Empirical Orthogonal Function Mode Research Articles

Investigation of the Historical Trends and Variability of Rainfall Patterns during the March–May Season in Rwanda

This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen’s slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda’s critical MAM season.

Atmospheric teleconnections responsible for the dominant patterns of interannual variability in summer drought over northern Asia

Abstract Summer drought over northern Asia (NA) seriously threatens the local fragile ecological environment and social economy development. In this study, using the standardized precipitation evapotranspiration index (SPEI), we firstly identify the dominant modes of interannual variability in summer drought condition over NA, and then explore the atmospheric patterns responsible for the formation of the modes. The results show that the first empirical orthogonal function mode (EOF1) of summer SPEI over NA exhibits a meridional dipole pattern, which is influenced primarily by the Polar–Eurasian teleconnection (POL) and Circumglobal teleconnection (CGT) patterns. Under the influence of negative POL and positive CGT patterns, there is an anomalous anticyclone (cyclone) over northwestern Siberia (Lake Baikal to Northeast China). Such atmospheric circulations lead to meridional dipole patterns in air temperature, moisture condition, vertical motion, and cloud cover over NA, favoring decreased (increased) precipitation and increased (decreased) potential evapotranspiration over northern (southern) NA, finally contributing to the formation of EOF1. The EOF2 shows an approximate zonal dipole pattern, which is influenced by the British-Baikal Corridor (BBC) and Scandinavia teleconnection (SCA) patterns. The positive BBC and SCA patterns can lead to an anomalous anticyclone over the Ural Mountains and cyclone over the Lake Baikal. Such atmospheric circulations result in a zonal dipole pattern in precipitation and potential evapotranspiration over NA through changing the local moisture condition, air temperature, and radiation, consequently favoring the formation of EOF2. Fitting analysis indicates that the aforementioned atmospheric factors can explain 76% (55%) of the interannual variability of EOF1 (EOF2).

Trend and interannual variability of summer marine heatwaves in the tropical Indian ocean: Patterns, mixed layer heat budget, and seasonal prediction

Marine heatwaves (MHWs) are extreme sea surface temperature (SST) events in all ocean basins, with far-reaching impacts on marine ecosystems and socio-economy. The leading patterns, trend, and interannual variability of summer MHWs in the tropical Indian Ocean (TIO) are investigated in this study. The first empirical orthogonal function (EOF) mode of frequency of MHWs exhibits a monopole pattern over the entire basin. This mode is highly associated with the concurrent Indian Ocean Basin warming, indicating a remarkable trend over the past four decades. The linear trend in MHW properties largely relates to increased summer Indian Ocean mean SST. The second EOF mode exhibits a zonal dipole with the MHW numbers increasing in the west and decreasing in the east. On the interannual timescale, the first two EOF modes are remotely affected by antecedent and concurrent El Niño events, respectively. The ocean mixed layer budget is utilized for examining the formation of different summer MHW patterns. During the preceding spring, the surface heat flux is important for the development of MHWs, while the ocean advections play a secondary role in the South Indian Ocean for the MHW monopole. Once the SST anomaly rises in summer, the ocean advections play a dominant role in maintaining the SST. Last, we assess the prediction skill of summer TIO MHWs by performing a bilinear seasonal statistical prediction model. Our results suggest the frequency of summer MHWs in the TIO could be predicted one season in advance. This study has great implications for understanding and predicting ocean extreme events in the TIO.

Characteristics of the East Asian Summer Monsoon Using GK2A Satellite Data

In East Asia, where concentrated summer precipitation often leads to climate disasters, understanding the factors that cause such extreme rainfall is crucial for effective forecasting and preparedness. The western North Pacific subtropical high (WNPSH) is a key driver of summer precipitation variability, and therefore, its monitoring is critical to predicting the wet or dry periods during the East Asian summer monsoon. Using the Geo-KOMPSAT 2A (GK2A) satellite cloud amount data and ERA5 reanalysis data during the years 2020–2023, this study identified three leading empirical orthogonal function (EOF) modes and investigated the associated WNPSH variability at synoptic and subseasonal scales. The analysis includes a linear regression of meteorological fields onto the principal component (PC) time series. All three modes play a role in the spatiotemporal variability of the WNPSH, exhibiting lead–lag relationships. In particular, the second mode is responsible for its northwestward shift and intensification. As the WNPSH moves northwestward, the position of the monsoon rain band also shifts, and its intensity is modulated mainly by the moisture transport along the WNPSH boundary. Our results highlight the potential of high-resolution, real-time data from the GK2A satellite to elucidate WNPSH variability and its impact on the East Asian summer monsoon. By addressing the variability of the WNSPH using GK2A data, we pave the way for the development of a real-time monitoring framework with GK2A, which will improve our predictability and readiness for extreme weather events in East Asia.

Observations of anomalously strong mode-2 internal solitary waves in the central Andaman sea by a mooring system

During the period from July 2016 to July 2018, a mooring system deployed in the central Andaman Sea recorded a significant number of highly intense mode-2 internal solitary waves (ISWs), with wave-induced current strengths comparable to those of local mode-1 ISWs. Distinct propagation characteristics and seasonal variations are uncovered, with mode-2 ISWs being identified as primarily propagating eastward and exhibiting a notable frequency peak from November to March. A significant correlation is established between the occurrence of mode-2 ISWs and higher-mode internal tides (ITs), particularly characterized by a high correlation with the third Empirical Orthogonal Function (EOF) mode. Combined with satellite remote sensing images, it is further confirmed that mode-2 ISWs are generated by the nonlinear steepening of ITs and propagate over long distances through resonance with higher-mode ITs. In contrast, our findings suggest that mode-1 ISWs are predominantly generated by the Lee-wave mechanism, especially south of the Ten Degree Channel, and typically propagate northeastward. This study underscores the complex interplay of ocean stratification and seabed topography in the genesis and propagation of ISWs.

The impact of interactions between various systems caused by three consecutive years of La Nina events on the abnormal summer high temperatures in China in 2022

In the summer of 2022, like in many other regions of the world, an unprecedented period of continuous high-temperature weather occurred in eastern China. The degree and duration of this event far exceeded normal standards. Between 2020 and 2022, the tropical Pacific experienced the most significant three-year consecutive La Nina event recorded in recent decades. We investigate linkages between these events: the high-temperature response in eastern China and Asia under the background of such La Nina events. Development of summer La Nina events contributed to a high-temperature heat wave during the summer of 2022. Rapid development of these events in the third year exacerbated negative Indian Ocean Dipole phases because of energy accumulation from abnormal easterly winds. The combined effects of the negative Indian Ocean Dipole phase and La Nina provided background field support that strengthened the West Pacific Subtropical High (WPSH) and the Iranian High, leading to high terrestrial temperature anomalies. An empirical orthogonal function (EOF) analysis of the vertical velocity in the middle and low latitudes of the tropical Indian Ocean and the Asian continent reveals the first two empirical orthogonal function modes to be conducive to the strengthening of Walker circulation in 2022. These two main modes jointly reflect the rising movement of the equatorial East Indian Ocean and South China Sea in 2022, and the sinking movement to the west of the Tibet Plateau and eastern China, which was conducive to generating high temperatures in eastern China. Finally, the South Asian High was affected by the La Nina event that lasted for three years, showing a strong trend towards the north, thus making an important contribution to this high temperature.

Relationship between the Uncertainty of Empirical Orthogonal Function (EOF) Modes and Sampling Sizes in Climate Models

Abstract This study investigates the relationship between the uncertainty of empirical orthogonal function (EOF) modes and sampling size in climate models, using simulated results of preindustrial control (piControl) experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6), and taking the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) as examples. The results indicate that this relationship can be quantified by a concise fitting function [i.e., y = a/(x − b)]. Here, y is the 5%–95% confidence interval of congruence coefficient, x is the sampling size, and a and b are two parameters depending on models or observations. As compared with b, which modulates the sampling size in the fitting function, the parameter a scales the sampling size and thus plays a much more important role. Further analysis indicates that the parameter a, or the uncertainty of EOF1 mode, decreases dramatically with the increase of the difference between variance fractions of EOF1 and EOF2 modes, approximately in the form of a power function. The minimum sampling size to ensure a reliable EOF mode can also be estimated by the fitting function and shows a great diversity among models both for the NAO and ENSO. The diversity suggests the importance of estimating the minimum sampling size before model evaluations on climate variability modes and projections on the future change in modes, particularly when the EOF2 mode explains the variance close to EOF1 mode. Significance Statement Empirical orthogonal function (EOF) analysis, principal component analysis, or eigenvector analysis has been widely used in various research fields. However, it remains as an open question as to how large the sampling size is required to be to obtain reliable modes through the EOF method. In this study, we investigate the relationship between the uncertainty of EOF results and sampling size in current climate models, using adequately long simulated data, and we find that this relationship can be depicted by the fitting function y = a/(x − b). Here, y represents the uncertainty, x is the sampling size, and a and b are parameters. The parameter a is closely related to the difference between variance fractions of first and second EOF modes and plays a more important role in the fitting function. The minimum sampling sizes that are required to obtain reliable EOF modes can also be estimated by the fitting function and vary greatly from model to model. The results provide a basis for judging the reliability of EOF modes, particularly when the first and second EOF modes explain similar variance fractions.

A comparison of ionospheric TEC between the South Atlantic anomaly region and the Indian Ocean region based on TIEGCM simulations in 2002

Using the Thermosphere-Ionosphere-Electrodynamic General Circulation Model (TIEGCM), a comparison of the ionospheric total electron content (TEC) between the South Atlantic anomaly (SAA) and the Indian Ocean (IO) at solar maximum is performed in this study. The results show that the average total electron content in the SAA is greater than that in the Indian Ocean in general. In order to further analyze the difference between the two regions, the empirical orthogonal function (EOF) are used to investigate the temporal and spatial characteristics of TEC. The empirical orthogonal function method separate part of the global four-peak structure (an equatorial ionization anomaly structure, distributed in Southeast Asia, South America, Africa, and central Pacific) and spatial variations in both regions. Moreover, the first mode of EOF shows the different distribution of Equatorial ionization anomaly in South America and central Pacific caused by deviation of geomagnetic field and tides between two regions, and the enhancement of TEC in SAA region at dusk is emphasized, but the enhancement of TEC in IO region at dawn is emphasized. The second mode performs the distribution of EIA in Africa related to solar radiation and E×B drift. The third mode indicates the similar spatiotemporal variations from the geomagnetic field. Besides, the correlation between TEC and Dst in two regions indicate that there are some deficiencies in simulation to the specificity of SAA, and the deficiencies are likely caused by the model’s inaccurate simulation of the magnetic field and particle deposition in the SAA region.

Dynamical Constraint on Precipitation Biases Over the Indo‐Pacific Region During Boreal Summer in AMIP6 Models

AbstractClimate models suffer from longstanding precipitation biases, much of which has been attributed to their atmospheric component owing to unrealistic parameterizations. Here we investigate precipitation biases in 37 Atmospheric Model Intercomparison Project Phase 6 (AMIP6) models, focusing on the Indo‐Pacific region during boreal summer. These models remain plagued by considerable precipitation biases, especially over regions of strong precipitation. In particular, 22 models overestimate the Asian‐Pacific monsoon precipitation, while 28 models underestimate the southern Indian Ocean Intertropical Convergence Zone precipitation. The inter‐model spread in summer precipitation is decomposed into Empirical Orthogonal Functions (EOFs). The leading EOF mode features an anomalous anticyclone circulation spanning the Indo‐northwest Pacific oceans, which we show is energized by barotropic conversion from the confluence of the background monsoonal westerlies and trade‐wind easterlies. Our results suggest precipitation biases in atmospheric models, though caused by unrealistic parameterizations, are organized by dynamical feedbacks of the mean flow.

Effective Deep Learning Seasonal Prediction Model for Summer Drought Over China

AbstractDrought is an important meteorological event in China and can cause severe damage to both livelihoods and socio‐ecological systems, but current seasonal prediction skill for drought is far from successful. This study used convolutional neural network (CNN) to build an effective seasonal forecast model for the summer consecutive dry days (CDD) over China. The principal components (PC) of the six leading empirical orthogonal function modes of CDD anomaly were predicted by CNN, using the previous winter precipitation, 2‐m temperature and 500 hPa geopotential height as predictors. These predicted PCs were then projected onto the observed spatial patterns to obtain the final predicted summer CDD anomaly over China. In the independent hindcast period of 2007–2018, the interannual variabilities of first six PCs were significantly predicted by CNN. The spatial patterns of CDD were then skillfully predicted with anomaly correlation coefficient skills generally higher than 0.2. The interannual variability of summer CDD over the middle and lower Yangtze River valley, northwestern China and northern China were significant predicted by our CNN model three months in advance. CNN identified that the previous winter precipitation was the important predictor for PC1–PC3, whereas the previous winter 2‐m temperature and 500 hPa geopotential height were important for the prediction of PC4–PC6. This research provides a new and effective method for the seasonal prediction of summer drought.

Acoustic tomographic inversion of 3D temperature fields with mesoscale anomaly in the South China Sea

Acoustic tomographic inversion is based on travel times measured along the transmission paths between all station pairs to reconstruct three-dimensional temperature structures with mesoscale anomalies. In this study, tomographic simulation experiments were designed based on the Hybrid Coordinate Ocean Model (HYCOM) reanalysis data to reconstruct mesoscale phenomena from travel time data obtained from five, seven, and nine stations in the South China Sea over a domain of 100 × 100 km. The travel times for each station pair were calculated in the vertical section using the Bellhop acoustic ray simulation method. Six Empirical orthogonal function (EOF) modes of sound speed along the sound transmission paths in a vertical slice were used to formulate the inversion equations. The horizontal-slice distributions of temperature in the tomography domain were reconstructed using the grid-segmented method for each depth layer. For station-to-station distances greater than 100 km, the performance of inversion was best for the seven-station case rather than for the nine-station case, with the highest horizontal resolution of the three cases. This case study concluded that the seven-station case rather than the nine-station case provided an optimal station number for reconstructing the three-dimensional temperature fields.

Characterizing variability of spatial patterns of annual and seasonal precipitation of Turkey and identifying the probable driving factors including teleconnection patterns

Abstract This study aimed to identify primary modes of annual and seasonal precipitation in Turkey using a rotated Empirical Orthogonal Function (EOF) method, and the resulting patterns were described concerning the prevalent atmospheric circulations, orography, and continentality. The varimax rotation of the EOF determines modes that are more localized in space than the conventional EOF modes The first three EOFs accounted for approximately 67% and 62% of the total variance in the annual and wet season precipitation series, respectively, whereas only 50% of the variance was captured by the first three EOFs for dry season precipitation. Spatially different atmospheric circulation mechanisms are major drivers of variability in Turkish precipitation on annual and seasonal timescales. The spatial coherence of the highest negative and positive EOF1 loadings of the annual data was observed in the western and southern regions where westerly and northwesterly circulations prevailed during the wet season. A lower spatial coherency was observed with the dry season precipitation. The contribution of atmospheric moisture advection to precipitation variability diminishes in summer, whereas that of local land surface processes increases. Some regional teleconnection patterns, such as the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO), also contributed to the annual variability in precipitation.

Different Configurations of Cross-Equatorial Flows over the Indian Ocean–Western Maritime Continent and Their Implications for Improving Regional Climate Predictability

Abstract Low-level cross-equatorial flows (CEFs) over the Indian Ocean–western Maritime Continent (IO-wMC) play a crucial role in transporting energy, mass, and water vapor into the Northern Hemisphere during the Asian summer monsoon season (May–September). Utilizing ECMWF reanalysis data (ERA5), we investigate three CEFs over the IO-wMC: the Somali-CEF, Bay of Bengal CEF (BoB-CEF), and South China Sea CEF (SCS-CEF). The statistical independence of the Somali-CEF and BoB-CEF implies distinct formation processes on the interannual time scale. To examine the interannual variability of CEFs, we perform an empirical orthogonal function (EOF) analysis of vertically integrated meridional winds from surface pressure to 850 hPa over the equatorial IO-wMC. The first EOF mode reveals a weakening of the Somali-CEF and strengthening of the BoB-CEF and SCS-CEF, which is associated with the concurrent summer Indian Ocean dipole and quasi-biennial phase transition of El Niño events. The second EOF is related to the Indo-western Pacific Ocean capacitor (IPOC) mode that often emerges in post–El Niño summers. Despite the IPOC’s influence on meridional winds over the tropical southwestern Indian Ocean, three CEFs are uncorrelated with the EOF2. On the other hand, the Somali-CEF and BoB-CEF are significantly weakened in the EOF3. The EOF3 is an ENSO-unrelated internal IPOC mode. We further use a multilinear regression model based on preceding sea surface temperature (SST) over the Indo-Pacific and EOF3 to predict regional climate anomalies and compare the prediction skill with the SST-based models. Our results suggest that adding EOF2- and EOF3-related variability to the prediction model can improve Asian summer monsoon predictability. Significance Statement This study examines the interannual variability of low-level cross-equatorial flows (CEFs) over the Indian Ocean and western Maritime Continent, crucial components of the Asian summer monsoon. We identify three CEFs and investigate their relationships with interannual sea surface temperature modes in the Indo-Pacific region. The leading empirical orthogonal function (EOF) modes of equatorial meridional wind reveal diverse CEF configurations and post–El Niño summer wind variability. Also, the EOFs distinguishes between El Niño and El Niño–unrelated equatorial meridional wind variability. Utilizing a multilinear regression model based on both preceding Indo-Pacific SST modes and configurations of CEFs, we demonstrate the potential to enhance regional climate predictions, contributing to a more comprehensive understanding and forecasting of the Asian summer monsoon and its associated climate impacts.

Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multi-decadal trend in the Warm Arctic Cold Eurasia pattern

The observed winter Barents-Kara Sea (BKS) sea ice concentration (SIC) has shown a close association with the second empirical orthogonal function (EOF) mode of Eurasian winter surface air temperature (SAT) variability, known as Warm Arctic Cold Eurasia (WACE) pattern. However, the potential role of BKS SIC on this WACE pattern of variability and on its long-term trend remains elusive. Here, we show that from 1979 to 2022, the winter BKS SIC and WACE association is most prominent and statistically significant for the variability at the sub-decadal time scale for 5–6 years. We also show the critical role of the multi-decadal trend in the principal component of the WACE mode of variability for explaining the overall Eurasian winter temperature trend over the same period. Furthermore, a large multi-model ensemble of atmosphere-only experiments from 1979 to 2014, with and without the observed Arctic SIC forcing, suggests that the BKS SIC variations induce this observed sub-decadal variability and the multi-decadal trend in the WACE. Additionally, we analyse the model simulated first or the leading EOF mode of Eurasian winter SAT variability, which in observations, closely relates to the Arctic Oscillation (AO). We find a weaker association of this mode to AO and a statistically significant positive trend in our ensemble simulation, opposite to that found in observation. This contrasting nature reflects excessive hemispheric warming in the models, partly contributed by the modelled Arctic Sea ice loss.

Comparison of ocean deoxygenation between CMIP models and an observational dataset in the North Pacific from 1958 to 2005

This study investigated the relationship between the observed and simulated dissolved oxygen (O2) inventory changes in the North Pacific by analyzing an observational dataset and the outputs of Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5/6) between 1958 and 2005. A total of 204 ensembles from 20 models were analyzed. Many of the models in the North Pacific subarctic region have higher climatological O2 concentrations than observed at deeper water depths. Therefore, the negative trend of O2 inventories tends to be larger, and in fact, several model ensemble members have a larger negative trend in O2 inventories than observed. The variability among model ensemble members is more influenced by the uncertainty due to internal variability than by the uncertainty resulting from model dependency. An inter-model empirical orthogonal function (EOF) analysis revealed that the different simulated magnitudes of the negative O2 trend is closely associated with the first EOF mode, and ensemble members with strong negative trends are characterized by large oxygen reduction in the subarctic North Pacific, especially around the boundaries between the North Pacific Ocean and the Sea of Okhotsk as well as the Bering Seas. The modeled strong O2 decrease in the subarctic North Pacific is consistent with the spatial pattern of the observed O2 trend. Further analysis of climate models indicated that the O2 decrease in the subarctic region was primarily caused by physical factors. This conclusion is supported by the significantly high correlation is present between the potential temperature and O2 inventory trend in the subarctic region, whereas an insignificant correlation coefficient is present between dissolved organic carbon and the O2 inventory trend. However, the observations have a larger ratio of O2 inventory trend to temperature trend than any of the ensembles, and thus the relationship between O2 and temperature change in the subarctic North Pacific seen in the CMIP5/6 simulations is not exact.

The Leading Modes of Northern Eurasian Winter Snowfall Variability and the Potential Influencing Factors

Abstract This study investigates the dominant modes of the interannual variability of the northern Eurasian winter snowfall during 1982–2020 and explores their potential influencing factors and the associated physical processes. The first and second empirical orthogonal function (EOF) modes feature coherent snowfall anomalies over the high latitudes of Eurasia and western Siberia, respectively. Further analyses indicate that the anomalous atmospheric circulations play a major role in forming the snowfall variability, which could be further attributed to the influences of the atmospheric teleconnection patterns and Arctic sea ice variations. Specifically, the anomalous circulations related to the first EOF mode are mainly contributed by the effects of the teleconnections of the Polar–Eurasian and Scandinavian patterns. The formation of the second EOF mode has a close connection with the North Atlantic Oscillation and the Eurasian pattern. In addition, the sea ice variations over Baffin Bay exert a considerable influence on the snowfall anomalies related to the second EOF mode by exciting a wave train–like anomalous circulation. This effect is further verified by a numerical simulation. An empirical statistical model based on the above influencing factors can well explain the temporal evolutions of the two dominant modes, verifying the important value of our results to improve the understanding of interannual variability of northern Eurasian winter snowfall.

Dynamics of Spring Snow Cover Variability over Northeast China

Spring snow cover variability over Northeast China (NEC) has a profound influence on the local grain yield and even the food security of the country, but its drivers remain unclear. In the present study, we investigated the spatiotemporal features and the underlying mechanisms of spring snow cover variability over NEC during 1983–2018 based on the satellite-derived snow cover data and atmospheric reanalysis products. The empirical orthogonal function (EOF) analysis showed that the first EOF mode (EOF1) explains about 50% of the total variances and characterizes a coherent snow cover variability pattern over NEC. Further analyses suggested that the formation of the EOF1 mode is jointly affected by the atmospheric internal variability and the sea surface temperature (SST) anomaly at the interannual timescale. Specifically, following a negative phase of the atmospheric teleconnection of the Polar–Eurasian pattern, a prominent cyclonic circulation appears over NEC, which increases the snowfall over the east of NEC by enhancing the water vapor transport and decreases the air temperature through reducing the solar radiation and intensifying the cold advection. As a result, the snow cover has increased over NEC. Additionally, the tripole structure of the North Atlantic spring SST anomaly could excite a wave-train-type anomalous circulation propagating to NEC that further regulates the snow cover variability by altering the atmospheric dynamic and thermodynamic conditions and the resultant air temperature and snowfall. Our results have important implications on the understanding of the spring snow cover anomaly over NEC and the formulation of the local agricultural production plan.

The variability of winter North Atlantic blocking and cold extremes connected to North Atlantic Sea surface temperature modes and ENSO: The mediated role of North Atlantic jet

In this paper, the linkage of the sub-seasonal variability of North Atlantic blocking (NAB) to the interannual-to-decadal winter midlatitude North Atlantic jet (NAJ) is examined. The variability of NAJ in meridional position (strength) is characterized by the first (second) empirical orthogonal function (EOF) mode of the winter-mean 46-days low-pass filtered North Atlantic 500-hPa zonal wind. The composite reveals that NAB exhibits weak (strong) westward movement and small (large) zonal width during the north- (south-) shifted NAJ winters, which result in severe cold anomalies over the southern Europe (northern Eurasia and eastern North America) and are characterized by a precursor of the positive (negative) North Atlantic Oscillation. In contrast, the NAB event during the strong (weak) NAJ winters mainly originates from the intensification of a ridge over North Europe (Atlantic), which has short (long) lifetime, small (large) intensity, small (large) zonal width, and leads to weather influences similar to those during south (north-) shifted NAJ winters. The underlying mechanism of the sub-seasonal variability of NAB can be explained by the nonlinear multi-scale interaction model of atmospheric blocking from the perspective of the meridional potential vorticity gradient.It is further shown that the meridional position of NAJ exhibits significant interannual variability, which is associated with the El Nino/Southern Oscillation (ENSO) via the changes in the Walker Cell and the Atlantic Hadley circulation as well as the second EOF of surface sea temperature (SST) over the North Atlantic. The strength of NAJ shows significant interannual-to-decadal variability, which is mainly regulated by the first EOF mode of North Atlantic SST.

Long-term statistics of atmospheric conditions over the Baltic Sea and meteorological features related to wind wave extremes in the Gulf of Gdańsk

The goal of this study is to describe wind wave climate and wave extremes of the Gulf of Gdańsk in the southern Baltic Sea and associated meteorological conditions over the Baltic Sea. We obtain the characteristic features of 34 severe historical storms in the Gulf of Gdańsk during the period 1958–2001 and link them with extreme significant wave heights hindcast for five grid points in this gulf. The long-term statistics of atmospheric pressure systems over central and northern Europe, and the north-eastern Atlantic Ocean are derived from a 44-year REMO reanalysis database. A link between the mean, minimum and variability range of atmospheric pressure has been quantified. In general, the higher the mean pressure the smaller its variability and vice versa. Long-term characteristic features of winds over the Baltic Sea have been estimated from the REMO database. Strong winds directions vary from W, WSW to SW in the southern Baltic to more southerly SSW directions in the northern part of the Baltic Sea. The Empirical Orthogonal Functions (EOF) analysis shows that more than 50% of the variability in the atmospheric pressure in the Baltic Sea can be explained by the first EOF mode. The first four EOF modes can reproduce above 90% variability of the hindcast pressure time series. Statistical properties of the hindcast significant wave height over the Gulf of Gdańsk are computed based on the 44-year HIPOCAS database. All the computed statistics of wave heights reveal a very strong sheltering effect caused by the Hel Peninsula.

Decadal Change in the Linkage between QBO and the Leading Mode of Southeast China Winter Precipitation

Abstract In this study, observational and model datasets are used to analyze winter precipitation and its leading empirical orthogonal function (EOF1) mode over Southeast China. EOF1 displays a dominant monosign pattern during the last 60 years; however, its major impacting factors have a decadal transition near the mid-1990s. The first principal component (PC1) is related to El Niño–Southern Oscillation (ENSO) after the mid-1990s and to the quasi-biennial oscillation (QBO) before the mid-1990s. An enhanced ENSO–precipitation relationship is associated with stronger ENSO-induced tropical zonal circulation and the westward shift of ENSO-induced SST over the tropical Pacific after the mid-1990s compared to before the mid-1990s. Negative correlation coefficients between QBO and precipitation are evident before the mid-1990s but are no longer statistically significant after the mid-1990s. This change originates from the interaction between QBO’s subtropical influences and the Holton–Tan effect. The QBO’s subtropical influence and the Holton–Tan effect lead to a zonal pressure gradient and meridional wind anomalies over East Asia before the mid-1990s, which further influence the meridional transport of water vapor and precipitation over Southeast China. However, the Holton–Tan effect is enhanced after the mid-1990s. Downward stratospheric polar vortex signals and the QBO’s subtropical influence cause a meridional pressure gradient over East Asia, and thus the relevant moisture flux divergence lacks statistical significance. The above results indicate that the subtropical response to QBO and the Holton–Tan effect should be considered together when using the QBO signal to improve forecasts of winter precipitation over East Asia. Significance Statement Southeast China winter precipitation (SCWP) is often attributed to variation in lower-atmospheric dynamics and sea surface temperature, such as El Niño–Southern Oscillation (ENSO). Few studies focus on the role of the mid- to upper atmosphere. In this study, we diagnose the influence of the stratospheric quasi-biennial oscillation (QBO) on SCWP. Both observational and modeling analyses indicate a strong decadal change in the QBO–SCWP relationship, which limits the use of the QBO in seasonal forecasts of SCWP. This decadal change originates from the strength of the QBO’s modulation of the stratospheric polar vortex. Our results provide a new perspective on the use of the mid- to upper atmosphere in seasonal forecasts of SCWP.