Potentially, the greatest benefit of commercial microwave links (CMLs) as opportunistic rainfall sensors lies in regions that lack dedicated rainfall sensors, most notably low-and middle-income countries. However, current CML rainfall retrieval algorithms are predominantly tuned and applied to (European) CML networks in temperate or Mediter-ranean climates. This study investigates whether local quantitative precipitation estimates from CMLs in a tropical region, specifically Sri Lanka, can be improved by optimizing two dominant parameters in the rainfall retrieval algorithm RAINLINK, namely, the wet antenna attenuation correction factor A_a and the relative contribution of minimum and max-imum received signal levels a. Using a grid search, based on 10 months of CML data from 22 link–gauge clusters consisting of 105 sublinks that lie within 1 km of a daily rain gauge, the optimal values of A_a and a are first derived for the entire country and compared to the default RAINLINK values. Subsequently, the CMLs are grouped by link length, frequency, climate zone, and daily rainfall depth classes, and A_a and a are derived for each of these classes. Calibrating parameters on all clusters across the country only leads to minor improvements. The actual optimal A_a and a values depend on the perfor-mance metric favored. Calibrating on network properties, particularly short link length and high-frequency classes, does significantly improve rainfall estimates. By relating the optimal A_a and a values to known network metadata, the results from this study are potentially applicable to other tropical CML networks that lack nearby reference rainfall data.

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Terrestrial microwave links are increasingly being used to estimate path-averaged precipitation by determining the attenuation caused by rainfall along the link path, mostly with commercial microwave links from cellular telecommunication networks. However, the temporal resolution of these rainfall estimates and the method to derive them are often determined by the temporal sampling strategy that is employed by the mobile network operators. Currently, the links are most often sampled at a temporal resolution of 15 min with a recording of the minimum and maximum values, while more recently, a form of instantaneous sampling with possible intervals up to 1 s has also been set up. For rainfall research purposes, often high temporal resolutions in combination with averaged values are preferred. However, it is uncertain how these various temporal sampling strategies affect the estimated rainfall intensity. Here we aim to understand how temporal sampling strategies affect the measured rainfall intensities using microwave links. To do so, we use data from three collocated microwave links, two 38 GHz and one 26 GHz, sampled at 20 Hz and covering a 2.2 km path over the city of Wageningen, the Netherlands. We aggregate the microwave link power levels to multiple time intervals (1 s to 60 min) and use a mean, instantaneous, and minimum and maximum value to characterize the signal. Based on the aggregated data, we compute rainfall intensities and compare these with 20 Hz rainfall estimates, such that we isolate errors and uncertainties caused by the sampling strategies from instrumental effects, such as different biases between instruments and representativeness errors. In general, our results show that for all sampling strategies, an increase in sampling time interval reduces the performance of the rainfall estimates, which especially holds for the instantaneous sampling strategy. Even the mean sampling strategy, which generally performs best of all strategies, is sensitive to this reduction in temporal resolution and could lead to significant underestimations. This sensitivity of the mean sampling to the temporal resolution seems to be largely affected by the non-linear relation between attenuation and rainfall. The min–max sampling strategy is mostly prone to minor underestimations or large overestimations of the path-averaged rainfall intensities. Moreover, our results, including a comparison with theoretical events, show that the attenuation due to wet antennas not only affects the comparison between the rainfall estimates obtained with a microwave link and another reference instrument but also has a significant influence on the performance of the rainfall retrieval algorithm, especially for devices with relatively long duration of the wet-antenna attenuation combined with the longer sampling time intervals. Overall, this study demonstrates the effect a selected sampling strategy can have on rainfall intensity estimates using (commercial) microwave links.@en

Opportunistic sensors are increasingly used for rainfall measurement. However, their raw data are collected by a variety of systems that are often not primarily intended for rainfall monitoring, resulting in a plethora of different data formats and a lack of common standards. This hinders the sharing of opportunistic sensing (OS) data, their automated processing, and, at the end, their practical usage and integration into standard observation systems. This paper summarises the experiences of the more than 100 members of the OpenSense Cost Action involved in the OS of rainfall. We review the current practice of collecting and storing precipitation OS data and corresponding metadata, and propose new common guidelines describing the requirements on data and metadata collection, harmonising naming conventions, and defining human-readable and machine readable file formats for data and metadata storage. We focus on three sensors identified by the OpenSense community as prominent representatives of the OS of precipitation: Commercial microwave links (CML): fixed point-to-point radio links mainly used as backhauling connections in telecommunication networks Satellite microwave links (SML): radio links between geostationary Earth orbit (GEO) satellites and ground user terminals. Personal weather stations (PWS): non-professional meteorological sensors owned by citizens. The conventions presented in this paper are primarily designed for storing, handling, and sharing historical time series and do not consider specific requirements for using OS data in real time for operational purposes. The conventions are already now accepted by the ever growing OpenSense community and represent an important step towards automated processing of OS raw data and community development of joint OS software packages.

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This paper shares an early-career perspective on potential themes for the upcoming International Association of Hydrological Sciences (IAHS) Scientific Decade (SD). This opinion paper synthesizes six discussion sessions in western Europe identifying three themes that all offer a different perspective on the hydrological threats the world faces and could serve to direct the broader hydrological community: “Tipping points and thresholds in hydrology,” “Intensification of the water cycle,” and “Water services under pressure.” Additionally, four trends were distinguished concerning the way in which hydrological research is conducted: big data, bridging science and practice, open science, and inter- and multidisciplinarity. These themes and trends will provide valuable input for future discussions on the theme for the next IAHS SD. We encourage other early-career scientists to voice their opinion by organizing their own discussion sessions and commenting on this paper to make this initiative grow from a regional initiative to a global movement.

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