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We propose a novel Bayesian framework for changepoint detection in large-scale spherical spatiotemporal data, with broad applicability in environmental and climate sciences. Our approach models changepoints as spatially dependent…
Current merged precipitation products such as IMERG, GSMAP, and CMORPH combine satellite estimates from passive microwave (PMW) and infrared (IR) observations. However, the different information content of these sensors makes it challenging…
We describe the new global land water storage data set GLWS2.0, which contains total water storage anomalies (TWSA) over the global land except for Greenland and Antarctica with a spatial resolution of 0.5{\deg}, covering the time frame…
Astronomical observations of extended sources, such as cubes of integral field spectroscopy (IFS), encode auto-correlated spatial structures that cannot be optimally exploited by standard methodologies. This work introduces a novel…
Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space under the flow of an McKean-Vlasov-Ito process. This work…
The world ocean plays a key role in redistributing heat in the climate system and hence in regulating Earth's climate. Yet statistical analysis of ocean heat transport suffers from partially incomplete large-scale data intertwined with…
Convective available potential energy (CAPE) is an important variable for forecasting severe weather and understanding deep convection and precipitation. The latest versions of the Global Forecast System (GFS) and related Global Ensemble…
Species distribution models (SDMs) are widely used to predict species' geographic distributions, serving as critical tools for ecological research and conservation planning. Typically, SDMs relate species occurrences to environmental…
Zero-inflated data pose significant challenges in precipitation forecasting due to the predominance of zeros with sparse non-zero events. To address this, we propose the Zero Inflation Diffusion Framework (ZIDF), which integrates Gaussian…
Images taken with modern detectors require calibration via flat fielding to obtain the same flux scale across the whole image. One method for obtaining the best possible flat fielding accuracy is to derive a photometric model from dithered…
The under-representation of cloud formation is a long-standing bias associated with climate simulations. Parameterisation schemes are required to capture cloud processes within current climate models but have known biases. We overcome these…
Precise, unbiased measurements of extragalactic background anisotropies require careful treatment of systematic effects in fluctuation-based, broad-band intensity mapping measurements. In this paper we detail improvements in methodology for…
Meridional flow is thought to play a very important role in the dynamics of the solar convection zone; however, because of its relatively small amplitude, precisely measuring it poses a significant challenge. Here we present a complete…
Accurate solar power forecasting is crucial to integrate photovoltaic plants into the electric grid, schedule and secure the power grid safety. This problem becomes more demanding for those newly installed solar plants which lack sufficient…
Velocity fields in the cosmic web are fundamental to structure formation but remain difficult to observe directly beyond the linear regime. Here we present observational evidence that galaxy filaments connecting pairs of galaxy clusters…
Context: The study of variations in total solar irradiance (TSI) is important for understanding how the Sun affects the Earth's climate. Aims: Full-disk continuum images and magnetograms are now available for three full solar cycles. We…
We perform a reanalysis of the BOSS CMASS DR12 galaxy dataset using a simulation-based emulator for the Wavelet Scattering Transform (WST) coefficients. Moving beyond our previous works, which laid the foundation for the first galaxy…
Satellite Image Time Series (SITS) is crucial for agricultural semantic segmentation. However, Cloud contamination introduces time gaps in SITS, disrupting temporal dependencies and causing feature shifts, leading to degraded performance of…
When inverting solar spectra, image degradation effects that are present in the data are usually approximated or not considered. We develop a data reduction method that takes these issues into account and minimizes the resulting errors. By…
Understanding the lifetime of CO2 in the atmosphere is critical for predictions regarding future climate changes. A simple mass conservation analysis presented here generates tight estimations for the atmosphere's retention time constant.…