Abstract

A formalism to obtain a mean sea level equation (MSLE) is constructed for any limited ocean region and/or the global ocean by considering the mass conservation equation with compressible effects and a linear equation of state. The MSLE contains buoyancy fluxes terms representing the steric effects and the mass flux is represented by surface water fluxes and volume transport terms. The MSLE is studied for the Mediterranean Sea case using a simulation experiment for the decade 1999–2008. It is found that the Mediterranean MSL tendency is made of a steric contribution that is almost periodic in time superimposed on a stochastic-like signal due to the mass balance, dominating the MSL tendency. The MSL tendency stochastic-like term is a result of the imbalance between the volume flux at Gibraltar and the area average surface water flux.

Abstract

Seven years of analyses and forecasts from the operational archives of the European Centre for Medium-Range Weather Forecasts have been analyzed to assess the performance of the model in forecasting blocking events. This paper extends the previous work by Tibaldi and Molteni to the other seasons of the year and to the Southern Hemisphere. The dataset covers the period from 1 December 1980 to 30 November 1987 and consists of 5OO-hPa geopotential height daily analyses and the 120 corresponding forecasts verifying on the same day, a dataset commonly known as the “Lorenz files.” Local blocking and sector blocking have been defined as in Tibaldi and Molteni, using a modified version of the Lejenas and Økland objective blocking index.

The results broadly confirm the conclusions previously reached for the winter season alone, extending their validity to the rest of the year and, mutatis mutandis, to the other hemisphere. The main observational difference between blocking in the two hemispheres is in the number of preferred locations: Atlantic and Pacific blocking in the Northern Hemisphere, and only one broad region in the Southern Hemisphere, around 180° longitude. Forecasting the onset of blocking events is in general a task that the model finds difficult, whereas if the integration starts from an already blocked initial condition, the performance of the model is usually better. The poor observational data coverage in the Southern Hemisphere is likely to produce initial conditions affected by larger errors, making the correct forecast of the onset of a blocking event an even more difficult task than it is in the Northern Hemisphere. In the Northern Hemisphere, although the dynamical characteristics of Atlantic and Pacific blocks are inferred from the respective model errors to be different, their detrimental effects on forecast performance are similar in the two cases.

This article discusses the interplay between computational experiments and scientific advancement in dynamical meteorology and climate dynamics. In doing so, the emphasis is on the dual role of computations in prediction and experimentation, permitting the development of physical insight and confidence in the mechanistic insight through verification. Modern climate dynamics has steadily evolved because of the ready access to computational power that has developed over the past quarter century.

The landscape for state-of-the-art computational climate science is changing rapidly, however, with the drive toward greater complexity in climate models in order to more fully represent the interactions among components, the need for higher-resolution atmospheric and oceanic models to fully capture critical aspects of the variability in these components, and the advent of petascale and (eventually) exascale computing facilities. Finally, the manner in which the combination of these changes will likely alter the planning and execution of grand-challenge computational experiments and what this might mean in terms of collaborative climate science is discussed.

Abstract

Through tropical cyclone (TC) activity the ocean and the atmosphere exchange a large amount of energy. In this work possible improvements introduced by a higher coupling frequency are tested between the two components of a climate model in the representation of TC intensity and TC–ocean feedbacks. The analysis is based on the new Centro Euro-Mediterraneo per I Cambiamenti Climatici Climate Model (CMCC-CM2-VHR), capable of representing realistic TCs up to category-5 storms. A significant role of the negative sea surface temperature (SST) feedback, leading to a weakening of the cyclone intensity, is made apparent by the improved representation of high-frequency coupled processes. The first part of this study demonstrates that a more realistic representation of strong TC count is obtained by coupling atmosphere and ocean components at hourly instead of daily frequency. Coherently, the positive bias of the annually averaged power dissipation index associated with TCs is reduced by one order of magnitude when coupling at the hourly frequency, compared to both forced mode and daily coupling frequency results. The second part of this work shows a case study (a modeled category-5 typhoon) analysis to verify the impact of a more realistic representation of the high-frequency coupling in representing the TC effect on the ocean; the theoretical subsurface warming induced by TCs is well represented when coupling the two components at the higher frequency. This work demonstrates that an increased horizontal resolution of model components is not sufficient to ensure a realistic representation of intense and fast-moving systems, such as tropical and extratropical cyclones, but a concurrent increase in coupling frequency is required.

Abstract

In this work the authors investigate possible changes in the intensity of rainfall events associated with tropical cyclones (TCs) under idealized forcing scenarios, including a uniformly warmer climate, with a special focus on landfalling storms. A new set of experiments designed within the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group allows disentangling the relative role of changes in atmospheric carbon dioxide from that played by sea surface temperature (SST) in changing the amount of precipitation associated with TCs in a warmer world. Compared to the present-day simulation, an increase in TC precipitation was found under the scenarios involving SST increases. On the other hand, in a CO₂-doubling-only scenario, the changes in TC rainfall are small and it was found that, on average, TC rainfall tends to decrease compared to the present-day climate. The results of this study highlight the contribution of landfalling TCs to the projected increase in the precipitation changes affecting the tropical coastal regions.

Abstract

The discharge of freshwater into oceans represents a fundamental process in the global climate system, and this flux is taken into account in simulations with general circulation models (GCMs). Moreover, the availability of realistic river routing schemes is a powerful instrument to assess the validity of land surface components, which have been recognized to be crucial for the global climate simulation. In this study, surface and subsurface runoff generated by the 13 land surface schemes (LSSs) participating in the Second Global Soil Wetness Project (GSWP-2) are used as input fields for the Hydrology Discharge (HD) routing model to simulate discharge for 30 of the world’s largest rivers. The simplest land surface models do not provide a good representation of runoff, and routed river flows using these inputs are affected by many biases. On the other hand, HD shows the best simulations when forced by two of the more sophisticated schemes. The multimodel ensemble GSWP-2 generates the best phasing of the annual cycle as well as a good representation of absolute values, although the ensemble mean tends to smooth the peaks. Finally, the intermodel comparison shows the limits and deficiencies of a velocity-constant routing model such as HD, particularly in the phase of mean annual discharge.

The second part of the study assesses the sensitivity of river discharge to the variation of external meteorological forcing. The Center for Ocean–Land–Atmosphere Studies version of the SSiB model is constrained with different meteorological fields and the resulting runoff is used as input for HD. River flow is most sensitive to precipitation variability, but changes in radiative forcing affect discharge as well, presumably because of the interaction with evaporation. Also, this analysis provides an estimate of the sensitivity of river discharge to precipitation variations. A few areas (e.g., central and eastern Asia, the Mediterranean, and much of the United States) show a magnified response of river discharge to a given percentage change in precipitation. Hence, an amplified effect of droughts as indicated by the consensus of climate change predictions may occur in places such as the Mediterranean. Conversely, increasing summer precipitation foreseen in places like southern and eastern Asia may amplify floods in these poor and heavily populated regions. Globally, a 1% fluctuation in precipitation forcing results in an average 2.3% change in discharge. These results can be used for the definition and assessment of new strategies for land use and water management in the near future.

Abstract

The effect of atmospheric horizontal resolution on tropical variability is investigated within the modified Scale Interaction Experiment (SINTEX) coupled model, SINTEX-Frontier (SINTEX-F), developed jointly at Istituto Nazionale di Geofisica e Vulcanologia (INGV), L’Institut Pierre-Simon Laplace (IPSL), and the Frontier Research System. The ocean resolution is not changed as the atmospheric model resolution is modified from spectral resolution 30 (T30) to spectral resolution 106 (T106). The horizontal resolutions of the atmospheric model T30 and T106 are investigated in terms of the coupling characteristics, frequency, and variability of the tropical ocean–atmosphere interactions. It appears that the T106 resolution is generally beneficial even if it does not eliminate all the major systematic errors of the coupled model. There is an excessive shift west of the cold tongue and ENSO variability, and high resolution also has a somewhat negative impact on the variability in the east Indian Ocean. A dominant 2-yr peak for the Niño-3 variability in the T30 model is moderated in the T106 as it shifts to a longer time scale. At high resolution, new processes come into play, such as the coupling of tropical instability waves, the resolution of coastal flows at the Pacific–Mexican coasts, and improved coastal forcing along the coast of South America. The delayed oscillator seems to be the main mechanism that generates the interannual variability in both models, but the models realize it in different ways. In the T30 model it is confined close to the equator, involving relatively fast equatorial and near-equatorial modes, and in the high-resolution model, it involves a wider latitudinal region and slower waves. It is speculated that the extent of the region that is involved in the interannual variability may be linked to the time scale of the variability itself.

In this article, the authors describe an innovative multimodel system developed within the Climate Change and Impact Research: The Mediterranean Environment (CIRCE) European Union (EU) Sixth Framework Programme (FP6) project and used to produce simulations of the Mediterranean Sea regional climate. The models include high-resolution Mediterranean Sea components, which allow assessment of the role of the basin and in particular of the air–sea feedbacks in the climate of the region.

The models have been integrated from 1951 to 2050, using observed radiative forcings during the first half of the simulation period and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario during the second half.

The projections show a substantial warming (about 1.5°–2°C) and a significant decrease of precipitation (about 5%) in the region for the scenario period. However, locally the changes might be even larger. In the same period, the projected surface net heat loss decreases, leading to a weaker cooling of the Mediterranean Sea by the atmosphere, whereas the water budget appears to increase, leading the basin to lose more water through its surface than in the past. Overall, these results are consistent with the findings of previous scenario simulations, such as the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE), Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES), and phase 3 of the Coupled Model Intercomparison Project (CMIP3). The agreement suggests that these findings are robust to substantial changes in the configuration of the models used to make the simulations.

Finally, the models produce a 2021–50 mean steric sea level rise that ranges between +7 and +12 cm, with respect to the period of reference.

A new field of study, “decadal prediction,” is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10–30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving three-dimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr.

This paper provides an update on research in the relatively new and fast-moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about 6–9 years. Recent multimodel results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialized multimodel ensemble decadal hindcasts than in single model results, with multimodel initialized predictions for near-term climate showing somewhat less global warming than uninitialized simulations. Some decadal hindcasts have shown statistically reliable predictions of surface temperature over various land and ocean regions for lead times of up to 6–9 years, but this needs to be investigated in a wider set of models. As in the early days of El Niño–Southern Oscillation (ENSO) prediction, improvements to models will reduce the need for bias adjustment, and increase the reliability, and thus usefulness, of decadal climate predictions in the future.