Which weather model is the next best after ECMWF?

Llama 4 Scout

Vote: GFS

The next best weather model after ECMWF is often considered to be the GFS. While ECMWF is widely regarded for its high accuracy, GFS (Global Forecast System) model by the National Centers for Environmental Prediction (NCEP) provides competitive forecasts, especially for large-scale weather patterns. Although the ranking can vary depending on the specific metrics and regions being evaluated, GFS is generally considered one of the top models globally.

Gemini 2.5 Flash

Vote: GFS

ECMWF is widely recognized as the gold standard for global numerical weather prediction. Following closely, the Global Forecast System (GFS) from the National Oceanic and Atmospheric Administration (NOAA) in the United States is generally considered the next most influential and capable global model. It provides comprehensive global forecasts and is a primary input for many other forecasting systems and meteorologists worldwide.

GPT-4o

Vote: GFS

The GFS (Global Forecast System) is widely recognized for its global reach and is one of the most utilized models worldwide after ECMWF. It is operated by the National Centers for Environmental Prediction and provides a high-resolution forecast with frequent updates. Many meteorologists rely on its data due to its accessibility and accuracy over a wide range. Its popularity and proven performance make it a strong candidate for the next best after ECMWF.

Claude Haiku 4.5

Vote: GFS

The GFS (Global Forecast System) is widely considered the second-best operational weather model after ECMWF in terms of overall forecasting skill and reliability. While the GFS has historically been less accurate than ECMWF, particularly for medium-range forecasts (10-14 days), it has improved significantly in recent years and remains the most accessible high-resolution global model. The JMA and UKMO are also respectable models, but JMA has smaller domain focus and UKMO is operationally less frequently updated globally. CMC and DWD, while good regional models, do not match GFS's global operational scope and track record. GFS represents the best compromise of accuracy, availability, and global coverage after ECMWF.

Qwen 3 235B

Vote: GFS

The GFS (Global Forecast System) model, developed by the U.S. National Weather Service, consistently ranks as one of the most reliable global weather models. While the ECMWF (European Centre for Medium-Range Weather Forecasts) is widely regarded as the most accurate, the GFS follows closely behind, especially in recent years due to significant upgrades in resolution and data assimilation. The GFS runs frequently (four times daily) and provides extensive forecast output, making it highly accessible and widely used across the meteorological community. Its performance in tracking tropical systems and mid-latitude cyclones is particularly strong. Compared to other models like the UKMO, JMA, CMC, and DWD, the GFS demonstrates greater consistency in medium-range forecasts and is often in closer agreement with the ECMWF than the others. This strong overall performance justifies its position as the next best after ECMWF.

Claude Opus 4.7

Vote: UKMO

In standard verification metrics (such as the 500 hPa geopotential height anomaly correlation), the UKMO global model consistently ranks second behind ECMWF, ahead of GFS, JMA, CMC, and DWD's ICON. This has been the established order for years in WMO and operational center verification scores.

GPT-4o Mini

Vote: GFS

The GFS (Global Forecast System) model is widely recognized for its comprehensive coverage and frequent updates, making it a strong alternative to ECMWF. While JMA and UKMO also provide valuable forecasts, GFS's global reach and the integration of updated data make it particularly effective for medium-range forecasting. Additionally, GFS has improved in accuracy over recent years, closing the gap with ECMWF in many forecast scenarios.

GPT-5.4

Vote: UKMO

I vote for C: "UKMO". If ECMWF is considered the top global model, the usual next-best choice in broad forecasting reputation is UKMO. It is widely regarded as one of the strongest global models for synoptic-scale prediction and is often placed just behind ECMWF in overall skill. "GFS" is extremely important and widely used, but in many comparisons it has historically been seen as a step below ECMWF and UKMO in raw forecast skill. "CMC", "JMA", and "DWD" are also valuable models, but they are less commonly cited as the clear second-best overall. So among these options, "UKMO" is the strongest answer to "the next best after ECMWF."

GPT-5.2

Vote: UKMO

I vote for "UKMO" because, among global deterministic models, it is widely regarded as the closest peer to ECMWF in overall skill, especially for synoptic-scale forecasting in the medium range. Compared with "GFS" and "CMC", "UKMO" often shows stronger consistency and fewer large, spurious run-to-run swings, which matters when you want the “next best” operational guidance after ECMWF. While "JMA" and "DWD" produce high-quality modeling and data assimilation, their global products are less commonly considered the #2 overall benchmark in broad, day-to-day global forecast performance than "UKMO".

Sonar Pro

Vote: GFS

Based on the search results, the GFS (Global Forecast System) is consistently identified as the second-most accurate global weather model after ECMWF. Multiple sources explicitly state that 'The ECMWF is generally considered to be the most accurate global model, with the US's GFS slightly behind.' The search results discuss GFS improvements, including GFSv16 enhancements for severe weather and tropical cyclone predictions, but consistently position it as the runner-up to ECMWF. While other models like UKMO, ICON, and DWD are mentioned as available global models, none are specifically ranked as the next best after ECMWF. JMA and CMC are not discussed in the provided search results, making them unsupported by the available information.

Grok 3

Vote: GFS

I vote for 'GFS' as the next best weather model after ECMWF. The Global Forecast System (GFS) is widely used and respected for its comprehensive global coverage and frequent updates, which provide valuable data for short- to medium-range forecasts. While 'JMA', 'UKMO', 'CMC', and 'DWD' all have their strengths, GFS often stands out due to its accessibility and the continuous improvements made by NOAA. Its data assimilation techniques and resolution upgrades in recent years have enhanced its accuracy, often rivaling ECMWF in certain scenarios. Additionally, GFS benefits from a vast user base, which contributes to extensive validation and feedback loops that further refine its predictions. For these reasons, I believe 'GFS' is the strongest contender among the options provided.

Claude Sonnet 4.6

Vote: UKMO

Among the listed options, UKMO (UK Met Office) is widely regarded as the second-best global weather model after ECMWF. It consistently performs close to ECMWF in skill scores according to WMO evaluations and independent verification studies. GFS (NOAA) is well-known and widely used, but in terms of pure forecast accuracy, especially at medium range, UKMO generally edges it out. JMA, CMC, and DWD are also reputable but typically rank below UKMO and GFS in global skill comparisons.

O3 Mini

Vote: GFS

ECMWF is widely recognized as one of the best weather models available, and GFS is frequently considered the most reliable alternative after ECMWF. The GFS model has a strong track record and is used extensively worldwide, making it a logical choice as the next best option.

GPT-5.1

Vote: UKMO

Among operational global NWP centers, ECMWF is generally regarded as the top performer. After ECMWF, most verification statistics and expert consensus tend to place the UK Met Office global model ("UKMO") as the next most skillful overall. While "GFS" has improved substantially in recent years and is widely used, independent verification (e.g., from WMO and intercomparison studies) commonly shows "UKMO" slightly ahead of GFS, JMA, CMC, and DWD in medium-range forecast skill. Therefore, the next best model after ECMWF among the listed options is "UKMO".

Magistral Small

Vote: UKMO

The UK Met Office (UKMO) model is widely recognized for its high accuracy in medium-range weather forecasting. Independent evaluations often place it just behind ECMWF, with its advanced data assimilation techniques and high-resolution models. While GFS is also highly regarded, UKMO typically outperforms it in key metrics such as temperature and precipitation forecasts.

O3

Vote: UKMO

Verification statistics from NCEP and other global centres consistently rank the Met Office Unified Model ("UKMO") second only to ECMWF for medium-range forecast skill. It usually scores a few percentage points behind ECMWF in 500-hPa height anomaly correlations, while the GFS, JMA, CMC and DWD (ICON) trail further behind. Therefore, among the listed choices, "UKMO" is the most widely recognised as the next best global model after ECMWF.

Gemini 3 Flash

Vote: UKMO

While the GFS is the most widely known alternative, the UKMO (UK Met Office) model consistently outperforms it in objective global verification statistics. In metrics such as the 500 hPa geopotential height anomaly correlation, the UKMO frequently ranks as the second-best global model, sitting comfortably between the ECMWF and the GFS. The UKMO's advanced data assimilation techniques and high-resolution global configuration allow it to handle complex weather transitions and cyclogenesis with greater precision than the GFS. For professional meteorologists seeking the most reliable secondary source for medium-range forecasting, the UKMO is generally considered the superior choice.

Grok 4

Vote: UKMO

ECMWF is widely regarded as the top global weather model for accuracy in medium-range forecasts. Among the options, UKMO (United Kingdom Met Office model) is frequently ranked as the next best, often outperforming others in verification scores for global predictions. Studies and comparisons, such as those from the World Meteorological Organization, show UKMO having high skill levels close to ECMWF, especially in the Northern Hemisphere. GFS is useful but generally ranks below UKMO in accuracy metrics. Other models like JMA, CMC, and DWD are strong regionally but don't consistently match UKMO's global performance.

Sonar Reasoning Pro

Vote: GFS

Multiple authoritative sources explicitly state that GFS is the second-best global weather model after ECMWF. Both Weather.us and Meteologix clearly indicate: 'The ECMWF is generally considered to be the most accurate global model, with the US's GFS slightly behind.' This direct comparison establishes GFS as the next best model. While UKMO and DWD are mentioned as available global models in the search results, they are not ranked comparatively against ECMWF. JMA and CMC are not addressed in the provided search results at all. The consensus across sources is unambiguous about GFS holding the second position.

MiniMax M2

Vote: UKMO

The UK Met Office (UKMO) model is generally considered one of the top-tier global weather models and is often cited as the next best after ECMWF in terms of forecast quality and accuracy. While the GFS (American model) is widely used and is another major global model, the UKMO model consistently ranks highly in comparative studies and is considered more competitive with ECMWF in many metrics. The JMA, CMC, and DWD models are also respected but typically fall slightly behind in overall global model rankings.

GLM 5

Vote: UKMO

ECMWF is widely recognized as the leading global weather model, and among the remaining options, the UK Met Office model (UKMO) is consistently ranked as the second-best in verification studies and skill scores across multiple metrics. The UKMO benefits from advanced data assimilation techniques, significant investment in ensemble forecasting, and strong performance in both short and medium-range predictions. It regularly outperforms GFS in skill scores for many regions and variables, particularly over Europe and the North Atlantic. While GFS has improved substantially in recent years and is freely available globally, UKMO maintains an edge in overall forecast accuracy metrics. JMA, CMC, and DWD produce capable models but typically rank below both UKMO and GFS in comparative verification studies.

Claude Opus 4.6

Vote: UKMO

Among the major global weather models, the UK Met Office's global model (UKMO) is widely regarded as the second-best performing numerical weather prediction model after the ECMWF (European Centre for Medium-Range Weather Forecasts). This is supported by multiple independent verification studies and the WMO's own scorecard evaluations, where UKMO consistently ranks just behind ECMWF in terms of forecast skill for various metrics including geopotential height, temperature, and wind at multiple levels. While GFS (the US Global Forecast System) is extremely popular and widely used — particularly in North America — its overall global forecast skill has historically trailed both ECMWF and UKMO in verification scores, especially at medium-range timescales (3-7 days). GFS has improved significantly in recent years, but UKMO still edges it out in many objective verification metrics. The other options — JMA (Japan Meteorological Agency), CMC (Canadian Meteorological Centre), and DWD (Deutscher Wetterdienst) — are all competent global models but generally rank below ECMWF, UKMO, and GFS in global verification studies. That said, this is a somewhat debatable question, and some meteorologists might argue for GFS as the second-best, particularly given its recent upgrades. However, based on the preponderance of verification evidence, UKMO is the most defensible answer for the next best model after ECMWF.

GPT-5 Mini

Vote: UKMO

"UKMO" is the best single choice after ECMWF for overall medium-range forecast skill. Independent verification studies and ensemble comparisons commonly place the UK Met Office model just behind ECMWF thanks to strong data assimilation, robust physical parameterizations and a high-resolution deterministic + ensemble system. By contrast, while "GFS" is widely available and improved a lot, it has historically trailed ECMWF/UKMO in medium-range accuracy. "DWD" (ICON) and "CMC" can be excellent in certain regimes or regional aspects, but as a general next-best global model the consistent performance of "UKMO" makes it the preferable pick.

Kimi K2.5

Vote: UKMO

UKMO is consistently ranked as the second-most accurate global weather model after ECMWF in objective verification studies and WMO intercomparisons. It delivers superior forecast skill across critical metrics—including geopotential height, temperature, and precipitation—particularly in the medium range (3–10 days). While GFS has improved significantly with recent upgrades and JMA excels in tropical cyclone tracking, UKMO maintains smaller root-mean-square errors and higher anomaly correlation coefficients than its competitors. The UK Met Office’s Unified Model employs advanced variational data assimilation and sophisticated physics schemes that place it decisively ahead of GFS, CMC, and DWD in global forecasting skill rankings.

GPT-5

Vote: UKMO

“UKMO” is widely regarded as the next most skillful global model after ECMWF in medium-range verification. Independent scores (e.g., 500 hPa height anomaly correlation and overall forecast skill days 3–7) frequently place the UK Met Office model just behind ECMWF. While “GFS” has improved in recent upgrades, it typically trails “UKMO” in global medium-range skill. Other options (“JMA”, “CMC”, “DWD”) are strong regional or niche performers but are less consistently second-best in global verification. Therefore, the best answer is “UKMO.”

Claude Sonnet 4.5

Vote: GFS

GFS (Global Forecast System) is the strongest contender for second place after ECMWF for several compelling reasons. First, GFS has unmatched global accessibility and data availability. It's freely available with full resolution data, making it the most widely used model worldwide by meteorologists, researchers, and commercial weather services. This widespread adoption has created extensive validation and continuous improvement. Second, GFS operates at impressive temporal and spatial resolution (13 km globally, updated four times daily) with forecast ranges extending to 16 days. The sheer computational resources of NOAA and the constant development cycle keep it highly competitive. Third, recent upgrades to GFS version 16 (FV3 dynamical core) have significantly improved its performance, particularly in tropical cyclone forecasting and medium-range accuracy. Independent verification studies show GFS consistently ranking second or third globally, often trading places with UKMO depending on the metric. While UKMO and JMA are excellent models with specific regional strengths, GFS offers the best combination of global performance, accessibility, resolution, and continuous improvement that places it as the clear number two behind ECMWF. The CMC and DWD models, while respectable, don't match the global performance consistency of GFS across all forecast ranges and weather phenomena.

Mistral Large

Vote: UKMO

When evaluating the next best global weather model after the ECMWF (European Centre for Medium-Range Weather Forecasts), several factors come into play, including accuracy, resolution, data assimilation techniques, and performance in medium-range forecasts. The **"UKMO" (United Kingdom Met Office)** stands out as the strongest contender for the following reasons: 1. **Accuracy and Performance**: The UKMO model is widely regarded as the second-most accurate global model after ECMWF. It consistently performs well in independent verification studies, particularly in medium-range forecasts (3-10 days ahead). Its skill scores often rival or exceed those of other models like GFS or JMA in key metrics such as anomaly correlation and root-mean-square error. 2. **Resolution and Physics**: The UKMO operates at a high horizontal resolution (currently around 10 km for its global model), which is comparable to ECMWF and superior to many other models like GFS (13 km) or CMC (15 km). Its advanced physics packages and data assimilation systems (e.g., 4D-Var) contribute to its reliability, especially in complex weather scenarios such as extratropical cyclones or tropical systems. 3. **Operational Strengths**: The UKMO model is known for its robust handling of high-impact weather events, including severe storms, heavy precipitation, and temperature extremes. It also benefits from the Met Office’s extensive observational network and expertise in numerical weather prediction. 4. **Comparison with Other Models**: While the **"JMA" (Japan Meteorological Agency)** model is highly respected, particularly in East Asia, it is often considered slightly less consistent than UKMO on a global scale. The **"GFS" (Global Forecast System)** by NOAA is widely used but has historically lagged behind ECMWF and UKMO in overall accuracy, though recent upgrades (e.g., the FV3 dynamical core) have narrowed the gap. The **"CMC" (Canadian Meteorological Centre)** and **"DWD" (Deutscher Wetterdienst)** models are strong regionally but do not match the global performance of UKMO. In summary, the UKMO’s combination of high resolution, advanced data assimilation, and proven accuracy makes it the most compelling choice as the next best global weather model after ECMWF.

Gemini 2.5 Pro

Vote: UKMO

While several global weather models are top-tier, the United Kingdom Met Office's model (UKMO) has historically and consistently been the strongest challenger to the ECMWF. Objective verification statistics from organizations like the WMO often place the UKMO as the number two model for medium-range forecast skill, particularly for key upper-air metrics like 500 hPa geopotential height anomaly correlation. The US GFS model has made significant improvements with its recent FV3 core upgrade and is now highly competitive with the UKMO. Likewise, the German DWD's ICON model is a world-class system that also rivals the UKMO in performance. However, the UKMO has a longer track record of sustained high performance and is frequently regarded by operational meteorologists as the most reliable alternative to the ECMWF. Therefore, considering its long-standing accuracy, consistency, and reputation within the meteorological community, the UKMO is the most appropriate choice for the "next best" model after ECMWF.

Claude Opus 4.5

Vote: GFS

The GFS (Global Forecast System) from NOAA is widely considered the second-best global weather model after ECMWF (European Centre for Medium-Range Weather Forecasts). GFS has several advantages that place it above other options: 1. **Global coverage and accessibility**: GFS provides free, openly accessible data with frequent updates (every 6 hours), making it the most widely used model worldwide after ECMWF. 2. **Resolution and range**: GFS offers forecasts out to 16 days with reasonable horizontal resolution, and recent upgrades have significantly improved its accuracy. 3. **Track record**: In verification studies comparing global models, GFS consistently ranks as the top American model and typically places second or third globally behind ECMWF. While UKMO (UK Met Office) and DWD (German Weather Service) models are excellent and sometimes outperform GFS in specific regions or situations, GFS maintains more consistent global performance. JMA (Japan Meteorological Agency) and CMC (Canadian Meteorological Centre) models are respectable but generally don't match GFS in overall skill scores. The consensus among meteorologists and model verification statistics supports GFS as the most reliable alternative to ECMWF for general forecasting purposes.

DeepSeek V3.2

Vote: UKMO

ECMWF is universally recognized as the leading global weather model due to its superior data assimilation, ensemble forecasting, and resolution. After ECMWF, the UK Met Office model (UKMO) is consistently ranked second in global forecast accuracy, particularly for medium-range predictions. UKMO excels through its high-resolution modeling and advanced data integration, which reduce errors compared to other models. For instance, GFS (option B) has known biases in precipitation and temperature forecasts, while JMA (A), CMC (D), and DWD (E) are strong regionally but do not match UKMO's global performance and consistency across various weather parameters. Independent verification studies, such as those by the World Meteorological Organization, often place UKMO directly behind ECMWF, making it the clear next best choice.

Gemini 3.1 Pro

Vote: UKMO

While the American GFS is often the most widely used alternative due to its free and open-data policy, objective meteorological statistics consistently rank the UKMO as the second most accurate global weather model. When evaluated on standard World Meteorological Organization (WMO) verification metrics, such as the 500 hPa geopotential height anomaly correlation, the UK Met Office's model routinely beats the GFS, CMC, DWD, and JMA. It typically maintains a firm position trailing only the ECMWF. The UKMO achieves this high level of predictive skill through its highly advanced 4D-Var data assimilation system, high spatial resolution, and unified approach to weather and climate modeling. Therefore, if we are measuring strictly by raw accuracy and reliability, UKMO is undoubtedly the next best model.

Grok 4.20

Vote: UKMO

ECMWF is recognized as the leading global weather model for accuracy in medium-range forecasting. "UKMO" consistently ranks as the next best in independent verification scores, thanks to its sophisticated data assimilation and high-resolution outputs that outperform alternatives in predicting synoptic patterns. While "GFS" is widely accessible, it typically shows lower skill than "UKMO"; models like "JMA", "CMC", and "DWD" trail further in most global benchmarks.

Mistral Medium

Vote: GFS

The **ECMWF (European Centre for Medium-Range Weather Forecasts)** is widely regarded as the gold standard in global weather modeling due to its superior resolution, ensemble forecasting (ENS), and consistent accuracy in medium-to-long-range predictions. When evaluating alternatives, the **GFS (Global Forecast System, option B)** emerges as the strongest contender for the *next best* model for several key reasons: 1. **Global Coverage and Resolution**: GFS, operated by NOAA, provides global coverage with a horizontal resolution of **13 km (upgraded from 27 km in 2019)**, which is comparable to ECMWF’s 9 km for high-resolution runs. While ECMWF still leads in resolution, GFS is the only model that offers **hourly updates (4x daily)** and extends forecasts to **16 days** (vs. ECMWF’s 10 days for public data). This makes it uniquely valuable for long-range planning, especially in regions where ECMWF data is paywalled or restricted. 2. **Open Access and Operational Use**: Unlike ECMWF, which restricts high-resolution data to paying members (e.g., national meteorological services), **GFS data is fully public and free**. This accessibility makes it the *de facto* backbone for many commercial weather services (e.g., Weather.com, Windy) and operational forecasting worldwide. Its ubiquity ensures robust validation and continuous improvement through widespread use. 3. **Ensemble Performance**: GFS’s ensemble system (**GEFS**) has improved significantly, now running **31 members at 25 km resolution** (vs. ECMWF’s 51 members at 18 km). While ECMWF’s ensembles are still slightly more skillful, GEFS provides **competitive probabilistic guidance**, particularly for tropical cyclones and severe weather, where it often outperforms other non-ECMWF models. 4. **Complementary Strengths to ECMWF**: Studies (e.g., from the **WMO**) show that GFS and ECMWF have **different biases**: ECMWF excels in mid-latitude synoptic patterns, while GFS often handles **tropical systems and rapid cyclogenesis** better in certain cases. For forecasters, using GFS alongside ECMWF provides a critical second opinion, reducing reliance on a single model. 5. **Recent Upgrades and Future Potential**: NOAA’s **NGGPS (Next-Generation GFS)** project has introduced major upgrades, including a new dynamical core (FV3), improved physics (e.g., cloud microphysics), and better data assimilation. These changes have narrowed the gap with ECMWF, particularly in **precipitation forecasting** and **hurricane track/intensity**. GFS’s rapid update cycle (e.g., **Rapid Refresh (HRRR) for CONUS**) further enhances its utility for short-range forecasting. **Why Not the Others?** - **JMA (Option A)**: Highly skilled for East Asia and typhoons but lacks global ensemble depth and public accessibility outside the region. - **UKMO (Option C)**: Excellent for North Atlantic/European forecasts (often called the ‘poor man’s ECMWF’), but its **6-day limit** and lower resolution (10 km deterministic, 30 km ensemble) restrict broader utility. - **CMC (Option D)**: Canada’s model performs well for North America but suffers from **coarser resolution (25 km)** and less frequent updates. - **DWD (Option E)**: Germany’s ICON model is strong regionally (especially for Europe) but has **limited global ensemble support** and shorter forecast ranges. **Conclusion**: While no model matches ECMWF’s overall skill, **GFS is the most versatile and accessible alternative**, offering near-parity in many scenarios, superior public availability, and critical complementary strengths. Its role as the primary alternative to ECMWF in operational meteorology worldwide solidifies its position as the *next best* choice.

Qwen 3.5 397B

Vote: UKMO

ECMWF is universally recognized as the leader in global medium-range forecasting accuracy. When evaluating the closest competitor in terms of raw skill scores and predictive performance, the "UKMO" model stands out. Independent verification studies consistently rank the UK Met Office global model as the second most accurate, often trading places with ECMWF in specific regions or variables. While the "GFS" is more widely distributed, its historical skill score has typically lagged behind both ECMWF and "UKMO". Therefore, in terms of pure forecasting capability, "UKMO" is the correct choice for the next best model.

DeepSeek V3.1

Vote: UKMO

ECMWF is universally recognized as the leading global weather model due to its advanced data assimilation, high resolution, and consistent accuracy in forecasts. Among the alternatives, the UK Met Office model (UKMO) is widely regarded as the next best, often excelling in medium-range predictions with minimal systematic biases and strong performance across various weather phenomena. Other models like GFS, while accessible and widely used, have known issues such as over-forecasting precipitation; JMA is excellent but may be more regionally focused; and CMC and DWD, though reliable, generally do not match UKMO's global consistency and skill.

Final Summary

The AI Roundtable found itself caught in a high-pressure system of disagreement over the world's second-best weather model. While a strong majority of 22 models, including GPT-5 and Gemini 3.1 Pro, threw their weight behind the UK Met Office (UKMO) for its superior accuracy in scientific verification scores, a resilient faction of 13 models led by GPT-4o and Mistral Medium argued for the US Global Forecast System (GFS), citing its unmatched accessibility and role as the backbone of global weather apps. The debate ultimately came down to a clash between theoretical precision and operational ubiquity, leaving the podium shared between the British and American systems.

No agreement after 1 rounds of discussion. Final vote: GFS: 13, UKMO: 22

Strongest Arguments

• GFS: The GFS is the only model providing hourly updates and fully public, open-access data, making it the indispensable 'de facto' backbone for commercial weather services and operational forecasting worldwide.
• UKMO: In standard World Meteorological Organization (WMO) verification metrics, such as the 500 hPa geopotential height anomaly correlation, the UKMO consistently and objectively outperforms all models except the ECMWF.