View source for OR/17/026 Appendix 3 - Mean monthly change

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As discussed in [[OR/17/026 Methodology|Methodology]], the recharge season generally considered as being from September through to April so the change in monthly recharge has been assessed for these months.

====A3.1 - Monthly changes during the 2020s====
Figure A12 shows the differences between the monthly recharge values calculated for the period between 2010 and 2039 and the simulated historic recharge values calculated between 1961 and 2009. The legend is set to negative values, i.e. future values less than historical values, are represented by a shade of colours from light brown/yellow to dark brown. Positive difference values, i.e. future values greater than historical values, are shown with colours ranging from light blue to dark blue. This figure shows that there is a general trend of increased recharge values for almost all months except for March and April where the trend is a reduction in future recharge values.

In addition, it can be inferred from Figure A12 that all scenarios produce future recharge values, the 20s recharge values, which are higher than the historical recharge values. However, detailed inspection, especially when interpreting the spatial variations of recharge values, reveals a more complex conclusion. For example, almost all scenarios show that there is increase in January recharge values across the study area especially to the south of England except scenarios afixo and afixq. However, scenarios afixc, afixj and afixk show reduction in January recharge over the north of England and north of Wales. In addition, scenarios afixh and afixl show significant increase in February recharge to the southwest of England, this is contradicted by the results obtained from scenarios afixj, afixk and afixm, which show reduction in February recharge values.

The monthly change by ensembles can be summarised as follows:

* afgcx reduction in March and April
* afixa reduction in March, February, November and December
* afixc reduction in March, April, September and October, but with increases in January, February and December
* afixh reduction in December
* afixi reduction in March, April, October and December
* afixj and afixk reduction January through to April, with January being the worse case.

* afixj shows an increase in December
* afixl reduction in March, but with increases in recharge in January, February, November and December

* afixm reduction in February, October and November
* afixo reduction from January to March, but increased recharge in December
* afixq reduction January, October and December but greater recharge in February to April
[[Image:OR17026figA12.jpg|thumb|center|600px|  '''Figure A12'''&nbsp;&nbsp;&nbsp;&nbsp;Changes in monthly recharge for the 2020s for all ensembles.    ]]

====A3.2 - Monthly changes during the 2050s====
Figure A13 shows the differences between the monthly recharge values calculated for the period between 2040 and 2069 and the simulated historic recharge values calculated between 1961 and 2009. The legend is the same as the one used in the [[OR/17/026 Summary of key results and narrative#Introduction|Introduction]] section. This figure shows that there is a general trend of increased recharge values for winter months of November, December, January and February and that there is a decrease in recharge values of May, June and August. There is an agreement between the scenarios, however, for recharge values to be higher during January, July and December in the future. This agreement between scenarios is more pronounced for this period, the 50s, than for the 20s discussed above. In addition, recharge values calculated for May are shown to be lower during the 50s than during the 20s. However, and similar to the in the previous section, it is difficult to infer one clear trend from the results obtained from all these scenarios when detailed inspection of the spatial variations of recharge values is undertaken.

The monthly change by ensembles can be summarised as follows:

* afgcx reduction in March, September with increased recharge in January
* afixa reduction in February, March and September with increased recharge in January, October, November and December. The latter two months the increases occur mainly in south-east England.
* afixc and afixh greater recharge in January, February and March along with increases in November and December
* afixi increased recharge in January to April with a reduction in September and October but with increases in November and December
* afixj, afixk and afixl increased recharge in January and February reduced in March and April with a reduction in September and October but with increases in November and December
* afixm greater recharge in January with a reduction in September and October but with increases in November and December
* afixo reduction in recharge in February and March as well as a reduction in September and October but with increases in November and December
* afixq greater recharge in January to March with a reduction in September and October but with increases in November and December

[[Image:OR17026figA13.jpg|thumb|center|600px|  '''Figure A13'''&nbsp;&nbsp;&nbsp;&nbsp;Changes in monthly recharge for the 2050s for all ensembles.    ]]

====A3.3 - Monthly changes during the 2080s====
Figure A14 shows the differences between the monthly recharge values calculated for the period between 2070 and 2099 and the simulated historic recharge values calculated between 1961 and 2009. The legend is the same as the one used in the [[OR/17/026 Appendix 3 - Mean monthly change#A3.2 - Monthly changes during the 2050s|Monthly changes during the 2050s]] section. Figure A14 shows that there is a general trend of increased recharge values for almost all months of the year except for August for which future calculated recharge values are in general lower than the historical recharge values.

There is a noticeable conclusion from this set of results, which is a more consistency of higher future recharge values across all models and for all months. Comparing with the 20s and 50s recharge values, the recharge values calculated over May and June are much higher in the 80s. A major outcome from the analysis of the results of this period is that it is most likely that more recharge is available during the 80s; however, it is very difficult to infer a general conclusion that describes all the spatial variations of recharge values.

The monthly change by ensembles can be summarised as follows:

* afgcx greater recharge in February with a reduction in recharge in September and October and an increase in November and December
* afixa greater recharge in January and September and an increase in October, November and December
* afixc and afixh both show a greater recharge in January to March with a reduction in recharge in September and October and an increase in November and December
* afixi greater recharge in January to February but reduction in March in the NW of England and reduction in April; reduction in September, October and December and with a greatly increased recharge in November
* afixj and afixk greater recharge January and February reduction in March and April and September with an increased very much increased recharge in December
* afixl greater recharge in January, reduction in February, March and April as well as in September and October but with a very much increased recharge in November and December
* afixm predominantly mixed spatial pattern of decreased and increased recharge January, February and March reduction in April, September, October and November but with an increase in December
* afixo increased recharge in February, reduction in March, September and October with increased November and December
* afixq increased in January and February, more modest increases in March and April reduction in September and October and increases in November and December
[[Image:OR17026figA14.jpg|thumb|center|600px|  '''Figure A14'''&nbsp;&nbsp;&nbsp;&nbsp;Changes in monthly recharge for the 2080s for all ensembles.    ]]
[[Category:OR/17/026 Summary of results for national scale recharge modelling under conditions of predicted climate change | 09]]