117: Cameroon - temperature trends STABLE before 1990

Like Chad (see Post 15) and the Central African Republic (see Post 116), Cameroon has no significant temperature data before 1950. However, the change in its climate is more reminiscent of that of West Africa (see Post 114). Before 1990 the climate is stable; thereafter the mean temperature appears to increase by about 0.5°C (see Fig. 117.1 below). This is a modest temperature rise and much less than the often quoted IPCC global value.

 

Fig. 117.1: The mean temperature change for Cameroon since 1940 relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1956 to 1990 and has a slight negative gradient of -0.02 ± 0.20 °C per century.

 

In order to quantify the changes to the climate of Cameroon since 1940 the temperature anomalies for the fifteen stations with the most data (i.e. over 300 months of data) 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, 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. 117.1 above and clearly shows that temperatures declined continuously from 1940.

The process of determining the MTA in Fig. 117.1 involved first determining 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 per month within the MRT interval then its anomalies were included in the calculation of the mean temperature anomaly (MTA). The total number of stations included in the MTA in Fig. 117.1 each month is indicated in Fig. 117.2 below. The peak in the frequency between 1950 and 1990 suggests that the 1951-1980 interval was probably the most appropriate to use for the MRTs.

 

Fig. 117.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Cameroon in Fig. 117.1.

 

The locations of the sixteen stations whose data was used to determine the MTA in Fig. 117.1 are shown in the map in Fig. 117.3 below. Eight are medium stations with over 480 months of data, but only one station has over 800 months of data before 2014, and only two have any data before 1950 (see here for a full list). In addition, there are another eight stations with over 300 months of data. According to the map below the geographical spread of stations is fairly uniform, in which case the simple average of the anomalies from all stations used to construct the MTA in Fig. 117.1 should yield a fairly accurate temperature trend for the country as a whole.

 

Fig. 117.3: The (approximate) locations of the sixteen longest weather station records in Cameroon. 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 medium stations with over 480 months of data, while diamonds denote stations with more than 300 months of data.

 

The MTA in Fig. 117.1 shows the temperature change over the time period where the data is most numerous and therefore reliable. There are, however, two stations with data before 1940. These are in the two main cities of Douala and Yaoundé. The fact that in both cases the data is discontinuous with large gaps in the data between 1900 and 1940, and both stations are located in large urban areas, would suggest the data for both is not representative of the country as a whole. If we do include this earlier data we get the extended MTA shown in Fig. 117.4 below. This appears to imply an additional warming of 1.3°C occurred before 1940 when increases in carbon dioxide levels were small which also raises questions about the quality of the data. For these reasons I would tend to discount all the MTA data before 1950.

 

Fig. 117.4: The mean temperature change for Cameroon since 1880 relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1956 to 1990 and has a slight negative gradient of -0.02 ± 0.20 °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. 117.5 below. This again was determined by averaging each monthly anomaly from the sixteen longest stations and suggests that the climate was fairly stable from 1940 until 1980 but then warmed by about 0.7°C thereafter.

 

Fig. 117.5: Temperature trends for Cameroon based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1952-2011 and has a positive gradient of +1.46 ± 0.05°C/century.

 

Comparing the curves in Fig. 117.5 with the published Berkeley Earth (BE) version for Cameroon in Fig. 117.6 below shows that there is good agreement between the two sets of data. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 117.5 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 117.6. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 117.1. How Berkeley Earth managed to determine the temperature change in Cameroon between 1900 and 1950 in Fig. 17.6 when there is virtually no data for this period is a point of debate.

 

Fig. 117.6: The temperature trend for Cameroon since 1840 according to Berkeley Earth.

 

The differences between the MTA in Fig. 117.4 and the BE versions using adjusted data in Fig. 117.5  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. 117.4 and Fig. 117.5. The magnitudes of these adjustments are shown graphically in Fig. 117.7 below. The blue curve is the difference in MTA values between adjusted (Fig. 117.5) and unadjusted data (Fig. 117.4), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Neither are larger than about 0.2°C.

 

Fig. 117.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 117.5 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 1952-2011 has a positive gradient of +0.41 ± 0.03 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

 

Summary

According to the raw unadjusted temperature data, the climate of Cameroon was stable until 1990 and then warmed by between 0.3°C and 0.6°C (see Fig. 117.1).

Over the same period adjusted temperature data from Berkeley Earth appears to show that the climate of Cameroon has warmed by about 0.8°C (see Fig. 117.5).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

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

116: Central African Republic (CAR) - temperature trends COOLING

There are thirteen medium stations with over 480 months of data in the Central African Republic (CAR), but only one station has over 800 months of data before 2014, and none have any data before 1940 (see here for a full list). In addition, there are another two stations with over 300 months of data.

The neighbouring countries of Chad, Cameroon, Congo and the DRC (formerly Zaire) have virtually no data before 1940 either. Only Sudan has significant data pre-1940. This means it is not possible to know the true temperature trend of CAR before 1940. What the data that we do have tells us is that the climate of the Central African Republic cooled by over 0.5°C from 1950 onwards (see Fig. 116.1 below).

 

Fig. 116.1: The mean temperature change for the Central African Republic relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1941 to 2005 and has a negative gradient of -0.50 ± 0.11 °C per century.

 

In order to quantify the changes to the climate of the CAR since 1940 the temperature anomalies for each of the fifteen stations with the most data 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, 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. 116.1 above and clearly shows that temperatures declined continuously from 1940.

The process of determining the MTA in Fig. 116.1 involved first determining 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 mean temperature anomaly (MTA). The total number of stations included in the MTA in Fig. 116.1 each month is indicated in Fig. 116.2 below. The peak in the frequency between 1960 and 1990 suggests that the 1961-1990 interval was indeed the most appropriate to use for the MRTs.

 

Fig. 116.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for the Central African Republic in Fig. 116.1.

 

The locations of the fifteen stations with the most temperature data are shown in the map in Fig. 116.3 below. This appears to show that the geographical spread is fairly uniform, although there does appear to be more stations in the south of the country than in the north. This variation in station density is probably not sufficient to significantly distort the average in Fig. 116.1 from its true value though. In which case the simple average of the anomalies from all stations used to construct the MTA in Fig. 116.1 should still yield a fairly accurate temperature trend for the country as a whole.

 

Fig. 116.3: The (approximate) locations of the fifteen longest weather station records in the Central African 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 medium stations with over 480 months of data, while diamonds denote stations with more than 250 months of data.

 

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 116.4 below. This again was determined by averaging each monthly anomaly from the fifteen longest stations and suggests that the climate was fairly stable before 1980 but then warmed by about 0.75°C thereafter.

 

Fig. 116.4: Temperature trends for the Central African Republic based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1941-2010 and has a positive gradient of +0.83 ± 0.08°C/century.

 

If we next compare the curves in Fig. 116.4 with the published Berkeley Earth (BE) version for the CAR in Fig. 116.5 below we see that there is good agreement between the two sets of data after 1940. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 116.4 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 116.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 116.1. What is more difficult to explain is how Berkeley Earth have determined the climate for the CAR as far back as 1880 when there is virtually no reliable temperature data for the country before 1940.

 

Fig. 116.5: The temperature trend for the Central African Republic since 1850 according to Berkeley Earth.

 

The differences between the MTA in Fig. 116.1 and the BE version using adjusted data in Fig. 116.4  are probably 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. 116.1 and Fig. 116.4. The magnitudes of these adjustments are shown graphically in Fig. 116.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 116.4) and unadjusted data (Fig. 116.1), 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 1940 of up to 1.5°C.

 

Fig. 116.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 116.4 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 1941-2010 has a positive gradient of +1.32 ± 0.03 °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 CAR has cooled from 1940 by about 0.5°C (see Fig. 116.1).

Over the same period adjusted temperature data from Berkeley Earth appears to show that the climate of the CAR has warmed by over 0.5°C (see Fig. 116.5).

 


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

Link to list of all stations in the Central African Republic and their raw data files.

115: Chad - temperature trends WARMING 2°C after 1980

Any analysis of the climate of Chad is complicated by two factors: the first is the lack of data; the second is the gap in the temperature data from 1979 to 1986 that coincides with a sudden jump in temperatures. The longest temperature record for Chad has less than 800 months of data before 2014 and only extends back to 1941. In total there are only seven medium stations with over 480 months of data and a further five stations with over 300 months of data. The locations of these stations are shown on the map in Fig. 115.1 below. All but one of these twelve stations are in the southern half of the country.

Fig. 115.1: The (approximate) locations of the twelve longest weather station records in Chad. 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 medium stations with over 480 months of data, while diamonds denote stations with more than 300 months of data.

In order to quantify the changes to the climate of Chad since 1941 the temperature anomalies for each of the twelve stations shown in Fig. 115.1 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, 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. 115.2 below and clearly shows that temperatures declined slowly before 1980 by about 0.4°C in total, and rose more rapidly by up to 2°C thereafter. However, the large gap in data from 1979 to 1987, together with the abrupt jump in temperatures after 1987, together raise questions over the reliability of the post-1987 data.

Fig. 115.2: The mean temperature change for Chad relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1941 to 1975 and has a negative gradient of -1.04 ± 0.38 °C per century.

The process of determining the MTA in Fig. 115.2 involved first determining 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 per month within the MRT interval then its anomalies were included in the calculation of the mean temperature anomaly (MTA). The total number of stations included in the MTA in Fig. 115.2 each month is indicated in Fig. 115.3 below. The peak in the frequency between 1950 and 1980 suggests that the 1951-1980 interval was indeed the most appropriate to use for the MRTs.

Fig. 115.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for Chad in Fig. 115.2.

If we next consider the change in temperature based on Berkeley Earth (BE) adjusted data we get the MTA data in Fig. 115.4 below. This again was determined by averaging each monthly anomaly from all the available stations and suggests that the climate was stable before 1980 and only warmed by about 1°C thereafter. So there is less cooling before 1980 and less warming after. It also appears that the data after 1987 has been offset downwards by about 0.5°C in order to eliminate some of the temperature rise seen in Fig. 115.2.

Fig. 115.4: Temperature trends for Chad based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1941-1975 and has a very slight negative gradient of -0.04 ± 0.16°C/century.

If we compare the curves in Fig. 115.4 with the published Berkeley Earth (BE) version in Fig. 115.5 below we see that there is good agreement between the two sets of data at least as far back as 1950. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 115.4 gives similar results to the more complex gridding method used by Berkeley Earth in Fig. 115.5. The official BE temperature trend also claims to know the temperature trend before 1940 and as far back as 1870, and also for all of the 1980s, even though there is no actual data in Chad for either time period.

Fig. 115.5: The temperature trend for Chad since 1850 according to Berkeley Earth.

The differences between the MTA in Fig. 115.2 and the BE version using adjusted data in Fig. 115.4  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. 115.2 and Fig. 115.4. The magnitudes of these adjustments are shown graphically in Fig. 115.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 115.4) and unadjusted data (Fig. 115.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. It can be seen that the main adjustment is a vertical offset of data after 1987.

Fig. 115.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 115.4 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 has a negative gradient of -1.17 ± 0.04 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

Summary

According to the raw unadjusted temperature data, the climate of Chad cooled by 0.4°C until 1975 and then warmed by about 2°C (see Fig. 115.2). However, the gap in data from 1979-1987 and the subsequent jump in temperatures thereafter may mean the rise post-1987 is only about 1.4°C and the net rise only 1°C.

Over the same period adjusted temperature data from Berkeley Earth appears to show that the climate of Chad has warmed by about 1.0°C (see Fig. 115.4). This is possibly the same as the raw data overall, but the pattern over time is different.


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

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

114: West Africa - temperature trends WARMING 0.7°C after 1980

There are fifteen countries that together make up West Africa: Mauritania, Mali, Burkina Faso, Niger, Nigeria, Benin, Togo, Ghana, Ivory Coast (Côte d'Ivoire), Liberia, Sierra Leone, Guinea, Guinea-Bissau, Senegal, and The Gambia. Unfortunately there are only seven long stations in the entire region with over 1200 months of data, most of which have cooling trends (see Fig. 114.1 below). There are, however, another 111 medium stations with over 480 months of data. Of these nearly 100 have over 600 months of data, nearly 50 have over 800 months of data and 11 have over 1000 months of data. For a full list see here.

While the region as a whole has reasonably good data, most individual countries do not. Most countries have fewer than ten long and medium stations in total. For that reason it makes sense to determine the temperature change across the region as a whole rather than concentrating on the data from individual countries. On the positive side, the distribution of stations is fairly uniform so averaging of the mean temperature anomaly (MTA) data should yield accurate results for the temperature change at least for the most recent 800 months (i.e. as far back as 1950), and possibly as far back as 1920.

Fig. 114.1: The (approximate) locations of the 118 longest weather station records in West Africa. 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 temperature anomalies for each station in Fig. 114.1 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 per month within the MRT interval then its anomalies were included in the calculation of the regional mean temperature anomaly (MTA). The resulting MTA after 1900 is shown in Fig. 114.2 below. It can be seen that before 1975 the climate was slowly cooling with the mean temperature falling by about 0.2°C over the preceding 75 years. Then after 1975 there was a rapid warming of about 0.75°C. The net warming since 1900 is therefore just over 0.5°C.

Fig. 114.2: The mean temperature change for West Africa since 1880 relative to the 1951-1980 monthly averages. The best fit is applied to the monthly mean data from 1901 to 1970 and has a negative gradient of -0.25 ± 0.08 °C per century.

The total number of stations included in the MTA in Fig. 114.2 each month is indicated in Fig. 114.3 below. The peak in the frequency around 1970 suggests that the 1951-1980 interval for the MRTs was indeed the most appropriate to use. It also indicates that there are a couple of stations with data before 1880 and about six with data before 1900.

Fig. 114.3: The number of station records included each month in the mean temperature anomaly (MTA) trend for West Africa in Fig. 114.2.

 

Unfortunately the data before 1880 is fragmented with large fluctuations in its values, as the MTA in Fig. 114.4 below shows. It is therefore likely to be very unreliable and thus adds nothing to our understanding of climate change in the region.

Fig. 114.4: The mean temperature change for West Africa since 1840. The best fit has a slight negative gradient of -0.25 ± 0.08 °C per century.

In contrast to Fig. 114.2, the corresponding MTA dataset based on data that has been adjusted by Berkeley Earth (BE) exhibits a strong warming trend before 1975 with temperatures rising by over 1.0°C since 1900 (see Fig. 114.5 below).

Fig. 114.5: Temperature trends for West Africa based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1901-2010 and has a gradient of +0.85 ± 0.03°C/century.

If we next compare the curves in Fig. 114.5 with the published Berkeley Earth (BE) version for West Africa in Fig. 114.6 below we see that there is remarkably good agreement between the two sets of data at least as far back as 1900. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 114.5 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 114.6. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 114.2. This also suggests that any difference between the two averages cannot be due primarily to the averaging process, but must instead be due at least in part to the temperature adjustments made by Berkeley Earth.

Fig. 114.6: The temperature trend for West Africa since 1840 according to Berkeley Earth.

The differences between the MTA in Fig. 114.2 and the BE versions using adjusted data in Fig. 114.5  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. 114.2 and Fig. 114.5. The magnitudes of these adjustments are shown graphically in Fig. 114.7 below.  

Fig. 114.7: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 114.5 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 1921-2010 has a slight negative gradient of -0.057 ± 0.009 °C per century. The orange curve shows the contribution just from breakpoint adjustments.

The blue curve in Fig. 114.7 above is the difference in MTA values between adjusted (Fig. 114.5) and unadjusted data (Fig. 114.2), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. Both adjustments are negligible after 1920, but before 1920 they add an additional warming of up to 0.8°C. But as Fig. 114.3 shows, the MTA data before 1920 is based on temperature data from at most 21 stations. So how reliable is the raw data before 1920? And how reliable are the BE adjustments before 1920?

The case in favour of believing the raw unadjusted data before 1920 is two-fold: that it is the real data, and that it follows the same trend as the raw data after 1920. In addition, the case against the adjusted data is that the adjustments are so large relative to any made after 1920. In reality, it is difficult to say categorically which is the more reliable, but the unadjusted data does also correlate with raw unadjusted data from elsewhere, such as southern Africa (see Posts 37, 77, 78, 79) and the Southern Hemisphere (see Post 64).

Summary

According to the raw unadjusted temperature data, the climate of West Africa cooled until 1975 and then warmed by about 0.75°C (see Fig. 114.2). The net warming since 1900 is only about 0.5°C.

Over the same period adjusted temperature data from Berkeley Earth appears to show that the climate of West Africa has warmed by over 1.0°C (see Fig. 114.5).

The data before 1920 is based on a small sample (only 21 stations) and so could be considered highly uncertain.


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

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

113: The Guianas - temperature trends STABLE

The Guianas is the region of north-eastern South America that comprises the three territories of Guyana (formerly British Guiana), Suriname (formerly Dutch Guiana) and French Guiana. It sits on the Atlantic coast between Venezuela and Brazil, and as the data in Fig. 113.1 below shows, it does not appear to have experienced any significant climate change over the last 100 years, although the mean temperature has fluctuated significantly by up to 1°C (see yellow curve).

Fig. 113.1: The mean temperature change for the Guianas relative to the 1961-1990 monthly averages. The best fit is applied to the monthly mean data from 1896 to 2005 and has a slight positive gradient of +0.11 ± 0.04 °C per century.

The MTA in Fig. 113.1 was calculated by averaging the temperature anomalies from the fourteen longest temperature records for the region. Eight of these records were from medium stations with over 480 months of temperature data before the end of 2013, but there are only two long stations with more than 1200 months of data.

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 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. 113.1 each month is indicated in Fig. 113.2 below. The peak just around 1975 suggests that the 1961-1990 interval was indeed the most appropriate.

Fig. 113.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for the Guianas in Fig. 113.1.

The locations of the fourteen main stations are shown in the map in Fig. 113.3 below. This appears to show that the geographical spread is fairly uniform, although there does appear to be far more stations in Suriname than in either Guyana or French Guiana. This variation in station density is probably not sufficient to significantly distort the average in Fig. 113.1 from its true value though. In which case the simple average of the anomalies from all stations used to construct the MTA in Fig. 113.1 should still yield a fairly accurate temperature trend for the region as a whole. 

Overall there are more stations close to the coast than inland, and the coastal stations appear more likely to have warming trends. A warming trend is defined here as one where the temperature gradient for 1911-2010 is positive and exceeds twice the uncertainty in that trend.

Fig. 113.3: The (approximate) locations of the fourteen longest weather station records in the Guianas. 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 300 months of data.

In contrast to Fig. 113.1, the corresponding MTA dataset based on data that has been adjusted by Berkeley Earth (BE) exhibits a strong warming trend with temperatures rising by over 1.5°C since 1890 (see Fig. 113.4 below).

Fig. 113.4: Temperature trends for the Guianas based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1896-2005 and has a gradient of +1.06 ± 0.03°C/century.

If we next compare the curves in Fig. 113.4 with the published Berkeley Earth (BE) version for Suriname in Fig. 113.5 below (where most stations are located) we see that there is remarkably good agreement between the two sets of data at least as far back as 1900. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 113.4 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 113.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 113.1.

Fig. 113.5: The temperature trend for Suriname since 1820 according to Berkeley Earth.

The differences between the MTA in Fig. 113.1 and the BE versions using adjusted data in Fig. 113.4  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. 113.1 and Fig. 113.4. The magnitudes of these adjustments are shown graphically in Fig. 113.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 113.4) and unadjusted data (Fig. 113.1), 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 1900 of up to 1.6°C.

Fig. 113.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 113.4 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 1896-2005 has a positive gradient of +0.96 ± 0.03 °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 the Guianas has remained stable (see Fig. 113.1).

Over the same period adjusted temperature data from Berkeley Earth appears to show that the climate of the Guianas has warmed by as much as 1.6°C (see Fig. 113.4).


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

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

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

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

112: Venezuela - temperature trends WARMING

The climate of Venezuela is interesting because the country sits between Colombia to the west and the Lesser Antilles to the north. In this blog I have already examined the climate for both these regions and the results are not entirely consistent. The mean temperature of Colombia has remained fairly stable since 1940, increasing only slightly by about 0.1°C (see Fig. 95.2 in Post 95). The caveat to this is that there is no temperature data for the country before 1920 and only two stations of note with data before 1940. The Lesser Antilles, on the other hand, have more data but spread over a larger area, and this data shows much more warming, up to 2°C since 1890 (see Fig. 111.3 in Post 111). It turns out that the climate of Venezuela more closely resembles that of the Lesser Antilles than it does its neighbour Colombia as can be seen in Fig. 112.1 below.

Fig. 112.1: The mean temperature change for Venezuela relative to the 1976-2005 monthly averages. The best fit is applied to the monthly mean data from 1941 to 1980 and has a slight positive gradient of +0.28 ± 0.31 °C per century.

The main features of the data in Fig. 112.1 are very similar to those seen in Fig. 111.3 of Post 111. Between 1940 and 1980 the climate is stable, with the mean temperature rising by at most 0.1°C, but after 1980 there is a rapid temperature increase of over 0.5°C. This is consistent with other trends seen in the region such as for Puerto Rico (see Fig. 110.1 in Post 110) and the Dominican Republic (see Fig. 109.3 in Post 109). Yet the mean temperature anomaly (MTA) dataset in Fig. 112.1 also displays a large jump in temperatures of over 1.5°C before 1940. This is not seen in the Puerto Rico or the Dominican Republic data, nor is it seen in the data for Colombia (see Fig. 95.2 in Post 95), but it is seen in the data for the Lesser Antilles (see Fig. 111.3 in Post 111). In both cases the MTA before 1940 is based on data from only about five stations or less (see Fig. 112.2 below and Fig. 111.4 of Post 111), yet the fact that they corroborate each other suggests that the data may be more reliable than than I first thought and may be indicative of real climate change. The problem is that, if this is true, it poses a lot of difficult questions about the real nature of climate change.

Fig. 112.2: The number of station records included each month in the mean temperature anomaly (MTA) trend for Venezuela in Fig. 112.1.

If we assume that the temperature rises of 1.5°C from 1900 to 1940 that are seen in Venezuela (see Fig. 112.1 above) and the Lesser Antilles are real, then we need to ask the question, why?

Historical measurements of carbon dioxide (CO₂) levels suggest that atmospheric CO₂ levels increased from about 290 ppm in 1880 to about 310 ppm in 1940. But even with the best will in the world it is difficult to believe that a 7% rise in CO₂ would result in a 1.5°C temperature rise. In Fig. 87.3 of Post 87 I showed that the most it could lead to was a rise of 0.08°C, and even then three quarters of that rise is likely to be negated by the pre-existing presence of water vapour in the atmosphere, the absorption spectrum of which overlaps both edges of the 15 µm CO₂ absorption band. So the temperature rise seen before 1940 in Venezuela is actually nearly one hundred times greater than would be expected from CO₂ alone. So if CO₂ cannot explain the temperature rise, what does that say about our faith in climate stability? For if the climate can fluctuate by 1.5°C from time to time off its own bat, why should we care about CO₂?

Then there is the more practical issue: why did no-one even notice this temperature rise? We are constantly being told by climate scientists that a 1.5°C rise in global temperatures would be disastrous for the planet. Yet just such an increase appears to have occurred in Venezuela and the Caribbean over a century ago and nothing untoward happened. 

Fig. 112.3: The (approximate) locations of the 21 medium weather station records in Venezuela. 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 stations with over 800 months of data, while diamonds denote stations with more than 480 months of data.

The mean temperature anomalies (MTA) in Fig. 112.1 were calculated by averaging the temperature anomalies from the 38 longest temperature records for the state. The anomalies for each station were determined using the usual method as outlined in Post 47. All the records used in calculating the MTA had over 240 months of temperature data before the end of 2013 and 21 were medium stations with over 480 months of data. Of these three had over 1000 months of data and a further ten had over 800 months of data. For a full list of stations see here. 

The locations of the medium stations are illustrated in Fig. 112.3 above. This map appears to show that the geographical spread of these stations is fairly uniform but confined to the northern half of the country. The variation in station density is probably not sufficient to significantly distort the average in Fig. 112.1 from its true value though. In which case the simple average of the anomalies from all stations used to construct the MTA in Fig. 112.1 should still yield a fairly accurate temperature trend for the country as a whole. This can be verified by calculating the equivalent MTA, but using Berkeley Earth (BE) adjusted data, and comparing the results with the official BE version. If they are the same then the averaging process should be sufficiently accurate.

Fig. 112.4: Temperature trends for Venezuela based on Berkeley Earth adjusted data. The best fit linear trend line (in red) is for the period 1941-2010 and has a gradient of +1.06 ± 0.07°C/century.

The corresponding MTA result based on data that has been adjusted by Berkeley Earth (BE) is shown in Fig. 112.4 above and, unlike the raw data in Fig. 112.1, it exhibits a strong warming trend that is more uniform in its gradient. The overall temperature rise from 1900 to 2010 is about 1.5°C and so is significantly less than the 2.2°C that is seen with the raw data in Fig. 112.1.

If we then compare the curves in Fig. 112.4 with the published Berkeley Earth (BE) version in Fig. 112.5 below we see that there is remarkably good agreement between the two sets of data at least as far back as 1920. This indicates that the simple averaging of anomalies used to generate the BE MTA in Fig. 112.4 is as effective and accurate as the more complex gridding method used by Berkeley Earth in Fig. 112.5. In which case simple averaging should be just as effective and accurate in generating the MTA using raw unadjusted data in Fig. 112.1.

Fig. 112.5: The temperature trend for Venezuela since 1820 according to Berkeley Earth.

The differences between the MTA in Fig. 112.1 and the BE versions using adjusted data in Fig. 112.4 and Fig. 112.5 are therefore 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. 112.1 and Fig. 112.4. 

The magnitudes of these adjustments are shown graphically in Fig. 112.6 below. The blue curve is the difference in MTA values between adjusted (Fig. 112.4) and unadjusted data (Fig. 112.1), while the orange curve is the contribution to those adjustments arising solely from breakpoint adjustments. The vertical offset between the two curves is due to the difference in MRT intervals used by Berkeley Earth (1961-1990) and for Fig. 112.1 in this blog (1976-2005). What is clear is that after 1960 any adjustments made by Berkeley Earth to the data have little effect on the overall trend. However, before 1940 these adjustments appear to reduce the magnitude of the temperature rise by about 0.5°C. Overall the adjustments tend to make the MTA curve more linear.

Fig. 107.6: The contribution of Berkeley Earth (BE) adjustments to the anomaly data in Fig. 112.4 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 +0.19 ± 0.10 °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 Venezuela has warmed by over 2°C (see Fig. 112.1).

The climate change seen for Venezuela appears to be very similar to that of the Lesser Antilles (see Fig. 111.3 of Post 111) with 75% of the warming occurring before 1940 and very little warming between 1940 and 1980. This does not correlate with changes to atmospheric carbon dioxide concentrations over the same period. 

The origin of the 1.5°C warming before 1940 remains unexplained but its similarity to data from the Lesser Antilles suggests that the temperature change is real and not the result of measurement biases or errors.

The adjusted temperature data from Berkeley Earth appears to show that the climate of Venezuela has warmed more continuously (or linearly) and by about 1.4°C (see Fig. 112.4 and Fig. 112.5) since 1880.


Acronyms

BE = Berkeley Earth.

MRT = monthly reference temperature (see Post 47).

MTA = mean temperature anomaly.

List of all stations in Venezuela and their raw data files.