Winter Sea Surface Temperature Research Articles

Dinoflagellate cysts and benthic foraminifera from surface sediments of Svalbard fjords and shelves as paleoenvironmental indicators

Due to the Arctic amplification effect, the Svalbard archipelago is an important area for studying ongoing environmental changes. However, its marine ecosystem is extremely complex. In this study, we analyze modern assemblages of dinoflagellate cysts (dinocysts) and benthic foraminifera from surface sediment samples around Svalbard. We use multivariate statistical analyses to examine relationships between environmental conditions (summer and winter sea surface temperature and salinity, sea-ice cover, etc.) and both microfossil groups to evaluate their use as proxies for reconstructions of the marine environment in the region. Our results show that the most important factor controlling the environment around Svalbard is the Atlantic Water which mostly impacts the western coast, but its influence reaches as far as the eastern coast of Nordaustlandet. However, on a local scale, such factors as the sea-ice cover, the presence of tidewater glaciers, or even the morphology and hydrology of fjords become increasingly important. We found that two dinocyst species, cysts of Polarella glacialis and Echinidinium karaense, can be considered regional winter drift ice indicators. The relationships between environmental parameters and benthic foraminiferal assemblages are much more difficult to interpret. Although statistical analysis shows a correlation of benthic foraminiferal species with various environmental parameters, this correlation might be somewhat coincidental and caused by other factors not analyzed in this study. Nevertheless, the use of two complementary microfossil groups as (paleo)environmental indicators can provide a more comprehensive picture of the environmental conditions.

Enhanced Influence of Tropical Pacific Sea Surface Temperature Anomalies on Spring Extreme Heat Events Over Mid‐High Latitude Eurasia

AbstractThis study presents an interdecadal enhancement in the interannual relationship between spring extreme heat events (EHEs) over mid‐high latitude Eurasia and winter sea surface temperature (SST) over the tropical central‐eastern Pacific (TECP) after the late 1990s. Comparative analyses of the two subperiods before and after the late 1990s show that the interdecadal changes in the winter TECP SST could be responsible for such changeable relationship. After the late 1990s, the winter TECP SST anomalies (SSTA) feature a central Pacific (CP)‐type pattern. The CP‐type SSTA cause an anticyclone anomaly over the North Atlantic through the Pacific‐North American‐like teleconnection, further leading to a dipole SST pattern over the tropical to mid‐latitude North Atlantic. The CP‐type SSTA and North Atlantic dipole SSTA persist well from winter to spring, and the North Atlantic dipole SSTA favor the propagation of the CP‐type SST‐excited Rossby wave train to Eurasia in spring. Therefore, the TCEP SSTA have a significant interannual relationship with the spring Eurasian atmospheric circulations and EHEs after the late 1990s. The above physical processes are further confirmed by the SSTA sensitivity numerical experiments. In contrast, before the late 1990s, the winter TECP SSTA show an eastern Pacific‐type pattern, which is related to weak and insignificant North Atlantic SSTA and spring Eurasian atmospheric circulations; consequently, the TCEP SSTA have a weak relationship with the EHEs variations during this period. The TCEP SSTA with one season leading can provide valuable information for the prediction of spring Eurasian EHEs variations in the recent two decades.

El Niño‐Southern Oscillation Modulation of Springtime Diurnal Rainfall Over a Tropical Indian Ocean Island

AbstractThis study analyzes the interannual variability of boreal springtime (March and April) diurnal rainfall (hereafter SDR) over the second biggest Island of the Indian Ocean, Sri Lanka (SL), and expresses the possible effects of the El Niño Southern Oscillation (ENSO) events in modulating this variability. The analysis is primarily based on high spatiotemporal resolution satellite precipitation estimates and reanalysis data from 2001 to 2019. Results indicate that the SDR in SL exhibited a consistent afternoon peak throughout the study period. In contrast, the SDR's amplitude consists of a notable 2 to 4‐year oscillation period, similar to the oscillation period of ENSO events. Further analysis revealed that the interannual variation of the SDR's amplitude in SL has a negative relationship with the springtime and previous winter sea surface temperature changes in the central and eastern tropical Pacific Ocean covering NINO3.4 and NINO3 regions (referred to as ENSO indices). When there is a winter La Niña (El Niño), the following SDR in SL is more (less) active. A possible explanation is that during La Niña (El Niño) years, the region around SL experienced an enhanced (suppressed) cyclonic circulation, enhanced (suppressed) large‐scale moisture flux convergence, and enhanced (suppressed) local‐scale diurnal varying moisture flux convergence, leading to an increase (decrease) in the potential for rainfall and more (less) active SDR over SL. These findings highlight the potential to use ENSO indices to predict the interannual variation of SDR activities over SL.

Impact of the climate regime shift around 2000 on recruitment of Antarctic krill at the Antarctic Peninsula and South Georgia

We examined how the climate regime shift around 2000 affected Antarctic krill recruitment variability at the North Antarctic Peninsula (NAP) and South Georgia (SG) during the period of 1990s through to 2000s. We used sea surface temperature (SST) as a proxy of the monthly sea ice extent and related it to the recruitment index (proportion of 1-year-old krill) of each succeeding year for NAP and SG by examining the correlation of the time series before and after 2000. For NAP, recruitment index was negatively correlated with winter SST at NAP in the 1990s but with autumn SST in the 2000s, suggesting that good recruitment was supported by extensive winter sea-ice in the 1990s but by extensive autumn sea-ice in the 2000s. This was attributed to the regime shift featured by winter warming and autumn cooling after 2000. For SG, recruitment was negatively correlated with winter SST at NAP in the 1990s but positively correlated with autumn SST in the southern Scotia Sea (SSS) in the 2000s. According to particle tracking experiment from NAP to SG in relation to the sea-ice extent and position of SACCF (Southern Antarctic Circumpolar Current Front), less sea-ice extent in 2000s meant less larvae distributing as north as SACCF, resulting in much fewer larval being transported to SG. Hence, we hypothesized that the regime shift weakened the connection between NAP and SG, but instead SSS became the main driver of recruitment at SG. We presume the krill population demonstrated adaptability to the regime shift by offsetting the unfavorable winter condition with the favorable autumn condition at NAP and for SG, replacing the source of recruits with those closer to it.

Spatiotemporal dynamics and potential restoration of mangroves in Circum-Xinying-Bay region, Hainan Province, China

Mangrove forests play an important role in absorbing carbon, filtering pollution, and protecting coastal residents from storms. However, mangrove forests are most susceptible to human interference and suffer more than one-third of losses globally. Therefore, quantifying their spatial-temporal changes and identifying their potential distributions are necessary for protection, restoration, and management. We first mapped and analysed the spatial-temporal changes in mangrove forests from 1993 to 2021 in the Xinying-Bay region (XYB), Hainan Province, China. Then, we predicted suitable habitats for mangrove forests by using the maximum entropy (MaxEnt) model based on mangrove distribution data for 2021 and related environmental data for the Circum-Xinying-Bay region (CXYB). The results show remarkable changes in mangrove forests in the XYB from 1993 to 2021, with the loss rate reaching 56 ha/y from 1998 to 2002. The MaxEnt model performs well, with the curve (AUC) extending beyond 0.9. Water quality and topography determined the distribution of mangrove forests, with the total contribution exceeding 65%. The six most important influential factors were salinity, DEM, precipitation in the driest quarter, pH, isothermality, and winter sea surface temperature. The area of mangroves highly suitable in the CXYB is approximately 3880 hm2 and is mainly located in the town of Xinzhou, the northeast area of the town of Mutang and the southwest area of the town of E'man. This suggests that areas prioritized for protection should include the northern and western areas of Xinzhou, northeastern areas of Mutang, and northern and western areas of E'man. These findings provide further understanding of mangrove distribution and can guide mangrove restoration and management.

The Role of Coupled North Pacific Atmosphere–Ocean Interactions in Impacts of Tibetan Plateau Snow Anomalies on the Northern Hemisphere Winter Atmospheric Circulation

Abstract Previous studies indicate observed influences of autumn and winter Tibetan Plateau (TP) snow-cover anomalies on the winter Pacific–North American (PNA) teleconnection. This study simulates atmospheric and oceanic responses to persistent autumn–winter TP snow forcing using an atmospheric general circulation model (AGCM) and a coupled atmospheric-oceanic general circulation model (AOGCM), and quantifies the role of atmosphere–ocean interactions over North Pacific in TP snow effects. The AOGCM experiment induces a stronger and more realistic remote PNA response to heavy TP snow anomalies, and also a significant winter horseshoe-like North Pacific sea surface temperature (SST) pattern resulting from an anomalous equivalent barotropic cyclone, or a strengthened Aleutian low, with associated cyclonic wind stress anomalies. The horseshoe-like SST anomaly pattern is used as boundary forcing (without prescribed heavy TP snow) in another AOGCM experiment, which simulates an enhanced winter Aleutian low and a PNA-like response similar to the original AOGCM responses, indicating that that the direct Pacific–North American atmospheric response to persistent TP snow forcing in the AGCM is amplified in the AOGCM by the North Pacific midlatitude atmosphere–ocean interactions. This suggests that the mechanisms of the winter PNA responses to TP snow forcing involve dynamical atmospheric processes such as horizontal propagation of Rossby wave energy and transient eddy feedbacks, and also North Pacific atmosphere–ocean interactions, which provide a positive feedback on the development of the remote PNA teleconnection. Significance Statement The Tibetan Plateau has a 2.5 million km2 area and a 4000 m average elevation, and is often called “the third pole” because of its polar-like climate in midlatitude Eurasia. A heavy Tibetan Plateau snow cover increases the albedo effect and causes tropospheric cold temperature and low height changes that can be carried or advected to the North Pacific by the prevailing westerlies. The purpose of this study is to better understand how Tibetan Plateau snow anomalies influence the North Pacific and the remote atmospheric circulation through numerical simulations. Our results find that those North Pacific responses amply the direct atmospheric response to Tibetan Plateau snow-cover anomalies. This greatly improves our understanding of physical mechanisms of Tibetan Plateau snow impacts.

Forecasting the July Precipitation over the Middle-Lower Reaches of the Yangtze River with a Flexible Statistical Model

The multiple regression method is still an important tool for establishing precipitation forecast models with a lead time of one season. This study developed a flexible statistical forecast model for July precipitation over the middle-lower reaches of the Yangtze River (MLYR) based on the prophase winter sea surface temperature (SST). According to the characteristics of observed samples and related theoretical knowledge, some special treatments (i.e., more flexible and better-targeted methods) were introduced in the forecast model. These special treatments include a flexible MLYR domain definition, the extraction of indicative signals from the SST field, artificial samples, and the amplification of abnormal precipitation. Rolling forecast experiments show that the linear correlation between prediction and observation is around 0.5, more than half of the abnormal precipitation years can be successfully predicted, and there is no contradictory prediction of the abnormal years. These results indicate that the flexible statistical forecast model is valuable in real-life applications. Furthermore, sensitivity experiments show that forecast skills without these special treatments are obviously decreased. This suggests that forecast models can benefit from using statistical methods in a more flexible and better-targeted way.

Hydroclimate seasonality from paired coral Sr/Ca and δ18O records of Kikai Island, Southern Japan: Evidence of East Asian monsoon during mid-to late Holocene

The East Asian Monsoon (EAM) modulates the seasonal variability of sea surface temperature (SST), sea surface salinity (SSS), and rainfall in the region. However, seasonal-scale reconstructions showing the hydroclimate response to monsoon intensity shifts in Holocene are limited. We used paired coral Sr/Ca and oxygen isotope (δ18Ocoral) records from modern (1989–2015), 5.7 ka, 4.9 ka, and 3.2 ka corals from Kikai Island, Southern Japan to reconstruct past seasonal variability of hydroclimatic variables. The monthly δ18Ocoral-SSS relationship revealed a statistically significant positive linear correlation (r = 0.63; p < 0.000; n = 310) while the δ18Osw and rainfall showed a statistically significant negative linear correlation (r = 0.55; p < 0.000; n = 93).The large SST and SSS seasonality in 5.7 ka (ΔSSTmax-min = 9.5 °C; Δδ18Omax-min = 1.86‰) and 4.9 ka (ΔSSTmax-min = 10.2 °C; Δδ18Omax-min = 1.45‰) indicate an enhanced seasonal ocean warming which amplified the Western Pacific Subtropical High (WPSH) and the southwesterlies. In contrast, the small SST amplitude in 3.2 ka (ΔSSTmax-min = 7.8 °C; Δδ18Omax-min = 0.98‰) indicates a weakened WPSH and southwesterlies which led to reduced summer rainfall and positive SSS signal. The lower salinity records due to higher rainfall in 7.0 ka, 6.1 ka, 5.7 ka, and 4.9 ka coincide with the strong East Asian summer monsoon (EASM) from 8.2 to 4.7 ka in stacked sediment records. The δ18Ocoral record shows positive SSS driven by weakened summer monsoon rainfall in 4.4 ka, 4.2 ka, 3.8 ka, 3.4 ka, and 3.2 ka.The higher winter SSS (positive δ18Ocoral) and lower winter SST derived from 5.7 ka coral in Kikai Island agree with the strong East Asian winter monsoon (EAWM) intensity from 8.2 to 5.6 ka based on the stacked sediment record. The weak EAWM phase from 5.6 ka to 4.5 ka is consistent with the winter records of warm SST and lower SSS in 4.9 ka. The lower winter SSS and warmer winter SST in 3.2 ka support the evidence of a weak phase around 3.0 ka. The extratropical systems such as the intensified or weakened Siberian High and Aleutian Low have affected the northeasterly EAWM and consequently influenced the variability of winter SST and SSS in subtropical southern Japan in mid- and late Holocene.

Two distinct population clusters of northern sand lance (Ammodytes dubius) on the northwest Atlantic shelf revealed by whole genome sequencing

AbstractNorthern sand lance (Ammodytes dubius) are essential forage fish in most offshore, temperate-to-polar waters on the Northwest Atlantic shelf (NWA), but their population structure and genetic separation from the American sand lance (A. americanus) remain unresolved. We assembled a reference genome for A. dubius (first in the Ammodytidae) and then used low-coverage whole genome sequencing on 262 specimens collected across the species distribution (Mid-Atlantic Bight to Greenland) to quantify genetic differentiation between geographic regions based on single nucleotide polymorphisms. We found strong separation between A. dubius from locations north and south of the Scotian Shelf, largely due to massive genetic differentiation spanning most of chromosomes 21 and 24. Genetic distance increased with geographic distance in the smaller southern cluster but not in the larger northern cluster, where genetic homogeneity appeared across large geographic distances (&amp;gt;103 km). The two genetic clusters coincide with a clear break in winter sea surface temperature, suggesting that differential offspring survival, rather than limited transport, causes a break in realized connectivity. Nuclear and mitochondrial DNA both clearly delineated A. dubius from A. americanus, thereby confirming a species boundary through spatial niche partitioning into inshore (A. americanus) and offshore (A. dubius) sand lance species on the NWA.

The reemergence of the winter sea surface temperature tripole in the North Atlantic from ocean reanalysis data

The reemergence of the winter sea surface temperature tripole in the North Atlantic from ocean reanalysis data

Projected harmful algal bloom frequency in the Yangtze River Estuary and adjacent waters

Harmful algal blooms (HABs) are a frequent occurrence in China's offshore waters due to climate change and human activity, particularly in the Yangtze River Estuary and adjacent waters. Here, we studied HABs and their relationship with climatic and environmental factors in these waters from 1979 to 2016 using historical observations and reanalysis data. We then projected HABs frequency under various climate scenarios using the “environmental impact factor-frequency of HABs” mathematical model built using the BP neural network method and CIMP5 model data (RCP 2.6, RCP 4.5, and RCP 8.5). The results suggest a significant positive correlation between HABs frequency and seawater nutrient concentration, winter sea surface temperature, and low-wind days, and HABs frequency is anticipated to increase significantly by the 2040s compared with that of the historical era. Furthermore, future phytoplankton conditions are predicted to favor HAB species.

Ocean acidification and seasonal temperature extremes combine to impair the thermal physiology of a sub-Antarctic fish

To predict the potential impacts of climate change on marine organisms, it is critical to understand how multiple stressors constrain the physiology and distribution of species. We evaluated the effects of seasonal changes in seawater temperature and near-future ocean acidification (OA) on organismal and sub-organismal traits associated with the thermal performance of Eleginops maclovinus, a sub-Antarctic notothenioid species with economic importance to sport and artisanal fisheries in southern South America. Juveniles were exposed to mean winter and summer sea surface temperatures (4 and 10 °C) at present-day and near-future pCO2 levels (~500 and 1800 μatm). After a month, the Critical Thermal maximum and minimum (CTmax, CTmin) of fish were measured using the Critical Thermal Methodology and the aerobic scope of fish was measured based on the difference between their maximal and standard rates determined from intermittent flow respirometry. Lipid peroxidation and the antioxidant capacity were also quantified to estimate the oxidative damage potentially caused to gill and liver tissue. Although CTmax and CTmin were higher in individuals acclimated to summer versus winter temperatures, the increase in CTmax was minimal in juveniles exposed to the near-future compared to present-day pCO2 levels (there was a significant interaction between temperature and pCO2 on CTmax). The reduction in the thermal tolerance range under summer temperatures and near-future OA conditions was associated with a reduction in the aerobic scope observed at the elevated pCO2 level. Moreover, an oxidative stress condition was detected in the gill and liver tissues. Thus, chronic exposure to OA and the current summer temperatures pose limits to the thermal performance of juvenile E. maclovinus at the organismal and sub-organismal levels, making this species vulnerable to projected climate-driven warming.

Winter North Atlantic SST as a Precursor of Spring Eurasian Wildfire

AbstractBoreal fires considerably influence carbon release and air quality, but its occurrence mechanisms need to be explored. This study investigated the influence of winter North Atlantic sea surface temperature (SST) on spring Eurasian wildfire using single value decomposition method. Two possible pathways link such time‐lag phenomena. The anomalous SST pattern in winter can persist to spring, resulting in a significant high air‐pressure anomaly over southeastern Siberia, which corresponds to less‐than‐normal precipitation and enhanced aridity conditions and the increasing wildfire risk. Meanwhile, there are simultaneously negative snow cover anomalies over southeastern Siberia during winter which is closely related to the winter SSTs. Such snow anomalies persist from winter to spring, leading to negatively anomalous soil moisture. Both pathways provide a favorable environment for wildfire activities. This study implies that the winter North Atlantic SST could be a robust driver and potential precursor for spring wildfire prediction over southeastern Siberia.

Warm bias of cold sea surface temperatures in the East Sea (Japan Sea)

The East/Japan Sea (ES) is regarded as a natural laboratory for predicting future changes in the global Meridional Overturning Circulation (MOC) under warming climates, as the ES MOC (EMOC) changes rapidly in comparison with the global MOC. Specifically, intermediate and deep-water masses of the ES are formed in its northern reaches via wind-driven subduction of surface water, and convection from the surface to deep layers during the winter. Accordingly, it is important to investigate the variation of winter sea surface temperatures (SSTs) for characterizing and predicting the EMOC; however, global SST products must be corrected and optimized for the ES, as they fail to incorporate the local marginal sea conditions. Here, a warm bias in cold SST was identified for three SST products, such as optimally interpolated sea surface temperatures (OISSTs), microwave SSTs, and operational SST and sea ice analysis products, suggesting the potential usefulness of a correction method incorporating Argo float data. When comparing OISSTs with 5 m temperature estimates from Argo float data during 2000–2020, under the assumption that the mixed layer depth is deeper than 8 m, a nearly normalized histogram of biases was produced, and the robust warm bias (mean = 0.9°C) was detected in the range of relatively cold SSTs (-2°C to 10°C), yet no significant bias in warm SSTs (&amp;gt; 10°C) was found. To minimize the warm bias in cold SSTs, OISSTs were corrected with an inverse 4th-order polynomial fitting method. Subsequently, the mean bias between the corrected SSTs and top depth temperatures of Argo float data was significantly reduced to less than 0.1°C. Moreover, the warm bias of cold SSTs resulted in severe underestimations of the outcropping area colder than 1°C over the northern region, as well as the occurrence period of 1°C to 5°C SSTs in the north-western ES. These results highlight the importance of local bias correction for SST products, and it is expected that the newly suggested correction method will improve model predictions of EMOC change by enhancing SST data quality in the northern ES.

Enhancement of the relationship between spring extreme precipitation over Southwest China and preceding winter sea surface temperature anomalies over the South Indian Ocean after the late 1980s

AbstractSpring extreme precipitation (SEP) significantly disturbs spring ploughing over Southwest China (SWC), bringing challenges for agricultural activities and production over the region. This study investigates the interannual relationship between SWC SEP and sea surface temperature (SST) in preceding winter, from a perspective of prediction. It is found that the dominate mode of SWC SEP interannual variability mainly reflects the variability over the eastern part. The variability of eastern SWC SEP has an enhanced connection with a dipole SST pattern over the South Indian Ocean in preceding winter after the late 1980s. Under the warmer SST background after the late 1980s, the South Indian Ocean dipole SST pattern can lead to significant convection activity over tropical central and western Indian Ocean. The tropical diabatic heating associated with enhanced convection can strengthen the western North Pacific anticyclone, which transports more water vapour to eastern SWC and induces stronger moisture convergence there, providing favourable moisture condition for the SEP occurrence. In addition, the dipole SST pattern can strengthen upward motion over eastern SWC through exiting a meridional circulation, providing a favourable dynamic condition for the SEP occurrence over there. In contrast, under the colder SST background before the late 1980s, the dipole SST pattern‐related convection and atmospheric circulation anomalies are weak over the Indo‐Pacific region. Therefore, the relationship of the dipole SST pattern with SEP over eastern SWC is weak before the late 1980s. The SST signals with one‐season leading could provide valuable source for seasonal prediction of eastern SWC SEP variability after the late 1980s.

Summer Marine Heatwaves in the Kuroshio-Oyashio Extension Region

During 1982–2021, the highest sea surface temperature (SST) variability over the North Pacific was in the Kuroshio-Oyashio Extension (KOE) region, with more intense marine heatwaves (MHWs), especially during summertime. In this study, we explored the evolution and driving factors of the strongest summer MHWs based on their cumulative intensity using satellite observations and reanalyzed model results. Strong summer MHWs in 1999, 2008, 2012, and 2016 were initiated and peaked around summer. The more recent summer MHW events in 2018, 2020, and 2021 appeared to be associated with intermittent MHW events in the previous winter that extended to boreal summer. Based on a mixed layer temperature budget analysis from March to their peaks in summer, MHWs in 1999, 2008, 2012, and 2016 were primarily driven by the air-sea heat flux anomalies, with anomalous shortwave radiation due to reduced cloud cover being the dominant factor. Summer MHWs in 2018, 2020, and 2021 were mainly contributed by the ocean memory of winter warming. The northward shift of the Kuroshio Extension axis, the northward intrusion of the anticyclonic eddies, and the decadal warming trend may contribute to the positive sea surface height anomalies and increased upper ocean heat content in the KOE to increase winter SST and precondition the summer MHWs. Understanding MHW variability and the underlying mechanisms will help manage the marine ecosystem of the KOE region, as well as predict climate change impacts.

Forecasting the June Ridge Line of the Western Pacific Subtropical High with a Machine Learning Method

The ridge line of the western Pacific subtropical high (WPSHRL) plays an important role in determining the shift in the summer rain belt in eastern China. In this study, we developed a forecast system for the June WPSHRL index based on the latest autumn and winter sea surface temperature (SST). Considering the adverse condition created by the small observed sample size, a very simple neural network (NN) model was selected to extract the non-linear relationship between input predictors (SST) and target predictands (WPSHRL) in the forecast system. In addition, some techniques were used to deal with the small sample size, enhance the stabilization of the forecast skills, and analyze the interpretability of the forecast system. The forecast experiments showed that the linear correlation coefficient between the predictions from the forecast system and their corresponding observations was around 0.6, and about three-fifths of the observed abnormal years (the years with an obviously high or low WPSHRL index) were successfully predicted. Furthermore, sensitivity experiments showed that the forecast system is relatively stable in terms of forecast skill. The above results suggest that the forecast system would be valuable in real-life applications.

Diagnosing Two‐Way Coupling in Decadal North Atlantic SST Variability Using Time‐Evolving Self‐Organizing Maps

AbstractDecadal variability in the North Atlantic plays a critical role in modulating regional and global climate. To identify the complex spatiotemporal patterns associated with decadal variability and diagnose mechanisms responsible spatially and over time simultaneously, we debut a novel application of a machine learning method—evolution self‐organizing maps. This time‐evolving framework is applied to a Community Earth System Model pre‐industrial simulation to identify 10‐year consecutive spatiotemporal evolutions of winter sea surface temperature (SST). Here we focus on a single evolution that transitions from SST patterns typically associated with a positive North Atlantic Oscillation (NAO) to a positive Atlantic Multidecadal Variability to a weak negative NAO and find that it can occur over just a 10‐year period. This method facilitates a new examination of buoyancy‐driven and wind‐driven ocean circulations as well as ocean‐atmosphere transient‐eddy feedbacks that confirms the importance of coupled atmosphere‐ocean dynamics in producing this decadal variability.

New downscaling prediction models for spring drought in China

AbstractAccurate prediction of spring drought in China is helpful toward reducing associated agricultural losses. In this study, spring drought is defined as the three‐month Standardized Precipitation Evapotranspiration Index (SPEI) ending in May. Based on the year‐to‐year increment and downscaling method, three single‐predictor prediction models (P1 model, P2 model, and P3 model) and two multi‐predictor models for spring drought at 677 stations in China are developed for the period 1983–2020. As physical processes affecting spring drought in the China region, the tropical Pacific–Indian Ocean sea surface temperature (SST) in winter, the Davis Strait–Barents sea‐ice concentration (SIC) in winter, and the 500‐hPa spring vertical velocity, predicted by the Climate Forecast System, version 2 (CFSv2), are considered in the prediction models. The prediction skill of the downscaling models for the spring SPEI is measured by cross‐validation for the period 1983–2020. The CFSv2 model only shows convincing prediction skill for the spring SPEI at 35 of 677 stations. However, among the 677 stations, the temporal correlation coefficient between the observed and predicted spring SPEI at 621 stations for P1 model, 598 stations for P2 model, 545 stations for P3 model, 674 stations for the statistical downscaling model (SD model), and 675 stations for the hybrid downscaling dynamical–statistical prediction model (HD model) exceeds the 95% confidence level. Therefore, compared to the CFSv2 model, the prediction skill for spring drought is improved by the single‐predictor and multi‐predictor models. The prediction skill of HD model for spring drought, which combines preceding observational predictors and the simultaneous predictor of the CFSv2 model, is higher than that of SD model. In addition, the severe drought that occurred in Northeast and North China in spring 2017 can be successfully predicted by HD model.

Propagation of Thermohaline Anomalies and Their Predictive Potential along the Atlantic Water Pathway

Abstract We assess to what extent seven state-of-the-art dynamical prediction systems can retrospectively predict winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic seas in the period 1970–2005. We focus on the region where warm water flows poleward (i.e., the Atlantic water pathway to the Arctic) and on interannual-to-decadal time scales. Observational studies demonstrate predictability several years in advance in this region, but we find that SST skill is low with significant skill only at a lead time of 1–2 years. To better understand why the prediction systems have predictive skill or lack thereof, we assess the skill of the systems to reproduce a spatiotemporal SST pattern based on observations. The physical mechanism underlying this pattern is a propagation of oceanic anomalies from low to high latitudes along the major currents, the North Atlantic Current and the Norwegian Atlantic Current. We find that the prediction systems have difficulties in reproducing this pattern. To identify whether the misrepresentation is due to incorrect model physics, we assess the respective uninitialized historical simulations. These simulations also tend to misrepresent the spatiotemporal SST pattern, indicating that the physical mechanism is not properly simulated. However, the representation of the pattern is slightly degraded in the predictions compared to historical runs, which could be a result of initialization shocks and forecast drift effects. Ways to enhance predictions could include improved initialization and better simulation of poleward circulation of anomalies. This might require model resolutions in which flow over complex bathymetry and the physics of mesoscale ocean eddies and their interactions with the atmosphere are resolved. Significance Statement In this study, we find that dynamical prediction systems and their respective climate models struggle to realistically represent ocean surface temperature variability in the eastern subpolar North Atlantic and Nordic seas on interannual-to-decadal time scales. In previous studies, ocean advection is proposed as a key mechanism in propagating temperature anomalies along the Atlantic water pathway toward the Arctic Ocean. Our analysis suggests that the predicted temperature anomalies are not properly circulated to the north; this is a result of model errors that seems to be exacerbated by the effect of initialization shocks and forecast drift. Better climate predictions in the study region will thus require improving the initialization step, as well as enhancing process representation in the climate models.