Chloé Prodhomme

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.

Impacts of Indian and Atlantic oceans on ENSO in a comprehensive modeling framework

Abstract The impact of the Indian and Atlantic oceans variability on El Niño–Southern-Oscillation (ENSO) phenomenon is investigated through sensitivity experiments with the SINTEX-F2 coupled model. For each experiment, we suppressed the sea surface temperature (SST) variability in either the Indian or Atlantic oceans by applying a strong nudging of the SST toward a SST climatology computed either from a control experiment or observations. In the sensitivity experiments where the nudging is done toward a control SST climatology, the Pacific mean state and seasonal cycle are not changed. Conversely, nudging toward an observed SST climatology in the Indian or Atlantic domain significantly improves the mean state and seasonal cycle, not only in the nudged domain, but also in the whole tropics. These experiments also demonstrate that decoupling the Indian or Atlantic variability modifies the phase-locking of ENSO to the annual cycle, influences significantly the timing and processes of ENSO onset and termination stages, and, finally, shifts to lower frequencies the main ENSO periodicities. Overall, these results suggest that both the Indian and Atlantic SSTs have a significant damping effect on ENSO variability and promote a shorter ENSO cycle. The reduction of ENSO amplitude is particularly significant when the Indian Ocean is decoupled, but the shift of ENSO to lower frequencies is more pronounced in the Atlantic decoupled experiments. These changes of ENSO statistical properties are related to stronger Bjerknes and thermocline feedbacks in the nudged experiments. During the mature phase of El Niño events, warm SST anomalies are found over the Indian and Atlantic oceans in observations or the control run. Consistent with previous studies, the nudged experiments demonstrate that these warm SSTs induce easterly surface wind anomalies over the far western equatorial Pacific, which fasten the transition from El Niño to La Niña and promote a shorter ENSO cycle in the control run. These results may be explained by modulations of the Walker circulation induced directly or indirectly by the Indian and Atlantic SSTs. Another interesting result is that decoupling the Atlantic or Indian oceans change the timing of ENSO onset and the relative role of other ENSO atmospheric precursors such as the extra-tropical Pacific Meridional Modes or the Western North Pacific SSTs.

Role of Tropical SST Variability on the Formation of Subtropical Dipoles

AbstractInterannual variations of sea surface temperature (SST) in the midlatitudes of the Southern Hemisphere play an important role in the rainfall variability over the surrounding countries by modulating synoptic-scale atmospheric disturbances. These are frequently associated with a northeast–southwest-oriented dipole of positive and negative SST anomalies in each oceanic basin, referred to as a subtropical dipole. This study investigates the role of tropical SST variability on the generation of subtropical dipoles by conducting SST-nudging experiments using a coupled general circulation model. In the experiments where the simulated SST in each tropical basin is nudged to the climatology of the observed SST, the subtropical dipoles tend to occur as frequently as the case in which the simulated SST is allowed to freely interact with the atmosphere. It is found that without the tropical SST variability, the zonally elongated atmospheric mode in the mid- to high latitudes, called the Antarctic Oscillation...

Benefits of Increasing the Model Resolution for the Seasonal Forecast Quality in EC-Earth

AbstractResolution in climate models is thought to be an important factor for advancing seasonal prediction capability. To test this hypothesis, seasonal ensemble reforecasts are conducted over 1993–2009 with the European community model EC-Earth in three configurations: standard resolution (~1° and ~60 km in the ocean and atmosphere models, respectively), intermediate resolution (~0.25° and ~60 km), and high resolution (~0.25° and ~39 km), the two latter configurations being used without any specific tuning. The model systematic biases of 2-m temperature, sea surface temperature (SST), and wind speed are generally reduced. Notably, the tropical Pacific cold tongue bias is significantly reduced, the Somali upwelling is better represented, and excessive precipitation over the Indian Ocean and over the Maritime Continent is decreased. In terms of skill, tropical SSTs and precipitation are better reforecasted in the Pacific and the Indian Oceans at higher resolutions. In particular, the Indian monsoon is bet...

Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992–2010 period performed by five different global coupled ocean–atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land–atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe

There is now a wide range of forecasts and observations of seasonal climatic conditions that can be used across a range of application sectors, including hydrological risk forecasting, planning and management. As we rely more on seasonal climate forecasts, it becomes essential to also assess its quality to ensure its intended use. In this study, we provide the most comprehensive assessment of seasonal temperature and precipitation ensemble forecasts of the EUROSIP multi-model forecasting system over Europe. The forecasts from the four individual climate models within the EUROSIP are assessed using both deterministic and probabilistic approaches. One equally and two unequally Weighted Multi-Models (WMMs) are also constructed from the individual models, for both climate variables, and their respective forecasts are also assessed. Consistent with existing literature, we find limited seasonal climate prediction skill over Europe. A simple equally WMM system performs better than both unequally WMM combination systems. However, the equally WMM system does not always outperform the single best model within the EUROSIP multi-model. Based on the results, it is recommended to assess seasonal temperature and precipitation forecast of individual climate models as well as their multi-model mean for a comprehensive overview of the forecast skill.