109. Hispaniola - temperature trends WARMING after 1990

To the east of Jamaica and Cuba is the island of Hispaniola. It is the second largest island in the Caribbean, and the largest by population. It is also divided between two separate countries: Haiti and the Dominican Republic. And just as the island is divided geographically and politically, so it is also divided by its temperature data.

To the west in Haiti there is only one station of note in the capital at Port-au-Prince airport, but this is also the only long station on the entire island that has over 1200 months of data before 2014 (all stations in Haiti are listed here). To the east in the Dominican Republic there are six medium stations with over 480 months of data and a further five stations with over 400 months of data (for a full list see here). The locations of all these twelve stations are indicated on the map below in Fig. 109.1. It can be seen that most have warming trends, where a warming trend is defined as one where the temperature gradient for 1911-2010 is positive and exceeds twice the error in that trend, but five have stable or cooling trends. And nine of the twelve stations are located close to the coast. The interior of the island is therefore very under-represented.

Fig. 109.1: The (approximate) locations of the twelve longest weather station records in Haiti and the Dominican Republic. 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 stations with more than 400 months of data.

The other distinction between Haiti and The Dominican Republic is in the amount of observed warming seen in each country. The trend for Port-au-Prince airport is shown in Fig. 108.2 below and it clearly exhibits strong warming of over 3°C since 1900 with most of the warming having occurred since 1940. However the data is discontinuous and is not corroborated by any other station, mainly because there are no other stations with enough data locally. In fact it is the only temperature record of any significant length (i.e. over 400 months of data) in the whole of Haiti. It is also from a single station based in the capital city where over 10% of the Haitian population live, so that may also have a strong impact on the trend (e.g. note the difference in trends between Jakarta and the rest of Indonesia shown in Post 31).

 

Fig. 109.2: The mean temperature change for Port-au-Prince relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1916 to 1995 and has a strong positive gradient of +4.18 ± 0.09 °C per century.

 

In contrast, the Dominican Republic has eleven stations with data extending back to the 1960s or beyond, but none with data before 1940. Its mean temperature anomaly (MTA) over time is shown in Fig. 109.3 below, and while it also exhibits some warming since 1950, it is much more modest at about 1°C. However, this is not the whole story as there are issues regarding data coverage, both geographically and temporally.

 

Fig. 109.3: The mean temperature change for the Dominican Republic relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1951 to 2010 and has a positive gradient of +1.91 ± 0.13 °C per century.

 

The MTA in Fig. 109.3 was calculated by averaging the temperature anomalies from the eleven longest temperature records for the country. All these records had over 400 months of temperature data before the end of 2013. 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 1961 to 1990, and then subtracting the MRTs from the raw temperature data to generate the anomalies. If a station had at least twelve valid temperatures per month within the MRT interval then its anomalies were included in the MTA calculation. The total number of stations included in the MTA in Fig. 109.3 each month is indicated in Fig. 109.4 below.

 

Fig. 109.4: The number of station records included each month in the mean temperature anomaly (MTA) trend for the Dominican Republic in Fig. 109.3.

 

The data in Fig. 109.4 suggests that the most reliable data in Fig. 109.3 is between 1950 and 1990 as this is where the MTA is calculated using the largest number of stations. Yet the data in Fig. 109.3 suggests that the warming over this interval is negligible (i.e less than 0.2°C) with far more warming occurring in the 1990s where there is much less data. The lack of data for the interior of the Dominican Republic may also play an important factor in affecting the reliability of the warming trend.

Next I calculate the corresponding MTA result based on data that has been adjusted by Berkeley Earth (BE). The result is shown in Fig. 109.5 below and like the raw data in Fig. 109.3 it exhibits a strong warming trend. However in this case, the warming seen for adjusted data is actually less than that seen for the raw data with temperatures rising by only 0.7°C since 1950 compared to about 1°C in Fig. 109.3. This is reflected in the gradients of the best fits in each case with the best bit gradient in Fig. 109.3 being almost 50% greater than the equivalent in Fig. 109.5.

 

Fig. 109.5: Temperature trends for the Dominican Republic based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1951-2010 and has a gradient of +1.28 ± 0.06°C/century.

 

Comparing the curves in Fig. 109.5 with the published Berkeley Earth (BE) version in Fig. 109.6 below indicates remarkably good agreement at least as far back as 1950. This indicates that the simple averaging of anomalies to generate the MTA in Fig. 109.3 is as effective and accurate as the more complex gridding method used by Berkeley Earth. It also means that the averaging process cannot be responsible for the difference in trends between that using unadjusted data in Fig. 109.3 and that using adjusted data in Fig. 109.5.

 

Fig. 109.6: The temperature trend for the Dominican Republic since 1820 according to Berkeley Earth.

 

The differences between the MTA in Fig. 109.3 and the BE versions using adjusted data in Fig. 109.5 and Fig. 109.6 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. 109.3 and Fig. 109.5. The magnitudes of these adjustments are shown graphically in Fig. 109.7 below. The blue curve is the difference in MTA values between adjusted (Fig. 109.5) and unadjusted data (Fig. 109.3), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both show significant fluctuations, but there is a distinct negative trend overall.

 

Fig. 109.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 109.5 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 1951-2010 has a negative gradient of -0.62 ± 0.06 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

 

Summary

According to the raw unadjusted temperature data, the climate of the Dominican Republic may have warmed by as much as 1°C over the past sixty years (see Fig. 109.3). But most of this warming appear to have occurred in the 1990s when there were fewer active stations (see Fig. 109.4). In contrast, there appears to be very little warming before 1990.

Over the same period adjusted temperature data from Berkeley Earth claims to show that the climate of the Dominican Republic has warmed more steadily, but by only 0.7°C since 1950 (see Fig. 109.5).

The lack of data for the Dominican Republic before 1950 and from its interior is a concern.

The data for Haiti comes from only a single station (Port-au-Prince airport) and exhibits much more warming than is seen for the Dominican Republic. It is also discontinuous at multiple times in its history and is uncorroborated by any other data.


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in Haiti.

List of all stations in the Dominican Republic.

108. Jamaica and Grand Cayman - temperature trends WARMING

To the south of Cuba lie the Cayman Islands and Jamaica. These islands have only five significant stations between them, one on Grand Cayman and the other four in Jamaica. Their locations are shown on the map in Fig. 108.1 below.

Fig. 108.1: The (approximate) locations of the five medium weather station records in Jamaica and Grand Cayman. Those stations with a high warming trend between 1911 and 2010 are marked in red.

All are medium stations with over 480 months of data, but only one has more than 900 months of data (Kingston-Norman Manley). Two stations have virtually no data before 1960 (Grand Cayman and Montego Bay) and two have virtually none after (Kingston and Negril Point Lighthouse). All five stations exhibit warming tends, where a warming trend is defined as one where the temperature gradient for 1911-2010 is positive and exceeds twice the error in that trend. The average of the temperature anomalies from these five stations is shown in Fig. 108.2 below. The mean temperature anomaly (MTA) for the region exhibits two distinct warming trends, a moderate warming of 0.68°C per century before 1980 and a much larger jump after.

Fig. 108.2: The mean temperature change for Jamaica and Grand Cayman relative to the 1941-1980 monthly averages. The best fit is applied to the monthly mean data from 1901 to 1980 and has a positive gradient of +0.68 ± 0.07 °C per century.

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 1941 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 per month within the MRT interval then its anomalies were included in the MTA calculation. The total number of stations included in the MTA in Fig. 108.2 each month is indicated in Fig. 108.3 below.

Fig. 108.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Jamaica and Grand Cayman in Fig. 108.2.

Next I calculate the corresponding MTA result based on data that has been adjusted by Berkeley Earth (BE). The result is shown in Fig. 108.4 below and, unlike the raw data in Fig. 108.2, it exhibits a more linear warming trend with temperatures rising by about 1°C since 1910.

Fig. 108.4: Temperature trends for Jamaica and Grand Cayman 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 +0.87 ± 0.03°C/century.

Comparing the curves in Fig. 108.4 with the published Berkeley Earth (BE) version for Jamaica only in Fig. 108.5 below indicates remarkably good agreement at least as far back as 1920. This is despite the MTA in Fig. 108.4 including data from Grand Cayman. This would suggest that the simple averaging of anomalies to generate the MTA in Fig. 108.2 is as effective and accurate as the more complex gridding method used by Berkeley Earth. It also means that the averaging process cannot be responsible for the difference in trends between that using unadjusted data in Fig. 108.2 and that using adjusted data in Fig. 108.4.

Fig. 108.5: The temperature trend for Jamaica since 1820 according to Berkeley Earth.

The differences between the MTA in Fig. 108.2 and the BE versions using adjusted data in Fig. 108.4 and Fig. 108.5 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. 108.2 and Fig. 108.4. The magnitudes of these adjustments are shown graphically in Fig. 108.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 108.4) and unadjusted data (Fig. 108.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. In this case, unlike most instances in previous posts for the region, the adjustments actually reduce the amount of warming.

Fig. 108.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 108.4 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 1911-1980 has a negative gradient of -0.252 ± 0.015 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Summary

According to the raw unadjusted temperature data, the climate of Jamaica and Grand Cayman has probably warmed by between 1°C and 2°C over the past century with only 0.5°C of warming occurring before 1980 (see Fig. 108.2). However, given that this is based on only five sets of data, and only three at most at any given time, this result contains a high degree of error.

Over the same period adjusted temperature data from Berkeley Earth claims to show that the climate of Jamaica has warmed by almost 1.0°C since 1900 (see Fig. 108.4) and 1.5°C since 1840 (see Fig. 108.5).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in Jamaica.

List of all stations in the Cayman Islands.

107. Cuba - temperature trends STABLE

Since 1958 Cuba has been subject to an almost total trade embargo by its nearest neighbour, the USA. The result is that much of Cuba looks like it is stuck in a time warp from the 1950s, and the same can be said for its climate. There has been no permanent rise in temperatures in over 130 years. Are these two facts related? How much do industrialization and consumerism lead to warming of the local climate, and how much is due to carbon dioxide? Cuba could be an interesting case study.

Fig. 107.1: The mean temperature change for Cuba relative to the 1971-2000 monthly averages. The best fit is applied to the monthly mean data from 1888 to 2007 and has a slight negative gradient of -0.05 ± 0.05 °C per century.

Like all the US states that border the Gulf of Mexico, Cuba has not experienced any global warming. In fact over the last 120 years the climate of Cuba has remained fairly stable as shown by the mean temperature anomaly (MTA) data for the state illustrated in Fig. 107.1 above.

The MTA in Fig. 107.1 was calculated by averaging the temperature anomalies from the eleven longest temperature records for the state. All these records had over 400 months of temperature data before the end of 2013 but there is only long stations with more than 1200 months of data, and eight medium stations with over 480 months of data. 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 1971 to 2000, 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 MTA calculation. In total ten stations were included with only one (Havana) being excluded for lack of data between 1971 and 2000. The total number of stations included in the MTA in Fig. 107.1 each month is indicated in Fig. 107.2 below. The peak just around 1980 suggests that the 1971-2000 interval was indeed the most appropriate. It also shows, though, that the trend before 1940 is dependent on data from only one station: Habana Casa Blanca.

Fig. 107.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Cuba in Fig. 107.1.

The locations of the eleven main stations are shown in the map in Fig. 107.3 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 capital, Havana. This variation in station density is probably not sufficient to significantly distort the average in Fig. 107.1 from its true value though. In which case the simple average of the anomalies from all stations used to construct the MTA in Fig. 107.1 should still yield a fairly accurate temperature trend for the country as a whole. Only four stations in Cuba appear to have warming trends, where a warming trend is defined as one where the temperature gradient for 1911-2010 is positive and exceeds twice the error in that trend.

Fig. 107.3: The (approximate) locations of the eleven longest weather station records in Cuba. 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 stations with more than 400 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. 107.4 below and, unlike the raw data in Fig. 107.1, it exhibits a strong warming trend with temperatures rising by over 1°C since 1890.

Fig. 107.4: Temperature trends for Cuba based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1891-2010 and has a gradient of +0.79 ± 0.02°C/century.

Comparing the curves in Fig. 107.4 with the published Berkeley Earth (BE) version in Fig. 107.5 below indicates remarkably good agreement at least as far back as 1920. This indicates that the simple averaging of anomalies to generate the MTA in Fig. 107.1 is as effective and accurate as the more complex gridding method used by Berkeley Earth. It also means that the averaging process cannot be responsible for the large difference in trends between that using unadjusted data in Fig. 107.1 and that using adjusted data in Fig. 107.4.

Fig. 107.5: The temperature trend for Cuba since 1820 according to Berkeley Earth.

The differences between the MTA in Fig. 107.1 and the BE versions using adjusted data in Fig. 107.4 and Fig. 107.5 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. 107.1 and Fig. 107.4. The magnitudes of these adjustments are shown graphically in Fig. 107.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 107.4) and unadjusted data (Fig. 107.1), 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 1880 of up to 1.8°C.

Fig. 107.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 107.4 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 1891-2010 has a positive gradient of +0.823 ± 0.019 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Summary

According to the raw unadjusted temperature data, over the past century the climate of Cuba has remained stable (see Fig. 107.1).

Over the same period adjusted temperature data from Berkeley Earth claims to show that the climate of Cuba has warmed by as much as 1.0°C (see Fig. 107.4 and Fig. 107.5).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations and 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.