20th Century Simulations Research Articles

Recent impact of reduced arctic sea-ice on the winter North Atlantic jet stream and its quantitative contributions compared to pre-industrial level

It has been a challenge to identify the impact of Arctic sea-ice loss on the intensity and position of the winter North Atlantic jet stream (NAJS) and the related mechanisms due to the uncertain effects of atmospheric internal variability. This study investigates the response of the winter NAJS to Arctic sea-ice loss and roughly estimates the contribution of internal variability in Arctic sea ice (ArcSIC) after the pre-industrial period, based on reanalysis dataset (referred to as observation here), the Coupled Model Inter-comparison Project phase 6 (CMIP6) and the Polar Amplification Model Inter-comparison Project (PAMIP). The results indicate that the majority of PAMIP models display robust but weak equatorward shift of the NAJS response to Arctic sea-ice loss, as well as robust NAJS-related circulation anomalies. Further analysis shows that the ability of models to reproduce observed NAJS response is primarily associated with tropospheric baroclinic wave activity and the troposphere–stratosphere coupling. Based on 20th-Century reanalysis data and CMIP6 historical simulations, we further estimate the relative contributions of external forcing and internal variability (including reduced ArcSIC) to NAJS latitude and speed variability. Compared to the pre-industrial period, the recent winter NAJS at 850 hPa has accelerated and shifted poleward. By calculating the ratio of the difference in NAJS speed (latitude) between the present-day and pre-industrial in CMIP6 multi-model ensemble mean to the difference in observation, this study approximately estimates that the external forcing contributes about 40 % of NAJS acceleration with minimal influence on its shift. The remaining acceleration and poleward shift are mainly attributed to internal variability. The difference between the present-day and pre-industrial PAMIP ensemble mean is considered as the “pure” forcing of Arctic sea-ice loss. Most models indicate that reduced ArcSIC tends to slow down the acceleration and poleward shift of winter NAJS, but show quantitively a wide range of uncertainty.

The underestimated magnitude and decline trend in near‐surface wind over China

AbstractThis study reports the magnitude, spatial pattern and temporal trend of near‐surface wind speed (NWS) by comparing 20th century simulations in Coupled Model Intercomparison Project phase 5 (CMIP5) and 3 (CMIP3) and the climate reanalyses with measurements at 563 weather stations in China over 1961–2005. Both CMIP5 and CMIP3 agree quite well with observations in reproducing the spatial pattern of annual mean NWS. CMIP5 models are superior to CMIP3 models in hindcasting the magnitude and spatial pattern of seasonal mean NWS, the temporal trend in annual and seasonal mean NWS. Although both CMIP3 and CMIP5 reproduced the decline trend in the annual and seasonal mean NWS, the hindcasted decline rate is smaller than observed decline trend by the magnitude of one order. The ensemble of optimal models that are better correlated to observations in both NWS and temporal trend possesses advantages over individual model hindcast and reanalyses. The reanalyzed data are not able to represent the observed either the spatial pattern or the decline trend of NWS. The analyses presented here reveal the uncertainties in the current wind field products including reanalyses and model outputs and highlight the benefits of parameterization development and increased horizontal resolution in the new‐generation CMIP models.

Response of Water Use Efficiency to Global Environmental Change Based on Output From Terrestrial Biosphere Models

AbstractWater use efficiency (WUE), defined as the ratio of gross primary productivity and evapotranspiration at the ecosystem scale, is a critical variable linking the carbon and water cycles. Incorporating a dependency on vapor pressure deficit, apparent underlying WUE (uWUE) provides a better indicator of how terrestrial ecosystems respond to environmental changes than other WUE formulations. Here we used 20th century simulations from four terrestrial biosphere models to develop a novel variance decomposition method. With this method, we attributed variations in apparent uWUE to both the trend and interannual variation of environmental drivers. The secular increase in atmospheric CO2 explained a clear majority of total variation (66 ± 32%: mean ± one standard deviation), followed by positive trends in nitrogen deposition and climate, as well as a negative trend in land use change. In contrast, interannual variation was mostly driven by interannual climate variability. To analyze the mechanism of the CO2 effect, we partitioned the apparent uWUE into the transpiration ratio (transpiration over evapotranspiration) and potential uWUE. The relative increase in potential uWUE parallels that of CO2, but this direct CO2 effect was offset by 20 ± 4% by changes in ecosystem structure, that is, leaf area index for different vegetation types. However, the decrease in transpiration due to stomatal closure with rising CO2 was reduced by 84% by an increase in leaf area index, resulting in small changes in the transpiration ratio. CO2 concentration thus plays a dominant role in driving apparent uWUE variations over time, but its role differs for the two constituent components: potential uWUE and transpiration.

Projecting South Asian summer precipitation in CMIP3 models: A comparison of the simulations with and without black carbon

Considering the importance of black carbon (BC), this study began by comparing the 20th century simulation of South Asian summer climate in IPCC CMIP3, based on the scenario of models with and without BC. Generally, the multi-model mean of the models that include BC reproduced the observed climate relatively better than those that did not. Then, the 21st century South Asian summer precipitation was projected based on the IPCC CMIP3 projection simulations. The projected precipitation in the present approach exhibited a considerable difference from the multimodel ensemble mean (MME) of IPCC AR4 projection simulations, and also from the MME of the models that ignore the effect of BC. In particular, the present projection exhibited a dry anomaly over the central Indian Peninsula, sandwiched between wet conditions on the southern and northern sides of Pakistan and India, rather than homogeneous wet conditions as seen in the MME of IPCC AR4. Thus, the spatial pattern of South Asian summer rainfall in the future may be more complicated than previously thought.

Chinese contribution to CMIP5: An overview of five Chinese models’ performances

An overview of Chinese contribution to Coupled Model Intercomparison Project-Phase 5 (CMIP5) is presented. The performances of five Chinese Climate/Earth System Models that participated in the CMIP5 project are assessed in the context of climate mean states, seasonal cycle, intraseasonal oscillation, interannual variability, interdecadal variability, global monsoon, Asian-Australian monsoon, 20th-century historical climate simulation, climate change projection, and climate sensitivity. Both the strengths and weaknesses of the models are evaluated. The models generally show reasonable performances in simulating sea surface temperature (SST) mean state, seasonal cycle, spatial patterns of Madden-Julian oscillation (MJO) amplitude and tropical cyclone Genesis Potential Index (GPI), global monsoon precipitation pattern, El Nino-Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO) related SST anomalies. However, the performances of the models in simulating the time periods, amplitude, and phase locking of ENSO, PDO time periods, GPI magnitude, MJO propagation, magnitude of SST seasonal cycle, northwestern Pacific monsoon and North American monsoon domains, as well as the skill of large-scale Asian monsoon precipitation need to be improved. The model performances in simulating the time evolution and spatial pattern of the 20th-century global warming and the future change under representative concentration pathways projection are compared to the multimodel ensemble of CMIP5 models. The model discrepancies in terms of climate sensitivity are also discussed.

Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction

Abstract. When correcting for biases in general circulation model (GCM) output, for example when statistically downscaling for regional and local impacts studies, a common assumption is that the GCM biases can be characterized by comparing model simulations and observations for a historical period. We demonstrate some complications in this assumption, with GCM biases varying between mean and extreme values and for different sets of historical years. Daily precipitation and maximum and minimum temperature from late 20th century simulations by four GCMs over the United States were compared to gridded observations. Using random years from the historical record we select a "base" set and a 10 yr independent "projected" set. We compare differences in biases between these sets at median and extreme percentiles. On average a base set with as few as 4 randomly-selected years is often adequate to characterize the biases in daily GCM precipitation and temperature, at both median and extreme values; 12 yr provided higher confidence that bias correction would be successful. This suggests that some of the GCM bias is time invariant. When characterizing bias with a set of consecutive years, the set must be long enough to accommodate regional low frequency variability, since the bias also exhibits this variability. Newer climate models included in the Intergovernmental Panel on Climate Change fifth assessment will allow extending this study for a longer observational period and to finer scales.

Response of mode water and Subtropical Countercurrent to greenhouse gas and aerosol forcing in the North Pacific

The response of the North Pacific Subtropical Mode Water and Subtropical Countercurrent (STCC) to changes in greenhouse gas (GHG) and aerosol is investigated based on the 20th-century historical and single-forcing simulations with the Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL CM3). The aerosol effect causes sea surface temperature (SST) to decrease in the mid-latitude North Pacific, especially in the Kuroshio Extension region, during the past five decades (1950–2005), and this cooling effect exceeds the warming effect by the GHG increase. The STCC response to the GHG and aerosol forcing are opposite. In the GHG (aerosol) forcing run, the STCC decelerates (accelerates) due to the decreased (increased) mode waters in the North Pacific, resulting from a weaker (stronger) front in the mixed layer depth and decreased (increased) subduction in the mode water formation region. The aerosol effect on the SST, mode waters and STCC more than offsets the GHG effect. The response of SST in a zonal band around 40°N and the STCC to the combined forcing in the historical simulation is similar to the response to the aerosol forcing.

A unifying view of climate change in the Sahel linking intra-seasonal, interannual and longer time scales

We propose a re-interpretation of the oceanic influence on the climate of the African Sahel that is consistent across observations, 20th century simulations and 21st century projections, and that resolves the uncertainty in projections of precipitation change in this region: continued warming of the global tropical oceans increases the threshold for convection, potentially drying tropical land, but this ‘upped ante’ can be met if sufficient moisture is supplied in monsoon flow. In this framework, the reversal to warming of the subtropical North Atlantic, which is now out-pacing warming of the global tropical oceans, provides that moisture, and explains the partial recovery in precipitation since persistent drought in the 1970s and 1980s. We find this recovery to result from increases in daily rainfall intensity, rather than in frequency, most evidently so in Senegal, the westernmost among the three Sahelian countries analyzed. Continuation of these observed trends is consistent with projections for an overall wetter Sahel, but more variable precipitation on all time scales, from intra-seasonal to multi-decadal.

Long-term behaviors of two versions of FGOALS2 in preindustrial control simulations with implications for 20th century simulations

Climate drift in preindustrial control (PICTL) simulations can lead to spurious climate trends and large uncertainties in historical and future climate simulations in coupled models. This study examined the longterm behaviors and stabilities of the PICTL simulations in the two versions of FGOALS2 (the Flexible Global Ocean-Atmosphere-Land System model Version 2), which have been submitted to the Coupled Model Intercomparison Project Phase 5 (CMIP5). As verified by examining time series of thermal fields and their linear trends, the PICTL simulations showed stable long-term integration behaviors and no obvious climate drift [the magnitudes of linear trends of SST were both less than 0.04°C (100 yr)−1] over multiple centuries. The changed SSTs in a century (that corresponded to the linear trends) were less than the standard deviations of annual mean values, which implied the internal variability was not affected. These trend values were less than 10% of those of global averaged SST from observations and historical runs during the periods of slow and rapid warming. Such stable long-term integration behaviors reduced the uncertainty of the estimation of global warming rates in the historical and future climate projections in the two versions of FGOALS2. Compared with the trends in the Northern Hemisphere, larger trends existed in the SST and sea ice extents at the middle to high latitudes of the Southern Hemisphere (SH). To estimate the historical and future climate trends in the SH or at some specific regions in FGOALS2, corrections needed to be carried out. The similar long-term behaviors in the two versions of FGOALS2 may be attributed to proper physical processes in the ocean model.

Simulation of sea ice in FGOALS-g2: Climatology and late 20th century changes

Sea ice is an important component in the Earth’s climate system. Coupled climate system models are indispensable tools for the study of sea ice, its internal processes, interaction with other components, and projection of future changes. This paper evaluates the simulation of sea ice by the Flexible Global Ocean-Atmosphere-Land System model Grid-point Version 2 (FGOALS-g2), in the fifth phase of the Coupled Model Inter-comparison Project (CMIP5), with a focus on historical experiments and late 20th century simulation. Through analysis, we find that FGOALS-g2 produces reasonable Arctic and Antarctic sea ice climatology and variability. Sea ice spatial distribution and seasonal change characteristics are well captured. The decrease of Arctic sea ice extent in the late 20th century is reproduced in simulations, although the decrease trend is lower compared with observations. Simulated Antarctic sea ice shows a reasonable distribution and seasonal cycle with high accordance to the amplitude of winter-summer changes. Large improvement is achieved as compared with FGOALS-g1.0 in CMIP3. Diagnosis of atmospheric and oceanic forcing on sea ice reveals several shortcomings and major aspects to improve upon in the future: (1) ocean model improvements to remove the artificial island at the North Pole; (2) higher resolution of the atmosphere model for better simulation of important features such as, among others, the Icelandic Low and westerly wind over the Southern Ocean; and (3) ocean model improvements to accurately receive freshwater input from land, and higher resolution for resolving major water channels in the Canadian Arctic Archipelago.

Interactive ozone and methane chemistry in GISS-E2 historical and future climate simulations

Abstract. The new generation GISS climate model includes fully interactive chemistry related to ozone in historical and future simulations, and interactive methane in future simulations. Evaluation of ozone, its tropospheric precursors, and methane shows that the model captures much of the large-scale spatial structure seen in recent observations. While the model is much improved compared with the previous chemistry-climate model, especially for ozone seasonality in the stratosphere, there is still slightly too rapid stratospheric circulation, too little stratosphere-to-troposphere ozone flux in the Southern Hemisphere and an Antarctic ozone hole that is too large and persists too long. Quantitative metrics of spatial and temporal correlations with satellite datasets as well as spatial autocorrelation to examine transport and mixing are presented to document improvements in model skill and provide a benchmark for future evaluations. The difference in radiative forcing (RF) calculated using modeled tropospheric ozone versus tropospheric ozone observed by TES is only 0.016 W m−2. Historical 20th Century simulations show a steady increase in whole atmosphere ozone RF through 1970 after which there is a decrease through 2000 due to stratospheric ozone depletion. Ozone forcing increases throughout the 21st century under RCP8.5 owing to a projected recovery of stratospheric ozone depletion and increases in methane, but decreases under RCP4.5 and 2.6 due to reductions in emissions of other ozone precursors. RF from methane is 0.05 to 0.18 W m−2 higher in our model calculations than in the RCP RF estimates. The surface temperature response to ozone through 1970 follows the increase in forcing due to tropospheric ozone. After that time, surface temperatures decrease as ozone RF declines due to stratospheric depletion. The stratospheric ozone depletion also induces substantial changes in surface winds and the Southern Ocean circulation, which may play a role in a slightly stronger response per unit forcing during later decades. Tropical precipitation shifts south during boreal summer from 1850 to 1970, but then shifts northward from 1970 to 2000, following upper tropospheric temperature gradients more strongly than those at the surface.

Systematic winter sea-surface temperature biases in the northern Arabian Sea in HiGEM and the CMIP3 models

Analysis of 20th century simulations of the High resolution Global Environment Model (HiGEM) and the Third Coupled Model Intercomparison Project (CMIP3) models shows that most have a cold sea-surface temperature (SST) bias in the northern Arabian Sea during boreal winter. The association between Arabian Sea SST and the South Asian monsoon has been widely studied in observations and models, with winter cold biases known to be detrimental to rainfall simulation during the subsequent monsoon in coupled general circulation models. However, the causes of these SST biases are not well understood. Indeed this is one of the first papers to address causes of the cold biases. The models show anomalously strong north-easterly winter monsoon winds and cold air temperatures in north-west India, Pakistan and beyond. This leads to the anomalous advection of cold, dry air over the Arabian Sea. The cold land region is also associated with an anomalously strong meridional surface temperature gradient during winter, contributing to the enhanced low-level convergence and excessive precipitation over the western equatorial Indian Ocean seen in many models.

Two interannual variability modes of the Northwestern Pacific Subtropical Anticyclone in boreal summer

Using the reanalysis data and 20th century simulation of coupled model FGOALS_gl developed by LASG/IAP, we identified two distinct interannual modes of Northwestern Pacific Subtropical Anticyclone (NWPAC) by performing Empirical Orthogonal Function (EOF) analysis on 850 hPa wind field over the northwestern Pacific in summer. Based on the associated anomalous equatorial zonal wind, these two modes are termed as “Equatorial Easterly related Mode” (EEM) and “Equatorial Westerly related Mode” (EWM), respectively. The formation mechanisms of these two modes are similar, whereas the maintenance mechanisms, dominant periods, and the relationships with ENSO are different. The EEM is associated with El Nino decaying phase, with the anomalous anticyclone established in the preceding winter and persisted into summer through local positive air-sea feedback. By enhancing equatorial upwelling of subsurface cold water, EEM favors the transition of ENSO from El Nino to La Nina. The EWM is accompanied by the El Nino events with long persistence, with the anomalous anticyclone formed in spring and strengthened in summer due to the warm Sea Surface Temperature anomalies (SSTA) forcing from the equatorial central-eastern Pacific. The model well reproduces the spatial patterns of these two modes, but fails to simulate the percentage variance accounted for by the two modes. In the NCEP reanalysis (model result), EEM (EWM) appears as the first mode, which accounts for 35.6% (68.2%) of the total variance.

Total cloud cover from satellite observations and climate models

Global and zonal monthly means of cloud cover fraction for total cloudiness (CF) from the ISCCP D2 dataset are compared to same quantities produced by the 20th century simulations of 21 climate models from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3). The comparison spans the time frame from January 1984 to December 1999 and the global and zonal averages of CF are studied. It is shown that the global mean of CF for the PCMDI-CMIP3 models, averaged over the whole period, exhibits a considerable variance and generally underestimates the ISCCP value. Large differences among models, and between models and observations, are found in the polar areas, where both models and satellite observations are less reliable, and especially near Antarctica. For this reason the zonal analysis is focused over the 60° S–60° N latitudinal belt, which includes the tropical area and mid-latitudes. The two hemispheres are analysed separately to show the variation of the amplitude of the seasonal cycle. Most models underestimate the yearly averaged values of CF over all the analysed areas, whilst they capture, in a qualitatively correct way, the magnitude and the sign of the seasonal cycle over the whole geographical domain, but overestimate the amplitude of the seasonal cycle in the tropical areas and at mid-latitudes, when taken separately. The interannual variability of the yearly averages is underestimated by all models in each area analysed, and also the interannual variability of the amplitude of the seasonal cycle is underestimated, but to a lesser extent. This work shows that the climate models have a heterogeneous behaviour in simulating the CF over different areas of the Globe, with a very wide span both with observed CF and among themselves. Some models agree quite well with the observations in one or more of the metrics employed in this analysis, but not a single model has a statistically significant agreement with the observational datasets on yearly averaged values of CF and on the amplitude of the seasonal cycle over all analysed areas.

Year-to-Year Variations in the Meiyu and Baiu Frontal Precipitation Zones in the CMIP3 20th Century Simulation

Year-to-Year Variations in the Meiyu and Baiu Frontal Precipitation Zones in the CMIP3 20th Century Simulation

Characteristics of Intense Rainfalls over Southwestern Japan in the Baiu Season in the CMIP3 20th Century Simulation and 21st Century Projection

Characteristics of Intense Rainfalls over Southwestern Japan in the Baiu Season in the CMIP3 20th Century Simulation and 21st Century Projection

Changes in precipitation extremes over Eastern China simulated by the Beijing Climate Center ­Climate System Model (BCC_CSM1.0)

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 50:227-245 (2011) - DOI: https://doi.org/10.3354/cr01066 Contribution to the CR Special: 'Changes in climatic extremes over mainland China' Changes in precipitation extremes over Eastern China simulated by the Beijing Climate Center ­Climate System Model (BCC_CSM1.0) Li Zhang*, Min Dong, Tongwen Wu Beijing Climate Center, China Meteorological Administration, Beijing, PR China *Email: zhangli@cma.gov.cn ABSTRACT: Performance of the Beijing Climate Center Climate System Model (BCC_CSM1.0) in simulating the regional extreme precipitation change over eastern China east of 105°E was evaluated. Daily observed precipitation data for 1956–2009 at 349 rain gauge stations in China were used for comparison. The 20th century simulation forced by observed greenhouse gases, aerosols, solar irradiance and volcanic aerosols shows that (1) BCC_CSM1.0 can reproduce the basic feature of observed climatology of annual total precipitation and extreme precipitation over the 95th percentile, with spatial correlation of 0.77 for both of them. (2) BCC_CSM1.0 is also able to capture the main change patterns of yearly accumulated extreme precipitation above the 95th percentile, although there are some model biases in the spatial extension and strength. Some model biases are also noted: (1) Annual total and extreme precipitation south of Yangtze River are underestimated. (2) Frequency of heavy precipitation (≥25.0 mm d–1) over eastern China is underestimated, but the frequency of light rain (0.1 to 9.9 mm d–1) is overestimated. (3) Simulated long-term trends of annual extreme precipita­tion amount and frequency in the last 50 yr are the opposite of the observations in North and South China. KEY WORDS: Extreme precipitation · Eastern China · BCC_CSM1.0 · Evaluation Full text in pdf format PreviousNextCite this article as: Zhang L, Dong M, Wu T (2011) Changes in precipitation extremes over Eastern China simulated by the Beijing Climate Center ­Climate System Model (BCC_CSM1.0). Clim Res 50:227-245. https://doi.org/10.3354/cr01066 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 50, No. 2-3. Online publication date: December 22, 2011 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2011 Inter-Research.

Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions

Future widespread coral bleaching and subsequent mortality has been projected using sea surface temperature (SST) data derived from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Nino Southern Oscillation (ENSO) variability. Such weaknesses most likely reduce the accuracy of pre- dicting coral bleaching, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends, and their propagation in predictions. To analyze the relative impor- tance of various types of model errors and biases in pre- dicting coral bleaching, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from 24 GCMs 20th century simulations included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate accuracy using an objective measure of forecast quality, the Peirce skill score (PSS). Major findings are that: (1) predictions are most sensitive to the seasonal cycle and inter-annual variability in the ENSO 24-60 months frequency band and (2) because models tend to understate the seasonal cycle at reef locations, they systematically underestimate future bleaching. The methodology we describe can be used to improve the accuracy of bleaching predictions by characterizing the errors and uncertainties involved in the predictions.

Detectable regional changes in the number of warm nights

[1] In this study we analyse gridded observed and multi‐ model simulated trends in the annual number of warm nights during the second half of the 20th century. We show that there is evidence that external forcing has significantly increased the number of warm nights, both globally and over many regions. We define thirteen regions with a high density of observational data over two datasets, for which we compare observed and simulated trends from 20th century simulations. The main analysis period is 1951–1999, with a sub‐period of 1970–1999. In order to investigate if observed trends changed past 1999, we also analysed periods of 1955–2003 and 1974–2003. Both observed and ensemble mean model data from all models analysed show a positive trend for the regional mean number of warm nights in all regions within this 49 year period (1951–1999). The trends tend to become more pronounced over the sub‐period 1970–1999 and even more so up to 2003. We apply a fingerprint analysis to assess if trends are detectable relative to internal climate variability.Wefindthat changes in the globalscale analysis, and in 9 out of 13 regions, are detectable at the 5% significance level. A large part of the observed global‐scale trend in TN90 results from the trend in mean temperature, which has been attributed largely to anthropogenic greenhouse gas increase. This suggests that the detected global‐ scale trends in the number of warm nights are at least partly anthropogenic. Citation: Morak,S., G.C. Hegerl,andJ. Kenyon (2011), Detectable regional changes in the number of warm nights, Geophys. Res. Lett., 38, L17703, doi:10.1029/2011GL048531.

Tropical Pacific-North Pacific teleconnection in a coupled GCM: remote and local effects

The connection between Tropical Pacific and North Pacific variability is investigated in a state-of-the-art coupled ocean-atmosphere model, comparing two 20th century simulations at T30 and T106 atmospheric horizontal resolutions. Despite a better simulation of the frequency and the spatial distribution of the Tropical Pacific anomalies associated with the El Niño Southern Oscillation (ENSO) in the high-resolution experiment, the response in the North Pacific is scarcely different from the low-resolution experiment where the ENSO variability is weaker and at higher than observed frequency. In the North Pacific, the response of surface atmospheric fields to the variability in the Tropical Pacific appears to be affected by local coupling processes significantly different in the two experiments. The coupling between sea level pressure (SLP) and sea surface temperature (SST) in the North Pacific as well as the influence of the Tropical Pacific SST has been measured here by means of the ‘coupled manifold’ technique. In the low-resolution case the SLP variances linked to the fraction of North Pacific SST not influenced by the Tropical Pacific are weak suggesting that the remote influence is strong, consistently with the observations. On the contrary, in the high-resolution experiment the fractions and the patterns of the SLP variances due to the Tropical Pacific SST and those linked to the North Pacific SST are comparable. In the latter case, model systematic errors in the northwestern Pacific influences the local coupling processes thus triggering the remote response. We conclude that an increased atmospheric horizontal resolution does not reduce the coupled model systematic errors in the representation of the teleconnection between the North and the Tropical Pacific and that the validation of coupled models has to consider both remote and local processes. Copyright © 2011 Royal Meteorological Society