At this point in the Arctic refreezing phase, LIFO inventory accounting comes into play.  Last-In, First-out is one accepted way to price the value of a company’s inventory.  For Arctic ice, it means that basins that are last to freeze over in winter are the first to melt out in the summer.  For example, in Mid January 2021, total NH ice extent is 91% of last March maximum, so most basins have long been covered with ice.  The last 9% will be added in four places (present % of max is noted):

Bering Sea        62%
Okhotsk Sea     70%
Barents Sea      58%
Baffin Bay         66%

In the Pacific animation above, Bering on the right adds ice extent from 261k km2 to 513k km2 since Jan. 1, while Okhotsk goes from 500k km2 to 800k km2.  Together they will likely add ~650k km2 more by March maximum.  

On the Atlantic side, Barents Sea added only ~100k km2 so far in January.  More interesting on the right side is the Baltic Sea quadrupled from 9K km2 to 42k km2.  While the Baltic extent is not large by comparison, it is already 38% greater than last March maximum, so that is surprising.

Normally, ice in the Yellow Sea is insignificant, but this year is different.  Perhaps you saw reports like this one from gcaptain Sea Ice Slows Ships In North China Ports  Excerpts in italics with my bolds.

By Muyu Xu and Chen Aizhu (Reuters) – Chinese ports and marine safety authorities are on high alert as an expansion of sea ice makes it tougher for ships to berth and discharge at key energy product import terminals along the coast of northern Bohai Bay.

A cold wave sweeping the northern hemisphere has plunged temperatures across China to their lowest in decades, boosting demand for power and fuel to historic highs in the world’s largest energy consumer.

Bohai Bay appears in the upper right corner, with Beijing nearby. Yellow Sea extent doubled in January up to 28,000 km2, which is twice the maximum last March.

Background on Okhotsk Sea

NASA describes Okhotsk as a Sea and Ice Factory. Excerpts in italics with my bolds.

The Sea of Okhotsk is what oceanographers call a marginal sea: a region of a larger ocean basin that is partly enclosed by islands and peninsulas hugging a continental coast. With the Kamchatka Peninsula, the Kuril Islands, and Sakhalin Island partly sheltering the sea from the Pacific Ocean, and with prevailing, frigid northwesterly winds blowing out from Siberia, the sea is a winter ice factory and a year-round cloud factory.

The region is the lowest latitude (45 degrees at the southern end) where sea ice regularly forms. Ice cover varies from 50 to 90 percent each winter depending on the weather. Ice often persists for nearly six months, typically from October to March. Aside from the cold winds from the Russian interior, the prodigious flow of fresh water from the Amur River freshens the sea, making the surface less saline and more likely to freeze than other seas and bays.

Map of the Sea of Okhotsk with bottom topography. The 200- and 3000-m isobars are indicated by thin and thick solid lines, respectively. A box denotes the enlarged portion in Figure 5. White shading indicates sea-ice area (ice concentration ⩾30%) in February averaged for 2003–11; blue shading indicates open ocean area. Ice concentration from AMSR-E is used. Color shadings indicate cumulative ice production in coastal polynyas during winter (December–March) averaged from the 2002/03 to 2009/10 seasons (modified from Nihashi and others, 2012, 2017). The amount is indicated by the bar scale. Source: Cambridge Core

Bering Sea Ice is Highly Variable

The animation above shows Bering Sea ice extents at April 2 from 2007 to 2020.  The large fluctuation is evident, much ice in 2012 -13 and almost none in 2018, other years in between.  Given the alarmist bias, it’s no surprise which two years are picked for comparison:

Source: Seattle Times ‘We’ve fallen off a cliff’: Scientists have never seen so little ice in the Bering Sea in spring.

Taking a boat trip from Hokkaido Island to see Okhotsk drift ice is a big tourist attraction, as seen in the short video below.  Al Gore had them worried back then, but not now.

Drift ice in Okhotsk Sea at sunrise.

At  the bottom is a discussion of statistics on year-end Arctic Sea Ice extents.  The values are averages of the last five days of each year.  End of December is a neutral point in the melting-freezing cycle, midway between September minimum and March maximum extents.

Background from Previous Post Updated to Year-End

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: “I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.” That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sine wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 40k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  Note November 2020 ice gain anomaly exceeded the October deficit anomaly by more than twice as much.  December added more surplus so that the anomaly for the year was nothing. The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

As noted in a previous post, alarms were raised over slower than average Arctic refreezing in October.  Those fears were laid to rest firstly when ice extents roared back in November, and now with the Arctic freezing fast in December. The image above shows the ice gains over the last two weeks, from Dec. 5 to 17, 2020.  In November, 3.5 Wadhams of sea ice were added during the month.  (The metric 1 Wadham = 1 M km2 comes from the professor’s predictions of an ice-free Arctic, meaning less than 1 M km2 extent). So far in December a further 1.9 Wadhams have been added with another two weeks to go in 2020.

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: “I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.” That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sine wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 40k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  Note November 2020 ice gain anomaly exceeded the October deficit anomaly by more than twice as much.  The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

Combining the months of October and November shows 2020 828k km2 more ice than baseline for the two months and matching 2019 ice recovery.

The average December adds 2M km2 of sea ice according to SII dataset, and in the first 17 days of December 2020 ice increased by 1.9M km2, with 2 weeks of futher freezing to come.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

As noted in a previous post, alarms were raised over slower than average Arctic refreezing in October.  Those fears are now laid to rest by ice extents roaring back in November.  The image above shows the ice gains completed from October 31 to November 30, 2020. In fact 3.5 Wadhams of sea ice were added during the month.  (The metric 1 Wadham = 1 M km2 comes from the professor’s predictions of an ice-free Arctic, meaning less than 1 M km2 extent)

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: “I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.” That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sine wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 40k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  Note November 2020 ice gain anomaly exceeded the October deficit anomaly by more than twice as much.  The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

Combining the months of October and November shows 2020 828k km2 more ice than baseline for the two months and matching 2019 ice recovery.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

After concerns over lackluster ice recovery in October, November is seeing ice roaring back.  The image above shows the last 3 weeks adding 3 M km2 of sea ice.  (The metric 1 Wadham = 1 M km2 comes from the professor’s predictions of an ice-free Arctic, meaning less than 1 M km2 extent) The Russian shelf seas on the left filled with ice early on.  On the CanAm side, Beaufort at the bottom center is iced over, Canadian Archipelago (center right) is frozen, and Baffin Bay is filling from the north down.  Hudson Bay (far right) first grew fast ice around the edges, and is now half iced over.  A background post is reprinted below, showing that in just 23 days, 2020 has added 3.1 M km2, 50% more than an average 30-day November.

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: “I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.” That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sine wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

Table 1 Monthly Arctic Ice rates of Extent Changes in M km2. Months with losses in pink, months with gains in blue.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 40k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

After concerns over lackluster ice recovery in October, November is seeing ice roaring back.  The image above shows the last 10 days adding sea ice at an average rate of 215k km2 per day.  The Russian shelf seas on the right have filled with ice in this period.  On the CanAm side, Beaufort at the top left is iced over, Canadian Archipelago (center left) is frozen, and Baffin Bay is filling from the north down.  Hudson Bay (far left) has grown fast ice around the edges.  A background post is reprinted below, showing that in just 10 days, 2020 has added as much ice as an average 30-day November.

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: “I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.” That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sine wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

Table 1 Monthly Arctic Ice rates of Extent Changes in M km2. Months with losses in pink, months with gains in blue.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 40k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

Some years ago reading a thread on global warming at WUWT, I was struck by one person’s comment: “I’m an actuary with limited knowledge of climate metrics, but it seems to me if you want to understand temperature changes, you should analyze the changes, not the temperatures.” That rang bells for me, and I applied that insight in a series of Temperature Trend Analysis studies of surface station temperature records. Those posts are available under this heading. Climate Compilation Part I Temperatures

This post seeks to understand Arctic Sea Ice fluctuations using a similar approach: Focusing on the rates of extent changes rather than the usual study of the ice extents themselves. Fortunately, Sea Ice Index (SII) from NOAA provides a suitable dataset for this project. As many know, SII relies on satellite passive microwave sensors to produce charts of Arctic Ice extents going back to 1979.  The current Version 3 has become more closely aligned with MASIE, the modern form of Naval ice charting in support of Arctic navigation. The SII User Guide is here.

There are statistical analyses available, and the one of interest (table below) is called Sea Ice Index Rates of Change (here). As indicated by the title, this spreadsheet consists not of monthly extents, but changes of extents from the previous month. Specifically, a monthly value is calculated by subtracting the average of the last five days of the previous month from this month’s average of final five days. So the value presents the amount of ice gained or lost during the present month.

These monthly rates of change have been compiled into a baseline for the period 1980 to 2010, which shows the fluctuations of Arctic ice extents over the course of a calendar year. Below is a graph of those averages of monthly changes during the baseline period. Those familiar with Arctic Ice studies will not be surprised at the sine wave form. December end is a relatively neutral point in the cycle, midway between the September Minimum and March Maximum.

The graph makes evident the six spring/summer months of melting and the six autumn/winter months of freezing.  Note that June-August produce the bulk of losses, while October-December show the bulk of gains. Also the peak and valley months of March and September show very little change in extent from beginning to end.

The table of monthly data reveals the variability of ice extents over the last 4 decades.

Table 1 Monthly Arctic Ice rates of Extent Changes in M km2. Months with losses in pink, months with gains in blue.

The values in January show changes from the end of the previous December, and by summing twelve consecutive months we can calculate an annual rate of change for the years 1979 to 2019.

As many know, there has been a decline of Arctic ice extent over these 40 years, averaging 40k km2 per year. But year over year, the changes shift constantly between gains and losses.

Moreover, it seems random as to which months are determinative for a given year. For example, much ado has been printed about October 2020 being slower than expected to refreeze and add ice extents. As it happens in this dataset, October has the highest rate of adding ice. The table below shows the variety of monthly rates in the record as anomalies from the 1980-2010 baseline. In this exhibit a red cell is a negative anomaly (less than baseline for that month) and blue is positive (higher than baseline).

Note that the  +/ –  rate anomalies are distributed all across the grid, sequences of different months in different years, with gains and losses offsetting one another.  Yes, October 2020 recorded a lower than average gain, but higher than 2016. The loss in July 2020 was the largest of the year, during the hot Siberian summer.  The bottom line presents the average anomalies for each month over the period 1979-2020.  Note the rates of gains and losses mostly offset, and the average of all months in the bottom right cell is virtually zero.

A final observation: The graph below shows the Yearend Arctic Ice Extents for the last 30 years.

Note: SII daily extents file does not provide complete values prior to 1988.

Year-end Arctic ice extents (last 5 days of December) show three distinct regimes: 1989-1998, 1998-2010, 2010-2019. The average year-end extent 1989-2010 is 13.4M km2. In the last decade, 2009 was 13.0M km2, and ten years later, 2019 was 12.8M km2. So for all the the fluctuations, the net loss was 200k km2, or 1.5%. Talk of an Arctic ice death spiral is fanciful.

These data show a noisy, highly variable natural phenomenon. Clearly, unpredictable factors are in play, principally water structure and circulation, atmospheric circulation regimes, and also incursions and storms. And in the longer view, today’s extents are not unusual.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

Just like the Arizona road in the image,  Arctic ice extent has dipped in September and is on the rise again.  The graph below shows how September monthly extent averages compare for the years since 2007. 

Overall it resembles the Arizona roadway.  Two low years are followed by two high years, then two low years and so on.  The last two years are low, comparable to 2007, and may portend higher ice extent ahead. As usual MASIE and SII are showing for 2020 nearly the same monthly averages, 4.0M km2 for MASIE and 3.9M km2 for SII. The graph below shows how the ice dipped and recovered in 2020 compared to the 13-year average and some notable years.

September 2020 daily minimum was lower than all previous years except for 2012.  As noted previously this year’s anomaly was the hot Siberian summer melting out the Eurasian shelf seas and the bordering parts of the Central Arctic Sea.  In 2012 it was the Great Arctic Cyclone in August of that year.  After day 255, ice recovered strongly in 2020 ending the month higher than 2007, close to 2019 and about 150k km2 less than the average daily minimum on day 260, 4.4M km2

The table shows monthly extent averages for the regions with ice in September for several years and the 13-year average for each region.

The last column shows the Standard Deviation % for each region and for NH as a whole.  Over this period the NH fluctuations have been +/- 10%.  The most variable is Barents Sea, which can be zero or over 100k km2.  Hudson Bay and Kara likewise either melt out or retain significant ice. The Central Arctic varies little from year to year.

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.