (17) ◽  
pp. 7353-7370
Author(s):  
H. M. Christensen ◽  
J. Berner ◽  
S. Yeager
Keyword(s):  
Time Scale ◽  
Initial Conditions ◽  
Heat Content ◽  
Atlantic Multidecadal Oscillation ◽  
Forced Response ◽  
Climate Change Signal ◽  
Seasonal Forecasts ◽  
The North ◽  
State Dependent ◽  
Start Dates

AbstractInformation in decadal climate prediction arises from a well-initialized ocean state and from the predicted response to an external forcing. The length of time over which the initial conditions benefit the decadal forecast depends on the start date of the forecast. We characterize this state-dependent predictability for decadal forecasts of upper ocean heat content in the Community Earth System Model. We find regionally dependent initial condition predictability, with extended predictability generally observed in the extratropics. We also detect state-dependent predictability, with the year of loss of information from the initialization varying between start dates. The decadal forecasts in the North Atlantic show substantial information from the initial conditions beyond the 10-yr forecast window, and a high degree of state-dependent predictability. We find some evidence for state-dependent predictability in the ensemble spread in this region, similar to that seen in weather and subseasonal-to-seasonal forecasts. For some start dates, an increase of information with lead time is observed, for which the initialized forecasts predict a growing phase of the Atlantic multidecadal oscillation. Finally we consider the information in the forecast from the initial conditions relative to the forced response, and quantify the crossover time scale after which the forcing provides more information. We demonstrate that the climate change signal projects onto different patterns than the signal from the initial conditions. This means that even after the crossover time scale has been reached in a basin-averaged sense, the benefits of initialization can be felt locally on longer time scales.

Two Limits of Initial-Value Decadal Predictability in a CGCM

2010 ◽  
Vol 23 (23) ◽  
pp. 6292-6311 ◽  
Author(s):  
Grant Branstator ◽  
Haiyan Teng
Keyword(s):  
Initial Conditions ◽  
Heat Content ◽  
Forced Response ◽  
Climate System ◽  
Change Scenario ◽  
Model Errors ◽  
Initial Value ◽  
Climate System Model ◽  
Predictive Skill ◽  
Decadal Climate

Abstract When the climate system experiences time-dependent external forcing (e.g., from increases in greenhouse gas and aerosol concentrations), there are two inherent limits on the gain in skill of decadal climate predictions that can be attained from initializing with the observed ocean state. One is the classical initial-value predictability limit that is a consequence of the system being chaotic, and the other corresponds to the forecast range at which information from the initial conditions is overcome by the forced response. These limits are not caused by model errors; they correspond to limits on the range of useful forecasts that would exist even if nature behaved exactly as the model behaves. In this paper these two limits are quantified for the Community Climate System Model, version 3 (CCSM3), with several 40-member climate change scenario experiments. Predictability of the upper-300-m ocean temperature, on basin and global scales, is estimated by relative entropy from information theory. Despite some regional variations, overall, information from the ocean initial conditions exceeds that from the forced response for about 7 yr. After about a decade the classical initial-value predictability limit is reached, at which point the initial conditions have no remaining impact. Initial-value predictability receives a larger contribution from ensemble mean signals than from the distribution about the mean. Based on the two quantified limits, the conclusion is drawn that, to the extent that predictive skill relies solely on upper-ocean heat content, in CCSM3 decadal prediction beyond a range of about 10 yr is a boundary condition problem rather than an initial-value problem. Factors that the results of this study are sensitive and insensitive to are also discussed.

scholarly journals The implications of initial model drift for decadal climate predictability using EC-Earth

2016 ◽  
Author(s):  
Andreas Sterl
Keyword(s):  
Climate Model ◽  
North Atlantic Ocean ◽  
Initial Conditions ◽  
Deep Convection ◽  
Heat Content ◽  
The North ◽  
Atmospheric Noise ◽  
Large Heat ◽  
Decadal Climate Predictability ◽  
Decadal Climate

Abstract. The large heat capacity of the ocean as compared to the atmosphere provides a memory in the climate system that might have the potential for skilful climate predictions a few years ahead. However, experiments so far have only found limited predictability after accounting for the deterministic forcing signal provided by increased greenhouse gas concentrations. One of the problems is the drift that occurs when the model moves away from the initial conditions towards its own climate. This drift is often larger than the decadal signal to be predicted. In this paper we describe the drift occurring in the North Atlantic Ocean in the EC-Earth climate model and relate it to the lack of decadal predictability in that region. While this drift may be resolution dependent and disappear in higher resolution models, we identify a second reason for the low predictability. A subsurface heat content anomaly can only influence de atmosphere if (deep) convection couples it to the surface, but the occurrence of deep convection events is random and probably mainly determined by unpredictable atmospheric noise.

scholarly journals The Value of Sustained Ocean Observations for Sea Ice Predictions in the Barents Sea

2019 ◽  
Vol 32 (20) ◽  
pp. 7017-7035 ◽  
Author(s):  
Mitchell Bushuk ◽  
Xiaosong Yang ◽  
Michael Winton ◽  
Rym Msadek ◽  
Matthew Harrison ◽  
...  
Keyword(s):  
Sea Ice ◽  
Barents Sea ◽  
Initial Conditions ◽  
Heat Budget ◽  
Heat Content ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
Seasonal Forecasts ◽  
Surface Heat Fluxes ◽  
The Barents Sea

ABSTRACT Dynamical prediction systems have shown potential to meet the emerging need for seasonal forecasts of regional Arctic sea ice. Observationally constrained initial conditions are a key source of skill for these predictions, but the direct influence of different observation types on prediction skill has not yet been systematically investigated. In this work, we perform a hierarchy of observing system experiments with a coupled global data assimilation and prediction system to assess the value of different classes of oceanic and atmospheric observations for seasonal sea ice predictions in the Barents Sea. We find notable skill improvements due to the inclusion of both sea surface temperature (SST) satellite observations and subsurface conductivity–temperature–depth (CTD) measurements. The SST data are found to provide the crucial source of interannual variability, whereas the CTD data primarily provide climatological and trend improvements. Analysis of the Barents Sea ocean heat budget suggests that ocean heat content anomalies in this region are driven by surface heat fluxes on seasonal time scales.

scholarly journals Sulfate Aerosol Control of Tropical Atlantic Climate over the Twentieth Century

2011 ◽  
Vol 24 (10) ◽  
pp. 2540-2555 ◽  
Author(s):  
C.-Y. Chang ◽  
J. C. H. Chiang ◽  
M. F. Wehner ◽  
A. R. Friedman ◽  
R. Ruedy
Keyword(s):  
Twentieth Century ◽  
Atlantic Multidecadal Oscillation ◽  
Forced Response ◽  
Sulfate Aerosol ◽  
Tropical Atlantic ◽  
Atlantic Sector ◽  
The North ◽  
Aerosol Forcing ◽  
Climate Forcings ◽  
Aerosol Emissions

Abstract The tropical Atlantic interhemispheric gradient in sea surface temperature significantly influences the rainfall climate of the tropical Atlantic sector, including droughts over West Africa and Northeast Brazil. This gradient exhibits a secular trend from the beginning of the twentieth century until the 1980s, with stronger warming in the south relative to the north. This trend behavior is on top of a multidecadal variation associated with the Atlantic multidecadal oscillation. A similar long-term forced trend is found in a multimodel ensemble of forced twentieth-century climate simulations. Through examining the distribution of the trend slopes in the multimodel twentieth-century and preindustrial models, the authors conclude that the observed trend in the gradient is unlikely to arise purely from natural variations; this study suggests that at least half the observed trend is a forced response to twentieth-century climate forcings. Further analysis using twentieth-century single-forcing runs indicates that sulfate aerosol forcing is the predominant cause of the multimodel trend. The authors conclude that anthropogenic sulfate aerosol emissions, originating predominantly from the Northern Hemisphere, may have significantly altered the tropical Atlantic rainfall climate over the twentieth century.

scholarly journals The Atlantic Multidecadal Oscillation Inferred from the Forced Climate Response in Coupled General Circulation Models

2009 ◽  
Vol 22 (7) ◽  
pp. 1610-1625 ◽  
Author(s):  
Jeff R. Knight
Keyword(s):  
North Atlantic ◽  
General Circulation ◽  
Internal Variability ◽  
Atlantic Multidecadal Oscillation ◽  
Forced Response ◽  
Climate System ◽  
Climate Response ◽  
The North ◽  
Ensemble Mean ◽  
The North Atlantic

Abstract Instrumental sea surface temperature records in the North Atlantic Ocean are characterized by large multidecadal variability known as the Atlantic multidecadal oscillation (AMO). The lack of strong oscillatory forcing of the climate system at multidecadal time scales and the results of long unforced climate simulations have led to the widespread, although not ubiquitous, view that the AMO is an internal mode of climate variability. Here, a more objective examination of this hypothesis is performed using simulations with natural and anthropogenic forcings from the Coupled Model Intercomparison Project phase 3 (CMIP3) database. Ensemble means derived from these data allow an estimate of the response of models to forcings, as averaging leads to cancellation of the internal variability between ensemble members. In general, the means of individual model ensembles appear to be inconsistent with observed temperatures, although small ensemble sizes result in uncertainty in this conclusion. Combining the ensembles from different models creates a multimodel ensemble of sufficient size to allow for a good estimate of the forced response. This shows that the variability in observed North Atlantic temperatures possess a clearly distinct signature to the climate response expected from forcings. The reliability of this finding is confirmed by sampling those models with low decadal internal variability and by comparing simulated and observed trends. In contrast to the inconsistency with the ensemble mean, the observations are consistent with the spread of responses in the ensemble members, suggesting they can be accounted for by the combined effects of forcings and internal variability. In the most recent period, the results suggest that the North Atlantic is warming faster than expected, and that the AMO entered a positive phase in the 1990s. The differences found between observed and ensemble mean temperatures could arise through errors in the observational data, errors in the models’ response to forcings or in the forcings themselves, or as a result of genuine internal variability. Each of these possibilities is discussed, and it is concluded that internal variability within the natural climate system is the most likely origin of the differences. Finally, the estimate of internal variability obtained using the model-derived ensemble mean is proposed as a new way of defining the AMO, which has important advantages over previous definitions.

scholarly journals A Comparison of Two Ensemble Generation Methods Using Oceanic Singular Vectors and Atmospheric Lagged Initialization for Decadal Climate Prediction

2016 ◽  
Vol 144 (7) ◽  
pp. 2719-2738 ◽  
Author(s):  
Camille Marini ◽  
Iuliia Polkova ◽  
Armin Köhl ◽  
Detlef Stammer
Keyword(s):  
North Atlantic ◽  
Initial Conditions ◽  
Heat Content ◽  
Forecast Skill ◽  
Meridional Overturning Circulation ◽  
Initial Time ◽  
The North ◽  
Skill Scores ◽  
The North Atlantic ◽  
Ensemble Generation

Abstract The sensitivity of ensemble spread and forecast skill scores of decadal predictions to details of the ensemble generation is investigated by incorporating uncertainties of ocean initial conditions using ocean singular-vector-based (OSV) perturbations. Results are compared to a traditional atmospheric lagged initialization (ALI) method. Both sets of experiments are performed using the coupled MPI-ESM model initialized from the GECCO2 ocean synthesis. The OSVs are calculated from a linear inverse model based on a historical MPI-ESM run. During the first three lead years, the sea surface temperature spread from ALI hindcasts appears to be strongly underestimated, while OSV hindcasts show a more realistic spread. However, for later lead times (the second pentad of hindcasts), the spread becomes overestimated for large areas of the ocean in both ensembles. Yet, for integrated measures such as the North Atlantic SST and Atlantic meridional overturning circulation, the spread of OSV hindcasts is overestimated at initial time and reduces over time. The spread reliability measures are shown to be sensitive to the choice of the verification dataset. In this context, it is found that HadISST tends to underestimate the variability of SST as compared to Reynolds SST and satellite observations. In terms of forecast skill for surface air temperature, SST, and ocean heat content, OSV hindcasts show improvement over ALI hindcasts over the North Atlantic Ocean up to lead year 5.

scholarly journals Climate predictability in the second year

2008 ◽  
Vol 367 (1890) ◽  
pp. 913-916 ◽  
Author(s):  
Leon Hermanson ◽  
Rowan T Sutton
Keyword(s):  
North Atlantic ◽  
Initial Conditions ◽  
Heat Content ◽  
Ocean Model ◽  
Ensemble Prediction ◽  
Sea Level Pressure ◽  
Tropical Precipitation ◽  
The North ◽  
Surface Temperatures

In this paper, the predictability of climate arising from ocean heat content (OHC) anomalies is investigated in the HadCM3 coupled atmosphere–ocean model. An ensemble of simulations of the twentieth century are used to provide initial conditions for a case study. The case study consists of two ensembles started from initial conditions with large differences in regional OHC in the North Atlantic, the Southern Ocean and parts of the West Pacific. Surface temperatures and precipitation are on average not predictable beyond seasonal time scales, but for certain initial conditions there may be longer predictability. It is shown that, for the case study examined here, some aspects of tropical precipitation, European surface temperatures and North Atlantic sea-level pressure are potentially predictable 2 years ahead. Predictability also exists in the other case studies, but the climate variables and regions, which are potentially predictable, differ. This work was done as part of the Grid for Coupled Ensemble Prediction (GCEP) eScience project.

North Atlantic decadal variability in a coupled global model and relevance to observations

2020 ◽  
Author(s):  
Yochanan Kushnir ◽  
Dog Run (Donna) Lee ◽  
Mingfang Ting
Keyword(s):  
Climate Change ◽  
North Atlantic ◽  
Time Scale ◽  
Decadal Variability ◽  
North Atlantic Ocean ◽  
Heat Content ◽  
Decadal Climate Variability ◽  
North Atlantic Current ◽  
Decadal Time Scale ◽  
The North

<p>This study focuses on the decadal time scale variability of the North Atlantic Ocean-Atmosphere system. This time scale is relevant to preparedness and adaptation as society becomes increasingly threatened by the adverse impact of anthropogenic climate change. North Atlantic decadal climate variability has been related to interaction between the subpolar and subtropical gyre and manifested in persistent multi-year SST and heat content anomalies and shifts in the latitude of the Gulf Stream/North Atlantic Current (GS/NAC). We apply a space-time analysis to annual, North Atlantic, upper ocean heat content (OHC) anomalies from the National Center for Atmospheric Research (NCAR), Community Earth System Model (CESM) long pre-industrial control run. The analysis reveals decadal anomalies associated with two patterns: a dipole centered on the GS/NAC, in the western side of the Basin that oscillates quasi-regularly, reversing its sign every of 6 to 7 years. The second pattern is centered in the eastern side of the basin and lags the first by about 5 years, implying that heat is transported between the subtropical and subpolar gyres. Analysis of surface windstress anomalies connected with these OHC fluctuations implies that the latter are forced by stochastic atmospheric variability. Further analysis compares the model patterns with observations to determine their relevance and predictability and assesses their response to climate change.</p>

scholarly journals Yearly evolution of Euro-Atlantic weather regimes and of their sub-seasonal predictability

2021 ◽  
Author(s):  
Nicola Cortesi ◽  
Verónica Torralba ◽  
Llorenó Lledó ◽  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
...  
Keyword(s):  
Annual Cycle ◽  
Winter Season ◽  
Skill Score ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Sea Level Pressure ◽  
Weather Regimes ◽  
Start Dates ◽  
Weekly Frequency

AbstractIt is often assumed that weather regimes adequately characterize atmospheric circulation variability. However, regime classifications spanning many months and with a low number of regimes may not satisfy this assumption. The first aim of this study is to test such hypothesis for the Euro-Atlantic region. The second one is to extend the assessment of sub-seasonal forecast skill in predicting the frequencies of occurrence of the regimes beyond the winter season. Two regime classifications of four regimes each were obtained from sea level pressure anomalies clustered from October to March and from April to September respectively. Their spatial patterns were compared with those representing the annual cycle. Results highlight that the two regime classifications are able to reproduce most part of the patterns of the annual cycle, except during the transition weeks between the two periods, when patterns of the annual cycle resembling Atlantic Low regime are not also observed in any of the two classifications. Forecast skill of Atlantic Low was found to be similar to that of NAO+, the regime replacing Atlantic Low in the two classifications. Thus, although clustering yearly circulation data in two periods of 6 months each introduces a few deviations from the annual cycle of the regime patterns, it does not negatively affect sub-seasonal forecast skill. Beyond the winter season and the first ten forecast days, sub-seasonal forecasts of ECMWF are still able to achieve weekly frequency correlations of r = 0.5 for some regimes and start dates, including summer ones. ECMWF forecasts beat climatological forecasts in case of long-lasting regime events, and when measured by the fair continuous ranked probability skill score, but not when measured by the Brier skill score. Thus, more efforts have to be done yet in order to achieve minimum skill necessary to develop forecast products based on weather regimes outside winter season.

scholarly journals Impact of air–sea coupling on the climate change signal over the Iberian Peninsula

2021 ◽  
Author(s):  
Alba de la Vara ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Claas Teichmann ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Mediterranean Sea ◽  
Large Scale ◽  
Regional Distribution ◽  
Coupled Model ◽  
Climate Change Signal ◽  
The North ◽  
The Mediterranean ◽  
The Impact

AbstractIn this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean.

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