bluewave

They are finally getting a trough out West. It has been a dueling WAR and Western Ridge pattern all summer. So it looks like the WAR will be going solo for a change.

Sunday into Monday looks like our first chance to make a run on 90° this month. The SE ridge will be near record levels. Tough to sustain cooler departures like the first 5 days of September. KEWR GFSX MOS GUIDANCE 9/09/2021 0000 UTC FHR 24| 36 48| 60 72| 84 96|108 120|132 144|156 168|180 192 THU 09| FRI 10| SAT 11| SUN 12| MON 13| TUE 14| WED 15| THU 16 CLIMO X/N 73| 61 79| 58 79| 63 87| 70 89| 68 82| 67 84| 69 83 59 76

Dew points back above 70° here on the South Shore. So it’s no surprise that more heavy rain is in the forecast around the region. A continuation of the high humidity theme. Ben Noll posted an expanded version of this for the entire Northeast. I posted the local NYC Metro records of recent years earlier in the thread. Wantagh N/A 77 72 83 S8

A recent paper used the STP to increase confidence in the reports of tornadoes shifting east from the Plains. https://www.nature.com/articles/s41612-018-0048-2 Meanwhile, a robust upward trend is found in portions of the Southeast, Midwest, and Northeast (Fig. 4). No significant increase (decrease) in tornado environments is observed west (east) of the 95th meridian. We believe these trends in tornado environments are significant and have not been documented with this level of detail by previous research. https://www.sciencedaily.com/releases/2018/10/181017172846.htm The researchers tracked the number of tornado reports from 1979 to 2017, while also investigating regional trends in the daily frequency of tornado-environment formation over the same time period, using an index known as the Significant Tornado Parameter (STP). Frequently used for predicting severe weather, the index captures the coexistence of atmospheric ingredients favorable for producing tornadoes. Both the number of actual tornado reports and the historical STP analysis showed the eastward uptick in tornado frequency. "One could argue that because a region's population has increased, more tornadoes are sighted and reported," Gensini said. "But we also identified this eastward trend when using the STP index, which looks at the frequency of tornado environments and has nothing to do with people. This increases our confidence in the reporting trend that we're seeing." The trend is important for understanding the potential for future tornado exposure, damage and casualties. Severe thunderstorms accompanied by tornadoes, hail and damaging winds cause an average of $5.4 billion of damage each year across the United States, and events with $10 billion or more in damages are no longer uncommon.

Current NSIDC daily extent is a little above the 2010s average. It’s at 4,838 million sq km. Extent was just below to the average before the August slowdown.

Yeah, that gets to prior experience and normalcy bias which are discussed in the article below. https://theconversation.com/why-do-people-try-to-drive-through-floodwater-or-leave-it-too-late-to-flee-psychology-offers-some-answers-157577 While playing in or driving through flood waters are avoidable risks, the latter involve adults who generally know the risks – much to the frustration of emergency authorities. So what convinces people make risky decisions in a flood? Drivers in our study reported that they saw a majority of people in other vehicles (about 64%) driving through the floodwater, while only 2% were turning around. Seeing others do something often leaves people with the impression this behaviour is typical and relatively safe, an effect known as “normalcy bias”. In 15% of cases we studied, passengers also put pressure on drivers to cross. When things go wrong, they can go very wrong Another key reason involves prior experience and perceived probability of adverse outcomes. While 9% reported a negative outcome (such damage to their car or having to be rescued), 91% reported proceeding without any incident. The reasons for these crossings were not sudden or impulsive, but often involved what the person saw as “careful consideration” of everyday needs — such as the need to get to work or buy groceries. This presents an obvious challenge for emergency authorities. While most people succeed without issues, the cases where something goes wrong can be catastrophic and in some cases fatal. So, how do we convey the very real risks of floodwater? How do we highlight the need for people to prepare an evacuation plan and avoid entering floodwater?

I don’t think that we are over-warned for flooding. The NWS usually gets reports verifying their flash flood warnings. With last weeks event, not much the NWS can do to solve societal issues. The illegal basement apartments in NYC have been around for a long time. They exist due to the lack of affordable housing in NYC. As for all the cars stuck on flooded roads, people often underestimate the depth of water. Every flash flood around the world has videos of people driving into floods and getting stuck. Maybe we need NWS spotter type education for the general public on the dangers of driving into floods.

It’s been a challenge to string 5 or more cool days together like we just did from 9-1 to 9-5 https://mesonet.agron.iastate.edu/plotting/auto/?_wait=no&q=32&network=NJCLIMATE&station=NJ6026&year=2021&var=avg&gddbase=50&gddceil=86&how=diff&cmap=jet&dpi=100&_fmt=png

This may be the furthest north along the East Coast that a post tropical or tropical cyclone has spawned an EF-3 tornado.

While we will eventually surpass the 2012 extent minimum, the summer pressure reversal since then has made it a challenge. But even a lower Arctic pressure summer like this year was able to dip below 5 million sq km on NSIDC extent. Extents never fell this low before 2007.

The last few years stand out when compared to the rest of the doppler era of much better radar detection.

These great tweets from the NWS Mt Holly highlight how extreme our weather has become.

This is going to be the first winter with the new warmer 1991-2020 climate normals. So the NYC new average for DJF rose from 35.1° to 36.2°. It will be interesting to see if the warmer averages make it easier for NYC to finally sneak in a cooler than average winter. Every winter since 15-16 in NYC has been warmer than normal.

The latest Euro seasonal for DJF has a similar 500 mb pattern to 2017-2018.

Larry will be a surfers special. Building swells peaking by later in the week. The very large wind field will result in a top 10 surfing period for the year. Beach patrols will probably close the ocean to swimmers.

August experienced the slowest rate of NSIDC extent loss of the whole post-2007 sea ice era. The sea ice only declined by 1.498 million sq km between 7-31 and 9-1. Notice how the August rate of decline has slowed after 2012 relative to the previous 6 years. In order to beat the 2012 extent minimum, we would need extreme May preconditioning like 2020 combined with August declines in excess of 2.3 million sq km. Dr. Francis had a great recent paper on this August slowdown in recent years. NSIDC August declines in millions of sq km 2021….-1.498 2020….-1.929 2019….-1.673 2018…..-1.639 2017…..-1.914 2016….-2.347 2015….-2.318 2014…..-1.655 2013…..-1.701 2012….-2.795 2011….-2.089 2010…..-1.641 2009….-1.663 2008….-2.449 2007….-2.154 https://iopscience.iop.org/article/10.1088/1748-9326/abc047 LETTER • THE FOLLOWING ARTICLE IS OPEN ACCESS Why has no new record-minimum Arctic sea-ice extent occurred since September 2012? Jennifer A Francis1 and Bingyi Wu2 Published 23 November 2020 • © 2020 The Author(s). Published by IOP Publishing Ltd Environmental Research Letters, Volume 15, Number 11Citation Jennifer A Francis and Bingyi Wu 2020 Environ. Res. Lett. 15 114034 Abstract One of the clearest indicators of human-caused climate change is the rapid decline in Arctic sea ice. The summer minimum coverage is now approximately half of its extent only 40 yr ago. Four records in the minimum extent were broken since 2000, the most recent occurring in September 2012. No new records have been set since then, however, owing to an abrupt atmospheric shift during each August/early-September that brought low sea-level pressure, cloudiness, and unfavorable wind conditions for ice reduction. While random variability could be the cause, we identify a recently increased prevalence of a characteristic large-scale atmospheric pattern over the northern hemisphere. This pattern is associated not only with anomalously low pressure over the Arctic during summer, but also with frequent heatwaves over East Asia, Scandinavia, and northern North America, as well as the tendency for a split jet stream over the continents. This jet-stream configuration has been identified as favoring extreme summer weather events in northern mid-latitudes. We propose a mechanism linking these features with diminishing spring snow cover on northern-hemisphere continents that acts as a negative feedback on the loss of Arctic sea ice during summer.

You would never guess that Newark had 40 days reaching 90° by just looking at how cool the big summer holiday weekends have been. Newark high temperatures May….29….52° May….30….53° May....31….76°….Memorial Day Jul…….3…..70° Jul……..4….84°….Independence Day Jul……..5….89° Sep……4….82° Sep…….5 Sep…….6…..Labor Day Time Series Summary for NEWARK LIBERTY INTL AP, NJ - Jan through Dec Click column heading to sort ascending, click again to sort descending. Rank Year Number of Days Max Temperature >= 90 Missing Count 1 2010 54 0 2 1993 49 0 3 1988 43 0 4 2002 41 0 - 1991 41 0 5 2021 40 118 - 2016 40 0 - 1983 40 0 - 1959 40 0

NYC has had the wettest June 1st to September 3rd by a wide margin. 6 out of the top 10 wettest years have all occurred since 2003. It’s also interesting that so many new snowfall records have happened over this same period. Time Series Summary for NY CITY CENTRAL PARK, NY Click column heading to sort ascending, click again to sort descending. Rank Ending Date Total Precipitation Jun 1 to Sep 3 Missing Count 1 2021-09-03 31.26 0 2 2011-09-03 25.23 0 3 1927-09-03 23.89 0 4 1975-09-03 22.40 0 5 1989-09-03 22.39 0 6 2006-09-03 22.14 0 7 2003-09-03 21.54 0 8 1928-09-03 21.41 0 9 2009-09-03 21.38 0 10 2007-09-03 20.62 0

Great write up from the Northeast Regional Climate Center. http://www.nrcc.cornell.edu/services/blog/2021/09/03/index.html Tropical Depression Ida dropped catastrophic amounts of rain on parts of the Northeast on September 1. A swath of the region stretching from eastern Pennsylvania and northern/central New Jersey through the New York City metro area and into southern New England saw rainfall totals of more than 6 inches. In fact, a corridor of 8- to 11-inch rainfall totals were found in southeastern Pennsylvania, northern/central New Jersey, and the New York City area. Newark, NJ, saw 8.41 inches of rain, making it the site’s all-time wettest day on record and already making September 2021 the site’s fourth wettest September on record. LaGuardia Airport, NY, also recorded its all-time wettest day with 6.80 inches of rain. Meanwhile, Bridgeport, CT, which saw 5.77 inches of rain, experienced its wettest September day. Rain fell at a rate of 3 to 5 inches per hour in some locations, with the bulk of the daily rainfall accumulating within a six-hour period in most areas. Newark, NJ, recorded its all-time wettest hour on record, seeing 3.24 inches of rain between 8 and 9 pm. The site’s one-hour rainfall, two-hour rainfall total of 5.06 inches, and six-hour total of 7.88 inches all qualified as 500-year storm events, meaning they have a 0.2% chance of happening in a given year. Similarly, Central Park, NY, had its all-time wettest hour on record with 3.15 inches of rain from 9 to 10 pm. That record had just been set less than two weeks prior from Tropical Storm Henri. Central Park’s two-hour rainfall of 4.65 inches and six-hour total of 6.63 inches also both qualified as 500-year storm events. Many of these locations had just seen excessive rainfall from tropical systems Fred and Henri a few weeks prior. With saturated soils, waterways already running high, and the deluge from Ida, dozens of streamgages reached major flood stage, a water level high enough that “extensive inundation of structures and roads” and “significant evacuations” are possible. In fact, water levels reached historic levels at several long-term sites. For example, Brandywine Creek at Chadds Ford, PA, which has records to the early 1900s, reached 21.04 feet, approaching the operational limit of the gage and beating the previous record of 17.15 feet from September 17, 1999. Similarly, the Raritan River at Manville, NJ, which also has records back to the early 1900s, reached a new record high water level of 27.66 feet. In addition, several more long-term sites reached near-record water levels. The Schuylkill River at Philadelphia, PA, reached 16.35 feet, its second highest crest on record and just below the all-time highest water level of 17.0 feet set back on October 4, 1869.

Luckily, these people were rescued from the basement by a family member.

The 50s dew points are very noticeable following another top 5 highest dew point summer.

Updated for Ida https://nwschat.weather.gov/p.php?pid=202109022136-KOKX-NOUS41-PNSOKX 9-1…Staten Island……9.64…….Manhattan…..9.55……Cranford….9.05….Ida

I just posted this paper a few days ago in the increase of 10” rainfall months in our area since around 2003 thread. A recent study also found an abrupt shift to more extreme precipitation in the Northeast over this same time period. https://journals.ametsoc.org/view/journals/hydr/18/6/jhm-d-16-0195_1.xml Abstract The northeastern United States has experienced a large increase in precipitation over recent decades. Annual and seasonal changes of total and extreme precipitation from station observations in the Northeast were assessed over multiple time periods spanning 1901–2014. Spatially averaged, both annual total and extreme precipitation across the Northeast increased significantly since 1901, with changepoints occurring in 2002 and 1996, respectively. Annual extreme precipitation experienced a larger increase than total precipitation; extreme precipitation from 1996 to 2014 is 53% higher than from 1901 to 1995. Spatially, coastal areas receive more total and extreme precipitation on average, but increases across the changepoints are distributed fairly uniformly across the domain. Increases in annual total precipitation across the 2002 changepoint are driven by significant total precipitation increases in fall and summer, while increases in annual extreme precipitation across the 1996 changepoint are driven by significant extreme precipitation increases in fall and spring. The ability of gridded observed and reanalysis precipitation data to reproduce station observations was also evaluated. Gridded observations perform well in reproducing averages and trends of annual and seasonal total precipitation, but extreme precipitation trends show significantly different spatial and domain-averaged trends than station data. The North American Regional Reanalysis generally underestimates annual and seasonal total and extreme precipitation means and trends relative to station observations, and also shows substantial differences in the spatial pattern of total and extreme precipitation trends within the Northeast. 1. Introduction Multiple studies have found increasing total and extreme precipitation across the northeastern United States (Kunkel et al. 2013a; Peterson et al. 2013; Hayhoe et al. 2007), and extreme precipitation events have increased faster over the Northeast region than in any other part of the United States (Kunkel et al. 2013a). Hayhoe et al. (2007) found an increase of 10 mm decade−1 in annual total precipitation from 1900 to 1999 using the 93 stations in the U.S. Historical Climatology Network in the states of Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, and Pennsylvania. Using the U.S. Climate Divisional Dataset, version 2, over the domain of Hayhoe et al. (2007) plus Maryland, Delaware, West Virginia, and Washington, D.C., Kunkel et al. (2013b) found a 10.2 mm decade−1 increase in annual total precipitation over 1895–2011. However, across a similar time period (1901–2000) as Hayhoe et al. (2007), Walsh et al. (2014) and Kunkel et al. (2013b) found a trend of approximately 5.6 mm decade−1. Extreme precipitation events have also been increasing across the Northeast, both in intensity and frequency, particularly over the past three decades (Walsh et al. 2014; Kunkel et al. 2013a; Hoerling et al. 2016). This increase in extreme precipitation events is consistent with expected impacts of climate change on precipitation, primarily more extreme events driven by the ability of the atmosphere to hold more water as described by the Clausius–Clapeyron relationship (e.g., Trenberth 1998; Mishra et al. 2012; Prein et al. 2017). Kunkel et al. (2013a) found significant increases in both 2-day precipitation events that occur once every 5 years and the amount of precipitation falling on the 1% wettest days during the time period 1957–2010 for the Northeast. Hoerling et al. (2016) discovered a 2%–3% increase per decade in both the total amount and frequency of heavy precipitation events (5% wettest days) in the Northeast over 1901–2013, with the increases in heavy precipitation total amount, frequency, and intensity accelerating after 1979. Walsh et al. (2014) also evaluated trends in the amount of precipitation falling in the Northeast on the 1% wettest days using the Global Historical Climatology Network-Daily (GHCN-D) dataset, finding a striking increase of 71% from 1958 to 2012. Given the growing consensus on the recent dramatic increase of extreme precipitation across the Northeast, our motivation is to explore the temporal and spatial attributes of precipitation increases in greater detail, as well as to assess the ability of gridded observational and reanalysis datasets to capture this precipitation increase. Specifically, we add to this literature by 1) assessing the sensitivity of total and extreme precipitation changes to the time period of analysis [sections 3a(1), 3a(3)]; 2) exploring the spatial distribution of total and extreme precipitation across the Northeast [sections 3a(2), 3a(4)]; 3) analyzing seasonal changes in total and extreme precipitation [section 3a(5)]; and 4) evaluating the consistency of means and trends in precipitation across station, gridded, and reanalysis data (section 3b). 4. Conclusions Over the 1901–2014 station observational record in the Northeast, we find a significant 6.8% (0.6% decade−1) increase in annual total precipitation and a much larger 41% (3.6% decade−1) increase in annual extreme precipitation. However, a key conclusion of our study is that the recent increases in annual total and extreme precipitation in the Northeast are best characterized as abrupt shifts in 2002 and 1996, respectively, rather than long-term increases over several decades as could be implied from a linear trend. While the pre-changepoint trends in annual total (1901–2001; −1.6 mm decade−1) and annual extreme (1901–95; 0.1 mm decade−1) precipitation are not statistically significant, total precipitation from 2002 to 2014 was 13% higher than from 1901 to 2001 and extreme precipitation from 1996 to 2014 was 53% higher than from 1901 to 1995, with both increases being statistically significant. The fact that these wetter periods both abut the end of our record in 2014 means that any long-term linear trends are highly dependent on their start date and should therefore be interpreted with caution, particularly when extrapolating into the future. Of note, the recent 2015–16 drought in the Northeast is not included in our analyses, although it is not likely to change the significance of the post-changepoint increases. Spatially, we find that the increases in annual total and extreme precipitation are widespread across the Northeast domain, with the exception of smaller increases and even some significant decreases to the east of Lake Erie, and in the southern part of the domain in West Virginia, Maryland, and Delaware. Our seasonal analysis reveals that fall and summer total precipitation have statistically significant increases after changepoints in 2002 and 2003, respectively, suggesting that they contribute to the annual total precipitation changepoint in 2002. The extreme precipitation increase across the 1996 changepoint is associated with 83% and 85% increases in spring and fall extreme precipitation, respectively, and may indicate common atmospheric forcing of spring and fall extreme precipitation in the mid- to late 1990s. The increase in fall precipitation across the 1995 changepoint is consistent with the finding of Kunkel et al. (2010) that increased heavy precipitation associated with tropical cyclones after 1994 is an important driver of the overall increase in extreme precipitation. Our ongoing investigations into the underlying dynamical causes for Northeast annual total and extreme precipitation increases are focusing on these critical time periods in the late 1990s and early 2000s. Our comparison of spatial and temporal extreme precipitation patterns in station (GHCN-D), gridded (LI2013), and reanalysis (NARR) datasets shows that LI2013 is more consistent with station data than NARR. LI2013 reasonably captures the mean (within 2%) and seasonality (within 11%) of GHCN-D extreme precipitation, but contains significant differences in its trends. NARR underestimates regionally averaged extreme precipitation across all seasons by 1%–16%, and the annual extreme trends show significant differences in their spatial distribution, particularly over New England. Perhaps more importantly, both the NARR and LI2013 annual extreme time series have no significant changepoints. LI2013 does, however, reproduce GHCN-D regionally averaged annual and seasonal total precipitation within 5% (and usually within 3%), and its trends faithfully capture those from station observations both across the region and averaged over the Northeast. In addition, LI2013 has a changepoint in 2003, only one year later than the changepoint identified in GHCN-D annual total precipitation. However, NARR underestimates annual and seasonal total precipitation by 3%–10% and has annual total precipitation trends that are a factor of 2–9 times smaller than GHCN-D trends. Spatially, NARR is also less accurate than LI2013, with decreasing 1979–2014 trends over much of the coastal and western portions of the domain where GHCN-D trends are positive. This comparison of LI2013 and NARR to GHCN-D provides important information on the strengths and limitations of these products for use in analyzing hydroclimate, forcing climate impacts models, and identifying drivers of total and extreme precipitation.

Break in the heat following the historic rainfall and flooding. But looks like a temperature rebound by mid-September. Tough to sustain a cooler to near normal pattern for extended periods. EPS 9-6 to 9-13 9-13 to 9-20