Forecast-Oriented Assessment of Decadal Hindcast Skill for North Atlantic SST

We demonstrate in this paper that conventional time-averaged decadal hindcast skill estimates can overestimate or underestimate the credibility of an individual decadal climate forecast.We show that hindcast skill in a long period can be higher or lower than skill in its subperiods. Instead of using time-averaged hindcast skill measures, we propose to use the physical state of the climate system at the beginning of the forecast to judge its credibility.We analyze hindcasts of North Atlantic sea surface temperature (SST) in an initialized prediction system based on the MPI-ESM-LR for the period 1901–2010. Subpolar North Atlantic Ocean heat transport (OHT) strength at hindcast initialization largely determines the skill of these hindcasts:We find high skill after anomalously strong or weak OHT, but low skill after average OHT. This knowledge can be used to constrain conventional hindcast skill estimates to improve the assessment of credibility for a decadal forecast

The relationship between sea surface temperature anomalies, wind and translation speed and North Atlantic tropical cyclone rainfall over ocean and land

There have been increasing losses from freshwater flooding associated with United States (US) landfalling hurricanes in recent years. This study analyses the relationship between sea surface temperature anomalies (SSTA), wind and translation speed and North Atlantic tropical cyclone precipitation (TCP) for the period 1998-2017. Based on our statistical analysis of observation data, for a 1 °C SST increase in the main development region (MDR), there is a 6% increase (not statistically significant) in the TCP rate (mmhr−1) over the Atlantic, which rises to over 40% over land (US states) and appears linked not only to the Clausius-Clapeyron relationship but also to the increase in tropical cyclone (TC) intensity associated with increasing SSTA. Total annual TCP is significantly correlated with the SST in the MDR. Over the Atlantic there is an increase of 116% and over land there is an increase of 140% in total TCP for a 1 °C rise in SST in the MDR. Again, this is linked to the increase in windspeed and the number of TC tracks which also rises with positive SSTAs in the MDR. Our analysis of landfalling TC tracks for nine US states provides a systematic review and highlights how TCP varies by US state. The highest number of landfalls per year are found in Florida, North Carolina and Texas. The median tropical cyclone translation speed is 20.3kmhr−1, although this falls to 16.5 kmhr−1 over land and there is a latitudinal dependence on translation speed. Overall, we find a different TCP response to rising SST over the ocean and land, with the response over land over four times more than the Clausius-Clapeyron rate. The links between SSTA in the MDR and both TCP rate and annual total TCP provide useful insights for seasonal to decadal US flood prediction from TCs

Climate change impacts on ocean circulation relevant to the UK and Ireland

What is happening • Observations of the Atlantic Meridional Overturning Circulation or Gulf Stream System since the 1980s have shown a strengthening in the 1990s and a weakening in the 2000s, with no clear overall trend. • Shifts in North-east Atlantic circulation, leading to a greater influence of warmer subtropical-origin waters which can impact marine ecosystems and economically important fish species such as mackerel. The changing subpolar ocean circulation is also having impacts on the food supply for deep-sea ecosystems. • The subpolar gyre recorded its freshest values on record in the 2010s. Ongoing freshwater build-up in the rapidly changing Arctic Ocean may exacerbate this freshening. What could happen • Projections from climate models consistently project a weakening of the Atlantic Meridional Overturning Circulation due to anthropogenic climate change. • Warming of Atlantic waters is expected to reduce the depth of mixed layers and limit nutrient supply to surface layers

Asynchronous Antarctic and Greenland ice-volume contributions to the last interglacial sea-level highstand

The last interglacial (LIG; ~130 to ~118 thousand years ago, ka) was the last time global sea level rose well above the present level. Greenland Ice Sheet (GrIS) contributions were insufficient to explain the highstand, so that substantial Antarctic Ice Sheet (AIS) reduction is implied. However, the nature and drivers of GrIS and AIS reductions remain enigmatic, even though they may be critical for understanding future sea-level rise. Here we complement existing records with new data, and reveal that the LIG contained an AIS-derived highstand from ~129.5 to ~125 ka, a lowstand centred on 125–124 ka, and joint AIS + GrIS contributions from ~123.5 to ~118 ka. Moreover, a dual substructure within the first highstand suggests temporal variability in the AIS contributions. Implied rates of sea-level rise are high (up to several meters per century; m c−1), and lend credibility to high rates inferred by ice modelling under certain ice-shelf instability parameterisations

Minimum Information about a Biosynthetic Gene cluster

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.Chemistry and Chemical Biolog

Current and emerging developments in subseasonal to decadal prediction

Weather and climate variations of subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus remains broadly similar (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correct, calibration and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Prograame (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis

Atlantic Inflow to the North Sea Modulated by the Subpolar Gyre in a Historical Simulation With MPI‐ESM

While the influence of the subpolar gyre (SPG) on thermohaline variability in the eastern North Atlantic is well documented, the extent and timescale of the influence of the SPG on North Sea is not well understood. This is primarily because earlier investigations on the causes of variability in the North Sea water properties mostly focused on the role of atmosphere and deployed regional models. Here using a historical simulation with the Max Planck Institute Earth System Model (MPI-ESM), we investigate circulation and water mass variability in key regions, namely, the Rockall Trough and the Faroe-Scotland Channel, which link the North Atlantic to the North Sea. We find that salinity covaries with advective lags in these three regions and that the northern North Sea salinity follows the Rockall Trough with a lag of 1 year. We show that recurring and persistent excursions of salinity anomalies into the northern North Sea are related to the SPG strength and not to the local acceleration of the inflow. Furthermore, we illustrate that the SPG signal is more pronounced in salinity than in temperature and that this simulated SPG signal has a period of 30–40 years. Overall, our study suggests that, at low frequency, water mass variability originating in the North Atlantic dominates changes in the North Sea water properties over those due to local wind-driven volume transport

Hidden Potential in Predicting Wintertime Temperature Anomalies in the Northern Hemisphere

Variability of the North Atlantic Oscillation (NAO) drives wintertime temperature anomalies in the Northern Hemisphere. Dynamical seasonal prediction systems can skilfully predict the winter NAO. However, prediction of the NAO‐dependent air temperature anomalies remains elusive, partially due to the low variability of predicted NAO. Here, we demonstrate a hidden potential of a multi‐model ensemble of operational seasonal prediction systems for predicting wintertime temperature by increasing the variability of predicted NAO. We identify and subsample those ensemble members which are close to NAO index statistically estimated from initial autumn conditions. In our novel multi‐model approach, the correlation prediction skill for wintertime Central Europe temperature is improved from 0.25 to 0.66, accompanied by an increased winter NAO prediction skill of 0.9. Thereby, temperature anomalies can be skilfully predicted for the upcoming winter over a large part of the Northern Hemisphere through increased variability and skill of predicted NAO.Plain Language Summary: Wintertime temperature in the Northern Hemisphere is regulated by the variations of atmospheric pressure, represented by the so‐called North Atlantic Oscillation (NAO). The NAO's phase—negative or positive—is associated with the pathways of cold and warm air masses leading to cold or warm winters in Europe. While the NAO phase can be predicted well, predictions of the NAO‐dependent air temperature remain elusive. Specifically, it is challenging to predict the strength of the NAO, the most important requirement for the accurate prediction of wintertime temperature. Here, we improve wintertime temperature prediction by increasing the strength of the predicted NAO. We use observation based autumn Northern Hemisphere ocean and air temperature, as well as ice and snow cover for statistical estimation of the first guess NAO for the upcoming winter. Then, we sub‐select only those simulations from the multi‐model ensemble, which are consistent with our first guess NAO. As a result, based on these selected members, the wintertime temperature prediction is substantially improved over a large part of the Northern Hemisphere.Key Points: Amplitude and skill of predicted North Atlantic Oscillation (NAO) improve significantly by subsampling of ensemble of existing seasonal prediction systems. Amplified NAO variability leads to significant improvement in predicting the upcoming winter temperature anomalies in the Northern Hemisphere.Deutsche ForschungsgemeinschaftClimate, Climatic Change, and SocietyMarine Institute grantEuropean Union's Horizon 2020 research and innovation programmehttps://cds.climate.copernicus.eu/cdsapp#!/dataset/seasonal-original-single-levels?tab=overviewhttp://www.ecmwf.int/en/forecasts/dataset

Time dependency of the prediction skill for the North Atlantic subpolar gyre in initialized decadal hindcasts

We analyze the time dependency of decadal hindcast skill in the North Atlantic subpolar gyre within the time period 1961–2013. We compare anomaly correlation coefficients and temporal interquartile ranges of total upper ocean heat content and sea surface temperature for three differently initialized sets of hindcast simulations with the global coupled model MPI-ESM. All initializations use weakly coupled assimilation with the same full value nudging in the atmospheric component and different assimilation techniques for oceanic temperature and salinity: (1) ensemble Kalman filter assimilating EN4 observations and HadISST data, (2) nudging of anomalies to ORAS4 reanalysis, (3) nudging of full values to ORAS4 reanalysis. We find that hindcast skill depends strongly on the evaluation time period, with higher hindcast skill during strong multiyear trends, especially during the warming in the 1990s and lower hindcast skill in the absence of such trends. Differences between the prediction systems are more pronounced when investigating any 20-year subperiod within the entire hindcast period. In the ensemble Kalman filter initialized hindcasts, we find significant correlation skill for up to 5–8 lead years, albeit along with an overestimation of the temporal interquartile range. In the hindcasts initialized by anomaly nudging, significant correlation skill for lead years greater than two is only found in the 1980s and 1990s. In the hindcasts initialized by full value nudging, correlation skill is consistently lower than in the hindcasts initialized by anomaly nudging in the first lead years with re-emerging skill thereafter. The Atlantic meridional overturning circulation reacts on the density changes introduced by oceanic nudging, this limits the predictability in the subpolar gyre in the first lead years. Overall, we find that a model-consistent assimilation technique can improve hindcast skill. Further, the evaluation of 20 year subperiods within the full hindcast period provides essential insights to judge the success of both the assimilation and the subsequent hindcast quality