Reconstructing winter climate anomalies in the  Euro-Atlantic sector using circulation patterns

Madonna, Erica; Battisti, David S.; Li, Camille; White, Rachel H.

doi:10.5194/wcd-2-777-2021

Cited by 7 publications

(5 citation statements)

References 54 publications

(69 reference statements)

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“…While the large-scale patterns derived using an EOF analysis are a good indicator of the changes in weather systems over the North Atlantic, recent works have found that jet regimes are better at capturing spatial structure compared to patterns like the NAO and have the advantage of a greater physical connection to the underlying weather systems (Madonna et al, 2021). Future work is planned to investigate how these jet regimes have varied over time in the reanalyses and how well the CMIP6 models capture these variations.…”

Section: Discussionmentioning

confidence: 99%

Changes in the North Atlantic Oscillation over the 20th century

Outten,

Davy

2024

Weather Clim. Dynam.

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Abstract. The North Atlantic Oscillation explains a large fraction of the climate variability across the North Atlantic from the eastern seaboard of North America across the whole of Europe. Many studies have linked the North Atlantic Oscillation to climate extremes in this region, especially in winter, which has motivated considerable study of this pattern of variability. However, one overlooked feature of how the North Atlantic Oscillation has changed over time is the explained variance of the pattern. Here we show that there has been a considerable increase in the percentage of variability explained by the North Atlantic Oscillation (NAO) over the 20th century from 32 % in 1930 to 53 % by the end of the 20th century. Whether this change is due to natural variability, a forced response to climate change, or some combination remains unclear. However, we found no evidence for a forced response from an ensemble of 50 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. These models did all show substantial internal variability in the strength of the North Atlantic Oscillation, but it was biased towards being too high compared to the reanalysis and with too little variation over time. Since there is a direct connection between the North Atlantic Oscillation and climate extremes over the region, this has direct consequences for both the long-term projection and near-term prediction of changes to climate extremes in the region.

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Section: Discussionmentioning

confidence: 99%

Changes in the North Atlantic Oscillation over the 20th century

Outten,

Davy

2024

Weather Clim. Dynam.

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“…While the large-scale patterns derived using EOF analysis are a good indicator of the changes in weather systems over the North Atlantic, recent works have found that jet regimes are better at capturing spatial structure compared to patterns like the NAO, and have the advantage of a greater physical connection to the underlying weather systems (Madonna et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Changes in the North Atlantic Oscillation over the 20th Century

Outten,

Davy

2023

Preprint

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Abstract. The North Atlantic Oscillation explains a large fraction of the climate variability across the North Atlantic from the eastern seaboard of North America across the whole of Europe. Many studies have linked the North Atlantic Oscillation to climate extremes in this region, especially in winter, which has motivated considerable study of this pattern of variability. However, one overlooked feature of how the North Atlantic Oscillation has changed over time is the explained variance of the pattern. Here we show that there has been a considerable increase in the percentage variance explained by the NAO over the 20th century from 32 % in 1930 to 53 % by the end of the 20th century. Whether this change is due to natural variability, a forced response to climate change, or some combination remains unclear. However, we found no evidence for a forced response from an ensemble of 50 CMIP6 models. These models did all show substantial internal variability in the strength of the North Atlantic Oscillation, but it was biased towards being too high compared to the reanalysis and with too little variation over time. Since there is a direct connection between the North Atlantic Oscillation and climate extremes over the region, this has direct consequences for both the long term projection and near term prediction of changes to climate extremes in the region.

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“…The moderate skill of winter hydrological drought forecasts might be linked to large-scale teleconnection patterns that affect European climate in winter. Some studies show that the North Atlantic Oscillation (NAO), the occurrence of blocking, and the North Atlantic jet stream are conjectured as strong predictors in winter meteorological forecasts in Europe 33,51,52 . The high skill in prediction of winter precipitation and temperature is then translated to better prediction of streamflow and subsequently streamflow drought.…”

Section: Discussionmentioning

confidence: 99%

Catchment memory explains hydrological drought forecast performance

Sutanto

Lanen

2022

Preprint

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<p>Skillful Drought Early Warning Systems (DEWSs) to predict drought a few months in advance are of utmost importance to reduce the impacts of the drought hazard. Previous studies on meteorological drought forecasts e.g. using the standardized precipitation index (SPI) show that drought can be sufficiently predicted up to 1-3 months ahead. The skill of hydrological drought forecasts e.g. using the standardized runoff index (SRI) and standardized ground index (SGI), on the other hand, is even 2-3 months higher than the meteorological ones. The high skill in hydrological drought forecasts is anticipated coming from the catchment storage/memory (e.g. lakes, soils, groundwater) that pools, attenuates, and lengthens the effect of the driving forces (i.e. precipitation). Yet, the importance of catchment memory in explaining hydrological drought forecast performance has not been studied. Here, we have conducted a pioneering study that investigates the importance of catchment memory on the forecast performance of streamflow drought across Europe. We identified streamflow drought using the Standardized Streamflow Index (SSI). The observed and forecasted streamflow droughts at major European rivers were derived from the streamflow data obtained from the European Flood Alert System (EFAS) driven by observed and forecasted weather data. Catchment memory was derived from the Baseflow Index (BFI) and the groundwater Recession Coefficient (gRC), which through the streamflow, give information on the catchment memory. Performance of streamflow drought forecasts was evaluated using the Brier Score (BS) for rivers across Europe. Results show that the use of higher accumulation periods in the SSI (e.g. SSI-3) forecasts improves forecast performance. The performance is even higher for catchment that has large memory. We found that BS is negatively correlated with BFI, meaning that rivers with high BFI (large memory) yield better drought prediction (low BS). A significant positive correlation between gRC and BS demonstrates that catchments slowly releasing groundwater to streams (low gRC), i.e. large memory, generates higher drought forecast performance. The higher performance of hydrological drought forecasts in catchments with relatively large memory (high BFI and low gRC) implies that Drought Early Warning Systems have more potential to be implemented there and will appear to be more useful.</p>

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Reconstructing winter climate anomalies in the Euro-Atlantic sector using circulation patterns

Cited by 7 publications

References 54 publications

Changes in the North Atlantic Oscillation over the 20th century

Changes in the North Atlantic Oscillation over the 20th century

Changes in the North Atlantic Oscillation over the 20th Century

Catchment memory explains hydrological drought forecast performance

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