a calibration of the lamb airflow classification model to predict past precipitation in wales

INTERNATIONAL JOURNAL OF CLIMATOLOGY, VOL. 17, 1397±1420 (1997)

A CALIBRATION OF THE LAMB AIRFLOW CLASSIFICATION MODELTO PREDICT PAST PRECIPITATION IN WALES

PETER BEAUMONT* AND KEVIN HAWKSWORTH

Department of Geography, University of Wales, Lampeter, Wales, UK

Received 28 November 1996Revised 26 April 1997

Accepted 30 April 1997

ABSTRACT

Daily precipitation data from 146 sites for the period 1982 to 1991 inclusive have been analysed in conjunction with the 27Lamb air¯ow types. An areal mean precipitation (AMP) series for Wales is constructed for the period 1861 to 1995 bysumming the mean daily AMP values associated with each Lamb air¯ow type. The results reveal that the use of coherentprecipitation regions together with seasonal AMP values are more likely to provide a better estimate of mean annualprecipitation than those combining a simple unweighted summation with non-seasonal values. The mean annual series forWales compares favourably with that provided by Wigley et al. and Woodley for England and Wales. Finally, the importanceof the major Lamb air¯ow types are considered in relation to periods of the record when dry and wet phases occur.Anticyclonic and cyclonic Lamb types are shown to be better predictors of mean annual precipitation than Lamb westerlies. Inpart, this re¯ects the fact that at the regional scale non-westerly Lamb air¯ow types can be embedded within a mobile westerlycirculation. These non-westerly air¯ow types often produce high precipitation totals over Wales. # 1997 by the RoyalMeteorological Society. # John Wiley & Sons, Ltd. Int. J. Climatol., Vol. 17, 1397±1420

(No of Figures: 9 No of Tables: 13 No. of References: 22)

KEY WORDS: Wales; Lamb air¯ow classi®cation; modelling; coherent precipitation regions; areal mean precipitation.

INTRODUCTION

For many years now it has been possible to analyse the weather types affecting the British Isles using the Lamb

air¯ow classi®cation (Lamb, 1972). Lamb considered that the categories he identi®ed were representative of an

area (50±60�N and 10�W±2�E), which included the whole of the British Isles. Since Lamb's original paper in

1972, a number of papers have appeared that have shown changes in the frequency of different Lamb types over

time, as well as associations with the spatial distribution of precipitation. For example, O'Hare and Sweeney

(1992), extending the work in Ireland by Sweeney (1985), revealed the declining frequency of Lamb westerlies

over the British Isles from the 1950s and the increased frequency of cyclonic and anticyclonic conditions.

Faulkner and Perry (1974) showed that the spatial distribution of precipitation over south Wales could be linked

to the Lamb air¯ow types and, therefore, future precipitation distributions would be strongly linked to changes in

these types. Similarly, Stone (1983a,b) has linked Lamb air¯ow types to precipitation distribution over central,

eastern and southern England. Briffa et al. (1990) applied principal components analysis to seasonal Lamb types,

identifying the importance of the balance between the major Lamb types (cyclonic, westerly and anticyclonic) in

determining the synoptic circulation over the British Isles. They suggest that signi®cant declines in westerlies

since the 1950s and the increase in anticyclonic and cyclonic days in recent decades are without precedent in the

120-year record (Briffa et al., 1990).

A more objective classi®cation of air¯ow types has been outlined by Jenkinson and Collison (1977). With

this approach, vorticity and resultant wind speed are used to classify cyclonic and anticyclonic days. The scheme

CCC 0899-8418/97/131397±24 $17.50

# 1997 by the Royal Meteorological Society

*Correspondence to: P. Beaumont, Department of Geography, University of Wales, Lampeter, Wales, UK. Email: [email protected]

has the advantage of a fourfold classi®cation of wind speed for every day analysed. Therefore, it reveals a

re®nement over the Lamb classi®cation by de®ning days when gales occurred for the period 1881±1977.

THE LAMB CLASSIFICATION INDEX

O'Hare and Sweeney (1992) provide an informative review of the strengths and weaknesses of the Lamb

classi®cation. Perhaps the most useful aspects of the classi®cation scheme are that it is easy to use, provides a

continuous record dating back to 1861, and introduces a dynamic element aiding synoptic interpretations.

Although the scheme is widely used to classify and describe weather conditions over the British Isles, a number

of problems can arise. In particular, because large variations in weather conditions often occur over the British

Isles during complex air¯ows, it is argued that regional air¯ow analysis is more appropriate, especially when

analysis is aimed at the regional scale (Mayes, 1991).

Synchronization problems may occur due to small sampling periods. With dynamic weather systems

mismatches may occur when a circulation pattern classi®ed at 1200 GMT does not adequately represent the 24-h

period. Complex synoptic patterns and the subjective nature of the scheme may prove problematical when

deciding upon the circulation type for a particular day. As a result, an unclassi®ed category was developed to

cope with this situation. Finally, Lamb's synoptic-scale approach may prove inappropriate for the study of meso-

and microscale processes. For example, a westerly air¯ow may prove to be relatively wet or dry dependent upon

whether frontal disturbances develop within it (O'Hare and Sweeney, 1992). To a certain extent Wilby et al.

(1995) have addressed this problem by incorporating a frontal subdivision of the Lamb classi®cation. This

re®nement recognizes that individual air¯ow types may be either wet or dry according to the proximity of low or

high pressure centres, thereby improving the ability of models to predict precipitation at the mesoscale. What this

present paper does is attempt to calibrate the Lamb classi®cation with areal mean precipitation (AMP) amounts

associated with each air¯ow type based on observed values at 146 stations for the period 1982±1991 in Wales and

the Welsh borderlands. The precipitation amounts associated with each Lamb type are summed on a daily basis to

produce an annual AMP for Wales. An AMP series is then calculated for the period 1861 to 1995 inclusive.

METHODS

In the ®rst instance Wales was treated as a single unit from the point of view of precipitation analysis. This

permits the combined analysis of all the relevant precipitation gauging stations in the Principality. For the study a

total of 146 stations were used which are distributed throughout Wales, including 11 stations in the Welsh borders

(Figure 1). Despite the dense network (1 gauge per 142 km2) and comparatively even distribution, notable gaps

occur around the Carmarthen District, the Welsh borderlands and in parts of Snowdonia. The inclusion of sites

across the border in England help to extend the overall coverage where gaps occur in the central part of the Welsh

borders. The gauges used in this study all possess a 100 per cent data record. This is because any missing data

were subjected to interpolation from nearby sites.

One of the questions that always has to be asked in a study of this nature is just how representative the

calibration period is compared with the historical sequence being investigated with regard to the different Lamb

air¯ow types. In the case of the calibration period 1982±1991, anticyclonic ¯ows accounted for 20�7 per cent of

the total (75�6 days per year), cyclonic ¯ows 16�29 per cent (59�5 days per year) and westerlies 15�01 per cent

(54�8 days per year) (Table I). Of all the other air¯ow types only south-westerlies accounted for more than 5 per

cent of the total. What is quite clear from this is that the major air¯ow types of anticyclonics, cyclonics and

westerlies dominate the yearly sequence and account for 72�7 per cent of all observed air¯ows during this period.

The ®rst part of the study consisted of calculating an unweighted areal mean precipitation (AMP) value for

each of the 27 Lamb air¯ow types for the period 1982 to 1991. The daily AMP values for each type were summed

to provide an annual value. The annual values were then assembled to form an AMP series for Wales for the

period 1861±1995:

AMP � 1

N � S

XN

i�1

XS

j�1

rij

1398 P. BEAUMONT AND K. HAWKSWORTH

INT. J. CLIMATOL, VOL. 17: 1397±1420 (1997) # 1997 Royal Meteorological Society

where rij is the total precipitation on day i at site j, N is the total number of days for that air¯ow and S is the total

number of gauges.

The values obtained varied from a maximum of 11�48 mm per day with the CSW (cyclonic south-westerly)

type to a minimum of 0�15 mm per day with ANE (anticyclonic north-easterly) air¯ows. Both of these conditions

it will be noted make up only a small proportion of the total observations. Of the air¯ow types with the largest

number of days the cyclonic type proved to be the wettest, with a daily value of 6�40 mm, and the anticyclonic

Table I. Frequency of Lamb types 1982-1991 and for the long-term average 1861-1980

Lamb air¯ow type Average annual numberof days 1982±1991

Percentage contribution1982±1991

Average annual numberof days 1861±1980

A 75�6 20�70 65�5ANE 4�4 1�20 5�1AE 5�5 1�51 9�2ASE 4�2 1�15 3�4AS 2�6 0�71 4�1ASW 6�1 1�67 2�9AW 15�2 4�16 17�2ANW 4�7 1�29 5�4AN 5�9 1�62 7�6NE 3�2 0�88 3�4E 13�2 3�61 12�9SE 9�6 2�63 6�1S 17�5 4�79 15�4SW 19�7 5�39 9�6W 54�8 15�01 68�5NW 10�0 2�74 13�9N 14�1 3�86 17�2C 59�5 16�29 46�5CNE 1�4 0�04 1�4CE 3�3 0�90 4�0CSE 1�7 0�47 1�7CS 2�8 0�77 4�6CSW 2�6 0�71 2�4CW 6�5 1�78 15�0CNW 1�9 0�52 3�3CN 3�1 0�85 5�0U 16�1 4�41 14�1

100

Table II. Seasonal variations in mean daily precipitation (mm) for selected Lamb air¯ow types 1982±1991 (Values inparentheses show the number of days for each category)

Air¯ow type January±March April±May July±September October±December Lowest as percentageof highest

Cyclonic 7�25 4�72 6�38 8�54 55�3(129) (191) (143) (132)

Westerly 6�12 3�17 3�68 5�85 51�8(170) (61) (157) (160)

Anticyclonic 0�60 0�34 0�42 0�48 56�8(156) (181) (224) (195)

Southerly 4�46 4�09 5�62 9�25 44�2(64) (29) (24) (84)

South-west 7�18 3�41 5�87 8�61 39�7(63) (20) (41) (73)

LAMB'S AIRFLOW CLASSIFICATION AND PAST PRECIPITATION 1399

# 1997 Royal Meteorological Society INT. J. CLIMATOL, VOL. 17: 1397±1420 (1997)

type the driest, with a daily value of 0�46 mm. Only nine of the Lamb types exhibited results of more than 5 mm

per day, and six recorded values of less than 1 mm per day (all of which were anticyclonic hybrids).

Despite the potential problems of using the Lamb classi®cation at the regional scale (Mayes, 1991), it was

felt that because Wales is not located on the periphery of the Lamb co-ordinate frame, the Lamb air¯ow types

were assumed to be consistent over Wales. However, it is recognized that under certain synoptic situations (e.g. a

very slow eastward-moving cold front) precipitation totals may be assigned to an inappropriate Lamb type. This

synchronization problem relates to the mismatch between de®ning Lamb air¯ow types at 1200 hours and

registering the precipitation catch for the observation period 0900 to 0900 hours. Because this paper is not

concerned with analysing the spatial distribution of precipitation, but instead temporal variations, problems of

regional changes in air¯ow become less important. Furthermore, Sumner (1996), when analysing the spatial

distribution of precipitation over Wales, found that the Lamb classi®cation was less likely to provide reliable

estimates of daily distributions than when using regional and more detailed synoptic classi®cations.

Two major criticisms of using Lamb air¯ow types for estimating past conditions have been put forward. The

®rst is that there are likely to be seasonal variations in the daily amount of precipitation associated with the

different air¯ow types that will be concealed by a single annual value. The second is that the daily amounts will

change over time associated with periodic variations in climate.

Seasonal variations can be tested for easily. Using the 10 year data set for the 146 stations in Wales, AMP

values were calculated for the ®ve major air¯ow types for each 3-month period (Table II). All ®ve air¯ow types

revealed a tendency for the autumn through to early spring (October±March) period to be wetter than the other

two 3-monthly divisions. This was particularly well marked with the Cyclonic, Westerly and South-westerly

air¯ows. In general, the minimum values varied from about 40 to 55 per cent of the maximum ®gures. It was also

noted that over the calibration period the three major air¯ow types demonstrated a degree of variation throughout

the year, with cyclonic activity at its peak in the spring and summer. Westerlies were very low during the spring

and anticyclonics reached a peak during the summer and autumn. Briffa et al. (1990) provide annual and seasonal

frequencies associated with each Lamb type for the period 1861 to 1980 (Table I). The seasonal differences

between the calibration period (1982±1991) and the long-term average (1861±1980) follow a similar pattern to

the annual differences. Most noticeably, anticyclonic and cyclonic types for the calibration period occur on

average on 10 and 13 days more per year respectively. In contrast, westerly days on average occur on 14 days less

per year. However, what is important is not the frequency of Lamb types but an adequate representation of the

areal mean for each of the Lamb types considered. To achieve this, therefore, two annual precipitation series were

calculated using the annual and seasonally adjusted AMP values to test for any signi®cant differences.

The problem of variations in average daily values for each air¯ow type over long periods of time is a more

dif®cult issue. The chief premise underpinning the current study is that each air¯ow type will produce a speci®c

amount of average precipitation whenever it occurs. Although the values that are utilized in this paper are

accurate for the period 1982 to 1991, it cannot be proved that similar values were associated with similar air¯ows

in, say, the 1860s. However, Sweeney and O'Hare (1992) showed that temporal variations in precipitation yield

for the same air¯ow were relatively minor. For example, approximately 90 per cent of the 20-year average yields

for the period 1881 to 1980 fell within � 10 per cent of the long-term mean. Anticyclonic yields were less

consistent, but precipitation amounts associated with this air¯ow type are very low.

In contrast, more recent work by Wilby et al. (1995) has shown that for a single station considerable

variations in mean daily precipitation for the three main air¯ow types, cyclonic, westerly and anticyclonic, can

occur. However, when considering only a single station a few rain-days with very high falls will disproportionally

change the mean value for a given air¯ow type. Also, little is known about site variations and the extent to which

these would cancel out speci®c ¯uctuations at a single site. In order to provide a de®nitive answer, enormous

daily data sets would be needed for each 10-year period over the time interval being considered. The further back

into the past the less likely are the data to be available. Even so, this is an important issue and clearly further

research is required to determine the extent and causes of this temporal instability in AMP yields (Conway et al.,

1996).

For the purpose of the present study, although the frequency of the different Lamb types for the period

1982±1991 are not necessarily representative of the long-term average from 1861 to 1995, it is assumed that the

AMP amounts for the air¯ow types are representative of conditions in the past. However, there are no detailed



research ®ndings to prove or disprove this assumption. A secondary implicit assumption is that the AMP values

adequately represent the differences that occur when the distinction is made between frontal and non-frontal

precipitation. Clearly, though, the absence or presence of large storms could lead to under- or overestimates for

that year. This is because the distributions of mean daily precipitation for all of the major air¯ow types are

strongly positively skewed. The result of this is that the mean daily value for a given air¯ow is often only a

fraction of the actual daily amount. For example, with cyclonic ¯ows although the mean daily value (non-

seasonal) is 6�40 mm, a maximum daily fall of 61�82 mm was recorded during the calibration period. Even with

the anticyclonic type a maximum daily value of 15�54 mm was noted, despite a mean daily value of only 0�46

mm. This higher value (15�54 mm) highlights the problem of mismatches, which can occur when dealing with

dynamic weather systems. Nevertheless, aggregation over such a large spatial and temporal scale is likely to

subsume such mesoscale processes and provide a reliable estimate of the AMP for that Lamb type.

Earlier work by one of the current authors has suggested that by the use of principal components (PCA) and

cluster analysis (CA) it is possible to divide Wales into eight homogeneous precipitation regions (Hawksworth,

1996) (Figure 1). Given this fact it was decided to prepare Lamb AMP curves for each of these regions to

discover if they revealed any signi®cant variations. The eight regions also provide a vehicle for calculating a

weighted AMP estimate based on the summation of the results from the individual regions. Because the regions

de®ned are coherent with respect to the spatial distribution of precipitation, the calculated AMP is likely to be a

more accurate representation of reality. Furthermore, the method adopted here affords a more statistically

rigorous and physically logical approach to calculating an areal mean total. By using the 27 Lamb air¯ow types,

both non-seasonal and seasonally adjusted (®ve most frequent Lamb types) AMP totals were produced.

Figure 1. Distribution of precipitation stations used for calibration purposes and homogeneous precipitation regions in Wales



NON-SEASONAL AND SEASONALLY ADJUSTED AMP VALUES 1861±1995

Wales non-seasonal

In the ®rst instance Lamb air¯ow type AMP values were used to represent the year as a whole. With this

approach no consideration was given to the fact that different Lamb air¯ow types may reveal signi®cant seasonal

variations in daily precipitation amounts. The results of this curve revealed a mean value over the period from

1861 to 1995 of 1280�20 mm (Figure 2; Appendix A). The maximum value recorded was 1675�85 mm in 1872

and the minimum 987�76 mm in 1973. The 10 driest years and the 10 wettest years are shown in Table III.

Figure 2. Modelled annual totals for AMP non-seasonal, AMP seasonal and AMP eight-region seasonal

Table III. Ten driest and wettest years derived from (a) modelled non-seasonally adjusted AMP series and (b) modelledseasonally adjusted AMP series 1861±1995

Non seasonalAMP

SeasonalAMP

Year Driest Year Wettest Year Driest Year Wettest

1973 987�76 1930 1440�27 1955 986�49 1994 1437�161955 1026�64 1960 1441�37 1973 994�87 1982 1441�841887 1058�85 1982 1441�76 1870 1043�55 1960 1454�291870 1068�29 1920 1455�82 1887 1055�13 1920 1467�941896 1086�41 1903 1487�07 1975 1081�82 1924 1486�291893 1090�69 1882 1522�35 1971 1102�08 1877 1507�351975 1095�98 1877 1524�04 1893 1103�86 1903 1512�911971 1108�21 1912 1536�45 1896 1104�88 1882 1537�501880 1135�50 1924 1546�84 1917 1105�74 1912 1540�771901 1136�82 1872 1675�85 1901 1118�80 1872 1675�77



Wales seasonal

As Table II demonstrates a marked seasonal contrast in Lamb type AMP values it was decided to produce an

AMP series for Wales based on seasonally adjusted data (Figure 2; Appendix A). The mean value for this curve

was 1270�65 mm. The maximum recorded value was 1675�78 mm in 1872 and the minimum 986�49 mm in 1955.

Although the mean value for the seasonally adjusted series is approximately 10 mm less than the non-seasonally

adjusted series it is noted that the extreme values are remarkably similar. When it was planned to calculate the

seasonal values it had been expected that this seasonally adjusted curve would produce the higher values owing to

the greater winter values more than compensating for the lower summer ®gures. In fact, this did not prove to be

the case.

The 10 driest and wettest years are shown in Table III. It should be noted that the order of the driest years

does show variation between the non-seasonal and seasonally adjusted series. With the seasonally adjusted data

1955 now becomes the driest year, with 1973 the second driest. It is seen that nine out of ten of the driest years

agree on both sequences. With the wettest years similar results are observed. The year 1872 remains the wettest in

both, but the order of the wettest years does change. Nevertheless, nine out of the ten years are similar in both

distributions.

When the two series are plotted the shapes are remarkably similar, with the peaks and troughs coinciding.

Indeed, the similarities are so great that it is very dif®cult to identify differences between the two curves when

shown graphically (Figure 2). A comparison of the differences between the two series on a yearly basis revealed

that the seasonally adjusted curve tended to produce lower values throughout the whole period of record (Figure

3). The reason for this is that the non-seasonal cyclonic AMP value appears to overestimate precipitation quite

considerably during the spring and summer when frequent numbers of cyclonic air¯ow types often occur. The

maximum difference between the two series was approaching 100 mm in 1984, but in general the vast majority of

the differences were less than 50 mm.

Figure 3. Annual differences in precipitation between the AMP non-seasonal and the AMP seasonal series



Results for homogeneous precipitation regions.

One of the problems with the above two approaches is that they are based on arithmetic mean values calculated

from 146 stations. As such they are neither weighted with respect to altitude nor to area. To overcome the areal

problem, Lamb AMP values were calculated for the eight regions mentioned earlier with seasonal values inserted

for the ®ve most frequent air¯ow types. The individual values for the different air¯ow types showed considerable

seasonal variations. For example, the westerlies had a daily minimum value (based on seasonal AMP values) of

1�66 mm in east Wales in April, May and June, and a daily maximum value of 9�68 mm in north Wales in

October, November and December (Table IV). This regional subdivision illustrates the importance of exposure

and shelter from the prevailing westerly winds in determining the spatial distribution of precipitation. Also,

seasonal variations in maritime westerlies are clearly important in determining the amount of precipitation over

Wales.

The results of the calculations for the eight regions are shown in Table V. Considerable variations in mean

values are noted, from a low of 803�42 mm for east Wales to a maximum of 1676�60 mm for north Wales. In

terms of the wettest year, 1872 provides the highest value in all of the regions. However, there are interesting

variations with the driest year. Five of the regions show 1955 to have received the least precipitation, but south,

south-east and south-west Wales show 1973 to be the driest year. This suggests some regional coherence to the

values.

Despite these differences it was interesting to note that the shape of the curves showed very little variation

between the different regions in terms of the main peaks and troughs (Figure 4). This is important with respect to

the question of scale, associated with the use of the Lamb classi®cation over small regions. As the shapes have

remained similar it can be reasonably assumed that the Lamb air¯ow types are spatially representative at this

scale, and are not suffering from any signi®cant problems with regard to regional variations. As a result only the

amplitude of the curve ¯uctuated with respect to the AMP value for the various regions, re¯ecting the importance

of exposure and shelter effects from the main rain-bearing winds. The fact remains, though, that the basic shape

of the curve is created by the dominance in almost all years of a selected few air¯ow types.

Table IV. Seasonal variations in westerly AMP values for the eight regions based on the calibration period 1982±1991

Region January±March April±June July±September October-December

Central 6�42 3�41 3�58 6�37North 9�44 4�99 5�42 9�68East 3�36 1�66 1�80 2�78North-east 3�10 2�05 1�83 2�99South 8�11 4�08 4�98 7�42South-east 4�86 2�01 2�93 4�22South-west 4�51 2�32 3�10 4�49North-west 5�74 3�53 3�65 6�01

Table V. Mean areal precipitation for the wettest and driest years by region based on the modelled AMP series 1861±1995

Region Mean annualvalue(mm)

Wettest year Precipitation forwettest year(mm)

Driest year Precipitation fordriest year(mm)

Central 1303�42 1872 1728�95 1955 996�04North 1676�60 1872 2188�96 1955 1272�61East 803�42 1872 1068�95 1955 625�05North-east 813�64 1872 1056�47 1955 654�09South 1641�15 1872 2192�66 1973 1248�16South-east 1061�87 1872 1430�81 1973 789�79South-west 1103�64 1872 1421�79 1973 864�30North-west 1222�17 1872 1563�92 1955 974�13



In order to calculate an AMP value for Wales from the eight regional values, a weighting system is needed

based on areal values. The total area of Wales covered by each region was calculated to provide an area

weighting factor by which the precipitation of each region could be multiplied before the eight AMP values were

summed to provide AMP totals for Wales (Table VI). The revised AMP value for Wales during the period 1861

to 1995 based on the eight-region seasonal model comes to 1288�79 mm (Figure 2; Appendix A). This is

approximately 18 mm more per year than that calculated for Wales using a seasonally adjusted arithmetic mean

for the 146 stations and 8 mm more than the non-seasonally adjusted total. This relatively small increase in the

overall mean suggests that the network of gauges is evenly distributed, with only a relatively small bias towards

lowland sites.

Figure 4. Modelled annual precipitation totals for the eight regions of Wales

Table VI. Areal mean precipitation (AMP) by region and the AMP for Wales obtained by the summation of the regionalvalues

Region Calculated AMP (mm)for each region

Per cent of area ofWales (eachregion)

Regional AMP (mm)contributions toAMP for Wales

Central 1303�42 9�51 123�98North 1676�60 16�23 272�13East 803�41 9�45 75�95North-east 813�64 9�57 77�88South 1641�15 23�07 378�58South-east 1061�87 11�30 119�95South-west 1103�64 12�43 137�14North-west 1222�17 8�44 103�18

AMPWales (Regional)

1288�79



For the eight-region seasonal model the wettest year is 1872, with 1698�04 mm, and the driest year is 1955,

with 999�36 mm (Table VII). When the order of the wettest and driest years are compared with the non-seasonal

and seasonal precipitation series it is noted that the eight-region seasonal model is identical to the seasonally

adjusted AMP series (Tables III and VII).

VALIDATION OF RESULTS

One of the greatest problems with this type of work, which is attempting to model conditions in the past, is how to

validate the results. Because the AMP series described in the present paper covers the whole of Wales, individual

precipitation stations with long records may not compare well with an areally weighted estimate. As a result other

tests have to be devised. Ideally, it is best if the predicted results are compared with areal values that have been

calculated for Wales based on actual precipitation data. However, the authors have not been able to discover any

published information for Wales covering the period from 1861 to 1995. Attempts were made to generate

precipitation records of Wales using British Rainfall and Monthly Weather Report data. However, the

inconsistency of the station records through time made this an unreliable approach.

Fortunately, there are two long-term precipitation series covering England and Wales. The ®rst was

published in a paper by Wigley et al., (1984) and provides monthly data for the period 1766 to 1980. This has

been extended subsequently to 1989 in two further papers (Wigley and Jones, 1987; Gregory et al., 1991). In the

second, Woodley (1996) has published an annual precipitation series for England and Wales for the period 1727

to 1992. Because the areal values were produced under the same air¯ow conditions as for Wales it seems

reasonable to compare the two series with the modelled data. It must be stated, though, that it is likely that the

inclusion of data from England and the different methods used in the estimation of areal means will affect any

correlation results (Figure 5).

To obtain a measure of the degree of correspondence between the modelled annual data for Wales and the

two England and Wales data sets regression analysis was used. In the ®rst place the two England and Wales series

were compared and were found to have an R2 value of 0�9767. This indicates a very high degree of correlation

between the two series. The next stage of analysis was to compare the three modelled data sets Ð AMP series

using non-seasonal data, AMP series using seasonally adjusted data, and AMP series based on the eight-region

seasonal model Ð with the two England and Wales series in terms of annual values (Table VIII).

The results indicate that the lowest R2 value obtained was 0�4642. This is surprisingly high value when it is

considered that the Wigley and Woodley data are dominated by English gauging stations. For example, during

frontal days this larger area may reveal regional differences in the Lamb air¯ow types when compared with those

for Wales. Comparisons with the Wigley series show that the non-seasonal data provide a lower value than for the

seasonally adjusted data. Perhaps somewhat surprisingly, there is little difference between the seasonally adjusted

AMP values and those for the eight-region seasonal model. A similar pattern is noted with the Woodley

Table VII. The 10 wettest and driest years derived from the 8-region seasonal model 1861±1995

Driest Year AMP (mm) Wettest Year AMP (mm)

1955 999�36 1994 1458�331973 1009�96 1982 1462�741870 1057�68 1960 1471�731887 1070�37 1920 1489�281975 1097�31 1924 1508�431971 1118�76 1877 1527�921893 1119�90 1903 1536�021896 1122�63 1882 1557�741917 1123�28 1912 1564�551901 1134�21 1872 1698�04



Figure 5. Modelled annual precipitation (AMP eight-region seasonal) compared with the Wigley et al. (1984) and Woodley (1996)precipitation series for England and Wales

Table VIII. Correlation analysis Ð R2 values for the three models compared with annual data from the Wigley (et al.) series(1861±1989) and Woodley series (1861±1992)

Wigley Woodley

WalesÐAMP non-seasonal 0�4872 0�4642WalesÐAMP seasonal 0�5064 0�4816WalesÐAMP eight-region seasonal 0�5037 0�4791

Table IX. Correlation values Ð R2 values for the monthly data of the three models compared with monthly data from theWigley (et al.) series (1861±1995)

Wigley (monthly values)

WalesÐAMP non-seasonal 0�5399WalesÐAMP seasonal 0�5564WalesÐeight-region AMP seasonal 0�5556



comparisons, although here the differences between the three modelled values are less pronounced. With both

comparisons, however, the best correlations are observed with the seasonally adjusted AMP series.

The three modelled AMP series for Wales were calculated in such a way that monthly estimates of

precipitation are also available. This has the advantage of permitting a comparison with the monthly values of the

Wigley data for England and Wales. In contrast, no monthly values are available for the Woodley data set. The

results provide surprisingly high correlations, which are greater than those observed for the annual values (Table

IX). Once again the seasonally adjusted values gave the highest R2 ®gures. However, as before, the more

sophisticated eight-region model did not provide a higher correlation result than the seasonally adjusted AMP

series.

One advantage of the availability of monthly ®gures is that it permits a comparison of the modelled values

with the Wigley data on a decade by decade basis (Table X). This allows us to determine whether the model can

predict certain decades more accurately than others. In general, the two seasonally adjusted series provide higher

correlations, with the values between the two data sets almost identical. Occasionally, the non-seasonal series

provides the highest correlation values for a particular decade (1911±1920 and 1921±1930). For all three

modelled data sets the highest R2 values were obtained for the period 1921±1930 and 1981±1989. The lowest

values were observed in 1871±1880 and 1971±1980. The high correlation values for the period 1981±1989 are to

be expected because this sequence overlaps with the calibration period for the model from 1982 to 1991.

The three modelled series all show strong similarities in terms of the graphical curves which they give rise

to. It was, therefore, decided to select one of them to compare temporally with the Wigley and Woodley records.

The Wales record generated by the eight-region seasonal model was chosen for this purpose.

At ®rst sight the modelled annual precipitation series for Wales (eight-region) shows considerable

correspondence with the Wigley and Woodley values, with many of the main peaks and troughs coinciding

(Figure 5). In all three cases, 1872 records the highest annual value. However, there are some signi®cant

variations. Perhaps the most obvious discrepancy is that the very dry conditions of 1921 in the Wigley and

Woodley series of England and Wales are not well represented in the modelled values for Wales. Similarly, the

two driest years of the modelled sequence for Wales, 1955 and 1973, are not particularly dry years in the Wigley

and Woodley records.

Data published in the Monthly Weather Reports indicate, for selected stations, the percentage of the long-

term precipitation average (1916±1951) that is accounted for by a particular annual value. For 1955 there are 14

values quoted for Wales, of which six are from north Wales and eight from south Wales. All 14 values are for 91

per cent or less than the long-term average. In north Wales it seems to have been a particularly dry year, with four

of the six values between 74 and 78 per cent of the long-term average. The degree of dryness is less pronounced

in south Wales, although even here, ®ve of the eight values are between 83 and 89 per cent of the long-term

Table X. Correlation analysis Ð R2 values for the eight-region seasonal model compared with Wigley (et al.) monthly data forindividual decades

Decade AMP non-seasonal AMP seasonal AMP eight-regionseasonal

1861±1870 0.5335 0.5968 0.59611871±1880 0�4992 0�4893 0�48891881±1890 0�4928 0�5185 0�51991891±1900 0�5950 0�5999 0�59941901±1910 0�4531 0�5015 0�49941911±1920 0�6131 0�5862 0�58581921±1930 0�6326 0�6281 0�62921931±1940 0�5458 0�5762 0�57491941±1950 0�5247 0�5316 0�53101951±1960 0�5321 0�5464 0�54651961±1970 0�4969 0�5450 0�54361971±1980 0�4841 0�4921 0�48981981±1989 0�6210 0�6557 0�6518



average. By 1973 there are 26 recording stations indicated, with nine in north Wales and 17 in south Wales. In

north Wales all nine stations reveal ®gures of between 88 and 94 per cent of the long-term average. This indicates

dryness, but not of a severe nature. In south Wales two of the stations record values in excess of 100 per cent (102

and 103), while six of the stations reveal ®gures of less than 70 per cent of the long-term average (65±69), and a

further ®ve stations record values in the 70 per cent range. These data show that the drought in parts of south

Wales was very pronounced in 1973. It is, therefore, encouraging to note that the modelled series of the three

south Wales regions (Figure 1) all indicate 1973 to be the driest year, whereas for the other regions 1955 is taken

to be the driest year (Table VI). These data do, therefore, indicate that both 1955 and 1973 were, in fact, dry years

in Wales, but that in each year the most intense dryness was concentrated in a particular area. In 1955 it was north

Wales that was driest, whereas in 1973 it was south Wales that recorded the lowest precipitation values.

When considering the spatial contrast in precipitation that exists between England and Wales for westerly

air¯ows, these and other anomalies may be understood. Glasspoole (1954) inferred that when westerly air¯ows

were at their peak in the ®rst half of the twentieth century, average annual precipitation in western districts

between the periods 1881±1915 and 1916±1950 increased by as much as 10 per cent. Therefore, during periods

when high frequencies of westerlies occur, Wales is likely to receive relatively more precipitation when

compared with England. As a result the eight-region seasonal model will tend to overestimate annual totals.

In contrast, a decline in westerlies since the 1950s may have led to a reduction in the west±east contrast in

precipitation (O'Hare and Sweeney, 1992). Indeed, O'Hare and Sweeney (1992) refer to the fact that summer

rainfall in parts of north-western Scotland and Wales was often less than 90 per cent of the 1916±1950 average. In

complete contrast, however, areas of central and southern England received totals in excess of 100 per cent of

their 1916±1950 average. In the light of this evidence, it is likely that Wales under these latter conditions will be

relatively drier. As a result the eight-region seasonal model will tend to underestimate annual totals. However, the

increase in cyclonic circulation that was observed from the late 1970s will have tended to enhance precipitation

totals over Wales relative to England (Figure 6). Additionally, Mayes (1996) has noted that for the periods 1941±

Figure 6. Nine-year running means of AMP eight-region seasonal model compared with the Wigley et al. (1984) and the Woodley (1996)precipitation for England and Wales



1970 and 1961±1990 there has been a shift in the frequency of westerlies from the summer to winter season. This

has been the result of enhanced baroclinicity across the North Atlantic (Namias, 1987). This is associated with the

recent increased latitudinal gradients of sea-surface and air temperatures between latitudes 30�N and 60�N(Mayes, 1996). Mayes also identi®es a cyclonic anomaly in spring since the mid-1970s over eastern England,

which has produced higher precipitation totals in April and May. To avoid generalizations it was decided to look

in detail at the differences between the two series and, in particular, focus attention on those years where the

largest discrepancies occurred.

A detailed analysis of 1921 shows that it was dominated by westerly air¯ows, which occurred on 97 days in

the year. Anticyclonic westerlies occurred on 33 days, almost twice the long-term average and cyclonic

westerlies on a further 12 days. In total, therefore, air¯ows with a westerly component occurred on 142 days.

Southerly ¯ows were also important, occurring on a further 22 days. Anticyclonic conditions were recorded on 85

days, but cyclonic conditions occurred on only 34 days. A correlation analysis between the eight-region monthly

model for Wales and the Wigley data set for 1921 reveals an R2 value of 0�7580. This is a particularly high ®gure

and indicates that the modelled high and low monthly values coincide well with those indicated by the Wigley

record in terms of the month of their occurrence. Absolute amounts, though, are very different. What seems likely

is that in 1921 in England and Wales the westerly air¯ows must have contributed much less precipitation than

normal to provide such a low annual total. This is somewhat surprising considering that the number of westerly

days in 1921 is so very high.

Another reason for the discrepancy between the very low annual total in 1921 for England and Wales and

the much higher value for Wales was that there was a north-west to south-east gradient in precipitation totals

during that year. An examination of available long-term precipitation records for Wales reveals that 1921 was a

very dry year in central and south-east Wales. Further west, although it was dry, it was not as dry as 1933. Finally,

to the north-west 1921 proved to be a year with generally average precipitation. Overall, the evidence would

seem to suggest that the further west and north travelled in Wales the less dry 1921 was. Therefore, the 1921

drought, which was so pronounced in England, was nothing like as well marked in west and north Wales.

However, it is interesting to note that the modelled precipitation series re¯ects this fact. Because anticyclonic

westerlies were frequent in 1921, the prominence of high pressure to the south would suppress much of the

precipitation activity in southern Britain. This may explain the marked difference between the modelled values

for Wales and the Wigley and Woodley data.

The two driest years in the modelled record for Wales are 1955 and 1973. In the Wigley and Woodley data

for England and Wales these two years are revealed to be dry, but not exceptionally so. The frequency of Lamb

air¯ow types for 1955 is considerably different from the long-term average. It is dominated by anticyclonic ¯ows,

which account for 83 days. Westerlies are registered on 52 days and cyclonic conditions on 31 days. However,

other anticyclonic hybrids account for a further 75 days in the year and have, of course, low average daily

precipitation amounts. Northerly and easterly air¯ows, which are also very dry for Wales, make up a further 49

days. Therefore, it is not surprising that it is modelled as a very dry year for Wales. In 1973, Lamb anticyclonics

account for 97 days, with a further 55 days occurring as anticyclonic hybrids. Westerly and cyclonic types

account for 50 and 36 days respectively. A further 57 days are made up of northerlies and north-westerlies, both

of which are dry in a Welsh context. The evidence here would seem to suggest that the balance of wind directions

in these two years is such that precipitation values over Wales would be expected to be very low when compared

with conditions in England.

This validation exercise has shown that there is a surprisingly good agreement between the modelled results

and the England and Wales precipitation series of both Wigley and Woodley. Indeed, a high degree of association

occurs down to the monthly level. This is extremely encouraging because it has to be remembered that the

modelled values for Wales are only covering a subset of the area making up the Wigley record.

So far in this section attention has been focused on annual or monthly values of precipitation. However, to

study periodic variations in the data other techniques have to be used. In an attempt to reduce the problem of data

`noise' a low-pass `®lter' using a moving average process was adopted for both the modelled and the Wigley and

Woodley data. This permitted the identi®cation of periods of wetness and dryness over the time interval being

considered and permitted a comparison between the different data sets. Moving averages with frequencies of 5, 9

and 13 years were calculated. Although there are differences between the three curves, the basic patterns remain



similar. The nine-year moving average was regarded as showing the variations most successfully, because

aggregation at this level demonstrated a suf®cient reduction in noise while not subsuming the presence of any

signals.

Interpretation of the 9-year running mean of the modelled annual values suggests below average

precipitation from the beginning of the record until the early 1870s (Figure 6). This was followed by above

average precipitation until the late 1880s and then below average until the early 1900s. From around 1900 until

the late 1930s above average conditions prevailed. Then from 1940 until the late 1970s a long period of below

average conditions were noted. Finally, from the late 1970s until the present day a period of above average

precipitation has prevailed. It is interesting to note that during the calibration period, 1982±1991, Lamb SW

air¯ows were twice the long-term average values for the period 1861±1980 (Table I). As Wales is particularly

exposed to south-west winds it should not be surprising that precipitation totals increased at this time. The general

pattern of the modelled series for Wales coincides well with the results for the Wigley and Woodley results. The

major peaks and troughs correspond well, although there are differences in amplitude between the modelled and

actual precipitation series. For example, the wettest phase with the England and Wales curves is in the late 1870s

and early 1880s, whereas with the modelled curve for Wales it is in the 1920s. The driest conditions in England

and Wales occurred in the 1890s and the early 1900s, whereas for Wales it is the 1970s. Notwithstanding these

differences, it would seem reasonable to conclude that the modelled series for Wales is identifying a similar

signal to that observed with the Wigley and Woodley series. Even greater similarities are seen when the 9-year

running means are calculated as dimensionless curves ¯uctuating around the mean value for each of the

sequences. Under such conditions the correspondence between the three series becomes even more pronounced

(Figure 7). As such, it provides further evidence for the validity of the method used.

Figure 7. Nine-year running means of AMP eight-region seasonal model compared with the Wigley et al. (1984) and the Woodley (1996)precipitation for England and Wales using dimensionless data centred around the mean values



LAMB AIRFLOW TYPES

The driving force behind the method applied above is the frequency of the different Lamb air¯ow types. In a

study of this type it is, therefore, important to examine the changing frequencies of the major types over the

period of record. Curves for the three major types of westerlies, cyclonic and anticyclonic conditions reveal very

large variations from year to year. To reduce the `noise' associated with these distributions the yearly values were

summed to produce 9-year moving averages. This permitted the identi®cation of any trends (Figure 8).

There seems to have been a slight decline in the frequency of westerlies from the late 1860s until around

1880. Following this, there is a steady increase until peak values of about 85 days per year are registered in the

early 1920s. Thereafter, there is a steady decline to around 1950, when another peak is reached, before continuing

to decline to minimum values of around 50 days per year in the late 1970s and early 1980s. From 1985 to the end

of the record a slight increase in Lamb westerlies is registered.

Cyclonic air¯ows reveal a peak in the mid-1870s of around 55 days per year. Between 1880 and 1910

annual values in the low 40s were the norm, rising to the high 40s for the period from 1910 to 1940. From 1940

there has been a general, but not uniform, rise, to a maximum of over 60 days per year in the mid-1980s.

Thereafter, a slight decrease is registered.

Low frequencies of anticyclonic air¯ows occur between 1875 and 1880, between 1920 and 1925, and around

1965. The highest values were from 1895 to 1990, from 1935 to 1945, from 1970 to 1975, and from 1985 to the

end of the period of record. With this latest peak, anticyclonic air¯ows averaged around 75 days per year.

The modelled precipitation series based on the seasonally adjusted data derived from the eight regions is

considered to be the most consistent because it uses both seasonal variations and areal weightings. The results

from it are, therefore, used in the calculations that follow in this section. A sorting of this precipitation series

permits the establishment of an AMP series from the wettest to the driest years. This sorted sequence can then be

correlated with the Lamb air¯ow types for individual years to discover if any patterns exist (Figure 9). For the

Figure 8. Nine-year running means for the major Lamb types 1861±1995



anticyclonic type the highest values of around 90 days per annum are associated with the predicted driest years,

whereas at the other extreme the wettest years record values of 60 days or less. For the cyclonic types the driest

conditions occur, on average, 40 days per annum and the wettest around 60 days. For the westerlies a similar

trend was observed, with the driest years revealing under 60 days per annum and the wettest in excess of 70 days.

However, what becomes obvious is that each of the air¯ow types reveal marked variations when plotted

against the sorted precipitation series. When the data were subjected to regression analysis it was found that the

anticyclonic type provided the best ®t with an R2 value of 0�4710. In contrast, the westerlies revealed a very low

R2 value of only 0�1454. The cyclonic type was between the other two results with a R2 value of 0�2990. These

results show that the best single indicator for AMP totals are anticyclonic air¯ows. Somewhat surprisingly, at

Figure 9. Frequency of major Lamb types plotted against increasing annual precipitation values.



least from the expectations of the authors, the frequency of Lamb westerlies was shown to be a very poor

indicator of AMP totals.

This analysis of the frequency of the different Lamb air¯ow types has so far been con®ned to the modelled

AMP values. However, given the fact that the Lamb air¯ow classi®cation covers the whole of the British Isles, it

is possible to utilize the Woodley annual precipitation series (chosen because of its slightly longer record) as a

check on the results of the modelled values. The results so produced are remarkably similar to those discussed

above. The annual frequency of westerly days when correlated with annual precipitation produces an R2 value of

only 0�0022. For cyclonic air¯ows it rises to 0�3558 and for anticyclonic air¯ows to 0�3969. This seems to

indicate beyond doubt that Lamb westerlies taken on their own are a very poor indicator of what the annual

precipitation total is likely to be. Initially, this would seem to be a surprising result because the westerlies are

often considered to be the most signi®cant air¯ow affecting the British Isles. Instead, it seems that the presence of

a mobile maritime westerly regime during wetter phases is important in allowing an increased frequency of

rigorous depressions to track east over the UK, as witnessed by the dominance of cyclonic types during these

periods.

In contrast, anticyclonic air¯ows appear to be a reasonable indicator of annual precipitation totals in both the

modelled and Woodley data series. This would seem to indicate that it is the suppression of precipitation, as

witnessed by anticyclonic blocking episodes, that is the controlling factor in understanding annual precipitation

totals over England and Wales. Moreover, the ®ndings in this paper reinforce those of Jones et al., (1993), who

highlighted signi®cant relationships between Lamb anticyclonic and cyclonic weather types and the long-term

England and Wales precipitation series.

This analysis has also shown that the three main air¯ow types cannot be studied in isolation of the other

air¯ows. It is, therefore, important to try to obtain an indication of the air¯ow types associated with extreme

Table XI. Average Lamb air¯ow types for dry and wet years (average of 10) for eight-region seasonal model

Air¯ow type Average number ofdays on driest year

Average number ofdays on wettest year

Unclassi®ed 14�4 16�0A 88�3 46�5ANE 5�4 3�0AE 9�3 4�7ASE 4�4 3�8AS 4�0 2�5ASW 4�0 4�4AW 22�5 16�2ANW 7�4 3�7AN 9�9 6�2NE 4�2 3�2E 8�7 11�6SE 5�0 8�4S 11�4 20�3SW 7�6 16�9W 52�2 71�2NW 14�4 11�0N 19�2 12�2C 40�5 61�8CNE 1�8 1�5CE 2�4 5�8CSE 0�7 2�3CS 3�4 6�1CSW 1�7 4�2CW 12�9 15�7CNW 3�8 3�3CN 5�7 3�0



conditions as witnessed by the 10 driest and wettest years predicted by the model. Therefore, the air¯ow types for

the 10 wettest and driest years were averaged to provide a general view of these two extreme conditions (Table

XI). With the driest years the dominant feature is the number of anticyclonic days, which number 88�3. With the

wettest years this ®gure has dropped to only 46�5. What is perhaps even more interesting is that if all anticyclonic

hybrids are included they total 155�2 days in the driest years, but only 91 days in the wettest years. In both wet

and dry years the cyclonic and westerly types continue to appear in the top three categories, but as would have

been predicted from the earlier results, the variations between the extreme conditions are not as great as with the

anticyclonic ¯ows. Both westerlies and cyclonic conditions increase with increasing precipitation totals. Of the

minor air¯ow types it can be seen that marked increases in southerlies and south-westerlies are characteristic of

wet conditions. On the other hand, increased northerlies and north-westerlies seem indicative of dry conditions.

Furthermore, during these dry phases the increased prominence of high pressure to the west (Azores High) or to

the east (near continent) will promote many of the anticyclonic hybrids.

As there are variations between the modelled results for Wales and those for England and Wales it is

interesting to assess the air¯ow types that have given rise to the driest and wettest years as revealed by the

Woodley and Wigley data sets. It is important to note that both the English and Welsh data sets agree as to which

are the 10 driest and wettest years, although it can be seen that the actual orders change slightly (Table XII).

Using these data from the 10 wettest and 10 driest years it is possible to produce the average Lamb air¯ow types

for wet and dry conditions derived from the England and Wales data of Wigley and Woodley. These results are

shown in Table XIII

The results when compared with the values from the modelled data for Wales are very similar. For the driest

years the Wigley±Woodley series for England and Wales reveals a higher number of westerlies, and fewer

cyclonics, but otherwise few differences are noted. With the wettest years the similarities are even closer. This

strongly suggests that the modelled values for Wales are predicting closely the conditions that have produced

recorded dryness or wetness in England and Wales. This is extremely encouraging and adds further credence to

the validity of the results of the model.

The calibration period used in this study, 1982±1991, reveals that of the three main air¯ow types (W, C and

A), both westerly and anticyclonic types represent conditions associated with drier phases, registering on average

55 and 76 days per year respectively. Conversely, the cyclonic type average 60 days, which is very close to

conditions experienced under wet phases. In relation to the 9-year moving average AMP curve, the 1980s are

classed as being above the long-term average. Therefore, the present increase in cyclonic activity is to a certain

extent compensating for the decline in westerlies and increase in anticyclonic types.

Table XII. The 10 driest and wettest years in the Wigley (et al�) and Woodley series for England and Wales 1861±1989

Wigley Woodley

Driestyear

Annual value(mm)

Wettestyear

Annual value(mm)

Driestyear

Annual value(mm)

Wettestyear

Annual value(mm)

1921 629�1 1872 1284�9 1921 609 1872 12521887 669�3 1960 1190�4 1887 643 1960 11661864 703�4 1903 1180�2 1864 664 1903 11151933 719�4 1882 1146�2 1933 707 1882 11031964 731�9 1877 1144�1 1870 713 1877 11021870 733�l 1927 1108�1 1964 714 1912 10871973 743�3 1954 1099�9 1893 720 1951 10791953 747�1 1912 1098�7 1973 724 1927 10701893 756�3 1924 1082�7 1902 731 1954 10551902 757�5 1951 1068�4 1953 736 1924 1046



CONCLUSIONS

This paper has shown that it is possible to devise and calibrate a model that is capable of predicting past annual

precipitation totals for Wales on the basis of AMP values for the Lamb air¯ow types. The results obtained reveal

good correlations with the series for England and Wales published by Wigley et al. (1984) and Woodley (1996).

Of the three modelled curves that were produced for Wales it was found that the two which took account of

seasonal variations in precipitation amounts provided the highest correlation when compared with the England

and Wales series. The curve based on the summation of precipitation for eight coherent precipitation regions in

Wales did not provide a higher correlation value. This was surprising, but is also encouraging, because it suggests

that the distribution of the 146 stations which were used for calibration provide a good representation of the

spatial distribution of precipitation within the Principality. However, when networks are distributed unevenly, as

they often are, it is recommended that coherent precipitation regions are adopted. This will provide a physically

logical approach when estimating areal mean precipitation totals.

Analysis of both the modelled and the England and Wales series reveal that wet years and dry years are

characterized by similar patterns of Lamb air¯ow types. It was discovered that the frequency of Lamb westerly

air¯ow types revealed no strong correlation with annual precipitation totals with either the modelled Wales data

or the England and Wales series. The point should be made that a variety of non-westerly Lamb types, such as

Lamb cyclonics and selected hybrids Ð CSE, CS, CSW and CW Ð are not incompatible with a strong westerly

circulation and, therefore, with high precipitation totals in Wales. Instead, it is the presence of mobile maritime

Table XIII. Average Lamb air¯ow types for driest and wettest years (average of 10) based on Wigley (et al.) and Woodleydata 1861±1989

Air¯ow type Average number ofdays in driest year

Average number ofdays in wettest year

Unclassi®ed 12�6 18�6A 85 43�8ANE 6�1 2�9AE 8�8 7�1ASE 4�2 2�8AS 3�9 2�7ASW 2�5 2�8AW 17�6 14�8ANW 5�8 3�9AN 8�7 6�4NE 1�8 3�3E 13�3 10�7SE 6�4 7�6S 14�7 17�1SW 7�4 14�4W 67�5 73�2NW 14�1 13N 19 16�1C 35�3 62�1CNE 1�1 1�4CE 2�7 6�2CSE 1�6 2�5CS 2�7 6�7CSW 2�2 4CW 14�2 17�9CNW 2�9 4�5CN 3�1 4�3



westerly situations that leads to an increase in the frequency of Lamb cyclonic and its hybrids (CSE, CS, CSW

and CW), which often lead to these wetter phases. Equally, it would be interesting, in terms of future research, to

repeat the analysis outlined in this paper for different calibration periods, in order to discover the effects of AMP

variations on the modelled precipitation series.

A further attraction of this calibrated model is that it is possible to put together any sequence of air¯ow types

in an attempt to see what conditions are likely to be in the future. As such the approach should prove to be a

valuable tool for the water industry in Wales when attempting to adjust to the potentially dif®cult conditions

associated with future changes in the climate over Wales.

ACKNOWLEDGEMENTS

The authors would like to acknowledge the original work of Professor Lamb that created the air¯ow classi®cation

and to thank Dr Mike Hulme, Climatic Research Unit, University of East Anglia for supplying a digital output of

the Lamb air¯ow classi®cation for the period 1861 to 1995.

The authors would also like to thank Dr Graham Sumner for allowing permission to use daily precipitation

data for Wales, which was obtained from a grant awarded by the Leverhulme Trust.

REFERENCES

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Conway, D., Wilby, R. L. and Jones, P. D. 1996. `Precipitation and air ¯ow indices over the British Isles', Climate Res.. 7, 169±183.Faulkner, R. and Perry, A. H. 1974. À synoptic precipitation climatology of South Wales', Cambria, 1, 127±138.Glasspoole, J. 1954. `New climatological averages for Great Britain', Meteorol. Mag., 83, 44±48.Gregory, J. M., Jones, P. D. and Wigley, T. M. L. 1991. `Precipitation in Britain: an analysis of area±average data updated to 1989', Int. J.

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200±205.Sumner, G. N. 1996. `Daily precipitation patterns over Wales: towards a detailed precipitation climatology', Trans. Inst. Geogr., 21, 157±176.Sweeney, J. C. 1985. `The changing synoptic origins of Irish precipitation', Trans. Inst. Br. Geogr., 10, 467±480.Sweeney, J. C. and O'Hare, G. P. 1992. `Geographical variations in precipitation yields and circulation types in Britain and Ireland', Trans.

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APPENDIX A

Annual precipitation values for the three modelled scenarios 1861±1995

Year AMP non-seasonal AMP seasonal AMP eight-region seasonal(mm) (mm) (mm)

1861 1304�6 1303�1 1321�81862 1358�9 1290�1 1308�61863 1351�2 1343�0 1364�01864 1274�1 1225�4 1241�51865 1148�0 1147�9 1162�91866 1375�8 1374�5 1394�21867 1243�5 1213�2 1228�71868 1173�6 1221�5 1240�21869 1140�0 1141�0 1155�91870 1068�3 1043�5 1057�71871 1267�1 1236�9 1254�31872 1675�9 1675�8 1698�01873 1277�6 1249�4 1268�01874 1196�2 1167�7 1187�51875 1207�7 1173�3 1189�71876 1378�9 1405�3 1421�51877 1524�0 1507�3 1527�91878 1245�9 1226�5 1242�21879 1291�4 1215�1 1230�41880 1135�5 1130�5 1146�71881 1367�5 1358�5 1376�61882 1522�4 1537�5 1557�71883 1287�2 1257�7 1278�31884 1368�3 1347�2 1366�61885 1218�6 1198�9 1215�31886 1319�1 1310�5 1327�41887 1058�8 1055�1 1070�41888 1279�2 1288�8 1305�61889 1224�1 1210�2 1227�81890 1330�5 1280�8 1297�91891 1330�8 1347�6 1367�11892 1202�7 1176�7 1192�41893 1090�7 1103�9 1119�91894 1289�9 1299�8 1318�61895 1179�5 1176�5 1193�31896 1086�4 1104�9 1122�61897 1306�0 1281�4 1298�11898 1213�3 1198�0 1216�51899 1191�5 1167�9 1184�31900 1310�3 1342�9 1362�81901 1136�8 1118�8 1134�21902 1231�1 1217�6 1235�31903 1487�1 1512�9 1536�01904 1305�6 1234�9 1254�71905 1293�2 1294�2 1313�81906 1244�8 1256�5 1276�61907 1355�0 1364�9 1383�21908 1239�4 1240�0 1259�01909 1155�9 1129�5 1145�51910 1320�2 1320�1 1337�11911 1195�9 1223�9 1240�31912 1536�5 1540�8 1564�5




1913 1435.4 1422.4 1441.91914 1265.7 1286.7 1306.41915 1203.0 1229.1 1244.71916 1353.5 1405.4 1424.01917 1154.2 1105.7 1123.31918 1358.6 1364.5 1387.61919 1156.6 1138.2 1154.11920 1455.8 1467.9 1489.31921 1213.6 1259.7 1279.71922 1309.6 1270.6 1289.01923 1395.5 1362.9 1383.81924 1546.8 1486.3 1508.41925 1265.1 1251.4 1268.71926 1365.0 1332.6 1352.21927 1428.7 1422.6 1442.61928 1386.3 1398.3 1418.51929 1275.0 1273.2 1292.41930 1440.3 1427.7 1451.41931 1240.1 1232.2 1249.21932 1336.8 1315.3 1334.31933 1173.7 1124.5 1140.11934 1315.0 1313.4 1333.01935 1402.2 1412.2 1431.41936 1327.0 1326.5 1346.41937 1259.4 1207.9 1226.01938 1344.2 1371.3 1393.71939 1236.3 1251.8 1268.21940 1239.2 1226.6 1244.91941 1154.3 1143.1 1157.31942 1188.4 1149.1 1168.11943 1320.0 1295.0 1314.51944 1145.7 1128.2 1147.01945 1208.6 1186.3 1202.31946 1354.4 1315.9 1334.91947 1247.5 1183.6 1199.21948 1375.0 1369.4 1389.61919 1155.2 1172.6 1190.91950 1428.2 1396.6 1418.31951 1394.0 1389.5 1407.61952 1137.8 1120.0 1137.71953 1173.4 1155.5 1173.91954 1381.7 1380.3 1401.31955 1026.6 986.5 999.41956 1164.0 1146.3 1163.21957 1180.6 1172.6 1192.61958 1390.2 1348.0 1366.71959 1181.3 1209.2 1227.41960 1441.4 1454.3 1471.71961 1259.7 1213.0 1230.71962 1153.1 1131.7 1148.31963 1312.3 1278.9 1295.81964 1248.8 1171.5 1189.51965 1270.7 1249.0 1267.11966 1328.5 1289.1 1307.61967 1343.3 1308.2 1329.21968 1213.6 1239.4 1255.1

(ocontinued)




1969 1210.7 1198.8 1213.41970 1261.9 1235.8 1253.51971 1108.2 1102.1 1118.81972 1306.3 1252.3 1270.31973 987.8 994.9 1010.01974 1356.6 1354.2 1374.71975 1096.0 1081.8 1097.31976 1176.9 1196.1 1212.21977 1254.1 1280.6 1296.41978 1281.6 1308.1 1324.41979 1370.7 1388.2 1405.41980 1350.8 1371.8 1390.11981 1228.2 1203.5 1220.11982 1441.8 1441.8 1462.71983 1265.0 1273.9 1292.11984 1253.9 1351.6 1369.01985 1316.6 1289.7 1304.91986 1421.9 1426.4 1447.81987 1231.3 1221.7 1237.01988 1318.8 1305.4 1321.71989 1254.3 1245.1 1262.91990 1365.1 1356.5 1377.21991 1260.2 1223.9 1240.51992 1396.8 1396.8 1416.11993 1272.7 1271.2 1289.21994 1432.0 1437.2 1458.31995 1229.8 1269.1 1286.2



a calibration of the lamb airflow classification model to predict past precipitation in wales

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