scholarly journals Predicting the Onset of the North Australian Wet Season with the POAMA Dynamical Prediction System

2014 ◽  
Vol 29 (1) ◽  
pp. 150-161 ◽  
Author(s):  
Wasyl Drosdowsky ◽  
Matthew C. Wheeler
Keyword(s):  
Southern Oscillation ◽  
Onset Date ◽  
Wet Season ◽  
Percent Correct ◽  
The North ◽  
Skill Scores ◽  
Ocean Atmosphere ◽  
Agricultural Applications ◽  
Threshold Rainfall ◽  
Atmosphere Model

Abstract A forecast product focusing on the onset of the north Australian wet season using a dynamical ocean–atmosphere model is developed and verified. Onset is defined to occur when a threshold rainfall accumulation of 50 mm is reached from 1 September. This amount has been shown to be useful for agricultural applications, as it is about what is required to generate new plant growth after the usually dry period of June–August. The normal (median) onset date occurs first around Darwin in the north and Cairns in the east in late October, and is progressively later for locations farther inland away from these locations. However, there is significant interannual variability in the onset, and skillful predictions of this can be valuable. The potential of the Predictive Ocean–Atmosphere Model for Australia (POAMA), version 2, for making probabilistic predictions of onset, derived from its multimember ensemble, is shown. Using 50 yr of hindcasts, POAMA is found to skillfully predict the variability of onset, despite a generally dry bias, with the “percent correct” exceeding 70% over about a third of the Northern Territory. In comparison to a previously developed statistical method based solely on El Niño–Southern Oscillation, the POAMA system shows improved skill scores, suggesting that it gains from additional sources of predictability. However, the POAMA hindcasts do not reproduce the observed long-term trend in onset dates over inland regions to an earlier date despite being initialized with the observed warming ocean temperatures. Understanding and modeling this trend should lead to further enhancements in skill.

Probabilistic Forecasts of the Onset of the North Australian Wet Season

2007 ◽  
Vol 135 (10) ◽  
pp. 3506-3520 ◽  
Author(s):  
Fiona Lo ◽  
Matthew C. Wheeler ◽  
Holger Meinke ◽  
Alexis Donald
Keyword(s):  
Southern Oscillation ◽  
Daily Rainfall ◽  
Sea Surface ◽  
Onset Date ◽  
Forecast Method ◽  
Wet Season ◽  
The North ◽  
Probabilistic Forecasts ◽  
Cape York ◽  
Agricultural Industries

Abstract The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July–August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July–August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July–August predictor) forecasts are more skillful using the SOI, long-lead (May–June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.

Investigating the effects of a summer storm on the North Sea stratification using a regional coupled ocean-atmosphere model

2017 ◽  
Vol 67 (2) ◽  
pp. 211-235 ◽  
Author(s):  
Alexandra Gronholz ◽  
Ulf Gräwe ◽  
André Paul ◽  
Michael Schulz
Keyword(s):  
North Sea ◽  
The North ◽  
Ocean Atmosphere ◽  
The North Sea ◽  
Atmosphere Model ◽  
Summer Storm

Atmospheric Teleconnections of Tropical Atlantic Variability: Interhemispheric, Tropical–Extratropical, and Cross-Basin Interactions

2007 ◽  
Vol 20 (5) ◽  
pp. 856-870 ◽  
Author(s):  
Lixin Wu ◽  
Feng He ◽  
Zhengyu Liu ◽  
Chun Li
Keyword(s):  
North Atlantic ◽  
Southern Oscillation ◽  
Wave Train ◽  
Seasonal Migration ◽  
Atmospheric Response ◽  
Tropical Atlantic ◽  
The North ◽  
Atmospheric Teleconnections ◽  
Ocean Atmosphere ◽  
The North Atlantic

Abstract In this paper, the atmospheric teleconnections of the tropical Atlantic SST variability are investigated in a series of coupled ocean–atmosphere modeling experiments. It is found that the tropical Atlantic climate not only displays an apparent interhemispheric link, but also significantly influences the North Atlantic Oscillation (NAO) and the El Niño–Southern Oscillation (ENSO). In spring, the tropical Atlantic SST exhibits an interhemispheric seesaw controlled by the wind–evaporation–SST (WES) feedback that subsequently decays through the mediation of the seasonal migration of the ITCZ. Over the North Atlantic, the tropical Atlantic SST can force a significant coupled NAO–dipole SST response in spring that changes to a coupled wave train–horseshoe SST response in the following summer and fall, and a recurrence of the NAO in the next winter. The seasonal changes of the atmospheric response as well as the recurrence of the next winter’s NAO are driven predominantly by the tropical Atlantic SST itself, while the resulting extratropical SST can enhance the atmospheric response, but it is not a necessary bridge of the winter-to-winter NAO persistency. Over the Pacific, the model demonstrates that the north tropical Atlantic (NTA) SST can also organize an interhemispheric SST seesaw in spring in the eastern equatorial Pacific that subsequently evolves into an ENSO-like pattern in the tropical Pacific through mediation of the ITCZ and equatorial coupled ocean–atmosphere feedback.

scholarly journals Letter to the editor: Are the North Atlantic Oscillation and the Southern Oscillation related in any time-scale?

2000 ◽  
Vol 18 (2) ◽  
pp. 247-251 ◽  
Author(s):  
R. García ◽  
P. Ribera ◽  
L. Gimenoo ◽  
E. Hernández
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Southern Oscillation ◽  
Singular Spectrum Analysis ◽  
Atmospheric Dynamics ◽  
Meteorology And Atmospheric Dynamics ◽  
The North ◽  
Ocean Atmosphere ◽  
The North Atlantic ◽  
The North Atlantic Oscillation

Abstract. The North Atlantic Oscillation (NAO) and the Southern Oscillation (SO) are compared from the standpoint of a possible common temporal scale of oscillation. To do this a cross-spectrum of the temporal series of NAO and SO indices was determined, finding a significant common oscillation of 6-8 years. To assure this finding, both series were decomposed in their main oscillations using singular spectrum analysis (SSA). Resulting reconstructed series of 6-8 years oscillation were then cross-correlated without and with pre-whitened, the latter being significant. The main conclusion is a possible relationship between a common oscillation of 6-8 years' that represents about 20% of the SO variance and about 25% of the NAO variance.Key words: Meteorology and atmospheric dynamics (climatology; ocean-atmosphere interactions)

scholarly journals Moisture Sources for Precipitation Variability over the Arabian Peninsula

2021 ◽  
Author(s):  
Matthew Horan ◽  
Fulden Batibeniz ◽  
Fred Kucharski ◽  
Mansour Almazroui ◽  
Muhammad Adnan Abid ◽  
...  
Keyword(s):  
Arabian Peninsula ◽  
Southern Oscillation ◽  
Source Region ◽  
Western Indian Ocean ◽  
Precipitation Variability ◽  
Congo Basin ◽  
Back Trajectory ◽  
Wet Season ◽  
Moisture Sources ◽  
The North

Abstract We apply a Lagrangian-based moisture back trajectory method on two reanalysis datasets to determine the moisture sources for wet season precipitation over the Arabian Peninsula, defined as land on the Asian Continent to the south of the Turkish border and west of Iran. For this purpose, we make use of evaporative source region between 65°W–120°E and 30°S–60°N which is divided into twelve sub-regions. Our results indicate a north to south spatiotemporal heterogeneity in the characteristics of dominant moisture sources. In the north, moisture for precipitation is mostly sourced from European land and major water bodies, such as Mediterranean and Caspian Seas. Areas further south dependent on moisture transport from the Western Indian Ocean and parts of the African continent. El Nino Southern Oscillation cycle (ENSO) oscillation exhibits an overall positive but sub-seasonally varying influence on the precipitation variability over the region with mostly positive moisture anomalies form all major source regions. A significant drying trend exists over parts of the Peninsula, which is partly attributed to anomalies in the moisture advection from the Congo Basin and South Atlantic Ocean. However, precipitation trends over the terrestrial part of evaporative source region vary across observations and reanalysis datasets, which warrants the need for additional modeling studies to further our understanding in the identification of key processes contributing to the negative trends.

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 Describing rainfall in northern Australia using multiple climate indices

2016 ◽  
Author(s):  
Cassandra Rogers ◽  
Jason Beringer
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Human Populations ◽  
Wet Season ◽  
Australian Monsoon ◽  
The North

Abstract. Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the implications on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas, and in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, inter-annual and decadal time scales. Precipitation trends, climate index trends, and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where inter-annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas inter-annual variability was related to a greater number of climatic phenomena (predominately the El Niño-Southern Oscillation along with Tasman Sea and Indonesian sea surface temperatures). These findings highlight the importance of rainfall variability and the need to understand the climate processes driving variability, and subsequently being able to accurately represent these in climate models in order to project future rainfall patterns in the Northern Territory.

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