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This paper investigates the spatial inhomogeneity of the time-averaged, quasigeostrophic, double-gyre circulation response to fixed, realistic, large-scale modes of wind-stress forcing. While the companion paper of this study focused on understanding the anatomy of low-frequency, midlatitude climate variability in an idealised, eddy-resolving coupled model, this paper looked at understanding the nature of the wind-induced ocean gyre response using an ocean-only configuration of the same model. Our analysis revealed two, time-averaged responses to an east–west dipole, wind-stress curl anomaly in the ocean basin. Firstly, wind-stress anomalies in the western ocean basin led to changes in relative strength of the inertial recirculation zones and jet-axis tilt. This is consistent with an advection-dominated, nonlinear adjustment of the ocean gyres to anomalous forcing. Secondly, wind-stress curl anomalies in the eastern ocean basin was found to induce a largely independent response involving meridional shifts of the western boundary current extension (WBCE). The effects of time-averaged advection in this region are weak and the discovery of westward-propagating Rossby waves along the WBCE revealed the response is more akin to a baroclinic Rossby wave adjustment.

This is the first of two papers that describe the generation of a 25-member perturbed parameter ensemble (PPE) of high-resolution, global coupled simulations for the period 1900–2100, using CMIP5 historical and RCP8.5 emissions. Fifteen of these 25 coupled simulations now form a subset of the global projections provided for the UK Climate Projections 2018 (UKCP18). This first paper describes the selection of 25 variants (combinations of 47 parameters) using a set of cheap, coarser-resolution atmosphere-only simulations from a large sample of nearly 3000 variants. Retrospective 5-day weather forecasts run at climate resolution, and simulations of 2004–2009 with prescribed SST and sea ice are evaluated to filter out poor performance. We opted for a single design choice and sensitivity tests were done after the PPE was generated to demonstrate the effect of design choices on the filtering. Given our choice, only 38 of the parameter combinations were found to have acceptable performance at this stage. Idealised atmosphere-only simulations were then used to select the subset of 25 members that were as diverse as possible in terms of their CO2 and aerosol forcing, and their response to warmer SSTs. Using our parallel set of atmosphere-only and coupled PPEs (the latter from paper 2), we show that local biases in the atmosphere-only experiments are generally informative about the biases in the coupled PPE. Biases in radiative fluxes and cloud amounts are strongly informative for most regions, whereas this is only true for a smaller fraction of the globe for precipitation and dynamical variables. Therefore, the cheap experiments are an affordable way to search for promising parameter combinations but have limitations.

This paper provides a quantitative assessment of large-scale features in a perturbed parameter ensemble (PPE) of Met Office Unified Model HadGEM-GC3.05 in coupled global historical and future simulations. The main motivation for the simulations is to provide a major component of the UK Climate Projections 2018 (UKCP18), but they will also be used to make worldwide projections and inform future model development. Initially, a 25-member PPE, with 25 different parameter combinations, was simulated. Five members were subsequently dropped because either their simulated climate was unrealistically cool by 1970 or they suffered from numerical instabilities. The remaining 20 members were evaluated after completing the historical phase (1900–2005) against 13 separately selected Climate Model Intercomparison Project Phase 5 (CMIP5) models, and five more members were dropped. The final product is a combined projection system of 15 PPE members and 13 CMIP5 models, which has a number of benefits. In particular, the range of outcomes available from the combined set of 28 is often larger than from either of the two constituent ensembles, thus providing users with a more complete picture of plausible impacts. Here we mainly describe the evaluation process of the 20 PPE members. We evaluate biases in a number of important properties of the global coupled system, including assessment of climatological averages, coupled modes of internal variability and historical and future changes. The parameter combinations yielded plausible yet diverse atmosphere and ocean model behaviours. The range of global temperature changes is narrow, largely driven by use of different CO2 pathways. The range of global warming is seemingly not linked to range of feedbacks estimated from atmosphere-only runs, though we caution that the range of the latter is narrow relative to CMIP5, and therefore this result is not unexpected. This is the second of two papers describing the generation of the PPE for UKCP18 projections. Part 1 (Sexton et al. 2021) describes the selection of 25 parameter combinations of 47 atmosphere and land surface parameters, using a set of cheap atmosphere-only runs at a coarser resolution from nearly 3000 samples of parameter space.

The present paper investigates changes in the feedback of Indian Ocean warming on the western Pacific by using observational data and model experiments. It is found that the relationship between easterly wind anomalies over the equatorial western Pacific and Indian Ocean warming during the mature and decaying phases of El Nino has changed since 1994. Before 1994, when El Nino reached its peak in the winter, significant warming of the entire Indian Ocean caused tropospheric temperature anomalies and emanated Kelvin waves into the western Pacific. Thus, Indian Ocean warming produced easterly wind anomalies over the western Pacific. However, significant warming of the Indian Ocean has been confined to the west of the Indian Ocean and Kelvin waves have been weakened since 1994. Therefore, the Indian Ocean has contributed less to easterly wind anomalies in the western Pacific after 1994. Changes in the intensity and pattern of the Indian Ocean dipole (IOD) mode may be responsible for these results. After 1994, the intensity of the IOD, especially the intensity of the cold component of the IOD mode, has become stronger, resulting in Indian Ocean warming being confined to the west of the Indian Ocean. These results are confirmed by numerical model experiments. The paper also discusses the enhancement in the feedback of the north tropical Atlantic on El Nino after 1994.

Dynamical downscaling (DD) consists in using archives of Coupled Global Climate Models (CGCM) simulations as the atmospheric and sea-surface boundary conditions (BC) to drive nested, Regional Climate Model (RCM) simulations. Biases in the CGCM-generated driving BC, however, can have detrimental impacts on RCM performance. It is well documented for the historical period that CGCM-simulated sea-surface temperatures (SST) suffer substantial biases, especially important near coastal regions. Assuming that these SST biases are time-invariant, they could in principle be subtracted from century-long CGCM projections before being used to drive RCMs. This paper investigates the performance of a 3-step DD approach as follows. The CGCM-simulated sea-surface temperatures (SST) are first empirically corrected by subtracting their systematic biases; the corrected SST are then used as ocean surface BC for an atmosphere-only GCM (AGCM) simulation; finally this AGCM simulation provides the atmospheric lateral BC to drive an RCM simulation. This is what we refer to as the 3-step approach CGCM–AGCM–RCM of DD, which can be compared to the traditional 2-step approach CGCM–RCM consisting of driving an RCM simulation directly by CGCM-generated BC. In this paper we compare the results obtained with the two approaches, for present and future climates under RCP8.5, using the fifth-generation Canadian Regional Climate Model (CRCM5) with a grid mesh of 0.22° over the North American CORDEX domain, driven by two CMIP5 models: the Canadian Earth System Model of the Canadian Centre for Climate modelling and analysis (CanESM2) and the Earth System Model of the Max-Planck-Institut fur Meteorologie (MPI-ESM-MR). The results show that, in current climate, the seasonal-mean 2-m temperature fields simulated with the 3-step DD have generally smaller biases with respect to the observations than those simulated with the 2-step DD; in fact the performance of the 3-step DD simulations often approaches that of the reanalyses-driven simulation. For the seasonal-mean precipitation field, however, the differences between the two DD methods are not conclusive. Differences between the projected climate changes with the two DD methods vary substantially depending upon the variable being considered. Differences are particularly important for temperature: over the bulk of the North American continent, the 3-step DD projects more warming in winter and less in summer. This result highlights the nonlinearities of the climate system, and constitutes an additional measure of uncertainty with DD.

Optimal fingerprinting is a standard method for detecting climate changes. Among the uncertainties taken into account by this method, one is the fact that the response to climate forcing is not known exactly, but in practice is estimated from ensemble averages of model simulations. This uncertainty can be taken into account using an Error-in-Variables model (or equivalently, the Total Least Squares method), and can be expressed through confidence intervals. Unfortunately, the predominant paradigm (likelihood ratio theory) for deriving confidence intervals is not guaranteed to work because the number of parameters that are estimated in the Error-in-Variables model grows with the number of observations. This paper discusses various methods for deriving confidence intervals and shows that the widely-used intervals proposed in the seminal paper by Allen and Stott are effectively equivalent to bias-corrected intervals from likelihood ratio theory. A new, computationally simpler, method for computing these intervals is derived. Nevertheless, these confidence intervals are incorrect in the “weak-signal regime”. This conclusion does not necessarily invalidate previous detection and attribution studies because many such studies lie in the strong-signal regime, for which standard methods give correct confidence intervals. A new diagnostic is introduced to check whether or not a data set lies in the weak-signal regime. Finally, and most importantly, a bootstrap method is shown to give correct confidence intervals in both strong- and weak-signal regimes, and always produces finite confidence intervals, in contrast to the likelihood ratio method which can give unbounded intervals that do not match the actual uncertainty.

Using 30 years of hourly rain gauge records and reanalysis data, this paper reveals two types of heavy summer rainfall in central North China (CNC): the lasting mountain (LM) rainfall and the mountain–plain (MP) rainfall, and further explains their formation mechanisms. The evolutions of the rainfall are found to be closely connected to upper-tropospheric temperature anomalies. When upper-tropospheric warm (cold) anomalies dominate North China (the Japan Sea) and stretch down to lower layers, positive (negative) geopotential anomalies, which appear above the warm (cold) anomalies governed by hydrostatic equilibrium, extend from upper to lower troposphere. In the lower layers, evident low-level easterly anomalies form to the south (north) of the positive (negative) geopotential center, controlling the downstream of CNC and making convective systems difficult to progress eastward. Correspondingly, the low-level convergence and strong convection maintain in the west, and the rainfall persists over the mountains constituting the LM process. But when upper-tropospheric cold (warm) anomalies dominate the west (east) of 110°E and stretch down to lower layers, CNC is situated between an upstream trough and a downstream ridge. As the trough-ridge system progresses eastward, the low-level moisture tongue and strong convections in front of the trough move from the mountains to the plains, and the rainfall propagates downstream constituting the MP process. Results in this paper indicate that upper-tropospheric temperature has significant influence on the evolution of rainfall, and pay attention to its characteristics could provide helpful information in the analysis and forecasting of rainfall propagation.

The paper examines the relationships between ENSO events and tropical cyclones (TCs) in the western North Pacific (WNP) during the ENSO decaying phase of March to July [MAMJJ(1)]. It is shown that WNP TC response is asymmetric to ENSO warm and cold events during MAMJJ(1), associated with the asymmetric patterns of oceanic and atmospheric environmental variables. Eastern Pacific warm events correspond to a westward shift in TC genesis location and a significant decrease of the TC number in the southwest subregion of the WNP, which is consistent with unfavorable atmospheric and oceanic conditions for TC activity during MAMJJ(1). Correspondingly, there is a much less WNP TC number, a shorter TC duration, and a decreased tendency in all three primary TC tracks. During MAMJJ(1) of eastern Pacific cold events, an increased TC activity in the northeast subregion results in an enhanced TC genesis number in the WNP. Central Pacific ENSO events have little effect on WNP TC activity during MAMJJ(1), except that central Pacific warm events are unfavorable for TCs to form in the northwest subregion associated with atmospheric and oceanic conditions. The paper also compares and discusses the TC response to ENSO events during the ENSO developing year of March–July.

The standard framework of predictability defines a variable to be unpredictable from a set of observations if it is independent of those observations. This definition requires comparing two distributions: a forecast distribution that is conditioned on observations, and a climatological distribution that is not. However, if the system is non-stationary because of externally forced climate changes, or is characterized by a climatological distribution that is much broader than the distribution of states over the recent past, then a rigorous application of this framework gives unsatisfying answers to reasonable questions about weather and climate predictability. This paper proposes generalizations of this framework that resolves these limitations and is consistent with the definition of independence. The first generalization, which was proposed effectively by Lorenz and Leith, is to distinguish initial-value predictability from forced predictability, where the latter is defined by time variations in the climatological distribution. This paper goes a step further by introducing a new measure, called total climate predictability, that can be decomposed into a sum of previously known measures of forced and initial-value predictability, namely relative entropy and mutual information. The second generalization, called generalized predictability, provides a new approach to filtering in such a way that processes with long time scales do not contribute to predictability. This generalization is important when the system’s climatological distribution is much broader than the range of climates experienced in the recent past. These concepts are illustrated using a simple model in which all aspects of predictability can be solved exactly.

This paper examines the three-dimensional geopotential height structure of the Madden–Julian oscillation (MJO) and proposes that the MJO convection signals can be well reflected by upper-tropospheric zonal anomalous height gradient (ZAHG, $$\nabla_{x} z'$$ ). A case study in 2011 and composite analyses have been done by applying a wavenumber-frequency filtering method on daily variable anomalies derived from different reanalysis datasets. Results show that the upper-level eastward-moving intraseasonal geopotential height anomaly does not exactly display a Rossby–Kelvin wave structure of the Gill model. Instead, it shows a height quadrupole pattern and is well associated with temperature and zonal wind anomalies. The notable tilted upper-tropospheric temperature structure can be derived from the height anomalies by the hydrostatic balance relationship. The first baroclinic mode vertical structure of zonal wind anomalies can be approximated from the height anomalies by the geostrophic equation. A highlight of the paper is the proposal of tracing the MJO convection center by the upper-tropospheric ZAHG ( $$\nabla_{x} z'$$ ). Composite analyses of all MJO events during extended winter (NDJFM) from 1979 to 2013 suggest that positive upper-tropospheric ZAHG is exactly in phase with negative outgoing longwave radiation (OLR) anomalies in the eastern Indian Ocean and Maritime Continent during a MJO event. On the other hand, positive upper-tropospheric ZAHG leads (lags) negative OLR anomalies by 1 (2) days in the western Indian Ocean (western Pacific Ocean), where MJO events generally initiate (dissipate). ZAHG can also be applied to modeling data and observation data before the satellite era. This study provides a new diagnostic parameter option to monitor MJO events, and an alternative for studying MJOs before the satellite era and model evaluation.

The purpose of this paper is to elucidate a potential use of the large samples of seasonal means that hindcasts provide for investigating different aspects of climate variability. This use of hindcasts complements their traditional uses in bias correction, real-time forecast calibration, and prediction skill assessment. For seasonal hindcast data from NCEP CFSv2 we show that a sample size 5208 for each target season is achievable. To demonstrate the utility of the proposed concept, we use this large sample dataset to illustrate how it could be used in documenting spatial variability in various moments of seasonal mean precipitation PDF over the US, and further, quantify nuances in the variations in precipitation PDF at different geographical locations with the amplitude of ENSO SSTs. It is our hope that analysis presented in this paper will accelerate utilization of seasonal hindcast datasets in furthering our understanding of different aspects of climate variability. With the advantage of the large sample size, we demonstrated that the precipitation PDF at the each grid of the CONUS can be represented by gamma distribution for a more concise and effective way to summarize precipitation variability. The availability of the large sample dataset also allowed us to analyze the statistical characteristic of the precipitation responses to the different amplitudes of ENSO SSTs. The results show that for strong warm events, enhancement in precipitation has larger amplitude than decrease in precipitation for cold events in the regions of Southern California and southeastern US. The variation of the precipitation signal over the other sub-regions including the southwestern US, mid-northwest, and mid-east shows more linear relationship with the ENSO SSTs. In response to anomalous ENSO SSTs, although the PDF of December–January–February seasonal mean precipitation anomaly is shifted from its climatological PDF, there is still a large overlap between precipitation PDFs for ENSO and its climatological counterpart. This uncertainty in seasonal mean outcomes of precipitation, therefore, limits the seasonal prediction skill.

It is well established that variations in extratropical North Pacific wind stress fields can influence the state of the tropical Pacific 12–15 months prior to the maturation of boreal winter El Nino/Southern Oscillation (ENSO) events. While most research has focused on accompanying variations in the North Pacific trade winds and underlying sea surface temperatures that subsequently shift equatorward via anomalous air–sea interactions—e.g. meridional mode dynamics—observational and numerical model analyses indicate empirical and dynamical links exist between these same trade-wind variations and concurrent changes in subsurface temperatures across the equatorial Pacific, which can also serve as a key initiator of ENSO events. This paper shows that within an observationally-constrained ocean reanalysis dataset this initiation mechanism—termed the trade-wind charging (TWC) mechanism—is induced by the second leading mode of boreal winter zonal wind stress variability over the tropical Pacific and operates separately from ENSO-induced recharge/discharge of the equatorial Pacific heat content. The paper then examines the characteristics and evolution of the ENSO and TWC modes. Results indicate that the oceanic evolution for both modes is consistent with wind stress induced vertically-integrated, meridional mass transport into and out of the equatorial Pacific—i.e. a charging and discharging of the equatorial Pacific—despite having distinctly different wind stress anomaly patterns. The process-based similarity between these two modes of tropical Pacific wind stress variability suggests that both can produce a charging/discharging of the equatorial Pacific, however one (the ENSO mode) represents part of the ENSO cycle itself and the other (the TWC mode) represents a separate forcing mechanism of that cycle.

A number of recent papers have examined sea level data, both local tide gauge records and regional/global averages, to estimate not only how fast sea level is rising but how the rate has changed over time, i.e. its pattern of acceleration and deceleration. In addition, a number of claims of cyclic/quasi-periodic variations have been proposed. However, many of these papers contain technical problems which call their results into question. In particular, the issue of autocorrelation is often ignored, and even when it is addressed its impact has sometimes been misinterpreted. Autocorrelation does more than just affect the standard errors of regression analysis, it can also make the spectrum of a noise process distinctly “red” and therefore be highly suggestive of low-frequency periodic or pseudo-periodic behavior when none is present. If any analysis is applied which acts as a band-pass filter, it can further exaggerate the illusion of oscillatory behavior. These issues are highlighted in a small number of recent papers, in order to improve the quality of future work on this subject.

Statistical downscaling methods are commonly used to address the scale mismatch between coarse resolution Global Climate Model output and the regional or local scales required for climate change impact assessments. The effectiveness of a downscaling method can be measured against four broad criteria: consistency with the existing baseline data in terms of means, trends and distributional characteristics; consistency with the broader scale climate data used to generate the projections; the degree of transparency and repeatability; and the plausibility of results produced. Many existing downscaling methods fail to fulfil all of these criteria. In this paper we examine a block bootstrap simulation technique combined with a quantile prediction and matching method for simulating future daily climate data. By utilising this method the distributional properties of the projected data will be influenced by the distribution of the observed data, the trends in predictors derived from the Global Climate Models and the relationship of these predictors to the observed data. Using observed data from several climate stations in Vanuatu and Fiji and out-of-sample validation techniques, we show that the method is successful at projecting various climate characteristics including the variability and auto-correlation of daily temperature and rainfall, the correlations between these variables and between spatial locations. This paper also illustrates how this novel method can produce more effective point scale projections and a more credible alternative to other approaches in the Pacific region.

This paper examines the uncertainty in the change in the heat content in the ocean component of a general circulation model. We describe the design and implementation of our statistical methodology. Using an ensemble of model runs and an emulator, we produce an estimate of the full probability distribution function (PDF) for the change in upper ocean heat in an Atmosphere/Ocean General Circulation Model, the Community Climate System Model v. 3, across a multi-dimensional input space. We show how the emulator of the GCM’s heat content change and hence, the PDF, can be validated and how implausible outcomes from the emulator can be identified when compared to observational estimates of the metric. In addition, the paper describes how the emulator outcomes and related uncertainty information might inform estimates of the same metric from a multi-model Coupled Model Intercomparison Project phase 3 ensemble. We illustrate how to (1) construct an ensemble based on experiment design methods, (2) construct and evaluate an emulator for a particular metric of a complex model, (3) validate the emulator using observational estimates and explore the input space with respect to implausible outcomes and (4) contribute to the understanding of uncertainties within a multi-model ensemble. Finally, we estimate the most likely value for heat content change and its uncertainty for the model, with respect to both observations and the uncertainty in the value for the input parameters.

The incidence of major storm surges in the last decade have dramatically emphasized the immense destructive capabilities of extreme water level events, particularly when driven by severe tropical cyclones. Given this risk, it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood and erosion management, engineering and for future land-use planning and to ensure the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. Australia has a long history of coastal flooding from tropical cyclones. Using a novel integration of two modeling techniques, this paper provides the first estimates of present day extreme water level exceedance probabilities around the whole coastline of Australia, and the first estimates that combine the influence of astronomical tides, storm surges generated by both extra-tropical and tropical cyclones, and seasonal and inter-annual variations in mean sea level. Initially, an analysis of tide gauge records has been used to assess the characteristics of tropical cyclone-induced surges around Australia. However, given the dearth (temporal and spatial) of information around much of the coastline, and therefore the inability of these gauge records to adequately describe the regional climatology, an observationally based stochastic tropical cyclone model has been developed to synthetically extend the tropical cyclone record to 10,000 years. Wind and pressure fields derived for these synthetically generated events have then been used to drive a hydrodynamic model of the Australian continental shelf region with annual maximum water levels extracted to estimate exceedance probabilities around the coastline. To validate this methodology, selected historic storm surge events have been simulated and resultant storm surges compared with gauge records. Tropical cyclone induced exceedance probabilities have been combined with estimates derived from a 61-year water level hindcast described in a companion paper to give a single estimate of present day extreme water level probabilities around the whole coastline of Australia. Results of this work are freely available to coastal engineers, managers and researchers via a web-based tool (www.sealevelrise.info). The described methodology could be applied to other regions of the world, like the US east coast, that are subject to both extra-tropical and tropical cyclones.

The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical applications.

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.

This paper assesses potential predictability of decadal variations in the El Nino/Southern Oscillation (ENSO) characteristics by constructing and performing simulations using an empirical nonlinear stochastic model of an ENSO index. The model employs decomposition of global sea-surface temperature (SST) anomalies into the modes that maximize the ratio of interdecadal-to-subdecadal SST variance to define low-frequency predictors called the canonical variates (CVs). When the whole available SST time series is so processed, the leading canonical variate (CV-1) is found to be well correlated with the area-averaged SST time series which exhibits a non-uniform warming trend, while the next two (CV-2 and CV-3) describe secular variability arguably associated with a combination of Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO) signals. The corresponding ENSO model that uses either all three (CVs 1–3) or only AMO/PDO-related (CVs 2 and 3) predictors captures well the observed autocorrelation function, probability density function, seasonal dependence of ENSO, and, most importantly, the observed interdecadal modulation of ENSO variance. The latter modulation, and its dependence on CVs, is shown to be inconsistent with the null hypothesis of random decadal ENSO variations simulated by multivariate linear inverse models. Cross-validated hindcasts of ENSO variance suggest a potential useful skill at decadal lead times. These findings thus argue that decadal modulations of ENSO variability may be predictable subject to our ability to forecast AMO/PDO-type climate modes; the latter forecasts may need to be based on simulations of dynamical models, rather than on a purely statistical scheme as in the present paper.

How soil moisture affects precipitation is an important question—with far reaching consequences, from weather prediction to centennial climate change—, albeit a poorly understood one. In this paper, an analysis of soil moisture–precipitation interactions over France based on observations is presented. A first objective of this paper is to investigate how large scale circulation modulates soil moisture–precipitation interactions, thanks to a weather regime approach. A second objective is to study the influence of soil moisture not only on precipitation but also on the difference between precipitation and evapotranspiration. Indeed, to have a total positive soil moisture–precipitation feedback, the potential decrease in precipitation associated with drier soils should be larger than the decrease in evapotranspiration that drier soils may also cause. A potential limited impact of soil moisture on precipitation is found for some weather regimes, but its sign depends on large scale circulation. Indeed, antecedent dry soil conditions tend to lead to smaller precipitation for the negative phase of the North Atlantic Oscillation (NAO) regime but to larger precipitation for the Atlantic Low regime. This differential response of precipitation to soil moisture anomalies depending on large scale circulation is traced back to different responses of atmospheric stability. For all circulation regimes, dry soils tend to increase the lifted condensation level, which is unfavorable to precipitation. But for the negative phase of the NAO, low soil moisture tends to lead to an increase of atmospheric stability while it tends to lead to a decrease of stability for Atlantic Low. Even if the impact of soil moisture anomalies varies depending on large scale circulation (it is larger for Atlantic low and the positive phase of the NAO), dry soils always lead to a decrease in evapotranspiration. As the absolute effect of antecedent soil moisture on evapotranspiration is always much larger than its effects on precipitation, for all circulation regimes dry soil anomalies subsequently lead to positive precipitation minus evapotranspiration anomalies i.e. the total soil moisture feedback is found to be negative. This negative feedback is stronger for the Atlantic Low and the positive phase of the NAO regimes.

Spain is one of the European countries with most environmental problems related to water scarcity and droughts. Additionally, several studies suggest trends of increasing temperature and decreasing rainfall, mainly for the Iberian Peninsula, due to climate variability and change. While Regional Climate Models (RCM) are a valuable tool for understanding climate processes, the causes and plausible impacts on variables and meteorological extremes present a wide range of associated uncertainties. The multi-model ensemble approach allows the quantification and reduction of uncertainties in the predictions. The combination of models (RCM in this case), generally increases the reliability of the predictions, although there are different weighting methodologies. In this paper, a strategy is presented for the building of non-stationary PDF (probability density functions) ensembles with the aim of evaluating the spatial pattern of future risk of drought for an area. At the same time, the uncertainty associated with the metric used in the construction of the PDF ensembles is assessed. A comparative study of methodologies based on the application of the Reliability Ensemble Averaging (REA), assessing its factors using two performance measures, on the one hand the Perkins Score Methods, on the other hand the Kolmogorov-Smirnov test, is proposed. The evaluation of the sensitivity of the methodologies used in the construction of ensembles, as proposed in this paper, although without completely eliminating uncertainty, allows a better understanding of the sources and magnitude of the uncertainties involved. Despite the differences between the spatial distribution results from each metric (which can be in the order of 40 % in some areas), both approaches concluded about a plausible significant and widespread increase throughout continental Spain of the mean value of annual maximum dry spell lengths (AMDSL) between the years 1990 and 2050. Finally, the more parsimonious approach in the building of ensembles PDF, based on AMDSL in peninsular Spain, is identified.

Stratospheric Aerosol Geoengineering (SAG) is one of the solar geoengineering approaches that have been proposed to offset some of the impacts of anthropogenic climate change. Past studies have shown that SAG may have adverse impacts on the global hydrological cycle. Using a climate model, we quantify the sensitivity of the tropical monsoon precipitation to the meridional distribution of volcanic sulfate aerosols prescribed in the stratosphere in terms of the changes in aerosol optical depth (AOD). In our experiments, large changes in summer monsoon precipitation in the tropical monsoon regions are simulated, especially over the Indian region, in association with meridional shifts in the location of the intertropical convergence zone (ITCZ) caused by changes in interhemispheric AOD differences. Based on our simulations, we estimate a sensitivity of − 1.8° ± 0.0° meridional shift in global mean ITCZ and a 6.9 ± 0.4% reduction in northern hemisphere (NH) monsoon index (NHMI; summer monsoon precipitation over NH monsoon regions) per 0.1 interhemispheric AOD difference (NH minus southern hemisphere). We also quantify this sensitivity in terms of interhemispheric differences in effective radiative forcing and interhemispheric temperature differences: 3.5 ± 0.3% change in NHMI per unit (Wm−2) interhemispheric radiative forcing difference and 5.9 ± 0.4% change per unit (°C) interhemispheric temperature difference. Similar sensitivity estimates are also made for the Indian monsoon precipitation. The establishment of the relationship between interhemispheric AOD (or radiative forcing) differences and ITCZ shift as discussed in this paper will further facilitate and simplify our understanding of the effects of SAG on tropical monsoon rainfall.

This paper is mainly concerned with the understanding and attribution of the recent observed freshening trend in the subpolar North Atlantic Ocean. From previous coupled model studies and an analysis of the long HadCM3 control simulation, it seems unlikely that this freshening trend is a direct consequence of anthropogenically forced climate change. It is shown in this paper that the subpolar North Atlantic can be freshened to the observed degree without invoking substantial large-scale surface freshwater flux changes. The source of freshening can come from a freshwater redistribution within the Arctic/subpolar North Atlantic. The redistribution (involving both liquid water and sea ice) is carried by a perturbed ocean circulation change in the subpolar seas and triggered by deep convection in the Labrador Sea. The freshening can be widespread but mainly in the north and northwest of the subpolar North Atlantic. A sustained 30–40 years freshening trend can be easily identified in specific locations such as the Labrador Sea or in the basin wide integral of freshwater storage. At the peak, the model subpolar North Atlantic can hold around 10,000 km3 of extra freshwater. An analysis of 1,400 years HadCM3 control simulation also reveals a good correlation between freshwater content anomalies and gyre transport in the subpolar North Atlantic on decadal timescales. A general mechanism involving circulation regime changes and freshwater redistribution between the subpolar North Atlantic and the Arctic/Nordic Seas is proposed, which can resolve a number of seemingly contradictory observed changes in the North Atlantic and contributes to the longer term goal of a full understanding of recent North Atlantic fresh water changes.

August 2006 was an exceptionally wet month in the Netherlands, in particular near the coast where rainfall amounts exceeded 300% of the climatological mean. August 2006 was preceded by an extremely warm July with a monthly mean temperature of almost 1°C higher than recorded in any other summer month in the period 1901–2006. This had resulted in very high sea surface temperatures (SSTs) in the North Sea at the end of July. In this paper the contribution of high SSTs to the high rainfall amounts is investigated. In the first part of this study, this is done by analyzing short-term integrations with a regional climate model (RACMO2) operated at 6 km resolution, which are different in the prescribed values of the SSTs. In the second part of the paper the influence of SSTs on rainfall is analyzed statistically on the basis of daily observations in the Netherlands during the period 1958–2006. The results from both the statistical analysis as well as the model integrations show a significant influence of SSTs on precipitation. This influence is particularly strong in the coastal area, that is, less than 30–50 km from the coastline. With favorable atmospheric flow conditions, the analyzed dependency is about +15% increase per degree temperature rise, thereby exceeding the Clausius–Clapeyron relation—which is often used as a temperature related constraint on changes in extreme precipitation—by approximately a factor of two. It is shown that the coastal area has consistently become wetter compared to the inland area since the 1950s. This finding is in agreement with the rather strong observed trend in SST over the same period and the dependencies of rainfall on SST reported in this study.

Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation.

This paper investigates the impact of equatorial wind stress on the equatorial Ekman transport during the Indian Ocean Dipole (IOD) mature phase. The results show that the equatorial zonal wind stress directly drives the meridional motion of seawater at the upper levels. In normal years, the zonal wind stress south of the equator is easterly and that north of the equator is westerly, which contributes to southward Ekman transport at the upper levels to form the climatological Indian Ocean shallow meridional overturning circulation. During the years of positive IOD events, abnormal easterly winds near the equator bring southward Ekman transport south of the equator while they bring northward Ekman transport north of the equator. This causes the seawater to move away from the equator and hence induces upwelling near the equator, which forms a pair of small circulation cells that are symmetric about the equator at the upper levels (approximately 100 m deep). The abnormal circulation cell south (north) of the equator strengthens (weakens) the southward (southward) motion south (north) of the equator. During years with negative IOD events, the opposite occurs. In addition, during the mature period of IOD, the remote sea surface temperature anomaly (SSTA) such as El Niño–Southern Oscillation (ENSO) may exert some influence on Ekman transport anomaly near the equator during the mature period of IOD.

Model simulations suggest that Madden-Julian Oscillation (MJO) activity changes under the anthropogenic climate change background. However, satellite observations, which provide information of MJO convection activity, are not available before the 1970s, hindering research on the historical long-term variability of MJO. This study aims at extending the data length of MJO indices that include both MJO circulation and convection features, such as the widely used Real-Multivariate MJO (RMM) index, to the pre-satellite era. This paper introduces a new MJO index construction method, of which the outgoing longwave radiation (OLR) input is derived from upper-level geopotential, and names it as the Geopotential-based Multivariate MJO (GMM) index. The GMM index is derived over 1902–2008 and compared with the filtered version of RMM (FMM) index during 1981–2008. The GMM index is shown to (1) have the same climatological properties as the FMM index, (2) be statistically highly correlated to the FMM index, and (3) be able to indicate MJO activities and its convection features in the pre-satellite era. The overall bivariate correlation between FMM index and GMM index based on ERA-20C ranges from 0.959 to 0.968 in different phases. Evaluation results confirm the validity of the proposed MJO index construction method, which could capture MJO convection activity in the pre-satellite era and can be applied to all MJO indices that require input of OLR. This study provides an alternative way that overcomes the difficulty of historical MJO studies, and will be beneficial to our understanding of the long-term change of MJO.

This paper investigates the characteristics and causes for the interdecadal change in the relationships between early and late summer rainfall over South China (SC). This study finds that the correlations of the precipitation over SC between June and August shift from weakly positive in 1979 – 1995 to obviously negative in 1996-2019. Further analysis demonstrates that the interdecadal variations of monthly SST anomaly (SSTA) and associated air-sea interactions in June and August account for the decadal variations of the precipitation relationships. During the prior period 1979-1995, the tropical West Indian Ocean (WIO) shows a significant positive SSTA in June, which triggers Kevin waves and an anticyclone circulation over the tropical Northwest Pacific (NWP). The warm and wet air transported by the southwest airflow at the north of the anticyclone provides favorable environmental condition to produce more precipitation over SC region in June. In contrast, the SST dipole pattern with the negative SSTAs in the maritime continent (MC) and positive SSTAs in the tropical Central Pacific (CP) is dominant in August. The SST dipole pattern is inconducive to the formation of anticyclone over SC, causing a weak positive precipitation correlation between June and August. During the latter period 1996-2019, the precipitation over SC in June is the same as that in the prior period as there is no significant decadal change in tropical WIO SST and East Asian circulation. However, an opposite phase of the SST dipole anomaly pattern in MC and the tropical CP is dominant in August during the latter period. Accordingly, the positive feedback mechanism of air-sea interaction leads to the enhancement of local convection activities in MC and the meridional Hadley circulations and the NWP subtropical high, leading to a decrease of precipitation over SC in August. Overall, the decadal variation of the SST dipole anomaly pattern in MC and the tropical CP is the key factor affecting the adjustment of the correlations between June and August precipitation in the two periods.

A coupled atmosphere–ocean–sea ice–land surface climate system model developed at the Canadian Centre for Climate Modelling and Analysis (CCCma) is used to investigate the response to glacial ice-sheet topography and decreased CO2 representative of the last glacial maximum (LGM, roughly 21,000 years before present). Imposing these glacial boundary conditions leads to a strong and rapid climate adjustment, first in the atmosphere, and then in the ocean. We describe the model and boundary conditions and analyze the initial transient response. In a subsequent paper we analyze the near-equilibrium response. During the transient phase, surface air temperature rapidly decreases with time. The rapid cooling over the Laurentide and Fennoscandian ice sheets introduces a strong inter-hemispheric asymmetry. Sea surface temperature also decreases and after 80 years of integration, ocean surface temperature has decreased by 3 °C and global surface air temperature by 5 °C. The expected overall cooling is contrasted by marked regions of unexpected localized ocean surface warming and the retreat of sea ice in the northern North Atlantic and in the high latitude Southern Ocean. This strong transient behavior, associated with more vigorous oceanic convection at these high latitudes, represents the localization of the initial response in areas remote from the direct forcing change. The strength of the North Atlantic (Southern Ocean) overturning stream function, associated with the formation of North Atlantic Deep Water (Antarctic Bottom Water), increases from 12 to 36 Sv (2 to 26 Sv). There is a marked increase in the Antarctic Circumpolar Current transport as well (from 80 to 140 Sv), even though the wind stress decreases over the Southern Ocean, presumably as a consequence of the enhanced bottom pressure torque due to an increase in the density and the formation of Antarctic Bottom Water. Both precipitation and evaporation decrease on average with time and the change in the hydrological cycle modifies sea surface salinity (SSS). SSS increases in the Arctic Ocean due to a decrease in river runoff while it decreases in the North Atlantic due to an increase in river runoff and an increase in precipitation minus evaporation. The initial (and near equilibrium) climate response to LGM forcing in the fully coupled atmosphere–ocean climate model is quite different from that in the associated atmosphere-mixed layer ocean model due to very strong oceanic feedbacks. This is especially evident where oceanic convection is active. The anomalously warm surface temperature, especially in the Southern Ocean, and the marked increase in the overturning circulation are transient features of the response to imposed LGM boundary conditions which moderate or reverse as the system approaches equilibrium (as described in the companion paper). Other differences with the mixed layer simulation include a considerably colder tropical Pacific and the development of a La Nina-like response both of which are absent in the mixed layer simulations.

Climate change leads to a more frequent occurrence of hot days (HDs) and hot nights (HNs). The consecutive occurrence of HDs and HNs (COHs) is often used as a measure of the persistence of an extremely hot spell. Nonetheless, the combined effect of air temperature and relative humidity on the changing COHs has never been studied. In this paper, we use an ensemble of global climate models and multiple thermal indices to robustly examine the combined effect of air temperature and relative humidity on COHs globally on an hourly basis. Our findings reveal that COHs show an increasing trend in the future and a strong latitudinal gradient increasing from high latitudes to the equator. Compared to COHs based on air temperature, the frequency of COHs based on perceived temperature is amplified by the combined effects of high temperature and humidity for both boreal and austral summers. To investigate the underlying mechanisms, we examine two different diurnal temperature ranges (DTRs), derived from air temperature and perceived temperature, for their corresponding types of COHs. Both DTRs are projected to increase in the future relative to the historical period from 1980 to 2004, but the DTR changes derived from perceived temperature are consistently larger than those derived from air temperature. Due to the nonlinearity in thermal indices, the perceived temperature in HDs and HNs rising faster than air temperature leads to a larger increase in perceived COHs. The COHs are further amplified by the increasing number of HNs and HDs that occur consecutively under wet conditions.

For those involved in planning for regional and local scale changes in future climate, there is a requirement for climate information to be available in a context more usually associated with meteorological timescales. Here we combine a tool used in numerical weather prediction, the 30 weather patterns produced by the Met Office, which are already applied operationally to numerical weather prediction models, to assess changes in the UK Climate Projections (UKCP) Global ensemble. Through assessing projected changes in the frequency of the weather patterns at the end of the 21st Century, we determine that future changes in large-scale circulation tend towards an increase in winter of weather patterns associated with cyclonic and westerly wind conditions at the expense of more anticyclonic, settled/blocked weather patterns. In summer, the results indicate a shift towards an increase in dry settled weather types with a corresponding reduction in the wet and windy weather types. Climatologically this suggests a shift towards warmer, wetter winters and warmer, drier summers; which is consistent with the headline findings from the UK Climate Projections 2018. This paper represents the first evaluation of weather patterns analysis within UKCP Global. It provides a detailed assessment of the changes in these weather patterns through the 21st Century and how uncertainty in emissions, structural and perturbed parameters affects these results. We show that the use of these weather patterns in tandem with the UKCP projections is useful for future work investigating changes in a range of weather-related climate features such as extreme precipitation.

Mesoscale convective systems (MCSs) are important warm-season precipitation systems in eastern China. However, our knowledge of their climatology and capability in their simulation is still insufficient. This paper examines their characteristics over the 2008–2017 warm seasons using convection-permitting climate simulations (CPCSs) with a 3-km grid spacing that explicitly resolves MCSs, as well as a high-resolution gauge-satellite merged precipitation product. An object-based tracking algorithm is applied to identify MCSs. Results indicate that the MCS genesis and occurrence are closely related to the progression of the East Asian monsoon and are modulated by the underlying topography. On average, about 243 MCSs are observed each season and contribute 19% and 47% to total and extreme warm-season precipitation. The climatological attributes and variabilities are reasonably reproduced in the CPCS. The major model deficiencies are excessive small MCS occurrence and overmuch MCS rainfall, consequently overestimating the precipitation contributions, whereas observational uncertainties may play a role too. Both the observed and simulated MCS precipitation feature a nocturnal or morning maximum and an eastward delayed diurnal peak east of the Tibetan Plateau, in contrast to the dominant afternoon peak of non-MCS precipitation. The favorable comparison with observations demonstrates the capability of CPCSs in simulating MCSs in the Asian monsoon climate, and its usefulness in projecting the future changes of MCSs under global warming. The finding that non-MCS precipitation is responsible for the high biased afternoon precipitation provides helpful guidance for further model improvement.

This paper examines the impact of Ural blocking (UB) on winter sub-seasonal Siberian cold anomalies under the different background conditions of the winter East Asian trough (EAT). It is found that the meridional displacement and the strength of the winter EAT possibly modulate the persistence or lifetime of UB and associated sub-seasonal cold anomalies over Siberia through changing background circulation conditions. Statistical analysis reveals that UB events tend to occur more frequently in strong or southward EAT winters than in weak or northward EAT winters. A composite analysis of UB events further shows that UB has larger amplitude and longer lifetime in strong or southward EAT winters (especially the latter) than in weak or northward EAT winters, thus more likely leading to stronger sub-seasonal cold anomalies over Siberia. Moreover, the possible physical cause of why a strong or southward EAT favors UB is further investigated. It is found that winter zonal wind and meridional gradient of potential vorticity (PVy) tend to be weakened on the upstream side of Siberia near the Ural Mountains when the EAT is stronger or located more southward, favoring the maintenance of UB due to the strengthening (weakening) of the nonlinearity (energy dispersion) of UB. In contrast, when the EAT is weak or northward-displaced, a strengthening of winter zonal wind and PVy is more likely seen over the Ural Mountains and adjacent regions, which may suppress UB through enhancing its energy dispersion and reducing its nonlinearity.

Analysis of wind generated waves due to the prevailing climate change induced by global warming is vital for benefit to the coastal community. In the present paper, the hindcasting of decadal variation namely (i) 1979–1992, (ii) 1993–2006, and (iii) 2007–2019 of wind-wave climate over seasonal and annual scale through 41 years starting from 1979 is carried out using ERA5 reanalysis wind-forcing with a daily temporal and 0.5° × 0.5° spatial resolution. The numerical simulations are executed over the computational domains (i) Global—Indian Ocean and (ii) Regional—south Gujarat to north Goa for evaluating the variability analysis of annual and seasonal mean significant wave heights. The evaluation framework is validated over three in-situ measurement locations with good correlation as compared to the simulated results. The results indicate that at this site the wind and wave activity is noted to increase during transition from 1979–1992 to 1993–2006, then a declination of mean significant wave height is noted during the span 2007–2019. Further, along with the spatial variation estimation, 27 locations along 15 m bathymetric contour at 25 km interval are selected for trend line study. All the 27 locations exhibits a similar kind of trend by variation of decreasing trend from 1979–2019 with variations 0.07–0.22 cm/year. This study highlights the significance in simulating the prevailing wind-wave changes at a regional level considering the impact of the climatology and seasonality changes for effective coastal management, environmental impact assessments and sustainable development.

This paper presents results from high-resolution climate change simulations that permit convection and resolve mesoscale orography at 3-km grid spacing over Fenno-Scandinavia using the HARMONIE-Climate (HCLIM) model. Two global climate models (GCMs) have been dynamically down-scaled for the RCP4.5 and RCP8.5 emission scenarios and for both near and far future periods in the 21st century. The warmer and moister climate conditions simulated in the GCMs lead to changes in precipitation characteristics. Higher precipitation amounts are simulated in fall, winter and spring, while in summer, precipitation increases in northern Fenno-Scandinavia and decreases in the southern parts of the domain. Both daily and sub-daily intense precipitation over Fenno-Scandinavia become more frequent at the expense of low-intensity events, with most pronounced shifts in summer. In the Scandinavian mountains, pronounced changes occur in the snow climate with a shift in precipitation falling as snow to rain, reduced snow cover and less days with a significant snow depth. HCLIM at 3-km grid spacing exhibits systematically different change responses in several aspects, e.g. a smaller shift from snow to rain in the western part of the Scandinavian mountains and a more consistent decrease in the urban heat island effect by the end of the 21st century. Most importantly, the high-resolution HCLIM shows a significantly stronger increase in summer hourly precipitation extremes compared to HCLIM at the intermediate 12-km grid spacing. In addition, an analysis of the statistical significance of precipitation changes indicates that simulated time periods of at least a couple of decades is recommended to achieve statistically robust results, a matter of important concern when running such high-resolution climate model experiments. The results presented here emphasizes the importance of using “convection-permitting” models to produce reliable climate change information over the Fenno-Scandinavian region.

This paper compiles indices for the El Nino—Southern Oscillation (ENSO) and seven unforced decadal-to-multidecadal climate modes (Interdecadal Pacific Oscillation (IPO), Tripole Pacific Index (TPI), Pacific Decadal Oscillation focused over North Pacific (PDO) and South Pacific (SPDO), North Atlantic Multidecadal Oscillation (AMO), South Atlantic Multidecadal Oscillation (SAMO), and Indian Ocean basin (IOB)) in a 100-member ensemble of the Max Planck Institute Earth System Model (MPI-ESM1.1) and a 35-member ensemble of Community Earth System Model (CESM1). Comparison among various detrending approaches indicates that the best approach to remove the unforced component is by subtracting the ensemble average temperature at each grid point from the original model output. Similar characteristics are investigated in the indices of both MPI-ESM1.1 and CESM1 ensemble models. The results further indicate no statistically significant lead-lag correlations between the unforced multidecadal climate modes originating from North Pacific (e.g., PDO) and North Atlantic (e.g., AMO), suggesting that a high correlation found in previous observational studies may be due to biased detrending approaches.

In this paper, the important role played by the local air-sea heat exchange in the east–west oscillation of the Western Pacific subtropical high (WPSH) on the sub-seasonal scale is revealed. First, the east–west oscillation index is defined for the WPSH using the relative vorticity field. The index can well characterize the sub-seasonal east–west oscillation of the WPSH, and it has a significant sub-seasonal cycle of 10–30 days. During the westward events, there is a cold sea surface temperature (SST) anomaly in the WPSH and its west side at the early stage of westward WPSH extension, and the cold SST anomaly makes the low-level atmosphere relatively stable, which is conducive to the generation of abnormal anticyclone, and then leads to the westward extension of the WPSH. During the westward WPSH extension, the convective activity is further suppressed; therefore, the water vapor evaporation and the cloud cover are reduced, and the net heat flux received by the ocean surface increases, eventually leading to the rise of SST. At the late stage of the westward extension, the continually enhanced warm SST causes instability of the low-level atmosphere, weakens the abnormal anticyclone, and then leads to the eastward retreat of the WPSH. Thereafter, the enhanced convective activities causes the increase of latent flux and cloud cover in the atmosphere, as well as the decrease of solar radiation flux. As a result, the warm SST anomaly weakens. The situation is the opposite for the eastward events. During the eastward or westward movement of the WPSH, beside the influence of the air-sea interaction in the WPSH region, the northward and northwestward propagation of the OLR anomaly in the tropical Indian Ocean and the Western Pacific respectively, and the SST anomaly in the equatorial western Pacific also have some influence on the WPSH east–west movement. The process of air-sea interaction is similar in the early and late summer, but the intensity of each meteorological factor is stronger in the early summer than that in late summer, which indicates that the air-sea interaction is more obvious in the early summer.

Quantifying ecological memory could be done at several levels from the rate of physiological changes in an ecosystem all the way down to responses at the genetic level. One way of unlocking the information encoded in a collective environmental memory is to examine the recorded time-series data generated by different components of an ecosystem. In this paper, we probe into the case of the Great Barrier Reef (GBR) which is threatened by elevated sea surface temperatures (SST) and ocean acidification attributed to rising atmospheric CO2 levels. Specifically, we investigate the interrelated dynamics between the degradation of the GBR, SST, and rising atmospheric CO2 levels, by considering three datasets: (a) the mean percentage hard coral cover of the GBR from the archives of the Australian Institute of Marine Science; (b) SST close to the GBR from the National Oceanic and Atmospheric Administration; and (c) the Keeling curve for atmospheric CO2 levels measured by the Mauna Loa Observatory. We show that fluctuating observables in these datasets have the same memory behavior described by a non-Markovian stochastic process. All three datasets show a good match between empirical and analytical mean square deviation. An explicit analytical form for the corresponding probability density function is obtained which obeys a modified diffusion equation with a time dependent diffusion coefficient. This study provides a new perspective on the similarities of and interaction between the GBR’s declining hard coral cover, SST, and rising atmospheric CO2 levels by putting all three systems into one unified framework indexed by a memory parameter $$\mu $$ and a characteristic frequency $$\nu $$ . The short-time dynamics of CO2 levels and SST fall in the superdiffusive regime, while the GBR exhibits hyperballistic fluctuation in percent coral cover with the highest values for $$\mu $$ and $$\nu $$ .

International audience; This paper presents a new reconstruction of the mean annual temperature obtained from a high altitude pollen sequence in equatorial Africa (3 degrees 28'S, 29 degrees 34'E, 2240 m). It has been achieved with an extended modern African reference data set by adding spectra from 228 new sites and using another selection for pollen taxa. The purpose of this paper is to test how the obtained temperature value depends upon the availability of modern analogues. The results are in good agreement with those previously published, reinforcing the validity of the method. The mean standard error is reduced by 0.3 degrees C. The mean temperature for the Holocene appears + 1.4 degrees C warmer than the present and the last glacial maximum (25-18 kyrs BP) cooling is better specified at -3 + 1.9 degrees C, a conservative value, more consistent with reconstructed sea surface temperature in the equatorial ocean.

Over time scales between 10 days and 10–20 years – the macroweather regime – atmospheric fields, including the temperature, respect statistical scale symmetries, such as power-law correlations, that imply the existence of a huge memory in the system that can be exploited for long-term forecasts. The Stochastic Seasonal to Interannual Prediction System (StocSIPS) is a stochastic model that exploits these symmetries to perform long-term forecasts. It models the temperature as the high-frequency limit of the (fractional) energy balance equation (fractional Gaussian noise) which governs radiative equilibrium processes when the relevant equilibrium relaxation processes are power law, rather than exponential. They are obtained when the order of the relaxation equation is fractional rather than integer and they are solved as past value problems rather than initial value problems. StocSIPS was first developed for monthly and seasonal forecast of globally averaged temperature. In this paper, we extend it to the prediction of the spatially resolved temperature field by treating each grid point as an independent time series. Compared to traditional global circulation models (GCMs), StocSIPS has the advantage of forcing predictions to converge to the real-world climate. It extracts the internal variability (weather noise) directly from past data and does not suffer from model drift. Here we apply StocSIPS to obtain monthly and seasonal predictions of the surface temperature and show some preliminary comparison with multi-model ensemble (MME) GCM results. For one month lead time, our simple stochastic model shows similar values of the skill scores than the much more complex deterministic models.

Climate models in the past decades have been developed to such an extent to include atmospheric chemistry as part of their climate simulations. This is necessary for providing policy-makers and other stakeholders with reliable atmospheric projections as well as information about changes in chemical species as a consequence of climate change. The regional climate model (RCM), RegCM4 is a community model which contains only one gas-phase mechanism module (CBM-Z) that includes the formation, deposition, and transport of a number of volatile organic compounds (VOCs). In this paper, the CB6-C, a new gas-phase mechanism module, is combined with RegCM4 to produce a larger suite of VOCs and chemical mechanisms for important anthropogenic and biogenic species, most notably benzene, terpenes, acetylene and their corresponding oxidation products. In order to evaluate this new module, climatologies of the CB6-C and CBM-Z simulations are compared to gridded and station data. The results reveal the two schemes to be similar with some improvement of surface carbon monoxide and tropospheric ozone in the CB6-C. However, organic products were found to be under-predicted for both schemes, suggesting the need of more development in the implementation of atmospheric chemistry in RegCM4. Despite its limitations, the input conditions (emissions and boundary conditions) are easy to modify, making the new gas-phase scheme an important advancement in the modelling of atmospheric chemistry within a RCM, as it provides a pathway for new research that may eventually help health studies.

The multidecadal regulation of wintertime extreme cold temperatures over Eurasia by the change of the North Atlantic sea surface temperature (SST) from 1950–1983 (P1) to 1984–2017 (P2) is examined in this paper. The warm Arctic–cold Siberia (WACS) trend pattern shows a distinct interdecadal transition from P1 to P2, which has a footprint of the Atlantic Multidecadal Oscillation (AMO). The positive trend of the WACS pattern during P2 coincides with the transition of AMO from its negative phase (AMO−) to positive phase (AMO+). The sea-ice reduction in Barents–Kara Seas (BKS) owing to AMO+ contributes to the BKS warming in the WACS pattern trend, while it also reduces the meridional potential vorticity gradient (PVy) over Eurasia and increases the persistence of Ural blocking (UB), thus favoring a positive WACS trend, especially a Siberian cooling trend during P2. During P1, when the AMO changes from AMO+ to AMO−, a reversed WACS pattern trend is seen because UB shows a shortened duration due to intensified PVy over Eurasia caused by increased BKS sea ice. In addition, the North Atlantic SST forcing on the WACS also shows a multiple time-scale feature. Embedded in the multidecadal timescale (≥ 50 years) of AMO, the North Atlantic SST tripole (NAT) pattern can also significantly influence the Siberian cold anomaly on decadal (10–30 years) time scales not by the BKS sea-ice decline. Even during the suppressed WACS trend period (P1) from AMO+ to AMO−, a positive WACS pattern is still seen during 1960–1970, which is mainly dominated by the NAT pattern through generating a negative-phase North Atlantic Oscillation with UB.

Climate is a special spatiotemporal dynamical system. Its time scale can be extended indefinitely, but its space scale can never exceed that of the size of the system. We call this a “mismatching” in space and time domains. With the help of a simplified system of primitive equations, this exploratory paper shows that these scale characteristics may have a significant impact on the mathematical and physical structure of the system. The results show that the mismatching of space–time scales will lead to a decrease of the system’s dimension, degenerating the system from an infinite dimensional to a finite one. Also they show that “mismatched” domains can lead to a greater consistency of the system’s structure in space, as they form a system of uniform structures which are described as “patches”. This may lead to an alternative way of representing climate and its variability as a pattern system defined by the collective behavior of interacting patches or subsystems.

We in this paper present a multi-proxy study of a 186-cm-long lacustrine sediment core (i.e., BY Core) obtained from the Youerdusi Basin in the middle Tianshan Mountains in an attempt to disentangle the causal associations among climate changes, ecological responses and hydrological variations. Palynological, assemblages and the associated biome scores indicate that the upper limit of the forest zone was closer to the Youerdusi Basin with a larger wetland extent in the Youerdusi Basin during the early part (i.e., from ~ 10.5 to ~ 5.8 cal. kyr BP) of the data-covering period (i.e., from ~ 10.5 to ~ 2.4 cal. kyr BP). The upper limit of the forest zone was farther away from the Youerdusi Basin with a smaller wetland extent in the Youerdusi Basin during the late part (i.e., from ~ 5.8 to ~ 2.4 cal. kyr BP). The changes of taiga biome score and the AP% ratio indicate a persistent cooling trend during the data-covering period which is well corroborated by various proxy data from nearby sites and the cooling trend is chronologically consistent with the trend of Northern Hemisphere temperature anomalies that was interpreted to be a delayed response to the summer solar irradiance at 50° N. The tundra biome score and the associated percentages of Cyperaceae in the Youerdusi Basin show two major stages of wetland extent variation. The wetland extent variation in the Youerdusi Basin might have been controlled by precipitation and/or by glacier-melting potential that was in turn controlled by both temperature and the extent of remained ice cover in higher elevations. The δ13Corg values obtained from the BY Core indicate a wetting trend during the data-covering period which is reasonably corroborated by various proxy data from nearby sites. We infer that the wetting trend was causally associated with the Holocene increasing trend of the North Atlantic Ocean SST (sea surface temperature) and also with the Holocene increasing trend of the westerlies’ intensity.

Abrupt climate change has an important impact on sustainable economic and social development, as well as ecosystem. However, it is very difficult to predict abrupt climate changes because the climate system is a complex and nonlinear system. In the present paper, the nonlinear local Lyapunov exponent (NLLE) is proposed as a new early warning signal for an abrupt climate change. The performance of NLLE as an early warning signal is first verified by those simulated abrupt changes based on four folding models. That is, NLLE in all experiments showed an almost monotonous increasing trend as a dynamic system approached its tipping point. For a well-studied abrupt climate change in North Pacific in 1976/1977, it is also found that NLLE shows an almost monotonous increasing trend since 1970 which give up to 6 years warning before the abrupt climate change. The limit of the predictability for a nonlinear dynamic system can be quantitatively estimated by NLLE, and lager NLLE of the system means less predictability. Therefore, the decreasing predictability may be an effective precursor indicator for abrupt climate change.

In this paper, the response of global monsoon to changes in orbital forcing is investigated using a coupled atmosphere–ocean general circulation model with an emphasis on relative roles of precession and obliquity changes. When precession decreases, there are inter-hemispheric asymmetric responses in monsoonal precipitation, featuring a significant increase over most parts of the Northern Hemisphere (NH) monsoon regions and a decrease over the Southern Hemisphere (SH) monsoon regions. In contrast, when obliquity increases, global monsoon is enhanced except for the American monsoon. Dynamic effects (caused by changes in winds with humidity unchanged) dominate the monsoonal precipitation response to both precession and obliquity forcing, while thermodynamic effects (caused by changes in humidity with winds unchanged) is related to the northward extension of the North African summer monsoon. During minimum precession, the seasonal cycle of tropical precipitation is advanced with respect to the maximum precession. The rainfall increase in the transitional season (April-June in the NH and October-December in the SH) is dominated by the dynamic component. From an energetics perspective, the southward (northward) cross-equatorial energy transport during April-June (October-December) corresponds to a northward (southward) shift of tropical precipitation, which results in a seasonal advance in the migration of tropical precipitation. Nonetheless, there is no significant change in the seasonal cycle in response to obliquity forcing.

The impact of sea surface temperature anomalies (SSTAs) over the North Pacific (32°–45° N, 140° E–150° W) and North Atlantic (north: 52°–68° N, 60°–20° W; south: 0°–30° N, 100°–40° W) on the summer surface air temperature (SAT) over the Mongolian Plateau (MP) is studied using NCEP/NCAR and Climatic Research Unit (CRU) reanalysis data. The results show that the circumglobal teleconnection (CGT) wave train related to the SSTAs in the North Atlantic propagates along with the westerly jet, resulting in a geopotential height anomaly at 200 hPa that favors an SAT anomalies (SATAs) on the MP. In addition, an anticyclonic (cyclonic) circulation anomaly with the characteristics of an atmospheric ultralong wave at 200 hPa over the Eurasia–Pacific region associated with the SSTAs in the North Pacific is also responsible for the positive (negative) SATAs on the MP. The results further reveal that the SSTAs in the North Pacific and the northern North Atlantic act synergistically on the SATAs on the MP. If there are strongly positive (negative) SSTAs in the North Pacific and the northern North Atlantic at the same time, the probability of a strongly positive (negative) SATAs on the MP is 67% (100%) for the research period of this paper. However, if the strongly positive (negative) SSTAs only appear in the North Pacific or the northern North Atlantic, the probability of a strongly positive (negative) SATAs on the MP is less than 34% (31%). The synergism of the SSTAs in the North Pacific and the northern North Atlantic enhances Rossby wave energy in Eurasia, with more Rossby wave energy spreading to the MP that in turn causes the circulation anomaly on the MP. Meanwhile, baroclinic conditions at 850 hPa north of the North Pacific, the northern and southern North Atlantic favor a northward shift of the westerly jet that guides the Rossby wave downstream so that the circulation anomaly that produces the SATAs on the MP is located in the mid–high latitudes.

Recent research suggests the widespread existence of the signal-to-noise paradox in seasonal-to-decadal climate predictions. The essence of the paradox is that the signal-to-noise ratio in models can be unrealistically small and models may make better predictions of the observations than they predict themselves. The paradox highlights a potentially serious issue with model predictions as previous studies may underestimate the limit of predictability. The focus of this paper is two-fold: the first objective is to re-examine decadal predictability from the lens of the signal-to-noise paradox in the context of CMIP5 models. We demonstrate that decadal predictability is generally underestimated in CMIP5 models possibly due to the existence of the signal-to-noise paradox. Models underestimate decadal predictability in regions where it is likely for the paradox to exist, especially over the Tropical Atlantic Ocean and Tropical Indian Ocean and eddy-rich regions, including the Gulf Stream, Kuroshio Current, and Southern Ocean. The second objective follows from the results of the first, attempting to determine if this underestimate of decadal predictability is, at least partially, due to missing ocean mesoscale processes and features in CMIP5 models. A suite of coupled model experiments is performed with eddying and eddy-parameterized ocean component. Compared with eddy-parameterized models, the paradox is less likely to exist in eddying models, particularly over eddy-rich regions. These also happen to be regions where increased decadal predictability is identified. We hypothesize that this enhanced predictability is due to the enhanced vertical connectivity in the ocean. The presence of mesoscale ocean features and associated vertical connectivity significantly influence decadal variability, predictability, and the signal-to-noise paradox.

Atmospheric blockings are generally associated with large-scale high-pressure systems that interrupt west-to-east atmospheric flow in mid and high latitudes. Blockings cause several days of quasi-stationary weather conditions, and therefore can result in monthly or seasonal climate anomalies and extreme weather events on the affected regions. In this paper, the long-term coupled CERA-20C reanalysis data from 1901 to 2010 are used to evaluate the links between blocking events over the North Atlantic north of 35° N, and atmospheric and oceanic modes of climate variability on decadal time scales. This study indicates more frequent and longer lasting blocking events than previous studies using other reanalyses products. A strong relationship was found between North Atlantic blocking events and North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO) and Baffin Island–West Atlantic (BWA) indices, in fall, winter and spring. More blocking events occur during the negative phases of the NAO index and positive phases of the BWA mode. In some situations, the BWA patterns provide clearer links with the North Atlantic blocking occurrence than with the NAO alone. The correlation between the synchronous occurrences of AMO and blocking is generally weak, although it does increase for a lag of about 6–10 years. Convergent cross mapping (CCM) furthermore demonstrates a significant two-way causal effect between blocking occurrences and the NAO and BWA indices. Finally, while we find no significant trends in blocking frequencies over the last 110 years in the Northern Hemisphere, these events become longer lasting in summer and fall, and more intense in spring in the North Atlantic.