Meteorological agencies of Ireland and the UK have confirmed that winter (December to
February) 2013-14 (W2013/14) set records for precipitation totals and the occurrence of
extreme wind speeds1,2,3. Less clear is whether storminess (characterised as the frequency
and intensity of cyclones) during W2013/14 was equally unprecedented. We assess multidecadal
variations in storminess by considering frequency and intensity together and find
that W2013/14 was indeed exceptional. Given the potential societal impacts there is clearly
a need to better understand the processes driving extreme cyclonic activity in the North
Atlantic (NA)

CC Raible

E Kalnay

GP Compo

I Harris

LV Alexander

MC Serreze

RC Cornes

XL Wang

Nature Climate Change

English

Tom Matthews (5363627)

Conor Murphy (7190264)

Robert Wilby (1255929)

Shaun Harrigan (7190270)

Loughborough University Institutional Repository

1  NOTICE: this is the author’s version of a work that was accepted for publication in Nature Climate Change.   Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in:   Matthews, T., Murphy, C., Wilby, R.L. and Harrigan, S. 2014. Stormiest winter on record for Ireland and UK. Nature Climate Change, 4, 738-740. DOI: 10.1038/nclimate2336   which has been published in final form at: http://www.nature.com/nclimate/journal/v4/n9/full/nclimate2336.html   This article may be used for non-commercial purposes in accordance with Macmillan Publishers Limited Terms and Conditions for self-archiving.    2  Winter 2013-14: Stormiest on Record Tom Matthews1, Conor Murphy1, Robert L. Wilby2 & Shaun Harrigan1 1Irish Climate Analysis and Research Units (ICARUS), Department of Geography, National University of Ireland Maynooth, Ireland 2 Centre for Hydrological and Ecosystem Science, Department of Geography, Loughborough University, Loughborough, UK *Corresponding Author: tom.matthews@nuim.ie To the Editor – Meteorological agencies of Ireland and the UK have confirmed that winter (December to February) 2013-14 (W2013/14) set records for precipitation totals and the occurrence of extreme wind speeds1,2,3. Less clear is whether storminess (characterised as the frequency and intensity of cyclones) during W2013/14 was equally unprecedented. We assess multi-decadal variations in storminess by considering frequency and intensity together and find that W2013/14 was indeed exceptional. Given the potential societal impacts there is clearly a need to better understand the processes driving extreme cyclonic activity in the North Atlantic (NA).  We applied an automated detection routine4 (see Supplementary Information) to the NCEP15 and 20CR6 reanalysis datasets to determine cyclone frequency and intensity over four domains (Fig. 1a). Storminess (I) was calculated7as Iy = CyLy, where C is the number of cyclones observed during each winter in year y and L is their mean local Laplacian (intensity). Based on NCEP1 we find that W2013/14 was the stormiest in the 66-year record (1948/49 to 2013/14) across the NA, due to unprecedented cyclone intensity and frequency for the mid- and high-latitude NA, respectively (Fig. 1b). Intensity has increased over the NA consistent with trends in NCEP1 near-surface wind speeds (see Supplementary Information) and with previous investigations into cold season cyclone activity over the NA8, 9. W2013/14 is also ranked stormiest on record for the I-UK domain, where the combination of high cyclone frequency, together with above average intensity results in exceptional storminess.  The 20CR was employed to gain a longer-term perspective of storminess. The accuracy of 20CR depends on the number of observations assimilated and is reduced in data-sparse 3  regions and periods9. Therefore, we only identified 20CR cyclones for I-UK, where the observational network is dense and early 20CR storminess has been corroborated10. Ensemble mean cyclone metrics were derived from the 56 20CR constituent ensemble members (20CR-CMs) for the years 1871/72 to 2011/12 and bridged to NCEP1 via linear regression for the overlapping years (see Supplementary Information). The regression adjusted (RA) ensemble mean (EM) cyclone metrics are hereafter referred to as RA-20CR-EM (same for RA-20CR-CMs). Reconstructed metrics for the full 143-year period were derived by appending NCEP1 W2012/13 and W2013/14. The resulting storminess series suggest that for I-UK, W2013/14 was unprecedented in the full 143-year record (Fig. 2a). Following assessment of the spread in storminess across all RA-20CR-CMs and sampling uncertainty in individual regression adjustments, we find that it is very unlikely (p=0.0137) that storminess in any year exceeded W2013/14 (see Supplementary Information). We compared the reanalysis metrics with other climate series. First, we examined correspondence with DJF counts of cyclonic Lamb Weather Types (LWTs), also derived from NCEP1 and 20CR11. This reveals statistically significant (p<0.05) correlations between our DJF cyclone counts and concurrent winter totals of hybrid and pure cyclonic LWTs (NCEP1, 1948-2014: rhybrid = 0.88, rpure = 0.86; RA-20CR-EM, 1872-2012: rhybrid = 0.90, rpure = 0.87). Our cyclone counts are less than the number of hybrid LWTs by 12% (NCEP1) and 11% (RA-20CR-EM), whereas our counts of pure cyclonic days are 23% and 24% higher in NCEP1 and RA-20CR-EM, respectively. Underestimation is likely due to our algorithm requiring a closed isobaric pattern for detection; a more stringent criterion than used to define hybrid cyclonic LWTs. Overestimation of pure cyclonic LWTs could be due to more frequent sampling (six hourly in NCEP rather than daily for Lamb) which would capture more systems with sub-daily residency over I-UK. Second, we assessed correspondence between RA-20CR-EM cyclone metrics and observed precipitation. Correlation with the CRU TS3.21 precipitation12 (Fig. 2b) reveals that our cyclone metrics capture regional-scale precipitation variability in the vicinity of I-UK with strongest correlations found between storminess (I) and precipitation across England and Wales.  The ability of the reconstructed storminess series to detect years of extreme precipitation totals is tested by examining the top ranked years. The three stormiest winters W2013/14, 4  W1914/15 and W1983/84 correspond well with regional rainfall totals: W2013/14 and W1914/15 rank first and second in the HadUKP England-Wales precipitation (EWP) series13 (which dates from winter 1767), whereas W1983/84 registers as fourth wettest in Northern Ireland (where records begin in 191014). There is also a match between the occurrence of extreme wind speeds and storminess: W2013/14 ranks first by counts of very severe gales11; W1909/10 and W1979/80 rank second and third, respectively, and feature sixth and eleventh in our analysis. For both precipitation and wind, the storminess metric is a more useful indicator of seasonal extremes than cyclone counts alone. As the quality of the 20CR is lower during the early part of the record we tested the reconstructed storminess series for in-homogeneities. We found no statistically significant (0.05 level) change point using the RA-20CR-EM series and weak evidence for a change point across RA-20CR-CMs in 1909. Even if all pre-1909 reconstructed storminess indices are revised upward by an amount equal to the maximum difference in means between all ensemble members (pre-and post-1909), W2013/14 remains the stormiest on record (see Supplementary Information). Furthermore, utilising the long-running EWP series (for the winters 1872-2014) we find no evidence that correspondence with reconstructed RA-20CR-EM storminess is weaker in the early years of 20CR (Fig. 2c), thus bolstering confidence in a part of the 20CR record where data quality has been questioned9. We conclude that W2013/14 experienced the most severe storminess for at least 143 years when cyclone frequency and intensity are considered together. This finding is supported by independent measures of precipitation, atmospheric circulation and gales (see Supplementary Information on latter). Given the severe impacts of storminess experienced in I-UK during W2013/14, as well as climate model projections showing enhanced cyclone activity for this part of the NA15, further research is needed into the key processes driving extreme storminess over the region. References 1. UK Met Office (March, 2014); http://www.metoffice.gov.uk/climate/uk/summaries/2014/winter 5  2. Met Éireann (March, 2014); http://www.met.ie/climate/MonthlyWeather/clim-2014-win.pdf 3. Cornes, R.C., Weather  69, 115. (2014). 4. Serreze, M.C. & Barrett, A.P. J. Climate 21, 1048-1065 (2008). 5. Kalnay, E. et al. B. Am. Meterol. Soc. 77, 655-663 (1996). 6. Compo, G.P. et al. Meteorol. So. 137, 1-28 (2011). 7. Wang, X. L., Swail, V. R., & Zwiers, F. W. J.Climatol. 19 (2006). 8. Raible, C.C., Della-Marta, P.M., Schwierz, C. Wernli, H. & Blender, R. Mon. Weather Rev. 136, 880-897 (2008). 9. Wang, X.L. et al. Clim. Dynam., 40, 2775-2800 (2013). 10. Wang, X. L. et al. (2014). Clim. Dynam. 42(1113-1125 (2014). 11. Climatic Research Unit (June, 2014); http://www.cru.uea.ac.uk/cru/data/lwt/ 12. Harris, I., Jones, P.D., Osborn, T.J. & Lister, D.H. Int. J. Climatol., 34, 623-642 (2014). 13. Alexander, L. V., &  Jones, P. D. Atmos. Sci.Lett., 1, 142-150 (2000). 14. UK Met Office (June, 2014); http://www.metoffice.gov.uk/climate/uk/summaries/datasets  15. Feser, F. et al. Q. J. Roy. Meteor. Soc. Accepted Article (2014). 6    Figure 1|Domains Analysed and NCEP1 Cyclone Metrics. A, The North Atlantic (NA) region analysed with the domains differentiated as: I-UK (Ireland and UK), HLNA (High-Latitude North Atlantic) and the MLNA (Mid-Latitude North Atlantic). B, Winter (December - February) cyclone metrics for each domain (from top I-UK, NA, HLNA, MLNA) derived from NCEP1 with associated rank for W2013/14. Units for cyclone counts are ‘cyclone days’, defined as the number of cyclones detected in 6-hourly sea-level pressure fields, divided by four. The units for cyclone intensity and storminess are Laplacians of sea level pressure (∇2p : hPa 10-5 Km-2).    7    Figure 2|Extended Cyclone Metrics from 20CR. A, I-UK storminess for RA-20CR-EM (blue) and NCEP1 (red) series. The shaded region is the 95% prediction bound of the transfer function used to bridge 20CR-EM to NCEP1 (see Supplementary Information). The red horizontal line shows the unprecedented nature of W2013/14 storminess. B, Correlation between CRUTS3.21 precipitation and cyclone metrics derived from RA-20CR-EM. White grid cells over land denote grid cells where the correlation is not significantly different from zero at the 0.05 level. C, 21-year moving average of the correlation between EWP and reconstructed RA-20CR-EM storminess (I). The dotted grey line indicates the critical r value (according to a t-test) for rejection of the null hypothesis (r = 0) at the 0.05 level.   

Stormiest winter on record for Ireland and UK

Meteorological agencies

of Ireland and the UK have confirmed that

winter (December to February) 2013–2014

(W2013–14) set records for precipitation

totals and the occurrence of extreme wind

speeds1–3. Less clear is whether storminess

(characterized as the frequency and intensity

of cyclones) during W2013–14 was equally

unprecedented. We assessed multidecadal

variations in storminess by considering

frequency and intensity together and found

that in the context of these large-scale

cyclone characteristics, W2013–14 was

indeed exceptional. Given the potential

societal impacts, there is clearly a need

to better understand the processes

driving extreme cyclonic activity in the

North Atlantic

Matthews, Tom K.R.

Murphy, Conor

Wilby, Robert L.

Harrigan, Shaun

Maynooth EPrints and ETheses Archive

NUI Maynooth Eprint Archive

MURAL - Maynooth University Research Archive Library

738 NATURE CLIMATE CHANGE | VOL 4 | SEPTEMBER 2014 | www.nature.com/natureclimatechangeopinion & commentCORRESPONDENCE:Stormiest winter on record for Ireland and UKTo the Editor — Meteorological agencies of Ireland and the UK have confirmed that winter (December to February) 2013–2014 (W2013–14) set records for precipitation totals and the occurrence of extreme wind speeds1–3. Less clear is whether storminess (characterized as the frequency and intensity of cyclones) during W2013–14 was equally unprecedented. We assessed multidecadal variations in storminess by considering frequency and intensity together and found that in the context of these large-scale cyclone characteristics, W2013–14 was indeed exceptional. Given the potential societal impacts, there is clearly a need to better understand the processes driving extreme cyclonic activity in the North Atlantic.We applied an automated detection routine4 (see Supplementary Information) to the National Centers for Environmental Prediction and National Center for Atmospheric Research Reanalysis 1 (NCEP1)5 and the 20th Century Reanalysis (20CR)6 datasets to determine cyclone frequency and intensity over four domains (Fig. 1a). Storminess (I) was calculated7 as Iy = CyLy, where C is the number of cyclones observed during each winter in year y and L is their mean local Laplacian (intensity). Based on the NCEP1 dataset, we found that W2013–14 was the stormiest in the 66-year record (1948–1949 to 2013–2014) across the North Atlantic, due to unprecedented cyclone intensity and frequency for the mid- and high-latitude North Atlantic, respectively (Fig. 1b). Cyclone intensity has increased over the North Atlantic, consistent with trends in NCEP1 near-surface wind speeds (see Supplementary Information) and with previous investigations into cold-season cyclone activity over the North Atlantic8,9. W2013–14 is also ranked as the stormiest on record for the Ireland–UK domain, where the combination of high cyclone frequency and above average cyclone intensity resulted in exceptional storminess.The 20CR dataset was used to gain a longer-term perspective of storminess. The accuracy of the 20CR dataset depends on the number of observations assimilated and is reduced in data-sparse regions and periods9. Therefore, we only identified Figure 1 | Domains analysed and NCEP1 cyclone metrics. a, The North Atlantic (NA) region analysed with the domains differentiated as: Ireland and UK (I-UK), high-latitude North Atlantic (HLNA) and mid-latitude North Atlantic (MLNA). b, Winter (December–February) cyclone metrics for each domain (from top I-UK, NA, HLNA, MLNA) derived from the NCEP1 dataset with the associated rank for winter 2013–2014. Units for cyclone counts are ‘cyclone days’, defined as the number of cyclones detected in six-hourly sea-level pressure fields, divided by four. The units for cyclone intensity and storminess are Laplacians of sea-level pressure (∇2p: hPa 10–5 km–2). See main text for definition of the dataset.LatitudeLongitudeNCEP1 surface height (m)−200 0 200 400 600 800HLNA I−UKMLNAYear1950 1970 1990 2010246810 Rank = 231950 1970 1990 2010202530Rank = 11950 1970 1990 2010050100Rank = 46MLNA1950 1970 1990 201024681012Rank = 31950 1970 1990 2010203040Rank = 221950 1970 1990 2010050100Rank = 1HLNA1950 1970 1990 20101214161820Rank = 11950 1970 1990 2010202530Rank = 31950 1970 1990 2010100150200Rank = 3NA1950 1970 1990 2010024Rank = 1Storminess index (I) (×103)1950 1970 1990 2010203040 Rank = 6Mean cyclone intensity (L)1950 1970 1990 201002040Rank = 1Cyclone counts (C)I−UK72° N66° N60° N54° N48° N42° N80° W60° W40° W 20° W0°20° Eab© 2014 Macmillan Publishers Limited. All rights reservedNATURE CLIMATE CHANGE | VOL 4 | SEPTEMBER 2014 | www.nature.com/natureclimatechange 739opinion & comment20CR cyclones for the Ireland–UK domain, where the observational network is dense and early 20CR storminess has been corroborated10. Ensemble mean cyclone metrics were derived from the 56 20CR constituent ensemble members (20CR-CMs) for the years 1871–1872 to 2011–2012 and bridged to the NCEP1 dataset via linear regression for the overlapping years (see Supplementary Information). The regression-adjusted ensemble-mean cyclone metrics are hereafter referred to as RA-20CR-EM (same for RA-20CR-CMs). Reconstructed metrics for the full 143-year period were derived by appending NCEP1 W2012–13 and W2013–14. The resulting storminess series suggest that for the Ireland–UK domain, W2013/14 was unprecedented in the full 143-year record (Fig. 2a). Following assessment of the spread in storminess across all RA-20CR-CMs and sampling uncertainty in individual regression adjustments, we found that it is very unlikely (P = 0.0137) that storminess in any year exceeded that in W2013–14 (see Supplementary Information).We compared the reanalysis metrics with other climate series. First, we examined correspondence with December–February counts of cyclonic Lamb weather types (LWTs), also derived from NCEP1 and 20CR11. This revealed statistically significant (two-tailed t-test: P < 0.05) correlations between our December–February cyclone counts and concurrent winter totals of hybrid and pure cyclonic LWTs (NCEP1, 1948–2014: rhybrid = 0.88, rpure = 0.86; RA-20CR-EM, 1872–2012: rhybrid = 0.90, rpure = 0.87; where r is the coefficient of correlation). Our cyclone counts are less than the number of hybrid LWTs by 12% (NCEP1) and 11% (RA-20CR-EM), whereas our counts of pure cyclonic days are 23% and 24% higher in NCEP1 and RA-20CR-EM, respectively. Underestimation is probably due to our algorithm requiring a closed isobaric pattern for detection; a more stringent criterion than used to define hybrid cyclonic LWTs. Overestimation of pure cyclonic LWTs could be due to more frequent sampling (six hourly in NCEP1 rather than daily for the LWT analysis), which would capture more systems with sub-daily residency over the Ireland–UK domain. Second, we assessed the correspondence between RA-20CR-EM cyclone metrics and observed precipitation. Correlation with precipitation from the Climatic Research Unit Time-Series Version 3.21 (CRU TS3.21) dataset12 (Fig. 2b) revealed that our cyclone metrics capture regional-scale precipitation variability in the vicinity of the Ireland–UK domain, with the strongest correlations found between storminess and precipitation across England and Wales.The ability of the reconstructed storminess series to detect years of extreme precipitation totals is tested by examining the top-ranked years. The three stormiest winters W2013–14, W1914–15 and W1983–84 correspond well with regional rainfall totals: W2013–14 and W1914–15 rank first and second, respectively, for England and Wales in the Met Office Hadley Centre UK Regional Precipitation Series (HadUKP), whereas W1983-84 registers as the fourth wettest in Northern Ireland (where records begin in 191014). There is also a match between the occurrence of extreme wind speeds and storminess: W2013–14 ranks first by counts of very severe gales11; W1909–10 and W1979–80 rank second and third, respectively, and feature sixth and eleventh in our analysis. For both precipitation and wind, the storminess metric is a more useful indicator of seasonal extremes than cyclone counts alone.As the quality of the 20CR dataset is lower during the early part of the record, we abc1880 1900 1920 1940 1960 1980 2000−50005001,0001,5002,0002,5003,0003,5004,000YearpStorminess (∇2 : hPa 10−5 km−2)1880 1900 1920 1940 1960 1980 200000.20.40.60.81.0CorrelationYearStorminess index (I)Cyclone counts (C) 9° W 9° E 18° E 27° E0°40° N48° N  56° N  64° N40° N48° N  56° N  64° N40° N48° N  56° N  64° NMean cyclone intensity (L)Correlation−1.0−0.500.51.0RA−20CR−EM NCEP19° W 9° E 18° E 27° E0° 9° W 9° E 18° E 27° E0°LatitutdeLongitudeFigure 2 | Extended cyclone metrics from the 20CR dataset. a, Ireland and UK storminess for RA-20CR-EM (blue) and NCEP1 (red) series. The shaded region is the 95% prediction bound of the function used to bridge 20CR-EM to NCEP1 (see Supplementary Information). The dashed line highlights the exceptional winter 2013–2014 storminess. b, Correlation between CRU TS3.21 precipitation and cyclone metrics from RA-20CR-EM. White cells over land denote locations where correlation is non-significant (0.05 level). c, A 21-year moving average of the correlation between England–Wales precipitation and reconstructed RA-20CR-EM storminess. The dashed line indicates the critical coefficient of correlation (r) value (according to t-test) for rejection of the null hypothesis (r = 0) at the 0.05 level. See main text for definitions of the datasets.© 2014 Macmillan Publishers Limited. All rights reserved740 NATURE CLIMATE CHANGE | VOL 4 | SEPTEMBER 2014 | www.nature.com/natureclimatechangeopinion & commenttested the reconstructed storminess series for inhomogeneities. We found no statistically significant (0.05 level) change point using the RA-20CR-EM series and weak evidence for a change point across RA-20CR-CMs in 1909. Even if all pre-1909 reconstructed storminess indices are revised upward by an amount equal to the maximum difference in means between all ensemble members (pre- and post-1909), W2013–14 remains the stormiest on record (see Supplementary Information). Furthermore, using the long-running England and Wales Precipitation series (for the winters 1872–2014), we find no evidence that correspondence with reconstructed RA-20CR-EM storminess is weaker in the early years of the 20CR dataset (Fig. 2c), thus bolstering confidence in a part of the 20CR record where data quality has been questioned9.We conclude that W2013–14 experienced the most severe storminess for at least 143 years when cyclone frequency and intensity are considered together. This finding is supported by independent measures of precipitation, atmospheric circulation and gales (see Supplementary Information on gales). Given the severe impacts of storminess experienced in the Ireland–UK domain during W2013–14, as well as climate model projections showing enhanced cyclone activity for this part of the North Atlantic15, further research is needed into the key processes driving extreme storminess over the region. ❐References1. www.metoffice.gov.uk/climate/uk/summaries/2014/winter2. www.met.ie/climate/MonthlyWeather/clim-2014-win.pdf3. Cornes, R. C. Weather 69, 115 (2014).4. Serreze, M. C. & Barrett, A. P. J. Clim. 21, 1048–1065 (2008).5. Kalnay, E. et al. Bull. Am. Meterol. Soc. 77, 655–663 (1996).6. Compo, G. P. et al. Q. J. R. Meteorol. Soc. 137, 1–28 (2011). 7. Wang, X. L., Swail, V. R. & Zwiers, F. W. J. Climatol.  19, 3145–3166 (2006).8. Raible, C. C., Della-Marta, P. M., Schwierz, C., Wernli, H. & Blender, R. Mon. Weather Rev. 136, 880–897 (2008).9. Wang, X. L. et al. Clim. Dynam. 40, 2775–2800 (2013).10. Wang, X. L. et al. Clim. Dynam. 42, 1113–1125 (2014).11. www.cru.uea.ac.uk/cru/data/lwt/12. Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H.  Int. J. Climatol. 34, 623–642 (2014).13. Alexander, L. V. & Jones, P. D. Atmos. Sci. Lett.  1, 142–150 (2000).14. www.metoffice.gov.uk/climate/uk/summaries/datasets15. Feser, F. et al. Q. J. R. Meteorol. Soc. http://doi.org/txg (2014).Additional informationSupplementary information is available in the online version of the paper.Tom Matthews1*, Conor Murphy1, Robert L. Wilby2 and Shaun Harrigan11Irish Climate Analysis and Research Units (ICARUS), Department of Geography, National University of Ireland, Maynooth, Co. Kildare, Ireland, 2Centre for Hydrological and Ecosystem Science, Department of Geography, Loughborough University, Loughborough LE11 3TU, UK.  *e-mail: tom.matthews@nuim.ieCORRESPONDENCE:Ever-wet tropical forests as  biodiversity refugesTo the Editor — Species assemblages are exceptionally rich in ever-wet tropical forests1, here broadly defined as tropical forests that experience high annual rainfall (≥2,000 mm yr−1) and are aseasonal (that is, zero months with ≤60 mm precipitation). Protecting as many of the remaining ever-wet tropical forests as we can stands to yield a double dividend through providing refugia for large numbers of tropical forest species that may be particularly vulnerable to the drier conditions presently occurring2 and predicted to occur over coming decades3,4, and helping to mitigate climate change impacts overall5. We estimate that ever-wet zones currently cover 30% of the tropical forest biome6,7, with 50% of this area remaining as intact natural forest8, of which only 6% is formally protected9 (Supplementary Information). A standard set of global climate models3,7 generally agree that tropical ever-wet zones will contract by at least 20% (Supplementary Fig. S1), potentially drying out one-fifth of extant intact ever-wet tropical forest and one-quarter of the protected ever-wet tropical forests by 2050 (Fig. 1 and Supplementary Tables S1–S3).The footprint of ever-wet zones is projected to largely contract throughout the tropics rather than expand or shift to new areas, attributable in our analysis to increasing seasonal variability in rainfall rather than pronounced decreases in areas that receive high (≥2,000 mm) annual precipitation. Extensive areas of the central Amazon Basin and the Guianas, however, will no longer qualify as ever-wet zones due to both longer dry spells and less annual rainfall (Supplementary Fig. S2). The projected loss of ever-wet zones in these two regions dominate global losses, with a marked trend of contraction westward, resulting in an estimated loss of one-third of the Neotropical ever-wet zone (Supplementary Table S1). Figure 1 | Ever-wet zones within the tropical and subtropical moist broadleaf forest (TSMBF) biome6 defined using current climate and future climates3,7 in 2050 under representative concentration pathway 8.5 (where ≥75% of 17 global climate models agree). Ever-wet zones are underlain with remaining forest data8 consisting of two classes of tree cover (also see Supplementary Fig. S2).Current ever-wet zone Future ever-wet zone Overlap in ever-wet  zonesForest ≥50 to <75% Forest ≥75% TSMBF biome© 2014 Macmillan Publishers Limited. All rights reserved

Maynooth University ePrints and eTheses Archive

Tom Matthews

Conor Murphy

Robert L. Wilby

Shaun Harrigan

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Stormiest winter on record for Ireland and UK

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