Selene’s Explorer for Roughness, Regolith, Resources, Neutrons and Elements (SER3NE) is a lunar orbiter mission designed to map the topmost composition of the lunar surface, including elemental composition and water abundance. Planned instruments include a Gamma Ray and Neutron Spectrometer (GRNS) for elemental composition, including hydrogen indicating water, a Laser Altimeter (LA) for surface roughness and albedo observations, and a near-infrared spectrometer (LIPS) to determine water forms.

The GRNS detector is designed for both in situ utilization as well as remote sensing. It has a core of CLLBC and LaBr₃ crystal scintillators in a chessboard pattern for high-resolution gamma-ray detection (30 keV-8MeV) and thermal to epithermal neutron sensitivity. Gd foil on CLLBC allows separation of thermal and epithermal neutrons, while LaB3 and CLLBC enable advanced neutron detection analysis. Encapsulated by EJ-248M plastic scintillators, the detector includes anti-coincidence detector for charged particle rejection. With gamma-ray spectroscopy, rock-forming elements as well as KREEP and trace elements can be detected in the shallow surface of the moon. The local count rates of thermal and epithermal neutrons allow for the analysis of the distribution of hydrogen on the lunar surface, as well as for estimation of neutron lifetime from the lunar orbit.

A demonstrator of the GRNS instrument has been successfully tested in the lab. A prototype of this lunar GRNS instrument will fly on the CENSSat-1 Bifrost CubeSat mission, scheduled for launch 2027.

In this presentation, the GRNS instrument concept will be presented, focusing on the detector design and suitability for elemental composition analysis on a lunar orbiter.

How to cite: Wahlén, R., Al Jebali, R., Teodoro, L., and Kohfeldt, A.: A Gamma Ray and Neutron Spectrometer (GRNS) for mapping lunar surface composition and water abundance on the SER3NE mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17007, https://doi.org/10.5194/egusphere-egu25-17007, 2025.

The Tumbleweed mission aims to revolutionize Mars exploration by leveraging the unique capabilities of wind-driven, spheroidal rovers. The use of modular design strategies, off-the-shelf components, and mass production will significantly reduce costs, making Mars exploration more accessible. Designed for rapid and extensive surface exploration, Tumbleweed rovers offer an affordable and efficient method for gathering crucial data across large areas of the Martian terrain. By deploying a swarm of more than 90 rovers equipped with various scientific instruments, this mission will significantly enhance our understanding of Mars, facilitating future human exploration and settlement.

The search for water in various forms is the common thread that binds the science goals of Mars exploration missions over the past few decades. For large scale water extraction (aimed at producing propellant and potable water in sizable quantities), a coordinated prospecting and characterisation campaign is required to arrive at maps of exploitable reserves.

Unfortunately, current architectures rely primarily on large, complex, and expensive rovers. While these platforms provide invaluable data, they are limited in their spatio-temporal coverage. Consequently, optimal Exploration Zones (EZs) for human exploration of Mars are yet to be defined.

Based on current priorities in Mars science and exploration, as well as the technical constraints of the Tumbleweed rover, a preliminary list of instruments was drafted. Exploring the synergies amongst these instruments, we arrived at the opportunity to use radiation-focused instrumentation to simultaneously achieve high-resolution mapping of hydrogen in the near-surface environment. Measuring the flux of epithermal neutron emissions is one of the best approaches towards estimating water equivalent hydrogen (WEH) abundance. Thermal and epithermal neutron measurements from instruments such as FREND, HEND and DAN have indicated the presence of WEH in the near-surface. This would represent the prime target for ISRU operations in the near future. However, the resolution of existing orbital maps of water ice is insufficient to direct and execute robotic/human operations on ground. 

This suite of radiation detection instruments will be consolidated in the future through the addition of a miniaturized Gamma Ray Spectrometer, providing the ability to perform elemental mapping along the rover traverse. Beyond neutron spectrometers, patch permittivity sensors may also be deployed on the Tumbleweed Rovers, enabling cross-confirmation of WEH mapping.

This instrumentation and our mission architecture enable high-resolution mapping of Martian environments, combining radiation scouting with WEH prospecting, thus identifying low-radiation and high-WEH regions ideal for crewed missions.

To aid further maturation and design of the mission, a conceptual study is proposed herein. Starting from a simulation of the individual rover’s trajectories on the surface of Mars, we shall geospatially compute the probable intersections with the already identified EZs on Mars. Based on these intersections we can infer thresholds for the controlled navigation of individual rovers (assessing intersections per trajectory buffer size) and classify candidate EZs according to known topography and available WEH mapping. This classification would enable more precise GEANT4 modelling of individual rovers and their instrumentation, resulting in probable neutron counts and dose/flux readings, leading to mission-specific requirements for our spacecrafts and their payloads.

How to cite: de Pinto Balsemão, M., Shanbhag, A., Kingsnorth, J., Bounova, G., Pikulić, L., Moisuc, C., Molhuijsen, D., and Rothenbuchner, J.: Mars Radiation Environment and Water-ice Prospecting through a Distributed Swarm of Tumbleweed Rovers , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19534, https://doi.org/10.5194/egusphere-egu25-19534, 2025.

The study of Cosmic Rays (CRs) and Solar Energetic Particles (SEPs) is key in analyzing the effect of solar activity on the terrestrial environment. Changes in the properties of the medium they pass through until their detection profoundly affect the intensity and the propagation direction of the CR flux.

Our starting point is that accurate measurements of CR and SEP flux can allow us to infer the conditions of the medium they pass through on their way to Earth, particularly the interplanetary medium, the magnetosphere and the atmosphere. The development of a CR simulation code helps us perform such analysis, which may contribute to future predictions of solar events and prevent potential damage and disturbances in the global technological system and the human environment. Computational simulation of these phenomena allows us to interpret the data and obtain a vision that will facilitate, for instance, explaining the generation and transport of solar neutrons to Earth’s atmosphere and their interaction with the atmosphere and the detectors installed in different geographical locations.

The Space Research Group of the University of Alcala (SGR – UAH) has extensive experience in the design, construction, control and maintenance of neutron measurement systems, distributed in different regions of the world. Among these, we can mention: CALMA, ORCA, ICaRO and the EPD aboard on the Solar Orbiter Mission. These instruments generate a large amount of data that must be analyzed and modeled for understanding and study. It is at this point where computational simulation techniques and data management are crucial for the SGR-UAH group.

In this work we present the code we developed to study the trajectory and rigidity of charged particles entering Earth’s magnetic field. The simulation code TOROS (Trajectories of cOsmic Rays Observed Simulator) is based on numerically calculating the trajectories of charged particles and their interaction with Earth’s magnetic field before reaching the atmosphere. The code uses the magnetic dipole model and various approximations of Tsyganenko’s magnetic field model. Our goal is to use this simulation tool and the data it generates as input for well known simulation codes in the research field, such as GEANT-4 and CORSIKA, to validate, simulate and propose models based on experimental measurements from detectors of the SGR-UAH group and others worldwide. Comparing our results with other simulation codes is also part of the validation and testing process for the “TOROS” code.

How to cite: Fuente, R., Guerrero, C. L., Blanco, J. J., and Cerviño, P.: Simulation of Cosmic Rays Trajectories and Neutron Transport generated on the Sun and observed on Earth, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3490, https://doi.org/10.5194/egusphere-egu25-3490, 2025.

Cosmic Ray Neutron Sensing (CRNS) is a technique to measure water content, for example soil moisture, on the hectare scale through the measurement of epithermal neutrons. The neutrons are results of  particle showers in the earth's atmosphere caused by cosmic rays impinging on it. The abundance and global distribution of neutrons is changed in time through different factors. On the largest scale, the heliosphere and therefore the solar cycle greatly affect the amount of galactic cosmic rays that are able to reach earth. Large solar events, such as Forbush decreases, also cause rapid changes in the cosmic ray flux. The aim of any incoming neutron flux correction method is ultimately to account for these heliospheric changes. Any neutron monitor based correction method has to overcome the uneven distribution of neutrons across latitudes, due to the earth's magnetic field.  There have been multiple, neutron monitor based, approaches developed, all of them based upon the assumption of linearity between the CRNS and the neutron monitor measurement. This assumption is challenged by multiple factors, most importantly geomagnetic and local conditions. Understanding the challenges and limitations of the linearity assumption is crucial to reliably correct CRNS measurements and produce a robust soil moisture product. Multiple correction methods have been evaluated and compared, with consideration towards the impact of different geomagnetic and local conditions. 

How to cite: Hertle, L., Zacharias, S., Larsen, N., Rasche, D., and Schrön, M.: Approaches and Challenges of the Neutron Monitor based Incoming Flux Correction for Cosmic-Ray Neutron Sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18374, https://doi.org/10.5194/egusphere-egu25-18374, 2025.

Cosmic Rays Neutron Sensing (CRNS) opened the possibility to measure water content in the environment by neutrons absorption overcoming the need of an artificial radioactive source of neutrons. While the exploitation of a naturally available source of radiation is a fundamental feature that allows the widespread deployment of permanent sensors on-field, it intruduces the need of monitoring the natural variation of the incoming radiation to correct the signal accordingly.

This so-called “incoming correction” for CRNS is usually obtained by referring to the public data provided by the Neutron Monitor DataBase (NMDB) observatories, with the Jungfraujoch (JUNG) often being the preferred one, due to its position in central Europe on the Swiss Alps. In fact, a critical factor affecting the incoming flux of cosmic rays at the ground is the geomagnetic cutoff rigidity parameter, which is site-specific with a strong dependence on the latitude. The site-specificity of the incoming correction, together with the need to rely on an external source of data, makes it a crucial topic for the CRNS community.

Finapp developed a patented detection technology with the feature of contextually detecting neutrons and muons. Muons are also generated by cosmic rays, but they are not backscattered by the soil like neutrons, which makes them suitable for monitoring the incoming flux itself. In order to provide a fair, site-specific comparison between the variations of muons counts by Finapp and cosmic neutrons counts by NMDB observatories, we installed a sensor at the NMDB-JUNG site in January 2024 and one at the NMDB-OULU site in Finland in October 2024. In this presentation we will report preliminary results of this project and its impact on CRNS applications.

We acknowledge the NMDB database (www.nmdb.eu), founded under the European Union's FP7 programme (contract no. 213007) for providing data. Jungfraujoch neutron monitor data were kindly provided by the Physikalisches Institut, University of Bern, Switzerland. Oulu neutron monitor data were kindly provided by the Sodankyla Geophysical Observatory (https://cosmicrays.oulu.fi).

How to cite: Bonvicini, C., Cracco, G., Biasuzzi, B., Gianessi, S., Lunardon, M., Zara, M., Zanetti, M., Stevanato, L., and Gazzola, E.: Site-specific incoming correction based on muons: a comparison with cosmic neutrons measurements at JUNG at OULU., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5935, https://doi.org/10.5194/egusphere-egu25-5935, 2025.

Cosmic Ray Neutron Sensing (CRNS) is attracting attention in irrigation management. CRNS can non-invasively and accurately measure soil moisture (SM) in the root zone at the field scale, thus addressing scale and logistics issues typical of point-scale sensor networks. CRNS are effectively used to inform large pivot irrigation systems but most agricultural landscapes in Europe and elsewhere consist of highly diversified and small fields. These are challenging for CRNS as the measured signal integrates an area of ~200m radius where multiple fields, soil heterogeneities, or variable amount of water applications can be found.

In this work, we present results from three case studies, and we develop and test solutions to improve CRNS accuracy in irrigated contexts. In 2023, a potato field in Leerodt (Germany) where strip irrigation is practiced was equipped with three CRNS (with moderators and thermal shielding), three meteorological stations, and six profile SM probes measuring at six different depths (up to 60 cm). In the same year, in Davis (California, USA), two CRNS with a 15 mm moderator, one of which also had a thermal shielding, were installed in an alfalfa field where flood irrigation is practiced. These were supported by meteorological measurements and point-scale TDR sensors. Similarly, a CRNS installed in a winter wheat field in Oehna (Germany) where pivot irrigation is applied. As the origin and propagation of neutrons detected by a CRNS cannot be inferred from the measured signal, we used the URANOS model to analyze neutron transport in the three case studies under varying soil moisture scenarios. To account for soil heterogeneity in the Leerodt study, we assessed the spatial distribution of soil characteristics by integrating soil sampling and Electromagnetic Induction (EMI) measurements in a machine-learning framework.

The Leerodt study showed that CRNS outperformed point-scale sensors, which were strongly affected by soil erosion in the top 10 cm. However, CRNS was unexpectedly sensitive only to nearby irrigation. Here, key insights on sub-footprint heterogeneity and soil roughness were gained through the analysis of URANOS simulations. In the Davis study, CRNS effectively monitored irrigation but also showed unexpected sensitivities to the irrigation of distant fields. Again, important insights were gained thanks to URANOS simulations. In the Oehna study, large quantitative differences between the CRNS and point-scale sensors were observed. However, the CRNS provided clear responses to irrigation that can outperform the information provided by the point-scale devices. Overall, the limitations of CRNS-based irrigation management in complex agricultural environments can generally be overcome through a synergetic use of measurements and modelling. Nonetheless, more efforts are needed to improve the understanding of the underlying processes and to standardize measurement procedures, which ultimately requires the involvement not only of researchers but also of manufacturers and stakeholders.

How to cite: Bogena, H., Brogi, C., Nieberding, F., Daccache, A., Scheiffele, L., and Dogar, S. S.: Irrigation Management and Soil Moisture Monitoring with Cosmic-Ray Neutron Sensors: Lessons Learned and Future Opportunities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12351, https://doi.org/10.5194/egusphere-egu25-12351, 2025.

Monitoring soil moisture is a challenging task due to its complex spatial patterns. In recent years, cosmic-ray neutron sensing has gained popularity for its ability to provide integral measurements over a few hectares horizontally and a few decimeters vertically, covering a representative volume for many research questions in various landscapes. However, interpreting signals using averaging methods becomes increasingly difficult as the heterogeneity of the observable increases.
As part of the SoMMet project, three field sites in Germany and Italy equipped with cosmic-ray neutron sensors are analyzed in detail using the Monte Carlo code URANOS. The virtual representation of these sites in the code allows for removing and adding structures. Thereby, all features of the landscape of the three different sites can be examined separately with respect to their impact on the local neutron field. These include general landscape heterogeneities, buildings, land use, and biomass. While this study focuses on three specific, although relatively common, site setups, it also offers general insights that can enhance the understanding of signal and footprint dynamics at other locations.

How to cite: Weimar, J., Köhli, M., Schrön, M., Oswald, S., and Zboril, M.: Understanding the influence of landscape heterogeneities on the signal of cosmic-ray neutron sensors by means of site-specific neutron transport simulation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19713, https://doi.org/10.5194/egusphere-egu25-19713, 2025.

Field-scale Soil Moisture (SM) is an important variable to derive and study agriculture, plant growth, nutrient management, water quality and management, soil carbon sequestration, groundwater availability, flood forecasting, forest fire risk, land surface models and is an Essential Climate Variable (ECV). Field-scale SM estimates are vital due to small scale soil heterogeneities and can fill the gap between the traditional in-situ point measurements and products derived from remote sensing.

The Cosmic-Ray Neutron Sensor (CRNS) technology detects and counts naturally occurring fast neutrons (generated by cosmic-rays) after they are slowed primarily by hydrogen atoms in soil water and biomass. The CRNS can measure the root-zone SM at field-scale in a non-invasive way to an effective depth of 10 to 70 cm depending on soil water content and over a footprint of around 300 m diameter.

The AGMET group (Working Group of Applied Agricultural Meteorology in Ireland) instigated the Irish Soil Moisture Observation Network (ISMON) in 2021 and installed ten CRNS stations across Ireland, covering a range of soil types, with a view to estimating regional soil moisture conditions more accurately.

In this study, we present the SM estimates recorded since 2021 at two different ISMON sites in Ireland. In each of these sites, the CRNS sensor is co-located with arrays of Time-Domain Reflectometry (TDR) in-situ sensors. The first site is an agricultural grazing system on a mineral soil at the ISMON Farmer’s Journal farm site in Tullamore, County Offaly. The second site locates in a forest setting at the ISMON Dooray forest in County Laois. The CRNS measurements are calibrated based on soil sampling campaigns and the CRNS derived SM products are compared with TDR measurements for validation. The effect of the soil types and vegetation cover on the final SM estimates are investigated.

How to cite: Karbala Ali, H., Finkele, K., Rosolem, R., Evans, J., Schrön, M., Tobin, B., and Daly, E.: Challenges and Opportunities with Soil Moisture Measurement in Ireland using Cosmic-Ray Neutron Sensing: Examples from an agriculture and a forest site, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3236, https://doi.org/10.5194/egusphere-egu25-3236, 2025.

Near-surface soil moisture variation is an important variable in peatlands, controlling chemical processes and peat development or degradation. Cosmic-ray neutron sensing (CRNS) provides an area average soil moisture over a support volume of > 150 m radius and down to 50 cm depth by relating the abundance of secondary fast neutrons above ground to soil moisture. However, standard calibration and weighting functions for CRNS were developed and tested for mineral soils with dry bulk densities above 1 g cm^-³ and only up to 55 % of volumetric soil moisture. Peat soils, in contrast, are characterized by high organic matter content, low bulk densities, and high soil moisture when saturated. This makes peatlands a challenging environment for any soil moisture monitoring, including CRNS. In such adverse conditions, questions remain on the appropriate CRNS calibration approach and therefore the accurate determination of soil moisture.

This study presents lessons learned from operating a CRNS at a fen site with extensively used grassland in Northeast Germany (nature conservation area “Kremmener Luch”) for 3.5 years. The CRNS was complemented with point-scale soil moisture sensor profiles down to 1 m (FDR and TDR) in several locations of its footprint as well as groundwater level observations to identify periods of ponding that occur frequently at the site. Measuring soil moisture with the dielectric point-scale sensors showed challenges on its own. We increased the precision of point-scale data by a local soil specific calibration relating sensor permittivity to soil moisture. However, strong jumps and unreliable values remained, presumably due to swelling and shrinking of the organic-rich soil and loss of contact with the sensor. FDR and TDR time series showed large differences in absolute values as well as spatially different soil moisture regimes due do effects of microtopography. This is opposed to the CRNS, which senses average water content independent of small-scale heterogeneities. To derive a CRNS soil moisture time series we tested calibrating the CRNS using data from dedicated soil moisture sampling campaigns or the point-scale time series. We obtained unrealistically high CRNS-soil moisture regardless of which calibration function we chose – the standard “Desilets’ equation” or the recently proposed advanced “Universal Transport Solution”. Following the suggestion in previous CRNS studies conducted at peaty sites, we adjusted the parameters of the Desilets’ equation, which lead to a more realistic soil moisture range. However, the estimation of the CRNS integration depth with the standard procedures is very sensitive to the low bulk density of the organic soil and remains largely uncertain. This data set serves as a valuable testbed for extending the validity of existing calibration and weighting functions, and we will utilize neutron simulations to enhance our understanding of the vertical footprint of CRNS under conditions of low bulk density and high soil moisture.

Improved understanding and precision of CRNS soil moisture in peatlands can support peatland restoration efforts by providing insights into near-surface soil moisture variations allowing the evaluation of water level management success.

How to cite: Grosse, P., Scheiffele, L., Dobkowitz, S., Dimitrova-Petrova, K., Rasche, D., and Oswald, S.: Adverse conditions for cosmic-ray neutron sensing: high water content low bulk density – can we still infer soil moisture over the full moisture range?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11935, https://doi.org/10.5194/egusphere-egu25-11935, 2025.

In the past 15 years, Cosmic-Ray Neutron Sensing (CRNS) has evolved to a useful tool for monitoring soil moisture at the field scale. Given the large measurement radius of up to 200 metres and measurement depth of 20 to 30 centimetres, it overcomes small-scale heterogeneities and allows to estimate soil moisture at spatio-temporal scales which are required to e.g., inform environmental models or validate soil moisture products from remote sensing data.

CRNS relies on the inverse relationship between soil moisture and observed low-energy cosmic-ray neutrons. Higher soil moisture results in lower neutron intensities but also a higher statistical noise in the data. In combination with the strongly non-linear relationship between soil moisture and observed low-energy cosmic-ray neutrons, this leads to larger uncertainties for soil moisture estimates when the soil moisture is high. Therefore, CRNS is expected to provide most accurate soil moisture estimates at monitoring sites with generally drier soils. Knowledge gaps remain with respect to the use of CRNS and the response of measured neutron intensities at observation sites with very wet soils and even partial water cover.

Against this background, we explore the signal dynamics of observed thermal and epithermal neutron intensities in a wetland in north-eastern Germany. Placing two identical neutron detectors at two different locations in the wetland and with different fractions of water cover in their respective measurement footprint allows for an investigation of the sensitivity of observed neutron signals to variations in partial water cover and soil moisture changes in water-free areas. Site-specific signal dynamics are modelled using neutron transport simulations conducted with the URANOS model code as well as simplified approaches to gain understanding on the influence of water cover and soil moisture on thermal and epithermal neutron signals. Ultimately, the possibility of deriving soil moisture information in water-free areas from observed neutron intensities is explored.

Our analyses shed additional light on the potential of CRNS for soil moisture estimation and its sensitive measurement footprint at extreme and unfavourable monitoring sites.

How to cite: Rasche, D., Sachs, T., Kalhori, A., Wille, C., Morgner, M., Güntner, A., and Blume, T.: A worst-case scenario? Exploring low-energy cosmic-ray neutron signal dynamics in wetlands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6803, https://doi.org/10.5194/egusphere-egu25-6803, 2025.

Alpine snow cover is shaped by complex topography, wind and insulation patterns, causing strong lateral heterogeneity in snow water equivalent (SWE) within only a few meters distance. While common SWE observation methods are confined to a footprint area of a few square meters, above-snow cosmic ray neutron sensing (CRNS) detects secondary cosmogenic neutrons that can be translated to SWE from an area of several hectares. The large footprint size decreases the observation bias that is caused by the choice of measurement location in conventional methods. However, the large footprint size also decreases the control on other signal contributing factors. Cosmogenic neutrons are sensitive to all sources of ambient hydrogen, including soil moisture and vegetation. Partial snow cover poses an additional challenge, due to the dissimilar and non-linear contribution of snow-free and snow-covered areas. The predominant development of mountain snowpack into partial snow cover highlights the intricacy of the CRNS signal in the alpine domain. In this study, we explore the complementary value of close-range, mid-range and far-range remote sensing snow products for the characterization of alpine CRNS snow monitoring sites in Austria and Italy. Joined observations of satellite-based fractional snow cover (FSC) products of Sentinel-1 and -2 and MODIS, at a spatial resolution of 20 m, 60 m and 500 m, respectively, provide quasi-daily observations of the snow cover state within the CRNS footprint area. This allows us to identify site-specific snow season parameters and dynamics in the CRNS signal. Further, air-borne and terrestrial topographic lidar (ALS and TLS) campaigns under snow-free and snow-covered conditions provide detailed FCS, snow height distribution and topographic information at a high spatial resolution. The good compatibility of these products is shown by the overall low deviation between lidar derived FSC and Sentinel FSC products of ~11% and between lidar and MODIS FSC of ~13%. Paired with complementary, manual snow density measurements for the computation of distributed SWE and the calibration of the neutron count to SWE conversion, these observations allow us to evaluate the complexity and dynamics of the seasonal CRNS signal at alpine sites. The similarity in spatial resolution between CRNS and satellite-based remote sensing products points towards its high potential for bridging the gap between ground- and space-based snow observations. Dedicated neutron simulations and further investigations are needed to gain a better understanding of factors that contribute to neutron count dynamics in alpine terrain.

How to cite: Krebs, N., Schattan, P., Premier, V., Mejia-Aguilar, A., Fey, C., Bremer, M., and Rutzinger, M.: The additive value of multi-scale remote sensing snow products for alpine above-snow Cosmic Ray Neutron Sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8780, https://doi.org/10.5194/egusphere-egu25-8780, 2025.

The increasing adoption of Cosmic-Ray Neutron Sensors (CRNS), across research infrastructures and beyond, necessitates standardised and flexible processing tools. Such tools should be accessible to new users with little experience in CRNS, as well as support researchers investigating novel processing methodologies and developing new theoretical frameworks. Here we present neptoon; an open-source python tool, using a modular, expandable framework, to ensure long term viability and software sustainability. Building from previous CRNS processing tools, we will present the overall architecture of neptoon and how it implements established processing methodologies while maintaining extensibility for emerging approaches. We will demonstrate streamlined data processing workflows through our configuration system and graphical user interface. We will show how neptoon supports replicability when processing sensors, supporting rapid updates when needed. Furthermore, we will showcase how neptoon enables systematic testing of new processing theories for CRNS, such as alternative correction methods, leading to a software that supports both operational deployment and methodological research. Lastly we will outline our roadmap for neptoon, explaining features which will be implemented in the near future. By creating a fully documented software toolset for processing, we aim to support the growing community of CRNS users and researchers.

How to cite: Power, D., Zacharias, S., Erxleben, F., Rosolem, R., and Schrön, M.: neptoon: An extensible software package for processing CRNS data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18234, https://doi.org/10.5194/egusphere-egu25-18234, 2025.