Development and application of topographic ... - Wiley Online Library

ATMOSPHERIC SCIENCE LETTERS Atmos. Sci. Let. 10: 177–184 (2009) Published online 15 July 2009 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/asl.228

Development and application of topographic descriptors for conditional analysis of rainfall Emma Jayne Sakamoto Ferranti,1 * James Duncan Whyatt1 and Roger James Timmis2 1 Lancaster Environment Centre, Lancaster University, Lancaster LA1 2 Environment Agency, Lancaster University, Lancaster LA1 4YQ, UK

*Correspondence to: Emma Jayne Sakamoto Ferranti, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK. E-mail: [email protected]

Received: 23 January 2009 Revised: 6 May 2009 Accepted: 6 May 2009

4YQ, UK

Abstract Upland rainfall is changing but regional climate models (RCMs) are poor at simulating observed precipitation in such areas of complex topography. This paper presents a method of examining observed rainfall patterns and processes under different conditions of synoptic meteorology and local topography. Objective topographic descriptors are defined and used to distinguish the modification of rainfall by local topography from that due to different synoptic conditions and climate change. A case study examining winter rainfall in Cumbria is presented. The conditional analysis method can be used to test RCM outputs so that model parameterisation can be improved. Copyright  2009 Royal Meteorological Society Keywords:

GIS; rainshadow; uplands; Cumbria; climate change

1. Introduction The seasonality and characteristics of rainfall across the United Kingdom are altering as a result of climate change (Jenkins et al., 2007). The amount and intensity of rainfall is generally decreasing in summer but increasing in winter, particularly in northern and western areas (Osborn et al., 2000; Maraun et al., 2008). Recent analyses suggest that the greatest changes in winter rainfall are occuring in upland regions and adjacent rainshadow zones (Malby et al., 2007). Understanding spatial and temporal changes in rainfall in such regions is important for the future management of water resources and ecosystems (Fowler et al., 2007; Orr et al., 2008). The current generation of regional climate models (RCMs) simulate observed precipitation poorly in such areas of complex topography (Fowler et al., 2005), casting doubt over future projections. Furthermore, the mechanisms controlling rainfall processes in leeside (rainshadow) zones are poorly understood (Roe, 2005). This paper presents a novel approach to analysing rainfall patterns and processes under a changing climate. A database of meteorological and topographical parameters was compiled for Cumbria, northwest England, to enable analysis of rainfall under different conditions. Cumbria was selected as an example of a topographically diverse mid-latitude region that has a predominately maritime and westerly defined climate. The region has a dense network of rain gauges and the database contains monthly, daily and sub-daily rainfall records from more than 400 stations operational for a period between 1900 and present day (MIDAS Land Surface Observation Copyright  2009 Royal Meteorological Society

Stations Data, 2008) (Figure 1). Other local meteorological observations such as temperature, wind speed and wind direction are included, together with Lamb–Jenkinson Weather Types (LJWTs) that provide a daily snapshot of air mass origins and the synoptic weather conditions over the British Isles (Jones et al., 1993). Although previous studies have produced precipitation maps and climatologies from standard observations (Frei and Schar, 1998; Perry and Hollis, 2005), none have used a conditional analysis approach to investigate how rainfall has varied under different synoptic situations and in different geographic settings in the context of a changing climate. Upland rainfall depends not only on the synoptic weather situation and cloud microphysics but also on the interaction of atmospheric flow with terrain (Sawyer, 1956). Many authors have studied how rainfall amount and intensity change with elevation (e.g. Hill et al., 1981; Gray and Seed, 2000) and how this basic relationship with elevation is modified by local geographic location; for example valleys in upland regions frequently record rainfall amounts uncharacteristic of their elevation (Salter, 1918), and rainfall amounts are also affected by the distance to sea (Hobbs et al., 1975). Identifying the rainshadow zone with respect to air flow is essential as these zones are characterised by a reduction in rainfall amount and duration relative to windward slopes (Atkinson, 1983; Hill, 1983). To investigate how the relationship between rainfall and terrain may have altered under a changing climate, a set of topographic descriptors is being developed using Geographic Information System (GIS) techniques. The descriptors characterise the landscape

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E. J. S. Ferranti, J. D. Whyatt and R. J. Timmis

Figure 1. The location of rain gauges operating in Cumbria for periods between 1900 and 2007.

configuration (e.g. elevation, slope, distance to sea) in order to identify and subsequently ‘type’ weather stations into similar geographic settings. Previous studies have used GIS techniques to develop similar topographic descriptors (e.g. Marqu´ınez et al., 2003; Ninyerola et al., 2007), but none have used descriptors to investigate orographic processes in conditioned synoptic situations or in the context of climate change. This paper presents a set of candidate topographic descriptors developed using GIS techniques and shows how they may be used to define five geographical settings into which stations may be grouped: coastal, windward-lowland, windward-upland, leeward-upland, and leeward-lowland. An example of how conditional analysis by synoptic situation and geographic setting may be used to investigate changing rainfall trends is presented for the case of winter rainfall associated with southwesterly (SW) air flow in Cumbria. Finally, the possible directions of future research are summarised.

2. Defining topographic descriptors A set of topographic descriptors that objectively define different characteristics of the terrain around each Cumbrian weather station are being developed. These descriptors allow the modification of Copyright  2009 Royal Meteorological Society

rainfall by local topography to be distinguished within the wider dependence of rainfall on weather type, temperature, wind speed/direction, and climate change. Understanding how the relationship between rainfall and different geographical settings varies will provide greater insight into the mechanisms controlling rainfall in areas of complex topography, and how these may be effected by a changing climate. A better understanding of the interaction between terrain and rainfall will help inform parameterisation and testing of RCMs, and ultimately lead to better simulation of rainfall in such areas. Several candidate topographic descriptors are being developed using ArcGIS (Figure 2). These fall broadly into two categories: (i) areal descriptors that are station centred and derived from the terrain within a given zone around a weather station and (ii) linear descriptors that are station terminating and characterise the terrain over which the precipitating air masses have travelled from open water. Areal and linear descriptors can be further subdivided into descriptors that take account of the direction of air flow and those independent of direction. Selected topographic descriptors include the following. Station elevation: The elevation of the station as derived from 50 m resolution Ordnance Survey digital Atmos. Sci. Let. 10: 177–184 (2009) DOI: 10.1002/asl

Development and application of topographic descriptors

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linear descriptor relates to air flow direction and gives the distance to the marine moisture source for SW originating air masses. This metric could be computed for any compass bearing. Cumulative vertical motion (SW): The cumulative change in elevation along a SW trajectory summed from the smoothed coastline to a station in order to estimate the orographic processing of an air parcel prior to arrival at the station. This descriptor is linear and relates to air flow direction (Figure 2(c)).

3. Defining geographic settings

Figure 2. Schematics showing the different topographic descriptors: (a) station elevation, zonal mean elevation and zonal maximum elevation; (b) distance to coast, distance to west coast and distance to southwest coast; and (c) cumulative vertical motion along an SW trajectory.

terrain data. This areal descriptor is independent of air mass origin. Zonal mean elevation and zonal maximum elevation: The mean and maximum elevation within a 1–10 km radius of the station. These descriptors are independent of air mass origin and were derived to characterise surrounding terrain and to explore how representative station elevation is of the surrounding area (Figure 2(a)). Distance to coast: The Euclidian (straight) distance from each station to the nearest coast. This linear descriptor was defined to investigate the influence of open water on rainfall and is independent of air mass origin (Figure 2(b)). Distance to coast (SW): The distance from each station to open water (Irish Sea) along an SW trajectory (225◦ ). A smoothed coastline that excluded minor bays and/or estuaries was used for this descriptor to more accurately represent the distance to open water. This Copyright  2009 Royal Meteorological Society

Topographic descriptors may be used to classify weather stations into distinctive geographic regions in order to examine rainfall patterns in areas of complex topography. Five geographic settings were chosen for this study: coastal, windward-lowland, windwardupland, leeward-upland, and leeward-lowland. A boundary height of 300 m was selected to classify stations into upland or lowland categories (after Orr and Carling, 2006). Given valleys located in upland regions may record rainfall totals characteristic of higher elevations, testing was undertaken to investigate which topographic descriptor, station elevation, zonal mean elevation, or zonal maximum elevation, was the most appropriate measure of elevation. Analysis of all permutations of the three elevation descriptors using buffers of radii 1–10 km showed 3 km zonal maximum elevation (i.e. the maximum height within 3 km of the station) to have the highest correlation coefficient when compared with mean daily winter rainfall under SW conditions (r 2 = 0.4; p < 0.001). This descriptor was therefore used to classify the weather stations into lowland or upland categories (Figure 3). To classify stations into windward or leeward categories under SW air flow, a series of parallel lines were constructed at 2.5 km spacing across Cumbria at a of bearing 225◦ , and the maximum elevation along each line determined (Figure 3). These points of maximum elevation were connected by straight lines to form an unsmoothed crest line. This crest line was compared with catchment areas obtained from the Environment Agency; all catchments with their area predominately to the NE of this line were classified as leeward and the remainder windward. This watershed-derived crest line is shown in Figure 3. Surface rainfall at low-lying coastal sites can be considered representative of baseline rainfall prior to enhancement over upland areas when rainfall is arriving over open water from the west (Hill et al., 1981). By defining coastal stations, the extent of orographic enhancement and the extent to which it may have altered under a changing climate can be determined. Given orographic effects have been observed on hills as low as 50 m elevation (Bergeron, 1961 cited within Roe, 2005), coastal stations are Atmos. Sci. Let. 10: 177–184 (2009) DOI: 10.1002/asl

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Figure 3. Schematic to show how the different geographic settings; lowland, upland, windward, and leeward were defined for SW air flow conditions.

defined in this study as those under 50 m elevation and located within 5 km of the coast along an SW trajectory (Figure 2(b)). At more than 5 km inland, the atmospheric boundary layer is unlikely to be predominantly marine in composition; this distance is in line with previous studies (e.g. Hill et al., 1981). The geographic setting of each weather station is shown in Figure 4(a). The weather stations are well-distributed inland and each setting contains 50–60 stations that operated for some period between 1960 and 2007 (Figure 4(b)). With the exception of 1960, every year contains at least 55 operational stations, a quantity sufficient for robust trend analysis.

4. Conditional analysis of rainfall Conditional analysis may be used to investigate how rainfall patterns change in different geographic settings for a selected synoptic situation, for example SW flow conditions. Daily observations from the Meteorological Office archive (MIDAS, 2008) were compared with the daily LJWT catalogue to select the rainfall recorded on SW weather type days during winter Copyright  2009 Royal Meteorological Society

(December, January and February). Observations from all Cumbrian stations with data capture greater than 90% over the winter season were included, except those located on the slopes of the Pennines (Figure 1). This case study focuses on the rainfall processes associated with the first cycle of air mass uplift and descent over an orographic barrier, i.e. from the Cumbrian coast to the Vale of Eden. Stations located within 3 km of a Pennine elevation greater than 300 m (Section 3) are likely to be effected by a secondary orographic processing, which is not part of this current investigation. The total winter rainfall provided by SW conditions was summed for every weather station from 1960 to 2007 to determine the mean winter rainfall for each geographic setting. Figure 4(c) shows the amount of winter rainfall increases in all geographic settings, most noticeably in upland areas. Leewardupland sites have experienced the greatest magnitude increase (+1.8 mm/year), a magnitude greater than in windward settings; the leeward trends are significant at the 95% level (Figure 4(c)). Coastal stations exhibit the least significant trend (r 2 = 0.03; p = 0.27) and the lowest magnitude increase in winter rainfall (+0.3 mm/year). This geographic setting contains the smallest number of contributing weather Atmos. Sci. Let. 10: 177–184 (2009) DOI: 10.1002/asl


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Figure 4. (a) The geographic setting of weather stations under SW air flow conditions; (b) the number of stations used to compute the mean winter rainfall associated with different geographic settings from 1960 to 2007; and (c) the mean winter rainfall for each geographic settings from 1960 to 2007. Linear trends were calculated using ordinary least squares regression. The increase in rainfall (mm/year), regression coefficient (r2 ) and significance (p) are shown on the graph. Error bars show one standard deviation of the mean. Note the differing range of the vertical axis.

stations (Figure 4(b)) and examination of rainfall records from similar low-lying westerly locations (e.g. Anglesey, Isle of Man) would be needed to confirm this trend. The rainfall trends discussed above are determined by a varying number of station records throughout the period and for each setting (Figure 4(b)), and the use of different stations could introduce sensitivity in Copyright  2009 Royal Meteorological Society

the calculated trends. For comparison, rainfall records of stations operational for the full time period were analysed and revealed similar trends in each geographic setting. Increasing trends are also present in the seasonal maximum, minimum and median values for each geographic setting. GIS techniques can also be used to interpolate station-specific rainfall amounts over larger areas, and Atmos. Sci. Let. 10: 177–184 (2009) DOI: 10.1002/asl

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(c)

Figure 4. Continued.

inverse-distance-weighted (IDW) techniques prove particularly useful when the network of observing stations is dense and regularly spaced (Perry and Hollis, 2005). To spatially examine the change in winter rainfall pattern, three time slices typical of the 1960–2007 period were selected and the 5-year seasonal mean was calculated. Figure 5 shows total winter rainfall under SW conditions has increased in upland areas from 1960 to 2007, and the wetter upland area has increased in size. Rainfall amount has increased in the Vale of Eden east of Penrith; however, the western coastal zone shows little change. Copyright  2009 Royal Meteorological Society


5. Conclusions and future work A high-resolution database of meteorological observations has been constructed for Cumbria. Synoptic and local site characteristics allow the rainfall associated with specific conditions to be defined and analysed over different time periods and in different geographic settings. An initial study of winter rainfall under SW conditions has shown the capabilities of the methodologies presented in this paper. Preliminary results show winter rainfall under SW conditions has increased from 1960 to 2007, with the magnitude of increase varying between geographic settings. Upland regions, particularly leeward-upland zones, are experiencing the greatest increase in rainfall under SW conditions. Ongoing research is repeating this methodology to investigate how the frequency distribution of rainfall amount may be changing for different synoptic situations and geographic settings. This, combined with the conditional analysis of other meteorological parameters such as wind speed, wind direction and temperature, will provide a detailed synopsis of Cumbrian rainfall patterns and processes under a changing climate. These results will be significant for other mid-latitude upland areas dominated by a maritime climate both within the United Kingdom and globally. This novel conditional approach allows the changing patterns of rainfall in topographically complex areas to be clearly identified and provides the observational detail needed to study the changing rainfall processes. With appropriate modification, the topographic descriptors could be used to generate geographic settings for other regions within the United Kingdom or elsewhere. Moreover, conditional analysis can be applied to test RCM output for selected synoptic and geographical settings to validate output and identify areas where parameterisation can be improved. This will ultimately lead to better simulation of rainfall in areas of complex topography and provide stronger support for future water and ecosystem management decisions. Conditional analysis may also be applied to other fields of atmospheric science where synoptic meteorology and geographic setting are important, such as air pollution or acid deposition.

Acknowledgements This worked was undertaken as part of an NERC studentship NE/F007434/1 supported in part by the Environment Agency for England and Wales. All MIDAS rainfall data were provided by the British Atmospheric Data Centre and are available online at http://badc.nerc.ac.uk/data/ukmo-midas. Catchment data were kindly provided by the Environment Agency for England and Wales. The authors acknowledge the helpful comments of two anonymous reviewers. Atmos. Sci. Let. 10: 177–184 (2009) DOI: 10.1002/asl


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Figure 5. The 5-year mean winter rainfall associated with SW weather types for (a) 1960–1964, (b) 1980–1984 and (c) 2000–2004.

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Atmos. Sci. Let. 10: 177–184 (2009) DOI: 10.1002/asl