Insights into rainfall undercatch for differing raingauge rim heights

The measurement of rainfall has a long history, but despite its apparent simplicity it is dif ﬁ cult to quantify accurately. The common installation of raingauges with rims above the ground surface results in a difference between the rainfall caught and the amount reaching ground level, termed undercatch. The UK standard installation of raingauges is for their rim to be sited at 0.305 m above the ground; however, the use of weighing gauges installed at a minimum rim height of 1 m has increased in recent years. The installation of these weighing raingauges raises complex questions of homogeneity in rainfall data across space and time. Here, we investigate the impact of these changes using ﬁ eld trials of commonly deployed UK raingauges at a site in south-east England. This paper discusses the results of the trial, exploring the variation in and potential drivers of undercatch with differing gauge sitings. With varying standards for gauge heights around the world and new rainfall measurement technologies coming to the market all the time, improved understanding of undercatch is needed to inform evolving operational practices and explore the possibility of developing catch correction algorithms to remove arising inhomogeneity in precipitation datasets.


INTRODUCTION
Accurate measurement of rainfall amount is crucial for many areas of hydrology, including water balance studies, flow forecasting, modelling and water resource assessments (Tian et al. ; Looper et al. ; Stisen et al. ). Rainfall has been measured since as early as the fourth century and there are currently many different types of gauge in use around the world, although manual storage gauges read by observers on a daily or monthly basis form a large part of the UK's long-established rainfall observational network (Strangeways ). This network is augmented with automatic recording gauges which are used to measure rainfall at a finer temporal resolution, essential for uses such as flood risk modelling and hazard warning systems (Tapiador et al. ). However, despite a long history of observations in the UK and around the world, it is widely acknowledged that there are many errors (both random and systematic) encountered when measuring rainfall whether manual or automatic gauges are used.
Irrespective of gauge type, a common issue in the measurement of rainfall is wind-induced undercatch where, due to the deformation of wind and increased turbulence above the gauge rim, raindrops are deflected away from the collecting orifice meaning less rain is recorded in a gauge mounted above the ground than would reach ground level (Rodda & Dixon ). This undercatch effect has been investigated extensively by field intercomparisons ) and computational fluid dynamics modelling (e.g. Nespor & Sevruk ; Colli et al. ). In addition, accuracy is found to be affected by rainfall intensity, most notably in tipping-bucket gauges where counting errors have been observed (Molini et al. ). For the users of precipitation data, understanding the impact of this issue on the homogeneity of records across space and time is made more complex due to variations between different types of gauges and the way in which they are sited.
While there are a set number of gauge types available (Strangeways ), many of which have been subject to extensive intercomparison studies (e.g. Lanza & Vuerich ), there is a significant variation in the way that gauges are installed around the world. The World Meteorological Organization (WMO) recommends that the height of the gauge rim should be as low as possible but high enough to prevent splashing in from the ground surface (WMO ).
A number of options exist to minimise the impact of increasing wind velocities with gauge height, including installing a shield to reduce the velocity around the gauge (Benning & Yang ), installing a turf wall (Essery & Wilcock ) or installing a gauge of a more aerodynamic shape (Strangeways ; Sieck et al. ; Colli et al. ). However, the most effective approach is to install a gauge within a pit to ensure the rim is at ground level preventing the body of the gauge from creating an obstacle to the wind (Rodda ).
Extensive trials took place in the 1960s in Wallingford (Oxfordshire, UK) to assess the impact of the shape and size of pit grids, and now a European standard exists for the design of reference raingauge pits (CEN ) which can be used to evaluate wind effects or to conduct comparison against other reference raingauges. The installation of gauges in pits to create a reference rainfall series means that the rainfall recorded in a gauge above the ground surface may be corrected to the value reaching the surface ( (Colli et al. ), and this study does not seek to repeat such work, the difference in shape and rim height between gauges raises the potential for increased amounts of wind-induced undercatch by the newly deployed WRGs.
In this study, we explore undercatch across the different UK dominant raingauge types and common sitings and attempt to isolate the impact of wind-induced errors by comparing observations from each gauge with ground-level installations of the same make and model.

Site location
The meteorological station at the Centre for Ecology

Instrumentation
For the purpose of this study, the station contains seven raingauges ( Figure 1)two UK Met Office MK2 daily storage gauges, two Casella tipping-bucket gauges and three Ott Pluvio weighing gauges (Table 1)

Data preparation
The data and results presented here reflect the period where all three gauge types were in operation (August 2015-August 2018). All sub-daily rainfall data were quality controlled using the other gauge heights and types. Records identified as being anomalous (e.g. due to the Pluvio incorrectly recording rainfall during high temperatures when the collecting bucket is empty) were removed. Daily and monthly totals were then checked for any large discrepancies, but none were found. Any periods of missing data (e.g. due to instrument calibration or telemetry failure) were checked against other gauge types. For the study period, there were four large (>24-h) missing data periods, two of which were within periods of no rainfall and two coincided with small (<1 mm) daily rainfall totals. Therefore, with minimal impact of missing data on the analysis, all data were included. Daily and monthly totals were calculated over the UK standard 09:00-09:00 hydrological day. Seasonal figures were calculated for UK winter (December-February), spring (March-May), summer (June-August) and autumn (September-November) using monthly totals.
In order to investigate the potential driving factors behind any undercatch, an event dataset was created using the 15-min resolution reference Pluvio gauge (0.000 m) data against which the 0.305 and 1 m Pluvio data could be compared. Although the Pluvio provides measurements at 1-min resolution this was not used in this study, as operationally within the UK 15-min data are used for reporting and analysis. In addition, wind speed measurements from the Wallingford station were only available at 15-min intervals for direct comparison with the rainfall.
The definition of rainfall event can vary depending on the purpose of a given study, but events are generally based on a period of accumulated rainfall above a set threshold separated by a given period of time. This period is known as the 'minimum inter-event time' (MIT) and in a review by Dunkerley () covering a wide range of geographical locations lengths of between 0.25 and 24 h were found to be in use, with the majority between 6 and 8 h. In southern England, rainfall events are a mixture of frontal events (long MIT) and convective storms (small MIT) (https://www.metoffice.gov.uk/climate/uk/regional-climates/so#rainfall). For this study, event datasets were produced and analysed for 1-, 2-, 3-and 4-h MITs. A 3-h MIT was chosen, as it was found to provide a good balance to include both convective and frontal events. In addition, an accumulation threshold of 1 mm (recorded in each of the three weighing gauges) was used, which generated a dataset of 288 events. Snowfall was present in six of these events, and as snow only represents a small proportion of the dataset and the climatology of the site is such that snowfall is rarely observed, these events were excluded creating a dataset of 282 events for analysis. For each event, the characteristics listed in Table 2 and the percentage catch for each Pluvio

Monthly undercatch analysis
To assess the degree to which undercatch is observed for the different gauges, the percentage catch for each month was    A weak negative relationship was observed between undercatch and event average intensity ( Figure 5(a)) but again, while statistically significant (p < 0.001), a large amount of scatter was seen, particularly at low intensities.
The differences between the two gauges were more pronounced at lower intensities ( Figure 5(b)); however, it should be noted that the dataset is highly skewed towards low-intensity events due to the climatology of the site (78% of the 282 events have an event average intensity of <2 mm/h) meaning that the effects of higher intensity events could not be well assessed.

The analysis presented in Figures 4 and 5 is based on
the average intensity and wind speed of each event and when the event dataset was analysed using maximum data, a similar relationship was found. In order to explore the data further, four events were chosen for more

DISCUSSION
The results presented here for the three gauges mounted at 0.305 m compared with a reference pit gauge are  Even with a more detailed understanding of the drivers of undercatch from higher resolution data, due to the vari-  The results presented in this study are from a lowland UK site. Previous studies suggest that higher undercatch could be expected at more exposed upland sites and the knowledge of spatial variation in undercatch with varying topography is currently poorly understood, both in the UK and globally. As such, it is recommended that to prevent this introduction of inhomogeneity in time series, any future installation of replacement gauges are done at the UK standard height of 0.305 m or, to further improve the understanding of undercatch and develop adjustment methods for rainfall data, a network of International Standard reference pit gauges need to be constructed around the UK (and in other countries) with full metadata detailing their siting.
While the focus of this study has been on the inhomogeneity which may be introduced to the UK rainfall records by changing gauge rim height, the authors acknowledge that the UK practice of installing gauges at 0.305 m is different from that in many other countries. In locations where the standard installation of gauges is higher, it will be easier to maintain consistency with changing gauge designs. However, the magnitude of the undercatch observed in this study for gauges installed at 1 m is of relevance to all networks with rim heights of this level and above. Precipitation time series are often used to underpin a wide variety of hydrological science and operational water management decisions. For such applications, it is the amount of water reaching the ground surface which is often of interest and hence, unless properly understood and accounted for across space and time, undercatch of the magnitude of the 12.7% observed in this study and potentially even higher, represents a significant uncertainty in catchment hydrology and therefore the management of water resources and water-related hazards.