Meteorological monitoring of an active volcano: Implications for eruption prediction

Journal of Volcanology and Geothermal Research 150 (2006) 339 – 358 www.elsevier.com/locate/jvolgeores

Meteorological monitoring of an active volcano: Implications for eruption prediction Jenni Barclay a,*, Jade E. Johnstone a, Adrian J. Matthews a,b a

School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom b School of Mathematics, University of East Anglia, Norwich, NR4 7TJ, United Kingdom Received 11 August 2004; received in revised form 17 June 2005; accepted 27 July 2005 Available online 21 November 2005

Abstract Rainfall data collected on and around the Soufriere Hills Volcano, Montserrat between 1998 and 2003 were analysed to assess the impact on primary volcanic activity, defined here as pyroclastic flows, dome collapses, and explosions. Fifteen such rainfalltriggered events were identified. If greater than 20 mm of rain fell on a particular day, the probability of a dome collapse occurring on that day increased by a factor of 6.3% to 9.2%, compared to a randomly chosen day. Similarly, the probability of observing pyroclastic flows and explosions on a day with N 20 mm of rainfall increased by factors of 2.6 and 5.4, respectively. These statistically significant links increased as the rainfall threshold was increased. Seventy percent of these rainfall-induced dome collapse episodes occurred on the same calendar day (most within a few hours) as the onset of intense rainfall, but an extra 3 occurred one or two calendar days later. The state of the volcano was important, with the rainfall–volcanic activity link being strongest during periods of unstable dome growth and weakest during periods of no dome growth or after a recent major collapse. Over 50% of the heavy rain days were associated with large-scale weather systems that can potentially be forecast up to a few days ahead. However, the remaining heavy rain days were associated with small-scale, essentially unpredictable weather systems. There was significant variability in the amount of rainfall recorded by different rain gauges, reflecting topographic variations around the volcano but also the inherent small-scale variability within an individual weather system. Hence, any monitoring/ warning program is recommended to use a network, rather than just a single gauge. The seasonal cycle in rainfall was pronounced, with nearly all the heavy rain days occurring in the May–December wet season. Hence, the dome was at its most vulnerable at the beginning of the wet season after a period of uninterrupted growth. Interannual variability in rainfall was related to tropical Pacific and Atlantic sea surface temperature anomalies, and holds out the prospect of some limited skill in volcanic hazard forecasts at even longer lead times. D 2005 Elsevier B.V. All rights reserved. Keywords: rainfall; dome collapse; Montserrat; forecasting

1. Introduction One of the main goals of any volcano-monitoring program is to predict the onset of an eruptive episode with sufficient warning to take appropriate mitigation * Corresponding author. Fax: +44 1603 591327. E-mail address: [email protected] (J. Barclay). 0377-0273/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jvolgeores.2005.07.020

measures (McNutt et al., 2000). Recent advances in technology and our physical understanding of active volcanoes have resulted in a significant improvement in our ability to predict changes in behaviour during eruption, particularly on intensively monitored volcanoes where a variety of geophysical and geochemical methods are deployed (e.g. Luckett et al., 2002). However, the accurate prediction of these changes in behaviour

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using these methods is still in its infancy and we are still some way from accurate, probabilistic forecasts of eruptive episodes. The challenge then remains to try to exploit and develop new techniques that might enhance our ability to improve the accuracy and the time-range over which we predict changes in activity. Volcanoes do not erupt in isolation; rising magma must interact with pre-existing rock and groundwater and once at the surface is subjected to the influence of our atmosphere. Intense periods of rainfall have long been suspected as an external forcing for volcanic activity. This activity mainly involves the generation of shallow gas explosions (e.g. Mastin, 1994; Morrissey and Mastin, 2000) and pyroclastic flows and dome collapse (see below). The link between rainfall and the generation of secondary activity in the form of lahars is unequivocal. Long-lived volcanic eruptions, particularly dome-forming examples, are especially susceptible to the influence of rainfall when in certain states. Anecdotal evidence for the initiation of volcanic activity by rainfall (including the generation of pyroclastic flows and small to moderate explosions) has been documented as far back as 1904 at Merapi (Voight et al., 2000), and during the 1929–1932 eruption of Mt. Pele´e on Martinique (Perret, 1937 in Carn et al., 2003). Links between rainfall and volcanic activity are discussed in reports to the Global Volcanism Network of the Smithsonian Institution for Santiaguito, Guatemala (GVN, 1990), Guagua Pichincha and Tungurahua, Ecuador (GVN, 1993a,b), Merapi, Indonesia (GVN, 1992), Lokon Empung, Indonesia (GVN, 2002) among others. More recently this link has been analysed more closely using precipitation data and geophysical (usually seismic) records. The correlation of pyroclastic flow activity to high rainfall has been demonstrated in this way at the Soufrie`re Hills Volcano, Montserrat (Matthews et al., 2002; Carn et al., 2003) and Unzen Volcano, Japan (Yamasato et al., 1998). The onset of this activity is often found to occur within 24 h of high rainfall, more usually within tens of minutes to hours. Longer intervals (N 24 h) between rainfall and explosive activity have been observed at Mt. St. Helens by Mastin (1993, 1994) although many of the 28 recorded explosions (including all six of those that definitely involved the release of volcanic gas) occurred within 24 h. Given this link, and the clear long-term hazard posed by rainfall-induced lahars, the purpose of this paper is to explore the utility of meteorological data as a predictive tool for active volcanoes in regions susceptible to high intensity rainfall. About 45% of the world’s active volcanoes lie in the Tropics, with many others in climatic regions subject to occasional high intensity

rainfall. The aim of this paper is to examine (1) the duration, intensity and localised variation of rainfall associated with heightened dactivityT at a volcano, (2) the types of related weather systems and their inherent predictability and (3) the patterns of volcanic activity observed in association with this rainfall. The ultimate goal of this work is to enhance any potential mitigation efforts against volcanic activity associated with rainfall. This analysis uses the example of the Soufrie`re Hills Volcano (SHV) on Montserrat where meteorological data has been gathered spanning 5 years of volcanic activity (between 1998 and 2003). In particular, we use data from a dense network of 0.2 mm tipping bucket rain gauges deployed across the island in January 2001. These have a 1 min temporal resolution and are used to demonstrate localised variations in rainfall as well as its precise timing in relation to volcanic activity. These are supplemented by daily totals from four additional rain gauges collected between 1998 and 2001. The regional climatology and interannual variability of rainfall are described in conjunction with the local rainfall patterns observed on Montserrat. These are used to identify periods of enhanced rainfall both on an annual and yearly basis and their causes. The recorded rainfall is then related to periods of enhanced volcanic activity at SHV and their relationship is analysed. The variations and patterns in dtriggeringT rainfall and their associated weather systems are then identified. These observations are then used to analyse the nature of the relationship between rainfall and volcanic activity at SHV, the utility of incorporating meteorological data into volcano monitoring and its application to other active volcanoes. 2. Volcanic activity at Soufrie`re Hills Volcano The SHV on the Caribbean island of Montserrat (16.78 N, 62.28 W) has been active since July 1995. Its andesitic dome-forming eruption is one of the most well-monitored and highly instrumented eruptive episodes of recent times and observations and inferences relating to its behaviour have also been extremely well documented (e.g. Druitt and Kokelaar, 2002). Sparks and Young (2002) provide a summary and chronology of activity until December 2001. The eruption has largely involved two prolonged phases of dome growth. Phase I occurred from November 1995 until March 1998 and involved vigorous dome growth, pyroclastic flows and surges, Vulcanian explosions, and one debris avalanche that triggered a lateral blast in December 1997. Following a period of dresidualT activity (defined by the Montserrat Volcano Observatory (MVO) as a period of activity following a major eruption with no

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new material seen at the surface), dome growth (phase II) recommenced in November 1999 and finished in August 2003, following a large dome collapse in July 2003. This latest residual phase (to the time of writing in June 2005) has again been characterised by occasional periods of ash-venting and one episode of dome collapse with associated explosion (3rd March 2004) to date. It is noteworthy that there is no recorded evidence, anecdotal or otherwise to link Phase I dome growth with episodes of intense rainfall, although no actual rainfall data is available to us for this time period. Phase II dome growth has generally involved more stable dome growth and significantly fewer periods of vigorous pyroclastic flow and collapse activity than Phase I, allowing the dome to attain larger volumes (Carn et al., 2003). Phase II growth has been strongly associated with rainfall-induced volcanic activity (Matthews et al., 2002; Carn et al., 2003). One episode of dome collapse during the first residual phase has also been linked to rainfall (Norton et al., 2002). Intense rainfall has resulted in frequent lahar

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(referred to as dmudflowT on Montserrat) activity down many flanks of the volcano throughout the entire eruption. In the context of this study we therefore refer to volcanic activity as any behaviour that occurs at the surface of the volcano. This is not then strictly related to the eruption and flux of new magma at the surface of the volcano but we do also distinguish between primary activity (pyroclastic flows, dome collapse and explosions) and secondary activity (lahars). We follow the nomenclature of the MVO and Carn et al. (2003) for ddome collapseT where this involves a sustained event involving many individual rockfalls and pyroclastic flows over a period of up to a few hours. The material involved in these events during this time period varies from 2–3 million to 125 million m3. 3. Instrumentation The locations of our instruments are shown in Fig. 1. In January 2001 a network of ten 0.2 mm tipping

Fig. 1. Montserrat: Location of rain gauges. Height contours at 150 m interval.

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bucket rain gauges with data loggers with a 1-min temporal resolution were deployed around the island, focussing on providing a range of topographic heights and geographic locations, particularly close to the volcano. Data from these were also supplemented from December 1998 to August 2001 by daily totals from four rain gauges deployed by the UK Department for International Development (DFID). In practice the data loggers recorded up to ~6 months of data during typical conditions. However, particularly for stations close to the volcano, more regular visits were needed during periods of high activity to keep the buckets clear of ash. The metallic buckets plus the fixings we used (for sites close into the volcano the gauges were pre-fixed to concrete plinths and deployed immediately on a vegetationfree flat surface using the MVO helicopter) were also highly susceptible to long-term corrosion from acid rainfall. Corrosion also affected the standard filter that we used and this had to be replaced on N 50% of the rain gauges. The data loggers themselves were not particularly robust. By May 2003, many rain gauges had ceased to function and were removed from the field. Our working network now consists of three rain gauges (Harris, Garibaldi Hill and MVO North, Fig. 1). Two rain gauges were deployed too close to the volcano and were complete-

ly destroyed during activity in 2001 and 2002. The maximum number of rain gauges working at any one time was six (Fig. 2). However, the deployment of the rain gauges at comparatively high elevations, close to the volcano gave us some limited insights into the potential variability of rainfall between the measured site and that on the volcano (or sediment source region) itself. Two global gridded data sets were used to examine the regional-scale meteorological and oceanographic conditions that affect Montserrat. The CPC Merged Analysis of Precipitation (CMAP) data set is a satellite-derived measure of precipitation, validated against station rainfall measurements (Xie and Arkin, 1997). The data is available on a 2.58  2.58 grid as monthly means from January 1979 to June 2003. The optimally interpolated sea surface temperature (SST) data set of Reynolds et al. (2002) is a merged analysis of satellite, ship and buoy SST measurements. In looking at the correlation between rainfall and volcanic activity the daily totals of rainfall were used and so the dataset includes both tipping bucket and DFID rain gauge data. This covers the time period between 1st December 1998 and 31st July 2003 and is referred to as the dextendedT dataset. For the examination of the nature and intensity of the rainfall only tipping bucket rain gauge data were used. This covers

Fig. 2. Time series of operational tipping bucket rain gauges. No useful data were retrieved from gauges deployed on Chance’s Peak or Centre Hills. The Galways (GAL) gauge did provide useful data but not for more than a complete month at a time.

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the time period 1st January 2001 to December 31st 2003 and is referred to as the dtipping bucketT dataset.

4.2. Regional climatology and dominant weather systems

4. Topography and climatology of Montserrat

Montserrat lies at the northern edge of the Intertropical Convergence Zone (ITCZ), the semi-permanent band of cloud and rainfall whose annual mean position is along 78 N over the Atlantic (Fig. 3). The annual mean rainfall total reaches nearly 2800 mm year 1 in the heart of the ITCZ, but is 890 mm year 1 in the region of Montserrat. The ITCZ undergoes a pronounced seasonal cycle, reflecting the annual cycle in solar insolation. Thus the ITCZ migrates north during northern summer and south during the northern winter such that the Eastern Caribbean experiences a bimodal May–November rainfall season with peaks in May– July and August–September (Taylor et al., 2002). Similar behaviour is also seen in the immediate region of Montserrat (heavy line in Fig. 4). The rainfall season runs from April–November and has a subsidiary peak in May and a larger, longer peak centred on September. On a day to day basis, rainfall is associated with individual weather systems. Of particular relevance to the Eastern Caribbean and to Montserrat are synopticscale (up to a few thousand kilometres across) lowpressure systems that develop through a hydrodynamic instability of the low-level easterly jet over Africa (Thorncroft and Hoskins, 1994). These systems then propagate in the easterly trade wind flow over the Atlantic as beasterly wavesQ (Reed et al., 1977). They develop a coherent cyclonic (anticlockwise) circulation in the wind field and a region of deep convective clouds and rainfall up to 1000 km across. If they reach suffi-

In this section we briefly discuss the topography and regional climatology of Montserrat. This places our own (shorter time period) results into context but also illustrates the kind of meteorological detail that can be gained without using rain gauge data. 4.1. Topography Montserrat is approximately 16.5 km north to south and 10 km wide east to west (Fig. 1) and is constructed almost exclusively from volcanic rock. It comprises three major massifs from north to south, namely Silver Hills (403 m, formed c. 2600 to 1200 ka)), Centre Hills (740 m, formed c. 950 to 550 ka) and the South Soufrie`re and Soufrie`re Hills (pre-eruptive height of 914 m, formed c. 170 ka to present). This migration of the active centre is reflected in the erosional maturity of each of these massifs (Harford et al., 2002) although each is characterised by many steeply eroded valleys and ridges radiating towards and truncated by a coastline predominantly composed of steep cliffs. This topographic variation means that, although comparatively small, Montserrat has considerable variation in precipitation patterns across the island. Our original siting of the rain gauge network was designed to test the extent of this variation and the degree to which it might affect volcanic activity.

Fig. 3. Climatological mean CMAP annual rainfall totals for 1979–2002. Contour interval is 1000 mm year

1

.

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Fig. 4. Time series of monthly rainfall totals. CMAP average (heavy line) is calculated from Jan. 1979 to June 2003 and covers the 2.58  2.58 grid box covering Montserrat (centred at 61.258 W, 16.258 N).

cient strength they are classified as tropical depressions, tropical storms and ultimately hurricanes. Rainfall is not uniform over the region of convection, as mesoscale structures such as cloud bands and squall lines with spatial scales of tens of kilometres and associated intense bursts of rainfall can develop within the overall envelope of large-scale convection. In addition, truly mesoscale weather systems such as isolated cumulonimbus clouds or larger mesoscale convective complexes can develop independently of any large-scale weather system. The steep topography on Montserrat has a profound influence on the local rainfall. As air flows over the island it is forced to rise over the terrain and cools adiabatically, leading to saturation and the formation of cloud droplets and ultimately rain. Hence, there is a strong topographic variation in rainfall received over the island, with the mountain tops receiving up to 60% more rainfall than the coastal regions (unpublished precipitation data 1933–1963, courtesy of the UK DFID). In terms of predictability of rainfall over Montserrat and, by inference, rainfall-induced volcanic activity, these weather systems can be divided into two types: (1) Large or synoptic-scale weather systems over 100 km across. These include easterly waves, tropical

depressions and storms, hurricanes and also trailing cold fronts from extratropical depressions. These systems are captured well by the global forecast/assimilation models run by national meteorological centres, and can potentially be forecast several days in advance. (2) Localised or mesoscale weather systems less than 100 km across. These include individual cumulonimbus cells and mesoscale convective complexes. Due to their small scale and rapid development, these systems would be very difficult to forecast more than a few hours in advance. 4.3. Regional interannual variability There is also pronounced interannual variability of rainfall in the region of Montserrat. In 1999, the region (as defined by the CMAP total ) received considerably more than the average (which was calculated using data from 1979 to 2002), while 2000, 2001 and 2002 were rainfall deficit years (Fig. 4). Rainfall in the tropics is intimately tied to the spatial distribution of tropical SSTs. Locally, warm SSTs provide an abundance of moisture for deep tropical convection. The latent heat release associated with this convection can then force a planetary scale change in the atmospheric circulation through equatorial waves and changes to the Hadley

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and Walker cells. The ascending/descending motion and the anomalous surface flow and evaporation from the sea surface that are associated with these circulation changes can then affect the occurrence of deep convection and rainfall in locations many thousands of kilo-

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metres from the original SST anomaly. The El Nin˜o– Southern Oscillation phenomenon is an example of these processes in action. Enhanced rainfall over the Caribbean is associated with negative SST anomalies over the eastern Pacific

Fig. 5. (a) Anomalous SST field for dwetT minus ddryT months in the Montserrat region. Contour interval is 0.1 8C. Negative contours are dotted and the zero contour is suppressed. (b) Anomalous SST field for 2001. Contour interval is 0.2 8C. Negative contours are dotted and the zero contour is suppressed.

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(La Nin˜a), positive SST anomalies over the north tropical Atlantic and negative SST anomalies over the south tropical Atlantic (Enfield and Elfaro, 1999; Giannini et al., 2000; Taylor et al., 2002). However, as Montserrat lies at the fareastern edge of the Caribbean, the SST patterns relevant to Montserrat rainfall may differ from those for the entire Caribbean. Hence, the anomalous SST patterns that are coincident with enhanced rainfall in the Montserrat region were calculated. An anomaly time series of CMAP rainfall for the grid box covering Montserrat (centred at 61.258 W, 16.258 N) was constructed by subtracting the mean annual cycle (heavy line in Fig. 4) from the monthly totals (solid line in Fig. 4). The months when the anomalous rainfall was above one standard deviation (wet months) were then selected, and a map of the mean SST anomaly pattern for these months was calculated. Similarly, the months when the anomalous rainfall was more than one standard deviation less than the mean (dry months) were selected and a corresponding SST pattern calculated. The two SST patterns were approximately linear, in that the bwetQ and bdryQ SST anomaly patterns were similar, but with opposite sign. The bwetQ minus bdryQ pattern is shown in Fig. 5a. Associated with wet months in the Montserrat region, there are positive SST anomalies over the north tropical Atlantic and over the southern Caribbean, and negative SST anomalies over the subtropical North Atlantic, in agreement with the reported findings for Caribbean rainfall as a whole. However, there are positive SST anomalies over the equatorial far eastern Pacific (corresponding to an El Nin˜o event) and off the west coast of South America, while there is no clear signal in the south tropical Atlantic. All these features are robust, in that they appear with opposite sign in the individual bwetQ and bdryQ composite. The dynamical mechanisms responsible for these relationships are being investigated as part of a modelling study. In terms of rainfall and rainfall-induced volcanic activity forecasting over Montserrat, these SST–rainfall relationships offer the possibility of a modest increase in forecast skill up to a few months ahead, such that the probability of heavy rainfall over Montserrat would be increased if the SST patterns resembled those in Fig. 5a. For example, the SST anomaly field in 2001 (Fig. 5b) included negative SST anomalies over the equatorial eastern Pacific and positive SST anomalies over the subtropical North Atlantic, i.e., some features of the composite map in Fig. 5a, but with opposite sign. The implication was that 2001 would be a dry year in the Montserrat region, which is consistent with the CMAP data (Fig. 4). However, the SST anomaly patterns and rainfall over

the Montserrat region do not correlate every year and it is worth noting that 2001 was not an especially dry year on Montserrat itself (Fig. 4). There are other large-scale factors that affect rainfall over the Caribbean, and there will be a large random or stochastic element also. These could be elucidated by a comprehensive statistical forecasting study, but this is beyond the scope of the present paper. 5. Rain gauge data on Montserrat: 1998–2003 5.1. Climatology and interannual variability on Montserrat Annual rainfall statistics for selected rain gauges on Montserrat are shown in Table 1. Annual totals are of the order of 750–1500 mm, compared to the large-scale long-term mean of 890 mm year 1 from the CMAP data (Fig. 4). The higher rainfall totals from the gauges on Montserrat are consistent with an enhancement of the regional open-ocean value of the CMAP data by topographic effects on the island. There is significant variability across the island due to local topographic effects. For example, the Hope gauge is located at an altitude of 250 m in the Centre Hills and records 1526 mm of rain in 2000. In contrast, the Brades gauge is located at an altitude of 75 m and in the northwest of the island and only records 1024 mm for the same year (Table 1). There are some 200 days a year when rainfall occurs. The monthly rainfall totals are shown in Fig. 4. The bimodal seasonal cycle that was evident in the CMAP data is also present in the gauge data. However, the seasonal cycle from the gauge data is usually enhanced and sometimes not exactly time coincident with the regional values. This variation is usually of the order of F 1 month. The larger variability in the gauge data when compared to the CMAP data is apTable 1 Annual rainfall statistics for Montserrat YEAR

Rain gaugea

Annual Total Rainfall (mm)

No. of Rainfall days

Days N 20 mm

1999 2000

HOPE HOPEb BRADES SGH MVN MVN MVN GAR

1474 1526 1024 1335 1020 1071 1134 747

219 230 264 215 184 199 204 208

20 19 8 14 10 12 13 4

2001 2002 2003 a

See Fig. 1 for rain gauge codes and location. For reference, MVN had 62% of the total rainfall of HOPE in the 8 months of 2001 where recording was coincident. b

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parent. This is due to the point nature of the rain gauges; individual weather systems can lead to quite different rainfall totals at gauges that are only separated by a few kilometres horizontally and a few hundred metres vertically. The CMAP data is an area-average that smooths over these variations, and is dominated by rainfall over the open ocean in this region. 5.2. Rainfall and primary volcanic activity Here, we examine the link between rainfall and volcanic activity on a day to day basis. In this context we refer to volcanic activity as any behaviour that occurs at the surface of the volcano and in this analysis we focus on rainfall deventsT that have delivered N 20 mm and between 10 and 20 mm of rainfall in any 24 h period at any rain gauge. From existing observations of the interaction between rainfall and volcanic activity (Matthews and Barclay, 2004; Matthews et al., 2002; Carn et al., 2003; Yamasato et al., 1998) this is a reasonable minimum threshold for rainfall that could provoke volcanic activity. To verify this the conditional probability of observing different forms of volcanic activity given different thresholds of daily total rainfall between December 1998 and July 2003 using our extended dataset and observations reported by the Montserrat Volcano Observatory in their Scientific Reports (Table 2). When defining volcanic activity, we sub-divided pyroclastic flow activity into multiple flows (where more than one flow occurred in rapid succession—often referred to as a dome collapse episode) and large and small individual pyroclastic flows. The latter two categories are included in Table 2 together with the multiple flows as dall pyroclastic flowsT. We did not record activity that was triggered or generated by an initial event (e.g. pyroclastic flows generated from column collapse following an explosion, or conversely an explosion generated by large volume dome collapse). This shows that the probability of observing some kind of volcanic activity is enhanced on any given rainy day, particularly for those where rain is z 20 mm. For example, of the 1704 days analysed, 76 (or 4.46%) had a daily total of 20 mm or more recorded by at least one of the rain gauges (Table 2). Furthermore multiple pyroclastic flows occurred on 25 (1.47%) days. There were 7 days on which both a multiple pyroclastic flow episode occurred and greater than 20 mm of rain fell. Given that the rainfall event exceeds 20 mm, the conditional probability of there being a multiple pyroclastic flow episode increases by a factor of 6.3% to 9.2%. Alternatively, the binomial probability that these two occurrences (all 7

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Table 2 Probabilistic assessment of likelihood of coincidence of rainfall of differing thresholds and differing types of volcanic activity, for the period 1st December 1998 to 31st July 2003 Rainfall threshold (mm) 10

20

30

Days ( y) Rainfall eventsa P (rainfall event) = p

1704 76 4.46%

1704 37 2.17%

25 1.47% 7 9.2% 6.3

25 1.47% 6 16.2% 11.1

1704 172 10.09%

Multiple pyroclastic flows (pfm)b No. occurring (n) 25 P (pfm)c 1.47% Rainfall + pfm (r) 10 P (pfm/rainfall) 5.8% No. of times more 4.0 likelyd P (r; n; p)e 7.27  10

3

All pyroclastic flows (pf)f No. occurring (n) 88 P (pf) 5.16% Rainfall + pf (r) 16 P (pf/rainfall) 9.30% No. of times more 1.80 likely P (r; n; p) 0.79% Explosions No. occurring (n) P (xp) Rainfall + xp (r) P (pfm/r) No. of times more likely P (r; n; p) Lahars (mu) No. occurring (n) P (mu) Rainfall + mu (r) P (mu/rainfall) No. of times more likely P (r; n; p) a

% 7.42  10

3

% 1.22  10

88 5.16% 10 13.16% 2.55

88 5.16% 8 21.62% 4.19

0.4%

0.05%

33 1.94% 8 4.65% 2.40

33 1.94% 5 10.53% 5.43

33 1.94% 5 13.51% 6.98

1.04%

6.95  10

34 2.00% 15 8.70% 4.37

34 2.00% 14 18.42% 9.23

2.83  10

5

% 6.89  10

3

3

%

% 0.06%

34 2.00% 11 29.73% 14.90 9

% 8.74  10

9

%

Rainfall events shows the number of days where a given rainfall threshold is exceeded. However consecutive days are not reported individually and deemed to be one event, e.g., the passage of Hurricane after 2–3 days will be considered as one rainfall event and only events triggered within 24 h of onset are considered in this table (for later triggered events see Table b). b Multiple pyroclastic flows are defined as those where more than one pyroclastic flow occurred in rapid succession. These flows are most commonly associated with episodes of dome collapse. c Where P = (n/y) * 100. d The numbers of times more likely that a pyroclastic flow will occur given that rainfall over the given threshold has occurred. e This is the simple binomial probability that the given number of individual days of activity fortuitously followed the given rainfall events, expressed as a percentage. Method is as described in Mastin (1994) for analysis of explosive tephra emissions at Mount St. Helens. f This figure also includes the pfm events given above.

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multiple pyroclastic flows and rainfall events of N 20 mm) is just random coincidence is 0.0074%. Similar calculations are shown in Table 2 for daily rainfall totals of 10 and 30 mm and for differing forms of activity. These show that the behaviour described above is robust. In particular the probability of the coincidence of rainfall with volcanic activity increases as the amount of rainfall increases. Our analysis of all pyroclastic flow activity demonstrates that it is the larger multiple pyroclastic flow events (usually dome collapse) that are the most sensitive to heavy rainfall. There is some suggestion that explosions are also influenced by rainfall on Montserrat (including anecdotal observations) but for the duration of our observations this is masked by episodes of explosive emissions generated by other mechanisms. For the time period where our tipping bucket data set was available (January 2001–December 2003) the intensity and duration of each of the rainfall events is also summarised (Tables 3 and 4) along with the broad classification of the weather system that delivered the rainfall. Table 3 lists each 24-h period during the 3 year period where rainfall greater than 20 mm was recorded at any station and Table 4 details those periods where rainfall was less than 20 mm but exceeded 10 mm in total. Using reported observations alone there were 5 periods of primary activity between 2001 and 2003 that were associated with intense rainfall N 20 mm (Table 3). All of these were associated with multiple pyroclastic flow (or dome collapse) episodes. Four of the five dome collapse episodes were when total rainfall exceeded 40 mm and N 30 mm of this rain was delivered in less than 3 h (Table 3: 29/07/01; 14/10/01; 16/10/01; 20/8/02). The remaining event during this time period, the 210 million m3 dome collapse of the 12th July 2003, was largely attributed to heightened sub-edifice activity while the dome was in an extremely vulnerable state (early morning rainfall may have provided the initial

trigger). A sixth event (2nd October 2002) was also attributed to 15 mm of rain recorded at an independent rain gauge at SGH in only 40 min (MVO reports). Our functioning rain gauges (MVN, GAR, HAR) did not record this localised event and so this is not shown on Table 3 or 4. Three other (smaller) periods of activity occurred during periods of rainfall just less than 20 mm (Table 4: 4/10/01; 26/7/02; 22/10/02). Days when N 40 mm of rain fell with no recorded primary activity usually occurred immediately after large volume collapses when the dome was no longer in a vulnerable state. 5.3. Rainfall and secondary volcanic activity (lahars) The observation-based record of lahar activity was also supplemented by days where lahar activity was recognised by the seismic heligraphs from the short period network (Chivers, 2004). This is clearly an underestimate of secondary activity (dlaharT signals may be masked by other types seismic activity) but provides a useful minimum number of days. Fifty-six percent of these days had rainfall N 20 mm and 26% between 10 and 20 mm for at least one station; only 18% recorded b 10 mm rainfall before lahar activity was initiated. It is intuitively obvious that lahar activity should be well correlated with rainfall and so the very good but slightly less than perfect correlation between lahar activity and rainfall (Table 2) gives some indication of the influence of under-reporting of volcanic activity by our using subjective reporting from scientific reports (and seismic heligraphs in the case of lahars) alone. It should also be noted however that there have been some anecdotal observations of lahar activity on days without apparent rainfall (Gill Norton pers. comm., 2004). Lahar activity is also strongly associated with 24 h periods where N 40 mm of rainfall fell. Of the 17 reported periods between 2001 and 2003 where this amount of rainfall occurred, lahar activity was either recorded in MVO reports or detected on the seismic

Notes to Table 3: a Maximum amount of rainfall recorded at any rain gauge in a 24 h period. Amounts are in millimeters. b Station code. c Minimum amount of rainfall recorded at any rain gauge Amounts are in millimeters. d Box is shaded if greater than the amount stated was recorded in a period of less than 3 h. The number in the box represents the number of times this occurred during the 24 h period. e The type of weather system that caused the rainfall. f No minimum is given as only MVN rain gauge was operational at this time. g This is the date on which the rainfall started. It is possible for a 24 h period to overlap 2 days. h The ratio of the number of stations that recorded any rainfall to the number of stations that were operational. i Comments include named hurricanes and tropical storms, dome dcollapseT events (as reported in Weekly Report and chronology of eruption by MVO: http://www.mvo.ms). These are somewhat objective as no quantitative scale for reporting could be used. Heligraph records (Chivers, 2004) were used for lahars and so are only reported on days when no pyroclastic flow activity occurred; they usually also occurred on dome collapse days. Name of large weather system is that from its highest intensity state, perturbation was often smaller at time of passing over Montserrat.

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traces (Table 3) for 11 events; of the remaining 6 periods on 3 occasions the volcano was active (1/12/01, 25/2/02, 21/7/03) such that lahar activity would have been masked on the seismic trace. The remaining three events were within a similar reporting period (21/8/03, 27/10/ 03 and 2/11/03) and lahars may well have occurred but not been recorded. On these days, however, intergauge

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variability was high with no more than 7.2 mm of rain recorded at the minimum gauges on any of these days. 5.4. Rainfall during differing dome states To test the role of dome state on producing rainfallinduced activity, the 1998–2003 activity was sub-divid-

Table 3 Summary of maximum and minimum rainfall data for rainfall deventsT which produced over 20 mm of rain in a 24 h period for the period January 1st 2001 to December 31st 2003

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Table 4 Summary rainfall data for rainfall events with b 20 but N 10 mm rainfall in a 24 h period, for the period January 1st 2001 to December 31st 2003 Datea

Maxb

Stnc

13/1/2001 27/1/2001 25/3/2001 1/4/2001 10/4/2001 24/6/2001 25/6/2001 30/6/2001 18/7/2001 9/8/2001 17/8/2001 30/8/2001 31/8/2001 1/9/2001 3/9/2001 9/9/2001 13/9/2001 2/10/2001 4/10/2001 19/10/2001 22/10/2001 25/10/2001 10/11/2001 13/11/2001 23/11/2001 4/12/2001 6/12/2001 7/12/2001 8/12/2001 10/12/2001 17/12/2001 23/12/2001 6/1/2002 10/1/2002 14/1/2002 16/1/2002 26/1/2002 28/1/2002 31/1/2002 19/2/2002 17/4/2002 18/4/2002 7/5/2002 16/6/2002 17/6/2002 26/7/2002 6/8/2002 7/8/2002 6/9/2002 23/9/2002 9/10/2002 18/10/2002 19/10/2002 20/10/2002 22/10/2002 15/11/2002 19/11/2002 24/12/2002

11.4 10.8 17.2 11.2 10.2 19 12.2 10.2 14.2 12 16.6 10.6 11.4 10.8 15.8 17.2 18.2 14 11.8 12 14.4 19.2 18 11 16.6 16 12 15.8 18.2 13.4 11.8 17.6 12.6 11.4 10.4 17 14.2 11 11.2 15.4 10.2 16.8 12.2 11.2 17.4 12.2 15 18.6 10.6 13.2 12.8 11.2 18.6 16 18.2 14 12.2 17.8

SGH MVN MOL MOL MOL HER MOL GOV GOV MOL MVN LGR MVN SGH MOL SGH MVN MOL LGR MVN MVN LGR LGR MVN HER MVN SGH MVN MVN SGH MVN MOL MOL MVN MOL MOL MOL MVN SGH MOL MOL MVN MVN MVN MVN MVN MVN MVN MVN MVN GAR GAR GAR GAR GAR GAR MVN GAR

Mind 0 1.6 0.4 2.2 3 7 1.2 1.0 2.4 4.6 6.2 0 2.6 2 3.8 2.6 5.4 6.2 3.8 0 1.4 1.2 3.8 0 0 9.8 0.2 0 3.6 0.4 0 1 0 0 0 0 0 0 0 7.2 1.8 3.8

Stne

Ratioe

Event typef

MVN/MOL HER GOV GOV GOV MVN GOV HER HER MVN MOL MVN LGR LGR LGR MVN SGH MVN MVN LGR MOL MVN MOL LGR SGH MOL MOL HER LGR MVN LGR LGR MVN SGH/LGR MVN LGR SGH/LGR LGR MVN MVN GAR GAR

2/4 5/5 5/5 5/5 5/5 5/5 5/5 5/5 5/5 3/3 3/3 3/4 4/4 4/4 4/4 4/4 4/4 4/4 4/4 3/4 4/4 4/4 4/4 3/4 4/5 4/4 5/5 4/5 5/5 5/5 4/5 5/5 4/5 2/4 3/4 3/4 2/4 3/4 3/4 2/2 3/3 3/3 1/1 1/1 1/1 1/1 1/1 1/1 1/1 1/1 2/2 2/2 2/2 2/2 2/2 2/2 2/2 2/2

Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Large scale Localized Localized Localized Localized Localized Localized Large scale Large scale Localized Localized Localized Localized Localized Localized Large scale Localized Localized Localized Localized Large scale Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Localized Large scale Large scale Localized Localized Localized Localized Localized Localized Localized

g g g g g g g g

3 5.8 2.2 4.4 13.8 5.2 1.2 16.8

MVN MVN MVN MVN MVN MVN GAR MVN

Comments

Pfm/Dome collapse

Pfm + 48 h

Pfm/dome collapse

Lahars

Pfm/Dome collapse, lahars Lahars

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Table 4 (continued) Datea

Maxb

Stnc

Mind

Stne

Ratioe

Event typef

4/1/2003 22/1/2003 17/2/2003 5/6/2003 14/6/2003 18/6/2003 7/7/2003 26/7/2003 25/8/2003 27/8/2003 8/9/2003 2/10/2003 19/10/2003 24/10/2003 29/10/2003 7/11/2003 9/11/2003 21/11/2003 25/11/2003 28/11/2003 29/11/2003 8/12/2003 13/12/2003 20/12/2003 25/12/2003 26/12/2003 27/12/2003

14.4 16.2 13.8 14.2 12.4 16.2 17.2 11.8 10.8 12.6 16 15.2 18.4 19 12.4 14.4 10.8 17.8 14.2 10.6 14.8 15.2 12.4 12.2 14.4 19.8 14.2

MVN MVN MVN HAR HAR MVN HAR MVN MVN GAR HAR HAR MVN HAR GAR GAR MVN HAR HAR GAR GAR MVN GAR MVN MVN MVN MVN

8 5.6 5.2 0 1.8 9.4 11.6 3.6 9 1.2 4.4 0 0.6 4.2 5.2 0.6 0 0 1.8 3 7.6 9 7.8 1.8 0 6.4 5.6

GAR GAR GAR MVN MVN HAR MVN GAR GAR HAR GAR GAR HAR MVN MVN MVN HAR MVN/GAR MVN MVN MVN GAR MVN GAR GAR GAR GAR

2/2 2/2 2/2 2/3 3/3 3/3 3/3 2/2 3/3 3/3 3/3 2/3 3/3 3/3 3/3 3/3 2/3 1/3 3/3 2/2 2/2 2/2 2/2 2/2 1/2 2/2 2/2

Localized Localized Localized Large scale Localized Large scale Large scale Localized Large scale Localized Localized Localized Localized Localized Large scale Localized Large scale Localized Localized Localized Localized Large scale Localized Localized Localized Localized Localized

a b c d g e f

Comments

Lahars

Lahars Lahars

This is the date on which the rainfall started. It is possible for a 24 h period to overlap 2 days. Maximum amount of rainfall recorded at any rain gauge in a 24 h period. Station code. Minimum amount of rainfall recorded at any rain gauge. No minimum is given as only MVN rain gauge was operational at this time. The ratio of the number of stations that recorded any rainfall to the number of stations that were operational. The type of weather system that caused the rainfall.

ed into 5 time periods (Table 5). This corresponded to times when either the dome was not growing (Period 1), was growing rapidly and in an unstable state (Periods 2, 4 and 5) or growing rapidly but with geometry domi-

nated by a collapse scar (Period 3). Although the least vulnerable time is immediately after a large collapse, these time periods were usually too short (a few weeks during rapid dome growth) to analyse in this way

Table 5 Variation of coincidence of rainfall and volcanic activity during differing periods of dome growth (at 20 mm rainfall threshold), for the period 1st December 1998 to 31st July 2003 Time

Total

Period 1a

Period 2

Period 3

Period 4

Period 5

Days Multiple pf daysb Lahar days Explosions days No. of times pfm more likely No. of times explosion more likely No. of times lahar more likely

1704 25 34 33 6.3 5.44 9.32

361 7 10 33 1.8 3.12 3.87

116 1 1 0 38.7 – 38.67

147 1 0 0 0 – –

348 3 2 0 9.7 – 14.50

732 13 5 0 6.6 – 9.04

a Time periods defined by broad scale changes in activity at SHV volcano. Period 1: 1st December 1998–November 27th 1999. No dome growth. Period 2: 28th November 1999–March 2000. Dome growing and becoming large and unstable. Period 3: March 21st 2000–August 16th 2000. Dome growing dominated by collapse scar. Period 4: August 17th 2000–July 29th 2001. Dome growing in large and unstable state. Period 5: July 30th 2001–July 31st 2003. Dome growing rapidly and dominated by large and unstable state. b Abbreviations as for Table 2.

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separately. However, our existing analysis shows that the correlation between volcanic activity and rainfall becomes less marked for the time period where there was no dome growth (Period 1) and where the dome geometry was dominated by a collapse scar (Period 3). Primary volcanic explosions were only recorded in the first time interval (other explosions were recorded during the course of the study but these have been attributed to the release of pressure following dome collapse) so it is not possible to correlate their occurrence with differing dome states and rainfall. 5.5. The lag between rainfall and volcanic activity The analysis this far deals with volcanic activity that has occurred within the same 24 h period. The length of the delay between intense rainfall events and the onset of elevated activity will have a bearing on the interpretation of the mechanism involved, particularly when differing types of activity are analysed. For this reason we also examined the variation of the probability of rainfall affecting volcanic activity for differing timescales after the onset of rainfall using the 20 mm threshold (Table 6). For example, 10 pyroclastic flow events were observed on the same calendar days when greater than 20 mm of rainfall was recorded. A further 6 were observed on the calendar days following the heavy rain days. However, it should be noted that some of these 6 may have occurred early on the following day, when the

Table 6 Variation of probability of rainfall affecting volcanic activity for varying time-scales after the onset of rainfall (20 mm threshold), for the period 1st December 1998 to 31st July 2003 Events

Same day

One calendar day latera

Two calendar days later

Rainfall + pfmb Rainfall + pf Rainfall + xp Rainfall + mu P (Pfm/rainfall) No. of times more P (Pf/rainfall) No. of times more P (xp/rainfall) No. of times more P (mu/rainfall) No. of times more

7 10 5 14 9.2% 6.30 10.5% 2.3 10.5% 5.4 18.4% 9.2

9 16 10 18 11.8% 7.13 21.1% 4.7 13.2% 6.8 23.7% 11.9

10 18 13 19 13.2% 8.94 23.7% 5.2 17.1% 8.8 25.0% 12.5

a

likely likely likely likely

Number in this column includes those events where the volcanic activity also took place on the same day as rainfall (cumulative total). For some of these events it was still raining when the delayed activity took place. b Abbreviations as in Table 2.

rainfall started on the day before so the lag between the onset of rainfall and the pyroclastic flow is not necessarily greater than 24 h. A further 2 pyroclastic flow events were observed two calendar days after the onset of rainfall. Similar lagged behaviour is also observed for multiple pyroclastic flows, explosions and lahars. 5.6. Characteristics of rainfall associated with individual weather systems and volcanic activity For each rainfall event a combination of GOES8 infrared images (see Appendix for archive details) over the current and preceding days were used to determine the nature and of the weather system, which was subjectively classified as either large or small scale (Tables 3 and 4). From January 2001 until December 2003 there were 56 24 h periods when N 20 mm of rainfall were recorded and on 7 instances (18 ddaysT) this occurred on consecutive days. Rainfall on 29 of these days was from large-scale weather systems, and there is a clear seasonal bias in the generation of larger-scale systems with the majority of those recorded during the rainy season. On Montserrat, most episodes of dome collapse have occurred within 1 to 2 h of the more intense bursts of rainfall that these systems deliver. This behaviour would seem to corroborate the observations relating to interannual variability. The large-scale regional systems that occur during the rainy season are the most important in delivering triggering levels of rainfall, with some notable exceptions (e.g. 20th March 2000, Carn et al., 2003). An example of a large-scale tropical weather system that brought intense rainfall to Montserrat occurred on 14th October 2001. The infrared satellite image (Fig. 6a) shows a large area of organised deep convection with four distinct centres in a northwest–southeast oriented band over the western tropical Atlantic. The majority of the rain on Montserrat (60 mm) fell between 1700 and 2000 (Fig. 6b) just after the organised convection reached Montserrat. Dome collapse that occurred on that day began about 1715, about an hour after the intense rainfall started, and peaked at 2215 (MVO reports). This collapse was associated with the removal of large amounts of unconsolidated talus associated with the dome grown prior to 29th July 2001. A typical case of intense rainfall on Montserrat with no attendant large scale weather system occurred on 12th July 2003. Over 20 mm of rain fell between 0600 and 0930 (Fig. 7b). The infrared satellite image at 0415 (Fig. 7a) shows clear skies around Montserrat. Hence, the rainfall originated from a localised weather system

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Fig. 6. (a) GOES-8 infrared image for 1615 local time on 14th October 2001, showing a typical large-scale tropical weather system affecting Montserrat (shown by white arrow). (b) Cumulative rainfall for 14th October 2001 from 4 rain gauges on Montserrat.

too small and short-lived to be visible on the satellite image. Pyroclastic flows started at 0653 and peaked much later in the day. This activity was preceded by considerable seismic unrest over the previous few days (MVO Reports). The reason for attempting to install and maintain a comparatively dense network of tipping bucket rain gauges was to assess the variability of rainfall across

the island during individual events. This allowed the suitability of using rain gauge sites remote from the volcano to determine thresholds for rainfall that might affect volcanic behaviour to be assessed. Table 1 provides summary information for some of the gauges and these variations in annual rainfall are found between most sites. When operational those rain gauges placed on and around the Soufrie`re Hills and at higher eleva-

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Fig. 7. (a) GOES-8 infrared image for 0415 local time on 12th July 2003, showing the absence of any large-scale weather system near Montserrat (shown by white arrow). (b) Cumulative rainfall for 12th July 2003 from the three gauges on Montserrat.

tions often recorded the wettest conditions with rainfall rarely uniform across the entire island. This is particularly true of low rainfall days (Table 4). St George’s Hill, for example, experienced 80 rainfall days where no rain was recorded at MVO North in 2001. Although the variation between gauges decreases at higher rainfall thresholds it remains at an average of approximately 35% of the average daily total until thresholds exceed 30 mm (e.g. see Fig. 7). For days with 30–40

mm maximum rainfall the variation is still approximately 25% of the maximum total (range 4–49% of the total) and for the 7 days where the daily total exceeded 50 mm the variation ranged from 2% to 70% of the maximum value. These data show that although large-scale weather systems have the potential to deliver large-amounts of rainfall to Montserrat, localised variation imposed by the topography and prevailing winds are still important

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for most systems. The use of just one (or even two) rain gauges in this region would not adequately represent or capture rainfall capable of triggering periods of enhanced volcanic activity. 6. Discussion During the monitoring period (December 1998–December 2003) there were 15 periods of primary activity that were associated with intense rainfall N 20 mm (Table 2). Because of the strong causative link between intense rainfall and dome collapse and the subsequent generation of pyroclastic flows, we will largely focus on these events in this discussion. Four of the seven multiple pyroclastic flow events were when total rainfall exceeded 40 mm and N 30 mm of this rain was delivered in less than 3 h. The data have shown a clear association between hazardous activity around the volcano and rainfall. For the purposes of this discussion we follow the suggestions of Francis and Oppenheimer (2004) and do not distinguish strictly between forecasting and prediction. With regard to the link between volcanic activity and rainfall we refer to short-range forecasts (of a few days), mid-range forecast (weeks to months) and longrange forecasts (seasons to years). This is not the same time-scale as that implicit in short, mid- and long-range meteorological forecasting but more appropriate to the time-scales on which volcanic activity is forecast. 6.1. The association of rainfall with volcanic activity It has been suggested that rainfall-induced activity is related to the phase change associated with the percolation and heating of intense rainfall (Mastin 1994; Matthews et al., 2002) or increased slope instability and the accelerated growth of cooling fractures (Mastin, 1994; Elsworth et al., 2004). The simple thermodynamic model of Matthews and Barclay (2004) suggests that this disruption should occur within 2–3 h of the onset of rainfall. This is largely the case (particularly for multiple pyroclastic flow or dome collapse episodes) but our analysis of the days immediately after these rainfall events would suggest that some activity occurs with a much longer time-scale of response (Table 6) as is suggested by Mastin (1994) for explosive gas emissions from Mount St. Helens. Furthermore, this delayed response appears to be most marked in the case of single pyroclastic flows and volcanic explosions, perhaps suggesting that the smaller-scale phenomena require longer for the propagation of the cooling effect of the rainfall. This could simply mean that the dome is in a less

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dprimedT state when these effects occur or that an entirely separate mechanism is in operation. The existing analysis of the influence of the style of dome growth (Table 5) also shows that the correlation between volcanic activity and rainfall becomes less marked for the time period where there was no dome growth (Period 1) and where the dome geometry was dominated by a collapse scar. These findings would suggest that the elevated thermal profile associated with dome growth (being more sensitive to the cooling effects of intense rainfall) and the geometry (or readiness to collapse) of the dome are indeed important in determining the strength of the association with rainfall. This must, however, be reconciled with the observation that there is no record of primary volcanic activity attributed to rainfall during the first phase of dome growth (1995–1998) on Montserrat. It has recently been suggested (Calder et al., 2005) from a statistical analysis of seismic rockfall data that dome failure is controlled more strongly by external forces (such as rainfall) when dome growth rates are comparatively slow and it could be that this has more often been the case between 1998 and 2003. The mechanisms for this response will be further elucidated by a detailed analysis of the time-series of both continuous rainfall and broadband seismic data (Johnstone et al., in preparation). 6.2. Annual and interannual variability and mid- to long-range forecasting The analysis of the 1998–2003 rain gauge dataset in conjunction with the regional climatology has shown that Montserrat usually experiences two peaks in the rainy season; one from May to July; and a longer, larger peak centred around late September. During this period ddailyT rainfall totals N 20 mm largely originate from synoptic-scale weather systems. At other times intense rainfall more usually originates from more localised weather systems (Table 3). All 10 of the pyroclastic flow episodes associated with rainfall occurred on or around one of the seasonal peaks in rainfall activity. It should be noted that once large-scale collapses have occurred, the volcano will not be in a vulnerable state for some considerable period of time (dependent on lava extrusion rate) and thus the likelihood of rainfall triggering dome collapse consequently decreases. This explains the bias towards dearlyT rainy season collapse between 2001 and 2003, dominated by the large collapse events on 29th July 2001 and 12th July 2003. Interannual variability in the regionally averaged rainfall (2.58  2.58 CMAP grid) around Montserrat is correlated with positive SST anomalies in the equatorial

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eastern Pacific, southern Caribbean and north tropical Atlantic, and negative anomalies in the subtropical North Atlantic; being associated with high rainfall years. However, this broad correlation between SST anomalies and averaged rainfall was not as clear at our point rain gauge sites on Montserrat (Fig. 2). This points to the localised topographic and other large-scale factors which can affect rainfall over the Caribbean in addition to the inherent noisiness of point rainfall measurements and random stochastic atmospheric processes. Nonetheless, these findings show that there is potential for an increase in forecast skill up to a few months ahead and this is the subject of an ongoing comprehensive statistical forecasting study. 6.3. Rainfall variability and short-range forecasting The correlation between high rainfall and synopticscale weather systems becomes more marked during the rainy season. Such systems are already predicted well by the global forecast and assimilation models run by national meteorological centres and relevant data are freely available (see Appendix). This means that the trajectory and evolution of such systems can often be forecast up to at least a few days in advance. For example, the rainfall on 29th July 2001 which resulted in the collapse of 45  106 m3 of material was predicted by the 60 h forecast issued by the UK Meteorological Office at 2000 Montserrat time on the 27th July 2001 (Matthews et al., 2002). Clearly, the immediate utility of using meteorological forecasts in volcano monitoring is dependent on the actual rainfall that is delivered from any particular weather system. For the time period December 1998 to July 2003 the conditional probability for volcanic activity for differing levels of rainfall was investigated using our rainfall data and published reports of activity from the MVO (Table 2) and the strong correlation between rainfall and volcanic activity of more than one type is consistent with the findings from a shorter time period (Matthews et al., 2002) and similar to the finding of Yamasato et al. (1998) for activity at Unzen volcano in Japan and those of Mastin (1994) for Mt. St. Helens. Measured rainfall shows considerable variation across the island, regardless of the type of weather system that has produced the precipitation. This can largely be attributed to topographic variation. This implies that when considering triggering thresholds for rainfall it is particularly important to site rain gauges on or very close to the volcano itself. Pragmatically we found that there was an important trade-off in siting rain

gauges in close proximity to the volcano and reliability and retrievability of the data. Knowledge of localised variation in precipitation from any existing climatological datasets should prove extremely useful. Variations in our data between rain gauge sites were similar to those in the 30 year average from 1933 to 1963 (UK DFID, unpublished data). Furthermore, for the heavier rainfall days the absolute variation between gauges was less, so location of the triggering gauge on the island would be less important. Nonetheless, the use of only one rain gauge on Montserrat would have failed to capture some of the significant rainfall events and could not have been used to predict higher levels of rainfall at other sites (see for example rainfall from 12th July 2003 at MVN, Fig. 7b). A long-term goal of our work is to produce a robust statistical analysis of mesoscale variations and their causes and incorporate them into a forecasting regime for the island. This will provide a useful test of the utility of using comparatively few rain gauges to define triggering thresholds of rain around an active volcano and considerably increase the skill of making short-range forecasts for activity relating to the passage of individual weather systems over Montserrat. 7. Conclusions and application to other active volcanoes within the Tropics In analysing the rainfall data from December 1998 to July 2003 we have found that: (1) There is a correlation between intense rainfall and enhanced primary volcanic activity as well as the generation of lahars. The most marked correlation is between multiple pyroclastic flow (dome collapse) episodes and rainfall although we have found evidence of increased explosive activity too. The majority of the rainfall associated with dome collapse was generated by synoptic-scale weather systems during the rainy season on the island. (2) Our existing analysis provides some evidence that the correlation between rainfall and volcanic activity is likely to be stronger when the dome is not stagnating and is already in an unstable state. There is also evidence that some activity (pyroclastic flows and explosions) is triggered up to 48 h after the onset of intense rainfall although the majority occurs within 24 h. (3) Montserrat lies north of the Intertropical Convergence Zone and as such only receives ~32% of the maximum rainfall that falls in that region.

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There is significant local enhancement of the regional open-ocean value due to topographic effects on the island and this also leads to large topographic variations in rainfall totals during any one event although there is no detectable diurnal variation in rainfall patterns. (4) Interannual variability can be partially attributed to regional variations in sea-surface temperatures and these can be detected weeks to months in advance of resultant enhanced rainfall. Seasonal variations are more pronounced with particularly enhanced rainfall in May–July and late August to October. The highest values for rainfall during these times are associated with (predictable) synoptic-scale weather systems. In the absence of long-term rain gauge data knowledge of open-ocean rainfall values and seasonal variability would allow for the prediction of likely periods of rainfall-induced volcanic activity. (5) Rainfall patterns during individual events are variable across the island, even from synoptic-scale weather systems. A single rain gauge (particularly if sited in a different orographic region) would be unlikely to capture many of the triggering rainfall events on the island. This work has shown that, given the link between rainfall and both primary and secondary volcanic activity, meteorological information can be exploited more fully to enhance volcano monitoring programs, particularly in the Tropics. Knowledge of the regional weather systems and interannual variability in global climate could prove particularly useful in forecasting rainy seasons with above average levels of rainfall weeks to months in advance, a time-scale of preparedness rarely available in volcano monitoring (see Appendix for information sources). The majority of rainfall events that induced activity were related to the passage of synoptic-scale weather systems which are predicted by forecast models run and issued by national meteorological centres (Appendix) with the potential to be forecast several days in advance. In defining and setting triggering thresholds for rainfall it is necessary to have a detailed and precise knowledge of mesoscale variation in rainfall across the triggering region and how this is reflected by actual rainfall recorded. A goal of future work will be to provide a comprehensive statistical, regional and mesoscale forecasting study of the rainfall around Montserrat with a view to its application at other volcanic sites.

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Acknowledgements We would like to thank an anonymous reviewer and Larry Mastin for their reviews. We would particularly like to thank Larry Mastin for his careful and thoughtful review and his generous sharing of ideas, provoking us to do more with our data. We would like to thank our colleagues at the Montserrat Volcano Observatory without whom this study would not have been possible. In particular we would like to thank Richard Herd and Pyiko Williams for downloading and maintaining the rain gauges as well as providing helpful discussion and Marie Edmonds, Art Jolly, Glenn Thomson, Gill Norton and Peter Dunkley for many useful discussions. The UK Department For International Development provided us with the rain gauge data. These data were gathered by the Ministry of Agriculture, Government of Montserrat. The CMPA and SST data were provided through the NOAA Climate Diagnostic Centre. This research was supported by the NERC and the School of Environmental Sciences, UEA. Appendix A. Useful URL’s and contacts used for obtaining meteorological information GOES 8 Image Archive (IR images every 12 h of Caribbean region). http://cdo.ncdc.noaa.gov/GOESBrowser/goesbrowser. CPC Merged Analysis Precipitation data set from the Climate Diagnostics Center. http://www.cdc.noaa.gov/. Montserrat Volcano Observatory (archived reports) http://www.mvo.ms/. UK Meteorological Office (forecast data). http://www.met-office.gov.uk/. References Calder, E.S., Cortes, J.A., Palma, J.L., Luckett, R., 2005. Probabilistic analysis of rockfall frequencies during an andesite lava dome eruption: The Soufriere Hills Volcano, Montserrat. Geophys. Res. Lett. 32, L16309. doi:10.1029/2005GL023594. Carn, S.A., Watts, R.B., Thompson, G., Norton, G.E., 2003. Anatomy of a lava dome collapse: the 20 March 2000 event at Soufriere Hills Volcano, Montserrat. J. Volcanol. Geotherm. Res. 120, 1 – 20. Chivers, C. 2004. Unpubl. MSc Thesis. Precipitation-triggered lahars at the Soufrie`re Hills volcano, Montserrat. University College, London. Druitt, T.H., Kokelaar, B.P. (Eds.), 2002. Geological Society of London Memoir, vol. 21, pp. 263 – 279. Elsworth, D., Voight, B., Thomson, G., Young, S.R., 2004. Thermal– hydrologic mechanism for rainfall-triggered collapse of lava domes. Geology 32, 969 – 972.

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