Interannual Tasmanian Rainfall Variability Associated with Large-Scale Climate Modes

2009 ◽  
Vol 22 (16) ◽  
pp. 4383-4397 ◽  
Author(s):  
Khalia J. Hill ◽  
Agus Santoso ◽  
Matthew H. England
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Climate Modes ◽  
Interannual Rainfall Variability ◽  
East West

Abstract Interannual rainfall variability over Tasmania is examined using observations and reanalysis data. Tasmanian rainfall is dominated by an east–west gradient of mean rainfall and variability. The Pacific–South American mode (PSA), El Niño–Southern Oscillation (ENSO), and the southern annular mode (SAM) each show clear influences on the interannual variability of Tasmanian rainfall. Composites of rainfall during each phase of ENSO and the PSA suggest a notable islandwide influence of these climate modes on Tasmanian rainfall. In contrast, the positive phase of the SAM is associated with drier conditions over the west of the island. The PSA and the SAM project most prominently over the southwest of the island, whereas the ENSO signature is strongest in the north. Empirical orthogonal functions (EOFs) of rainfall over Tasmania show a leading mode (explaining 72% of total variance) of coherent islandwide in-phase anomalies with dominant periods of 2 and 5 yr. The second EOF accounts for ∼14% of total variation, characterized by out-of-phase east–west anomalies, which is likely a combination of all three modes. The EOF1 mode can be attributed to ENSO, the PSA, and to a lesser extent the SAM.

scholarly journals Links between Central West Western Australian Rainfall Variability and Large-Scale Climate Drivers

2013 ◽  
Vol 26 (7) ◽  
pp. 2222-2246 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Western Australia ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Winter Season ◽  
Principal Component ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Past Century ◽  
Drying Trend

Abstract Over the past century, and especially after the 1970s, rainfall observations show an increase (decrease) of the wet summer (winter) season rainfall over northwest (southwest) Western Australia. The rainfall in central west Western Australia (CWWA), however, has exhibited comparatively much weaker coastal trends, but a more prominent inland increase during the wet summer season. Analysis of seasonally averaged rainfall data from a group of stations, representative of both the coastal and inland regions of CWWA, revealed that rainfall trends during the 1958–2010 period in the wet months of November–April were primarily associated with El Niño–Southern Oscillation (ENSO), and with the southern annular mode (SAM) farther inland. During the wet months of May–October, the Indian Ocean dipole (IOD) showed the most robust relationships. Those results hold when the effects of ENSO or IOD are excluded, and were confirmed using a principal component analysis of sea surface temperature (SST) anomalies, rainfall wavelet analyses, and point-by-point correlations of rainfall with global SST anomaly fields. Although speculative, given their long-term averages, reanalysis data suggest that from 1958 to 2010 the increase in CWWA inland rainfall largely is attributable to an increasing cyclonic anomaly trend over CWWA, bringing onshore moist tropical flow to the Pilbara coast. During May–October, the flow anomaly exhibits a transition from an onshore to offshore flow regime in the 2001–10 decade, which is consistent with the observed weaker drying trend during this period.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals Some Factors That Influence Seasonal Precipitation in Argentinean Chaco

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Marcela Hebe González ◽  
María Laura Cariaga ◽  
María de los Milagros Skansi
Keyword(s):  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Spring Precipitation ◽  
Study Region ◽  
Central Brazil ◽  
The North ◽  
Interannual Rainfall Variability ◽  
Oceanic Forcing ◽  
Main Activity

The Chaco plain region in Argentina is located in the north of the country and east of Los Andes where the main activity is the agriculture. As such activity is highly affected by interannual rainfall variability, the influence of some of the principal atmospheric and oceanic forcing is investigated in this paper. Results show that the factors which affect precipitation highly depend on the season and the subregion. The position of the South Atlantic Height and the sea surface temperature in the coast of southern Brazil and Buenos Aires seem to be the factors that affect rainfall, all over the year. The El Niño-Southern Oscillation phenomenon affects summer and spring rainfall and the Southern Annular Mode involves spring precipitation but both only in the east of the study region. Furthermore, enhanced convection in Central Brazil, mainly influences autumn and spring rainfall.

scholarly journals Skill in Simulating Australian Precipitation at the Tropical Edge*

2016 ◽  
Vol 29 (4) ◽  
pp. 1477-1496 ◽  
Author(s):  
Penelope Maher ◽  
Steven C. Sherwood
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Linear Independence ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Southern Annular Mode ◽  
Reanalysis Data ◽  
Hadley Cell ◽  
Model Errors ◽  
Skill Scores

Abstract Expansion of the tropics will likely affect subtropical precipitation, but observed and modeled precipitation trends disagree with each other. Moreover, the dynamic processes at the tropical edge and their interactions with precipitation are not well understood. This study assesses the skill of climate models to reproduce observed Australian precipitation variability at the tropical edge. A multivariate linear independence approach distinguishes between direct (causal) and indirect (circumstantial) precipitation drivers that facilitate clearer attribution of model errors and skill. This approach is applied to observed precipitation and ERA-Interim reanalysis data and a representative subset of four models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and their CMIP3 counterparts. The drivers considered are El Niño–Southern Oscillation, southern annular mode, Indian Ocean dipole, blocking, and four tropical edge metrics (position and intensity of the subtropical ridge and subtropical jet). These models are skillful in representing the covariability of drivers and their influence on precipitation. However, skill scores have not improved in the CMIP5 subset relative to CMIP3 in either respect. The Australian precipitation response to a poleward-located Hadley cell edge remains uncertain, as opposing drying and moistening mechanisms complicate the net response. Higher skill in simulating driver covariability is not consistently mirrored by higher precipitation skill. This provides further evidence that modeled precipitation does not respond correctly to large-scale flow patterns; further improvements in parameterized moist physics are needed before the subtropical precipitation responses can be fully trusted. The multivariate linear independence approach could be applied more widely for practical model evaluation.

scholarly journals An Empirical Seasonal Rainfall Forecasting Model for the Northeast Region of Brazil

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1613
Author(s):  
Rodrigo Lins da Rocha Júnior ◽  
David Duarte Cavalcante Pinto ◽  
Fabrício Daniel dos Santos Silva ◽  
Heliofábio Barros Gomes ◽  
Helber Barros Gomes ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Northern Region ◽  
Empirical Orthogonal Functions ◽  
Rainfall Forecasting ◽  
Orthogonal Functions ◽  
Northeast Region ◽  
Teleconnection Patterns ◽  
The North

The Northeast region of Brazil (NEB) is characterized by large climate variability that causes extreme and long unseasonal wet and dry periods. Despite significant model developments to improve seasonal forecasting for the NEB, the achievement of a satisfactory accuracy often remains a challenge, and forecasting methods aimed at reducing uncertainties regarding future climate are needed. In this work, we implement and assess the performance of an empirical model (EmpM) based on a decomposition of historical data into dominant modes of precipitation and seasonal forecast applied to the NEB domain. We analyzed the model’s performance for the February-March-April quarter and compared its results with forecasts based on data from the North American Multi-model Ensemble (NMME) project for the same period. We found that the first three leading precipitation modes obtained by empirical orthogonal functions (EOF) explained most of the rainfall variability for the season of interest. Thereby, this study focuses on them for the forecast evaluations. A teleconnection analysis shows that most of the variability in precipitation comes from sea surface temperature (SST) anomalies in various areas of the Pacific and the tropical Atlantic. The modes exhibit different spatial patterns across the NEB, with the first being concentrated in the northern half of the region and presenting remarkable associations with the El Niño-Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), both linked to the latitudinal migration of the intertropical convergence zone (ITCZ). As for the second mode, the correlations with oceanic regions and its loading pattern point to the influence of the incursion of frontal systems in the southern NEB. The time series of the third mode implies the influence of a lower frequency mode of variability, probably related to the Interdecadal Pacific Oscillation (IPO). The teleconnection patterns found in the analysis allowed for a reliable forecast of the time series of each mode, which, combined, result in the final rainfall prediction outputted by the model. Overall, the EmpM outperformed the post-processed NMME for most of the NEB, except for some areas along the northern region, where the NMME showed superiority.

scholarly journals Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations

2018 ◽  
Vol 11 (5) ◽  
pp. 1823-1847 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Seasonal Precipitation ◽  
Physical Mechanisms ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyse the sensitivity to air–sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ∼ 200, 90 and 40 km in the zonal direction at the equator, respectively) are analysed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China but improve with finer resolution and coupling. Empirical orthogonal teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air–sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal mean time series. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals On the Remote Drivers of Rainfall Variability in Australia

2009 ◽  
Vol 137 (10) ◽  
pp. 3233-3253 ◽  
Author(s):  
James S. Risbey ◽  
Michael J. Pook ◽  
Peter C. McIntosh ◽  
Matthew C. Wheeler ◽  
Harry H. Hendon
Keyword(s):  
Large Scale ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Southern Annular Mode ◽  
Wet Season ◽  
The North ◽  
Eastern Australia ◽  
Different Seasons ◽  
The Individual

Abstract This work identifies and documents a suite of large-scale drivers of rainfall variability in the Australian region. The key driver in terms of broad influence and impact on rainfall is the El Niño–Southern Oscillation (ENSO). ENSO is related to rainfall over much of the continent at different times, particularly in the north and east, with the regions of influence shifting with the seasons. The Indian Ocean dipole (IOD) is particularly important in the June–October period, which spans much of the wet season in the southwest and southeast where IOD has an influence. ENSO interacts with the IOD in this period such that their separate regions of influence cover the entire continent. Atmospheric blocking also becomes most important during this period and has an influence on rainfall across the southern half of the continent. The Madden–Julian oscillation can influence rainfall in different parts of the continent in different seasons, but its impact is strongest on the monsoonal rains in the north. The influence of the southern annular mode is mostly confined to the southwest and southeast of the continent. The patterns of rainfall relationship to each of the drivers exhibit substantial decadal variability, though the characteristic regions described above do not change markedly. The relationships between large-scale drivers and rainfall are robust to the selection of typical indices used to represent the drivers. In most regions the individual drivers account for less than 20% of monthly rainfall variability, though the drivers relate to a predictable component of this variability. The amount of rainfall variance explained by individual drivers is highest in eastern Australia and in spring, where it approaches 50% in association with ENSO and blocking.

scholarly journals On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

2008 ◽  
Vol 5 (5) ◽  
pp. 2791-2815 ◽  
Author(s):  
D. Verdon-Kidd ◽  
A. S. Kiem
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Global Climate Models ◽  
Phase Changes ◽  
Rainfall Forecasting ◽  
Climate Modes ◽  
Synoptic Patterns ◽  
Decadal Scale

Abstract. In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Impact of the El Niño–Southern Oscillation, Indian Ocean Dipole, and Southern Annular Mode on Daily to Subdaily Rainfall Characteristics in East Australia

2012 ◽  
Vol 140 (5) ◽  
pp. 1665-1682 ◽  
Author(s):  
Alexander Pui ◽  
Ashish Sharma ◽  
Agus Santoso ◽  
Seth Westra
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
El Nino Southern Oscillation ◽  
Rainfall Events ◽  
Annular Mode ◽  
Climate Modes

Abstract The relationship between seasonal aggregate rainfall and large-scale climate modes, particularly the El Niño–Southern Oscillation (ENSO), has been the subject of a significant and ongoing research effort. However, relatively little is known about how the character of individual rainfall events varies as a function of each of these climate modes. This study investigates the change in rainfall occurrence, intensity, and storm interevent time at both daily and subdaily time scales in east Australia, as a function of indices for ENSO, the Indian Ocean dipole (IOD), and the southern annular mode (SAM), with a focus on the cool season months. Long-record datasets have been used to sample a large variety of climate events for better statistical significance. Results using both the daily and subdaily rainfall datasets consistently show that it is the occurrence of rainfall events, rather than the average intensity of rainfall during the events, which is most strongly influenced by each of the climate modes. This is shown to be most likely associated with changes to the time between wet spells. Furthermore, it is found that despite the recent attention in the research literature on other climate modes, ENSO remains the leading driver of rainfall variability over east Australia, particularly farther inland during the winter and spring seasons. These results have important implications for how water resources are managed, as well as how the implications of large-scale climate modes are included in rainfall models to best capture interannual and longer-scale variability.

Interannual Extremes in New Zealand Precipitation Linked to Modes of Southern Hemisphere Climate Variability

2007 ◽  
Vol 20 (21) ◽  
pp. 5418-5440 ◽  
Author(s):  
Caroline C. Ummenhofer ◽  
Matthew H. England
Keyword(s):  
New Zealand ◽  
Climate Variability ◽  
Southern Hemisphere ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Heat Fluxes ◽  
Ekman Transport ◽  
The South ◽  
Climate Modes

Abstract Interannual extremes in New Zealand rainfall and their modulation by modes of Southern Hemisphere climate variability are examined in observations and a coupled climate model. North Island extreme dry (wet) years are characterized by locally increased (reduced) sea level pressure (SLP), cold (warm) sea surface temperature (SST) anomalies in the southern Tasman Sea and to the north of the island, and coinciding reduced (enhanced) evaporation upstream of the mean southwesterly airflow. During extreme dry (wet) years in South Island precipitation, an enhanced (reduced) meridional SLP gradient occurs, with circumpolar strengthened (weakened) subpolar westerlies and an easterly (westerly) anomaly in zonal wind in the subtropics. As a result, via Ekman transport, anomalously cold (warm) SST appears under the subpolar westerlies, while anomalies of the opposite sign occur farther north. The phase and magnitude of the resulting SST and evaporation anomalies cannot account for the rainfall extremes over the South Island, suggesting a purely atmospheric mode of variability as the driving factor, in this case the Southern Annular Mode (SAM). New Zealand rainfall variability is predominantly modulated by two Southern Hemisphere climate modes, namely, the El Niño–Southern Oscillation (ENSO) and the SAM, with a latitudinal gradation in influence of the respective phenomena, and a notable interaction with orographic features. While this heterogeneity is apparent both latitudinally and as a result of orographic effects, climate modes can force local rainfall anomalies with considerable variations across both islands. North Island precipitation is for the most part regulated by both local air–sea heat fluxes and circulation changes associated with the tropical ENSO mode. In contrast, for the South Island the influence of the large-scale general atmospheric circulation dominates, especially via the strength and position of the subpolar westerlies, which are modulated by the extratropical SAM.

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