139: Alaska - temperature trends WARMING (probably)

The US state most often linked to climate change is Alaska. This is probably because it is seen as having an Arctic climate even though only about a third of the state actually lies within the Arctic Circle. In fact Alaska is no more northerly than Norway and its Aleutian Island chain stretches further south than London and Berlin. It has an area three times that of France but its population is less than that of Marseille, yet it has an extensive network of weather stations that is greater in data quality than that seen in many industrialized countries. Ordinarily this should be sufficient to determine the temperature change for Alaska to a high level of precision but it isn't. In fact the data is so inconclusive it is difficult to determine whether Alaska has warmed at all over the last one hundred years let alone quantify that warming and discern when exactly it occurred. This is because the natural variation in the long term temperature averages is far greater than the likely warming.

There are one hundred stations in Alaska with over 480 months of data before 2014 including seven long stations with over 1200 months of data. Of the 93 medium stations with over 480 months of data twenty have over 1000 months of data (for a full list of stations see here). The locations of these stations are shown in Fig. 139.1 below.

Fig. 139.1: The (approximate) locations of the 100 longest weather station records in Alaska. Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

 

The map in Fig. 139.1 shows that most of the temperature data for Alaska come from stations that are outside the Arctic Circle. In fact of the one hundred longest stations in Alaska only eight are actually inside the Arctic Circle. And while the remainder are fairly evenly distributed geographically, there are significant clusters of stations around Anchorage, Fairbanks and the panhandle along the coast in the southeast between the the border of Canada and the Alexander Archipelago. As usual for simplicity I will disregard this clustering and assume it makes very little difference to the measured temperature change as it only affects the contribution or weighting of about 15% of stations.

In order to quantify the changes to the climate of Alaska the temperature anomalies for all stations with over 480 months of data before 2014 were determined and averaged. This was done using the usual method as outlined in Post 47 and involved first calculating the temperature anomaly each month for each station relative to its monthly reference temperatures (MRT), and then averaging those anomalies to determine the mean temperature anomaly (MTA) for the country. This MTA is shown as a time series in Fig. 139.2 below with the MRTs for each station calculated using data between 1961 and 1990,  (again using the methodology outlined in Post 47).

Fig. 139.2: The mean temperature change for Alaska since 1900 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1921 to 2000 and has a positive gradient of +0.31 ± 0.31 °C per century.

The data in Fig. 139.2 above illustrates the difficulty of determining a definitive temperature trend when the data is subject to significant variability over time. In this case choosing to fit to the data from 1921 to 2000 leads to a small positive gradient of 0.31°C per century, but this is no bigger than the uncertainty and so is not statistically significant. If other fitting intervals are chosen then the gradient can be significantly different. For example, an interval of 1921-1995 results in a gradient of 0.18°C per century while 1926-2005 produces 0.96°C per century. All of which poses the awkward question, which result is correct?

In my opinion there is no obvious answer, but there are two factors that we could consider that may shed some additional light on the problem. The first of these is to choose an appropriate fitting interval based on the cycle of the natural variations (i.e. fitting from peak to peak), while the second is to concentrate on data that is the result of averaging the greatest number of station records. 

In Post 4 I explained how the best fit line to a single period of a sine wave gives a non-zero gradient (see Fig. 4.7) whereas fitting to a cosine wave does not. This is because a cosine wave is symmetric about the y-axis while the sine wave is anti-symmetric. As most temperature data tends to oscillate over time due to natural variations it therefore follows that the gradient of any fit to that data will depend on the interval chosen relative to the peaks of those natural oscillations. 

In order to avoid biasing the gradient due to asymmetry in the fitting range, the range should be symmetric relative to the natural oscillations. These natural oscillations are seen most clearly in the 5-year moving average (see the yellow curve in Fig. 139.2). So the fitting range should be chosen so that it starts and ends on a peak in the 5-year average, or alternatively starts and ends on a trough. The best fit in Fig. 139.2 does not do this. It starts near a trough at 1921 and ends on a plateau in 2000. But if we change the fitting interval from 1914 to 2003 then the interval starts and ends on a peak in the 5-year average. The result is the best fit shown in Fig. 139.3 below.

Fig. 139.3: The mean temperature change for Alaska since 1900 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1914 to 2003 and has a positive gradient of +0.71 ± 0.26 °C per century.

The gradient of the best fit in Fig. 139.3 is more than twice that in Fig. 139.2 even though the data hasn't changed. This is simply a result of changing the fitting interval. Of course the underlying reason why a change of fitting interval makes such a big difference in this case is that the natural fluctuations in the 5-year average are so large. These changes in temperature can exceed 2°C in less than five years. So we could ask, is the temperature rise of about 0.7°C indicated by the best fit in Fig. 139.3 really that significant in comparison?

Fig. 139.4: The number of station records included each month in the mean temperature anomaly (MTA) trend for Alaska in Fig. 139.2 and Fig. 139.3.

The second factor in determining any choice of fitting range is the quantity of data available. The graph in Fig. 139.4 above shows the number of stations included in the MTA in Fig. 139.2 and Fig. 139.3. From 1920 onwards there are over twenty stations each month. In the previous post and in Post 57 I argued that at least ten, and possibly over twenty-five stations are needed in order for the MTA to be reliable, so this condition is satisfied for all months after January 1920. The data before 1920 will therefore be much less reliable, but there is still enough data to allow us to calculate an approximate MTA as far back as the 1820s. This is shown in Fig. 139.5 below.

Fig. 139.5: The mean temperature change for Alaska since 1820 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1911 to 2010 and has a positive gradient of +0.73 ± 0.22 °C per century.

The data in Fig. 139.5 indicates that it is possible to calculate and MTA as far back as 1829, but before 1900 there are gaps in the data and most of the MTA data for this period is based on an average of anomaly data from less than three different stations. So that raises questions over its reliability.

So how should we interpret this data? The station frequency data in Fig. 139.4 suggests only data after 1900 or even 1920 is sufficiently reliable. As for the data after 1900, there are many ways to interpret it. For example, if we just look at data from 1901 to 1975 the best fit (as determined from trough to trough) is strongly negative (see Fig. 139.6 below). But after 1975 the temperature appears to increase abruptly by about 1°C. So is this interpretation of the temperature trend any more believable than those shown in Fig. 139.2 or Fig. 139.3? It is hard to tell, again because of the high level of natural variability in the data which could be varying on multiple timescales. Such multi-frequency variability is potentially indicative of chaotic or fractal behaviour as I discussed in Post 9, Post 17 and Post 42.

Fig. 139.6: The mean temperature change for Alaska since 1900 relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1901 to 1975 and has a negative gradient of -0.52 ± 0.33 °C per century.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 139.7 below. This again was determined by averaging the anomalies for each month from the one hundred longest stations in Alaska and suggests that the climate of Alaska has warmed by over 1°C since 1870, but with large natural variations of up to 1.5°C in the 10-year average.

Fig. 139.7: Temperature trends for Alaska based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1876-2010 and has a positive gradient of +1.00 ± 0.06°C/century.

Comparing the curves in Fig. 139.7 with the published Berkeley Earth (BE) version for Alaska in Fig. 139.8 below we see that there is good agreement between the two sets of data as far back as 1880. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 139.7 using adjusted data is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 139.8. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 139.2 and Fig. 139.5. In other words, any discrepancy between the adjusted data in Fig. 139.7 and the unadjusted data in Fig. 139.5 cannot be due to the averaging process. Any form of weighted averaging would also not affect the results.

Fig. 139.8: The temperature trend for Alaska since 1820 according to Berkeley Earth.

Most of the differences between the MTA in Fig. 139.6 and the BE versions using adjusted data in Fig. 139.7 are instead mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values seen in Fig. 139.5 and Fig. 139.7.

Fig. 139.9: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 139.7 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1921-2000 has a positive gradient of +0.262 ± 0.009 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The magnitudes of these adjustments are shown graphically in Fig. 139.9 above. The blue curve is the difference in MTA values between adjusted (Fig. 139.7) and unadjusted data (Fig. 139.5), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The overall adjustment from 1920 to 2000 is small, about +0.2°C. Nevertheless, it can be seen in the difference in the 5-year means (see Fig. 139.10 below) for the unadjusted data (blue curve) and the adjusted data (red curve). The difference, though, is about ten times less than the variability in the two MTAs over time. The data in Fig. 139.10 also highlights the difficulty in interpreting the data. If the data between 1940 and 1980 were missing or ignored, then one could postulate that Alaska has seen fairly consistent warming since 1900 amounting to about 1°C in total. But if the 1940-1980 data is included the data all looks very random.

Fig. 139.10: The 5-year mean temperature change for Alaska since 1900 based on the original raw data (in blue) and the Berkeley Earth adjusted data (in red).

Summary

The temperature data for Alaska demonstrates the difficulty in determining an accurate temperature trend for a region when the climate is subject to a high degree of variability.

It is possible that the climate has warmed by almost 1°C since 1900 (see Fig. 139.3), or it might not have warmed at all (see Fig. 139.2).

If the climate has warmed, this warming may have been fairly continuous (see Fig. 139.3), or it could have been fairly recent, occurring mainly after 1980 (see Fig. 139.6).

The one thing we can say is that the difference between the temperature rise based on Berkeley Earth adjusted data (see Fig. 139.7) and that based on the raw unadjusted data (see Fig. 139.5) is small (less than 0.3°C) and much less that the 5-year natural variability of the data (about 2°C).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in Alaska with links to their raw data files.

106. Bahamas and Key West - temperature trends STABLE to 1988

The islands of The Bahamas stretch over a distance of more than 800 km on the edge of the Atlantic Ocean southeast of Florida. Yet only four weather stations in the region have sufficient temperature data to be useful (for a list see here), and two of these are in Nassau (see map in Fig. 106.1 below). In addition, however, there are two stations in Key West (Key West and Key West airport) that are so far from the Florida coast as to be possibly more representative of the climate of The Bahamas than that of Florida (see Post 103). For this reason I will include them in this analysis.

Fig. 106.1: The (approximate) locations of the six longest weather station records in The Bahamas and Key West. Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

In total there are two long stations with over 1200 months of data before 2014 and four medium stations with over 480 months in this analysis. The two long stations both had more or less continuous data that stretched from before 1900 to 2013. The four medium stations were more problematic. Three had virtually no data before 1950 while the station at Nassau had no data after. Added to that, the station at Freeport airport had no data before 1970.

The temperature anomalies for each station were determined using the usual method as outlined in Post 47. This involved first calculating the monthly reference temperatures (MRTs) for each station using a set reference period, in this case from 1961 to 1990, and then subtracting the MRTs from the raw temperature data to deliver the anomalies. If a station had at least twelve valid temperatures per month within the MRT interval then its anomalies were included in the calculation of the regional mean temperature anomaly (MTA). 

As no one single time interval for the monthly reference temperatures (MRTs) would allow all six stations to be included in the final average, the MRT interval was set to be 1961-1990. The one station to be excluded from the MTA calculation in this case was the Nassau station, but this exhibits virtually zero temperature change over its data range from 1900 to 1950.

Fig. 106.2: The mean temperature change for The Bahamas and Key West relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1901 to 1980 and has a slight positive gradient of +0.11 ± 0.12 °C per century.

The resulting MTA is shown in Fig. 106.2 above. It can be seen that before 1988 there is only a very slight upward temperature trend that is less than the uncertainty in the trend. Then in 1988 the temperature jumps suddenly by about 0.5°C. This is similar to the jump of about 1°C that was identified earlier in Post 44 for the MTA of Europe which also occurred in or around 1988. Is this coincidence, or did something happen to data collection methods in 1988?

The total number of stations included in the MTA in Fig. 106.2 each month is indicated in Fig. 106.3 below. The peak in the frequency around 1980 suggests that the 1961-1990 interval was indeed the most appropriate, but it also shows how much of the MTA trend in Fig. 106.2 relies on data from just two stations: Nassau airport and Key West airport.

Fig. 106.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for The Bahamas and Key West in Fig. 106.2.

Next I calculate the corresponding MTA result based on data that has been adjusted by Berkeley Earth (BE). The result is shown in Fig. 106.4 below.

Fig. 106.4: Temperature trends for The Bahamas and Key West based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1911-2010 and has a gradient of +0.79 ± 0.03°C/century.

 

Comparing the curves in Fig. 106.4 with the published Berkeley Earth (BE) version in Fig. 106.5 below indicates remarkably good agreement at least as far back as 1900 despite Fig. 103.4 also including data from Key West. This suggests that the simple averaging of anomalies I have used is effective and accurate, and adding the Key West stations was probably appropriate.

Fig. 106.5: The temperature trend for The Bahamas since 1750 according to Berkeley Earth.

The differences between the MTA in Fig. 106.2 and the BE versions using adjusted data in Fig. 106.4 and Fig. 106.5 are mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values seen in Fig. 106.2 and Fig. 106.4. The magnitudes of these adjustments are shown graphically in Fig. 106.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 106.4) and unadjusted data (Fig. 106.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both are considerable and produce an additional warming since 1900 of about 0.4°C.

Fig. 106.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 106.4 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1901-1980 has a positive gradient of +0.682 ± 0.018 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

 

Summary 

According to the raw unadjusted temperature data, over the ninety year period up to 1988 the climate of The Bahamas and Key West remained stable before experiencing a sudden jump in temperature of about 0.5°C (see Fig. 106.2).

Over the period 1901-2010 the adjusted temperature data from Berkeley Earth claims to show that the climate of The Bahamas and Key West has warmed by as much as 1.0°C (see Fig. 106.4).

Acronyms 

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

 

List of all stations

Nassau airport

Nassau

Abrahams Bay

Freeport airport

Key West

Key West airport

105. US southern states - summary of BE temperature adjustments

In my previous post I summarized the temperature trends since 1900 of the six US states closest to the Gulf of Mexico (Texas, Louisiana, Mississippi, Alabama, Georgia and Florida). All the trends were constructed using data from the longest available temperature records in the state, all involved averaging the temperature anomalies from over 90 different station records, and none exhibited a significant positive warming trend.

Yet in every case the official Berkeley Earth (BE) trend does exhibit warming, often lots of it. The difference of course is largely down to the adjustments that Berkeley Earth make to the data via homogenization, Kriging, gridding and of course breakpoint alignment. In the post for each state (the links are here: Texas, Louisiana, Mississippi, Alabama, Georgia and Florida) I have quantified the magnitude of these adjustments, but I thought it would also be instructive to summarize them in one post just so that their full impact can be seen and compared.

The adjustments shown in the graphs below are of two types. The orange curve is the mean adjustment each month solely from breakpoint adjustments while the blue curve is the mean adjustment relative to unadjusted data from all sources of correction. This will also include homogenization, Kriging and gridding in addition to breakpoints, but it will also be affected by any difference in the chosen period for calculating the monthly reference temperatures (MRTs). The last of these will, however, only change the offset of the blue curve in the vertical direction relative to the orange one, not its slope or total change over time.

The graphs below indicate that the BE adjustments to the temperature data add between 0.5°C and 1.2°C to the final BE temperature trends. Given that we are constantly being told by climate scientists that the total global warming experienced so far is about 1.2°C, I would suggest that this is a bit of a problem.

Fig. 105.1: The Berkeley Earth (BE) temperature adjustments for Texas since 1900. The linear best fit (red line) to these adjustments for the period 1911-2010 has a positive gradient of +0.568 ± 0.003 °C per century.

Fig. 105.2: The Berkeley Earth (BE) temperature adjustments for Louisiana since 1900. The linear best fit (red line) to these adjustments for the period 1911-2010 has a positive gradient of +0.731 ± 0.004 °C per century.

Fig. 105.3: The Berkeley Earth (BE) temperature adjustments for Mississippi since 1900. The linear best fit (red line) to these adjustments for the period 1931-2010 has a positive gradient of +1.300 ± 0.007 °C per century.

Fig. 105.4: The Berkeley Earth (BE) temperature adjustments for Alabama since 1900. The linear best fit (red line) to these adjustments for the period 1931-2010 has a positive gradient of +1.231 ± 0.012 °C per century.

Fig. 105.5: The Berkeley Earth (BE) temperature adjustments for Georgia since 1900. The linear best fit (red line) to these adjustments for the period 1911-2010 has a positive gradient of +1.087 ± 0.006 °C per century.

Fig. 105.6: The Berkeley Earth (BE) temperature adjustments for Florida since 1900. The linear best fit (red line) to these adjustments for the period 1941-2010 has a positive gradient of +0.611 ± 0.010 °C per century.

104. US southern states - summary of temperature trends

Over the last month I have examined the temperature trends of five different US states (Louisiana, Mississippi, Alabama, Georgia and Florida) that surround, or are within 100km of (in the case of Georgia), the Gulf of Mexico. These all appear to have similar trends to that of Texas that I examined in Post 52. All have negative or stable temperature trends over the last 100 years. For comparison their temperature trends are republished here with identical data ranges (from 1900) and fitting ranges (1911-2010). What is clear is that none of these trends is remotely similar to either the Berkeley Earth (BE) versions for each state based on adjusted data, or the global trends published by NOAA, NASA-GISS, BE, HadCRU etc.

Fig. 104.1: The mean temperature change for Texas. The best fit has a slight negative gradient of -0.15 ± 0.15 °C per century.

Fig. 104.2: The mean temperature change for Louisiana. The best fit has a negative gradient of -0.38 ± 0.15 °C per century.

Fig. 104.3: The mean temperature change for Mississippi. The best fit has a negative gradient of -0.76 ± 0.17 °C per century.

Fig. 104.4: The mean temperature change for Alabama. The best fit has a negative gradient of -0.72 ± 0.17 °C per century.

Fig. 104.5: The mean temperature change for Georgia. The best fit has a negative gradient of -0.76 ± 0.16 °C per century.

Fig. 104.6: The mean temperature change for Texas. The best fit has a slight positive gradient of +0.08 ± 0.13 °C per century.

103. Florida - temperature trends STABLE

Like all the other US states that border the Gulf of Mexico, Florida has not experienced any global warming, but neither has the climate cooled. In fact over the last 100 years the climate of Florida has remained fairly stable as shown by the mean temperature anomaly (MTA) data for the state illustrated in Fig. 103.1 below.

Fig. 103.1: The mean temperature change for Florida relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1911 to 2010 and has a slight positive gradient of +0.08 ± 0.13 °C per century.

The MTA in Fig. 103.1 was calculated by averaging the temperature anomalies from the 100 longest temperature records for the state. All these records had over 700 months of temperature data before the end of 2013 and 31 were long stations that each had more than 1200 months of data in total. For a full list of stations see here.

The anomalies for each station were determined using the usual method as outlined in Post 47. This involved first calculating the monthly reference temperatures (MRTs) for each station using a set reference period, in this case from 1951 to 1980, and then subtracting the MRTs from the raw temperature data to deliver the anomalies. If a station had at least twelve valid temperatures within the MRT interval then its anomalies were included in the MTA calculation. In total 93 stations were included with seven being excluded for lack of data between 1951 and 1980. The total number of stations included in the MTA in Fig. 103.1 each month is indicated in Fig. 103.2 below. The peak just around 1960 suggests that the 1951-1980 interval was indeed the most appropriate.

Fig. 103.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Florida in Fig. 103.1.

The locations of the one hundred stations is shown in the map in Fig. 103.3 below. This appears to show that the geographical spread is fairly uniform, although there does appear to be a greater concentration of stations in the more highly populated areas of Tampa and Miami. These areas also appear to have more stations with warming trends where a warming trend is defined as one where the temperature gradient for 1911-2010 is positive and exceeds twice the error. Nevertheless, the variation in station density is probably not sufficient to significantly distort the average in Fig. 103.1 from its true value. In which case the simple average of the anomalies from all stations used to construct the MTA in Fig. 103.1 should still yield a fairly accurate temperature trend for the state as a whole.

Fig. 103.3: The (approximate) locations of the 100 longest weather station records in Florida. Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

Next I calculate the corresponding MTA result based on data that has been adjusted by Berkeley Earth (BE). The result is shown in Fig. 103.4 below.

Fig. 103.4: Temperature trends for Florida based on Berkeley Earth adjusted data from the 100 longest station data records. The best fit linear trend line (in red) is for the period 1911-2010 and has a gradient of +0.52 ± 0.05°C/century.

Comparing the curves in Fig. 103.4 with the published Berkeley Earth (BE) version in Fig. 103.5 below indicates remarkably good agreement at least as far back as 1900. This indicates that the 100 longest records are sufficient to determine the MTA for this period, and that simple averaging of anomalies is also highly effective and accurate.

Fig. 103.5: The temperature trend for Florida since 1750 according to Berkeley Earth.

The differences between the MTA in Fig. 103.1 and the BE versions using adjusted data in Fig. 103.4 and Fig. 103.5 are mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values seen in Fig. 103.1 and Fig. 103.4. The magnitudes of these adjustments are shown graphically in Fig. 103.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 103.4) and unadjusted data (Fig. 103.1), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both are considerable with the former leading to an additional warming since 1935 of over 0.5°C.

Fig. 103.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 103.4 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1911-2010 has a positive gradient of +0.414 ± 0.007 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Finally there is the question of the negative discontinuity in the temperature data in 1957 that was observed in the data for Texas (Post 98), Louisiana (Post 98), Mississippi (Post 99) and Alabama (Post 101). Surprisingly, this is not obvious in the Florida data. This may suggest that the discontinuity is a natural regional phenomenon rather than man-made due to changes in national data recording protocols.

Summary 

According to the raw unadjusted temperature data, over the past century the climate of Florida has remained stable (see Fig. 103.1). Most of the state has cooled but the more populated areas around Miami and Tampa have exhibited some warming that has compensated for the cooling (see Fig. 103.3).

Over the same period adjusted temperature data from Berkeley Earth claims to show that the climate of Florida has warmed by as much as 0.5°C (see Fig. 103.4 and Fig. 103.5).

Acronyms 

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Link to list of all stations and their raw data files.

102. Georgia (US) - temperature trends COOLING

In a number of previous posts I have analysed the temperature data for all the US states along the Gulf of Mexico. None has experienced any global warming and the same is true for Georgia. In fact over the last 100 years the climate of Georgia has cooled by about 0.7°C as shown by the mean temperature anomaly (MTA) data for the state illustrated in Fig. 102.1 below.

Fig. 102.1: The mean temperature change for Georgia relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1911 to 2010 and has a negative gradient of -0.76 ± 0.16 °C per century.

The MTA in Fig. 102.1 was calculated by averaging the temperature anomalies from the 100 longest temperature records for the state. All these records had over 480 months of temperature data before the end of 2013 and 37 were long stations that each had more than 1200 months of data in total. For a full list of stations see here.

The anomalies for each station were determined using the usual method as outlined in Post 47. This involved first calculating the monthly reference temperatures (MRTs) for each station using a set reference period, in this case from 1951 to 1980, and then subtracting the MRTs from the raw temperature data to deliver the anomalies. If a station had at least twelve valid temperatures within the MRT interval then its anomalies were included in the MTA calculation. In total 98 stations were included with only two being excluded for lack of data between 1951 and 1980. These were Greensboro (Berkeley Earth ID: 28632) and Columbus (Berkeley Earth ID: 28632).

The total number of stations included in the MTA in Fig. 102.1 each month is indicated in Fig. 102.2 below. The broad peak from 1955 to 1990 suggests that the 1951-1980 interval was probably the most appropriate although a 1961-1990 interval could have been equally optimal.

Fig. 102.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Georgia in Fig. 102.1.

The locations of the one hundred stations is shown in the map in Fig. 102.3 below. This appears to show that the geographical spread is fairly uniform and in turn suggests that a simple average of all the anomalies should yield an accurate temperature trend for the state as a whole.

Fig. 102.3: The (approximate) locations of the 100 longest weather station records in Georgia. Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

Next I compare the MTA based on raw unadjusted data with the MTA result based on data that has been adjusted by Berkeley Earth (BE). The result is shown in Fig. 102.4 below.

Fig. 102.4: Temperature trends for Georgia based on Berkeley Earth adjusted data from the 100 longest station data records. The best fit linear trend line (in red) is for the period 1911-2010 and has a gradient of +0.35 ± 0.05°C/century.

Comparing the curves in Fig. 102.4 with the published Berkeley Earth (BE) version in Fig. 102.5 below indicates remarkably good agreement. This indicates that the 100 longest records are sufficient to determine the MTA and that simple averaging of anomalies is also highly effective and accurate.

Fig. 102.5: The temperature trend for Georgia since 1750 according to Berkeley Earth.

The differences between the MTA in Fig. 102.1 and the BE versions in Fig. 102.4 and Fig. 102.5 are mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values in Fig. 102.1 and Fig. 102.4. The magnitudes of these adjustments are shown graphically in Fig. 102.6 below. The blue curve is the difference in MTA between adjusted (Fig. 102.4) and unadjusted data (Fig. 102.1), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both are considerable with the former leading to an additional warming since 1935 of over 1°C.

Fig. 102.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 102.4 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1911-2010 has a positive gradient of +1.018 ± 0.011 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Finally there is the question of the negative discontinuity in the temperature data in 1957 that was observed in Texas (Post 98), Louisiana (Post 98), Mississippi (Post 99) and Alabama (Post 101). It is again present in the data for Georgia and amounts to a temperature jump of 0.84°C. It can also be seen even more starkly in the BE adjusted data in Fig. 102.4. Correcting for this jump yields the MTA time series shown in Fig. 102.7 below.

Fig. 102.7: The mean temperature change for Georgia after breakpoint adjustment in 1957. The best fit is applied to the monthly mean data from 1911 to 2010 and has a positive gradient of +0.48 ± 0.16 °C per century.

The net result of making this correction is that the temperature trend since 1910 changes from a negative value of -0.76°C per century in Fig. 102.1 to a positive one of 0.48°C per century. Yet the origin of this discontinuity is still unclear. So the validity of this correction is therefore not known either.

Summary 

According to the raw unadjusted temperature data, over the past century the climate of Georgia has cooled by around 0.76°C (see Fig. 102.1).

Over the same period adjusted temperature data from Berkeley Earth claims to show that the climate of Georgia has warmed by over 1°C (see Fig. 102.4 and Fig. 102.5).

Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Link to list of all stations and their raw data files.

101. Alabama - temperature trends COOLING

Like most of its neighbours Alabama has not experienced any global warming. In fact over the last ninety years the climate has cooled by about 0.7°C as shown by the mean temperature anomaly (MTA) data for the state illustrated in Fig. 101.1 below.

Fig. 101.1: The mean temperature change for Alabama relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1911 to 2010 and has a negative gradient of -0.72 ± 0.17 °C per century.

The MTA in Fig. 101.1 was calculated by averaging the temperature anomalies from the 100 longest temperature records for the state. All these records had over 480 months of temperature data before the end of 2013 and seventeen were long stations that each had more than 1200 months of data in total. For a full list of stations see here.

The anomalies for each station were determined using the usual method as outlined in Post 47. This involved first calculating the monthly reference temperatures (MRTs) for each station using a set reference period, in this case from 1951 to 1980, and then subtracting the MRTs from the raw temperature data to deliver the anomalies. If a station had at least twelve valid temperatures within the MRT interval then its anomalies were included in the MTA calculation. In total 92 stations were included with eight being excluded for lack of data between 1951 and 1980. The total number of stations included in the MTA in Fig. 101.1 each month is indicated in Fig. 101.2 below. The peak just after 1960 suggests that the 1951-1980 interval was indeed the most appropriate.

Fig. 101.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Alabama in Fig. 101.1.

The locations of the one hundred stations is shown in the map in Fig. 101.3 below. This appears to show that the geographical spread is fairly uniform and in turn suggests that a simple average of all the anomalies should yield an accurate temperature trend for the state as a whole.

Fig. 101.3: The (approximate) locations of the 100 longest weather station records in Alabama. Those stations with a high warming trend between 1911 and 2010 are marked in red while those with a cooling or stable trend are marked in blue. Those denoted with squares are long stations with over 1200 months of data, while diamonds denote medium stations with more than 480 months of data.

Next I compare the MTA based on raw unadjusted data with the MTA result based on data that has been adjusted by Berkeley Earth (BE). The result is shown in Fig. 101.4 below.

Fig. 101.4: Temperature trends for Alabama based on Berkeley Earth adjusted data from the 100 longest station data records. The best fit linear trend line (in red) is for the period 1911-2010 and has a positive gradient of +0.32 ± 0.05°C/century.

Comparing the curves in Fig. 101.4 with the published Berkeley Earth (BE) version in Fig. 101.5 below indicates remarkably good agreement. This indicates that the 100 longest records are sufficient to determine the MTA and that simple averaging of anomalies is also highly effective and accurate.

Fig. 101.5: The temperature trend for Alabama since 1750 according to Berkeley Earth.

The differences between the MTA in Fig. 101.1 and the BE versions in Fig. 101.4 and Fig. 101.5 are mainly due to the data processing procedures used by Berkeley Earth. These include homogenization, gridding, Kriging and most significantly breakpoint adjustments. These lead to changes to the original temperature data, the magnitude of these adjustments being the difference in the MTA values in Fig. 101.1 and Fig. 101.4. The magnitudes of these adjustments are shown graphically in Fig. 101.6 below. The blue curve is the difference in MTA between adjusted (Fig. 101.4) and unadjusted data (Fig. 101.1), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both are considerable with the former leading to an additional warming since 1935 of over 1°C.

Fig. 101.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 101.4 after smoothing with a 12-month moving average. The blue curve represents the total BE adjustments including those from homogenization. The linear best fit (red line) to these adjustments for the period 1911-2010 has a positive gradient of +1.018 ± 0.011 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Finally there is the question of the negative discontinuity in the temperature data in 1957 that was observed in Texas (Post 98), Louisiana (Post 98) and Mississippi (Post 99). It is again present in the data for Alabama and amounts to a temperature jump of 0.92°C. It can also be seen in the BE adjusted data in Fig. 101.4. Correcting for this jump yields the MTA time series shown in Fig. 101.7 below.

Fig. 101.7: The mean temperature change for Alabama after breakpoint adjustment in 1957. The best fit is applied to the monthly mean data from 1921 to 2010 and has a positive gradient of +0.52 ± 0.19 °C per century.

The net result of making this correction is that the temperature trend since 1910 changes from a negative value of -0.72°C per century in Fig. 101.1 to a positive one of 0.52°C per century. Yet the origin of this discontinuity is still unclear. So the validity of this correction is therefore not known either.

Summary

According to the raw unadjusted temperature data, over the past century the climate of Alabama has cooled by around 0.6°C (see Fig. 101.1).

Over the same period adjusted temperature data from Berkeley Earth claims to show that the climate of Alabama has warmed by as much as 1°C (see Fig. 101.4 and Fig. 101.5).

Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Link to list of all stations and their raw data files.

100. List of completed temperature analyses by country

 

As this is my 100th post on this blog I thought it would be a good moment to summarize the results that have emerged from the temperature data I have analysed so far. Below is a list of all the countries and regions that I have investigated to date with links to the relevant post. This amounts to about 60 countries, states and territories in total, which is roughly one third of all the countries in the world. 

The main areas that so far remain to be studied are the Arctic, Canada, Russia, UK, Scandinavia, Mediterranean, North Africa, Middle East, China and Japan. In the Southern Hemisphere only Brazil, Venezuela, Guyana, Suriname, French Guiana and the South Atlantic remain. However, most of these Southern Hemisphere regions are already included in the analysis of South America in Post 35.

Europe

Europe has the longest temperature records available with several in Germany, Sweden and the Netherlands stretching back to the early 18th century. The average of the 109 longest records yields a mean temperature anomaly (MTA) that shows a small but continuous warming of about 0.1°C per century for over 200 years until 1988. Then the temperature jumps suddenly by over 1°C. The reason for this jump is unclear. It is certainly not related directly to carbon dioxide emissions. The only countries that appear to have strong warming trends are the Benelux countries, Denmark and Switzerland. The Baltic states and most of central Europe appear to cool before 1980 and then warm suddenly.

109 longest station records (Post 44)

Austria (Post 55)

Baltic States (Post 51)

Belgium and Luxembourg (Post 40)

Central Europe average (Post 57)

Czechoslovakia (Post 53)

Denmark (Post 48)

Germany (Post 49)

Hungary (Post 54)

Netherlands (Post 41)

Poland (Post 50)

Switzerland (Post 56)

 

USA

The USA may not have any temperature records that are as long as the longest that Europe can boast, but its temperature data from 1850 onwards is the best there is. Virtually every state has over 100 station records with over 50 years of data and over 50 records with over 100 years of data. An average of the 400 longest temperature records appears to indicate that the climate warmed by more than 2°C from 1780 to 1920 when carbon dioxide levels barely increased, and then cooled by over 0.5°C when carbon dioxide levels took off. The early warming cannot therefore be due to CO2 and is therefore generally attributed to urbanization and deforestation in the north and east. The cooling seen after 1920 is also seen in most southern states like Louisiana, Mississippi and Texas.

400 longest station records (Post 66)

Louisiana (Post 97)

Mississippi (Post 99)

Texas (Post 52)

 

Central America

The temperature data for Central America can basically be split between Mexico and the rest, however, even then there are more than four times as many stations in Mexico as there are in the rest of Central America. The picture in Mexico is also complicated by the stations there falling into two distinct types from two different sources. On balance it is likely that the overall climate was stable until 1980 and then warmed over the following twenty years by about 1°C.

Mexico (Post 93)

Rest of Central America (Post 94)

South America

Of the countries in South America studied so far, only Argentina (0.6°C), Ecuador (1°C) and Uruguay (1°C) show significant warming, although the Ecuador data is far from reliable. In Paraguay and Chile the climate has cooled while in most other countries it has remained stable. The average of all medium and long stations in South America yields a warming of about 0.5°C since 1900.

All long and medium stations (Post 35)

Argentina (Post 61)

Bolivia (Post 58)

Chile (Post 62)

Colombia (Post 95)

Ecuador (Post 96)

Paraguay (Post 59)

Peru (Post 63)

Uruguay (Post 60)

Asia

My analysis so far of temperatures in Asia has focused on the countries of Indochina and the Indian subcontinent. The overall temperature trend for Indochina is one of cooling before 1980 and warming thereafter. The result is that temperatures in 2010 are barely any higher than they were in 1890. This is also reflected in the individual temperature records of Burma, Malaysia and Vietnam, while those of the Philippines and Thailand remain stable from 1920 onwards. In India and Pakistan there is little warming before 1990 and then a sudden jump in temperatures of about 0.5°C in the mid-1990s. For Sri Lanka the jump in temperature occurs in 1978 while Bangladesh sees a continuous warming of only 0.3°C per century. 

Bangladesh (Post 74)

Burma/Myanmar (Post 69)

India including Nepal (Post 71)

Indian subcontinent (Post 75)

Indochina (Post 70)

Malaysia and Singapore (Post 69)

Pakistan (Post 72)

Philippines (Post 69)

Sri Lanka (Post 73)

Thailand (Post 69)

Vietnam (Post 69)

Africa

Most of southern Africa has exhibited some significant warming of over 1°C since 1980 but the overall picture before 1980 is varied. Angola, Mozambique and South Africa show no warming before 1980 while Malawi, Zambia, Zimbabwe and Madagascar all cool significantly by as much as they later warm. The data for Namibia and Botswana is not great but may indicate a slight warming before 1980 as well as much larger warming thereafter. Of all the countries listed below, Madagascar, Mozambique, South Africa and Zimbabwe have the best quality data and none of these countries appear to exhibit any warming before 1980.

Angola (Post 82)

Botswana (Post 38)

Madagascar (Post 77)

Mozambique (Post 78)

Namibia (Post 39)

South Africa including Lesotho and Eswatini/Swaziland (Post 37)

Zambia and Malawi (Post 81)

Zimbabwe (Post 79)

Australia

Analysis of temperature data for Australia indicates that the mean temperature trend is parabolic with the climate cooling from 1875 to 1960 and then warming. Overall temperatures in 2010 are only about 0.1-0.2°C warmer than in 1875 with temperatures having increased by about 0.5°C since 1960. This pattern in seen in most states such as South Australia, New South Wales and Victoria. It is harder to be conclusive for Tasmania and Western Australia due to a lack of data before 1900 while the trend in Northern Territory is one of consistent cooling. Only Queensland shows constant warming of about 1°C since 1990.

Australia (Post 26)

New South Wales and ACT (Post 18)

Northern Territory (Post 23)

Queensland (Post 24)

South Australia (Post 21)

Tasmania (Post 20)

Victoria (Post 19)

Western Australia (Post 22)

Oceania

Most of the countries and regions of Oceania show little of no warming. In Antarctica the only warming is found around the peninsula. New Zealand cools slightly from 1860 until 1960 then warms by about 0.5°C, rather like much of Australia. Yet despite this, temperatures in 2010 are barely above those in 1860. In Indonesia only the capital city Jakarta shows any strong warming but the average temperature for the country remains stable, although data quality and quantity before 1960 is poor. This is also true for Papua New Guinea where there is some evidence of warming after 1960 by about 0.5°C. In the South Pacific there is a contrast between east and west with the eastern half cooling significantly while the west cools slightly until 1970 before warming again by about 0.5°C. In fact of all the regions listed below, only the Indian Ocean shows significant warming of about 1°C.

Antarctica (Post 30)

Indian Ocean (Post 76)

Indonesia (Post 31)

New Zealand (Post 8)

Papua New Guinea (Post 32)

South Pacific Islands - East (Post 34)

South Pacific Islands - West (Post 33)

Southern Hemisphere

An average of the temperature anomalies from the 1000 longest records in the Southern Hemisphere shows a slight cooling of about 0.1°C until 1975 followed by a modest warming of only about 0.6°C.

Southern Hemisphere station average (Post 64)