Abstract
Abstract. A new type of rainfall sensor (the intervalometer), which counts the arrival of raindrops at a piezo electric element, is implemented during the Tanzanian monsoon season alongside tipping bucket rain gauges and an impact disdrometer. The aim is to test the validity of the Poisson hypothesis underlying the estimation of rainfall rates using an experimentally determined raindrop size distribution parameterisation based on Marshall and Palmer (1948)'s exponential one. These parameterisations are defined independently of the scale of observation and therefore implicitly assume that rainfall is a homogeneous Poisson process. The results show that 28.3 % of the total intervalometer observed rainfall patches can reasonably be considered Poisson distributed and that the main reasons for Poisson deviations of the remaining 71.7 % are non-compliance with the stationarity criterion (45.9 %), the presence of correlations between drop counts (7.0 %), particularly at higher arrival rates (ρa>500 m-2s-1), and failing a χ2 goodness-of-fit test for a Poisson distribution (17.7 %). Our results show that whilst the Poisson hypothesis is likely not strictly true for rainfall that contributes most to the total rainfall amount, it is quite useful in practice and may hold under certain rainfall conditions. The parameterisation that uses an experimentally determined power law relation between N0 and rainfall rate results in the best estimates of rainfall amount compared to co-located tipping bucket measurements. Despite the non-compliance with the Poisson hypothesis, estimates of total rainfall amount over the entire observational period derived from disdrometer drop counts are within 4 % of co-located tipping bucket measurements. Intervalometer estimates of total rainfall amount overestimate the co-located tipping bucket measurement by 12 %. The intervalometer principle shows potential for use as a rainfall measurement instrument.
Highlights
Africa, and Sub-Saharan Africa, is one of the most vulnerable regions in the world to climate change (Boko et al, 2007)
NV(D) can be related to the drop size distribution (DSD) of drops arriving at a unit surface area, NA(D) [mm−1 m−2 s−1], by v(D) [m s−1], which describes the relationship between drop diameter and terminal fall velocity
These results clearly show the importance of accurately modelling the DSD, at larger drop sizes, for rainfall estimation
Summary
Sub-Saharan Africa, is one of the most vulnerable regions in the world to climate change (Boko et al, 2007). Much of SubSaharan Africa is greatly underserviced by weather observations, and the existing observational networks have been in decline since the mid-1990s; from an average of eight stations per 1 million square kilometres, the density has decreased to less than one in 2015 (data from the Climate Research Unit of the University of East Anglia, 2017). There are some organisations working on setting up new observational networks, such as the Trans-African Hydro-Meteorological Observatory (TAHMO), but progress is slow due to the lack of financial incentives for weather data. The African climate has not been as well researched in comparison to those of western Europe and the United States (Otto et al, 2015; Washington et al, 2006).
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