TRENDS IN EXTREME DAILY RAINFALL ACROSS THE SOUTH PACIFIC AND RELATIONSHIP TO THE SOUTH PACIFIC CONVERGENCE ZONE

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1 INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 23: (2003) Published online in Wiley InterScience ( DOI: /joc.923 TRENDS IN EXTREME DAILY RAINFALL ACROSS THE SOUTH PACIFIC AND RELATIONSHIP TO THE SOUTH PACIFIC CONVERGENCE ZONE G. M. GRIFFITHS, a, * M. J. SALINGER a and I. LELEU b a National Institute of Water and Atmospheric Research (NIWA), Auckland, New Zealand b Météo France DSO/DEL, 7, rue Teisserenc-de-Bort BP 202, 78195, Trappes, France Received 10 July 2002 Revised 28 March 2003 Accepted 2 April 2003 ABSTRACT Daily rainfall records from 22 high-quality stations located in the South Pacific were analysed, over the common period , in order to assess whether extreme rainfall events have altered in their frequency or magnitude. A comprehensive spatial coverage across the South Pacific was provided, analysing a range of indices of extreme precipitation, which reflect both high rainfall events and drought. Clear spatial patterns emerged in the trends of extreme rainfall indices, with a major discontinuity across the diagonal section of the South Pacific Convergence Zone (SPCZ). Stations located between 180 and 155 W exhibit a greater number of significant abrupt changes in extreme climate than elsewhere in the South Pacific, and the majority of climatic jumps occur in the 1970s or 1980s (coincident with a displacement northeastward of the diagonal part of the SPCZ and a large local increase in mean annual temperature). Notably, all significant abrupt changes in an extreme rainfall intensity index occurred in the late 1970s or early 1980s, and in every case the index showed an increase in extremity following the change point, regardless of station location. For the stations located south of the SPCZ, this may also be linked to the observed warming since the 1970s. Significant abrupt changes in mean precipitation were also identified around the mid 1940s, for two longer, century-scale records, which again correspond to a major displacement of the diagonal section of the SPCZ. An indicator of the diagonal SPCZ position is significantly temporally correlated with an extreme rainfall intensity index, at two locations either side of the diagonal section of the SPCZ, at decadal time scales or longer. This suggests that the displacement of the diagonal portion of the SPCZ on decadal time scales influences not only mean precipitation, but also daily rainfall extremes. Copyright 2003 Royal Meteorological Society. KEY WORDS: South Pacific; rainfall; extreme climate indices; South Pacific Convergence Zone 1. INTRODUCTION The most significant consequences of global warming for small island nations are likely to be related to changes in sea levels, rainfall regimes, soil moisture budgets, and prevailing winds (McCarthy et al., 2001). The island states of the South Pacific Ocean are particularly at risk from these changes. Pacific Island nations are typically small in physical size, and are isolated by large expanses of ocean. They are highly susceptible to natural disasters and extreme events, such as tropical cyclones, storm surge, and drought with severe economic effects (McCarthy et al., 2001). Climate change is expected to affect extremes, with larger yearto-year variations in precipitation very likely over most areas where an increase in mean precipitation is projected (Houghton et al., 2001). Indices of climate extremes have been used to monitor changes in extreme events. Improved knowledge of past changes in extreme climate complements climate modelling of global warming, as projected by climate models driven by increasing greenhouse gases (Houghton et al., 2001). Uniform sets of indicators and methods * Correspondence to: G. M. Griffiths, National Institute of Water and Atmospheric Research Ltd (NIWA), PO Box , Newmarket, Auckland, New Zealand; g.griffiths@niwa.cri.nz Copyright 2003 Royal Meteorological Society

2 848 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU have been developed (Nicholls and Murray, 1999), so that there might be some global consistency. A few regional studies have used indices specifically to look at changes in extreme climate, often in relation to changes in mean climate (Haylock and Nicholls, 2000; Manton et al., 2001). Little information was available about trends in extreme temperature or rainfall in the Asia Pacific region before the Manton et al. (2001) paper, which investigated trends in extremes in Southeast Asia and the tropical South Pacific region for the period Manton et al. (2001) concluded that almost all stations in the Southeast Asia and tropical South Pacific study region exhibited increases in the frequency of hot extremes, and decreases in the frequency of cold extremes, often significantly. Trends in extreme rainfall showed little spatial consistency, however, with very few statistically significant trends. Exceptions were the number of rain days (which had decreased at most, but not all, tropical locations, with some decreases being significant), and the proportion of annual rainfall from extreme events (which had increased at the majority of tropical stations analysed). It is notable that, in the Manton et al. (2001) study, the data coverage across the vast South Pacific Ocean was limited to stations within three Pacific Island countries only (New Caledonia, Fiji, and French Polynesia) with no data at all between longitudes 180 and 150 W. It was beneficial, therefore, to analyse further the extreme rainfall trends across the entire South Pacific, with a more comprehensive data coverage, especially around the South Pacific Convergence Zone (SPCZ), given Pacific Island nations susceptibility to extreme events, and the strong influence the SPCZ is known to have on mean precipitation. The relatively broad SPCZ is one of the most extensive and significant features of the atmospheric circulation in the South Pacific (Vincent, 1994). The SPCZ is characterized by low-level convergence, cloudiness, and precipitation, and it is located in the region of strong sea-surface temperature (SST) gradient (Karoly and Vincent, 1998). The SPCZ is schematically orientated northwest southeast (Figure 1), its mean annual position extending from around 0 S, 140 E, to approximately 30 S, 110 W (Vincent, 1994). The northwestern portion of the SPCZ is zonally orientated, with a diagonal section lying east of the dateline (180 ). The two sections of the SPCZ have different characteristics: SST gradients strongly affect the zonal portion of the SPCZ, and the subtropical jet and tropical midlatitude interactions influence the diagonal part of the SPCZ (Vincent, 1994). There is significant movement around the SPCZ mean position seasonally, annually and on longer time scales. For example, the SPCZ is most active during the austral summer, December February (DJF; Vincent, Tarawa 0 0 Nanumea Funafuti Penrhyn Atuona Pukapuka Rotuma Apia Labasa Keppel Rarawai Faaa Suva Alofi Aitutaki Koumac Nukualofa Rarotonga Noumea Pitcairn Rapa Raoul Figure 1. Location map showing all stations used in the analysis (dots) and corresponding place names referred to in the text. The dashed line represents the schematic mean position of the SPCZ, after Folland et al. (2002), defined as a maximum of low-level convergence. The zonal portion of the SPCZ lies west of the dateline, and the diagonal section to the east of 180

3 SOUTH PACIFIC EXTREME DAILY RAINFALL ), with lowest surface pressures and highest rainfall rates. When at its strongest, in DJF, the diagonal portion of the SPCZ is located much further poleward (Karoly and Vincent, 1998). The SPCZ position is also known to vary systematically with the polarity of El Niño Southern Oscillation (ENSO), moving northeastward during an El Niño event (Karoly and Vincent, 1998). The location of the SPCZ also varies with the Interdecadal Pacific Oscillation (IPO), a Pacific-wide fluctuation in SST and circulation of year oscillations (Folland et al., 2002). When the IPO is in its positive (negative) phase, the mean SPCZ position is displaced northeast (southwest). Folland et al. (2002) found that shifts in the position of the SPCZ related to ENSO on interannual time scales, and the IPO on decadal time scales, are largely linearly independent, except around 170 W. Therefore, the SPCZ is located furthest northeast during El Niño events with a positive IPO, and furthest southwest during La Niña events with a negative IPO. The position of the SPCZ varies most strongly in the diagonal section of the SPCZ, between about 180 and 130 W, with the zonal section of the SPCZ showing slightly less latitude change under the effects of ENSO and the IPO (interpretation from figure 4(a), Folland et al. (2002)). The effects of SPCZ movement on mean rainfall regimes in the South Pacific have been large in the past. Much of the variability in the mean rainfall record in the Pacific Islands is closely linked to ENSO or the IPO (Salinger et al., 2001) and is directly attributable to shifts in the SPCZ or intertropical convergence zone (ITCZ; McCarthy et al., 2001; Folland et al., 2002). Salinger et al. (2001) found that increases of mean annual precipitation of 30% or more occurred northeast of the diagonal section of the SPCZ, between the most recent phase of the IPO ( ) and the previous negative phase ( ). Decreases in mean annual rainfall to the southwest of the SPCZ were found to be smaller, but both changes in annual precipitation were considered consistent with a movement in the mean location of the diagonal SPCZ northeastwards. However, the above changes in mean precipitation occurred against a background of warming, with a regional increase in mean annual temperature between the two IPO periods of 0.3 C (Salinger et al., 2001). Mean annual temperatures northeast of the diagonal part of the SPCZ, and around a line from Rotuma to Alofi (Figure 1), increased more than this, with most warming observed since the 1970s, while the region north of the zonal portion of the SPCZ showed less or no warming (Salinger et al., 2001). Regions to the southwest of the SPCZ showed steady warming throughout the period. Folland et al. (1997) also noted a major discontinuity in decadal-scale temperature trends across the SPCZ, for annual South Pacific island and ocean temperatures. This study aims to assess the influence of the SPCZ on extreme rainfall in the tropical South Pacific, given the strong relationship exhibited between the SPCZ and mean rainfall and the importance of the SPCZ as a major climatic feature of the region, against a background of warming. Annual indices of extreme rainfall across 22 stations in the South Pacific, from a comprehensive coverage of 11 island nations, have been analysed. Trends in extreme rainfall, and the spatial and temporal coherence of these with the SPCZ, are presented in Section 3, on decadal or multi-decadal time scales. To the authors knowledge, this is the first investigation into the relationship between extreme rainfall and the SPCZ. 2. DATA ANALYSIS METHODS 2.1. Data Daily rainfall data from 22 climate stations in New Caledonia, Kiribati, Tuvalu, Fiji, Raoul Island, Tonga, Cook Islands, Western Samoa, Niue, Pitcairn, and French Polynesia were analysed (Figure 1). Some of these data were made available through the second Asia Pacific Network (APN) workshop on climate extremes (Manton et al., 2001) and other data were accessed either through the NIWA National Climate Database, Meteo-France or directly from national meteorological services. Station details are listed in Appendix A. These 22 stations, of high quality, were selected from a much larger pool of stations in the South Pacific. The selected stations satisfied the following criteria: The daily records were as complete as possible, with less than 20% of data missing in each year. Most station records had significantly less missing data than this.

4 850 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU The record was as long as possible and the station remained open at the time of analysis. The stations selected were of high quality, were non-urban and were well maintained. The station usually had documented metadata history consisting of a history of site location, observing instruments, and observing practices. The station usually had not been moved from the original site location. In most cases, the selected stations were located at the principal site of the national meteorological service in each country, with the site location and environment not being altered significantly and being well maintained. Instrumentation and observation practices were less well documented Quality control All major outliers in the rainfall records were examined visually. Confirmation that these data were related to real meteorological events, rather than being erroneous, was made manually against known flood or heavy rainfall events, or tropical cyclone passages, if this information was to hand. Some of the Pacific Island communities confirmed events when contacted (personal communications), since major rainfall events were either associated with a tropical cyclone or with destructive flooding events. The outlier data were also checked for internal consistency against other records within the same island group, if these existed. The 22 rainfall records were carefully screened for inhomogeneities by firstly examining metadata (Collen, 1992). Major events, such as instrumentation change or environment change, which may have altered the record stationarity, were noted. Comparisons with neighbouring stations to identify unrecorded site changes, or other environmental changes near the climate station site, were performed. Annual total rainfall series were produced and examined using the Multiple Analysis of Series for Homogenisation (MASH) software (Szentimrey, 1996). Some shorter duration records, which were close to sites being analysed, were used as nearest neighbours in the MASH process, but were not included in the 22 stations selected for further analysis. If MASH identified a breakpoint in the rainfall series related to a known event found through the metadata search, then the data adjustment calculated by MASH was adopted, otherwise it was not. There were only two adjustments required (to Alofi and Keppel Island). Because of the isolation of some Pacific Island climate stations, it is acknowledged that the method of nearest-neighbour checks is sub-optimal Indices analysis: methods Annual indices of extreme rainfall or temperature have been used in numerous previous studies, in order to quantify trends in a consistent way across a study domain. Some indices use arbitrary thresholds, such as the number of days above 25 C (Salinger and Griffiths, 2001). Other indices are based on statistical quantities such as percentiles, which are suitable for regions that contain a broad range of climates. For example, the South Pacific area of interest covers from the equator to near 30 S. The mean annual rainfall across the region varies from approximately 1000 mm to around 3500 mm. Percentiles were therefore used in this study to calculate several indices, and were computed using all the non-missing days. The 95th percentile corresponds to the 18th highest value per annum, and the 99th percentile corresponds to the fourth highest value, in a 365 day year. If, in any year, the probability that all of the four most extreme events for that year would be missing exceeds 0.5, then the index for that year is set to missing. No adjustment was undertaken to remove the annual cycle from any of the indices, because absolute extremes, which are traditionally those events with the largest impact on the populations exposed to them, are the focus of this study. The indices are calculated over the full calendar year (January December), although it is more common to deal with the November April period (the wet season ) when analysing tropical features in the Southern Hemisphere. Figure 2 is one illustration of what was uniformly found for all precipitation indices across the South Pacific (the Pukapuka record was used here as an example) that, in fact, to capture all available information about the most extreme daily rainfall events it is necessary to use rainfall data from the full 12 months of a year. Figure 2 shows the extreme intensity index at Pukapuka, an indicator of the typical size of an extreme daily rainfall event (it is the average of the highest four rainfalls each year). The annual calculation captures more

5 SOUTH PACIFIC EXTREME DAILY RAINFALL (MM) Figure 2. A comparison of the extreme intensity index at Pukapuka, calculated both annually (dashed line) and over the months November April (solid line), for the period information about extreme precipitation than the 6 month calculation, for very extreme years. For example, in 1987, the annual index was 173 mm, and the six-monthly index 132 mm. That is, several extreme high daily rainfall events occurred outside the November April period in 1987, of practical importance to the community at Pukapuka. Also, the trend in extreme intensity at Pukapuka was largest (and more significant) when calculated over the calendar year (not shown here), more adequately reflecting the rise in extreme rainfall events for the island, regardless of what time of year these occurred. It was therefore considered appropriate here to use the full calendar year for indices calculations. This study does not address the seasonal aspects of either the SPCZ or extreme precipitation. An investigation into seasonal changes of the SPCZ and extreme rainfall may be valuable in future work, however. In this study, each annual index of extreme precipitation is analysed at the decadal or multi decadal time scale, and related to an SPCZ position indicator. Seven extreme indices were examined from daily rainfall data at 22 stations. Some of the indices were calculated using software provided by two APN workshops. Four of the indices chosen are the same as thoseusedbymantonet al. (2001). These are rain days, extreme intensity, extreme frequency, andextreme proportion. Only nine stations are in common between the Manton et al. (2001) paper and this study. All 22 stations selected were used when analysing the indices over the period This period was chosen as it was the common data period for these highest quality stations. The seven annual rainfall indices analysed in this paper are defined in Table I. Annual indices of total annual rainfall, and the number of rain days, are easily interpreted. The dry spell index calculates the maximum consecutive number of dry days each year, and the 5 day index simply measures the greatest 5 day rainfall received per annum. Extreme Table I. Annual extreme rainfall indices; the index units are in parentheses Measurement Total annual rainfall (mm) Number of days with greater than or equal to 2 mm of precipitation (days) Maximum number of consecutive days with rainfall less than 1 mm (days) The greatest 5 day rainfall total (mm) Average intensity of events greater than or equal to the 99th percentile, i.e. average size of the four wettest events (mm) Frequency of daily rainfall exceeding the mean 99th percentile (days) Percentage of annual total rainfall from events greater than or equal to the 99th percentile, i.e. received in the four wettest events (%) Index name Total rain Rain days Dry spell 5 day Extreme intensity Extreme frequency Extreme proportion

6 852 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU frequency is a count of high rainfall events per year. Two indices (extreme intensity, extreme proportion) are more difficult to interpret, in that they relate to percentiles. As there are 365 days in a year, the 99th percentile corresponds to the fourth highest rainfall. An extreme rainfall is defined here as being equal to or above the 99th percentile. Extreme intensity is an indicator of the typical size of an extreme rainfall event: it is the average of the highest four rainfalls each year. Extreme proportion measures how much of the total rain comes from extreme events: it is the proportion of annual rainfall that comes from the highest four rainfalls each year. Linear trends, calculated using least-squares linear regression, were examined for each of the indices. Statistical significance was determined using the Mann Kendall ranked τ statistic (Tarhule and Woo, 1998). A trend is indicated as significant if it has at least 95% significance using this test Relationships between extreme rainfall indices: methods The rainfall indices were selected to describe whether extreme daily precipitation is increasing or decreasing in either magnitude or frequency. The dry spell index is a measure of whether droughtlike periods are increasing or decreasing in duration, whereas the 5 day index is a measure of extended duration rainfall extremity. Even without a parametric approach to the question have rainfall distributions changed over time, the relationship between extreme rainfall indices over the period can be examined, and some conclusions about the changes in the shape of the daily rainfall distribution inferred. Correlations between the seven indices were analysed, over the period The correlations were calculated for all seven indices at each station and tested for significance, with p-values adjusted for multiple significance testing. Carrying out many significance tests increases the risk of one or more significant correlations being discovered due to chance (a type I error). A standard method to adjust for this is the Bonferroni correction, where the α level (the chance of a type I error) of each individual test is adjusted downwards by the number of tests simultaneously performed (Miller, 1981). Additionally, principal component analysis (PCA) and hierarchical cluster analysis (a multivariate procedure for detecting natural groupings in data) were used to confirm these results Orographic versus convective extreme precipitation: method The 22 stations were divided into two groups, atoll and island, depending on the nature of the location. Atolls were defined as having low elevation, with a lack of hills or mountains to form orographic precipitation. Rainfall at atolls is therefore produced by convective processes, which may or may not be associated with synoptic features such as troughs or convergence zones. Islands were deemed here to be locations with significant hills or mountains; capable of producing orographic precipitation if wind flows and the ambient meteorological conditions were conducive. A t-test was used to determine whether indices of extreme precipitation over the period differ between the two groups, with significance adjusted for simultaneous testing (Bonferroni corrections) Extended time series analysis: methods The SPCZ position index (SPI), an indicator of SPCZ position directly after Folland et al. (2002), is shown in Figure 3. The SPI is calculated as the normalized November April difference in mean sea-level pressure between Suva, Fiji, and Apia, Samoa, based on the normal period. These two stations have reliable, century-scale pressure records, and were chosen because they are located either side of the mean SPCZ location. The SPI defines the SPCZ latitude between longitudes 180 and 170 W, with positive (negative) values of the SPI indicating displacement of the SPCZ anomalously north (south) of its mean position. However, previous analysis of 10 m divergence and the SPI index (personal communication with the authors of Folland et al. (2002)) indicated that the SPI is highly correlated with the SPCZ position between 160 E and 120 W, between the equator and 30 S, although there is an area of lower correlation (less than 0.5) between 160 E and 170 E, south of the zonal section of the SPCZ. Therefore, the SPI is considered a

7 SOUTH PACIFIC EXTREME DAILY RAINFALL 853 Figure 3. A bar graph of the SPI (with padded nine-point binomial filter) over the period robust indicator of displacement of the diagonal portion of the SPCZ. The long-term positional change of the (western) zonal portion of the SPCZ is difficult to quantify by pressure-based position indicators, because of a lack of available long-term pressure data close to the zonal SPCZ. Significant changes in the SPI series were identified by the non-parametric Pettitt test. This test signals a change in a series of observations, with no assumptions made about the distribution of the variable (Pettitt, 1979). Note that the performance of the test may be affected by outliers or missing data. Identification of abrupt changes (also called change points or climatic jumps) in a time series is viewed as complementary to the analysis of trends for a given time period (Tarhule and Woo, 1998), since a linear trend across natural abrupt changes in a time series can result in artificial trends, which do not adequately reflect the variability or cyclic nature of the underlying processes. For example, a significant linear trend can result across an abrupt step in a time series, even with the series being stationary both before and afterwards. An extended temporal analysis of five extreme rainfall indices was undertaken at six South Pacific sites, namely Funafuti, Pukapuka, Penrhyn (north of the SPCZ mean position), and Alofi, Aitutaki, and Pitcairn (south of or near the SPCZ mean position). These six stations were chosen because they represent the longest available daily rainfall records in the South Pacific, are of high quality, and are spatially distributed approximately evenly. Three analyses were performed on these series. The first analysis identified abrupt changes (Pettitt, 1979) in the extreme rainfall series at each individual station (individual series not shown), since the start of each record. A comparison with the identified SPI change points was made. In the second analysis, where a significant climatic jump was identified, the linear trend prior to and following the abrupt change was calculated, with trend significance assessed by the Mann Kendall ranked τ test. This testing of the stationarity of the sub-series was intended to address both the issue of artificial linear trends arising across an abrupt change, and also to gain information about the nature of the index series itself. It is important to determine whether a series is non-stationary due to the occurrence of climatic jumps, trends, or a mixture of both, when making inferences about climate records. The third analysis utilizes daily rainfall data from the start of two of the longest available daily rainfall records, Alofi (complete daily data start in 1907) and Pukapuka (daily data start in 1932), which are located either side of the mean SPCZ position. The movement of five extreme rainfall indices at these two sites is compared with movement in the SPI index, via lag correlations between detrended and differenced time series.

8 854 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU 3.1. Extreme rainfall trends RESULTS Table II contains the (raw) trends per decade for the seven precipitation indices analysed at 22 stations in the South Pacific. The spatial distribution of the (normalized) trends is shown in Figures 4 6. Over the period , the SPI (Figure 3) exhibited a strong increasing trend. The more recent positive values of the SPI indicate that the diagonal section of the SPCZ has moved northwards of its mean position over the period of analysis Total rain. The total rain (Figure 4, upper panel) has generally decreased over the South Pacific south of the schematic diagonal part of the SPCZ over the period (e.g. east of 180 ). There has been a general increase in the index northeast of the diagonal SPCZ, with the largest trends occurring in the eastern Pacific Ocean, east of 160 W. Funafuti, Keppel and the northern Cook Islands have all shown weak (non-significant) increases in the total rain index over the period. Statistically significant increases in the total rain index were observed only at Penrhyn (with an increase of around 500 mm per decade over the period analysed) and at Atuona (approximately 250 mm per decade). The southern Cook Islands, Rapa, Apia, Nuku alofa, and Raoul Island all exhibit a weak (non-significant) decrease in the total rain index, with a significant decline of 180 mm per decade observed at Pitcairn. Trends in the total rain index are small west of the dateline, with the sign of the trend not coherent within the island groups of Tonga, Fiji, New Caledonia and Tuvalu. Broadly, trends are spatially consistent east of about the dateline, with a discontinuity across the diagonal portion of the SPCZ. These results are consistent with the diagonal SPCZ having moved northwards over the analysis period. Table II. Linear trends per decade, for the period Statistically significant trends at the 95% level are in bold Country Location Total (mm) Rain days (days) Dry spell (days) 5Day (mm) Extreme intensity (mm) Extreme frequency (days) Extreme proportion (%) New Caledonia Noumea Koumac New Zealand Raoul Tuvalu Funafuti Nanumea Kiribati Tarawa Fiji Suva Rarawai Rotuma Labasa Tonga Nukualofa Keppel Niue Alofi Samoa Apia Southern Cook Islands Rarotonga Aitutaki Northern Cook Islands Pukapuka Penrhyn French Polynesia Rapa Faaa Atuona Pitcairn Pitcairn

9 SOUTH PACIFIC EXTREME DAILY RAINFALL Figure 4. Normalized trends in total rain ( upper panel), rain days ( middle panel) and dry spell (lower panel) over the period Circle size is proportional to the size of the normalized linear trend per decade. Black circles represent positive trends; white circles represent negative trends

10 856 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU Rain days. Generally, trends in the rain days index are similar to trends seen in the total rain index, with observations of more rainfall typically corresponding to more rain days, with the converse also holding true (Figure 4, middle panel). Rain days have generally decreased south of the schematic diagonal SPCZ location (e.g. east of 180 ), over the period Significant trends were again observed east of 160 W, at Penrhyn (an increase of 17 rain days per decade over the period ), at Atuona (an increase of 13 days), and at Pitcairn (a decrease of 8 days). Often the non-significant trends in this index were of the same sign as the trend in total rain, except where the normalized trends were effectively zero (Raoul Island, Nanumea, Labasa, Keppel and Pukapuka). Again, the observed trends are consistent with the northward movement of the diagonal portion of the SPCZ Dry spell. The dry spell index calculates the maximum consecutive number of dry days each year. Stations lying to the southwest of both zonal and diagonal sections of the SPCZ, or near the SPCZ zone itself, clearly exhibit an increase in the dry spell index, corresponding to a lengthening of the maximum dry period duration (Figure 4, lower panel). New Caledonia, Raoul Island, Tonga, Niue, Samoa, Pukapuka, Rarawai, Labasa and Pitcairn all show an increasing trend in this index, to a maximum of 4.3 days per decade at Koumac. The only significant trend occurs at Aitutaki, with an increase of 1.7 days per decade over the period Tarawa, Penrhyn and Atuona generally show a decrease in the dry spell index, but, unlike the total rain and rain days indices, the eastern Pacific Ocean stations do not show the largest trends or any significance in these trends. This lengthening of the dry spell southwest of the entire SPCZ is consistent with the diagonal section of the SPCZ having moved northwards, and with an increase in mean sea-level pressure west of the dateline since 1977, as observed by Salinger et al. (2001) The 5 day Index. The 5 day index simply measures the greatest 5 day rainfall received per annum. This index (Figure 5, upper panel) shows inconsistent trends to the west of the dateline, but a general increase in the vicinity of the SPCZ between 180 and 170 W (around a line from Rotuma to Alofi) and also at Pukapuka, Penrhyn (with a significant increase of 29 mm per decade) and Atuona, all lying northeast of the diagonal SPCZ. Notably, there is a difference between the total rain and the 5 day indices in the vicinity of the SPCZ region at Nuku alofa and Apia. At these sites, the trends in the two indices are of opposite sign, although of a non-significant size. Weak (non-significant) decreases are observed at Koumac, Raoul Island, Funafuti, Tarawa, Suva, Aitutaki and also at Pitcairn, Rapa and Faaa in the east. Nanumea shows a significant decreasing trend in the 5 day index of 22 mm per decade over the period East of 170 W, these trends are consistent with the northward displacement of the diagonal part of the SPCZ. A marked warming since 1977 was observed by Salinger et al. (2001), in the vicinity of the SPCZ between 180 and 170 W (between Rotuma and Alofi), which coincides with the area of increase in the 5 day index Extreme intensity. The extreme intensity is an indicator of the typical size of an extreme rainfall event: it is the average of the highest four rainfalls each year. Figure 5 (middle panel) shows trends in extreme intensity, which are again incoherent to the west of the dateline, and in the island groups of Fiji and the southern Cook Islands. Increasing trends are exhibited in the vicinity of the diagonal SPCZ near 170 W (e.g. Rotuma to Alofi), and to the north of the diagonal SPCZ east of 170 W. New Caledonia, Niue, Apia and Pukapuka show non-significant increasing trends in the extreme intensity index over the period. Significant increases in the index are exhibited at Penrhyn and Atuona, both with an increase of 10 mm per decade. A significant negative trend is seen at Nanumea, Rapa and Pitcairn (with decreases ranging between 6 and 10 mm). In a similar fashion to total rain, the largest trends in this index occur in the eastern Pacific Ocean, e.g. east of 160 W, with Nanumea being the exception Extreme frequency. The extreme frequency is a count of high rainfall events per year. The trends in the extreme frequency index show the same sign and spatial pattern as the trends in extreme intensity. Generally, a decrease in the extreme frequency index is observed south of the schematic diagonal SPCZ (Figure 5, lower

11 SOUTH PACIFIC EXTREME DAILY RAINFALL E 160 E 170 E W 160 W 150 W 140 W 130 W 170 E W 160 W 150 W 140 W 130 W 120 W 120 W Figure 5. Normalized trends in 5 day (upper panel), extreme intensity (middle panel) and extreme frequency (lower panel) over the period Circle size is proportional to the size of the normalized linear trend per decade. Black circles represent positive trends; white circles represent negative trends

12 858 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU panel), with an increase to the north of the diagonal SPCZ and in the vicinity of the SPCZ near 170 W. West of the dateline, trends are incoherent. In a similar fashion to total rain, significant trends in this index only occur in the eastern Pacific Ocean east of 160 W. Significant increases in the extreme frequency index are observed at Penrhyn and Atuona (1.5 days per decade and 1.2 days per decade respectively), whilst significant decreases are seen at Rapa and Pitcairn (0.5 days per decade and 0.8 days per decade respectively) Extreme proportion. The extreme proportion index measures how much of the total rain comes from extreme events: it is the proportion of annual rainfall that comes from the highest four rainfalls each year. Figure 6 shows trends in the extreme proportion index over the South Pacific over the period. The maximum trend observed is 1.5% per decade (Table II). Nevertheless, some of these trends are statistically significant, because the index shows very little interannual variability, and also may be of practical concern. For example, at Apia, Samoa, the top four rainfall events on average contribute approximately 15% of the total annual rainfall. The extreme proportion index has increased significantly in Samoa and Rarotonga by 1.0% and 1.5% per decade respectively, and decreased significantly at Rapa ( 0.7%) and Penrhyn ( 1.4%). Trends in the index are spatially coherent, with non-significant increases in New Caledonia, and incoherent (non-significant) trends otherwise in the region west of 180. Extreme proportion appears to have increased in the broad vicinity of the SPCZ, and reduced elsewhere, even at stations where total rainfall has decreased Relationships between extreme rainfall indices Significant correlation exists between total rain and all of the indices rain days, extreme intensity and extreme frequency (Table III), with significance adjusted for multiple testing (using the Bonferroni correction to consider simultaneous testing and the inflated risk of a type I error). These correlations (0.93, 0.71, and 0.93 respectively) imply that wetter years receive rain on more days, with higher extreme rainfall intensities, and more frequent extreme events. No significant correlation was found between total rain and 5 day, total rain and dry spell, ortotal rain and extreme proportion. The latter correlations were both negative, indicating that an increase in total rain would correspond to a decrease in dry spell length, and an increase in total rain would correspond to a decrease in the proportion of total rainfall that is produced in the wettest four events. Rain days are significantly correlatedwith extremefrequency (0.85), and this relationship implies an increase in rain days is associated with an increase in the frequency of extreme rainfalls. Significant correlation exists between extreme frequency and extreme intensity (0.85), indicating that an increase in extreme rainfall 0 0 Figure 6. Normalized trends in extreme proportion over the period Circle size is proportional to the size of the normalized linear trend per decade. Black circles represent positive trends; white circles represent negative trends

13 SOUTH PACIFIC EXTREME DAILY RAINFALL 859 Table III. Correlations between indices. Numbers in bold indicate tests that are significant at the 95% level, adjusted for simultaneous tests (Bonferroni correction) Total Rain days Dry spell 5 day Extreme intensity Extreme frequency Extreme proportion Total Rain days Dry spell day Extreme Intensity Extreme Frequency Extreme Proportion magnitude is likely to be linked to an increase in extreme rainfall frequency. This is intuitive, if the hypothesis that the distribution is shifted somewhat linearly is correct, with the shape parameter of a rainfall distribution remaining approximately stable. The 5 day index is significantly correlated to both the extreme frequency and extreme intensity indices, so that an increase of extreme 5 day rainfall totals is associated with an increase in extreme daily rainfall size and frequency. Both the dry spell index and the extreme proportion index are not significantly correlated with any other indices. PCA was performed on the group of seven rainfall indices, and two rotated components (factors) were found, which explain 81% of the total variance in the indices. These components are simply linear combinations of the indices and, when rotated, show two distinct groups of indices: one group consists of the dry spell and extreme proportion indices, and the other contains the remaining five indices. Cluster analysis also showed that the precipitation indices naturally fall into two groups, one consisting of dry spell and extreme proportion, and the other containing the remainder of the indices Orographic versus convective extreme precipitation An analysis of trends over the period for the seven extreme rainfall indices between atolls and islands showed that there were no significant differences between the two groups, performing a t-test of trends across all indices at all stations, with probabilities adjusted for simultaneous tests via the Bonferroni adjustment Changes in extreme rainfall indices over the 20th century 1978 was identified as a significant change point in the SPI series by the non-parametric Pettitt test (Pettitt, 1979) and 1947 were also identified as abrupt changes in the series, but were not significant at the 95% level. These change points are coincident with those of the IPO (Folland et al., 2002), confirming that the SPI index is strongly related to the polarity of the IPO. Significant change points identified by the Pettitt test in time series of six extended South Pacific daily rainfall records are listed in Table IV. It is clear that stations located in the central South Pacific, between 180 and 155 W exhibit a greater number of significant changes than elsewhere, and that the majority of abrupt changes in extreme rainfall indices occur in the late 1970s or early 1980s and are concurrent with a rapid northwards movement of the SPCZ. Significant change points for total rain and rain days were also identified around the mid 1940s at the two stations with longer, century-scale record (Alofi, Aitutaki), which also corresponds to a rapid movement of the SPCZ (as signalled by the SPI). Notably, all significant abrupt changes in the extreme intensity index occurred in the early 1980s, and in every case there was an increase in extremity following the change point, regardless of station location, and independent of the observed trend (or otherwise) following this climatic shift.

14 860 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU Table IV. Significant change points (95% level), identified by the non-parametric Pettitt test, for the extended extreme rainfall indices Daily rainfall record Total rain Rain days Frequency Intensity Proportion Alofi , 1977, , Aitutaki Funafuti Pukapuka Pitcairn Penrhyn Table V. Linear trends per decade for the sub-series either side of the statistical change points identified in Table IV. Trends that are significant at α = 0.05 are marked, trends that are significant at α = 0.10 are marked. Series that are stationary (trend is not statistically different to zero) are marked no trend Station Index Period Trend Statistical significance Alofi Total (mm) No trend No trend Decreasing No trend Rain days (days) No trend Decreasing No trend Extreme frequency (days) Decreasing Decreasing Extreme intensity (mm) Decreasing No trend Extreme proportion (%) Decreasing No trend Aitutaki Total (mm) No trend Decreasing Rain days (days) No trend Decreasing Extreme proportion (%) Decreasing No trend Pukapuka Extreme intensity (mm) Decreasing Decreasing Penrhyn Total (mm) No trend No trend Rain days (days) No trend No trend Extreme frequency (days) No trend No trend Extreme intensity (mm) No trend No trend

15 SOUTH PACIFIC EXTREME DAILY RAINFALL 861 Table V contains trend information for each index for which a statistical change point was identified, from the six extended daily rainfall records available for analysis. The series have been split into sub-series at each abrupt change, and the linear trend for each sub-series calculated and assessed for significance by the Mann Kendall τ test. The occurrence of a statistically significant trend in a sub-series is an indication of non-stationarity across that sub-period. At Penrhyn, every sub-series listed is stationary (with no linear trend) either side of the change point; there has been an abrupt change in all of the indices in Table V in the late 1970s or early 1980s, coincident with a major change in the SPI. Figure 7 (upper panel) shows the Penrhyn total rain series as an example of this. The linear trends either side of the change point (1976) are shown as solid lines and the linear trend is shown as a dashed line. The highly significant trend over the period is a feature of imposing a linear trend across an abrupt change, with the series homogeneous either side of the climatic shift. The Pukapuka extreme intensity series (Figure 7, lower panel) shows a similar pattern to Penrhyn, with a change point in the series around Significant, decreasing linear trends (Table V) occur within both sub-series, but are superimposed on a shift to a larger mean and variance at the change point. The increasing (non-significant) trend over the period (dashed line) is again a feature of imposing a linear trend across an abrupt change. Table V shows numerous abrupt changes for extreme indices at Alofi, Niue. All indices show a mixture of stationary sub-series (no significant trend) and sub-series with weakly significant to highly significant Figure 7. Linear trends fitted to sub-periods defined by statistical change points (thin solid line), compared with linear trends fitted to the set period (dashed line)

16 862 G. M. GRIFFITHS, M. J. SALINGER AND I. LELEU decreasing trends. Analysis of means and variances (not shown) indicate a higher variability prior to 1944, and post-1977, for the total rain, extreme intensity and extreme proportion indices at Alofi (both positive phases of the SPI). The extreme frequency index exhibits a decreasing trend over the entire record length (significant at the 90% level, not shown), whereas a non-significant increase is calculated over the period (Table II). This demonstrates both the value of analysis of longer series, such that longer trends may be apparent and not overshadowed by short-term cycles, and the need to assess abrupt changes in time series, which can be a valuable tool in understanding the processes that drive climate variability. Figure 8 (upper panel) shows the Alofi extreme intensity index, with both sub-series either side of the 1984 change point showing significant decreasing trends (solid line). The trend (dashed line) exhibits a non-significant increasing trend, again a feature of imposing a linear trend across an abrupt change. Table V shows Aitutaki abrupt changes for total rain, rain days and extreme proportion. All indices show a mixture of stationary sub-series (no significant trend) and sub-series with weakly significant to highly significant decreasing trends. Trends across the statistically defined sub-periods and the analysis period are the same in sign (all decreasing) for total rain and rain days (Figure 8, lower panel). However, for extreme proportion, the trend is weakly positive (but not statistically different to zero), whereas the sub-series trends are significantly negative prior to 1981 (the change point) and zero following. Figures 9 and 10 show normalized annual index data for Alofi and Pukapuka, in relation to annual SPI data. Local maxima in the positive phase of the SPI (1941, 1992) appear to be mimicked by Figure 8. Linear trends fitted to sub-periods defined by statistical change points (thin solid line), compared with linear trends fitted to the set period (dashed line)

17 SOUTH PACIFIC EXTREME DAILY RAINFALL 863 Figure 9. Upper panel: low-pass normalized Alofi total rain, Alofi rain days, and SPI (nine-point binomial filter). Lower panel: low-pass normalised Alofi extreme intensity, Alofi extreme frequency and Alofi extreme proportion, and SPI (nine-point binomial filter) the Alofi total rain and rain days indices, with local maxima in these two indices around 1940, and again around Also, the coherency between the three time series in Figure 9 (upper panel) appears strongest in the positive phases of the SPI. In Figure 9 (lower panel) the Alofi indices of extreme intensity, extreme frequency and extreme proportion also exhibit local maxima near those of the SPI in its positive phases (around the 1930s and in the 1980s), and these are, in fact, prior to each SPI maximum. For the Pukapuka indices in Figure 10, a weaker relationship is evident between total rain and rain days and the SPI. Local maxima for the extreme intensity, extreme frequency and extreme proportion indices are observed in the 1980s, again prior to the SPI peak in 1992, but are not evident for the SPI peak near A time series analysis on detrended, low-pass SPI and detrended, low-pass extreme precipitation indices at Alofi and Pukapuka was undertaken. The analysis confirmed a significant relationship only between the SPI and the extreme intensity index. The extreme intensity index at both Alofi and Pukapuka is significantly correlated to the SPI, leading the SPI by years at Alofi, and by 6 7 years at Pukapuka. These results are consistent with the precursor peaks between this index and the SPI, observed in Figures 9 and 10, and indicate that the relationships between other indices and the SPI are not significant.