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Activity Stream for space Phase2
26 Nov 2024
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MJO and Teleconnections 26 Nov, 04:38 2024
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14 May 2024
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Stratosphere Sub-Project 14 May, 03:29 2024
20 Jul 2023
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Stratosphere Sub-Project 20 Jul, 03:07 2023
09 Dec 2022
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S2S Phase-II Ensembles Sub-project 09 Dec, 10:33 2022
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Thank you for your interest in the topics.
You may notice that the S2S coordinated webinar during the COVID-19 pandemic period (there was one webinar of the Ensemble sub-project). The S2S project organizes the S2S Summit (workshop) in July next year. Please check the S2S Summit website for more info. Your contribution is welcomed.
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25 Oct 2022
20 Oct 2022
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Stratosphere Sub-Project 20 Oct, 21:54 2022
07 Jul 2022
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MJO and Teleconnections 07 Jul, 20:44 2022
08 Apr 2022
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Stratosphere Sub-Project 08 Apr, 04:24 2022
03 Mar 2022
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MJO and Teleconnections 03 Mar, 03:57 2022
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Dear Colleagues,
The MJO-Teleconnections webinars are back by popular demand. Please join us for the February webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project.
Title: The Temperature Anomaly Pattern of the Pacific North/American Teleconnection: Growth and Decay
Speaker: Joseph Clark, Princeton UniversityDate: Thursday, February 24, 2022
Time: 2:00pm EST | 7:00pm UTCAbstract
The Pacific North/American (PNA) teleconnection pattern has a wide range of weather impacts over the Northern Hemisphere during winter. In this study, we examine the Surface Air Temperature (SAT) anomaly pattern associated with the PNA. Both the positive and negative phases of the PNA generate SAT anomalies over the Russian far east, western North America and eastern North America. However, during the positive PNA phase, there is a significant positive SAT anomaly over Siberia that does not occur during the negative PNA phase. Furthermore, during the negative PNA phase, there is a negative SAT anomaly over the subtropical North Pacific that does not occur during the positive PNA phase. The SAT anomaly over Siberia is shown to be associated with a Eurasian wavetrain that exists preferentially during the positive PNA phase.
We examine the thermodynamic energy equation to determine the relevant physical processes driving each of the SAT anomalies associated with the PNA. The symmetric SAT anomalies (occurring during both PNA phases) that overlie the Russian far east, western North America and eastern North America, grow through horizontal advection of the climatological temperature by the anomalous wind and through downgradient diffusive mixing. The asymmetric SAT anomalies, overlying Siberia during the positive PNA and the subtropical North Pacific during the negative PNA, grow through downgradient diffusive mixing only. For both the symmetric and asymmetric SAT anomalies, downgradient diffusive mixing acts to relocate temperature anomalies from higher in the boundary layer downward to the near surface. In addition, all SAT anomalies decay primarily due to longwave radiation. These results reveal a diversity of processes that contribute to the growth and decay of SAT anomalies within the PNA pattern.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meeting recording:
https://gmu.zoom.us/rec/share/k2O4GiPl33A4T0QmJgHzPilHghktLjeIhEyfAhXvmhwe6H2jKLT57ToNeap9TbWD.I-3zVEaPfEF8OmrL?startTime=1645729562000
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30 Oct 2021
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MJO and Teleconnections 30 Oct, 00:44 2021
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Dear Colleagues,
Please join us for the October webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project. This will be the last webinar in 2021.
Title: NAO Influence on the MJO and its Prediction Skill in the Subseasonal-to-Seasonal Prediction Models
Speaker: Hai Lin, Environment and Climate Change CanadaDate: Thursday, October 28, 2021
Time: 11:00am EDT | 3:00pm UTCAbstract
Based on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP) / World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden‐Julian Oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase and amplitude changes following positive and negative NAO events. About 20 days after initialized with a positive (negative) NAO, the forecast MJO appears more frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models, the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong Northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to well represent the NAO influence to improve the simulation and prediction of the MJO.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meeting recording:
https://gmu.zoom.us/rec/share/n-bq5We6HN1y5qV4-KQWs1TbPWH7SHrl2iksdMHjWhY5CqJaU_8J-4Ht750jHA9v.dAuAZ-txuDW08LIr
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19 Oct 2021
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Applications 19 Oct, 01:35 2021
18 Oct 2021
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MJO and Teleconnections 18 Oct, 10:19 2021
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Dear Colleagues,
Please join us for the October webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project. This will be the last webinar in 2021.
Title: NAO Influence on the MJO and its Prediction Skill in the Subseasonal-to-Seasonal Prediction Models
Speaker: Hai Lin, Environment and Climate Change CanadaDate: Thursday, October 28, 2021
Time: 11:00am EDT | 3:00pm UTCAbstract
Based on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP) / World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden‐Julian Oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase and amplitude changes following positive and negative NAO events. About 20 days after initialized with a positive (negative) NAO, the forecast MJO appears more frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models, the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong Northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to well represent the NAO influence to improve the simulation and prediction of the MJO.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
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01 Oct 2021
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MJO and Teleconnections 01 Oct, 23:25 2021
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Dear Colleagues,
Please join us for the September webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project.
Title: Systematic Decomposition, Dynamics and Secular Changes of the Madden-Julian Oscillation
Speaker: Christian Franzke, Pusan National University, Busan, South KoreaDate: Thursday, September 30, 2021
Time: 6:00pm EDT | 10:00pm UTCAbstract
The Madden–Julian Oscillation (MJO) is the dominant form of intra-seasonal variability in the Tropics and has pronounced impacts on surface weather and extremes extending to the extra-tropics. The MJO is a complex convectively coupled phenomenon, which is still poorly represented in the current generation of climate models, and our understanding of its essential dynamics and its influence on the midlatitude circulation is still incomplete. Here, we use a normal-mode decomposition method to decompose the MJO systematically into Kelvin, inertio-gravity (IG), and Rossby-wave components to provide a climatology of the eight MJO phases for the Kelvin, IG, and Rossby-wave components. In my presentation, I will discuss the relative contributions of these modes to the MJO, the extra-tropical response to the MJO and the secular change of the MJO over the last 2 decades and its connection to Western Pacific SST.Meeting Recording:
Topic: S2S/MJO and Teleconnections Monthly Webinar
Date: Sep 30, 2021 05:42 PM Eastern Time (US and Canada)Meeting Recording:
https://gmu.zoom.us/rec/share/6XJSw0D2T3j2cx-J4qPf4sydkRTGhi5WP6z0qOMnu2bDtn09RMI5kosy5UHRITQq.pt01-_UvgW1JtMRG
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27 Aug 2021
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MJO and Teleconnections 27 Aug, 03:00 2021
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Dear Colleagues,
Please join us for the August webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project.
Title: Predictability of Sahelian heatwaves and importance of tropical modes of variability
Speaker: Guigma Kiswendsida, Red Cross Red Crescent Climate CenterDate: Thursday, August 26, 2021
Time: 1:00pm EDT | 5:00pm UTCAbstract
Heatwaves are a growing threat to human health worldwide, but remain poorly documented over Africa. This study addresses the predictability of Sahelian heatwaves during the February-March and April to June seasons as well as their large-scale drivers, with a focus on the role of the Madden-Julian Oscillation (MJO), the equatorial Rossby (ER) and Kelvin (EK) waves. The ECMWF ENS extendedrange forecasting system (ENS-ext), with a forecast horizon of 46 days, is used for the prediction skill assessment, the ERA5 reanalysis being the main reference dataset. Heatwaves are defined as spells of three or more consecutive days, where a given thermal index exceeds both the 75th percentile of its total distribution and the 90th percentile of its calendar day distribution. Tropical modes are obtained through a wavenumber-frequency decomposition of OLR anomalies.The results show that ENS-ext is able to predict heatwaves with relatively good skill out to two to three weeks ahead. The highest forecast scores are obtained for daytime heatwaves and for the shortest leadtimes. With increasing lead-times, heatwaves become more predictable at nighttime than at daytime. Likewise, the prediction skill is initially higher during the February-March season for the shortest leadtimes, whereas for week 2 of the forecast and beyond, the April to June season heatwaves have a better predictability.
Tropical modes significantly affect the occurrence of heatwaves in the Sahel. Depending on their convective phase, they can either increase or decrease their probability. The MJO has the greatest effect, closely followed by the ER wave whereas the EK wave is less important to heatwave occurrence.
The observed relationship between heatwave occurrence and tropical mode activity is relatively well simulated by ENS-ext. The heatwave prediction skill is also found to be higher when the MJO and the ER wave are predicted to be active than when they are predicted to be inactive. Whilst this gain in prediction skill is limited to the first week of forecast for the ER wave, it extends out to the third week for the MJO.
Therefore, improving the representation of tropical modes in models will positively impact heatwave prediction at the subseasonal scale in the Sahel, and gain more time and precision for anticipatory actions.
If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Recording of presentation:
https://docs.google.com/presentation/d/1ABqtjVGczf_oXxc8BlGsYh6kppjrQF06/edit?usp=sharing&ouid=101993203456660376262&rtpof=true&sd=true
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19 Aug 2021
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Dear Colleagues,
Please join us for the August webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project.
Title: Predictability of Sahelian heatwaves and importance of tropical modes of variability
Speaker: Guigma Kiswendsida, Red Cross Red Crescent Climate CenterDate: Thursday, August 26, 2021
Time: 1:00pm EDT | 5:00pm UTCAbstract
Heatwaves are a growing threat to human health worldwide, but remain poorly documented over Africa. This study addresses the predictability of Sahelian heatwaves during the February-March and April to June seasons as well as their large-scale drivers, with a focus on the role of the Madden-Julian Oscillation (MJO), the equatorial Rossby (ER) and Kelvin (EK) waves. The ECMWF ENS extendedrange forecasting system (ENS-ext), with a forecast horizon of 46 days, is used for the prediction skill assessment, the ERA5 reanalysis being the main reference dataset. Heatwaves are defined as spells of three or more consecutive days, where a given thermal index exceeds both the 75th percentile of its total distribution and the 90th percentile of its calendar day distribution. Tropical modes are obtained through a wavenumber-frequency decomposition of OLR anomalies.The results show that ENS-ext is able to predict heatwaves with relatively good skill out to two to three weeks ahead. The highest forecast scores are obtained for daytime heatwaves and for the shortest leadtimes. With increasing lead-times, heatwaves become more predictable at nighttime than at daytime. Likewise, the prediction skill is initially higher during the February-March season for the shortest leadtimes, whereas for week 2 of the forecast and beyond, the April to June season heatwaves have a better predictability.
Tropical modes significantly affect the occurrence of heatwaves in the Sahel. Depending on their convective phase, they can either increase or decrease their probability. The MJO has the greatest effect, closely followed by the ER wave whereas the EK wave is less important to heatwave occurrence.
The observed relationship between heatwave occurrence and tropical mode activity is relatively well simulated by ENS-ext. The heatwave prediction skill is also found to be higher when the MJO and the ER wave are predicted to be active than when they are predicted to be inactive. Whilst this gain in prediction skill is limited to the first week of forecast for the ER wave, it extends out to the third week for the MJO.
Therefore, improving the representation of tropical modes in models will positively impact heatwave prediction at the subseasonal scale in the Sahel, and gain more time and precision for anticipatory actions.
If you would like to attend the webinar, please email to cstan AT gmu DOT edu
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Dear Colleagues,
Please join us for the August webinar hosted by the WWRP/WCRP/S2S/MJO and Teleconnections sub-project.
Title: Predictability of Sahelian heatwaves and importance of tropical modes of variability
Speaker: Guigma Kiswendsida, Red Cross Red Crescent Climate CenterDate: Thursday, August 29, 2021
Time: 1:00pm EDT | 5:00pm UTCAbstract
Heatwaves are a growing threat to human health worldwide, but remain poorly documented over Africa. This study addresses the predictability of Sahelian heatwaves during the February-March and April to June seasons as well as their large-scale drivers, with a focus on the role of the Madden-Julian Oscillation (MJO), the equatorial Rossby (ER) and Kelvin (EK) waves. The ECMWF ENS extendedrange forecasting system (ENS-ext), with a forecast horizon of 46 days, is used for the prediction skill assessment, the ERA5 reanalysis being the main reference dataset. Heatwaves are defined as spells of three or more consecutive days, where a given thermal index exceeds both the 75th percentile of its total distribution and the 90th percentile of its calendar day distribution. Tropical modes are obtained through a wavenumber-frequency decomposition of OLR anomalies.The results show that ENS-ext is able to predict heatwaves with relatively good skill out to two to three weeks ahead. The highest forecast scores are obtained for daytime heatwaves and for the shortest leadtimes. With increasing lead-times, heatwaves become more predictable at nighttime than at daytime. Likewise, the prediction skill is initially higher during the February-March season for the shortest leadtimes, whereas for week 2 of the forecast and beyond, the April to June season heatwaves have a better predictability.
Tropical modes significantly affect the occurrence of heatwaves in the Sahel. Depending on their convective phase, they can either increase or decrease their probability. The MJO has the greatest effect, closely followed by the ER wave whereas the EK wave is less important to heatwave occurrence.
The observed relationship between heatwave occurrence and tropical mode activity is relatively well simulated by ENS-ext. The heatwave prediction skill is also found to be higher when the MJO and the ER wave are predicted to be active than when they are predicted to be inactive. Whilst this gain in prediction skill is limited to the first week of forecast for the ER wave, it extends out to the third week for the MJO.
Therefore, improving the representation of tropical modes in models will positively impact heatwave prediction at the subseasonal scale in the Sahel, and gain more time and precision for anticipatory actions.
If you would like to attend the webinar, please email to cstan AT gmu DOT edu
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30 Jul 2021
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Dear Colleagues,
Please join us for the July webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: Linear inverse modeling: A framework for subseasonal forecasting and the diagnosis of physical sources of forecast skill
Speaker: John Albers, NOAA PSL/CIRES/University of Colorado BoulderDate: Thursday, July 29, 2021
Time: 10:30am EST | 2:30pm UTCAbstract
We introduce the linear inverse model (LIM) framework and discuss its application as a subseasonal forecast model, a free-running climate model, and as a tool to isolate physical sources of subseasonal forecast skill. A LIM is an observationally based, statistical-dynamical model that approximates the chaotic evolution of a ‘coarse-grained’ climate anomaly as the sum of slowly evolving, predictable linear dynamics and rapidly evolving, unpredictable white noise. Here we construct a LIM that models the coupled dynamics of tropical heating, tropical sea-surface temperatures, extratropical tropospheric and stratospheric dynamical variability, and 2m temperature. Using this LIM, we examine the predictability and sources of forecast skill of the North Atlantic Oscillation (NAO) and the record breaking February 2021 North American cold air outbreak (CAO). First, we demonstrate that the LIM can be used to decompose the dynamics that drive NAO variability and predictability. A LIM-based dynamical (‘nonnormal’) filter identifies those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. The joint tropical-stratosphere modes are associated with non-canonical ENSO teleconnections that extend upwards into the lower stratosphere, while the downward propagating mode captures stratospheric NAM anomalies that are commonly associated with sudden stratospheric warmings. The predictable LIM subspace identifies high skill NAO forecasts, both for the LIM and for the state-of-the-art European Centre for Medium-Range Weather Forecasts Integrated Forecast System (IFS), for the 1997-2016 period. For the 2021 CAO, the LIM had high confidence in a cold surge at least 4 weeks in advance of the event onset, which was contrary to the dynamical forecast model guidance. When the LIM’s nonnormal filter is applied to the CAO, it is shown that the cold surge was due primarily to (predictable) SST-stratosphere based teleconnections and (unpredictable) internal variability, with small cold anomaly contributions from the MJO and the early January sudden stratospheric warming.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meeting Recording:
https://gmu.zoom.us/rec/share/MSf8LdLWs0wyFsVMUaB3G5dDwSPXazmho2BUNWDyT71N9o789eV1fY3R3CWsE1sh.S0G8eS1PlxxRFFRT -
Dear Colleagues,
Please join us for the July webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: Linear inverse modeling: A framework for subseasonal forecasting and the diagnosis of physical sources of forecast skill
Speaker: John Albers, NOAA PSL/CIRES/University of Colorado BoulderDate: Thursday, July 29, 2021
Time: 10:30am EST | 2:30pm UTCAbstract
We introduce the linear inverse model (LIM) framework and discuss its application as a subseasonal forecast model, a free-running climate model, and as a tool to isolate physical sources of subseasonal forecast skill. A LIM is an observationally based, statistical-dynamical model that approximates the chaotic evolution of a ‘coarse-grained’ climate anomaly as the sum of slowly evolving, predictable linear dynamics and rapidly evolving, unpredictable white noise. Here we construct a LIM that models the coupled dynamics of tropical heating, tropical sea-surface temperatures, extratropical tropospheric and stratospheric dynamical variability, and 2m temperature. Using this LIM, we examine the predictability and sources of forecast skill of the North Atlantic Oscillation (NAO) and the record breaking February 2021 North American cold air outbreak (CAO). First, we demonstrate that the LIM can be used to decompose the dynamics that drive NAO variability and predictability. A LIM-based dynamical (‘nonnormal’) filter identifies those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. The joint tropical-stratosphere modes are associated with non-canonical ENSO teleconnections that extend upwards into the lower stratosphere, while the downward propagating mode captures stratospheric NAM anomalies that are commonly associated with sudden stratospheric warmings. The predictable LIM subspace identifies high skill NAO forecasts, both for the LIM and for the state-of-the-art European Centre for Medium-Range Weather Forecasts Integrated Forecast System (IFS), for the 1997-2016 period. For the 2021 CAO, the LIM had high confidence in a cold surge at least 4 weeks in advance of the event onset, which was contrary to the dynamical forecast model guidance. When the LIM’s nonnormal filter is applied to the CAO, it is shown that the cold surge was due primarily to (predictable) SST-stratosphere based teleconnections and (unpredictable) internal variability, with small cold anomaly contributions from the MJO and the early January sudden stratospheric warming.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meting Recording:
Topic: S2S/MJO-Teleconnections Monthly Webinar
Date: Jul 29, 2021 09:53 AM Eastern Time (US and Canada)Meeting Recording:
https://gmu.zoom.us/rec/share/MSf8LdLWs0wyFsVMUaB3G5dDwSPXazmho2BUNWDyT71N9o789eV1fY3R3CWsE1sh.S0G8eS1PlxxRFFRT -
Dear Colleagues,
Please join us for the June webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: On the relationship between intraseasonal and interannual teleconnections from Indo-Pacific heating
Speaker: Franco Molteni, ECMWFDate: Thursday, June 24, 2021
Time: 10:30am EST | 2:30pm UTCAbstract
Many studies on the extratropical teleconnections of the Madden-Julian Oscillation (MJO) in boreal-winter have associated an increased frequency of positive North Atlantic Oscillation (NAO) anomalies with the occurrence of MJO phase-3 10 to 15 days earlier, when increased convection is located in the eastern Indian Ocean. Connections between the NAO and the MJO phase-2 (when increased convection is located further west) appear to be weaker in intra-seasonal diagnostics.
On the other hand, on the interannual time scale, teleconnections computed from 2-month or 3-month means indicate a stronger connection of positive NAO with convection in the western-to-central part of the tropical Indian Ocean.This discrepancy between results on the two time-scales are due, to a large extent, to the impact of ENSO on the inter-annual component of Indian Ocean circulation and heating anomalies. This implies that the way in which the seasonal-to-interannual signal is (or is not) filtered out may significantly affect the estimation of intra-seasonal teleconnections. Since the impact of ENSO on both Indian Ocean convection and the NAO varies between early and late winter, results are also dependent on the specific period of the year considered.
In this talk, diabatic heating computed from ERA-5 data (specifically, as a residual between total and adiabatic temperature tendencies) in a 36-year period, and 200-hPa geopotential height from the same re-analysis, are used to investigate the relationship between inter-annual and intra-seasonal teleconnections of MJO-like heating anomalies over the Indian Ocean and the Maritime Continents. Results show that the interannual signal dominates the NAO teleconnection from the Indian Ocean in early winter (Nov.-Dec.); in this period the interannual teleconnections from the western and eastern part of the ocean are anti-correlated over the North Atlantic, and differ significantly from the intra-seasonal signals. Later in the winter (Jan.-Feb.), intraseasonal variability explains a larger fraction of the large-scale diabatic heating variance, and intra-seasonal teleconnections are more similar to those computed without any scale separation.
Finally, results from a set of sub-seasonal ensembles run with the ECMWF coupled model, and initialized on 1 Nov. 1981 to 2016, will be compared with ERA-5 results for the Nov.-Dec. period. Confirming earlier findings on ECMWF sub-seasonal forecasts, a good agreement is found on the patterns of tropical heating variability, but the amplitude of their extratropical teleconnections is significantly under-estimated.
If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meeting Recording:
https://gmu.zoom.us/rec/share/FGzhe-QBQDfHQcR_PRABSEPpLY8kiDSqk7ANn7Kfh7Rs3Y6aliLkYVcQqEuPrCaD.4zpTyrTkNIQqOM10 -
Dear Colleagues,
Please join us for the July webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: Linear inverse modeling: A framework for subseasonal forecasting and the diagnosis of physical sources of forecast skill
Speaker: John Albers, NOAA PSL/CIRES/University of Colorado BoulderDate: Thursday, July 29, 2021
Time: 10:30am EST | 2:30pm UTCAbstract
We introduce the linear inverse model (LIM) framework and discuss its application as a subseasonal forecast model, a free-running climate model, and as a tool to isolate physical sources of subseasonal forecast skill. A LIM is an observationally based, statistical-dynamical model that approximates the chaotic evolution of a ‘coarse-grained’ climate anomaly as the sum of slowly evolving, predictable linear dynamics and rapidly evolving, unpredictable white noise. Here we construct a LIM that models the coupled dynamics of tropical heating, tropical sea-surface temperatures, extratropical tropospheric and stratospheric dynamical variability, and 2m temperature. Using this LIM, we examine the predictability and sources of forecast skill of the North Atlantic Oscillation (NAO) and the record breaking February 2021 North American cold air outbreak (CAO). First, we demonstrate that the LIM can be used to decompose the dynamics that drive NAO variability and predictability. A LIM-based dynamical (‘nonnormal’) filter identifies those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. The joint tropical-stratosphere modes are associated with non-canonical ENSO teleconnections that extend upwards into the lower stratosphere, while the downward propagating mode captures stratospheric NAM anomalies that are commonly associated with sudden stratospheric warmings. The predictable LIM subspace identifies high skill NAO forecasts, both for the LIM and for the state-of-the-art European Centre for Medium-Range Weather Forecasts Integrated Forecast System (IFS), for the 1997-2016 period. For the 2021 CAO, the LIM had high confidence in a cold surge at least 4 weeks in advance of the event onset, which was contrary to the dynamical forecast model guidance. When the LIM’s nonnormal filter is applied to the CAO, it is shown that the cold surge was due primarily to (predictable) SST-stratosphere based teleconnections and (unpredictable) internal variability, with small cold anomaly contributions from the MJO and the early January sudden stratospheric warming.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meting Recording:
https://gmu.zoom.us/rec/share/1tYHPeJKbLGlasTJJlZ1uY5Y2lt_S_383WVnQTBAGj88QA1oNI6RTKYwVu5HLkB-.slwpmxZllNxDwOfS Passcode: 0c6%b#5?
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28 Jun 2021
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MJO and Teleconnections 28 Jun, 21:25 2021
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Dear Colleagues,
Please join us for the June webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: On the relationship between intraseasonal and interannual teleconnections from Indo-Pacific heating
Speaker: Franco Molteni, ECMWFDate: Thursday, June 24, 2021
Time: 10:30am EST | 2:30pm UTCAbstract
Many studies on the extratropical teleconnections of the Madden-Julian Oscillation (MJO) in boreal-winter have associated an increased frequency of positive North Atlantic Oscillation (NAO) anomalies with the occurrence of MJO phase-3 10 to 15 days earlier, when increased convection is located in the eastern Indian Ocean. Connections between the NAO and the MJO phase-2 (when increased convection is located further west) appear to be weaker in intra-seasonal diagnostics.
On the other hand, on the interannual time scale, teleconnections computed from 2-month or 3-month means indicate a stronger connection of positive NAO with convection in the western-to-central part of the tropical Indian Ocean.This discrepancy between results on the two time-scales are due, to a large extent, to the impact of ENSO on the inter-annual component of Indian Ocean circulation and heating anomalies. This implies that the way in which the seasonal-to-interannual signal is (or is not) filtered out may significantly affect the estimation of intra-seasonal teleconnections. Since the impact of ENSO on both Indian Ocean convection and the NAO varies between early and late winter, results are also dependent on the specific period of the year considered.
In this talk, diabatic heating computed from ERA-5 data (specifically, as a residual between total and adiabatic temperature tendencies) in a 36-year period, and 200-hPa geopotential height from the same re-analysis, are used to investigate the relationship between inter-annual and intra-seasonal teleconnections of MJO-like heating anomalies over the Indian Ocean and the Maritime Continents. Results show that the interannual signal dominates the NAO teleconnection from the Indian Ocean in early winter (Nov.-Dec.); in this period the interannual teleconnections from the western and eastern part of the ocean are anti-correlated over the North Atlantic, and differ significantly from the intra-seasonal signals. Later in the winter (Jan.-Feb.), intraseasonal variability explains a larger fraction of the large-scale diabatic heating variance, and intra-seasonal teleconnections are more similar to those computed without any scale separation.
Finally, results from a set of sub-seasonal ensembles run with the ECMWF coupled model, and initialized on 1 Nov. 1981 to 2016, will be compared with ERA-5 results for the Nov.-Dec. period. Confirming earlier findings on ECMWF sub-seasonal forecasts, a good agreement is found on the patterns of tropical heating variability, but the amplitude of their extratropical teleconnections is significantly under-estimated.
If you would like to attend the webinar, please email to cstan AT gmu DOT edu
Meeting Recording:
Topic: S2S/MJO-teleconnections Monthly Webinar
Start Time : Jun 24, 2021 09:52 AMMeeting Recording:
https://gmu.zoom.us/rec/share/FGzhe-QBQDfHQcR_PRABSEPpLY8kiDSqk7ANn7Kfh7Rs3Y6aliLkYVcQqEuPrCaD.4zpTyrTkNIQqOM10
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17 Jun 2021
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MJO and Teleconnections 17 Jun, 23:17 2021
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Dear Colleagues,
Please join us for the June webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: On the relationship between intraseasonal and interannual teleconnections from Indo-Pacific heating
Speaker: Franco Molteni, ECMWFDate: Thursday, June 24, 2021
Time: 10:30am EST | 2:30pm UTCAbstract
Many studies on the extratropical teleconnections of the Madden-Julian Oscillation (MJO) in boreal-winter have associated an increased frequency of positive North Atlantic Oscillation (NAO) anomalies with the occurrence of MJO phase-3 10 to 15 days earlier, when increased convection is located in the eastern Indian Ocean. Connections between the NAO and the MJO phase-2 (when increased convection is located further west) appear to be weaker in intra-seasonal diagnostics.
On the other hand, on the interannual time scale, teleconnections computed from 2-month or 3-month means indicate a stronger connection of positive NAO with convection in the western-to-central part of the tropical Indian Ocean.This discrepancy between results on the two time-scales are due, to a large extent, to the impact of ENSO on the inter-annual component of Indian Ocean circulation and heating anomalies. This implies that the way in which the seasonal-to-interannual signal is (or is not) filtered out may significantly affect the estimation of intra-seasonal teleconnections. Since the impact of ENSO on both Indian Ocean convection and the NAO varies between early and late winter, results are also dependent on the specific period of the year considered.
In this talk, diabatic heating computed from ERA-5 data (specifically, as a residual between total and adiabatic temperature tendencies) in a 36-year period, and 200-hPa geopotential height from the same re-analysis, are used to investigate the relationship between inter-annual and intra-seasonal teleconnections of MJO-like heating anomalies over the Indian Ocean and the Maritime Continents. Results show that the interannual signal dominates the NAO teleconnection from the Indian Ocean in early winter (Nov.-Dec.); in this period the interannual teleconnections from the western and eastern part of the ocean are anti-correlated over the North Atlantic, and differ significantly from the intra-seasonal signals. Later in the winter (Jan.-Feb.), intraseasonal variability explains a larger fraction of the large-scale diabatic heating variance, and intra-seasonal teleconnections are more similar to those computed without any scale separation.
Finally, results from a set of sub-seasonal ensembles run with the ECMWF coupled model, and initialized on 1 Nov. 1981 to 2016, will be compared with ERA-5 results for the Nov.-Dec. period. Confirming earlier findings on ECMWF sub-seasonal forecasts, a good agreement is found on the patterns of tropical heating variability, but the amplitude of their extratropical teleconnections is significantly under-estimated.
If you would like to attend the webinar, please email to cstan AT gmu DOT edu
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21 May 2021
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MJO and Teleconnections 21 May, 03:56 2021
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Dear Colleagues,
Please join us for the May webinar hosted by the WWRP/WCRP/S2S/MJO-Teleconnections sub-project.
Title: The importance of a stratospheric route for MJO teleconnections to the Euro-Atlantic sector
Speaker: Chaim Garfinkel, Hebrew UniversityDate: Thursday, May 27, 2021
Time: 1:30pm EST | 5:30pm UTCAbstract
The effect of the Madden‐Julian Oscillation (MJO) on the Northern Hemisphere wintertime stratospheric polar vortex and major, mid‐winter stratospheric sudden warmings (SSWs) is evaluated using a meteorological reanalysis dataset. The MJO influences the region in the tropospheric North Pacific sector that is most strongly associated with a SSW. Consistent with this, SSWs in the reanalysis record have tended to follow certain MJO phases. SSW events are more predictable if they are preceded by an MJO event. The magnitude of the influence of the MJO on the vortex is comparable to that associated with the Quasi‐Biennial Oscillation and El Niño. The MJO could be used to improve intra‐seasonal projections of the Northern Hemisphere high latitude circulation, and in particular of the tropospheric Northern Annular Mode and North Atlantic Oscillation, at lags exceeding one month. The ability of operational subseasonal forecasting models archiving their data as part of the S2S project to capture this is assessed, and most models are found to underestimate the magnitude of the observed effect.If you would like to attend the webinar, please email to cstan AT gmu DOT edu
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14 May 2021
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MJO and Teleconnections 14 May, 10:01 2021
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and I am waiting for your next wriote ups thanks once again. https://Evolution.org.ua/