Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO2 concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2 to 5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6 to 9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2 to 5 years and 6 to 9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6 to 9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.

The coupled model predictability of the Western North Pacific summer monsoon with different leading times

Leading time length is an important issue for modeling seasonal forecasts. In this study, a comparison of the interannual predictability of the Western North Pacific (WNP) summer monsoon between different leading months was performed by using one-, four-, and seven-month lead retrospective forecasts (hindcasts) of four coupled models from Ensembles-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) for the period of 1960-2005. It is found that the WNP summer anomalies, including lower-tropospheric circulation and precipitation anomalies, can be well predicted for all these leading months. The accuracy of the four-month lead prediction is only slightly weaker than that of the one-month lead prediction, although the skill decreases with the increase of leading months.

The coupled δ13C-radiocarbon systematics of three Late Glacial/early Holocene speleothems: insights into soil and caveprocesses at climatic transitions

The coupled δ13C-radiocarbon systematics of threeEuropean stalagmites deposited during the Late Glacial and early Holocene were investigated to understand better how the carbon isotope systematics of speleothems respond to climate transitions. The emphasis is on understanding how speleothems may record climate-driven changes in the proportions of biogenic (soil carbon) and limestone bedrock derived carbon. At two of the three sites, the combined δ13C and 14C data argue against greater inputs of limestone carbon as the sole cause of the observed shift to higher δ13C during the cold Younger Dryas. In these stalagmites (GAR-01 from La Garma cave, N. Spain and So-1 from Sofular cave, Turkey), the combined changes in δ13C and initial 14C activities suggest enhanced decomposition of old stored, more recalcitrant, soil carbon at the onset of the warmer early Holocene. Alternative explanations involving gradual temporal changes between open- and closed-system behaviour during the Late Glacial are difficult to reconcile with observed changes in speleothem δ13C and the growth rates. In contrast, a stalagmite from Pindal cave (N. Spain) indicates an abrupt change in carbon inputs linked to local hydrological and disequilibrium isotope fractionation effects, rather than climate change. For the first time, it is shown that while the initial 14C activities of all three stalagmites broadly follow the contemporaneous atmospheric 14C trends (the Younger Dryas atmospheric 14C anomaly can be clearly discerned), subtle changes in speleothem initial 14C activities are linked to climate-driven changes in soil carbon turnover at a climate transition.

Importance of oceanic resolution and mean state on the extra-tropical response to El Niño in a matrix of coupled models

The extra-tropical response to El Niño in configurations of a coupled model with increased horizontal resolution in the oceanic component is shown to be more realistic than in configurations with a low resolution oceanic component. This general conclusion is independent of the atmospheric resolution. Resolving small-scale processes in the ocean produces a more realistic oceanic mean state, with a reduced cold tongue bias, which in turn allows the atmospheric model component to be forced more realistically. A realistic atmospheric basic state is critical in order to represent Rossby wave propagation in response to El Niño, and hence the extra-tropical response to El Niño. Through the use of high and low resolution configurations of the forced atmospheric-only model component we show that, in isolation, atmospheric resolution does not significantly affect the simulation of the extra-tropical response to El Niño. It is demonstrated, through perturbations to the SST forcing of the atmospheric model component, that biases in the climatological SST field typical of coupled model configurations with low oceanic resolution can account for the erroneous atmospheric basic state seen in these coupled model configurations. These results highlight the importance of resolving small-scale oceanic processes in producing a realistic large-scale mean climate in coupled models, and suggest that it might may be possible to “squeeze out” valuable extra performance from coupled models through increases to oceanic resolution alone.

Roles of proteolysis in regulation of G protein-coupled receptor function

The enzymatic activity of peptidases must be tightly regulated to prevent uncontrolled hydrolysis of peptide bonds, which could have devastating effects in biological systems. Peptidases are often generated as inactive propeptidases, secreted with endogenous inhibitors or they are compartmentalized. Propeptidases become active after proteolytic removal of N-terminal activation peptides by other peptidases. Some peptidases only become active towards substrates only at certain pHs, thus confining activity to specific compartments or conditions. This review discusses the different roles proteolysis plays in regulating G protein-coupled receptors (GPCRs). At the cell-surface, certain GPCRs are regulated by the hydrolytic inactivation of bioactive peptides by membrane-anchored peptidases, which prevents signaling. Conversely, cell-surface peptidases can also generate bioactive peptides that directly activate GPCRs. Alternatively, cell-surface peptidases activated by GPCRs, can generate bioactive peptides to cause transactivation of receptor tyrosine kinases, thereby promoting signaling. Certain peptidases can signals directly to cells, by cleaving GPCR to initiate intracellular signaling cascades. Intracellular peptidases also regulate GPCRs; lysosomal peptidases destroy GPCRs in lysosomes to permanently terminate signaling and mediate downregulation; endosomal peptidases cleave internalized peptide agonists to regulate GPCR recycling, resensitization and signaling; and soluble intracellular peptidases also participate in GPCR function by regulating the ubiquitination state of GPCRs, thereby altering GPCR signaling and fate. Although the use of peptidase inhibitors has already brought success in the treatment of diseases such as hypertension, the discovery of new regulatory mechanisms involving proteolysis that control GPCRs may provide additional targets to modulate dysregulated GPCR signaling in disease.

Trafficking and signaling of G protein-coupled receptors in the nervous system: implications for disease and therapy

G protein-coupled receptors (GPCRs) are expressed throughout the nervous system where they regulate multiple physiological processes, participate in neurological diseases, and are major targets for therapy. Given that many GPCRs respond to neurotransmitters and hormones that are present in the extracellular fluid and which do not readily cross the plasma membrane, receptor trafficking to and from the plasma membrane is a critically important determinant of cellular responsiveness. Moreover, trafficking of GPCRs throughout the endosomal system can initiate signaling events that are mechanistically and functionally distinct from those operating at the plasma membrane. This review discusses recent advances in the relationship between signaling and trafficking of GPCRs in the nervous system. It summarizes how receptor modifications influence trafficking, discusses mechanisms that regulate GPCR trafficking to and from the plasma membrane, reviews the relationship between trafficking and signaling, and considers the implications of GPCR trafficking to drug development.

The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century

The boreal summer Asian monsoon has been evaluated in 25 Coupled Model Intercomparison Project-5 (CMIP5) and 22 CMIP3 GCM simulations of the late 20th Century. Diagnostics and skill metrics have been calculated to assess the time-mean, climatological annual cycle, interannual variability, and intraseasonal variability. Progress has been made in modeling these aspects of the monsoon, though there is no single model that best represents all of these aspects of the monsoon. The CMIP5 multi-model mean (MMM) is more skillful than the CMIP3 MMM for all diagnostics in terms of the skill of simulating pattern correlations with respect to observations. Additionally, for rainfall/convection the MMM outperforms the individual models for the time mean, the interannual variability of the East Asian monsoon, and intraseasonal variability. The pattern correlation of the time (pentad) of monsoon peak and withdrawal is better simulated than that of monsoon onset. The onset of the monsoon over India is typically too late in the models. The extension of the monsoon over eastern China, Korea, and Japan is underestimated, while it is overestimated over the subtropical western/central Pacific Ocean. The anti-correlation between anomalies of all-India rainfall and Niño-3.4 sea surface temperature is overly strong in CMIP3 and typically too weak in CMIP5. For both the ENSO-monsoon teleconnection and the East Asian zonal wind-rainfall teleconnection, the MMM interannual rainfall anomalies are weak compared to observations. Though simulation of intraseasonal variability remains problematic, several models show improved skill at representing the northward propagation of convection and the development of the tilted band of convection that extends from India to the equatorial west Pacific. The MMM also well represents the space-time evolution of intraseasonal outgoing longwave radiation anomalies. Caution is necessary when using GPCP and CMAP rainfall to validate (1) the time-mean rainfall, as there are systematic differences over ocean and land between these two data sets, and (2) the timing of monsoon withdrawal over India, where the smooth southward progression seen in India Meteorological Department data is better realized in CMAP data compared to GPCP data.

p90 ribosomal S6 kinases play a significant role in early gene regulation in the cardiomyocyte response to Gq protein-coupled receptor stimuli, endothelin-1 and α1-adrenergic receptor agonists

Extracellular signal-regulated kinases 1/2 (ERK1/2) and their substrates, p90 ribosomal S6 kinases (RSKs), phosphorylate different transcription factors, contributing differentially to transcriptomic profiles. In cardiomyocytes, ERK1/2 are required for >70% of the transcriptomic response to endothelin-1. Here, we investigated the role of RSKs in the transcriptomic responses to Gq protein-coupled receptor agonists, endothelin-1, phenylephrine (generic α1-adrenergic receptor agonist) and A61603 (α1A-adrenergic receptor selective). Phospho-ERK1/2 and phospho-RSKs appeared in cardiomyocyte nuclei within 2-3 min of stimulation (endothelin-1>a61603≈phenylephrine). All agonists increased nuclear RSK2, but only endothelin-1 increased nuclear RSK1 content. PD184352 (inhibits ERK1/2 activation) and BI-D1870 (inhibits RSKs) were used to dissect the contribution of RSKs to the endothelin-1-responsive transcriptome. Of 213 RNAs upregulated at 1 h, 51% required RSKs for upregulation whereas 29% required ERK1/2 but not RSKs. The transcriptomic response to phenylephrine overlapped with, but was not identical to, endothelin-1. As with endothelin-1, PD184352 inhibited upregulation of most phenylephrine-responsive transcripts, but the greater variation in effects of BI-D1870 suggests that differential RSK signalling influences global gene expression. A61603 induced similar changes in RNA expression in cardiomyocytes as phenylephrine, indicating that the signal was mediated largely through α1A-adrenergic receptors. A61603 also increased expression of immediate early genes in perfused adult rat hearts and, as in cardiomyocytes, upregulation of the majority of genes was inhibited by PD184352. PD184352 or BI-D1870 prevented the increased surface area induced by endothelin-1 in cardiomyocytes. Thus, RSKs play a significant role in regulating cardiomyocyte gene expression and hypertrophy in response to Gq protein-coupled receptor stimulation.

Simulated variations in atmospheric CO2 over a Wisconsin forest using a coupled ecosystem-atmosphere model

Ecosystem fluxes of energy, water, and CO2 result in spatial and temporal variations in atmospheric properties. In principle, these variations can be used to quantify the fluxes through inverse modelling of atmospheric transport, and can improve the understanding of processes and falsifiability of models. We investigated the influence of ecosystem fluxes on atmospheric CO2 in the vicinity of the WLEF-TV tower in Wisconsin using an ecophysiological model (Simple Biosphere, SiB2) coupled to an atmospheric model (Regional Atmospheric Modelling System). Model parameters were specified from satellite imagery and soil texture data. In a companion paper, simulated fluxes in the immediate tower vicinity have been compared to eddy covariance fluxes measured at the tower, with meteorology specified from tower sensors. Results were encouraging with respect to the ability of the model to capture observed diurnal cycles of fluxes. Here, the effects of fluxes in the tower footprint were also investigated by coupling SiB2 to a high-resolution atmospheric simulation, so that the model physiology could affect the meteorological environment. These experiments were successful in reproducing observed fluxes and concentration gradients during the day and at night, but revealed problems during transitions at sunrise and sunset that appear to be related to the canopy radiation parameterization in SiB2.

Global ocean warming tied to anthropogenic forcing

Observed global ocean heat content anomalies over the past five decades agree well with an anthropogenically forced simulation using the European Center/Hamburg coupled general circulation model (GCM) ECHAM4/OPYC3 considering increasing greenhouse gas concentrations, the direct and indirect effect of sulphate aerosols, and anthropogenic changes in tropospheric ozone. An optimal detection and attribution analysis confirms that the simulated climate change signal can be detected in the observations in both the upper 300 m and 3000 m of the water column and that the observed changes in ocean heat content are consistent with those expected from the anthropogenically forced GCM integration. This suggests that anthropogenic forcing is a likely explanation for the observed global ocean warming over the past five decades.

Recent Glacier Retreat Exceeds Internal Variability

Glacier fluctuations exclusively due to internal variations in the climate system are simulated using downscaled integrations of the ECHAM4/OPYC coupled general circulation model (GCM). A process-based modeling approach using a mass balance model of intermediate complexity and a dynamic ice flow model considering simple shearing flow and sliding are applied. Multimillennia records of glacier length fluctuations for Nigardsbreen (Norway) and Rhonegletscher (Switzerland) are simulated using autoregressive processes determined by statistically downscaled GCM experiments. Return periods and probabilities of specific glacier length changes using GCM integrations excluding external forcings such as solar irradiation changes, volcanic, or anthropogenic effects are analyzed and compared to historical glacier length records. Preindustrial fluctuations of the glaciers as far as observed or reconstructed, including their advance during the “Little Ice Age,” can be explained by internal variability in the climate system as represented by a GCM. However, fluctuations comparable to the present-day glacier retreat exceed any variation simulated by the GCM control experiments and must be caused by external forcing, with anthropogenic forcing being a likely candidate.

Secular trends in daily precipitation characteristics: greenhouse gas simulation with a coupled AOGCM

Secular trends of daily precipitation characteristics are considered in the transient climate change experiment with a coupled atmosphere-ocean general circulation model ECHAM4/OPYC3 for 1900-2099. The climate forcing is due to increasing concentrations of the greenhouse gases in the atmosphere. Mean daily precipitation, precipitation intensity, probability of wet days and parameters of the gamma distribution are analyzed. Particular attention is paid to the changes of heavy precipitation, Analysis of the annual mean precipitation trends for 1900-1999 revealed general agreement with observations with significant positive trends in mean precipitation over continental areas. In the 2000-2099 period precipitation trend patterns followed the tendency obtained for 1900-1999 but with significantly increased magnitudes. Unlike the annual mean precipitation trends for which negative values were found for some continental areas, the mean precipitation intensity and scale parameter of the fitted gamma distribution increased over all land territories . Negative trends in the number of wet days were found over most of the land areas except high latitudes in the Northern Hemisphere. The shape parameter of the gamma distribution in general revealed a slight negative trend in the areas of the precipitation increase. Investigation of daily precipitation revealed an unproportional increase of heavy precipitation events for the land areas including local maxima in Europe and the eastern United States.

Intensified Asian summer monsoon and its variability in a coupled model forced by increasing greenhouse gas concentrations

The Asian summer monsoon response to global warming is investigated by a transient green-house warming integration with the ECHAM4/OPYC3 CGCM. It is demonstrated that increases of greenhouse gas concentrations intensify the Asian summer monsoon and its variability. The intensified monsoon results mainly from an enhanced land-sea contrast and a northward shift of the convergence zone. A gradual increase of the monsoon variability is simulated from year 2030 onwards. It seems to be connected with the corresponding increase of the sea surface temperature variability over the tropical Pacific.

An investigation of QBO signals in the east Asian and Indian monsoon in GCM experiments

Observations have shown that the monsoon is a highly variable phenomenon of the tropical troposphere, which exhibits significant variance in the temporal range of two to three years. The reason for this specific interannual variability has not yet been identified unequivocally. Observational analyses have also shown that EI Niño indices or western Pacific SSTs exhibit some power in the two to three year period range and therefore it was suggested that an ocean-atmosphere interaction could excite and support such a cycle. Similar mechanisms include land-surface-atmosphere interaction as a possible driving mechanism. A rather different explanation could be provided by a forcing mechanism based on the quasi-biennial oscillation of the zonal wind in the lower equatorial stratosphere (QBO). The QBO is a phenomenon driven by equatorial waves with periods of some days which are excited in the troposphere. Provided that the monsoon circulation reacts to the modulation of tropopause conditions as forced by the QBO, this could explain monsoon variability in the quasi-biennial window. The possibility of a QBO-driven monsoon variability is investigated in this study in a number of general circulation model experiments where the QBO is assimilated to externally controlled phase states. These experiments show that the boreal summer monsoon is significantly influenced by the QBO. A QBO westerly phase implies less precipitation in the western Pacific, but more in India, in agreement with observations. The austral summer monsoon is exposed to similar but weaker mechanisms and the precipitation does not change significantly.