National Institute for Space Research,Ministry of Science, Technology and Innovation

Future projections of South American (SA) monsoon precipitation from the Coupled Model Intercomparison Project phase 6 (CMIP6) show a consistent drying during the early part of the monsoon season (September–November), which is also seen in a convection-permitting model simulation. Using a set of idealized atmosphere-only general circulation model (GCM) experiments, this drying signal is shown to be mainly driven by sea surface temperature (SST) changes: uniform SST warming and patterned SST change. Different processes appear to be more important in different months for the ensemble mean drying signal, with this primarily driven by SST pattern change in October and by uniform SST warming in November. There is significant intermodel uncertainty in the SA monsoon precipitation response to each of these drivers, particularly SST pattern change. For uniform SST warming, an existing hypothesis, which suggests that SA monsoon drying is driven by the enhanced land–sea temperature contrast, is tested, but we find that this process is not dominant. For patterned SST warming, moderate intermodel correlations (across the coupled CMIP6 models) are found between SA monsoon precipitation change and changes in meridional and zonal Atlantic SST gradients. In November, a combined zonal and meridional Atlantic SST gradient index can explain more than half of CMIP6 intermodel uncertainty in SA monsoon core region precipitation change.

We present the first application of marked power spectra to weak lensing data, using maps from the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) survey. Marked convergence fields, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. Using simulations tailored to the HSC-Y1 data, we test three mark functions that up- or down-weight different density environments. Our results show that combining multiple types of marked auto and cross-spectra improves constraints on the clustering amplitude parameter $S_8\equiv \sigma _8\sqrt{\Omega _{\rm m}/0.3}$ by $\approx$43 per cent compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on $S_8 = 0.807\pm 0.024$. We assess the sensitivity of the marked power spectra to systematics, including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias. We note that some of the additional information introduced by the marked field originates from scales smaller than the scale cut, and is partly Gaussian in nature. This does not invalidate our systematic tests. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.

The w(dagger) VCDM (V-cold dark matter) framework provides a theoretically well-controlled extension of ACDM within the class of minimally modified gravity theories, allowing for flexible cosmological background evolution and linear perturbation dynamics while remaining free of pathological instabilities. In this work, we have shown that this scenario remains robust when confronted with current cosmological observations, even in the presence of an extended neutrino sector. Combining Planck CMB data with the Dark Energy Spectroscopic Instrument Data Release 2 baryon acoustic oscillations (BAO) and PantheonPlus, we obtain stringent constraints on neutrino physics, including Sigma m(nu) <0.12 eV (95% confidence level) and N-eff = 3.114(-0.128)(+0.139) fully consistent with Standard Model expectations within 16. Crucially, the data exhibit a statistically significant preference for a late-time dark-energy transition, characterized by a robust quintessence-phantom crossing that remains stable across all dataset combinations and neutrino-sector extensions, including the presence of a sterile neutrino. The combined effects of modified late-time expansion and additional relativistic degrees of freedom systematically raise the inferred Hubble constant, substantially alleviating the H-0 tension without invoking early dark energy or introducing theoretical instabilities. Overall, the w(dagger )VCDM scenario emerges as a compelling phenomenological framework that simultaneously accommodates current constraints on neutrino physics, provides an excellent fit to recent BAO and supernovae data, and offers a viable pathway toward resolving persistent tensions in the standard cosmological model.

Accurately tracking the global distribution of precipitation is essential for both research and operational meteorology. Satellite observations remain the only means of achieving consistent, global precipitation monitoring. While machine learning has long been applied to satellite-based precipitation retrieval, the absence of a standardized benchmark dataset has hindered fair comparisons between methods. To address this, the International Precipitation Working Group has developed SatRain, the first AI benchmark dataset for satellite-based detection and estimation of rain. SatRain integrates multi-sensor satellite observations from the primary platforms used in precipitation remote sensing with high-quality reference precipitation estimates derived from gauge-corrected ground-based radar composites over the conterminous United States. It offers a standardized evaluation protocol and out-of-distribution testing data from Asia and Europe to enable robust and reproducible comparisons across machine learning approaches. In addition to algorithm evaluation, the diversity of sensors and inclusion of time-resolved geostationary observations make SatRain a valuable foundation for developing next-generation AI models to deliver more accurate global precipitation estimates.

In this study we investigate potential large-angle anisotropies in the angular distribution of the cosmological parameters H-0 (the Hubble constant) and Omega(m) (the matter density) in the flat-Lambda CDM framework, using the Pantheon+SH0ES supernovae catalog. For this we perform a directional analysis by dividing the celestial sphere into a set of directions, and estimate the best-fit cosmological parameters across the sky using a MCMC approach. Our results show a dominant dipolar pattern for both parameters in study, suggesting a preferred axis in the universe expansion and in the distribution of matter. However, we also found that for z greater than or similar to 0.015, this dipolar behavior is not statistically significant, confirming the expectation -in the Lambda CDM scenario- of an isotropic expansion and a uniform angular distribution of matter (both results at 1 sigma confidence level). Nevertheless, for nearby supernovae, at distances less than or similar to 60 Mpc or z less than or similar to 0.015, the peculiar velocities introduce a highly significant dipole in the angular distribution of H-0. Furthermore, we perform various robustness tests that support our findings, and consistency tests of our methodology.