Laurent Terray

The Seasonal Cycle over the Tropical Pacific in Coupled Ocean–Atmosphere General Circulation Models

Abstract The seasonal cycle over the tropical Pacific simulated by 11 coupled ocean–atmosphere general circulation models (GCMs) is examined. Each model consists of a high-resolution ocean GCM of either the tropical Pacific or near-global means coupled to a moderate- or high-resolution atmospheric GCM, without the use of flux correction. The seasonal behavior of sea surface temperature (SST) and eastern Pacific rainfall is presented for each model. The results show that current state-of-the-art coupled GCMs share important successes and troublesome systematic errors. All 11 models are able to simulate the mean zonal gradient in SST at the equator over the central Pacific. The simulated equatorial cold tongue generally tends to be too strong, too narrow, and extend too far west. SSTs are generally too warm in a broad region west of Peru and in a band near 10°S. This is accompanied in some models by a double intertropical convergence zone (ITCZ) straddling the equator over the eastern Pacific, and in others...

Potential impact of climate change on marine export production

Future climate change will affect marine productivity, as well as other many components of Earth system. We have investigated the response of marine productivity to global warming with two different ocean biogeochemical schemes and two different atmosphere-ocean coupled general circulation models (GCM). Both coupled GCMs were used without flux correction to simulate climate response to increased greenhouse gases (+1% CO2/yr for 80 years). At 2×CO2, increased stratification leads to both reduced nutrient supply and increased light efficiency. Both effects drive a reduction in marine export production (−6%), although regionally changes can be both negative and positive (from −15% zonal average in the tropics to +10% in the Southern Ocean). Both coupled models and both biogeochemical schemes simulate a poleward shift of marine production due mainly to a longer growing season at high latitudes. At low latitudes, the effect of reduced upwelling prevails. The resulting reduction in marine productivity, and other marine resources, could become detectable in the near future, if appropriate long-term observing systems are implemented.

Tropical Atlantic Influence on European Heat Waves

Abstract Diagnostics combining atmospheric reanalysis and station-based temperature data for 1950–2003 indicate that European heat waves can be associated with the occurrence of two specific summertime atmospheric circulation regimes. Evidence is presented that during the record warm summer of 2003, the excitation of these two regimes was significantly favored by the anomalous tropical Atlantic heating related to wetter-than-average conditions in both the Caribbean basin and the Sahel. Given the persistence of tropical Atlantic climate anomalies, their seasonality, and their associated predictability, the suggested tropical–extratropical Atlantic connection is encouraging for the prospects of long-range forecasting of extreme weather in Europe.

North Atlantic Winter Climate Regimes: Spatial Asymmetry, Stationarity with Time, and Oceanic Forcing

Abstract The observed low-frequency winter atmospheric variability of the North Atlantic–European region and its relationship with global surface oceanic conditions is investigated based on the climate and weather regimes paradigm. Asymmetries between the two phases of the North Atlantic Oscillation (NAO) are found in the position of the Azores high and, to a weaker extent, the Icelandic low. There is a significant eastward displacement or expansion toward Europe for the NAO+ climate regime compared to the NAO− regime. This barotropic signal is found in different datasets and for two quasi-independent periods of record (1900–60 and 1950–2001); hence, it appears to be intrinsic to the NAO+ phase. Strong spatial similarities between weather and climate regimes suggest that the latter, representing long time scale variability, can be interpreted as the time-averaging signature of much shorter time scale processes. Model results from the ARPEGE atmospheric general circulation model are used to validate observ...

Representing El Niño in Coupled Ocean–Atmosphere GCMs: The Dominant Role of the Atmospheric Component

A systematic modular approach to investigate the respective roles of the ocean and atmosphere in setting El Nino characteristics in coupled general circulation models is presented. Several state-of-the-art coupled models sharing either the same atmosphere or the same ocean are compared. Major results include 1) the dominant role of the atmosphere model in setting El Nino characteristics (periodicity and base amplitude) and errors (regularity) and 2) the considerable improvement of simulated El Nino power spectra—toward lower frequency—when the atmosphere resolution is significantly increased. Likely reasons for such behavior are briefly discussed. It is argued that this new modular strategy represents a generic approach to identifying the source of both coupled mechanisms and model error and will provide a methodology for guiding model improvement.

Near-Surface Salinity as Nature’s Rain Gauge to Detect Human Influence on the Tropical Water Cycle

AbstractChanges in the global water cycle are expected as a result of anthropogenic climate change, but large uncertainties exist in how these changes will be manifest regionally. This is especially the case over the tropical oceans, where observed estimates of precipitation and evaporation disagree considerably. An alternative approach is to examine changes in near-surface salinity. Datasets of observed tropical Pacific and Atlantic near-surface salinity combined with climate model simulations are used to assess the possible causes and significance of salinity changes over the late twentieth century. Two different detection methodologies are then applied to evaluate the extent to which observed large-scale changes in near-surface salinity can be attributed to anthropogenic climate change.Basin-averaged observed changes are shown to enhance salinity geographical contrasts between the two basins: the Pacific is getting fresher and the Atlantic saltier. While the observed Pacific and interbasin-averaged sal...

Identifying human influences on atmospheric temperature.

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the fingerprint) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

Oceanic Forcing of the Wintertime Low-Frequency Atmospheric Variability in the North Atlantic European Sector: A Study with the ARPEGE Model

Abstract The relationship between global sea surface temperatures (SSTs) and the North Atlantic–Europe (NAE) atmospheric circulation is investigated using an ensemble of eight simulations with the ARPEGE atmospheric global circulation model forced with prescribed SSTs over the 1948–97 period. The model mean state is first validated against NCEP reanalyses. The interannual SST-forced variability is then compared to the internal one using analysis of variance (ANOVA) techniques. Both components are maximum in winter over the Northern Hemisphere and the associated potential predictability shows weak but significant values located over the Icelandic low (IL) and the Azores high (AH). The North Atlantic oscillation (NAO) is found to be the leading internal variability mode over the NAE sector as shown by principal component analysis of a control simulation with climatological SSTs. The noise imprint dominates the forced response estimated from the ensemble mean. The latter is related first to the El Nino–South...

Summer Sea Surface Temperature Conditions in the North Atlantic and Their Impact upon the Atmospheric Circulation in Early Winter

Abstract The origin of the so-called summer North Atlantic “Horseshoe” (HS) sea surface temperature (SST) mode of variability, which is statistically linked to the next winters North Atlantic Oscillation (NAO), is investigated from data and experiments with the CCM3 atmospheric general circulation model (AGCM). Lagged observational analyses reveal a linkage between HS and anomalous rainfall in the vicinity of the Atlantic intertropical convergence zone. Prescribing the observed anomalous convection in the model generates forced atmospheric Rossby waves that propagate into the North Atlantic sector. The accompanying perturbations in the surface turbulent and radiative fluxes are consistent with forcing the SST anomalies associated with HS. It is suggested that HS can therefore be interpreted as the remote footprint of tropical atmospheric changes. The ARPEGE AGCM is then used to test if the persistence of HS SST anomalies from summer to late fall can feed back to the atmosphere and have an impact on the n...

Application of regularised optimal fingerprinting to attribution. Part I: method, properties and idealised analysis

Optimal fingerprinting has been the most widely used method for climate change detection and attribution over the last decade. The implementation of optimal fingerprinting often involves projecting onto k leading empirical orthogonal functions in order to decrease the dimension of the data and improve the estimate of internal climate variability. However, results may be sensitive to k, and the choice of k remains at least partly arbitrary. One alternative, known as regularised optimal fingerprinting (ROF), has been recently proposed for detection. This is an extension of the optimal fingerprinting detection method, which avoids the projection step. Here, we first extend ROF to the attribution problem. This is done using both ordinary and total least square approaches. Internal variability is estimated from long control simulations. The residual consistency test is also adapted to this new method. We then show, via Monte Carlo simulations, that ROF is more accurate than the standard method, in a mean squared error sense. This result holds for both ordinary and total least square statistical models, whatever the chosen truncation k. Finally, ROF is applied to global near-surface temperatures in a perfect model framework. Improvements provided by this new method are illustrated by a detailed comparison with the results from the standard method. Our results support the conclusion that ROF provides a much more objective and somewhat more accurate implementation of optimal fingerprinting in detection and attribution studies.