Twentieth Century Reanalysis Version Research Articles

Historical and Future Asymmetry of ENSO Teleconnections with Extremes

Abstract El Niño–Southern Oscillation (ENSO) is the dominant source of climate variability globally. Many of the most devastating impacts of ENSO are felt through extremes. Here, we present and describe a spatially complete global synthesis of extreme temperature and precipitation relationships with ENSO. We also investigate how these relationships evolve under a future warming scenario under high greenhouse gas emissions using 14 models from phase 6 of Coupled Model Intercomparison Project (CMIP6) ensemble. First, we demonstrate that models broadly capture observed ENSO teleconnections to mean and extreme climate using the Twentieth Century Reanalysis, version 3 (20CRv3). The models project that more regions will experience an amplification of the historical ENSO teleconnection with mean temperature and precipitation than a dampening under a high-emission climate scenario. The response of the ENSO teleconnection with extremes is very similar to the mean response, with even larger changes in some regions. Hence, regions that are predicted to experience an amplification of the ENSO teleconnection under future warming can also expect a comparable amplification in the intensity of extremes. Furthermore, models that suggest greater amplification of ENSO amplitude also tend to exhibit greater intensification of mean and extreme teleconnections. Future changes in regional climate variability may be better constrained if changes in ENSO itself are better understood.

Role of single and compound Pacific natural variability in extratropical cyclone activity over North America

AbstractThe role of large‐scale natural variability in influencing the distribution of midlatitude storm tracks and extratropical cyclones is well known. However, less understood is how compound natural variability—the concurrence of two modes of variability—influences the geospatial characteristics of extratropical cyclones. Here, we evaluate compound modes of Pacific‐North American variability—ENSO and PNA with the slow varying PDO—on extratropical cyclones over the North American region during 1950–2013, using an automated tracking algorithm applied to the Twentieth Century Reanalysis version 3 data. Seasonal analysis is conducted on spatial statistics including track, genesis and lysis density and some mean fields in varying compound phases. Spatial correlations of track density with seasonal mean of individual variability indices show that the PNA, ENSO and PDO enhance cyclone activity over Pacific storm track significantly while shifting the North American and Atlantic storm tracks in seasons, that is, equatorward in the positive phase. But the decadal variability of PDO moves the Atlantic storm track poleward, particularly in boreal winter. By comparing to the single Pacific variability impacts, compound Pacific variability results demonstrate the dominance of the higher‐frequency modes of ENSO and PNA on extratropical cyclone activity, while the slow varying PDO can modulate the ENSO‐ and PNA‐related cyclone variability. For example, during a negative PNA, cyclones over the North Atlantic become more (less) frequent during a positive (negative) PDO. The in‐phase modes of the PDO and ENSO influence Pacific storm track significantly, increasing (decreasing) cyclone frequency when both are positive (negative) in boreal winter. Results are linked to and used to explain the previous findings on how natural variability influences the occurrence of tornado outbreaks and high precipitation over the southeastern United States, Great Lakes, Ohio Valley and other US regions. Understanding compound variability modulations may be useful to predict extratropical cyclone frequency, development and decay regions seasonally and to study the physical mechanisms of extreme weather events.

Northern Hemisphere Extratropical Cyclone Activity in the Twentieth Century Reanalysis Version 3 (20CRv3) and Its Relationship with Continental Extreme Temperatures

In this study, we detect and track extratropical cyclones using 6-hourly mean sea level pressure data taken from the Twentieth Century Reanalysis version 3 (20CRv3) over the period 1951–2015 and compare them with those in the Interim and fifth generation of ECMWF reanalyses over the period 1979–2018. Three indices were employed to characterize cyclone activity, including cyclone count, cyclone intensity, and a cyclone activity index (CAI) that combines the count and intensity. The results show that the cyclone indices in the three datasets have comparable annual climatologies and seasonal evolution over the northern extratropical land and ocean in recent decades. Based on the cyclone indices over the period 1951–2010 in 80 ensemble members of 20CRv3, cyclone count and intensity are negatively correlated in winter and tend to be positively and weakly correlated in summer. The interannual CAI variability is dominated by the cyclone count variability. Regional mean cyclone activity can be well represented using the ensemble average cyclone index. We then examined the linkage of the cyclone activity in 20CRv3 and observed cold and warm extremes over Eurasia and North America over the period 1951–2010. In winter, the principal components of interannual cold and warm extreme anomalies are more correlated with the regional mean cyclone count index over Eurasia, while they are more correlated with the cyclone intensity index over North America. The temperature anomalies associated with the regional and ensemble mean cyclone count index explain about 10% (20%) of interannual cold (warm) extreme variances averaged over Eurasia. The temperature anomalies associated with the mean cyclone intensity explain about 10% of interannual cold and warm extreme variances over North America. Large-scale atmospheric circulation anomalies in association with cyclone activity and the induced temperature advection drive temperature anomalies over Eurasia and North America. In summer, circulation and thermal advection anomalies associated with cyclone activity are weak over the two continents. Hence, that season’s relationship between cyclone activity and extreme temperature variability is weak.

Can current reanalyses accurately portray changes in Southern Annular Mode structure prior to 1979?

Early reanalyses are less than optimal for investigating the regional effects of ozone depletion on Southern Hemisphere (SH) high-latitude climate because the availability of satellite sounder data from 1979 significantly improved their accuracy in data sparse regions, leading to a coincident inhomogeneity. To determine whether current reanalyses are better at SH high-latitudes in the pre-satellite era, here we examine the capabilities of the European Centre for Medium-range Weather Forecasts (ECMWF) fifth generation reanalysis (ERA5), the Twentieth Century Reanalysis version 3 (20CRv3), and the Japanese Meteorological Agency (JMA) 55-year reanalysis (JRA-55) to reproduce and help explain the pronounced change in the relationship between the Southern Annular Mode (SAM) and Antarctic near-surface air temperatures (SAT) between 1950 and 1979 (EARLY period) and 1980–2020 (LATE period). We find that ERA5 best reproduces Antarctic SAT in the EARLY period and is also the most homogeneous reanalysis across the EARLY and LATE periods. ERA5 and 20CRv3 provide a good representation of SAM in both periods with JRA-55 only similarly skilful in the LATE period. Nevertheless, all three reanalyses show the marked change in Antarctic SAM-SAT relationships between the two periods. In particular, ERA5 and 20CRv3 demonstrate the observed switch in the sign of the SAM-SAT relationship in the Antarctic Peninsula: analysis of changes in SAM structure and associated meridional wind anomalies reveal that in these reanalyses positive SAM is linked to cold southerly winds during the EARLY period and warm northerly winds in the LATE period, thus providing a simple explanation for the regional SAM-SAT relationship reversal.

A twice‐daily barometric pressure record from Durham Observatory in north‐east England, 1843–1960

AbstractA twice‐daily record of barometric pressure exists for Durham Observatory (54.768 °N, 1.584 °W, barometer cistern 107.3 m above mean sea level, MSL) from 23 July 1843 to 31 December 1960 and is published here for the first time. The Durham record, which is 98.7% complete, is by far the longest digital barometric pressure series in northern England and fills a very large temporal and spatial gap in the International Surface Pressure Database (ISPD: Cram et al, [2015] Geoscience Data Journal, 2, 31–46). In what is believed to be the first study of its kind, the record has been independently quality‐controlled against the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3; Slivinski et al., [2019] Quarterly Journal of the Royal Meteorological Society, 145, 2876; Slivinski et al., [2021] Journal of Climate, 34, 1417–1438), which did not include the Durham records in its assimilation set. This paper describes the instruments used and their exposure, the sources of the record, digitization work undertaken to generate the digital time series (including quality control assessments using 20CRv3) and reduction to mean sea level pressure from station level observations, and examines consistency over the period of record against 20CRv3, concluding with a summary of monthly and annual means and extremes over the 117 year series and the details of the new dataset.

An Evaluation of the Performance of the Twentieth Century Reanalysis Version 3

AbstractThe performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a “best estimate” of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

Digitizing observations from the Met Office Daily Weather Reports for 1900–1910 using citizen scientist volunteers

AbstractWe describe the digitization of 1.8 million sub‐daily and daily weather observations which were recorded in the UK Met Office Daily Weather Reports during the 1900–1910 period. The data were rescued from scanned images of the original documents by 2,148 volunteer citizen scientists using the weatherrescue.org website. The rescued observations include dry and wet bulb temperatures, daily maximum and minimum temperatures, daily rainfall amounts and sub‐daily sea‐level pressure from 72 different locations across western Europe. These observations will be used to fill gaps in existing pressure, temperature and rainfall records and are one of the largest recoveries of weather data by citizen scientists. The value of these additional observations is highlighted by comparing the pressure observations to the Twentieth Century Reanalysis version 3 ensemble for some specific case studies.

Evaluation of physical parameterizations for atmospheric river induced precipitation and application to long-term reconstruction based on three reanalysis datasets in Western Oregon

Dynamically downscaled precipitation is often used for evaluating sub-daily precipitation behavior on a watershed-scale and for the input to hydrological modeling because of its increasing accuracy and spatiotemporal resolution. Despite these advantages, physical parameterizations in regional models and systematic biases due to the dataset used for boundary conditions greatly influence the quality of downscaled precipitation data. The present paper aims to evaluate the performance and the sensitivities of physical parameterizations of the Weather Research and Forecasting (WRF) model to simulate extreme precipitation associated with atmospheric rivers (ARs) over the Willamette watershed in Oregon. Also investigated was whether the optimized WRF configuration for extreme events can be used for long-term reconstruction using different boundary condition datasets. Three reanalysis datasets, the Twentieth Century Reanalysis version 2c (20CRv2c), the European Center for Medium-Range Weather Forecasts (ECMWF) twentieth century reanalysis (ERA20C), and the Climate Forecast System Reanalysis (CFSR), which have different spatial resolutions and dataset periods, were used to simulate precipitation at 4 km resolution. Sensitivity analyses showed that AR precipitation is most sensitive to the microphysics parameterization. Among 13 microphysics schemes investigated, the Goddard and the Stony-Brook University schemes performed the best regardless of the choice of reanalysis. Reconstructed historical precipitation with the optimized configuration showed better accuracies during the wet season than the dry season. With respect to simulations with CFSR, it was found that the optimized configuration for AR precipitation can be used for long-term reconstruction with small biases. However, systematic biases in the reanalysis datasets may still lead to uncertainties in downscaling precipitation in a different season with a single configuration.

Dynamical Properties of the North Atlantic Atmospheric Circulation in the Past 150 Years in CMIP5 Models and the 20CRv2c Reanalysis

AbstractIt is of fundamental importance to evaluate the ability of climate models to capture the large-scale atmospheric circulation patterns and, in the context of a rapidly increasing greenhouse forcing, the robustness of the changes simulated in these patterns over time. Here we approach this problem from an innovative point of view based on dynamical systems theory. We characterize the atmospheric circulation over the North Atlantic in the CMIP5 historical simulations (1851–2000) in terms of two instantaneous metrics: local dimension of the attractor and stability of phase-space trajectories. We then use these metrics to compare the models to the Twentieth Century Reanalysis version 2c (20CRv2c) over the same historical period. The comparison suggests that (i) most models capture to some degree the median attractor properties, and models with finer grids generally perform better; (ii) in most models the extremes in the dynamical systems metrics match large-scale patterns similar to those found in the reanalysis; (iii) changes in the attractor properties observed for the ensemble-mean 20CRv2c are artifacts resulting from inhomogeneities in the standard deviation of the ensemble over time; and (iv) the long-term trends in local dimension observed among the 56 members of the 20CR ensemble have the same sign as those observed in the CMIP5 multimodel mean, although the multimodel trend is much weaker.

Representation of mid‐latitude North American coastal storm activity by six global reanalyses

ABSTRACTExtratropical cyclones often produce extreme and hazardous weather conditions, such as high winds, heavy precipitation, blizzard conditions, and flooding, all of which have detrimental environmental/physical and socio‐economic impacts. Furthermore, storm interaction with the ocean produces additional hazards, with major local impacts, including inundation and coastal erosion. The North American west coast is influenced by the North Pacific storm track and by ‘atmospheric river’ events while the east coast is particularly influenced by winter storms that track along two favoured routes: the St. Lawrence Valley and the Eastern Seaboard. Reanalysis provides an invaluable tool for studying the characteristics of storm events that are identified as causing the most severe impacts. However, reanalysis products differ substantially in spatial resolution, model physics, assimilation approach, and the data that are assimilated. This study evaluates the representation of storm activity along the mid‐latitude North American coastlines by six global reanalyses: NCEP‐1, NCEP‐2, ERA‐Interim, Modern‐Era Retrospective analysis for Research and Applications (MERRA), Climate Forecast System Reanalysis (CFSR), and Twentieth Century Reanalysis Version 2 (20CR). Storm activity representation is evaluated at annual and seasonal timescales (JFM, AMJ, JAS, OND, and ‘extended winter’ ONDFM) during the 1979–2010 time period through comparison with selected meteorological stations using single‐point surface pressure‐based proxies of extratropical storm activity. Stations are selected on the basis of record length, reporting frequency, coastal proximity, and relatively uniform spatial distribution. Comparisons are made using data extracted from the reanalysis grid box centre that is closest to each selected station. All reanalyses are found to successfully represent most aspects of mid‐latitude North American coastal strong storm activity, annually and seasonally, along both coasts. Nevertheless, ERA‐Interim, MERRA, and CFSR provide the better representations of mid‐latitude North American coastal strong storm activity, with ERA‐Interim performing best overall.

Depiction of drought over sub‐Saharan Africa using reanalyses precipitation data sets

AbstractReanalysis precipitation is routinely used as a surrogate for observations due to its high spatial and temporal resolution and global coverage, and it has been widely used in hydrologic and agricultural applications. The resultant product and analysis are largely dependent on the accuracy of the reanalysis precipitation data set. In this study, we analyze the impact of reanalysis precipitation uncertainties on drought depiction. Five reanalyses precipitation data sets (Climate Forecast System Reanalysis, R1: National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research reanalysis, R2: NCEP/Department of Energy reanalysis II, 20CR: The Twentieth Century Reanalysis version 2 and Modern‐Era Retrospective Analysis for Research and Applications) are evaluated from 1979 to 2012 over sub‐Saharan Africa against an observational‐based reference: The Princeton Global Meteorological Forcing data set. Results show that all the reanalyses precipitation data sets provide a relatively good representation of the long‐term statistics of spatiotemporal drought characteristics in sub‐Saharan Africa. However, deficiencies are found in the estimation of drought severity, the spatial pattern, and temporal persistency of droughts. Drought depiction over central Africa appears more problematic due to a lack of observational data. A comparison of drought depiction based on the Standardized Precipitation Index reveals higher monthly to seasonal precipitation variability that further increases after ~1999 due to changes in the observations included in the reanalyses assimilation systems.

Large-scale drivers of Australian east coast cyclones since 1851

Subtropical maritime low-pressure systems are one of the most complex and destructive storm types to impact Australia’s eastern seaboard. This family of storms, commonly referred to as East Coast Cyclones (ECC), is most active during the late autumn and early winter period when baroclinicity increases in the Tasman Sea region. ECC have proven challenging to forecast at both event and seasonal timescales. Storm activity datasets, objectively determined from reanalyses using cyclone detection algorithms, have improved understanding of the drivers of ECC over the era of satellite data coverage. In this study we attempt to extend these datasets back to 1851 using the Twentieth Century Reanalysis version 2c (20CRv2c). However, uncertainty in the 20CRv2c increases back through time due to observational data scarcity, and individual cyclones counts tend to be underestimated during the 19th century. An alternative approach is explored whereby storm activity is estimated from seasonal atmosphere-ocean circulation patterns. Seasonal ECC frequency over the 1955 to 2014 period is significantly correlated to regional sea-level pressure and sea surface temperature (SST) patterns. These patterns are used to downscale the 20CRv2c during early years when individual events are not well simulated. The stormiest periods since 1851 appear to have been 1870 to the early 1890s, and 1950 to the early 1970s. Total storm activity has been below the long-term average for most winters since 1976. Conditions conducive to frequent ECC events tend to occur during periods of relatively warm SST in the southwest Pacific typical of negative Interdecadal Pacific Oscillation (IPO-ve). Extratropical cyclogenesis is associated with negative Southern Annular Mode (SAM-ve) and blocking in the southern Tasman Sea. Subtropical cyclogenesis is associated with SAM+ve and blocking in the central Tasman Sea. While the downscaling approach shows some skill at estimating seasonal storm activity from the large-scale circulation, it cannot overcome data scarcity based uncertainties in the 19th century when the 20CRv2c is effectively unconstrained throughout most of the southern hemisphere. Storm frequency estimates during the 19th century are difficult to verify and should be interpreted cautiously and with reference to available documentary evidence.

Greenland Blocking Index 1851–2015: a regional climate change signal

ABSTRACTWe present an extended monthly and seasonal Greenland Blocking Index (GBI) from January 1851 to December 2015, which more than doubles the length of the existing published GBI series. We achieve this by homogenizing the Twentieth Century Reanalysis version 2c‐based GBI and splicing it with the NCEP/NCAR Reanalysis‐based GBI. For the whole time period, there are significant decreases in GBI in autumn, October and November, and no significant monthly, seasonal or annual increases. More recently, since 1981 there are significant GBI increases in all seasons and annually, with the strongest monthly increases in July and August. A recent clustering of high GBI values is evident in summer, when 7 of the top 11 values in the last 165 years – including the two latest years 2014 and 2015 – occurred since 2007. Also, 2010 is the highest GBI year in the annual, spring, winter and December series but 2011 is the record low GBI value in the spring and April series. Moreover, since 1851 there have been significant increases in GBI variability in May and especially December. December has also shown a significant clustering of extreme high and low GBI values since 2001, mirroring a similar, recently identified phenomenon in the December North Atlantic Oscillation index, suggesting a related driving mechanism. We discuss changes in hemispheric circulation that are associated with high compared with low GBI conditions. Our GBI time series should be useful for climatologists and other scientists interested in aspects and impacts of Arctic variability and change.

Evaluation of landfalling atmospheric rivers along the U.S. West Coast in reanalysis data sets

AbstractAn intercomparison of landfalling atmospheric rivers (ARs) between four reanalysis data sets using one satellite‐derived AR detection method as a metric to characterize landfalling atmospheric rivers (ARs) along the U.S. West Coast is performed over 15 cool seasons (October–March) during the period from water years 1998 to 2012. The four reanalysis data sets analyzed in this study are the Climate System Forecast Reanalysis (CFSR), Modern‐Era Retrospective Analysis for Research and Applications (MERRA), ERA‐Interim (ERA‐I), and the Twentieth Century Reanalysis version 2 (20CR) data set. The Atmospheric River Detection Tool is used to identify AR features in the total vertically integrated water vapor (IWV) data of the reanalysis data, and validation of the reanalysis AR data are compared with AR data derived from satellite IWV observations. The AR landfall data from reanalysis were generally found to be in good agreement with satellite observations. Reanalysis data with less (CFSR) or no assimilation (20CR) of the satellite data used in this study had greater bias with AR characteristics such as IWV, width, and landfall location. The 20CR ensemble data were found to better characterize the AR landfall characteristics than the 20CR ensemble mean although all 20CR data underestimated AR landfalls particularly in the southern section of the U.S. West Coast. Overall AR landfall detections for the 15 year cool season period were within 5% of the satellite for the CFSR, MERRA, and ERA‐I data.

Simulated Atlantic Meridional Overturning Circulation in the 20th century with an ocean model forced by reanalysis-based atmospheric data sets

Global ocean hindcast simulations for the period 1871–2009 have been run with the ocean-sea ice component of the Norwegian Earth System Model (NorESM-O), forced by an adjusted version of the Twentieth Century Reanalysis version 2 data set (20CRv2 data set), as well as by the commonly used second version of atmospheric forcing data set for the Coordinated Ocean-ice Reference Experiments phase-II (CORE-II) for the period 1948–2007 (hereafter CORE.v2 data set). The simulated Atlantic Meridional Overturning Circulation (AMOC) in the 20CR and the CORE simulations have comparable variability as well as mean strength during the last three decades of the integration. The simulated AMOC undergoes, however, distinctly different evolutions during the period 1948–1970, with a sharply declining strength in CORE but a gradual increase in 20CR. Sensitivity experiments suggest that differences in the wind forcing between CORE and 20CR have major impact on the simulated AMOCs during this period. It is furthermore found that differences in the air temperature between the two data sets do contribute to the differences in AMOC, but to a much lesser degree than the wind. An additional factor for the diverging AMOC in the two decades following 1948 is the inevitable switching of atmospheric forcing fields in 1948 in the CORE.v2-based runs due to the cyclic spin-up procedure of the ocean model. The latter is a fundamental issue for any ocean hindcast simulation. The ocean initial state mainly influence the actual value but to a lesser degree also the temporal evolution (variability) of AMOC. It may take about two decades for the AMOC to adjust to a new atmospheric state during the spin-up, although a dynamically balanced ocean initial state tends to reduce the adjustment time and the magnitude of the deviation, implying that an ocean model run with atmospheric forcing fields extending back in time, like 20CRv2, can be used to extend the reliable duration of CORE-type of simulations.

Large-scale drivers of Australian east coast cyclones since 1851

Subtropical maritime low-pressure systems are one of the most complex and destructive storm types to impact Australia’s eastern seaboard. This family of storms, commonly referred to as East Coast Cyclones (ECC), is most active during the late autumn and early winter period when baroclinicity increases in the Tasman Sea region. ECC have proven challenging to forecast at both event and seasonal timescales. Storm activity datasets, objectively determined from reanalyses using cyclone detection algorithms, have improved understanding of the drivers of ECC over the era of satellite data coverage. In this study we attempt to extend these datasets back to 1851 using the Twentieth Century Reanalysis version 2c (20CRv2c). However, uncertainty in the 20CRv2c increases back through time due to observational data scarcity, and individual cyclones counts tend to be underestimated during the 19th century. An alternative approach is explored whereby storm activity is estimated from seasonal atmosphere-ocean circulation patterns. Seasonal ECC frequency over the 1955 to 2014 period is significantly correlated to regional sea-level pressure and sea surface temperature (SST) patterns. These patterns are used to downscale the 20CRv2c during early years when individual events are not well simulated. The stormiest periods since 1851 appear to have been 1870 to the early 1890s, and 1950 to the early 1970s. Total storm activity has been below the long-term average for most winters since 1976. Conditions conducive to frequent ECC events tend to occur during periods of relatively warm SST in the southwest Pacific typical of negative Interdecadal Pacific Oscillation (IPO-ve). Extratropical cyclogenesis is associated with negative Southern Annular Mode (SAM-ve) and blocking in the southern Tasman Sea. Subtropical cyclogenesis is associated with SAM+ve and blocking in the central Tasman Sea. While the downscaling approach shows some skill at estimating seasonal storm activity from the large-scale circulation, it cannot overcome data scarcity based uncertainties in the 19th century when the 20CRv2c is effectively unconstrained throughout most of the southern hemisphere. Storm frequency estimates during the 19th century are difficult to verify and should be interpreted cautiously and with reference to available documentary evidence.

Large-scale drivers of Australian east coast cyclones since 1851

Subtropical maritime low-pressure systems are one of the most complex and destructive storm types to impact Australia’s eastern seaboard. This family of storms, commonly referred to as East Coast Cyclones (ECC), is most active during the late autumn and early winter period when baroclinicity increases in the Tasman Sea region. ECC have proven challenging to forecast at both event and seasonal timescales. Storm activity datasets, objectively determined from reanalyses using cyclone detection algorithms, have improved understanding of the drivers of ECC over the era of satellite data coverage. In this study we attempt to extend these datasets back to 1851 using the Twentieth Century Reanalysis version 2c (20CRv2c). However, uncertainty in the 20CRv2c increases back through time due to observational data scarcity, and individual cyclones counts tend to be underestimated during the 19th century. An alternative approach is explored whereby storm activity is estimated from seasonal atmosphere-ocean circulation patterns. Seasonal ECC frequency over the 1955 to 2014 period is significantly correlated to regional sea-level pressure and sea surface temperature (SST) patterns. These patterns are used to downscale the 20CRv2c during early years when individual events are not well simulated. The stormiest periods since 1851 appear to have been 1870 to the early 1890s, and 1950 to the early 1970s. Total storm activity has been below the long-term average for most winters since 1976. Conditions conducive to frequent ECC events tend to occur during periods of relatively warm SST in the southwest Pacific typical of negative Interdecadal Pacific Oscillation (IPO-ve). Extratropical cyclogenesis is associated with negative Southern Annular Mode (SAM-ve) and blocking in the southern Tasman Sea. Subtropical cyclogenesis is associated with SAM+ve and blocking in the central Tasman Sea. While the downscaling approach shows some skill at estimating seasonal storm activity from the large-scale circulation, it cannot overcome data scarcity based uncertainties in the 19th century when the 20CRv2c is effectively unconstrained throughout most of the southern hemisphere. Storm frequency estimates during the 19th century are difficult to verify and should be interpreted cautiously and with reference to available documentary evidence.

Summer heat waves in southeastern Patagonia: an analysis of the intraseasonal timescale

ABSTRACTWe explore the occurrence of intraseasonal summer heat waves in southeastern Patagonia (SEPG, 46°–52°S; 65°–70°W) since the late 19th century by means of the Twentieth Century Reanalysis version 2 (20CRv2). In total, we identify 201 cases for 1872–2010 using criteria of intensity and persistence. In SEPG, the corresponding intraseasonal temperature signals are centred around the first day of each cluster of days fulfilling those conditions (named day 0). The mean warm deviation lasts for approximately 2 weeks and exhibits a mean temperature peak of 4.3 °C on day 0 (the warmest day in the mean signal). In a regional context, the mean temperature perturbation associated with these heat waves affects a broad area on both sides of the Andes. The warming in SEPG is caused by temperature advection and enhanced radiative heating, following a high pressure system over southern South America (SSA). This atmospheric perturbation is embedded in a wave‐train‐like pattern along the South Pacific. As part of this pattern, a cyclonic anomaly progresses eastward over the Tasman Sea in Oceania, moving from southeastern Australia (day −6, causing a dry anomaly there) over New Zealand (day −3, inducing a wet anomaly on its Southern Island). The anomalous circulation triggered by the wave train leads thus to a teleconnection between SSA and Oceania, documented in a previous work for the interannual scale. Two thirds of the heat wave events are linked to enhanced ascent in the South Atlantic Convergence Zone (SACZ) and around one third of the events within 1957–2010 are associated with extreme absolute maximum temperatures observed at a station‐based record from SEPG. Finally, possible spatial modulations of the wave train pattern at the interannual and interdecadal timescales are discussed.

Multidecadal Drought Cycles in the Great Basin Recorded by the Great Salt Lake: Modulation from a Transition-Phase Teleconnection

This study investigates the meteorological conditions associated with multidecadal drought cycles as revealed by lake level fluctuation of the Great Salt Lake (GSL). The analysis combined instrumental, proxy, and simulation datasets, including the Twentieth Century Reanalysis version 2, the North American Drought Atlas, and a 2000-yr control simulation of the GFDL Coupled Model, version 2.1 (CM2.1). Statistical evidence from the spectral coherence analysis points to a phase shift amounting to 6–9 yr between the wet–dry cycles in the Great Basin and the warm–cool phases of the interdecadal Pacific oscillation (IPO). Diagnoses of the sea surface temperature and atmospheric circulation anomalies attribute such a phase shift to a distinctive teleconnection wave train that develops during the transition points between the IPO’s warm and cool phases. This teleconnection wave train forms recurrent circulation anomalies centered over the southeastern Gulf of Alaska; this directs moisture flux across the Great Basin and subsequently drives wet–dry conditions over the Great Basin and the GSL watershed. The IPO life cycle therefore modulates local droughts–pluvials in a quarter-phase manner.

Interannual and interdecadal variations in the North Atlantic Oscillation spatial shift

The spatial shift of the North Atlantic Oscillation (NAO) is analyzed by using the Twentieth Century Reanalysis version 2 dataset and identifying NAO action centers directly on winter mean sea-level pressure (SLP) anomaly maps. The spatial shift of the NAO is characterized by four NAO spatial shift indices: the zonal and meridional shifts of the NAO southern and northern action centers. It is found that the zonal and meridional shift trends of the NAO action centers move along a path of southwest-northwest direction. Spectral analysis shows that the four NAO spatial shift indices have periodicity of 2–6 years and the NAO index has periodicity of 2–3 years in terms of high-frequency variations. On a decadal time scale, the NAO spatial shift indices are closely (positively) related to the NAO index, which is in agreement with previous studies of the relationship between the NAO index and the spatial shift of the NAO pattern. However, there is no relationship between the NAO index and the meridional shift of the northern action center on an interannual time scale. The significant relationship between the NAO index and the interannual variability of NAO spatial shift indices is very likely to be associated with synoptic-scale Rossby wave breaking, which generates surface pressure anomalies and thus affects the phase and pattern of the NAO. The correlations of winter westerly winds over 90°W-0° and the NAO index and the NAO spatial shift indices have a ‘+ − + −’ structure from the Equator to the North Pole. Although there is close correlation between the NAO spatial shift indices and the strength of the zonal winds in the North Atlantic region, the effect of the zonal winds on the NAO spatial shift differs at different latitudes. Hence, the role of the zonal winds is probably a result of the NAO spatial shifts.