scholarly journals Lagged Oceanic Effects on the East African Short Rains

2021 ◽  
Author(s):  
Erik W Kolstad ◽  
David MacLeod
Keyword(s):  
El Niño ◽  
Statistical Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Forecast Errors ◽  
Seasonal Forecasts ◽  
East African ◽  
Forecast Performance ◽  
Dry Conditions ◽  
Short Rains

Abstract The East African ‘short rains’ in October–December (OND) exhibit large interannual variability. Drought and flooding are not unusual, and long-range rainfall forecasts can guide planning and preparedness. Although seasonal forecasts based on dynamical models are making inroads, statistical models based on sea surface temperature (SST) precursors are still widely used. It is important to better understand the sources of skill of statistical models and why they sometimes fail. Here, we define a linear regression model, where the August states of El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) predict about 40% of the short rains variability in 1950–2020. The forecast errors are traced back to the initial SSTs: toowet (too-dry) forecasts are linked linearly to positive (negative) initial ENSO and IOD states in August. The link to the initial IOD state is mediated by IOD between August and OND, highlighting a physical mechanism for prediction busts. We also identify asymmetry and nonlinearity: when ENSO and/or the IOD are positive in August, the range and variance of OND forecast errors are larger than when the SST indices are negative. Upfront adjustments of predictions conditional on initial SSTs would have helped in some years with large forecast busts, such as the dry 1987 season during a major El Niño, for which the model erroneously predicts copious rainfall, but it would have exacerbated the forecast performance in the wet 2019 season, when the IOD was strongly positive and the model predicts too-dry conditions.

scholarly journals The Moderate Impact of the 2015 El Niño over East Africa and Its Representation in Seasonal Reforecasts

2019 ◽  
Vol 32 (22) ◽  
pp. 7989-8001 ◽  
Author(s):  
David MacLeod ◽  
Cyril Caminade
Keyword(s):  
Indian Ocean ◽  
East Africa ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Lower Troposphere ◽  
Eastern Indian Ocean ◽  
East African ◽  
The Indian Ocean ◽  
Short Rains

Abstract El Niño–Southern Oscillation (ENSO) has large socioeconomic impacts worldwide. The positive phase of ENSO, El Niño, has been linked to intense rainfall over East Africa during the short rains season (October–December). However, we show here that during the extremely strong 2015 El Niño the precipitation anomaly over most of East Africa during the short rains season was less intense than experienced during previous El Niños, linked to less intense easterlies over the Indian Ocean. This moderate impact was not indicated by reforecasts from the ECMWF operational seasonal forecasting system, SEAS5, which instead forecast large probabilities of an extreme wet signal, with stronger easterly anomalies over the surface of the Indian Ocean and a colder eastern Indian Ocean/western Pacific than was observed. To confirm the relationship of the eastern Indian Ocean to East African rainfall in the forecast for 2015, atmospheric relaxation experiments are carried out that constrain the east Indian Ocean lower troposphere to reanalysis. By doing so the strong wet forecast signal is reduced. These results raise the possibility that link between ENSO and Indian Ocean dipole events is too strong in the ECMWF dynamical seasonal forecast system and that model predictions for the East African short rains rainfall during strong El Niño events may have a bias toward high probabilities of wet conditions.

Did the ECMWF Seasonal Forecast Model Outperform Statistical ENSO Forecast Models over the Last 15 Years?

2005 ◽  
Vol 18 (16) ◽  
pp. 3240-3249 ◽  
Author(s):  
Geert Jan van Oldenborgh ◽  
Magdalena A. Balmaseda ◽  
Laura Ferranti ◽  
Timothy N. Stockdale ◽  
David L. T. Anderson
Keyword(s):  
El Niño ◽  
Statistical Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Forecast Model ◽  
Seasonal Forecasts ◽  
Weather Forecasts ◽  
Forecast Models ◽  
System 2 ◽  
System 1

Abstract The European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts since 1997 with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification. Seasonal predictability is to a large extent due to the El Niño–Southern Oscillation (ENSO) climate oscillations. ENSO predictions of the ECMWF models are compared with those of statistical models, some of which are used operationally. The relative skill depends strongly on the season. The dynamical models are better at forecasting the onset of El Niño or La Niña in boreal spring to summer. The statistical models are comparable at predicting the evolution of an event in boreal fall and winter.

scholarly journals Three Putative Types of El Niño Revealed by Spatial Variability in Impact on Australian Wheat Yield

2005 ◽  
Vol 18 (10) ◽  
pp. 1566-1574 ◽  
Author(s):  
A. B. Potgieter ◽  
G. L. Hammer ◽  
H. Meinke ◽  
R. C. Stone ◽  
L. Goddard
Keyword(s):  
Spatial Patterns ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Wheat Yield ◽  
Severe Drought ◽  
Seasonal Forecasts ◽  
El Niño Events ◽  
Australian Wheat ◽  
El Nino Events

Abstract The El Niño–Southern Oscillation (ENSO) phenomenon significantly impacts rainfall and ensuing crop yields in many parts of the world. In Australia, El Niño events are often associated with severe drought conditions. However, El Niño events differ spatially and temporally in their manifestations and impacts, reducing the relevance of ENSO-based seasonal forecasts. In this analysis, three putative types of El Niño are identified among the 24 occurrences since the beginning of the twentieth century. The three types are based on coherent spatial patterns (“footprints”) found in the El Niño impact on Australian wheat yield. This bioindicator reveals aligned spatial patterns in rainfall anomalies, indicating linkage to atmospheric drivers. Analysis of the associated ocean–atmosphere dynamics identifies three types of El Niño differing in the timing of onset and location of major ocean temperature and atmospheric pressure anomalies. Potential causal mechanisms associated with these differences in anomaly patterns need to be investigated further using the increasing capabilities of general circulation models. Any improved predictability would be extremely valuable in forecasting effects of individual El Niño events on agricultural systems.

scholarly journals Predictable and Unpredictable Aspects of U.S. West Coast Rainfall and El Niño: Understanding the 2015/16 Event

2019 ◽  
Vol 32 (10) ◽  
pp. 2843-2868 ◽  
Author(s):  
Benjamin A. Cash ◽  
Natalie J. Burls
Keyword(s):  
Pacific Northwest ◽  
West Coast ◽  
El Niño ◽  
El Nino ◽  
Rainfall Variability ◽  
Winter Season ◽  
Seasonal Forecasts ◽  
The North ◽  
Dry Conditions ◽  
The Individual

AbstractCalifornia experienced record-setting drought from 2012 to 2017. Based on both seasonal forecast models and historical associations, there was widespread expectation that the major El Niño event of 2015/16 would result in increased winter-season precipitation and break the drought. However, the 2015/16 winter rainy season ultimately resulted in slightly below-average precipitation and the drought continued. In this work we analyze data from both observations and seasonal forecasts made as part of the North American Multi-Model Ensemble (NMME) to better understand the general relationship between El Niño and U.S. West Coast rainfall, focusing on Southern California (SOCAL) rainfall, Pacific Northwest (PNW) rainfall, and the 2015/16 event. We find that while there is a statistically significant positive correlation between El Niño events and the SOCAL and PNW rainfall anomalies, this relationship explains at most one-third of the observed variance. Examination of hindcasts from the NMME demonstrates that the models are capable of accurately reproducing this observed correlation between tropical Pacific sea surface temperatures and California rainfall when information from the individual ensemble members is retained. However, focusing on the multimodel ensemble mean, which deliberately reduces the influence of unpredicted variability, drastically overestimates the strength of this relationship. Our analysis demonstrates that much of the winter rainfall variability along the U.S. West Coast is dominated by unpredicted variations in the 200-hPa height field and that this same unpredicted variability was largely responsible for the unexpectedly dry conditions in 2015/16.

Seasonal climate summary for the southern hemisphere (autumn 2017): the Great Barrier Reef experiences coral bleaching during El Niño–Southern Oscillation neutral conditions

2019 ◽  
Vol 69 (1) ◽  
pp. 310
Author(s):  
Grant A. Smith
Keyword(s):  
Western Australia ◽  
Coral Bleaching ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Maximum Temperature ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Dry Conditions ◽  
The Mean

Austral autumn 2017 was classified as neutral in terms of the El Niño–Southern Oscillation (ENSO), although tropical rainfall and sub-surface Pacific Ocean temperature anomalies were indicative of a weak La Niña. Despite this, autumn 2017 was anomalously warm formost of Australia, consistent with the warming trend that has been observed for the last several decades due to global warming. The mean temperatures for Queensland, New South Wales, Victoria, Tasmania and South Australiawere all amongst the top 10. The mean maximum temperature for all of Australia was seventh warmest on record, and amongst the top 10 for all states but Western Australia, with a region of warmest maximum temperature on record in western Queensland. The mean minimum temperature was also above average nationally, and amongst top 10 for Queensland, Victoria and Tasmania. In terms of rainfall, there were very mixed results, with wetter than average for the east coast, western Victoria and parts of Western Australia, and drier than average for western Tasmania, western Queensland, the southeastern portion of the Northern Territory and the far western portion of Western Australia. Dry conditions in Tasmania and southwest Western Australia were likely due to a positive Southern Annular Mode, and the broader west coast and central dry conditions were likely due to cooler eastern Indian Ocean sea-surface temperatures (SSTs) that limited the supply of moisture available to the atmosphere across the country. Other significant events during autumn 2017 were the coral bleaching in the Great Barrier Reef (GBR), cyclone Debbie andmuch lower than average Antarctic sea-ice extent. Coral bleaching in the GBR is usually associated on broad scales with strong El Niño events but is becoming more common in ENSO neutral years due to global warming. The southern GBR was saved from warm SST anomalies by severe tropical cyclone Debbie which caused ocean cooling in late March and flooding in Queensland and New SouthWales. The Antarctic sea-ice extent was second lowest on record for autumn, with the March extent being lowest on record.

ENSO and the Spatial Extent of Interannual Precipitation Extremes in Tropical Land Areas

2005 ◽  
Vol 18 (23) ◽  
pp. 5095-5109 ◽  
Author(s):  
Bradfield Lyon ◽  
Anthony G. Barnston
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Precipitation Extremes ◽  
Spatial Extent ◽  
Human Populations ◽  
Enso Events ◽  
Dry Conditions ◽  
Negative Impacts

Abstract The extreme phases of El Niño–Southern Oscillation (ENSO) are known to dominate the interannual variability of tropical rainfall. However, the relationship between ENSO and the spatial extent of drought and excessively wet conditions is an important characteristic of the tropical climate that has received relatively less attention from researchers. Here, a standardized precipitation index is computed from monthly rainfall analyses and the temporal variability of the spatial extent of such extremes, for various levels of severity, is examined from a Tropics-wide perspective (land areas only, 30°S–30°N). Maxima in the spatial extent of both precipitation extremes are compared across multiple ENSO events that occurred during the period 1950–2003. The focus on tropical land areas is motivated by the numerous, often negative, impacts of ENSO-related precipitation variability on human populations. Results show that major peaks in the spatial extent of drought and excessively wet conditions are generally associated with extreme phases of ENSO. A remarkably robust linear relationship is documented between the spatial extent of drought in the Tropics and El Niño strength (based on Niño-3.4 sea surface temperature anomalies), with a comparatively weaker relationship for La Niña and excessive wetness. Both conditions are found to increase by about a factor of 2 between strong and weak ENSO events, and in several locations they are shown to be more likely during ENSO events than at all other times, especially for severe categories. Relatively stronger El Niño events during recent decades are associated with increased drought extent in tropical land areas with increasing surface temperatures likely acting to exacerbate these dry conditions.

Towards onset: shades of ENSO skill

2020 ◽  
Author(s):  
Dougal Squire ◽  
James Risbey
Keyword(s):  
El Niño ◽  
Statistical Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Skill Score ◽  
Forecast Skill ◽  
The North ◽  
Forecast Models ◽  
The Impact ◽  
Better Than

<p>Climate forecast skill for the El Nino-Southern Oscillation (ENSO) is better than chance, but has increased little in recent decades. Further, the relative skill of dynamical and statistical models varies in skill assessments, depending on choices made about how to evaluate the forecasts. Using a suite of models from the North American Multi-Model Ensemble (NMME) archive we outline the consequences for skill of how the bias corrections and forecast anomalies are formed. We show that the method for computing forecast anomalies is such a critical part of the provenance of a skill score that any score for forecast anomalies lacking clarity about the method is open to wide interpretation. Many assessments of hindcast skill are likely to be overestimates of attainable forecast skill because the hindcast anomalies are informed by observations over the period assessed that would not be available to a real forecast. The relative skill rankings of forecast models can change between hindcast and forecast systems because the impact of model bias on skill is sensitive to the ways in which forecast anomalies are formed. Dynamical models are found to be more skillful than simple statistical models for forecasting the onset of El Nino events.</p>

scholarly journals Oceanic Origins of Historical Southwest Asia Precipitation During the Boreal Cold Season

2017 ◽  
Vol 30 (8) ◽  
pp. 2885-2903 ◽  
Author(s):  
Andrew Hoell ◽  
Mathew Barlow ◽  
Forest Cannon ◽  
Taiyi Xu
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Atmospheric Model ◽  
Cold Season ◽  
Southwest Asia ◽  
Regional Variability ◽  
Model Simulations ◽  
Dry Conditions

While a strong influence on cold season southwest Asia precipitation by Pacific sea surface temperatures (SSTs) has been previously established, the scarcity of southwest Asia precipitation observations prior to 1960 renders the region’s long-term precipitation history largely unknown. Here a large ensemble of atmospheric model simulations forced by observed time-varying boundary conditions for 1901–2012 is used to examine the long-term sensitivity of November–April southwest Asia precipitation to Pacific SSTs. It is first established that the models are able to reproduce the key features of regional variability during the best-observed 1960–2005 period and then the pre-1960 variability is investigated using the model simulations. During the 1960–2005 period, both the mean precipitation and the two leading modes of precipitation variability during November–April are reasonably simulated by the atmospheric models, which include the previously identified relationships with El Niño–Southern Oscillation (ENSO) and the multidecadal warming of Indo-Pacific SSTs. Over the full 1901–2012 period, there are notable variations in precipitation and in the strength of the SST influence. A long-term drying of the region is associated with the Indo-Pacific warming, with a nearly 10% reduction in westernmost southwest Asia precipitation during 1938–2012. The influence of ENSO on southwest Asia precipitation varied in strength throughout the period: strong prior to the 1950s, weak between 1950 and 1980, and strongest after the 1980s. These variations were not antisymmetric between ENSO phases. El Niño was persistently related with anomalously wet conditions throughout 1901–2012, whereas La Niña was not closely linked to precipitation anomalies prior to the 1970s but has been associated with exceptionally dry conditions thereafter.

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