SACRUS

The slower the progression once to Sun night / Monday the retreating high will allow the secondary low to gain latitude as the Euro shows and phasing capture. Timing is key and Euro /UK were leading there (so far)

Records: Highs: EWR: 62 (2006) NYC: 62 (1951) LGA: 61 (2006) JFK: 56 (2013) Lows: EWR: -3 (1985) NYC: 0 (1994) LGA: 0 (1994) JFK: 3 (1994) Historical: 1606: 2,000 people died around the Severn Estuary as the result of severe flooding along the Severn River in England. (Ref. Wilson Wx. History) 1852: The temperature fell to 20 °F in Jacksonville, Florida and 22 °F in St. Augustine, Florida. (Ref. Early American Winters Vol. II 1821-1870 by David M. Ludlum pp. 109 - 110) 1863: The famous "Mud March" begins in the Fredericksburg area of Virginia. 1883: Yuma, Arizona, sets its all-time record low of 22 degrees. The record is tied in 1911 and again in 1937. 1917: 16 inches of snow falls in the Twin Cities, MN. (Ref. AccWeather Weather History) 1933: The greatest snowfall officially fell at Phoenix, AZ reaching one inch. Four years to the day later, another snowfall of one inch fell. (Ref. Wilson Wx. History) 1937 - The wettest Inaugural Day of record with 1.77 inches of rain in 24 hours. Temperatures were only in the 30s as Franklin D. Roosevelt was sworm in for his second term. (David Ludlum) 1933: Phoenix, Arizona, receives light snow between 7:55 pm and 9:25 pm 1937 - The wettest Inaugural Day of record with 1.77 inches of rain in 24 hours. Temperatures were only in the 30s as Franklin D. Roosevelt was sworm in for his second term. (David Ludlum) 1943 - Strange vertical antics took place in the Black Hills of South Dakota. While the temperature at Deadwood was a frigid 16 degrees below zero, the town of Lead, just a mile and a half away, but 600 feet higher in elevation, reported a balmy 52 degree reading. (David Ludlum) 1943: Strange vertical temperature antics took place in the Black Hills of South Dakota. While the temperature at Deadwood was a frigid 16 degrees below zero, the town of Lead, just a mile and a half away, but 600 feet higher in elevation, reported a balmy 52 degree reading. (David Ludlum) 1951: The maximum temperature for the date in Washington, DC is 70°F. (Ref. Washington Weather Records - KDCA) 1954 - The temperature at Rogers Pass, MT, plunged to 70 degrees below zero to establish a new record for the continental U.S. (David Ludlum) 1961: The "Kennedy Inaugural snowstorm" belted the mid-Atlantic and New England states. Up to 29 inches of snow fell in northern New Jersey and southeastern New York. Areas north and west of Boston, MA received over two feet. This was the 2nd of three major snowstorms during the 1960-61 winter season across the northeastern U.S. (Ref. Wilson Wx. History) 1978 - A paralyzing "Nor'easter" produced a record 21 inches of snow at Boston, 15 to 20 inches in Rhode Island, and one to two feet of snow in Pennsylvania. Winds along the coast of Connecticut gusted to 70 mph. (David Ludlum) 1982: Just over 17 inches of snow fell in the Twin Cities, MN. Amazingly, this record was to be outdone within two days. (Ref. AccWeather Weather History) 1984: An Arctic cold wave in the east through the 22nd claimed 42 lives across 14 states. One of the coldest readings was -40° at Minong, WI. Subzero readings were measured from the Rockies to New England. (Ref. AccWeather Weather History) 1985: The minimum temperature for the date is -2 °F. in Washington, DC. (Ref. Washington Weather Records - KDCA) A major Arctic outbreak brought extreme cold to much of the central and eastern U.S. Many all time record lows were set, including: Chicago, IL -27° (daytime high of -4 with a wind chill as low as -77°), Nashville, TN -16° (broken the next day), Asheville, NC -13° (broken the next day) and Raleigh/Durham, NC -3° (broken the next day). Even New Orleans was in the deep freeze with a low of 15°. Fort Wayne, INrecorded their coldest overall day, with a high of -11° and a low of -22°. South Bend, IN set their coldest January high temperature, at -6°. Quincy, IL set their January record low with -21°. St. Louis & Columbia, MO recorded their all-time coldest wind chill readings of -48°& -44°. Residents in Birmingham, AL woke up to an inch of snow on the ground and temperatures in the deep freeze. Readings remained in the single digits all day. The high temperature at Muscle Shoals in the northern part of Alabama never got above 0° that day. The extreme cold actually caused television cable wires to shrink, resulting in service disruptions across the state of Virginia.=(Ref. Wilson Wx. History) (Ref. AccWeather Weather History) 1987 - Gale force winds lingered along the northern Atlantic coast in the wake of a holiday weekend storm. High winds along the eastern slopes of the Northern Rockies gusted to 67 mph at Livingston MT, and high winds in southern California gusted to 70 mph near San Bernardino. (National Weather Summary) (Storm Data) 1988 - A storm in the Upper Midwest produced heavy snow and gale force winds. Up to 27.5 inches of snow was reported along the Lake Superior shoreline of Michigan, with 22 inches at Marquette. (National Weather Summary) (Storm Data) 1989 - The temperature in the Washington D.C. area warmed into the lower 50s for the Presidential Inauguration during the late morning hours, before gusty northwest winds ushered in colder air that afternoon. (National Weather Summary) 1990 - While heavy thunderstorm rains drenched the Central Gulf Coast States, with 4.23 inches reported at Centreville AL in 24 hours, unseasonably warm weather continued across Florida. Five cities in Florida reported record high temperatures for the date. Tampa FL equalled their record high for January of 85 degrees. (National Weather Summary) 1993: A fast moving 980-millibar storm (28.94 inches of mercury) produced high winds across the Pacific Northwest. A wind gust to 64 mph occurred at the Sea-tac airport in Seattle, WA; their 2nd highest wind gust ever recorded at that location. Winds gusted to near 100 mph at the mouth of the Columbia River. Over 750,000 people in the vicinity of Puget Sound lost power. Damage was severe, with 79 homes destroyed and 581 suffering major damage. In Oregon, wind gusts hit 89 mph at Netarts and 86 mph at Cape Blanco. The storm caused $130 million dollars in damage.(Ref. Wilson Wx. History) Heavy rains across Louisiana caused flooding. Nearly eleven inches fell in Lafayette, LA along with nine inches in Baton Rouge. (Ref. AccWeather Weather History) 1994: Relentless lake effect snow squalls dumped nearly 60 inches of snow at Adams, NY in only 17 hours The three day snowfall total in the town exceeded 100 inches, one of the greatest lake effect snowfall totals ever recorded. Frigid conditions persisted over the northeastern U.S. Rangeley, ME was the cold spot in the nation with a temperature of -45°. First Connecticut Lake, NH dropped to -44°. South Bend, IN completed its longest stretch of sub-zero weather at 64 hours. Both Pittsburgh, PA and Cleveland, OH also completed their longest stretch of subzero readings on record, with 52 and 56 consecutive hours, respectively. (Ref. Wilson Wx. History) Very cold conditions over the Northeast: Cleveland, OH and Pittsburgh, PA ended their longest continuous subzero periods with fifty-two and fifty-six hours respectively. Temperature bottomed out at -45 °F at Rangeley, ME. (Ref. AccWeather Weather History) 2006: A winter storm moved across northern Illinois during the afternoon and evening hours, continuing into early the next morning. A band of very heavy snow fell across northeast Illinois across Kane County, southeast McHenry County, northwest Cook County, and most of Lake County. Snowfall amounts in this band ranged from 10 to 12 inches. Outside of this heavy band, snow amounts ranged from 6 to 9 inches, but snowfall amounts tapered off quickly across south central DuPage and south central Cook Counties, with those areas receiving 3 to 5 inches. Some of the largest snowfall amounts included 12 inches at Elgin, 11.7 inches at Grayslake, 11.5 inches at Shabbona, 11 inches at Barrington, and 9 inches at Paw Paw. Northwest parts of the state saw ice accumulations around a quarter inch, enhanced by thunderstorms. (Ref. Wilson Wx. History)

15 / 1 off a low of 10 here. Overall cold to much below normal the next 11 days or through the 31st / 1st. Coldest days look to be 1/24-1/25 - perhaps temps at or sub 20 all day then single digit low (coldest since 2019 perhaps) , then again 1/28 - 1/30. The much talked WAA / overrunning and potential secondary developent later Sat (1/24) - Sun (1/25) and into Mon (1/26) and perhaps Tue (1/27 long duration event. Hints at additional energy clipper or southern in the 1/31 period. Beyond there moderation back towards / above normal.

GFS Total QPF: Euro AI AIFS:

06Z Total QPF (NYC) GFS: 0.4 - 0.5 Euro AI AIFS: 0.9 - 1.1 Euro: through 144 looked more or less in line with the 1/20 00Z GEFS: 0.6

Euro total QPF long duration into Tue

00Z QPF Summary NYC GFS: 0.4 GGEM: 0.9- 1.1 UKMET: 0.8 - 1.0 GEFS: 0.4 - 0.6 GEPS (Canadian Ensemble mean QPF): 0.8 - 1.0 Euro AI AIFS: 0.4 - 0.6 ECMWF: Coming.. 1.0

GEFS - mean Total QPF GGEM GEPS

GGEM Total QPF

UKMET Total QPF

GFS Total QPF

Euro AI AIFS QPF

Recent coldest at EWR last 25 years: Bolded 5 and below

Down to 23 here and dropping Coldest air descending onto the upper MId West / G-L

The 18Z Euro was a bit south of 12z but still had snow into the region (north of the GFS). It only is out to 144 at 18z with likely a bit more at H150/H156.

Ill have to check and i dont think we'll quite be in the single digitis in the city / metro areas byt of recent Jan 3 2014 comes to mind. Will need to check (low teens then)

Some flurries / snow squallls into PA with the front, maybe a stray flurry or shower makes it this way. Was up to 33 now clouds / mostly cloudy and down to 30

Your safest bet is to leave Friday or send flowers and stay back and enjoy the snow.

FRom the Mid Atlantic contingent

(A) is Anthony for that run. 32 / 19 here

12Z Guidance (QPF) Jan 24 OOZ to Jan 25 1800 Don or others can you add specific QPF for NYC? I think it'll be helpful to track run to run. GFS: 0 ICON: GGEM (CMC) : 0.75-1.00 UKMET: >1.00 ECMWF: GEFS: GEP: EPS:

Suspect we'll have the typical wax on / wax off windshield wiper suprssed / crushed run to run or model to model through Wed AM before honing in.

im torn between anything or 14+ / go big or go home.

GFS and ECMWF Core vs AI details: (AI) just for reference ECMWF’s AI system (AIFS) is a fully separate, AI-native forecast model, not the traditional ECMWF model with machine learning layered on top. Unlike the main Integrated Forecasting System (IFS), AIFS does not solve physical equations; it uses deep learning trained on decades of reanalysis and operational forecast data to predict the next atmospheric state directly. It ingests similar inputs (pressure, temperature, wind, humidity fields) but produces forecasts via neural networks rather than numerical integration. The operational IFS remains the authoritative, physics-based backbone for warnings, ensembles, and high-impact decision support. ECMWF runs AIFS in parallel, comparing skill, speed, and bias against IFS at multiple lead times. In medium-range forecasts (≈3–10 days), AIFS has shown skill comparable to—and in some metrics better than—the full physics model, at a fraction of the computational cost. Key takeaways Separate model: AIFS is independent from IFS, not a post-processing or hybrid add-on Massively faster: Enables rapid global forecasts and large ensembles with minimal compute Complementary role: IFS provides physical realism and extremes; AIFS adds speed and pattern skill AIFS (AI Forecasting System): Research & development: 2022–2023 First real-time parallel runs: mid-2023 Publicly released experimental real-time forecasts: 2024 Status today: Operational parallel model (not replacing IFS) ECMWF was the first major global center to run an AI-native global model continuously in real time. -------------------------------------------------------------------------------------------------------------------------------------- NOAA’s GFS AI efforts are not a single AI-native replacement model like ECMWF’s AIFS, but a combination of experimental AI models and AI-enhanced components run alongside the main GFS. The operational GFS remains a fully physics-based numerical weather prediction system using the FV3 dynamical core. NOAA’s AI models are trained on decades of global reanalysis and past GFS outputs to forecast future atmospheric states directly, without explicitly solving physical equations. These AI forecasts are run in parallel to GFS for evaluation, research, and medium-range pattern guidance rather than operational warnings. In addition, machine learning is increasingly used inside the GFS workflow to improve data quality control, parameterizations, and bias correction. The strategy prioritizes reliability and explainability, with AI enhancing—but not replacing—the core physics model. Key takeaways Hybrid approach: Physics-based GFS plus separate experimental AI models No AI-only operational GFS: AI runs inform and augment forecasts, not replace them Risk-aware path: Emphasis on safety, interpretability, and gradual adoption NOAA (GFS + AI) GFS (physics model): Operational since the 1980s (FV3 core since 2019) NOAA AI global models: Research pilots (ML weather prototypes): 2021–2022 Sustained real-time parallel AI runs: 2023 Expanded evaluation vs GFS: 2024–2025 Status today: Experimental / evaluation only (not operational) NOAA deliberately moved slower and more conservatively than ECMWF. ------------------------------------------------------------------------------------------------------------------------------------ At 96h (Day 4), ECMWF’s physics-based IFS/HRES and the AI model (AIFS) are often very close on large-scale “pattern” skill (e.g., 500-hPa height), with AIFS frequently matching IFS despite being cheaper to run. At 144h (Day 6), verification shown by ECMWF commonly has AIFS slightly ahead on upper-air headline scores (ACC/RMSE for fields like 500-hPa geopotential height), which is exactly where ML models tend to shine. At 168h (Day 7), AIFS’ advantage can persist for broad circulation patterns, but that does not mean it’s “better at everything.” IFS still tends to win on fine-scale/high-impact details that depend on explicit physics and higher resolution (e.g., local precipitation structure, boundary-layer processes), while AIFS can be more “smooth” because it’s learned and typically coarser. Importantly, AIFS is its own model (AI-native), but it uses the same initial conditions as IFS (from ECMWF’s assimilation/analysis pipeline), so the comparison is about the forecast engine, not the starting point. Bottom line: by Day 4/6/7, AIFS often matches or edges IFS on upper-air pattern skill, while IFS remains stronger for physically constrained, local extremes and “weather sensible” detail. 96h: usually “tie-ish” on big patterns; IFS often better on local detail 144h: AIFS commonly slightly better on headline upper-air skill (pattern metrics) 168h: AIFS can stay ahead on large scales, but IFS remains the safer bet for extremes/structure ---------------------------------------------------------------------------------------------------------------------------- NOAA’s physics-based GFS still outperforms its experimental AI models at shorter lead times, especially where mesoscale detail and physical constraints matter. At 96 hours (Day 4), the operational GFS generally verifies better against observations for precipitation placement, fronts, and boundary-layer–driven features, while AI runs are competitive mainly on broad upper-air patterns. By 144 hours (Day 6), NOAA’s parallel AI models often match GFS on large-scale circulation metrics (e.g., 500-mb height anomalies) but begin to diverge more in sensible weather details. At 168 hours (Day 7), AI models can sometimes show similar or slightly better pattern skill than GFS, reflecting strengths in learned climatology and flow regimes. However, GFS remains more reliable for physically rare or extreme events (strong cyclogenesis, sharp gradients, convective outbreaks). Because NOAA’s AI systems are still experimental and not ensemble-anchored, GFS remains the authoritative model for verification, warnings, and downstream products. Key takeaways 96h: GFS usually verifies better overall; AI competitive mainly on upper-air patterns 144h: AI ≈ GFS on large scales; GFS better on precipitation and structure 168h: AI can edge pattern scores, but GFS remains stronger for extremes and decision use Highest overall pattern skill (global): GraphCast ECMWF AIFS FourCastNet / Pangu-Weather Best operational reliability: ECMWF IFS NOAA GFS Best short-range precipitation AI: MetNet-3