Sources of Subseasonal Skill and Predictability in Wintertime California Precipitation Forecasts

2021 ◽  
Author(s):  
Michelle L. L'Heureux ◽  
Michael K. Tippett ◽  
Emily J. Becker
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Longwave Radiation ◽  
Lead Times ◽  
Strongly Correlated ◽  
Zonal Winds ◽  
Wide Range ◽  
Upper Level ◽  
Tropical Sea

AbstractThe relation between the El Niño-Southern Oscillation (ENSO) and California precipitation has been studied extensively and plays a prominent role in seasonal forecasting. However, a wide range of precipitation outcomes on seasonal timescales are possible, even during extreme ENSO states. Here, we investigate prediction skill and its origins on subseasonal timescales. Model predictions of California precipitation are examined using Subseasonal Experiment (SubX) reforecasts for the period 1999–2016, focusing on those from the Flow-Following Icosahedral Model (FIM). Two potential sources of subseasonal predictability are examined: the tropical Pacific Ocean and upper-level zonal winds near California. In both observations and forecasts, the Niño-3.4 index exhibits a weak and insignificant relationship with daily to monthly averages of California precipitation. Likewise, model tropical sea surface temperature and outgoing longwave radiation show only minimal relations with California precipitation forecasts, providing no evidence that flavors of El Niño or tropical modes substantially contribute to the success or failure of subseasonal forecasts. On the other hand, an index for upper-level zonal winds is strongly correlated with precipitation in observations and forecasts, across averaging windows and lead times. The wind index is related to ENSO, but the correlation between the wind index and precipitation remains even after accounting for ENSO phase. Intriguingly, the Niño 3.4 index and California precipitation show a slight but robust negative statistical relation after accounting for the wind index.

scholarly journals Detection of Mesoscale Seasonal and Interannual Variation in the Vegetation of the Amazon Basin

2005 ◽  
Vol 9 (25) ◽  
pp. 1-16
Author(s):  
Miles G. Logsdon ◽  
Robin Weeks ◽  
Milton Smith ◽  
Jeffery E. Richey ◽  
Victoria Ballester ◽  
...  
Keyword(s):  
Time Series ◽  
El Niño ◽  
Amazon Basin ◽  
El Nino ◽  
Southern Oscillation ◽  
Mathematical Framework ◽  
Spectral Change ◽  
Range Analysis ◽  
Local Variance ◽  
Wide Range

Abstract In the Amazon basin, seasonal and interannual spectral changes measured by satellites result from anthropogenic disturbance and from the interaction between climate variation and the surface cover. Measurements of spectral change, and the characterization of that change, provide information concerning the physical processes evident at this mesoscale. A 17-yr sequence of daily Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) images were analyzed to produce a monthly record of surface spectral change encompassing El Niño–Southern Oscillation (ENSO) cycles. Monthly cloud-free composite images from daily AVHRR data were produced by linear filters that minimized the finescale spatial variance and allowed for a wide range analysis within a consistent mathematical framework. Here the use of a minimized local variance (MLV) filter that produced spatially smooth images in which major land-cover boundaries and spatial gradients are clearly represented is discussed. Changes in the configuration of these boundaries and the composition of the landscape elements they defined are described in terms of quantitative changes in landscape pattern. The time series produced with the MLV filter revealed a marked seasonal difference in the pattern of the landscape and structural differences over the length of the time series. Strikingly, the response of the region to drier El Niño years appears to be delayed in the MLV series, the maximum response being in the year following El Niño with little or no change seen during El Niño.

scholarly journals An Analysis of Anomalous Winter and Spring Tornado Frequency by Phase of the El Niño/Southern Oscillation, the Global Wind Oscillation, and the Madden-Julian Oscillation

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Todd W. Moore ◽  
Jennifer M. St. Clair ◽  
Tiffany A. DeBoer
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Madden Julian Oscillation ◽  
La Nina ◽  
Upper Level ◽  
Favorable Conditions

Winter and spring tornado activity tends to be heightened during the La Niña phase of the El Niño/Southern Oscillation and suppressed during the El Niño phase. Despite these tendencies, some La Niña seasons have fewer tornadoes than expected and some El Niño seasons have more than expected. To gain insight into such anomalous seasons, the two La Niña winters and springs with the fewest tornadoes and the two El Niño winters and springs with the most tornadoes between 1979 and 2016 are identified and analyzed in this study. The relationships between daily tornado count and the Global Wind Oscillation and Madden-Julian Oscillation in these anomalous seasons are also explored. Lastly, seasonal and daily composites of upper-level flow, low-level flow and humidity, and atmospheric instability are generated to describe the environmental conditions in the anomalous seasons. The results of this study highlight the potential for large numbers of tornadoes to occur in a season if favorable conditions emerge in association with individual synoptic-scale events, even during phases of the El Niño/Southern Oscillation, Global Wind Oscillation, and Madden-Julian Oscillation that seem to be unfavorable for tornadoes. They also highlight the potential for anomalously few tornadoes in a season even when the oscillations are in favorable phases.

scholarly journals Cluster Analysis of Typhoon Tracks. Part II: Large-Scale Circulation and ENSO

2007 ◽  
Vol 20 (14) ◽  
pp. 3654-3676 ◽  
Author(s):  
Suzana J. Camargo ◽  
Andrew W. Robertson ◽  
Scott J. Gaffney ◽  
Padhraic Smyth ◽  
Michael Ghil
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Vertical Wind Shear ◽  
Longwave Radiation ◽  
Probabilistic Clustering ◽  
Consistent Picture ◽  
Regression Mixture ◽  
Typhoon Tracks

Abstract A new probabilistic clustering method, based on a regression mixture model, is used to describe tropical cyclone (TC) propagation in the western North Pacific (WNP). Seven clusters were obtained and described in Part I of this two-part study. In Part II, the present paper, the large-scale patterns of atmospheric circulation and sea surface temperature associated with each of the clusters are investigated, as well as associations with the phase of the El Niño–Southern Oscillation (ENSO). Composite wind field maps over the WNP provide a physically consistent picture of each TC type, and of its seasonality. Anomalous vorticity and outgoing longwave radiation indicate changes in the monsoon trough associated with different types of TC genesis and trajectory. The steering winds at 500 hPa are more zonal in the straight-moving clusters, with larger meridional components in the recurving ones. Higher values of vertical wind shear in the midlatitudes also accompany the straight-moving tracks, compared to the recurving ones. The influence of ENSO on TC activity over the WNP is clearly discerned in specific clusters. Two of the seven clusters are typical of El Niño events; their genesis locations are shifted southeastward and they are more intense. The largest cluster is recurving, located northwestward, and occurs more often during La Niña events. Two types of recurving and one of straight-moving tracks occur preferentially when the Madden–Julian oscillation is active over the WNP region.

scholarly journals Statistical Analysis of Tropical Cyclones in the Solomon Islands

2018 ◽  
Author(s):  
Edward Maru ◽  
Taiga Shibata ◽  
Kosuke Ito
Keyword(s):  
Tropical Cyclone ◽  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Solomon Islands ◽  
Climatic Variability ◽  
Vertical Wind Shear ◽  
Longwave Radiation ◽  
Relative Vorticity

This paper examines the tropical cyclone (TC) activity in Solomon Islands (SI) using the best track data from Tropical Cyclone Warning Centre Brisbane and Regional Specialized Meteorological Centre Nadi. The long-term trend analysis showed that the frequency of TCs has been decreasing in this region while average TC intensity becomes strong. Then, the datasets were classified according to the phase of Madden-Julian Oscillation (MJO) and the index of El Nino Southern Oscillation (ENSO) provided by Bureau of Meteorology. The MJO has sufficiently influenced TC activity in the SI region with more genesis occurring in phases 6-8, in which the lower outgoing longwave radiation indicates enhanced convective activity. In contrast, TC genesis occurs less frequently in phases 1, 2, and 5. As for the influence of ENSO, more TCs are generated in El Nino period. The TC genesis locations during El Nino (La Nina) period were significantly displaced to the north (south) over SI region. TCs generated during El Nino condition tended to be strong. This paper also argues the modulation in terms of seasonal climatic variability of large-scale environmental conditions such as sea surface temperature, low level relative vorticity, vertical wind shear, and upper level divergence.

Opposite Phases of the Antarctic Oscillation and Relationships with Intraseasonal to Interannual Activity in the Tropics during the Austral Summer

2005 ◽  
Vol 18 (5) ◽  
pp. 702-718 ◽  
Author(s):  
Leila M. V. Carvalho ◽  
Charles Jones ◽  
Tércio Ambrizzi
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Deep Convection ◽  
Low Frequency ◽  
Austral Summer ◽  
Longwave Radiation ◽  
Antarctic Oscillation ◽  
The Tropics ◽  
The Antarctic

Abstract The Antarctic Oscillation (AAO) has been observed as a deep oscillation in the mid- and high southern latitudes. In the present study, the AAO pattern is defined as the leading mode of the empirical orthogonal function (EOF-1) obtained from daily 700-hPa geopotential height anomalies from 1979 to 2000. Here the objective is to identify daily positive and negative AAO phases and relationships with intraseasonal activity in the Tropics and phases of the El Niño–Southern Oscillation (ENSO) during the austral summer [December–January–February (DJF)]. Positive and negative AAO phases are defined when the daily EOF-1 time coefficient is above (or below) one standard deviation of the DJF mean. Composites of low-frequency sea surface temperature variation, 200-hPa zonal wind, and outgoing longwave radiation (OLR) indicate that negative (positive) phases of the AAO are dominant when patterns of SST, convection, and circulation anomalies resemble El Niño (La Niña) phases of ENSO. Enhanced intraseasonal activity from the Tropics to the extratropics of the Southern (Northern) Hemisphere is associated with negative (positive) phases of the AAO. In addition, there is indication that the onset of negative phases of the AAO is related to the propagation of the Madden–Julian oscillation (MJO). Suppression of intraseasonal convective activity over Indonesia is observed in positive AAO phases. It is hypothesized that deep convection in the central tropical Pacific, which is related to either El Niño or eastward-propagating MJO, or a combination of both phenomena, modulates the Southern Hemisphere circulation and favors negative AAO phases during DJF. The alternation of AAO phases seems to be linked to the latitudinal migration of the subtropical upper-level jet and variations in the intensity of the polar jet. This, in turn, affects extratropical cyclone properties, such as origin, minimum/maximum central pressure, and their equatorward propagation.

scholarly journals Global responses of terrestrial productivity to contemporary climatic oscillations

2008 ◽  
Vol 363 (1504) ◽  
pp. 2779-2785 ◽  
Author(s):  
F.I Woodward ◽  
M.R Lomas ◽  
T Quaife
Keyword(s):  
Time Series ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Gross Primary Production ◽  
Ecosystem Structure ◽  
Climatic Oscillations ◽  
Enso Events ◽  
The Pacific ◽  
Wide Range

The terrestrial biosphere is subjected to a wide range of natural climatic oscillations. Best known is the El Niño–southern oscillation (ENSO) that exerts globally extensive impacts on crops and natural vegetation. A 50-year time series of ENSO events has been analysed to determine those geographical areas that are reliably impacted by ENSO events. Most areas are impacted by changes in precipitation; however, the Pacific Northwest is warmed by El Niño events. Vegetation gross primary production (GPP) has been simulated for these areas, and tests well against independent satellite observations of the normalized difference vegetation index. Analyses of selected geographical areas indicate that changes in GPP often lead to significant changes in ecosystem structure and dynamics. The Pacific decadal oscillation (PDO) is another climatic oscillation that originates from the Pacific and exerts global impacts that are rather similar to ENSO events. However, the longer period of the PDO provided two phases in the time series with a cool phase from 1951 to 1976 and a warm phase from 1977 to 2002. It was notable that the cool phase of the PDO acted additively with cool ENSO phases to exacerbate drought in the earlier period for the southwest USA. By contrast in India, the cool phase of the PDO appears to reduce the negative impacts of warm ENSO events on crop production.

scholarly journals Evaluation of ENSO Prediction Skill Changes since 2000 Based on Multimodel Hindcasts

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 365
Author(s):  
Shouwen Zhang ◽  
Hui Wang ◽  
Hua Jiang ◽  
Wentao Ma
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Water Volume ◽  
Lead Times ◽  
The North ◽  
Spring Predictability Barrier ◽  
Sea Surface Temperature Anomalies ◽  
Warm Water Volume

In this study, forecast skill over four different periods of global climate change (1982–1999, 1984–1996, 2000–2018, and 2000–2014) is examined using the hindcasts of five models in the North American Multimodel Ensemble. The deterministic evaluation shows that the forecasting skills of the Niño3.4 and Niño3 indexes are much lower during 2000–2018 than during 1982–1999, indicating that the previously reported decline in forecasting skill continues through 2018. The decreases in skill are most significant for the target months from May to August, especially for medium to long lead times, showing that the forecasts suffer more from the effect of the spring predictability barrier (SPB) post-2000. Relationships between the extratropical Pacific signal and the El Niño-Southern Oscillation (ENSO) weakened after 2000, contributing to a reduction in inherent predictability and skills of ENSO, which may be connected with the forecasting skills decline for medium to long lead times. It is a great challenge to predict ENSO using the memory of the local ocean itself because of the weakening intensity of the warm water volume (WWV) and its relationship with ENSO. These changes lead to a significant decrease in the autocorrelation coefficient of the persistence forecast for short to medium lead months. Moreover, for both the Niño3.4 and Niño3 indexes, after 2000, the models tend to further underestimate the sea surface temperature anomalies (SSTAs) in the El Niño developing year but overestimate them in the decaying year. For the probabilistic forecast, the skills post-2000 are also generally lower than pre-2000 in the tropical Pacific, and in particular, they decayed east of 120° W after 2000. Thus, the advantages of different methods, such as dynamic modeling, statistical methods, and machine learning methods, should be integrated to obtain the best applicability to ENSO forecasts and to deal with the current low forecasting skill phenomenon.

scholarly journals The Connection Between the Hadley Circulation and Meridional Structure of Tropical SST during ENSO from 1950 to 1977

2021 ◽  
Author(s):  
Mingxin Yu ◽  
Juan Feng ◽  
Jianping Li ◽  
Ran An
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Hadley Circulation ◽  
Tropical Indian Ocean ◽  
Interdecadal Shift ◽  
El Niño Events ◽  
Sst Warming ◽  
Tropical Sea ◽  
El Nino Events

Abstract The connection between the meridional structure of tropical sea surface temperature (SST) and the Hadley circulation (HC) under the effect of ENSO (El Niño Southern Oscillation) from 1950 to 1977 is studied. We decompose the HC and zonal mean SST into equatorially symmetric (HES for HC, SES for SST) and asymmetric variations (HEA for HC, SEA for SST) to discuss the modulation of their connection by ENSO. During El Niño events from 1950 to 1977, the HC is less sensitive to the different SST meridional structures and expressed by response ratio. The ratio in La Niña and neutral events is around 4, which is equivalent to the result in the climatology. The reason for the decreased ratio during El Niño events is explored. The interdecadal variation in the linkage between the HC and tropical SST is due to a clear interdecadal shift in the impacts of ENSO on the tropical Indian Ocean (TIO) SST. For the period 1950–1977, when El Niño events occur, larger SST warming amplitude is observed over the northern TIO (0°–15°N, 50°–100°E). However, the southern TIO (15°S–0°, 50°–100°E) shows greater warming amplitude during 1980–2016. The anomalous SST variation over the TIO linked to El Niño events alters the meridional SST distribution, inducing anomalies in the meridional circulation. These results can help us to understand the interdecadal modulation by ENSO of the relationship between tropical SST and the HC.

scholarly journals Benchmarking prediction skill in binary El Niño forecasts

2021 ◽  
Author(s):  
Xinjia Hu ◽  
Jan Eichner ◽  
Eberhard Faust ◽  
Holger Kantz
Keyword(s):  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Prediction Method ◽  
Surrogate Data ◽  
Prediction Skill ◽  
Lead Times ◽  
Small Data ◽  
Predictive Skill ◽  
Forecast Validation

AbstractReliable El Niño Southern Oscillation (ENSO) prediction at seasonal-to-interannual lead times would be critical for different stakeholders to conduct suitable management. In recent years, new methods combining climate network analysis with El Niño prediction claim that they can predict El Niño up to 1 year in advance by overcoming the spring barrier problem (SPB). Usually this kind of method develops an index representing the relationship between different nodes in El Niño related basins, and the index crossing a certain threshold is taken as the warning of an El Niño event in the next few months. How well the prediction performs should be measured in order to estimate any improvements. However, the amount of El Niño recordings in the available data is limited, therefore it is difficult to validate whether these methods are truly predictive or their success is merely a result of chance. We propose a benchmarking method by surrogate data for a quantitative forecast validation for small data sets. We apply this method to a naïve prediction of El Niño events based on the Oscillation Niño Index (ONI) time series, where we build a data-based prediction scheme using the index series itself as input. In order to assess the network-based El Niño prediction method, we reproduce two different climate network-based forecasts and apply our method to compare the prediction skill of all these. Our benchmark shows that using the ONI itself as input to the forecast does not work for moderate lead times, while at least one of the two climate network-based methods has predictive skill well above chance at lead times of about one year.

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