One of the more exciting developments in the world of weather and climate science this year has been the release of new data sets by the European Union's Copernicus Climate Change Service. The program is funding the free and open distribution of vast quantities of data through the Climate Data Store, so there is almost unlimited scope for new research as well as commercial development using the data.
The data set that I'm most excited about is the latest generation of reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF), which is well-known for having the most accurate global weather forecast model in the short-medium-range time frame (out to two weeks in the future). I've often used reanalysis data from NOAA on this blog, and indeed NOAA's global reanalysis from 1948-present is heavily used worldwide and is extremely valuable. However, the NOAA reanalysis relies on a model that is very out of date now. Happily, the new ECMWF reanalysis - using the ECMWF's top-notch modeling capability - is now coming online via the Copernicus program; the data are currently available back to 2000, but next year we'll see the product extended back to 1950.
Here's an article about ECMWF's new ERA5 reanalysis:
https://www.ecmwf.int/en/about/media-centre/science-blog/2017/era5-new-reanalysis-weather-and-climate-data
Back in 2015 I did a brief comparison of NOAA's reanalysis data with real observations from Fairbanks; here's one of the figures, showing the very poor correlation of reanalysis to actual temperature and precipitation in summer.
The chart below is a similar figure using ERA5 data for the nearest grid point to Fairbanks, which happens to be located just to the south across the Tanana River (the grid spacing is about 20km). The performance is impressive. Now admittedly the correlations ought to be very high for temperature, because the ECMWF model uses surface observations to refine its gridded estimates of evolving weather conditions hour by hour. However, precipitation is predicted by the model over short time intervals, so the model does not "know" how much precipitation occurred in reality; and neither ground-truth data nor radar estimates are used to improve the estimates. Given that the ERA5 precipitation data is purely a (short-range) forecast, I think it's very impressive that the monthly correlations are as high as ~0.8 in May through July, when hard-to-predict showers and thunderstorms produce most of the rain.
Here's a look at correlations of daily rather than monthly temperatures through the year. Daily low temperatures are generally more difficult to get right than high temperatures, because the warmest conditions of the day tend to be more closely tied to the more homogeneous, well-predicted temperatures of the free atmosphere above.
Finally, the wind speed estimates from the model are not as impressive; apparently the low-level wind regimes near Fairbanks are a challenge even for the world's best global modeling system.
In due course I will be acquiring a larger volume of the ERA5 data and will have a chance to do a more extensive analysis; and it would be fun to set up an online map catalog of ERA5 data for the Alaska domain. If anyone has an interest in helping out with such a project, let me know - perhaps there could be a collaboration.
Objective Comments and Analysis - All Science, No Politics
Primary Author Richard James
2010-2013 Author Rick Thoman
Wednesday, November 28, 2018
Wednesday, November 21, 2018
Freezing Drizzle
Residents of Fairbanks experienced one of the more unpleasant kinds of wintry weather at times last night and this morning: freezing drizzle. At least, that's what was reported by automated instruments for a period of 7 hours at the international airport and more briefly at Fort Wainwright and Eielson AFB.
Freezing drizzle occurs when cloud droplets grow large enough to produce drizzle at the same time that (a) the cloud and underlying air temperature are below freezing, and (b) the cloud top is no colder than roughly -10°C. The cloud and drizzle droplets are therefore supercooled, but the cloud is not cold enough to contain much or any ice. (See this old post for a more detailed discussion.)
Here are the atmospheric profile measurements from Fairbanks airport at 3pm yesterday (top) and 3am today (bottom). The observations fit the conceptual model for freezing drizzle formation quite nicely, with a saturated layer in the lowest few thousand feet - where the red (temperature) and green (dewpoint) lines are superimposed - but cloud-free air above that.
Here are a couple of shots from the Ester Dome webcam that normally looks out over Fairbanks. These were taken after the freezing drizzle ended, but they show the low cloud layer below with fair weather above.
Looking at hourly ASOS data since 2000, Fairbanks tends to report freezing drizzle on just one or two days a year, on average, although the distribution is very uneven: a few winters account for most of the events. Looking at a handful of sites across Alaska, here's the percentage of all observations (throughout the year) at which drizzle is reported along with a temperature below freezing:
Utqiaġvik/Barrow 0.39%
Bettles 0.08%
Fairbanks 0.06%
Anchorage 0.05%
Northway 0.03%
McGrath 0.03%
Tanana 0.02%
Gulkana 0.02%
I'm slightly suspicious of the data, because in more than 18 years of data there are zero reports of freezing drizzle in Eagle, Delta Junction, or Kaltag - all of which I understand to have the same ASOS instrumentation as the sites above. Perhaps there are in fact some instrument differences that contribute to the variation in the results.
Here's the seasonal distribution of freezing drizzle reports in Fairbanks; less than 20 years is insufficient to build up a good climatology, but there does seem to be a preference for these events in early winter rather than mid-late winter.
Up in Utqiaġvik, where freezing drizzle is much more common, the majority of events occur in early winter and late spring; it is very unusual in deep winter, when moisture levels and temperatures are usually both too low to produce the phenomenon.
Freezing drizzle occurs when cloud droplets grow large enough to produce drizzle at the same time that (a) the cloud and underlying air temperature are below freezing, and (b) the cloud top is no colder than roughly -10°C. The cloud and drizzle droplets are therefore supercooled, but the cloud is not cold enough to contain much or any ice. (See this old post for a more detailed discussion.)
Here are the atmospheric profile measurements from Fairbanks airport at 3pm yesterday (top) and 3am today (bottom). The observations fit the conceptual model for freezing drizzle formation quite nicely, with a saturated layer in the lowest few thousand feet - where the red (temperature) and green (dewpoint) lines are superimposed - but cloud-free air above that.
Here are a couple of shots from the Ester Dome webcam that normally looks out over Fairbanks. These were taken after the freezing drizzle ended, but they show the low cloud layer below with fair weather above.
Looking at hourly ASOS data since 2000, Fairbanks tends to report freezing drizzle on just one or two days a year, on average, although the distribution is very uneven: a few winters account for most of the events. Looking at a handful of sites across Alaska, here's the percentage of all observations (throughout the year) at which drizzle is reported along with a temperature below freezing:
Utqiaġvik/Barrow 0.39%
Bettles 0.08%
Fairbanks 0.06%
Anchorage 0.05%
Northway 0.03%
McGrath 0.03%
Tanana 0.02%
Gulkana 0.02%
I'm slightly suspicious of the data, because in more than 18 years of data there are zero reports of freezing drizzle in Eagle, Delta Junction, or Kaltag - all of which I understand to have the same ASOS instrumentation as the sites above. Perhaps there are in fact some instrument differences that contribute to the variation in the results.
Here's the seasonal distribution of freezing drizzle reports in Fairbanks; less than 20 years is insufficient to build up a good climatology, but there does seem to be a preference for these events in early winter rather than mid-late winter.
Up in Utqiaġvik, where freezing drizzle is much more common, the majority of events occur in early winter and late spring; it is very unusual in deep winter, when moisture levels and temperatures are usually both too low to produce the phenomenon.
Saturday, November 17, 2018
Alaska Observation Palooza
Hi, Rick T. here. In searching back through Deep Cold posts, it looks like we've never put up a review of a subject near and dear to my heart: an overview of point-based weather and climate observations in Alaska. So, I thought it might be worthwhile to lay out some of the details. Note: this piece is acronym heavy. I've included a decoder table at the end.
When it comes to weather observations: right now here in Alaska, we are living in the golden age of real time environmental observations: the good old days were definitely not always good. When I started with the NWS in Alaska in 1988, for most of the year there were less than four dozen reliable, real-time 24-hour/per weather observations in the entire state, and some of those (ones with the asterisk in the graphics below) only had temperature, wind and pressure for part, or all, of the day. Every single one of these were operated by either then NWS, FAA or DoD.
There were more part-time or irregular weather observations the 1980s. There were perhaps 20 contract aviation observations (paid for by NWS or FAA) that took 6 to 16 observations a day, e.g. Umiat, Slana and Ambler. By the late 1980s the DoD dew line stations were no longer regularly reporting 24 hours per day but sent observation on an occasional schedule. There were a tiny number of NWS operated remote stations (RAMOS) that reported temperature and winds and were still operating in places like Anaktuvuk Pass and Sitkanak (southern Kodiak Island). There were some, but not usually real-time observations from a small number of the Soil Conservation Service (now NRCS) SNOTel sites. In the summer there were even more, from Alaska Fire Services RAWS (which were deployed and then removed at the start and end of the fire season) and from relatively few river gauges which had temperature and tipping bucket sensors.
Fast forward to today: a quick count of observations in Alaska available on the MESO-WEST website for 3am Saturday morning revealed about 785 separate observations with at least one meteorlogical element, and to that you could add more than a dozen more home weather stations that are online only on Weather Underground. Here's a graphic I made up in 2017 that identifies the operators and types of observation in the eastern Interior and Copper River Basin.
This shows most of the classes of 24 hour per day weather observations that are currently deployed around Alaska, with the exception of some coastal specific observations. You'll see that most of the platforms belong to some Federal agency (e.g. NWS, FAA, BLM, NRCS) but there are some others, including state of Alaska DOT and private (the home weather stations). The stations marked as USARRAY are an interesting class. These are actually part of a temporary, high density seismic monitoring network on which weather sensors have been installed. Only a fraction of the stations have weather stations included (the full map is here). These stations have provided never before seen real-time weather detail over the North Slope and Brooks Range, you can as see in this graphic (same 2017 project):

On the climate side of the house, it's a different story. The March 1988 edition of the NCDC publication Climatological Data had data from about 130 stations in Alaska reporting daily temperature extremes and precipitation data, and this represents the vast majority of climate observations that were made that month in Alaska. About 75 of these were NWS cooperative sites which made observations once a day and the rest NWS and FAA (including the contract observations) and DoD sites. In March 2018, there were just over 100 stations with data in that publication, and NWS cooperative sites was still number about 75. The losses are mostly from the drop off of the aviation contract and DoD sites: almost none of those became strictly cooperative stations.
The big difference beween 1988 and 2018 is that now there are multiple sources of readily available climate data that are not included in the Climatological Data publication. These include explicit daily climate data from unaugmented NWS ASOS (e.g. Kaltag and Seldovia) and the nearly two dozen NCEI flagship Climate Reference Network stations as well as derived climate data from the 100+ RAWS (mostly operated by the Alaska Fire Service and National Park Service) and four dozen NRCS SNOTel sites. Now one can question the climate value of some of these platforms, e.g. RAWS, which we know report temperatures that are too warm during high-sun, low-wind situations to due insufficient thermistor shielding, but clearly, Climatological Data is no longer the definitive source for Alaska climate data. Rather, it's perhaps the definitive source for NWS cooperative data, only some of which is reported in near real-time, and of course this does (eventually) make it into online climate sources, e.g. the NWS NOWData and scACIS.
But that's not the end of the story. Since 2010 the FAA has upgraded nearly all of the early 1990s era AWOS, the first generation automated operational weather observing systems that included visibility and ceiling height, with modern automated equipment which is functionally very similar to the NWS ASOS, as well as installing this modern equipment at at airports that previously lacked any weather observations. There are about 80 of these these FAA owned and operated systems that report temperatures and precipitation in the same way as ASOS, including sites with long histories of climate observations as well as sites that have never had climate observations before. While these systems don't handle frozen precipitation, the temperature data is reliable, but at the moment none of this is being used systematically in most climate analyzes. It's not true that it's been tossed out: the data is all archived at NCEI and other online locations, but we're not making much use of it. Here's a plot of these stations climate data we're not using:
As a sidenote, I do keep track of the daily data from several of these location that have historic climate data (Kaktovik, Unalakleet, Gambell, Ft. Yukon) and use it in my work. So while we have many, many more weather observations nowadays, climate data has not expanded, and in fact over much of northern and western Alaska we have less now than we did 30 years ago.
Acronyms:
- ASOS Automated Surface Observing System: the NWS standard, requires commercial power
- AWOS Automated Weather Observing System: the first generation FAA station, did not report climate data, required commercial power
- NRCS: Natural Resources Conservation Service: Successor to Soil Conservation Service, part of the US Department of Agriculture.
- RAWS: Remote Automated Weather Station: the workhorse of fire weather. Run on solar or wind power, often installed at higher elevations
- SNOTel: Snow Telemetry: NRCS station widely in the West and Alaska primarily for to measuring snow pack but now includes in a variety of meteorological parameters.
- USARRAY: US Array: a 15-year program to place a dense network of permanent and portable seismographs across the continental United States. Installed in Alaska 2015-17, scheduled for removal starting in 2019.
Thursday, November 15, 2018
Warm Winter Ahead?
Today the U.S. Climate Prediction Center came out with their seasonal forecast for winter, i.e. December through February, and to probably no-one's surprise they are showing a rather high chance of above-normal temperatures in Alaska in the coming months.
By way of reminder, the CPC forecast is probabilistic and aims to predict the chances of each of the three terciles of the 1981-2010 distribution; so a 50-60% chance of "above normal" (as for most of Alaska above) means that the probability of the upper tercile is 50-60% rather than the baseline normal probability of 33%. This is a big shift in the probability distribution and a very strong warm signal; it's the first time that CPC has shown such a large area of 50+% warmth in Alaska for Dec-Feb.
Here's the corresponding precipitation forecast.
My blog co-author Rick will be presenting much of the rationale behind the forecast in his regular monthly webinar tomorrow, and listeners are guaranteed to learn something even if they're already familiar with the complexities of seasonal forecasting.
https://accap.uaf.edu/November2018
Not to steal Rick's thunder, but I'll suggest just a few reasons why a very warm forecast seems reasonable if not inevitable. First, sea surface temperatures to the west and south of Alaska have been extremely warm in recent months, so regardless of how the weather pattern plays out, there is a lot of residual heat available. The map below (click to enlarge) shows that October SSTs were more than 3 standard deviations above the 1981-2010 normal near Alaska, according to NOAA's ERSST data. This is a pretty extraordinary warm anomaly.
Second, El Niño has developed in the tropical Pacific Ocean. As we speculated back in July (see here), this El Niño episode is focused in the central rather than eastern tropical Pacific, so it's a so-called Modoki El Niño. It's interesting to consider the different implications for Alaska of having a Modoki rather than East Pacific El Niño; I've found that the results are a bit sensitive to the definition that's used, but the overall message seems to be that Modoki episodes favor warmth more widely across the Bering Sea - Alaska region. East Pacific El Niño's are more closely linked to warmth in eastern and southeast Alaska than in the rest of the state. But in any case, an El Niño winter is most definitely a warm signal overall.
Third, the long-range computer model forecasts are showing pronounced warm signals for the upcoming winter. Here's a sample.
The NMME multi-model ensemble mean anomaly: note the +3-4°C anomaly near the Bering Strait.
The NMME (non-calibrated) tercile probability forecast:
The UK Met Office ensemble mean anomaly:
And the Japanese seasonal model - see below. It's a little hard to see the coastlines, so I've circled Alaska in red. The top left panel shows 500mb height, indicating a southerly flow over Alaska; the middle left panel shows 850mb temperature - note that the model expects the warmest conditions in the Northern Hemisphere (relative to normal) over Alaska. The bottom left panel shows sea-level pressure - note the Bering Sea trough.
Finally, the map below shows a statistical forecast based on sea surface temperatures that I developed at work recently; this is an ensemble mean forecast from a number of models that have undergone cross-validated historical testing to determine the optimal predictors. Note that the baseline is the 1950-2017 trend, so the forecast for Alaska would be even warmer relative to the standard 1981-2010 climatology. The skill of these statistical forecasts is modest at best, but they're worth having because they provide independent guidance to complement the computer models.
So is there any contradictory guidance showing a cold or even a normal winter? Having looked at a very broad collection of predictors in the past couple of weeks, the answer is "almost none". The only hint I found was in looking at past years in which late summer and early autumn produced strong and persistent high pressure ridging over the northern North Pacific, similar to this year. The subsequent winters had a modest tendency for unusual high pressure over the Bering Sea, which is a cold pattern for Alaska (see below); but the signal is not very striking, and in any case most of the "analog" years are taken from earlier decades that were colder to begin with.
Tune in to Rick's talk tomorrow for much more detail and considerably more expertise related to the winter forecast!
By way of reminder, the CPC forecast is probabilistic and aims to predict the chances of each of the three terciles of the 1981-2010 distribution; so a 50-60% chance of "above normal" (as for most of Alaska above) means that the probability of the upper tercile is 50-60% rather than the baseline normal probability of 33%. This is a big shift in the probability distribution and a very strong warm signal; it's the first time that CPC has shown such a large area of 50+% warmth in Alaska for Dec-Feb.
Here's the corresponding precipitation forecast.
My blog co-author Rick will be presenting much of the rationale behind the forecast in his regular monthly webinar tomorrow, and listeners are guaranteed to learn something even if they're already familiar with the complexities of seasonal forecasting.
https://accap.uaf.edu/November2018
Not to steal Rick's thunder, but I'll suggest just a few reasons why a very warm forecast seems reasonable if not inevitable. First, sea surface temperatures to the west and south of Alaska have been extremely warm in recent months, so regardless of how the weather pattern plays out, there is a lot of residual heat available. The map below (click to enlarge) shows that October SSTs were more than 3 standard deviations above the 1981-2010 normal near Alaska, according to NOAA's ERSST data. This is a pretty extraordinary warm anomaly.
Second, El Niño has developed in the tropical Pacific Ocean. As we speculated back in July (see here), this El Niño episode is focused in the central rather than eastern tropical Pacific, so it's a so-called Modoki El Niño. It's interesting to consider the different implications for Alaska of having a Modoki rather than East Pacific El Niño; I've found that the results are a bit sensitive to the definition that's used, but the overall message seems to be that Modoki episodes favor warmth more widely across the Bering Sea - Alaska region. East Pacific El Niño's are more closely linked to warmth in eastern and southeast Alaska than in the rest of the state. But in any case, an El Niño winter is most definitely a warm signal overall.
Third, the long-range computer model forecasts are showing pronounced warm signals for the upcoming winter. Here's a sample.
The NMME multi-model ensemble mean anomaly: note the +3-4°C anomaly near the Bering Strait.
The NMME (non-calibrated) tercile probability forecast:
The UK Met Office ensemble mean anomaly:
And the Japanese seasonal model - see below. It's a little hard to see the coastlines, so I've circled Alaska in red. The top left panel shows 500mb height, indicating a southerly flow over Alaska; the middle left panel shows 850mb temperature - note that the model expects the warmest conditions in the Northern Hemisphere (relative to normal) over Alaska. The bottom left panel shows sea-level pressure - note the Bering Sea trough.
Finally, the map below shows a statistical forecast based on sea surface temperatures that I developed at work recently; this is an ensemble mean forecast from a number of models that have undergone cross-validated historical testing to determine the optimal predictors. Note that the baseline is the 1950-2017 trend, so the forecast for Alaska would be even warmer relative to the standard 1981-2010 climatology. The skill of these statistical forecasts is modest at best, but they're worth having because they provide independent guidance to complement the computer models.
So is there any contradictory guidance showing a cold or even a normal winter? Having looked at a very broad collection of predictors in the past couple of weeks, the answer is "almost none". The only hint I found was in looking at past years in which late summer and early autumn produced strong and persistent high pressure ridging over the northern North Pacific, similar to this year. The subsequent winters had a modest tendency for unusual high pressure over the Bering Sea, which is a cold pattern for Alaska (see below); but the signal is not very striking, and in any case most of the "analog" years are taken from earlier decades that were colder to begin with.
Tune in to Rick's talk tomorrow for much more detail and considerably more expertise related to the winter forecast!
Tuesday, November 6, 2018
North Pacific Blog Post
It's been a while since I did one of these, but I've just posted an update on the North Pacific "blob tracker" blog.
https://alaskapacificblob.wordpress.com/2018/11/06/record-north-pacific-warmth/
I'll aim to add some interpretation for the Alaska climate scene on here in the coming days.
https://alaskapacificblob.wordpress.com/2018/11/06/record-north-pacific-warmth/
I'll aim to add some interpretation for the Alaska climate scene on here in the coming days.
Tuesday, October 30, 2018
Cooler At Last
The air temperature is much more seasonable across interior and northern Alaska today, courtesy of a strong cold front that pushed its way across the state on Sunday. Here's yesterday morning's 500mb map, showing the associated upper-level low over the North Slope (click to enlarge).
Fairbanks has seen a high temperature of "only" about 17°F today, but this is completely normal for the time of year. It's quite a dramatic change, however, as this is the first day with a sub-freezing high temperature, and prior to Saturday the coldest day had a high of 37°F.
The sudden change to colder got me thinking about the statistics of sudden "one-way" temperature drops in autumn or early winter in Fairbanks. (And let the reader beware - what follows is a rather arcane discussion.) By "one-way" I mean an instance when daily high temperatures drop below a threshold that was not breached earlier in the season, and then the temperature fails to rise back above that threshold at any later date in the same year. For example, as noted above the coldest day in Fairbanks until Saturday had a high of 37°F, but it's possible that we've seen a "one-way" change to colder, as 37°F may not be reached again until the spring. This would constitute a "one-way" drop in high temperatures at the 37°F threshold.
Digging through Fairbanks climate data reveals that this kind of thing is fairly common as a result of the high rate of seasonal cooling; about 30% of all years see a "one-way" change to colder high temperatures at some point in the autumn. The most dramatic was in 1950, when up until September 26 the coldest day had a high of 46°F, but no temperature above 38°F was observed from that date on; that's the largest one-way drop (8°F) that I found.
Here's a chart showing the high temperature thresholds and dates for which these "one-way" cooling events have occurred in Fairbanks. Unsurprisingly, the earliest was in the absurdly cold September of 1992; the latest was in 1942, when the temperature sank below 22°F at the end of October and did not reach that level again in the same year. (Note that I haven't included winter after December 31 in this analysis.)
Looking at a number of other sites in Alaska, the frequency of sudden one-way cooling is highest for the most continental sites and lower for more maritime sites, as we would expect. For example, Anchorage sees such an event in about 20% of years, but Bettles and Northway manage it more often than not at some point in the autumn.
On a related note, it's worth pointing out that Fairbanks has never seen a true one-way temperature drop in which subsequent daily high temperatures never reach the lowest daily low temperatures prior to the drop. I rather doubt if this has been observed anywhere in the world, as it would require both an extreme rate of normal seasonal cooling and an extreme shift in the weather pattern at the right time.
To finish up, here's a pleasing clear-sky scene from UAF this evening just after sunset. Officially the snow cover is still only a "trace" - it hasn't made it up to 1 inch yet.
Fairbanks has seen a high temperature of "only" about 17°F today, but this is completely normal for the time of year. It's quite a dramatic change, however, as this is the first day with a sub-freezing high temperature, and prior to Saturday the coldest day had a high of 37°F.
The sudden change to colder got me thinking about the statistics of sudden "one-way" temperature drops in autumn or early winter in Fairbanks. (And let the reader beware - what follows is a rather arcane discussion.) By "one-way" I mean an instance when daily high temperatures drop below a threshold that was not breached earlier in the season, and then the temperature fails to rise back above that threshold at any later date in the same year. For example, as noted above the coldest day in Fairbanks until Saturday had a high of 37°F, but it's possible that we've seen a "one-way" change to colder, as 37°F may not be reached again until the spring. This would constitute a "one-way" drop in high temperatures at the 37°F threshold.
Digging through Fairbanks climate data reveals that this kind of thing is fairly common as a result of the high rate of seasonal cooling; about 30% of all years see a "one-way" change to colder high temperatures at some point in the autumn. The most dramatic was in 1950, when up until September 26 the coldest day had a high of 46°F, but no temperature above 38°F was observed from that date on; that's the largest one-way drop (8°F) that I found.
Here's a chart showing the high temperature thresholds and dates for which these "one-way" cooling events have occurred in Fairbanks. Unsurprisingly, the earliest was in the absurdly cold September of 1992; the latest was in 1942, when the temperature sank below 22°F at the end of October and did not reach that level again in the same year. (Note that I haven't included winter after December 31 in this analysis.)
Looking at a number of other sites in Alaska, the frequency of sudden one-way cooling is highest for the most continental sites and lower for more maritime sites, as we would expect. For example, Anchorage sees such an event in about 20% of years, but Bettles and Northway manage it more often than not at some point in the autumn.
On a related note, it's worth pointing out that Fairbanks has never seen a true one-way temperature drop in which subsequent daily high temperatures never reach the lowest daily low temperatures prior to the drop. I rather doubt if this has been observed anywhere in the world, as it would require both an extreme rate of normal seasonal cooling and an extreme shift in the weather pattern at the right time.
To finish up, here's a pleasing clear-sky scene from UAF this evening just after sunset. Officially the snow cover is still only a "trace" - it hasn't made it up to 1 inch yet.
Wednesday, October 24, 2018
Excessive Warmth
There's a lot that could be said about the ongoing persistent and increasingly extreme warmth (relative to normal) across much of Alaska, but time doesn't permit more than a brief update at this point.
To illustrate, Fairbanks has seen 3 days in the past week with a high temperature of 50°F or higher - and to put this into context, the 1981-2010 normal high and low temperature for October 24th are 25°F and 10°F respectively. Fairbanks doesn't normally see more than a small handful of days above freezing from this point on, so 50°F is quite extreme.
Today was actually the warmest day in Fairbanks since the first week of the month, with a high of 52°F. This degree of warmth has not occurred so late in the season since the 1930s: it happened in 1934 (the year of the great December chinook) and also in November 1936 and late October 1938. But similar conditions occurred in 2013, of course, with 51°F on October 28.
The map below shows the culprit for today's balmy conditions: a deep southerly flow aloft, leading to downslope warming to the north of the Alaska Range. As we would expect, the middle Tanana River valley was warm and windy today owing to the chinook flow; Delta Junction reported wind gusts over 50mph.
Here's the snowless scene this evening on campus at UAF: a disheartening prospect for winter enthusiasts as well as, more seriously, residents who rely on frozen land and water for important activities.
Here's a comparison of this month's daily mean temperatures to the two other years that were outstandingly warm in Fairbanks in the month of October: 2013 and 1938. No other years have come close to having the same amplitude of warm anomaly for this calendar month. But neither of those years could hold off winter's freeze until the very end of the month; and so surely it is just a matter of a few days now until the landscape is finally transformed.
To illustrate, Fairbanks has seen 3 days in the past week with a high temperature of 50°F or higher - and to put this into context, the 1981-2010 normal high and low temperature for October 24th are 25°F and 10°F respectively. Fairbanks doesn't normally see more than a small handful of days above freezing from this point on, so 50°F is quite extreme.
Today was actually the warmest day in Fairbanks since the first week of the month, with a high of 52°F. This degree of warmth has not occurred so late in the season since the 1930s: it happened in 1934 (the year of the great December chinook) and also in November 1936 and late October 1938. But similar conditions occurred in 2013, of course, with 51°F on October 28.
The map below shows the culprit for today's balmy conditions: a deep southerly flow aloft, leading to downslope warming to the north of the Alaska Range. As we would expect, the middle Tanana River valley was warm and windy today owing to the chinook flow; Delta Junction reported wind gusts over 50mph.
Here's the snowless scene this evening on campus at UAF: a disheartening prospect for winter enthusiasts as well as, more seriously, residents who rely on frozen land and water for important activities.
Here's a comparison of this month's daily mean temperatures to the two other years that were outstandingly warm in Fairbanks in the month of October: 2013 and 1938. No other years have come close to having the same amplitude of warm anomaly for this calendar month. But neither of those years could hold off winter's freeze until the very end of the month; and so surely it is just a matter of a few days now until the landscape is finally transformed.
Saturday, October 20, 2018
No Rain in Yakutat
Hi, Rick T. here with an analysis of one piece of exceptional September we just came through. Specifically, the lack of precipitation on the Gulf of Alaska Coast. One of the most amazing climate statistics to come out of September was from Yakutat, where there was an astonishing 20 consecutive days with no rain at all, not even a sprinkle. Considering that Yakutat averages 24 days in September with some rain and that this streak was several days longer than any previous dry streak this time of year, the question is, just how unusual was 20 straight days with no rain at all?
Richard, Brian and I had a long email string on ways to think about analyzing this event. With their help, here's what I came up with.
First, some background to set the stage.
There are a number of ways to potentially answer such questions, but the one I'll provide here involves our old friend, regression. But rather than linear regression (which obviously is not appropriate), I tried mathematical forms that have the potential to represent what we see in the plot above: large and rapid changes as we move from left to right along the x (horizontal) axis. Two commonly used forms for distributions of this shape are exponential and power law. In order to facilitate this analysis I first converted the raw count values into frequencies per year and then plotted the frequency on a log scale, which results in this:
This is the same information as in first figure, just displayed in a different way. But it allows us to immediately to see that that an exponential fit is not likely to work so well. How do we know that? Well, with the y (vertical) axis plotted in log scale, an exponential fit will appear as a straight line. Just eyeballing the top of the bars, you can see that a straight line will fit pretty well for streaks of 11 days or less, but then fails to capture the handful of events longer duration. For that, a power law fit works out better. Now a well established issue with power law fits is that the often only part of a distribution (typically the right tail) is well represented by a power law. How does that work out in this case? I systematically fitted a power law using the observed frequency of all the streak lengths, i.e. 1 day to 25 days (everything about 20 is zero). Then I fitted a power law to streaks of two days or longer, then three days or longer, etc. The "winner" was the fit that had the lowest root mean squared error but still utilized most of the data (there are more sophisticated ways to do this but I have not had the time to implement them, though in this case will lead to the same answer). It turns out that the best fit was for runs to two or more days and it looks like this:
So based on this analysis, the streak of 20 completely dry days in row has only about a 0.7% chance of occurring in any particular August through October season. I've noted the return period as calculated from the fit on the graphic for selected streaks, though I don't really like to do that because it's easy to misinterpret. Why do it? People like to see it, and in principle it is perhaps a more intuitive way to express low likelihood events. But, it is important to remember that a long return period is the inverse of a very small number, and so small changes in the fit result in big changes in the return period. So if I improve this analysis and come up with probability for a 20-day streak as 0.9% in any given year, that's a small change from 0.7%, but the return period would drop by 40 years, to 111.
So from this analysis, the 20 dry days in a row at Yakutat this September was likely a once in a lifetime event, at least if you're of mature years. After all, 0.7% annual chance of occurrence means that, assuming no change and no year-to-year correlation, that there is about a 30% that this will happen at least once in the next 50 years.
First, some background to set the stage.
- Since I am looking at days with zero precipitation, not even a trace, I used data since 1947, since this is entirely within the Weather Bureau/Weather Service era of 24-hour per day observations and there is no missing daily precipitation data.
- The frequency of precipitation varies seasonally, e.g. May in Yakutat averages twice as many days without any precipitation as October, so we need to limit the analysis to this time of year. Therefore I confined the analysis to the early autumn (August through October) season. I'm also assuming there is no trend in dry days streaks (which is the case for the total number of dry days in ASO).
- For statistical analysis, the independence of events is often an important underlying assumption. So while it's easy to generate simple counts of consecutive days without precipitation, it took a bit more work to find the independent streaks. To illustrate this, a simple count revels that there are two streaks of 19 days with zero precipitation during August through October, 1947 to 2018. However, both of these streaks are simply subsets of the 20-day streak from this past September (Sep 2-20 and Sep 3-21). So removing all the streaks that are simply subsets of longer ones, here's what we find for the counts of independent, non-overlapping streaks of specific lengths:
There are a number of ways to potentially answer such questions, but the one I'll provide here involves our old friend, regression. But rather than linear regression (which obviously is not appropriate), I tried mathematical forms that have the potential to represent what we see in the plot above: large and rapid changes as we move from left to right along the x (horizontal) axis. Two commonly used forms for distributions of this shape are exponential and power law. In order to facilitate this analysis I first converted the raw count values into frequencies per year and then plotted the frequency on a log scale, which results in this:
This is the same information as in first figure, just displayed in a different way. But it allows us to immediately to see that that an exponential fit is not likely to work so well. How do we know that? Well, with the y (vertical) axis plotted in log scale, an exponential fit will appear as a straight line. Just eyeballing the top of the bars, you can see that a straight line will fit pretty well for streaks of 11 days or less, but then fails to capture the handful of events longer duration. For that, a power law fit works out better. Now a well established issue with power law fits is that the often only part of a distribution (typically the right tail) is well represented by a power law. How does that work out in this case? I systematically fitted a power law using the observed frequency of all the streak lengths, i.e. 1 day to 25 days (everything about 20 is zero). Then I fitted a power law to streaks of two days or longer, then three days or longer, etc. The "winner" was the fit that had the lowest root mean squared error but still utilized most of the data (there are more sophisticated ways to do this but I have not had the time to implement them, though in this case will lead to the same answer). It turns out that the best fit was for runs to two or more days and it looks like this:
So based on this analysis, the streak of 20 completely dry days in row has only about a 0.7% chance of occurring in any particular August through October season. I've noted the return period as calculated from the fit on the graphic for selected streaks, though I don't really like to do that because it's easy to misinterpret. Why do it? People like to see it, and in principle it is perhaps a more intuitive way to express low likelihood events. But, it is important to remember that a long return period is the inverse of a very small number, and so small changes in the fit result in big changes in the return period. So if I improve this analysis and come up with probability for a 20-day streak as 0.9% in any given year, that's a small change from 0.7%, but the return period would drop by 40 years, to 111.
So from this analysis, the 20 dry days in a row at Yakutat this September was likely a once in a lifetime event, at least if you're of mature years. After all, 0.7% annual chance of occurrence means that, assuming no change and no year-to-year correlation, that there is about a 30% that this will happen at least once in the next 50 years.
Friday, October 19, 2018
Bering Ridge Wrap-Up
As a postscript to my earlier analysis of the intense ridge over the Bering Sea and western Alaska (see here and here), the charts below indicate the magnitude of the recent 500mb anomaly at 15-day, 30-day, and 45-day time scales compared to the Northern Hemispheric extremes since 1958. As before, we're looking at the standardized 500mb height anomaly, i.e. the departure from normal divided by the standard deviation, and I've removed the (seasonally-varying) long-term linear trend at each location. The charts show the daily maximum and minimum values of the standardized anomaly across the entire Northern Hemisphere since 1958. Click to enlarge the images.
Based on this analysis, the upper-level ridge that affected western Alaska in recent weeks was most anomalous on a 30-day time scale. Remarkably, the 30-day standardized height anomaly at 500mb just to the south of Nome was the most extreme in the global reanalysis history back to 1958, for either Northern or Southern Hemisphere, and for either positive or negative anomalies. Here's a map of the peak 30-day height anomaly:
In the earlier post I noted that the record 15-day ridge was an extreme high-pressure block over northern Greenland in November 1965. But interestingly the record event for a 45-day time scale was also over Alaska, in the late winter of 1989. This event appears to have been related to a major disruption of the stratospheric polar vortex (a "sudden stratospheric warming") in February 1989.
Finally, here's a chart showing Southern Hemisphere extremes on a 45-day basis. The record for most anomalous ridge occurred near the southern tip of South America in the early austral winter (late April - early June) of 2016.
Based on this analysis, the upper-level ridge that affected western Alaska in recent weeks was most anomalous on a 30-day time scale. Remarkably, the 30-day standardized height anomaly at 500mb just to the south of Nome was the most extreme in the global reanalysis history back to 1958, for either Northern or Southern Hemisphere, and for either positive or negative anomalies. Here's a map of the peak 30-day height anomaly:
In the earlier post I noted that the record 15-day ridge was an extreme high-pressure block over northern Greenland in November 1965. But interestingly the record event for a 45-day time scale was also over Alaska, in the late winter of 1989. This event appears to have been related to a major disruption of the stratospheric polar vortex (a "sudden stratospheric warming") in February 1989.
Finally, here's a chart showing Southern Hemisphere extremes on a 45-day basis. The record for most anomalous ridge occurred near the southern tip of South America in the early austral winter (late April - early June) of 2016.
Tuesday, October 16, 2018
Still No Snow
With rain and very mild temperatures today (up to 48°F so far), Fairbanks is moving further into uncharted territory in terms of the lack of any wintry weather so far this season. Today the airport has reported 0.05" of rain and no snow, there's zero snow on the ground, and the temperature seems very likely to stay above freezing through midnight.
Putting aside the lack of snow on earlier dates, there are only two other days in Fairbanks history that meet these conditions at this late date in the autumn: October 23, 1981, and October 28, 2013. In 1981 several inches of snow had fallen earlier in the month and then melted out; the situation in 2013 was more similar to this year, but even then there had been hints of winter's approach with occasional light snow in both September and October. Here's my post from late October 2013: http://ak-wx.blogspot.com/2013/10/record-warmth-again.html
Here are some non-wintry webcam views from Fairbanks-land this afternoon.
Cleary Summit (2200' elevation) on the Steese Highway:
UAF's webcam on the West Ridge of campus:
Ester Dome:
In view of the bare ground, an interesting question to ask is, "How cold can it get without snow cover?" The quick answer is, of course, "Pretty cold"; in December 1934, after the great chinook melted Fairbanks' snow cover, the temperature dropped to -29°F on Christmas Eve with only a trace of snow reported on the ground.
A more comprehensive search for cold conditions with no snow cover is complicated by the fact that Alaska's cooperative observers have often reported zero snow depth in error (instead of new snow amount, for example), and missing snow depth is often recorded as zero. I did find a couple of interesting examples, though. Just a couple of years ago (Nov 2016) the Fort Yukon SNOTEL site reported -36°F with a zero-inch snow depth, and the Fort Yukon RAWS saw -34°F the same day. I don't really trust the snow depth number, however; I suspect there could easily have been an inch or two on the ground.
Perhaps a more credible instance is November 11, 1984, at Chandalar Lake in the Brooks Range, when -33°F was reported with only a trace of snow on the ground. However, in this case a "trace" may just mean "less than an inch", as preceding conditions suggest there might have been a very thin but continuous snow cover.
I haven't investigated to see what Alaska's lowest reported temperature is with zero snow on the ground - if anyone has an idea, please leave a comment!
Putting aside the lack of snow on earlier dates, there are only two other days in Fairbanks history that meet these conditions at this late date in the autumn: October 23, 1981, and October 28, 2013. In 1981 several inches of snow had fallen earlier in the month and then melted out; the situation in 2013 was more similar to this year, but even then there had been hints of winter's approach with occasional light snow in both September and October. Here's my post from late October 2013: http://ak-wx.blogspot.com/2013/10/record-warmth-again.html
Here are some non-wintry webcam views from Fairbanks-land this afternoon.
Cleary Summit (2200' elevation) on the Steese Highway:
UAF's webcam on the West Ridge of campus:
Ester Dome:
In view of the bare ground, an interesting question to ask is, "How cold can it get without snow cover?" The quick answer is, of course, "Pretty cold"; in December 1934, after the great chinook melted Fairbanks' snow cover, the temperature dropped to -29°F on Christmas Eve with only a trace of snow reported on the ground.
A more comprehensive search for cold conditions with no snow cover is complicated by the fact that Alaska's cooperative observers have often reported zero snow depth in error (instead of new snow amount, for example), and missing snow depth is often recorded as zero. I did find a couple of interesting examples, though. Just a couple of years ago (Nov 2016) the Fort Yukon SNOTEL site reported -36°F with a zero-inch snow depth, and the Fort Yukon RAWS saw -34°F the same day. I don't really trust the snow depth number, however; I suspect there could easily have been an inch or two on the ground.
Perhaps a more credible instance is November 11, 1984, at Chandalar Lake in the Brooks Range, when -33°F was reported with only a trace of snow on the ground. However, in this case a "trace" may just mean "less than an inch", as preceding conditions suggest there might have been a very thin but continuous snow cover.
I haven't investigated to see what Alaska's lowest reported temperature is with zero snow on the ground - if anyone has an idea, please leave a comment!
Sunday, October 14, 2018
Persistent Alaska Warmth
Hi, Rick T. here with a quick post of the recent warmth in Alaska. One of the most frequent questions I get from Outside media is something along the lines of "Is it warm in Alaska?" After going through the stock "Alaska's a big place with diverse climates" and then giving some impressionistic answer about a hundred times, I thought that it would be worthwhile to try and come up with an objective way of answering those kind of questions. So, a few years ago Brian B. and I developed a real-time index that could help answer this. If your interested the background on how this index is calculated, read on below the chart.
Up through early September Alaska had considerably more days warmer than normal than cooler than normal in 2018, but periodic cool spells kept the run of warm days at a moderate length. Since early September though the index has been persistently quite high: by construction, index values above +3.3 fall into the "significantly above normal" tercile, and that has been the case every day since September 5th. This is an interesting situation in that the cause of the warmth has varied. For much of September and the first days of October, as Richard has noted here, strong high pressure aloft, first over the Bering and then a bit farther east from the Arctic to the Gulf of Alaska dominated. In the past week the pattern has transitioned to a "Gulf of Alaska" storm track pattern. In different parts of the state this weather pattern change has resulted in changing temperature regimes, but on the statewide scale, it's a nice example of how distinctly different patterns can lead to the same outcome: much above normal temperatures.
Exactly how the index is derived has gone through several iterations but here's the current version.
1) Find the standardized departure of the daily average temperature for each the 25 sites below (daily departure from normal divided by the standard deviation). This levels the playing field, so to speak, between inland areas, with much higher variability of temperatures, and marine dominated parts of the state, where water dampens the air temperature variability. These particular sites were chosen to be geographically representative as possible, the observations are all ASOS, so the climate day ends at the same time (midnight), the instrumentation is the same and all have NCEI published 1981-2010 normals (daily average temperature and daily standard deviation). The obvious gaps are the northeast Interior, inland North Slope and the Aleutians. In these regions there are no ASOS sites with published normals.
The next step is simply to find the mean of the 25 standardized departure. This is almost always a value ±1.5. The last step is to convert this "Alaska-wide average standardized departure" for the day into an index. To do this, we convert the daily average standardized departure into a Z-score. Doing this requires knowing the standard deviation of the "Alaska-wide average standardized departure". Now you might think that this should be 1. After all, by construction the 25 daily standardized departures have an a standard deviation of 1. However, because of the spatial correlation in daily departures, the standard deviation of the mean of the 25 sites is significantly less than 1: it turns out that it is about 0.71. The rest is simple: take the Z-score, which is a value between 0 and 1 and create the index. For simplicity, we wanted a "0 to 10" index, but after a little though, having zero be exactly average made it easier to understand. So the index goes from -10 to +10, with 0 being normal. Being derived from a Z-score, the index can never get to ±10, but it can get arbitrarily close: May 13 and May 14, 2016 had index values of +9.98, while January 27, 2012 the index value was -9.81.
Up through early September Alaska had considerably more days warmer than normal than cooler than normal in 2018, but periodic cool spells kept the run of warm days at a moderate length. Since early September though the index has been persistently quite high: by construction, index values above +3.3 fall into the "significantly above normal" tercile, and that has been the case every day since September 5th. This is an interesting situation in that the cause of the warmth has varied. For much of September and the first days of October, as Richard has noted here, strong high pressure aloft, first over the Bering and then a bit farther east from the Arctic to the Gulf of Alaska dominated. In the past week the pattern has transitioned to a "Gulf of Alaska" storm track pattern. In different parts of the state this weather pattern change has resulted in changing temperature regimes, but on the statewide scale, it's a nice example of how distinctly different patterns can lead to the same outcome: much above normal temperatures.
Exactly how the index is derived has gone through several iterations but here's the current version.
1) Find the standardized departure of the daily average temperature for each the 25 sites below (daily departure from normal divided by the standard deviation). This levels the playing field, so to speak, between inland areas, with much higher variability of temperatures, and marine dominated parts of the state, where water dampens the air temperature variability. These particular sites were chosen to be geographically representative as possible, the observations are all ASOS, so the climate day ends at the same time (midnight), the instrumentation is the same and all have NCEI published 1981-2010 normals (daily average temperature and daily standard deviation). The obvious gaps are the northeast Interior, inland North Slope and the Aleutians. In these regions there are no ASOS sites with published normals.
The next step is simply to find the mean of the 25 standardized departure. This is almost always a value ±1.5. The last step is to convert this "Alaska-wide average standardized departure" for the day into an index. To do this, we convert the daily average standardized departure into a Z-score. Doing this requires knowing the standard deviation of the "Alaska-wide average standardized departure". Now you might think that this should be 1. After all, by construction the 25 daily standardized departures have an a standard deviation of 1. However, because of the spatial correlation in daily departures, the standard deviation of the mean of the 25 sites is significantly less than 1: it turns out that it is about 0.71. The rest is simple: take the Z-score, which is a value between 0 and 1 and create the index. For simplicity, we wanted a "0 to 10" index, but after a little though, having zero be exactly average made it easier to understand. So the index goes from -10 to +10, with 0 being normal. Being derived from a Z-score, the index can never get to ±10, but it can get arbitrarily close: May 13 and May 14, 2016 had index values of +9.98, while January 27, 2012 the index value was -9.81.
Friday, October 12, 2018
Still No Snow in Fairbanks
The calendar says we're already in mid-October, which is just about the end of interior Alaska's short autumn. According to climate statistics, the temperature often struggles to rise much above freezing from this point on in Fairbanks, and snow is on the ground more often than not after the 15th.
But this year, like some other recent years, is much different. Remarkably, no snow at all has been observed yet at Fairbanks airport - not even a half-melted flake or a momentary flurry, although some snow occurred at last yesterday in the hills outside town. According to the NWS, this is the latest that Fairbanks has gone without seeing any snow at all.
Snow is also absent across vast areas of western Alaska, and the cause is two-fold: excessively mild temperatures and a lack of precipitation. The dry conditions are of course closely tied to the astonishing ridge that has prevailed lately over the Bering Sea and western Alaska. And the warmth is amazing: Kotzebue has not even seen a freeze yet, which is also an all-time record.
Looking out at water temperatures in the Bering and Chukchi Seas, a tremendous amount of warmth is evident at the ocean surface. Here's Rick Thoman's depiction of September's departure from normal in sea surface temperatures.
And here's a chart (click to enlarge) showing the daily trajectory of SSTs in the southern Chukchi Sea, to the north of the Bering Strait. The red line indicates this year's data, while the gray shaded area shows the minimum and maximum values for each date in the 1981-2017 history. Since September 19, the average sea surface temperature has been at record high levels; the area average is still above +5°C, which has not been observed at this date before. The previous record years were 2007 (for the entire summer) and 2016 (from early October through freeze-up).
But this year, like some other recent years, is much different. Remarkably, no snow at all has been observed yet at Fairbanks airport - not even a half-melted flake or a momentary flurry, although some snow occurred at last yesterday in the hills outside town. According to the NWS, this is the latest that Fairbanks has gone without seeing any snow at all.
Snow is also absent across vast areas of western Alaska, and the cause is two-fold: excessively mild temperatures and a lack of precipitation. The dry conditions are of course closely tied to the astonishing ridge that has prevailed lately over the Bering Sea and western Alaska. And the warmth is amazing: Kotzebue has not even seen a freeze yet, which is also an all-time record.
Looking out at water temperatures in the Bering and Chukchi Seas, a tremendous amount of warmth is evident at the ocean surface. Here's Rick Thoman's depiction of September's departure from normal in sea surface temperatures.
Sea surface temperatures around Alaska were near to much above normal in September except for parts of the Beaufort Sea. Except for the Beaufort and northern Chukchi Seas, these SSTs are warmer than Sept 2017. #akwx #Arctic @Climatologist49 @amy_holman @IARC_Alaska @lisashefguy pic.twitter.com/VAkkUQVX2x— Rick Thoman (@AlaskaWx) October 11, 2018
And here's a chart (click to enlarge) showing the daily trajectory of SSTs in the southern Chukchi Sea, to the north of the Bering Strait. The red line indicates this year's data, while the gray shaded area shows the minimum and maximum values for each date in the 1981-2017 history. Since September 19, the average sea surface temperature has been at record high levels; the area average is still above +5°C, which has not been observed at this date before. The previous record years were 2007 (for the entire summer) and 2016 (from early October through freeze-up).
Saturday, October 6, 2018
Sea Ice Update
Freeze-up is now under way across portions of the Arctic Ocean, notably in the eastern Beaufort Sea, the Canadian high Arctic, and the Greenland Sea. According to NSIDC's daily sea ice index, total Arctic sea ice extent has already increased about 12% from its seasonal minimum on September 16th.
Let's take a look at how this year's September sea ice extent compared to earlier years; we now have 40 years of consistent sea ice data from satellite microwave observations (not visible or infrared wavelengths - thus not obscured by cloud). See the chart below, and click to enlarge.
This year's Arctic ice extent was right in line with September's data from recent years, which is good news from one perspective, as we are not seeing (at least not yet) the kind of rapid downward acceleration in sea ice loss that was perhaps feared a few years ago. However, the loss of ice in just the last 20 years has been dramatic and unquestionably very rapid from the perspective of longer term climate.
With 40 years of data now in front of us, I think it's safe to say that the multi-decadal ice loss has been far from linear; the chart above shows rather little change in the first 20 years, with some high ice years mixed in until 1996. If we look at ice area rather than ice extent - see below - we also find that the highest values occurred in the last 15 years of the 20th century. (See here for an explanation of the difference between extent and area.)
In both charts the really rapid loss occurred from about 1998 through 2012, and there appears to have been a lessening of the trend in the most recent years. Of course it's too early to assign much confidence to potential changes in trend over such short periods, but nevertheless it is interesting to note that there is no statistical significance to the most recent trend in ice extent for anything less than a 15-year period. In other words the 2005-2018 downward trend, and any shorter trend ending in 2018, is not statistically significant; and I take this to be a hint of good news for Arctic sea ice prospects in coming years.
Finally, the estimated September Arctic sea ice volume from the University of Washington's PIOMAS model also came in close to the values of recent years - higher than 2012 and 2016, it would seem, but lower than 2013-2015. However, according to PIOMAS, the volume of sea ice remains well below the then-record low 2007 value, and this is an important contrast with the sea ice area and extent data. Based on volume estimates, then, there is perhaps less reason to be optimistic about any possible slowdown or reprieve in the rate of Arctic ice loss.
Let's take a look at how this year's September sea ice extent compared to earlier years; we now have 40 years of consistent sea ice data from satellite microwave observations (not visible or infrared wavelengths - thus not obscured by cloud). See the chart below, and click to enlarge.
This year's Arctic ice extent was right in line with September's data from recent years, which is good news from one perspective, as we are not seeing (at least not yet) the kind of rapid downward acceleration in sea ice loss that was perhaps feared a few years ago. However, the loss of ice in just the last 20 years has been dramatic and unquestionably very rapid from the perspective of longer term climate.
With 40 years of data now in front of us, I think it's safe to say that the multi-decadal ice loss has been far from linear; the chart above shows rather little change in the first 20 years, with some high ice years mixed in until 1996. If we look at ice area rather than ice extent - see below - we also find that the highest values occurred in the last 15 years of the 20th century. (See here for an explanation of the difference between extent and area.)
In both charts the really rapid loss occurred from about 1998 through 2012, and there appears to have been a lessening of the trend in the most recent years. Of course it's too early to assign much confidence to potential changes in trend over such short periods, but nevertheless it is interesting to note that there is no statistical significance to the most recent trend in ice extent for anything less than a 15-year period. In other words the 2005-2018 downward trend, and any shorter trend ending in 2018, is not statistically significant; and I take this to be a hint of good news for Arctic sea ice prospects in coming years.
Finally, the estimated September Arctic sea ice volume from the University of Washington's PIOMAS model also came in close to the values of recent years - higher than 2012 and 2016, it would seem, but lower than 2013-2015. However, according to PIOMAS, the volume of sea ice remains well below the then-record low 2007 value, and this is an important contrast with the sea ice area and extent data. Based on volume estimates, then, there is perhaps less reason to be optimistic about any possible slowdown or reprieve in the rate of Arctic ice loss.
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