The ECMWF-Ext ensemble-mean forecast minimum for 10-hPa zonal-mean zonal winds at 60°N has decreased by more than 10 m/s since October 19. On October 19, the ECMWF-Ext forecast a minimum near 15 m/s in early November. Today's (October 26) initialization forecasts a minimum below 5 m/s. A particularly large revision occurred between the October 23 and 24 initializations, when the forecast minimum decreased from approximately 11 m/s to 6 m/s. Despite these downward revisions, the ensemble-mean forecast remains above the 0 m/s wind reversal threshold. The attached GIF illustrates how the ECMWF-Ext forecasts have evolved over the past week.

What is a Dunkelflaute period, and why does it matter for European power and natural gas markets? Dunkelflaute refers to a sustained period of low wind and solar electricity generation. Reduced renewable generation can increase residual load and the need for other electricity sources, including natural gas-fired generation. The actual market impact depends on demand, available generation, storage, and imports. We explain the meteorological conditions associated with Dunkelflaute and how weather forecasts can help assess these periods in my recent article: worldclimateservice.com/dunk… #Dunkelflaute #EnergyMeteorology

Could Germany experience a multi-day Dunkelflaute period beginning October 29? Today's 00Z AIFS-ENS and ECMWF forecasts indicate a more persistent low Dunkelflaute Risk Index (DRI) signal than GEFS. The percentage of ensemble members forecasting at least 3 consecutive days below the historical 10th-percentile DRI threshold is: • AIFS-ENS: 49% • ECMWF: 37% • GEFS: 13% These percentages cover each model's forecast horizon and represent ensemble-member fractions, not calibrated event probabilities. Explore the Point-in-Time Weather Forecast API: worldclimateservice.com/pit-… #Dunkelflaute #EnergyMeteorology #Germany

Attending Energy Trading Week (ETW) Americas 2026 on October 27–28? Stop by World Climate Service at Booth #34 and meet Kevin Stenson and Jan Dutton! If you work in power or natural gas trading, we'd welcome the opportunity to discuss how weather forecasts and data fit into your trading and risk management workflows. Topics include: • Weather regimes and long-range weather risk • Medium-range, subseasonal, and seasonal forecasts • Historical and real-time weather data APIs 📍 Find us at Booth #34! Check out the attached event floor map to see exactly where we're located. We look forward to connecting with you in person! Want to schedule a meeting with Kevin Stenson? Book a time here: info.prescientweather.com/me… #EnergyTradingWeek #EnergyTrading #EnergyMeteorology #WeatherRisk

The ensemble mean is only one view of the forecast. For an energy meteorologist, the harder task is understanding the range of plausible outcomes, how probabilities are changing, and which scenarios could materially change risk for the trading desk. World Climate Service is designed to support that analysis across medium-range, subseasonal, and seasonal horizons, helping meteorologists compare scenarios, quantify uncertainty, verify forecast skill, and communicate weather risk clearly to power and natural gas traders. We will be demonstrating WCS at our booth during Energy Trading Week Americas 2026 on October 27-28. Schedule a meeting with Kevin Stenson here: info.prescientweather.com/me… #EnergyTradingWeek #EnergyTrading #EnergyMeteorology #PowerTrading #NaturalGas

It's starting to look more likely that El Niño may not achieve the peak Niño3.4 SST anomaly predicted by the seasonal models in the past couple of months. Still a long way to go, however. And there will be little or no practical difference in global weather/climate impacts.

Which climate index has the strongest relationship with ERCOT winter HDDs? Using World Climate Service data, we analyzed 35 climate indices against ERCOT population-weighted heating degree day (HDD) anomalies over 45 winters (1981–82 through 2025–26). The results: ABNA and EPO have the strongest historical correlations with winter HDDs. • ABNA: r = -0.40 • EPO: r = -0.38 (p = 0.01) • Both ranked among the top five indices across all four winter periods analyzed. Lower ABNA and EPO values have historically been associated with higher ERCOT HDDs. What about El Niño? • Niño 3.4 ranked 27th of 35 indices (r = +0.07, p = 0.65). • Of the six strongest El Niño winters, four had below-normal HDDs and two had above-normal HDDs. • HDD anomalies ranged from 14% below normal to 37% above normal. These results do not rule out an ENSO influence on ERCOT winter weather. However, EPO and ABNA have shown substantially stronger historical relationships with winter HDDs. Even the strongest correlation explains only approximately 16% of winter-to-winter HDD variability. These relationships provide historical context, not a forecast. Which ISO and climate index combination should we analyze next? Let us know in the comments. #EnergyMeteorology #EnergyTrading #ERCOT #NaturalGas #WeatherRisk #ABNA #EPO #ENSO

What happens when Google WxNext3 assigns a substantially higher probability to a European weather regime than other forecast models? Today's World Climate Service analysis highlights a significant difference in the 11–15 day Euro-Atlantic weather regime forecasts from ECMWF, AIFS ENS, WxNext3, GEFS, and CMC. Through the medium range, the models show relatively consistent weather regime probabilities. However, WxNext3 diverges considerably in the 11–15 day period. On October 24, WxNext3 assigns a 77% probability of Scandinavian Blocking, compared with 47% from ECMWF, 39% from AIFS ENS, 29% from GEFS, and 24% from CMC. WxNext3 maintains a relatively high probability of Scandinavian Blocking through October 28, although it declines to 52%. What does this mean for energy meteorologists on power and natural gas trading desks? The WxNext3 ensemble members associated with Scandinavian Blocking indicate warmer-than-normal temperatures across much of Europe and below-normal wind speeds. This scenario would suggest: • Reduced heating demand relative to normal temperatures. • Below-normal wind power generation potential. • Different weather-related risks for natural gas demand and power markets. Using the World Climate Service Grams seven-regime forecasts, energy meteorologists can quantify differences in regime probabilities across models, identify the circulation scenarios driving those differences, and evaluate their associated temperature and wind risks. Rather than relying solely on ensemble mean forecasts, weather regime analysis provides additional information about the range of potential weather outcomes and where forecast models disagree. The World Climate Service helps energy meteorologists amplify their meteorological expertise. #EnergyMeteorology #WeatherRegimes #WeatherRisk #EnergyTrading #WeatherForecasting

World Climate Service will be at Energy Trading Week Americas 2026 with a booth focused on the weather decisions that matter to energy meteorologists on power and natural gas trading desks. WCS is built for energy meteorologists who need to turn forecast uncertainty into risk intelligence their traders can use. Rather than relying on a single forecast outcome, WCS helps meteorologists evaluate the range and probability of weather scenarios across medium-range, subseasonal, and seasonal time scales. If you support a power or natural gas trading desk, stop by the World Climate Service booth on October 27-28 to meet the team and discuss how you approach long-range weather risk. Schedule a meeting with Kevin Stenson here: info.prescientweather.com/me… #EnergyTradingWeek #EnergyTrading #EnergyMeteorology #WeatherRisk

The ensemble mean can hide forecast scenarios with materially different impacts. Weather regime analysis helps energy meteorologists identify alternative scenarios, assess their probabilities, and examine associated weather outcomes. Today's World Climate Service (WCS) forecast provides an example using Google's new WxNext3 model. The attached graphics compare North American weather regime forecasts from: • Top: Multi-model ensemble blend (ECMWF, GEFS, CMC, AIFS ENS, and WxNext3). • Bottom: WxNext3 alone. What happens when we isolate ensemble members associated with the Greenland High regime? For October 23, the WxNext3 regime-matched ensemble subset forecasts precipitation anomalies exceeding +3 standard deviations across parts of North Texas. The multi-model blend also shows above-normal precipitation, but with a less pronounced anomaly. Interestingly, WxNext3 assigns a lower probability to the Greenland High regime than the multi-model blend, despite forecasting a more extreme precipitation anomaly within that scenario. For power and natural gas trading desks, this illustrates how regime probabilities and regime-matched ensemble forecasts provide additional information about potential weather outcomes and forecast uncertainty. Today's update also marks the WCS transition from Google's WxNext2 to WxNext3 model in its weather regime analysis. The World Climate Service helps energy meteorologists amplify their meteorological expertise. #EnergyMeteorology #WeatherRisk #EnergyTrading #WeatherRegimes