Subseasonal Time Scales Research Articles

Subseasonal Forecast Skill over the Northern Polar Region in Boreal Winter

AbstractPentad (5-day averaged) forecast skill over the Arctic region in boreal winter is evaluated for the subseasonal to seasonal prediction (S2S) systems from three operational centers: the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction (NCEP), and Environment and Climate Change Canada (ECCC). The results indicate that for a lead time longer than about 10 days the forecast skill of 2-m air temperature and 500-hPa geopotential height in the Arctic area is low compared to the tropical and midlatitude regions. The three S2S systems have comparable forecast skill in the northern polar region. Relatively high skill is observed in the Arctic sector north of the Bering Strait in pentads 4–6. Possible sources of S2S predictability in the polar region are explored. The polar forecast skill is found to be dependent on the phase of the Arctic Oscillation (AO) in the initial condition; that is, forecasts initialized with the negative AO are more skillful than those starting from the positive AO. This is likely due to the influence of the stratospheric polar vortex. The tropical MJO is found to also influence the prediction skill in the polar region. Forecasts starting from MJO phases 6–7, which correspond to suppressed convection in the equatorial eastern Indian Ocean and enhanced convection in the tropical western Pacific, tend to be more skillful than those initialized from other MJO phases. To improve the polar prediction on the subseasonal time scale, it is important to have a well-represented stratosphere and tropical MJO and their associated teleconnections in the model.

Forecast Skill of Minimum and Maximum Temperatures on Subseasonal‐to‐Seasonal Timescales Over South Africa

AbstractForecast skill of three subseasonal‐to‐seasonal models and their ensemble mean outputs are evaluated in predicting the surface minimum and maximum temperatures at subseasonal timescales over South Africa. Three skill scores (correlation of anomaly, root‐mean‐square error, and Taylor diagrams) are used to evaluate the models. It is established that the subseasonal‐to‐seasonal models considered here have skill in predicting both minimum and maximum temperatures at subseasonal timescales. The correlation of anomaly indicates that the multimodel ensemble outperforms the individual models in predicting both minimum and maximum temperatures for the day 1–14, day 11–30, and full calendar month timescales during December months. The Taylor diagrams suggest that the European Centre for Medium‐Range Weather Forecasts model and MM performs better for the day 11–30 timescale for both minimum and maximum temperatures. In general, the models perform better for minimum than maximum temperatures in terms of root‐mean‐square error. In fact, the skill difference in terms of correlation of anomalies (CORA) is small.

Madden-Julian Oscillation influence on sub-seasonal rainfall variability on the west of South America.

The Madden-Julian Oscillation (MJO) is the leading driver of intraseasonal rainfall variability in the global tropics. However, the influence of MJO on western tropical South America (WTSA) has not been a focus of research. This is not surprising since the MJO convective core becomes nondescript as it propagates across the eastern Pacific, such that its influence on the Pacific coast of tropical South America is not obvious in global analyses. In this study, we examine MJO impacts on subseasonal rainfall variability in the rainiest season for WTSA (February-April). In order to avoid confusion with El Niño Southern Oscillation (ENSO) signals, only ENSO-neutral years are included in the analysis. We found that the MJO convective core reemerges when it propagates onto land in WTSA, and that it is associated with subseasonal precipitation anomalies of 20-50% relative to climatology. The MJO signal is evident in the Real-Time Multivariate MJO (RMM) index; however, the signal is clearer when a custom subseasonal index for the region based on WTSA outgoing longwave radiation is employed. Dynamically, the MJO influence is consistent with a modulation of the Pacific Ocean Walker Circulation descending branch, which is climatologically located in or near WTSA. Furthermore, MJO drives zonal and vertical motions on moisture and wind fields that influence precipitation in the region. We found that the timing of deep convection on subseasonal timescales captured by the regional index is consistent with a dominant role of the MJO convective core, rather than propagation of equatorial Rossby or Kelvin waves. However, there is evidence that equatorial Rossby waves that emerge over the tropical Atlantic Ocean also influence precipitation in WTSA on MJO timescales.

Improving sub-seasonal forecast skill of meteorological drought: a weather pattern approach

Abstract. Dynamical model skill in forecasting extratropical precipitation is limited beyond the medium-range (around 15 d), but such models are often more skilful at predicting atmospheric variables. We explore the potential benefits of using weather pattern (WP) predictions as an intermediary step in forecasting UK precipitation and meteorological drought on sub-seasonal timescales. Mean sea-level pressure forecasts from the European Centre for Medium-Range Weather Forecasts ensemble prediction system (ECMWF-EPS) are post-processed into probabilistic WP predictions. Then we derive precipitation estimates and dichotomous drought event probabilities by sampling from the conditional distributions of precipitation given the WPs. We compare this model to the direct precipitation and drought forecasts from the ECMWF-EPS and to a baseline Markov chain WP method. A perfect-prognosis model is also tested to illustrate the potential of WPs in forecasting. Using a range of skill diagnostics, we find that the Markov model is the least skilful, while the dynamical WP model and direct precipitation forecasts have similar accuracy independent of lead time and season. However, drought forecasts are more reliable for the dynamical WP model. Forecast skill scores are generally modest (rarely above 0.4), although those for the perfect-prognosis model highlight the potential predictability of precipitation and drought using WPs, with certain situations yielding skill scores of almost 0.8 and drought event hit and false alarm rates of 70 % and 30 %, respectively.

Atmospheric rivers associated with summer heavy rainfall over the Yangtze Plain

Atmospheric rivers (ARs) are long, narrow bands of enhanced water vapour transport in the low atmosphere, mainly from the tropics into the midlatitudes. However, it is still unclear how ARs act on different timescales during the boreal summer when frequent heavy precipitation events take place in East Asia, often resulting in severe flood that impacts property and human lives. In this study, we investigated climatological ARs, and their evolution on both synoptic and subseasonal timescales, associated with heavy rainfall events over the Yangtze Plain in China. Furthermore, their predictability was assessed by examining hindcast skills from an operational coupled seasonal forecast system of the Australian Bureau of Meteorology named ACCESS-S1. Results showed that ARs embedded within the South Asian monsoon and Somali cross-equatorial flow provide a favourable background for steady moisture supply of summer rainfall into East Asia. We call this favourable background a ‘climatological East Asian AR’, which has close connections with seasonal cycles and climatological intraseasonal oscillation of rainfall in the Yangtze Plain during its Meiyu season. The East Asian AR was also influenced by anomalous anticyclonic circulations over the tropical West Pacific when heavy rainfall events occurred over the Yangtze Plain. Different from orography-induced precipitation, ARs that led to heavy rainfall over the Yangtze Plain were linked with the intrusions of cold air from the north. The major source of ARs responsible for heavy precipitation events over the Yangtze Plain appeared to originate from the tropical West Pacific on both synoptic and subseasonal timescales. In 23-year hindcasts for May-June-July the current model, ACCESS-S1, had skillful rainfall forecasts at a lead time of 0 month, but the skill degraded significantly with longer lead times. Nevertheless, the model showed skills in predicting the variations of low-level moisture transport affecting the Yangtze River at longer lead time, suggesting that the ARs influencing summer monsoon rainfall in the East Asian region are likely to be more predictable than rainfall itself. There is potential in using AR predictions from the coupled forecast system to guide rainfall forecasts in the East Asian summer season at longer lead time, which can contribute to disaster prevention and reduction in East Asia.

Satellite Observations of Wind Wake and Associated Oceanic Thermal Responses: A Case Study of Hainan Island Wind Wake

The wind wake on the lee side of Hainan Island in the winter covers the southwest entrance of Beibu Gulf (or Gulf of Tonkin) and is essential to regional ocean dynamics. Using multiple satellite observations including advanced synthetic aperture radar (ASAR), we revisited the wake process during the winter of 2011. Asymmetric oceanic thermal responses were found with a warm band expanding northwestwardly while a cold tongue formed to the southeast. Combining satellite observations, model simulations, and reanalysis data, heat advection terms (ADV) are reconstructed and compared to air-sea heat flux terms. The observed thermal evolution process across the wake footprint is closely related to the balanced spatial variability from the Ekman ADV, the barotropic geostrophic ADV, and the latent heat flux (LHF), which are all on the order of 10−5 K·m·s−1. Specifically, the Ekman ADV tends to heat the northwestern side of the wake and cool the southeastern side, while the geostrophic ADV compensates with the Ekman ADV across the wake footprint. This study reveals detailed oceanic responses associated with the wind wake and clarifies the contribution of ADV to the asymmetric spatial thermal variabilities. The identified role of heat advection on a sub-seasonal timescale may further benefit the understanding of regional oceanic dynamics.

Subseasonal to Seasonal Prediction of Wintertime Northern Hemisphere Extratropical Cyclone Activity by S2S and NMME Models

AbstractIn this study, the prediction of wintertime extratropical cyclone activity from subseasonal to seasonal timescale in current dynamical models' reforecasts is investigated. On seasonal time scales, the North American Multi‐Model Ensemble (NMME) models show skillful predictions over the eastern North Pacific, North America and the western North Atlantic with at least 5 months lead. The prediction skill is highly related to El Nino‐Southern Oscillation (ENSO), as using the ENSO‐related SST pattern gives rise to prediction skill with very similar spatial pattern and amplitude. On subseasonal time scales, models in the Seasonal to Sub‐seasonal Prediction (S2S) dataset have skillful predictions up to 4 weeks lead over regions from the eastern North Pacific to the western Atlantic, as well as northern Europe, the eastern Atlantic and East Asia. Generally, forecast skill improves with a larger ensemble size. The subseasonal prediction skill from the Pacific to the western Atlantic is related to ENSO, and that over eastern Atlantic, Europe and East Asia are associated with stratospheric polar vortex anomalies. Current models do not show much skill from the Madden‐Julian Oscillation (MJO), as the MJO impact on extratropical cyclone activity is not well captured by the models. European Centre for Medium‐Range Weather Forecasts (ECMWF) model has the highest single model subseasonal prediction skill. The prediction skill in the ECMWF model is higher than its estimated potential predictability, likely because the signal‐to‐noise ratio is too low in the model hindcasts.

Seasonality of surface stirring by geostrophic flows in the Bay of Bengal

Stirring of passive tracers in the Bay of Bengal driven by altimetry derived daily geostrophic surface currents, is studied on subseasonal timescales. To begin with, Hovmöller plots, wavenumber-frequency diagrams and power spectra confirm the multiscale nature of the flow. Advection of latitudinal and longitudinal bands highlights the chaotic nature of stirring in the Bay via repeated straining and filamentation of the tracer field. An immediate finding is that stirring is local, i.e. of the scale of the eddies, and does not span the entire basin. Further, stirring rates are enhanced along the coast of the Bay and are relatively higher in the pre- and post-monsoonal seasons. Indeed, Finite Time Lyapunov Exponent (FTLE) and Finite Size Lyapunov Exponent (FSLE) maps in all the seasons are patchy with minima scattered through the interior of the Bay. Further, these maps bring out a seasonal cycle wherein rapid stirring progressively moves from the northern to southern Bay during pre- and post-monsoonal periods, respectively. The non-uniform stirring of the Bay is reflected in long tailed probability density functions of FTLEs, that become more stretched for longer time intervals. Quantitatively, advection for a week shows the mean FTLE lies between 0.13±0.07 day−1, while extremes reach almost 0.6 day−1. Averaged over the Bay, Relative dispersion initially grows exponentially, followed by a power-law at scales between approximately 100 and 250 km, which finally transitions to an eddy-diffusive regime. Quantitatively, below 250 km, a scale dependent diffusion coefficient is extracted that behaves as a power-law with cluster size, while above 250 km, eddy-diffusivities range from 6×103−1.6×104 m2s−1 in different regions of the Bay. These estimates provide a useful guide for resolution dependent diffusivities in numerical models that hope to properly represent surface stirring in the Bay.

The non-linear relationship between the western North Pacific anticyclonic circulation and Korean summer precipitation on subseasonal timescales

It has been widely known that the pulse of the western North Pacific anticyclonic circulation (WNPAC) plays a key role on East Asian summer climate variability in subseasonal to interannual time scales. Yet, the relation between the WNPAC and summer precipitation over Korea is not robust on seasonal and subseasonal timescales for the recent few decades. Here, we show that the low correlation between WNPAC and Korean precipitation is attributable to their distinctive non-linear relationship and investigate detailed features in their four different phase relationships on subseasonal time scales. First, the positive Korean precipitation anomaly occurs as the part of zonally elongated precipitation band along with the positive WNPAC anomaly closely connected with the decaying phase of El Nino and Indian Ocean warming. The second case is enhanced Korean precipitation accompanying with negative WNPAC anomaly. In this case, the negative WNPAC anomaly constitutes a part of atmospheric wave train across the North Pacific and this feature is associated with the decaying phase of La Nina. The typhoon-related precipitation event also contributes to this case. Third, the negative Korean precipitation anomaly arises when the low-level easterly anomaly along with the northern flank of negative WNPAC anomaly leads to suppressed convective activity in Korea. Lastly, the negative Korean precipitation anomaly happens with the positive WNPAC anomaly when anomalous high covers entire East Asia and the WNP mainly during the decaying phase of central Pacific El Nino. The understanding of the non-linear relationship between WNPAC and Korean precipitation in this study provides better insight into the potential impacts of El Nino-Southern Oscillation and circulation/convection anomaly over the WNP on summer Korean precipitation.

Frequency of Persistent Blocking and Ridge Events Related to Precipitation over Eastern China during August and Its Preceding Atmospheric Signals

Abstract Based on a recently developed approach that can recognize both persistent blocking and ridge events effectively, the contributions of the frequency of these persistent events (FOPE) over different regions in Eurasia to precipitation over eastern China were investigated. The results reveal that, the FOPE over the longitudinal range of 110°–130°E, near the Stanovoy Mountains and the Okhotsk Sea, is significantly correlated with precipitation over the middle and lower reaches of the Yangtze River (MLRYR) during summer, particularly in August. The preceding full July (or 1–20 July) mean Balkhash Lake–Caucasus geopotential height index, which measures the combined effect of the Balkhash Lake and Caucasus geopotential height anomalies, is closely related to the August geopotential height anomaly around the Stanovoy Mountains and the Okhotsk Sea, and can therefore reflect the August 110°–130°E FOPE. The predictability based on this preceding atmospheric signal seems to be attributable to slow-varying atmospheric processes on a subseasonal (20-day mean) time scale. On this time scale, the Balkhash Lake and Caucasus geopotential height anomalies occur prior to, and seem to modulate, the geopotential height anomaly around the Stanovoy Mountains and the associated 110°–130°E FOPE through an eastward extension and through exciting a positive–negative–positive pattern in 500-hPa geopotential heights, respectively. As a result of the slow-varying atmospheric processes, this preceding atmospheric signal performs well in predicting the August 110°–130°E FOPE, which also facilitates the prediction of the MLRYR precipitation.

Relationships between Sea Ice Concentration and Wind Speed over the Arctic Ocean during 1979–2015

AbstractNCEP CFSR reanalysis 6-hourly fields from 1979 to 2015 were used to investigate the relationships of sea ice concentration (SIC), atmospheric stratification, surface roughness, and wind speed at 10-m height (W10) and 850-hPa level (W850). We found that in autumn (September–November), winter (December–February), and spring (March–May) a lower SIC favors less-stable stratification and a higher W10. In autumn, the decrease in SIC is strongest, and SIC has its strongest correlation with the atmospheric stratification, W10, and the ratio of W10 and W850 (WSR). W10 and WSR have increased in autumn, and the negative trends in SIC typically are collocated with positive trends in W10 and WSR. In winter, W850 has negative trends over the Arctic Ocean, which, together with the lack of decrease of SIC in the central Arctic, has prevented W10 from increasing in winter. The winter trends are notably different from those for autumn, but the correlations are fairly similar. In autumn, winter, and spring, the negative correlation between SIC and W10 originated from the reduction of both stratification and aerodynamic surface roughness z0 with a reduction of SIC. The dependence of z0 on SIC is, however, weak in NCEP CFSR. In summer, the ratio of W10 and W850 has increased over large areas. The correlations between SIC and atmospheric variables were stronger on interannual time scales than on subseasonal time scales. The causal relationships are complicated by the two-way interaction between SIC and W10. In most cases, especially in summer, SIC increases after periods of W10 exceeding 5 m s−1.

Stratospheric modulation of the large‐scale circulation in the Atlantic–European region and its implications for surface weather events

AbstractExtreme states of the stratospheric polar vortex can have long‐lasting impacts on extratropical circulation patterns, such as the North Atlantic Oscillation (NAO). This provides windows of subseasonal predictability beyond the typical weather forecast horizon of about 10 days. Subseasonal forecasts of surface weather are of significant interest in weather‐dependent socio‐economic sectors. For example, demand and supply for electricity and gas are weather dependent and therefore accurate forecasts are important for the energy industry and energy trading. Here we investigate the subseasonal impact of stratospheric conditions on surface weather events relevant to the energy industry in five subregions of Europe in winter. We use a definition of seven Atlantic–European weather regimes to describe the variability of the large‐scale circulation on subseasonal time scales. Results indicate that weather events are often associated with more than one preferred weather regime. In turn, some weather regimes project onto a specific NAO phase, while others are independent of the NAO. As expected, anomalous stratospheric polar vortex states predominantly modulate the occurrence of regimes related to the NAO and affect the likelihood of their associated weather events. In contrast, the occurrence of weather regimes which do not project well onto the NAO is not affected by anomalous stratospheric polar vortex states. These regimes provide pathways to unexpected weather events in extreme stratospheric polar vortex states. For example, weak stratospheric polar vortex states enhance the likelihood of negative NAO. High wind events in Central Europe predominantly occur during the zonal regime, strongly projecting onto positive NAO. However, these events also occur during the Atlantic trough regime, which is unaffected by anomalous stratospheric polar vortex states and thus provides a pathway to Central European high wind events during weak stratospheric polar vortex states. A correct NAO prediction alone is therefore not sufficient to correctly predict surface weather after extreme stratospheric polar vortex states. Moreover, weather regime life cycles independent of the NAO also need to be forecast accurately.

Meridionally Extending Anomalous Wave Train over Asia During Breaks in the Indian Summer Monsoon

Anomalous interactions between the Indian summer monsoon (ISM) circulation and subtropical westerlies are known to trigger breaks in the ISM on subseasonal time-scales, characterised by a pattern of suppressed rainfall over central-north India, and enhanced rainfall over the foothills of the central–eastern Himalayas (CEH). An intriguing feature during ISM breaks is the formation of a mid-tropospheric cyclonic circulation anomaly extending over the subtropical and mid-latitude areas of the Asian continent. This study investigates the mechanism of the aforesaid Asian continental mid-tropospheric cyclonic circulation (ACMCC) anomaly using observations and simplified model experiments. The results of our study indicate that the ACMCC during ISM breaks is part of a larger meridional wave train comprising of alternating anticyclonic and cyclonic anomalies that extend poleward from the monsoon region to the Arctic. A lead–lag analysis of mid-tropospheric circulation anomalies suggests that the meridional wave-train generation is linked to latent heating (LH) anomalies over the CEH foothills, Indo-China, and the Indian landmass during ISM breaks. By conducting sensitivity experiments using a simplified global atmospheric general circulation model forced with satellite-derived three-dimensional LH, it is demonstrated that the combined effects of the enhanced LH over the CEH foothills and Indo-China and decreased LH over the Indian landmass during ISM breaks are pivotal for generating the poleward extending meridional wave train and the ACMCC anomaly. At the same time, the spatial extent of the mid-latitude cyclonic anomaly over Far-East Asia is also influenced by the anomalous LH over central–eastern China. While the present findings provide interesting insights into the role of LH anomalies during ISM breaks on the poleward extending meridional wave train, the ACMCC anomaly is found to have important ramifications on the daily rainfall extremes over the Indo-China region. It is revealed from the present analysis that the frequency of extreme rainfall occurrences over Indo-China shows a twofold increase during ISM break periods as compared to active ISM conditions.

Data-adaptive spatio-temporal filtering of GRACE data

SUMMARYMeasurements of the spatio-temporal variations of Earth’s gravity field from the Gravity Recovery and Climate Experiment (GRACE) mission have led to new insights into large spatial mass redistribution at secular, seasonal and subseasonal timescales. GRACE solutions from various processing centres, while adopting different processing strategies, result in rather coherent estimates. However, these solutions also exhibit random as well as systematic errors, with specific spatial patterns in the latter.In order to dampen the noise and enhance the geophysical signals in the GRACE data, we propose an approach based on a data-driven spatio-temporal filter, namely the Multichannel Singular Spectrum Analysis (M-SSA). M-SSA is a data-adaptive, multivariate, and non-parametric method that simultaneously exploits the spatial and temporal correlations of geophysical fields to extract common modes of variability.We perform an M-SSA analysis on 13 yr of GRACE spherical harmonics solutions from five different processing centres in a simultaneous setup. We show that the method allows us to extract common modes of variability between solutions, while removing solution-specific spatio-temporal errors that arise from the processing strategies. In particular, the method efficiently filters out the spurious north–south stripes, which are caused in all likelihood by aliasing, due to the imperfect geophysical correction models and low-frequency noise in measurements.Comparison of the M-SSA GRACE solution with mass concentration (mascons) solutions shows that, while the former remains noisier, it does retrieve geophysical signals masked by the mascons regularization procedure.

Flash Drought Characteristics Based on U.S. Drought Monitor

Understanding the characteristics of flash drought events and further predicting the onset of such events on subseasonal timescales is of critical importance for impact assessment, disaster mitigation, and loss prevention. In this study, we employ a rate-of-change approach and define a flash drought event as a drought event with greater than or equal to two categories degradation in a four-week period based on the U.S. Drought Monitor. Unlike conventional drought, which can occur year-round and everywhere in the United States, flash drought has preferred seasons and locations to occur, mostly in the warm season and over the central United States. Widespread flash drought over the United States is largely correlated with La Niña episodes. In contrast with conventional drought, which is mainly driven by precipitation deficits, anomalously high evapotranspiration rates, caused by anomalously high temperatures, winds, and/or incoming radiation, are usually present before the onset of flash drought. Comparing to precipitation and soil moisture, evapotranspiration typically has the largest decline rate during the fast-development phase. Three-month Standardized Precipitation Indexes are mostly dry right before flash drought onset, but large deficits are not required. As a result, monitoring rapid changes in evapotranspiration, along with precipitation and soil moisture conditions, can provide early warnings of flash drought development.

Thermal fronts and attracting Lagrangian Coherent Structures in the north Bay of Bengal during December 2015–March 2016

We investigate two-dimensional advective stirring by satellite-derived ocean surface currents in the north Bay of Bengal during December 2015–March 2016 using the framework of Lagrangian Coherent Structures (LCS). The forward and backward finite-time Lyapunov exponent (fFTLE and bFTLE, respectively) fields indicate that freshwater parcels from the river run-off are subjected to intense stirring by the ocean surface currents, which contain both geostrophic and wind-forced Ekman currents. Large-scale thermal fronts present in the satellite-based sea surface temperature (SST) fields are then shown to closely resemble attracting LCS (aLCS) that govern horizontal advective stirring on subseasonal time scales. Statistical estimates of the angle between the thermal fronts (of all spatial scales present in the SST data) and the aLCS from the entire north Bay of Bengal show a preference to align with each other. Significantly, in the presence of sufficiently strong aLCS in their neighbourhood, thermal fronts are shown to have a strong preference to align with them. Finite-time advection of fluid particles over around a week to compute the bFTLE fields results in the strongest alignment between the thermal fronts and neighbouring aLCS. The robustness of our results are established by presenting analyses of (i) geostrophic currents from altimeter data, and (ii) a reanalysis-based fine-scale salinity field. Attracting LCS, identified as sufficiently strong ridges in the bFTLE fields, are argued to represent reasonable estimates of the location and orientation of fronts (thermal or salinity) formed by advective stirring over subseasonal time scales.

Ocean Observations to Improve Our Understanding, Modeling, and Forecasting of Subseasonal-to-Seasonal Variability

Subseasonal-to-seasonal (S2S) forecasts have the potential to provide advance information about weather and climate events. The high heat capacity of water means that the subsurface ocean stores and re-releases heat (and other properties) and is an important source of information for S2S forecasts. However, the subsurface ocean is challenging to observe, because it cannot be measured by satellite. Subsurface ocean observing systems relevant for understanding, modeling, and forecasting on S2S timescales will continue to evolve with the improvement in technological capabilities. The community must focus on designing and implementing low-cost, high-value surface and subsurface ocean observations, and developing forecasting system capable to extract their observation potential in forecast applications. S2S forecasts will benefit significantly from higher spatiotemporal resolution data in regions that are sources of predictability on these timescales (coastal, tropical, and polar regions). While ENSO has been a driving force for the design of the current observing system, the subseasonal time scales present new observational requirements. Advanced observation technologies such as autonomous surface and subsurface profiling devices as well as satellites that observe the ocean-atmosphere interface simultaneously can lead to breakthroughs in coupled data assimilation (CDA) and coupled initialization for S2S forecasts. These observational platforms should also be tested and evaluated in ocean observation sensitivity experiments with current and future generation CDA and S2S prediction systems. Investments in the new ocean observations, as well as model and DA system developments, can lead to substantial returns on cost savings from disaster mitigation as well as socio-economic decisions that use S2S forecast information.

Skillful Prediction of Monthly Major Hurricane Activity in the North Atlantic with Two‐way Nesting

AbstractWe investigate the monthly prediction of North Atlantic hurricane and especially major hurricane activity based on the Geophysical Fluid Dynamics Laboratory High‐Resolution Atmospheric Model (HiRAM). We compare the performance of two grid configurations: a globally uniform 25‐km grid and the other with an 8‐km interactive nest over the tropical North Atlantic. Both grid configurations show skills in predicting anomalous monthly hurricane frequency and accumulated cyclone energy. Particularly, the 8‐km nested model shows improved skills in predicting major hurricane frequency and accumulated cyclone energy. The skill in anomalous monthly hurricane occurrence prediction arises from the accurate prediction of zonal wind shear anomalies in the Main Development Region, which in turn arises from the sea surface temperature anomalies persisted from the initialization time. The enhanced resolution on the nested grid permits a better representation of hurricanes and especially intense hurricanes, thereby showing the ability and the potential for prediction of major hurricanes on subseasonal timescales.

Winter pressures on the UK health system dominated by the Greenland Blocking weather regime

In many countries, wintertime cold weather is linked to ill-health and intense pressure on public health services. This study examines how both long-term climate change and sub-seasonal variability contribute to the temperature extremes that increase pressures on the UK's National Health Service. The impact of temperature on fractional mortality and hospital admissions due to chronic obstructive pulmonary disease are used as metrics of wintertime pressure on the health system. The focus of the study is on days during the year in which the fractional mortality and hospital admissions attributable to cold weather exceed the five-year return period. These days are henceforth called winter pressure days since they likely to lead to significant pressure on the health service to meet demand. On interdecadal and longer timescales, winter pressure days show a robust decline over recent decades with a reduction from a probability of 0.29 in the pre-industrial period to 0.11 for the period 2000–2016. Comparing the risk of winter pressure days in two different climate model simulations of the historical period and a counterfactual ensemble of only natural climate forcings shows that this decline can be clearly attributed to anthropogenic activity. The average Fraction of Attributable risk due to anthropogenic activity for these two climate models for winter pressure days is −0.94. On sub-seasonal timescales, weather drivers of winter pressure days are assessed through analysis of diagnostics of weather regime lifecycles. This analysis shows winter pressure days occur almost exclusively in the Greenland Blocking regime. Although the risk of winter pressure days is likely to continue to decline with current climate trends, there remains a substantial weather driven risk to the UK health system. Preparing for weather events that cause stress on the system should focus on the analysis and prediction of the Greenland Blocking regime on weekly timescales.

Interdecadal Variations in the Frequency of Persistent Hot Events in Boreal Summer over Midlatitude Eurasia

ABSTRACT Based on the daily Japanese 55-year Reanalysis (JRA-55) dataset, this study reveals that southern Europe/western Asia (SEWA) and northern China are two large-scale regions that have exhibited consistent interdecadal variations in the frequency of persistent hot events (PHEs). Over the past 58 summers, the period approximately from 1973 to 1996 represents an inactive period for the occurrence of PHEs over the two regions, whereas the antecedent and subsequent periods are active periods. At the subseasonal time scale, the regional PHEs over SEWA are characterized by quasi-stationary wave train anomalies aloft from the northwest Atlantic to Europe, while the regional PHEs over northern China are characterized by quasi-stationary wave train anomalies over the Eurasian continent. The persistence of the quasi-stationary anomalies is associated with the Rossby wave propagation. Moreover, the energy extraction from the basic flow is also favorable for their persistence. Our study reveals that the above typical circulation anomalies for the PHEs over both SEWA and northern China are in phase with the background circulation changes during the two active periods. Thus, the interdecadal changes in background circulation can modulate the frequency of PHEs over the two regions simultaneously. Further analysis reveals that the background circulation changes are closely related to the interdecadal variation in the Silk Road pattern based on their similarities in both spatial pattern and temporal variation. The sea surface temperature over four particular regions seems to facilitate the phase shifts in the Silk Road pattern on the interdecadal time scale.