Mean Sea Level Pressure Anomalies Research Articles

Technical note: An improved methodology for calculating the Southern Annular Mode index to aid consistency between climate studies

Abstract. The Southern Annular Mode (SAM) strongly influences climate variability in the Southern Hemisphere. The SAM index describes the phase and magnitude of the SAM and can be calculated by measuring the difference in mean sea level pressure (MSLP) between middle and high latitudes. This study investigates the effects of calculation methods and data resolution on the SAM index, and subsequent interpretations of SAM impacts and trends. We show that the normalisation step that is traditionally used in calculating the SAM index leads to substantial differences in the magnitude of the SAM index calculated at different temporal resolutions. Additionally, the equal weighting that the normalisation approach gives to MSLP variability at the middle and high southern latitudes artificially alters temperature and precipitation correlations and the interpretation of climate change trends in the SAM. These issues can be overcome by instead using a natural SAM index based on MSLP anomalies, resulting in consistent scaling and variability in the SAM index calculated at daily, monthly and annual data resolutions. The natural SAM index has improved representation of SAM impacts in the high southern latitudes, including the asymmetric (zonal wave-3) component of MSLP variability, whereas the increased weighting given to mid-latitude MSLP variability in the normalised SAM index incorporates a stronger component of tropical climate variability that is not directly associated with SAM variability. We conclude that an improved approach of calculating the SAM index from MSLP anomalies without normalisation would aid consistency across climate studies and avoid potential ambiguity in the SAM index, including SAM index reconstructions from palaeoclimate data, and thus enable more consistent interpretations of SAM trends and impacts.

Skillful decadal prediction of German Bight storm activity

Abstract. We evaluate the prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) decadal hindcast system for German Bight storm activity (GBSA) on a multiannual to decadal scale. We define GBSA every year via the most extreme 3-hourly geostrophic wind speeds, which are derived from mean sea-level pressure (MSLP) data. Our 64-member ensemble of annually initialized hindcast simulations spans the time period 1960–2018. For this period, we compare deterministically and probabilistically predicted winter MSLP anomalies and annual GBSA with a lead time of up to 10 years against observations. The model produces poor deterministic predictions of GBSA and winter MSLP anomalies for individual years but fair predictions for longer averaging periods. A similar but smaller skill difference between short and long averaging periods also emerges for probabilistic predictions of high storm activity. At long averaging periods (longer than 5 years), the model is more skillful than persistence- and climatology-based predictions. For short aggregation periods (4 years and less), probabilistic predictions are more skillful than persistence but insignificantly differ from climatological predictions. We therefore conclude that, for the German Bight, probabilistic decadal predictions (based on a large ensemble) of high storm activity are skillful for averaging periods longer than 5 years. Notably, a differentiation between low, moderate, and high storm activity is necessary to expose this skill.

On the Ridging of the South Atlantic Anticyclone Over South Africa: The Impact of Rossby Wave Breaking and of Climate Change

AbstractRidging South Atlantic Anticyclones contribute an important amount of precipitation over South Africa. Here, we use a global coupled climate model and the ERA5 reanalysis to separate for the first time ridging highs (RHs) based on whether they occur together with Rossby wave breaking (RWB) or not. We show that the former type of RHs are associated with more precipitation than the latter type. The mean sea level pressure anomalies caused by the two types of RHs are characterized by distinct patterns, leading to differences in the flow of moisture‐laden air onto land. We additionally find that RWB mediates the effect of climate change on RHs during the twenty‐first century. Consequently, RHs occurring without RWB exhibit little change, while those occurring with RWB contribute more precipitation over the southern and less precipitation over the northeastern South Africa in the future.

A CLIMATOLOGY BASED FORECAST TOOL FOR COASTAL FLOODING IN THE LOWCOUNTRY

AbstractCoastal nuisance flooding has increased by an order of magnitude over the past half century, but the National Weather Service has a limited suite of statistical tools to forecast them. Such a tool was developed using coastal flood events from 1996—2014 in Charleston, South Carolina, which were identified and classified by prevailing synoptic conditions based on composite mean sea level pressure anomalies. The synoptic climatology indicated low level northeasterly winds dominated the forcing in anticyclonic and cyclonic events, while a southeasterly surge was the main forcing component for frontal events. Tidal anomalies between flood events and previous low tides were used to create linear regression models for each composite classification studied for forecasting levels of coastal flood magnitude. Beta tests using data from 2018—2019 confirmed the effectiveness of the models with RMSE values less than 0.3 ft and MAE values less than 0.25 ft for each event type. The veracity of the methods was further verified by a multiple day case study from November 2018, where the model was tested against both statistically predicted heights and heights based on ETSS Model (v2.2). The RMSE and MAE for the statical model were 0.18 and 0.15 respectively, while the same values for the ETSS model were 0.28 and 0.23 respectively.

Synopsis of the dramatic climate change in Iran: a seasonal synoptic analysis

This study examines the NCEP (National Centers for Environmental Prediction)/NCAR (National Center for Atmospheric Research) reanalysis model datasets to display the existence of the anomaly periodic time with the significant atmospheric changes in Iran. Datasets such as surface air temperatures, relative humidity, surface soil moisture, precipitation rate, mean sea level pressure, 500 hPa geopotential height, near-surface vorticity and surface scale winds have been used. The anomalies’ departures from climate normal for the meteorological datasets are investigated, and synoptically patterns have been analysed. The yearly seasonal mean surface air temperature time series during 1948–2018 displays a dramatic warming shift with an abnormal pattern in Iran from 1994 onwards. The analysis of the other datasets resulted from ERA-Interim and MERRA-2 database also confirm a warming shift nearly from 1994 over Iran. The statistical analysis of t-tests shows the existence of a significant difference in seasonal mean surface air temperatures during the anomaly period (1994–2018) and the mean values during climatology normal periodic time (1981–2010). This suggests remarkable warming over all parts of Iran with the highest changes in surface temperatures ranging ~0.1–1 °C in spring and the lowest change in fall ranging ~0.1–0.7 °C. Significant changes have resulted in precipitation rate, atmospheric humidity, soil moistures and surface wind speeds. Also, due to the strengthened northern high-pressure system along with the intensification of the 500 hPa ridge and less atmospheric humidity, a rather stable, warmer and drier atmosphere with less precipitation (respect to climate normal) over the most part of Iran has been indicated. The low-level vorticity anomalies have displayed the intensified flows from the regional desert areas to the central and north-east of Iran and from Iraq to the west and south-west of Iran for all seasons (with the higher gradient in summer rather than other seasons). Also, mean sea level pressure anomalies have exposed the increase in pressure gradient mostly over the western and central parts in all seasons except winter (with decreased wind speeds leads to haze or accumulated pollutants). This may cause instability in these parts with the possibility of frequent dust storm because of wind acceleration and warmer and dry atmospheric conditions rather normal mean. However, this study shows that during the fall seasons, humidity and precipitation values in the south-west and south-east area have been increased in comparison with the normal mean values. The increase in relative humidity during fall in the south-east areas can be associated with the impact of the intensified south-easterly flows (southern low-pressure tongue). This is accompanying by rather warmer sea surface temperatures in the southern marine areas, especially in the Oman sea and the northern Indian Ocean. Overall, this study presents some synoptic abnormal patterns associated with the recent Iran significant atmospheric climate changes.

Strong quasi-stationary wintertime atmospheric surface pressure anomalies drive a dipole pattern in the Subantarctic ModeWater formation

AbstractThe deepest wintertime (Jul-Sep) mixed layers associated with Subantarctic Mode Water (SAMW) formation develop in the Indian and Pacific sectors of the Southern Ocean. In these two sectors the dominant interannual variability of both deep wintertime mixed layers and SAMW volume is a east-west dipole pattern in each basin. The variability of these dipoles are strongly correlated with the interannual variability of overlying winter quasi-stationary mean sea level pressure (MSLP) anomalies. Anomalously strong positive MSLP anomalies are found to result in the deepening of the wintertime mixed layers and an increase in the SAMW formation in the eastern parts of the dipoles in the Pacific and Indian sectors. These effects are due to enhanced cold southerly meridional winds, strengthened zonal winds and increased surface ocean heat loss. The opposite occurs in the western parts of the dipoles in these sectors. Conversely, strong negative MSLP anomalies result in shoaling (deepening) of the wintertime mixed layers and a decrease (increase) in SAMW formation in the eastern (western) regions. The MSLP variability of the Pacific and Indian basin anomalies are not always in phase, especially in years with a strong El Niño, resulting in different patterns of SAMW formation in the western vs. eastern parts of the Indian and Pacific sectors. Strong isopycnal depth and thickness anomalies develop in the SAMW density range in years with strong MSLP anomalies. When advected eastward, they act to precondition downstream SAMW formation in the subsequent winter.

The linkages between Antarctic sea ice extent and Indian summer monsoon rainfall

Teleconnection between the Antarctic sea ice and the tropical climate has been extensively investigated. This study examines the interannual relationship between the variability of sea ice extent in the Indian Ocean sector (20–90°E) and Indian summer monsoon rainfall under the influence of the Mascarene High. Sea ice extent during April-May-June (AMJ) appears to have a significant correlation with the summer monsoon rainfall over Peninsular India region during June-July-August-September from 1979 to 2013. Composites of mean sea level pressure (MSLP), 500 hPa geopotential height, and 850 hPa wind anomalies during high and low ice phases show a positive relation between the sea ice extent and the Mascarene High, revealing that high (low) ice phase corresponds respectively to the strengthening (weakening) of the Mascarene High as well as an increase (decrease) in Indian summer monsoon rainfall. During the respective high (low) ice phase years, positive (negative) MSLP anomalies were found, particularly over the Mascarene High region, associated with the eastwards (westwards) shifts of its climatology locations. Similar features were observed at 500 hPa geopotential height anomalies. In addition, strong anticyclonic (cyclonic) anomalies in the Mascarene High region were found in 850 hPa winds, which led to corresponding strong (weak) south westerlies and thus respective positive (negative) Indian summer monsoon rainfall anomalies.

Using statistical downscaling to assess skill of decadal predictions

We test a hypothesis that the signal-to-noise ratio of decadal forecasts improves with larger scales and can be utilised through model output statistics (MOS) involving empirical-statistical downscaling and dependencies to large-scale conditions. Here, we used MOS applied to an ensemble of decadal forecasts to predict local wet-day frequency, the wet-day mean precipitation, and the mean temperature for one to nine year long intervals of forecasts with a one year lead time. Our study involved a set of decadal forecasts over the 1961–2011 period, based on a global coupled ocean-atmosphere model that was downscaled and analysed for the North Atlantic region. The MOS for the decadal forecasts failed to identify aspects that were associated with higher skill for temperature and precipitation over Europe on time scales shorter than five years. A likely explanation for not enhancing skillful parts of the forecasts was that the raw model output had low skill for the general large-scale atmospheric circulation. This was particularly true for the wet-day frequency over Europe, which had a strong connection to the mean sea-level pressure (SLP) anomalies over the North Atlantic. There was a weak connection between large-scale maritime surface temperature anomalies and local precipitation and temperature variability over the European continent. The decadal forecasts for time scale of nine years and longer, on the other hand, exhibited moderate skill. The dependency between temporal and spatial scales was found to differ for the temperature and the mean SLP anomalies, but we found little indication that the decadal predictions for anomalies with large-scale regional extent were associated higher skill than for more local patterns in these forecasts.

Long-term variability and trends in the Caspian Sea – Hindu Kush Index: Influence on atmospheric circulation patterns, temperature and rainfall over the Middle East and Southwest Asia

Abstract The Caspian Sea – Hindu Kush Index (CasHKI) has been introduced as an indicator of modulation of the wind regime and dust activity over southwest (SW) Asia. This study analyzes the long-term series in CasHKI values and the associated mean sea-level pressure (MSLP) anomalies over the Caspian Sea (CS) and Hindu Kush (HK) domains during the period 1963–2014, aiming at examining the trends in CasHKI and the associated climate implications. An overall negative trend (−0.12 hPa per decade) in CasHKI is revealed during 1963–2014, mostly driven by the large decrease in CasHKI during 1963–1980, whereas an increasing trend is found during the 2000s. The CasHKI values are mostly related to the MSLP anomalies over the CS rather than HK domain; however, the negative anomalies in MSLP over HK during the 1960s determine the corresponding CasHKI trends. The MSLP values and anomalies show a regional shift in the core maximum and higher increasing trends at the southern compared to northern latitudes within the CS domain. The synoptic maps of the MSLP, geopotential height at 700 hPa (Z700) and vertical profile of the meridional wind are compared between the months with highest and lowest CasHKI values, revealing a significant intensification in the north wind over the SW Asia and a deepening of the Indian/Pakistan thermal low for the high-CasHKI months in summer. In addition, the high-CasHKI months are mostly associated with a decrease in Z700 over SW Asia and the Middle East, an intensification of the Indian monsoon trough, a decrease in temperature over the SW Asia and a slight increase in rainfall over parts of SW Asia, Middle East and east Africa. Finally, ENSO variability seems not to be significantly linked with CasHKI - but this issue requires further examination.

Weather regimes associated with summer rainfall variability over southern Mexico

ABSTRACTThis study focuses on the identification of weather regimes (WRs) over Mexico, the tropical eastern Pacific, Central America and the Caribbean, associated with seasonal precipitation over southern Mexico. A self‐organizing maps (SOM) analysis of sea level pressure, 850‐hPa horizontal winds and 925‐hPa‐specific humidity for the period 1997–2013 was carried out to identify the circulation patterns. This approach allowed the discrimination of wet and dry regimes, with clear and distinct features. Weather patterns exhibiting negative (positive) mean sea level pressure anomalies, southerly (northerly) winds, above‐ (below‐) average low‐level moisture and little (large) influence of the North Atlantic Subtropical High (NASH), resulted in above‐ (below‐) average precipitation over southern Mexico. The intra‐seasonal variability of the WRs and their associated rainfall is well captured by this methodology. In particular, the mid‐summer drought (MSD) during late July and early August, is clearly represented by a group of patterns, which evidence a strong influence of the NASH, strong easterly winds in the Caribbean Basin and reduced low‐level humidity, all factors that combine to induce below‐normal rainfall over southern Mexico. The analysis of the inter‐annual variability of the WRs suggests that year‐to‐year variations in their frequencies can impact summer rainfall in the regions of southern Mexico considered in this study. In particular, the analysis indicates that the dominant WR associated with the MSD exhibits a 3‐ to 4‐year modulation in its frequency of occurrence, which has not been previously reported in the literature. The main MSD pattern is more frequent during dry years and has a significant correlation with the Multivariate El Niño‐Southern Oscillation (ENSO) Index (MEI), indicating that MSD is stronger during ‘El Niño’ years. Also, WRs associated with negative (positive) rainfall anomalies showed positive (negative) correlations with the MEI, suggesting a possible modulation by ENSO phases.

Assessment of changes in atmospheric dynamics and dust activity over southwest Asia using the Caspian Sea–Hindu Kush Index

ABSTRACTThis study examines the influence of the Caspian Sea–Hindu Kush Index (CasHKI) on local and synoptic meteorology as well as on dust emissions over southwest (SW) Asia by means of National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP‐NCAR) re‐analysed mean sea‐level pressure (MSLP), geopotential height at 700 hPa and surface meridional wind, along with meteorological data at Zabol, east Iran and Meteosat/Infrared Difference Dust Index (IDDI) retrievals. The analysis focuses on the summer period (June to September) of 2000–2014 and the winter period (November to March) of 1963–2014. The CasHKI values are mostly controlled by the MSLP anomalies over the Caspian Sea (CS) domain, varying from approximately −25 to +35 hPa in winter and from approximately−10 to +14 hPa in summer, but without a clear annual pattern. The CasHKI values are classified into four modes for each month depending on their intensity. In the summer months, the high CasHKI mode is associated with enhanced MSLP over central Asia and deepening of the Indo‐Pakistan thermal low associated with the Indian summer monsoon. At 700‐hPa level, the high CasHKI mode shows an enhancement of the Arabian ridge, expanding it to the north over Iran and the CS, with a concurrent strengthening of the Indian trough, leading to intensification of northerly winds along east Iran. This results in significant increase in dust activity over SW Asia, which is also apparent in the winter months. Furthermore, the intensification of the northerly flow associated with the high CasHKI modes drops the temperature and increases the relative humidity over Zabol, especially during winter. The SPRINTARS‐model simulations also show increased dust emissions and concentrations for the high CasHKI values, confirming that the CasHKI variations modulate the dust activity over SW Asia throughout the year.

Salinity and streamflow variability in the Mid-Atlantic region of the United States and its relationship with large-scale atmospheric circulation patterns

The historical variability of streamflow and salinity was examined for three large estuaries of the Mid-Atlantic region of the United States (US) in order to determine how they are influenced by large-scale circulation patterns. New wavelet methods identified 2- and 4-year periodicities from the streamflow time series. A composite analysis of meteorological data revealed that the anomalously high daily streamflow events coincided with Rossby waves emanating from the tropical Pacific and an eastern mean sea-level pressure (MSLP) dipole pattern in which negative MSLP anomalies were situated over the southeast US and positive MSLP anomalies were situated over the northwestern North Atlantic Ocean. Based on this pattern, a new Eastern North American (ENA) index was constructed that could explain more daily streamflow variance than existing climate indices. A wavelet coherence analysis identified ENA index relationships with streamflow and salinity at periods of 2–4years, suggesting that the ENA index may offer predictability beyond the weather forecasting timescale. The ENA index was also found to be phase-locked to the Gulf Stream index at a period of 74months. Because the MSLP dipole pattern is linked to the upstream Rossby wave train, salinity variability at that timescale may have resulted from MSLP dipole-related changes in precipitation.

Extreme daily precipitation in coastal western Norway and the link to atmospheric rivers

AbstractThis work investigates the link between the most extreme daily precipitation (EDP) events observed since 1900 on the west coast of Norway and the large‐scale moisture fluxes over the North Atlantic Ocean. Using station precipitation data, vertically integrated water vapor (IWV) from Special Sensors Microwave Imager/Sounder (SSMIS) satellite observations and the state of the art NOAA‐twentieth Century (NOAA‐20C) reanalysis, it is shown that 55 out of 58 EDPs are associated with narrow plumes of intense low‐level moisture defined as atmospheric rivers. Despite the high spatial correlation between IWV fields in the SSMIS and NOAA‐20C data sets, the significant positive relationship between the maximum amount of observed precipitation at all stations and the IWV content hitting the coastal terrain is only observed in the SSMIS data set. Further, the composite analyses of synoptic conditions show that the preferred circulation type consists of a mean sea level pressure (MSLP) dipole pattern where a high‐pressure system over central Europe and a series of low‐pressure systems to the east of Iceland and over the Norwegian Sea are present. The west coast of Norway is located in the exit region of the anticyclonically curved upper tropospheric polar jet stream implying that the coupling of upper troposphere and surface dynamics begins to weaken at the time of EDPs. It is also found that the primary synoptic‐scale precursors are persistent positive 500 hPa height geopotential and MSLP anomalies over central Europe up to 10 days before the occurrence of EDP events.

Analysis of WRF extreme daily precipitation over Alaska using self‐organizing maps

AbstractWe analyze daily precipitation extremes from simulations of a polar‐optimized version of the Weather Research and Forecasting (WRF) model. Simulations cover 19 years and use the Regional Arctic System Model (RASM) domain. We focus on Alaska because of its proximity to the Pacific and Arctic oceans; both provide large moisture fetch inland. Alaska's topography also has important impacts on orographically forced precipitation. We use self‐organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events. The SOM algorithm employs an artificial neural network that uses an unsupervised training process, which results in finding general patterns of circulation behavior. The SOM is trained with mean sea level pressure (MSLP) anomalies. Widespread extreme events, defined as at least 25 grid points experiencing 99th percentile precipitation, are examined using SOMs. Widespread extreme days are mapped onto the SOM of MSLP anomalies, indicating circulation patterns. SOMs aid in determining high‐frequency nodes, and hence, circulations are conducive to extremes. Multiple circulation patterns are responsible for extreme days, which are differentiated by where extreme events occur in Alaska. Additionally, several meteorological fields are composited for nodes accessed by extreme and nonextreme events to determine specific conditions necessary for a widespread extreme event. Individual and adjacent node composites produce more physically reasonable circulations as opposed to composites of all extremes, which include multiple synoptic regimes. Temporal evolution of extreme events is also traced through SOM space. Thus, this analysis lays the groundwork for diagnosing differences in atmospheric circulations and their associated widespread, extreme precipitation events.

Troposphere‐stratosphere dynamical coupling in the southern high latitudes and its linkage to the Amundsen Sea

AbstractExtremes in the distribution of Southern Hemisphere stratospheric heat flux are connected simultaneously to anomalous high‐latitude tropospheric weather patterns in reanalysis, consistent with results from the Northern Hemisphere. The dynamical links are revealed using a metric based on extreme stratospheric planetary‐scale wave heat flux events, defined as the 10th and 90th percentiles of the daily high‐latitude wave 1 heat flux distribution at 50 hPa. We show extreme negative (positive) heat flux events are linked to a westward (eastward) shift in the Amundsen Sea Low and anomalous warming (cooling) over the Amundsen Bellingshausen Seas in reanalysis data. Since coupling to the stratosphere via planetary waves has significant impacts on the tropospheric circulation of both hemispheres, it is important to understand which coupled climate models can reproduce this phenomenon. The heat flux metric is used to evaluate troposphere‐stratosphere coupling in models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and compare their performance across hemispheres. The results show that models with a degraded representation of stratospheric extremes exhibit robust biases in tropospheric sea level pressure variability over the Antarctic Peninsula. Models which fail to capture the extremes in stratospheric heat flux, significantly underestimate the variance of the distribution of mean sea level pressure anomalies over Western Antarctica.

A flexible approach to defining weather patterns and their application in weather forecasting over Europe

ABSTRACTA method is presented for deriving weather patterns objectively over an area of interest, in this case the UK and surrounding European area. A set of 30 and eight patterns are derived through k‐means clustering of daily mean sea level pressure (MSLP) data (1850–2003). These patterns have been designed for the purpose of post‐processing forecast output from ensemble prediction systems and understanding how forecast models perform under different circulation types. The 30 weather patterns are designed for use in the medium‐range and the eight weather patterns are designed for use in the monthly and seasonal timescales, or when there is low forecast confidence in the medium‐range. Weather patterns are numbered according to their annual historic occurrences, with lower numbered patterns occurring most often. Lower numbered patterns occur more in summer (with weak MSLP anomalies) and higher numbered patterns occur more in winter (with strong MSLP anomalies). Weather patterns have been applied in a weather forecasting context, whereby ensemble members are assigned to the closest matching pattern definition. This provides a probabilistic insight into which patterns are most likely within the forecast range and summarises key aspects from the large volumes of data which ensembles provide. Verification of European Centre for Medium‐Range Weather Forecasts medium‐range ensemble forecasts for the set of eight weather patterns shows small forecast biases annually with some large variations seasonally. The most prominent seasonal variation shows the westerly (NAO+) pattern to over‐forecast in summer and under‐forecast in winter. Forecast skill was found to be better in winter than summer for most patterns.

The Caspian Sea–Hindu Kush Index (CasHKI): A regulatory factor for dust activity over southwest Asia

This work investigates the modulation in dust activity over southwest (SW) Asia attributed to changes in the mean sea level pressure (MSLP) between the Caspian Sea (CS) and Hindu Kush (HK) during the summer months (June–July–August–September, JJAS) of the period 2000–2014. The MSLP anomalies obtained via NCEP/NCAR re-analysis are evaluated via a new climatology index, the Caspian Sea–Hindu Kush Index (CasHKI), which is defined as CasHKI=MSLPanom.CS−MSLPanom.HK, over specific domains taken over the CS and HK. The changes in CasHKI intensity are examined against dust activity and rainfall distributions over south Asia. The satellite remote sensing (Meteosat, OMI, MODIS) analyses show that high CasHKI values corresponding to enhanced pressure gradient between the CS and the HK, are associated with intensification of northerly winds, increased dust emissions and transportation over SW Asia and north Arabian Sea. In contrast, variations in CasHKI intensity do not seem to have a significant effect on the Indian summer monsoon. Only a slight decrease of precipitation over the southern Indian peninsula and the neighboring oceanic areas and an increase of precipitation along the Ganges Basin and Himalayan range are found to be related to high CasHKI values. Model (MIROC-SPRINTARS) simulations of dust concentration and dust AOD (Aerosol Optical Depth) over SW Asia are consistent with the satellite observations, highlighting for the first time the modulation of the SW Asian dust activity by CasHKI.

Attribution of Exceptional Mean Sea Level Pressure Anomalies South of Australia in August 2014

Attribution of Exceptional Mean Sea Level Pressure Anomalies South of Australia in August 2014

Attribution of Exceptional Mean Sea Level Pressure Anomalies South of Australia in August 2014

August 2014 saw very strong monthly positive mean sea level pressure (MSLP) anomalies and intense daily to multiday MSLP events south of Australia and in the Tasman Sea (Fig. 32.1a). To the west of Tasmania there were monthly anomalies of over 10 hPa (2.4 standard deviations from the mean), the highest on record since 1979 using ERA-Interim reanalysis (ERAint; Dee et al. 2011), or from 1850 using the Hadley Centre Sea Level Pressure analysis (HadSLP2r; Allan and Ansell 2006). Atmospheric blocking west of Tasmania on 10–15 August (Figs. 32.1b,c) featured the highest daily August MSLP anomaly in either record in that location. Blocking was seen in the south Tasman Sea later in the month, including the highest daily MSLP anomaly on record at that location. The spatial distribution of the monthly MSLP anomalies resembles a wave-3 pattern (Fig. 32.1a).

A Tripole Index for the Interdecadal Pacific Oscillation

A new index is developed for the Interdecadal Pacific Oscillation, termed the IPO Tripole Index (TPI). The IPO is associated with a distinct ‘tripole’ pattern of sea surface temperature anomalies (SSTA), with three large centres of action and variations on decadal timescales, evident in the second principal component (PC) of low-pass filtered global SST. The new index is based on the difference between the SSTA averaged over the central equatorial Pacific and the average of the SSTA in the Northwest and Southwest Pacific. The TPI is an easily calculated, non-PC-based index for tracking decadal SST variability associated with the IPO. The TPI time series bears a close resemblance to previously published PC-based indices and has the advantages of being simpler to compute and more consistent with indices used to track the El Nino–Southern Oscillation (ENSO), such as Nino 3.4. The TPI also provides a simple metric in physical units of °C for evaluating decadal and interdecadal variability of SST fields in a straightforward manner, and can be used to evaluate the skill of dynamical decadal prediction systems. Composites of SST and mean sea level pressure anomalies reveal that the IPO has maintained a broadly stable structure across the seven most recent positive and negative epochs that occurred during 1870–2013. The TPI is shown to be a robust and stable representation of the IPO phenomenon in instrumental records, with relatively more variance in decadal than shorter timescales compared to Nino 3.4, due to the explicit inclusion of off-equatorial SST variability associated with the IPO.