Subseasonal Time Scales Research Articles

Roles of Atmospheric Variability and Arctic Sea Ice in the Asymmetric Arctic–Eurasia Temperature Connection on Subseasonal Time Scale

Abstract Despite the severe impacts on Eurasian extreme weather, the mechanisms and causes of the “warm Arctic–cold Eurasia” (WACE) pattern and its opposite phase “cold Arctic–warm Eurasia” (CAWE) remain a subject of active debate. With a focus on subseasonal time scale, this study investigates the roles of atmospheric variability and Arctic sea ice in the variation of asymmetric WACE and CAWE patterns in the cold season. WACE (CAWE) patterns are predominantly driven by the temperature advection by anticyclonic (cyclonic) wave activity anomaly over Ural region. Low-frequency processes from both eddy vorticity and heat fluxes are important for the formation of the Ural wave activity anomaly. The subseasonal Arctic sea ice anomaly plays an additional role in maintaining the persistence of WACE and CAWE anomalies through surface heat flux exchange and alteration of Ural wave activity anomaly. Both comprehensive and idealized numerical experiments suggest that sea ice anomalies or thermal forcing act to maintain the WACE pattern by increasing the persistence of Ural anticyclonic anomaly through reducing background flow. The net effect of subseasonal thermal forcing on the WACE and CAWE anomalies is dependent on the mean state on longer time scale. We argue that the dominance of WACE over CAWE is mainly attributed to stronger roles of internal low-frequency atmospheric variability in driving the Ural anticyclonic anomaly and sea ice anomaly or thermal forcing in extending the persistence of the Ural anticyclonic anomaly through modulation on the background flow. Significance Statement The purpose of this study is to better understand the subseasonal variability of the “warm Arctic–cold Eurasia” (WACE) and “cold Arctic–warm Eurasia” (CAWE) patterns, which have severe impacts on Eurasian extreme weather. We highlight a dominance of WACE over CAWE, and attribute it to stronger roles of atmospheric variability in driving the WACE pattern and Arctic sea ice in maintaining the WACE anomalies. These findings have important implications for improving the subseasonal prediction of regional extremes.

Subseasonal Warming of Surface Soil Enhances Precipitation Over the Eastern Tibetan Plateau in Early Summer

AbstractThe precipitation over the eastern Tibetan Plateau (ETP, here defined as 29°–38°N, 91°–103°E) usually exhibits significant subseasonal variation during boreal summer. As the hot spot of land‐air interaction, the influences of ETP surface soil temperature (Tsoil) on the local precipitation through subseasonal land‐air interaction are still unclear but urgently needed for improving subseasonal prediction. Based on station and reanalysis datasets of 1979–2018, this study identifies the evident quasi‐biweekly (QBW) (9–30 days) periodic signal of ETP surface Tsoil variation during the early summer (May–June), which results from the anomalies of southeastward propagating mid‐latitude QBW waves in the mid‐to‐upper troposphere. The observational results further show that the maximum positive anomaly of precipitation over the ETP lags the warmest surface Tsoil by one phase at the QBW timescale, indicating that the warming surface Tsoil could enhance the subseasonal precipitation. The numerical experiments using the WRF model further demonstrate the effect of warming surface Tsoil on enhancing the local cyclonic and precipitation anomaly through increasing upward sensible heat flux, the ascending motion, and water vapor convergence at the QBW timescale. In contrast, the effect of soil moisture over the ETP is much weaker than Tsoil at the subseasonal timescale. This study confirms the importance of surface Tsoil over the ETP in regulating the precipitation intensity, which suggests better simulating the land thermal feedback is crucial for improving the subseasonal prediction.

A surface temperature dipole pattern between Eurasia and North America triggered by the Barents–Kara sea-ice retreat in boreal winter

The Arctic has experienced dramatic climate changes, characterized by rapid surface warming and sea-ice loss over the past four decades, with broad implications for climate variability over remote regions. Some studies report that Arctic warming may simultaneously induce a widespread cooling over Eurasia and frequent cold events over North America, especially during boreal winter. In contrast, other studies suggest a seesaw pattern of extreme temperature events with cold weather over East Asia accompanied by warm weather in North America on sub-seasonal time scales. It is unclear whether a systematic linkage in surface air temperature (SAT) exists between the two continents, let alone their interaction with Arctic sea ice. Here, we reveal a dipole pattern of SAT in boreal winter featuring a cooling (warming) in the Eurasian continent accompanied by a warming (cooling) in the North American continent, which is induced by an anomalous Barents–Kara sea-ice decline (increase). The dipole operates on interannual and multidecadal time scales. We find that an anomalous sea-ice loss over the Barents–Kara Seas triggers a wavenumber one atmospheric circulation pattern over the high-latitude Northern Hemisphere, with an anomalous high-pressure center over Siberia and an anomalous low-pressure center over high-latitude North America. The circulation adjustment generates the dipole temperature pattern through thermal advection. Our finding has important implications for Northern Hemisphere climate variability, extreme weather events, and their prediction and projection.

Diabatic Upwelling in the Tropical Pacific: Seasonal and Subseasonal Variability

Abstract The equatorial Pacific zonal circulation is composed of westward surface currents, the eastward equatorial undercurrent (EUC) along the thermocline, and upwelling in the eastern cold tongue. Part of this upwelling arises from water flowing along isotherms sloping up to the east, but it also includes water mass transformation and consequent diabatic (cross-isothermal) flow (wci) that is a key element of surface-to-thermocline communication. In this study we investigate the mean seasonal cycle and subseasonal variability of cross-isothermal flow in the cold tongue using heat budget output from a high-resolution forced ocean model. Diabatic upwelling is present throughout the year with surface-layer solar-penetration-driven diabatic upwelling strongest in boreal spring and vertical mixing in the thermocline dominating during the rest of the year. The former constitutes warming of the surface layer by solar radiation rather than exchange of thermal energy between water parcels. The mixing-driven regime allows heat to be transferred to the core of the EUC by warming parcels at depth. On subseasonal time scales the passage of tropical instability waves (TIWs) enhances diabatic upwelling on and north of the equator. On the equator the TIWs enhance vertical shear and induce vertical-mixing-driven diabatic upwelling, while off the equator TIWs enhance the sub-5-daily eddy heat flux which enhances diabatic upwelling. Comparing the magnitudes of TIW, seasonal, and interannual wci variability, we conclude that each time scale is associated with sizeable variance. Variability across all of these time scales needs to be taken into account when modeling or diagnosing the effects of mixing on equatorial upwelling.

East Asian heatwaves driven by Arctic-Siberian warming

This study investigates the contributing factors of East Asian heatwaves (EAHWs) linked to the Arctic-Siberian Plain (ASP) over the past 42 years (1979–2020). EAHWs are mainly affected by two time scales of variabilities: long-term externally forced and interannual variabilities. The externally forced EAHWs are attributed to the increasing global warming trend, while their interannual variability is related to the circumglobal teleconnection (CGT) and the ASP teleconnection patterns. In addition to the CGT, the Rossby wave energy originating from the ASP propagates to East Asia through the upper troposphere, amplifying the EAHWs. The stationary high pressure in the ASP is generated by vorticity advection in the upper troposphere. Enhanced surface radiative heating and evaporation on the ASP surface increase the specific humidity and temperature, amplifying the thermal high pressure via positive water vapor feedback. Thermal high-pressure amplified by land–atmosphere interactions in the ASP during the peak summer season leads to EAHWs by the propagation of stationary Rossby wave energy. The results indicate that our enhanced understanding of the ASP teleconnection can improve forecasting of the EAHWs not only on a sub-seasonal time scale but also in future projections of global climate models.

Potential applications for climate services originated from the CLIMAX project

CLIMAX (Climate Services Through Knowledge Co-Production: A Euro-South American Initiative For Strengthening Societal Adaptation Response to Extreme Events) was an international project funded by FAPESP-Belmont forum developed during the 2016–2021 period. Germany, France, Netherlands, Argentina/France and Brazil were the international partners who worked in common objectives and tasks. The project was composed of four main Work Packages (WP), which interacted to achieve the final goal of developing potential applications to climate services. Here, some of the researches and results conducted by the team in Brazil, aiming at the application by climate services in several sectors, mainly in the energy sector are presented, some including international partners collaborations. The WP0—Co-design and Co-Production of Knowledge, was developed in collaboration with the energy sector, the National Operator of Electric System (ONS). Climate research activities were conducted through interactions between climate researchers, energy sector personnel and social scientists, focusing on applications. WP1—Physical processes explaining climate variability in South America, aimed to study the remote and regional features associated with precipitation extremes over South America, with emphasis on regions where the main hydrographic basins are located. WP2—Predictability and Prediction tools developed several studies, mainly at the sub-seasonal timescale, which was a timescale identified to be useful for ONS. WP3—Social processes explaining climate information appropriation was composed of social scientists and had the mission of producing a characterization of the electric sector. Here, some of the WP1 and WP2 results are summarized, illustrating the potential applications. WP0 and WP3 results are presented in other papers.

Identifying Causes of Short-Range Forecast Errors in Maximum Temperature during Recent Central European Heatwaves Using the ECMWF-IFS Ensemble

Abstract In the last few years, central Europe faced a number of severe, record-breaking heatwaves. Previous studies focused on predictability of heatwaves on medium-range to subseasonal time scales (5–30 days). However, also short-range (3-day) forecasts of maximum temperature (Tmax) can exhibit substantial errors even on larger spatial scales. This study investigates the causes of short-range forecast errors in Tmax over central Europe for the summers of 2015–20 using the 50-member ensemble of the operational ECMWF-IFS (ECMWF-ENS). The 3-day forecast errors, individually calculated for each ensemble member with respect to a 0–18-h control forecast, are fed into a multivariate linear regression model to study the relative importance of different error sources. Outside of heatwaves, errors in Tmax forecasts are predominantly caused by incorrectly predicted downwelling shortwave radiation, mainly due to errors in low cloud cover. During heatwaves, ECMWF-ENS exhibits a systematic underestimation of Tmax (−0.4 K), which is exacerbated under clear-sky and low wind conditions, and other error sources gain importance: the second most important error source is over- or underestimation of nocturnal temperatures in the residual layer. Additional Lagrangian trajectory analysis for the years 2018–20 (due to limited data availability) suggests a link to accumulating errors in near-surface diabatic heating of air masses associated with forecast errors in residence time over land and cloud cover. Regionally, other physical processes can be of dominant importance during heatwaves. Coastal regions are influenced by errors in near-surface wind whereas errors in soil moisture are more important in southeastern parts of central Europe.

What Distinguishes MJO Events Associated with Atmospheric Rivers?

Abstract Atmospheric rivers (ARs) are long and narrow bands of intense water vapor transport that often induce heavy precipitation and flooding along the west coast of North America. Previous studies demonstrate that the Madden–Julian oscillation (MJO) contributes to the predictability of AR activity on a subseasonal time scale. However, individual AR responses vary widely following the same phase of MJO. Here we investigate 96 MJO events following phase 3 (convection over the Indian Ocean) and analyze the differences between events that brought large-scale ARs to the entire Pacific Northwest coastal region and those that did not. The MJO events with ARs tend to stay longer at phase 3 than those without ARs. We use linear regression to isolate the extratropical signals linearly related to the MJO and explore how the residual fields differ between the two groups. The linearly dependent signal shows slow-moving planetary-scale water vapor transport across the North Pacific. The residual field exhibits a contrasting extratropical low-frequency (>10 days) pattern in the Gulf of Alaska resembling the Pacific–North American (PNA) pattern: a trough for events with ARs and a ridge for events without ARs. This low-frequency variability alters the Pacific waveguide such that, for MJO events with ARs, baroclinic waves are directed into the Pacific Northwest with an orientation that favors anomalous positive IVT. For MJO events without ARs, the ridge strengthens large-scale anticyclonic flow over the North Pacific and prevents moisture access to the Pacific Northwest.

North Pacific and North Atlantic Jet Covariability and Its Relationship to Cool Season Temperature and Precipitation Extremes

Abstract Cool season (September–May) extreme temperature and precipitation events are frequently tied to surface cyclones and anticyclones, which are modulated on the synoptic scale by the state and evolution of the upper-tropospheric jet stream. This study adopts a jet-centered approach to classify the prevailing large-scale flow pattern into jet regimes based on the leading modes of variability of the North Pacific jet (NPJ) and the North Atlantic jet (NAJ), respectively. The characteristics of these joint NPJ–NAJ regimes are subsequently examined using composite analysis to identify large-scale flow environments conducive to the occurrence of anomalous temperatures and precipitation across North America. The analysis reveals that composite large-scale flow environments associated with each joint NPJ–NAJ regime can be approximated as a linear combination of the separate large-scale environments that characterize each NPJ regime and NAJ regime independently. Furthermore, knowledge of the joint NPJ–NAJ regime provides more precision regarding the relative likelihood and spatial coverage of anomalous temperatures and precipitation than would be obtained from consideration of the NPJ or NAJ regime in isolation. The frequencies of each joint NPJ–NAJ regime can also be modulated by the occurrence of sudden stratospheric warmings, with increased frequencies of an equatorward-shifted NAJ and a retracted NPJ during the 30-day period following a warming event. The results from the present study demonstrate that knowledge of the joint NPJ–NAJ regime exhibits the potential to inform forecasts of anomalous temperatures and precipitation at medium-range and subseasonal time scales. Significance Statement The development of cool season temperature and precipitation extremes are modulated by the state and evolution of the upper-tropospheric jet stream. Therefore, this study adopts a jet-centered approach to quantify the extent to which temperature and precipitation extremes over North America are related to the coevolution of the North Pacific and North Atlantic segments of the jet stream. The analysis demonstrates that the relative likelihood and spatial coverage of temperature and precipitation extremes varies significantly across North America based on the combined state of the North Pacific and North Atlantic jets. The jet-centered approach utilized in this study exhibits the potential to inform operational medium-range (6–10 day) and subseasonal forecasts of temperature and precipitation across North America.

Respective and Combined Impacts of North Indian Ocean and Tropical North Atlantic SST Anomalies on the Subseasonal Evolution of Anomalous Western North Pacific Anticyclones

Abstract The subseasonal variation of the anomalous western North Pacific anticyclone (WNPAC) has important implications for East Asian summer monsoon variability. How the WNPAC evolves on the subseasonal time scale under the different configurations of tropical North Atlantic (TNA) Ocean and north Indian Ocean (NIO) SST warming is elucidated in this study. The WNPAC forced by individual TNA SST warming shows an obvious subseasonal variation with a stepwise northward movement. In contrast, the WNPAC forced by individual NIO SST warming shows a weak subseasonal variation, being nearly stabilized at around 20°N from June to August and thereby causing long-lasting and intense positive mei-yu–baiu–changma rainfall anomalies. The physical mechanism for the different subseasonal variation of WNPAC is further investigated. The TNA SST warming generates a WNPAC via a Rossby wave–induced divergence/convergence chain response. In this process, the TNA SST warming-induced suppressed convection over the western Pacific moves northward with the northward movement of climatological intertropical convergence zone and summer monsoon region, which generates a northward shift of the WNPAC. However, the NIO SST warming produces a WNPAC via a Kelvin wave–induced suppressed convection over the western Pacific Ocean. This suppressed convection is stabilized at around 20°N because of the Kelvin wave activity scope being limited within 20°N, which finally produces a nearly stationary WNPAC from June to August. In addition, under the simultaneous occurrence of the TNA and NIO SST warming, the subseasonal variation of WNPAC bears a resemblance to that for the individual NIO SST warming condition, where the TNA SST warming fails to exert its impact.

Subseasonal forecasts of precipitation over maritime continent in boreal summer and the sources of predictability

In this study, subseasonal precipitation forecast skills over Maritime Continent in boreal summer are investigated for the ECMWF and CMA models involved in the S2S Project. Results indicate that the ECMWF model shows generally superior forecast performances than CMA, which is characterized by lower errors and higher correlations compared with the observations. Meanwhile, ECMWF tends to produce wet biases with increasing lead times, while the mean errors of CMA are revealed to be approximately constant throughout lead times of 2–4 weeks over most areas. Besides, the temporal correlations between model outputs and observations obviously decrease with growing lead times, with a high-low distribution presented from north to south. In addition, the roles of large-scale drivers like ENSO and BSISO in modulating subseasonal precipitation forecast skills are also assessed in the models. Both ECMWF and CMA can reasonably capture the ENSO related precipitation anomalies for all lead times, while their capabilities of capturing BSISO related precipitation anomalies decrease with growing lead times, which is more obvious in CMA. The enhanced subseasonal precipitation forecast skills mainly respond to the BSISO associated precipitation variability. For most MC areas such as southern Indochina, western Indonesia, Philippines and the eastern ocean, the forecast skills of both ECMWF and CMA can be improved to a great extent by enhancing the capture of BSISO related precipitation anomalies, with the temporal correlations for both ECMWF and CMA increased by about 0.15 for lead times of 3–4 weeks. It provides an opportunity window for the models to improve precipitation forecasts on the subseasonal timescale.

Improving the prediction of the Madden–Julian Oscillation of the ECMWF model by post-processing

Abstract. The Madden–Julian Oscillation (MJO) is a major source of predictability on the sub-seasonal (10 to 90 d) timescale. An improved forecast of the MJO may have important socioeconomic impacts due to the influence of MJO on both tropical and extratropical weather extremes. Although in the last decades state-of-the-art climate models have proved their capability for forecasting the MJO exceeding the 5-week prediction skill, there is still room for improving the prediction. In this study we use multiple linear regression (MLR) and a machine learning (ML) algorithm as post-processing methods to improve the forecast of the model that currently holds the best MJO forecasting performance, the European Centre for Medium-Range Weather Forecasts (ECMWF) model. We find that both MLR and ML improve the MJO prediction and that ML outperforms MLR. The largest improvement is in the prediction of the MJO geographical location and intensity.

Subseasonal reversal of haze pollution over the North China Plain

China has been frequently suffering from haze pollution in the past several decades. As one of the most emission-intensive regions, the North China Plain (NCP) features severe haze pollution with multiscale variations. Using more than 30 years of visibility measurements and PM2.5 observations, a subseasonal seesaw phenomenon of haze in autumn and early winter over the NCP is revealed in this study. It is found that when September and October are less (more) polluted than the climatology, haze tends to be enhanced (reduced) in November and December. The abrupt turn of anomalous haze is found to be associated with the circulation reversal of regional and large-scale atmospheric circulations. Months with poor air quality exhibit higher relative humidity, lower boundary layer height, lower near-surface wind speed, and southerly anomalies of low-level winds, which are all unfavorable for the vertical and horizontal dispersion and transport of air pollutants, thus leading to enhanced haze pollution over the NCP region on the subseasonal scale. Further exploration indicates that the reversal of circulation patterns is closely connected to the propagation of midlatitude wave trains active on the subseasonal time scale, which is plausibly associated with the East Atlantic/West Russia teleconnection synchronizing with the transition of the North Atlantic SST. The seesaw relation discussed in this paper provides greater insight into the prediction of the multiscale variability of haze, as well as the possibility of efficient short-term mitigation of haze to meet annual air quality targets in North China.摘要中国近几十年来频受雾霾污染问题困扰, 其中华北平原作为排放最密集的区域之一, 常遭遇不同尺度的严重雾霾污染. 本文利用30余年的能见度和颗粒物 (PM2.5) 观测数据, 发现了华北平原地区在秋季和早冬时雾霾污染在次季节尺度上“跷跷板式”反向变化的关系. 研究发现, 当9–10月污染较轻 (重) 时, 11–12月的污染倾向于加重 (减轻) . 这种突然的变化与局地和大尺度环流的反向变化有关. 污染较重的月份常伴随有更高的相对湿度, 更低的边界层高度和近地面风速以及低层的南风异常, 均不利于污染的垂直和水平扩散和传输, 从而导致了次季节尺度上霾污染的加重. 进一步的研究发现环流场的突然转向与在次季节尺度上活跃的中纬度波列的传播密切相关, 而此波列可能主要与大西洋海温转变及引起的EA/WR遥相关型有关. 这一次季节反向变化为霾污染多尺度变率预测提供了新的理解, 同时为华北地区年度空气质量达标的短期目标提供了具有可行性的参考方法.

Machine Learning Model-Based Ice Cover Forecasting for a Vital Waterway in Large Lakes

The St. Marys River is a key waterway that supports the navigation activities in the Laurentian Great Lakes. However, high year-to-year fluctuations in ice conditions pose a challenge to decision making with respect to safe and effective navigation, lock operations, and ice breaking operations. The capability to forecast the ice conditions for the river system can greatly aid such decision making. Small-scale features and complex physics in the river system are difficult to capture by process-based numerical models that are often used for lake-wide applications. In this study, two supervised machine learning methods, the Long Short-Term Memory (LSTM) model and the Extreme Gradient Boost (XGBoost) algorithm are applied to predict the ice coverage on the St. Marys River for short-term (7-day) and sub-seasonal (30-day) time scales. Both models are trained using 25 years of meteorological data and select climate indices. Both models outperform the baseline forecast in the short-term applications, but the models underperform the baseline forecast in the sub-seasonal applications. The model accuracies are high in the stable season, while they are lower in the freezing and melting periods when ice conditions can change rapidly. The errors of the predicted ice-on/ice-off date lie within 2–5 days.

The Impact of Mean-State Moisture Biases on MJO Skill in the Navy ESPC

Abstract The Madden–Julian oscillation (MJO) is a key source of predictability in the subseasonal time scale (weeks to months) and influences a wide range of weather and climate phenomena. Although there have been enormous gains in simulating the MJO, many climate and forecast models still have biases in MJO behavior and structure. In this study, we examine the MJO in the Navy Earth System Prediction Capability (Navy ESPC) forecasts performed for the Subseasonal Experiment (SubX) using process-based diagnostics and a moisture budget analysis that uses wavenumber–frequency filtering to isolate the MJO. The MJO in the Navy ESPC is too strong in both boreal winter and summer. This amplitude bias is driven by biases in the vertical moisture advection in the Navy ESPC, which is too strong and deep, driven by a more bottom-heavy vertical motion profile and too steep lower-tropospheric vertical moisture gradient. Additionally, the convective moisture adjustment time scale in the Navy ESPC is faster than observed, such that for a given moisture anomaly the precipitation response is greater than observed. In the Navy ESPC, the MJO propagation shows strong agreement with observations in the Indian Ocean, followed by too rapid propagation east of the Maritime Continent in both seasons. This MJO acceleration east of the Maritime Continent is linked to an acceleration of moisture anomalies driven by biases in anomalous moisture tendency. The mechanisms that drive this bias have seasonal differences, with excess evaporation in the western Pacific dominating in boreal winter and horizontal moisture advection dominating in boreal summer.

Assessing the importance of mesoscale sea‐surface temperature variations for surface turbulent cooling of the Kuroshio Extension in wintertime

Western boundary currents are well known to exhibit a strong eddy field and meandering on subseasonal timescales and wavelengths of a few hundreds of kilometers. However, the extent to which the ocean mesoscale activity associated with these motions can enhance the turbulent air–sea heat flux averaged over a large spatial domain has not been fully characterized. This study aims to do so during the cold season using reanalysis data and simplified air–sea interaction models. The correlation between sea-surface height anomaly and the wintertime mean heat fluxes does not indicate any significant relations between eddy activity and large-scale surface heat flux in the Kuroshio Extension during winter over the 2003–2018 period. The results from simple models designed to isolate the contributions from the eddies suggest that the eddy enhancement of the heat flux via a rectified effect (a bit more anomalous cooling over a warm mesoscale feature than anomalous heating over a cold one) is small compared with the long-time, large-spatial scale mean in the reanalysis data, especially along the Kuroshio Extension. It is found larger north of it, where it can reach 5 W · $$ \cdotp $$ m − 2 $$ {}^{-2} $$ . Although different datasets might disagree about the level of energy of the sea-surface temperature field at the mesoscale, a simple scaling analysis gives confidence in the relatively small values of the rectified effect found here.

The 1–31-Day Predictions of the South China Sea Summer Monsoon in the CAMS-CSM Climate Forecast System

The South China Sea summer monsoon (SCSSM) is crucial for the East Asian monsoon system, which has been detected from plenty of aspects, while its prediction has been relatively less investigated on the subseasonal timescale. The 1–31-day predictions of SCSSM, including fundamental dynamic and thermodynamic characteristics, indices, onset date and associated circulations, are examined and diagnosed for different climate systems, i.e., T106 and T106 × T255 (with a nudging process added) in the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). The results indicate the general decreasing prediction skills of the model with the growing lead times. For lead times of 1–10 days, zonal winds at the lower (850 hPa) and higher (200 hPa) levels can be reasonably predicted, as well as the pseudo-equivalent potential temperatures at 850 hPa. Meanwhile, the prediction skill for the higher level generally shows a better performance than that for the lower level. The prediction capability is relatively weak during the circulation adjustment period before the monsoon onset, while a significant enhancement occurs after that. During the analyzed period of 2011–2020, the prediction of SCSSM onset date is mainly skillful in most years, while the year of 2015 shows a prediction result with at least six pentads earlier than the observation, which is subsequently taken as a failure case for further investigation. At the lower level, the model could not effectively predict the weakening and eastward withdrawal of the Western Pacific subtropical high and the shift in wind field during the SCSSM onset. As for the upper level, the rapid northward movement of the South Asia high and its establishment in the Indochina Peninsula are neither well captured. In addition, the models of T106 and T106 × T255 do not show significant differences in most cases, but the latter tends to be more skillful on the continent.

Combining precipitation forecasts and vegetation health to predict fire risk at subseasonal timescale in the Amazon

Current forecast systems provide reliable deterministic forecasts at the scale of weather (1–7 days) and probabilistic outcomes at the scale of seasons (1–9 months). Only in recent years research has begun transitioning to operational settings to provide numerical predictions for a lead time of 2–4 weeks, a timescale known as subseasonal. The Subseasonal Experiment (SubX) multi-model ensemble mean precipitation forecast (2017–2021) for days 8–14 (week-2 forecast) is used as a covariate in logistic regression models to predict fire risk in the Amazon. In a complementary experiment, a vegetation health index (VHI) is added to SubX precipitation forecasts as a predictor of fires. We find that fire risk can be skillfully assessed in most of the Amazon where fires occur regularly. In some sectors, SubX week-2 precipitation alone is a reliable predictor of fire risk, but the addition of VHI as a predictor results both in (a) a larger portion of the Amazon domain with skillful forecasts and; (b) higher skill in some sectors. By comparing two sectors of the Amazon, we find that the added information provided by VHI is most relevant where the mosaic of land covers includes savannas and grassland, whereas SubX precipitation can be used as the sole predictor for week-2 fire risk forecast in areas where the mosaic of land cover is dominated by forests. Our results illustrate the potential for using numerical model forecasts, at the subseasonal timescale, in combination with satellite remote sensing of vegetation to obtain skillful fire risk forecasts in the Amazon. The operationalization of the methods presented in this study could allow for better preparedness and fire risk reduction in the Amazon with a lead time greater than a week.

Turbulent Heat Flux, Downward Longwave Radiation, and Large-Scale Atmospheric Circulation Associated with Wintertime Barents–Kara Sea Extreme Sea Ice Loss Events

AbstractWe investigate wintertime extreme sea ice loss events on synoptic to subseasonal time scales over the Barents–Kara Sea, where the largest sea ice variability is located. Consistent with previous studies, extreme sea ice loss events are associated with moisture intrusions over the Barents–Kara Sea, which are driven by the large-scale atmospheric circulation. In addition to the role of downward longwave radiation associated with moisture intrusions, which is emphasized by previous studies, our analysis shows that strong turbulent heat fluxes are associated with extreme sea ice melting events, with both turbulent sensible and latent heat fluxes contributing, although turbulent sensible heat fluxes dominate. Our analysis also shows that these events are connected to tropical convective anomalies. A dipole pattern of convective anomalies with enhanced convection over the Maritime Continent and suppressed convection over the central to eastern Pacific is consistently detected about 6–10 days prior to extreme sea ice loss events. This pattern is associated with either the Madden–Julian oscillation (MJO) or El Niño–Southern Oscillation (ENSO). Composites show that extreme sea ice loss events are connected to tropical convection via Rossby wave propagation in the midlatitudes. However, tropical convective anomalies alone are not sufficient to trigger extreme sea ice loss events, suggesting that extratropical variability likely modulates the connection between tropical convection and extreme sea ice loss events.

Retrospective sub-seasonal forecasts of extreme precipitation events in the Arabian Peninsula using convective-permitting modeling

This work demonstrates the potential of extreme cool-season precipitation forecasts in the Arabian Peninsula (AP) at sub-seasonal time scales, identifies regions and periods of forecast opportunity, and investigates the predictability of synoptic-scale forcing at sub-seasonal time scales. To this end, we simulate 18 extreme precipitation events using the convective-permitting Weather Research and Forecasting (CP-WRF) model with lateral boundary forcing from the European Centre of Medium-range Weather Forecasts sub-seasonal to seasonal reforecasts (ECMWF S2S reforecasts). The simulations are initiated at one-, two-, and three-week lead times. At all lead times, the CP-WRF improves the mean accumulated precipitation in the extratropical synoptic regimes over the west coastal and central AP and the central Red Sea compared to ECMWF S2S reforecasts as evaluated against the Global Precipitation Measurement Final (GPMF) and King Abdullah University of Science and Technology reanalysis (KAUST-RA) precipitation products. Based on categorical statistics with a threshold of 20 mm accumulated precipitation over 7 days, the CP-WRF skillfully forecasts the precipitation over Jeddah, the west coast of AP, and the central Red Sea up to three-week lead time. The relative operating characteristic curve reconfirmed the high forecast skill of the CP-WRF, with an area under the curve above 0.5 in most of the events at all lead times. Finally, the correlation coefficients between the ECMWF S2S reforecast and ECMWF reanalysis interim 500 hPa geopotential heights are higher in the events associated with an extratropical synoptic regime than in those associated with a tropical synoptic regime, regardless of lead time. Therefore, the convective-permitting model can potentially improve the accuracy of extreme winter precipitation forecasts at two-and three-week lead times over Jeddah, the west coast of AP, and the central Red Sea in the extratropical synoptic regime.