AbstractOn behalf of the journal, AGU, and the scientific community, the editors of Geophysical Research Letters would like to sincerely thank those who reviewed manuscripts for us in 2023. The hours reading and commenting on manuscripts not only improve the manuscripts, but also increase the scientific rigor of future research in the field. With the advent of AGU's data policy, many reviewers have also helped immensely to evaluate the accessibility and availability of data, and many have provided insightful comments that helped to improve the data presentation and quality. We greatly appreciate the assistance of the reviewers in advancing open science, which is a key objective of AGU's data policy. We particularly appreciate the timely reviews in light of the demands imposed by the rapid review process at Geophysical Research Letters. We received 4,512 submissions in 2023 and 5,112 reviewers contributed to their evaluation by providing 8,587 reviews in total. We deeply appreciate their contributions.

Idealized general circulation models (GCMs) suggest global-mean precipitation ceases to increase with warming in hot climates. However, it is unclear if this occurs in more comprehensive GCMs. Here, we examine precipitation over a wide range of climates simulated with comprehensive GCMs. We find that in the Community Atmosphere Model, global-mean precipitation increases approximately linearly with global-mean surface temperatures up to about 330~K, where it peaks at 5~mm~day$^{-1}$. Beyond 330~K, global-mean precipitation decreases substantially despite increasing surface temperatures. This occurs because of increased atmospheric shortwave absorption from water vapor, which limits shortwave radiation available for surface evaporation. Precipitation decreases in the tropics and subtropics, but continues to increase in the extratropics due to increased poleward moisture transport. Precipitable water increases everywhere, resulting in longer water-vapor residence times and implying more episodic precipitation. Other GCMs indicate global-mean precipitation might exhibit a smaller maximum rate and begin to decrease at lower surface temperatures.

Abstract The hydrological cycle in South America during austral summer, including extreme precipitation and floods, is significantly influenced by northerly Low-Level Jets (LLJs) along the eastern Andes. The LLJ represents a synoptic weather event characterized by different types (Central, Northern, and Andes). Given that numerous characteristics of the LLJ are sensitive to large-scale climate forcing originating remotely, this study aims to understand how tropical forcings, such as the El Niño/Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), regulate the duration and frequency of each LLJ type on low-frequency time scales and related impacts in precipitation changes based on reanalysis and gauge-based datasets. Our analysis reveals that ENSO and PDO are pivotal in driving the variability of LLJs over the past sixty years. Specifically, the central LLJ type is more prevalent during El Niño years and warm PDO phases, leading to heightened extreme precipitation in southern South America. Conversely, La Niña years during cold PDO phases tend to favor the Northern and Andes LLJs, which are associated with increased precipitation extremes in the western and southeastern parts of the Amazon. Typically, LLJs tend to persist longer during these favored conditions, causing more pronounced precipitation events in the areas under the influence of the LLJs. This study enhances our understanding of the influence of large-scale atmospheric forcings on the regional precipitation dynamics in South America.

AbstractThe ionospheric convection electric field is often assumed to be a potential field. This assumption is not always valid, especially when the ionosphere changes on short time scales min. We present a technique for estimating the induction electric field using ground magnetometer measurements. The technique is demonstrated on real and simulated data for sudden increases in solar wind dynamic pressure of 1 and 10 nPa, respectively. For the real data, the ionospheric induction electric field is 0.15 0.015 mV/m, and the corresponding compressional flow is 2.5 0.3 m/s. For the simulated data, the induction electric field and compressional flow reach 3 mV/m and 50 m/s, respectively. The induction electric field can locally constitute tens of percent of the total electric field. Inclusion of the induction electric field increased the total Joule heating by 2.4%. Locally the Joule heating changed by tens of percent. This corresponds to energy dissipation that is not accounted for in existing models.

The efficiency of marine cloud brightening in cooling Earth’s surface temperature is investigated by using a medium ensemble of simulations with the Community Earth System Model version 2 (CESM2). Various cloud seeding schemes based on susceptibility are examined to determine what area extent will be required to induce 1C cooling under SSP2-4.5. The results indicate that cloud seeding over 5% of the ocean area is capable of achieving this goal. Under this seeding scheme, cloud seeding is mainly deployed over lower latitudes where strong surface temperature and precipitation responses are induced. The simulations also reveal that the 5% cloud seeding scheme induces an overall reduction in global precipitation, with an increase over land and a decrease over the ocean.

To address the effect of stratiform latent heating on meso- to large scale circulations, an enhanced implementation of the Multiscale Coherent Structure Parameterization (MCSP) is developed for the Met Office Unified Model. MCSP represents the top-heavy stratiform latent heating from under-resolved organized convection in general circulation models. We couple the MCSP with a mass-flux convection scheme (CoMorph-A) to improve storm lifecycle continuity. The improved MCSP trigger is specifically designed for mixed-phase deep convective cloud, combined with a background vertical wind shear, both known to be crucial for stratiform development. We also test a cloud top temperature dependent convective-stratiform heating partitioning, in contrast to the earlier fixed partitioning. Assessments from ensemble weather forecasts and decadal simulations demonstrate that MCSP directly reduces cloud deepening and precipitation areas by moderating mesoscale circulations. Indirectly, it amends tropical precipitation biases, notably correcting dry and wet biases over India and the Indian Ocean, respectively. Remarkably, the scheme outperforms a climate model ensemble by improving seasonal precipitation cycle predictions in these regions. This enhancement is partly due to the scheme’s refinement of Madden-Julian Oscillation (MJO) spectra, achieving better alignment with reanalysis data by intensifying MJO events and maintaining their eastward propagation after passing the Maritime Continent. However, the scheme also increases precipitation overestimation over the Western Pacific. Shifting from fixed to temperature-dependent convective-stratiform partitioning reduces the Pacific precipitation overestimation but also lessens the improvements of seasonal cycle in India. Spatially correlated biases highlight the necessity for advancements beyond deterministic approaches to align MCSP with environmental conditions.

A Variable-Resolution, global configuration of the Community Earth System Model (VR-CESM) in which the atmosphere and land are the only active components is employed to investigate the climate of the Euro-Mediterranean region. Two variable-resolution grids with regionally-refined resolutions of 0.25° and 0.125° over the study domain, respectively, are used. The fidelity of these VR-CESM simulations is evaluated considering the near-surface air temperature and precipitation fields for the 2000-2014 period in comparison to available observation-based datasets and those of a coarse resolution (quasi-uniform 1°) control simulation. Our analysis shows that, as a global model, VR-CESM is a promising alternative to regional climate models to advance our understanding of the Euro-Mediterranean climate. The improvements obtained are mainly related to a better representation of the complex topography of the region with higher resolution. Increasing the regional resolution to 0.25° generally yields considerable improvements over the control simulation, however some persistent biases remain. Doubling the highest resolution to 0.125° leads to only modest improvements, primarily in the representation of small-scale processes including representation of extreme events that are of substantial relevance for the present and future of the regional climate.

<div class="section abstract"><div class="htmlview paragraph">Evaluating real-world hazards associated with perception subsystems is critical in enhancing the performance of autonomous vehicles. The reliability of autonomous vehicles perception subsystems are paramount for safe and efficient operation. While current studies employ different metrics to evaluate perception subsystem failures in autonomous vehicles, there still exists a gap in the development and emphasis on engineering requirements. To address this gap, this study proposes the establishment of engineering requirements that specifically target real-world hazards and resilience factors important to AV operation, using High-Definition Maps, Global Navigation Satellite System, and weather sensors. The findings include the need for engineering requirements to establish clear criteria for a high-definition maps functionality in the presence of erroneous perception subsystem inputs which enhances the overall safety and reliability of the autonomous vehicles. In conjunction, global navigation satellite system consistently provides highly accurate positional information, thereby enabling precise navigation and trajectory. Additionally, a requirement was formulated that mandates the integration of weather sensors into the autonomous vehicles perception subsystem to collect precise weather condition data. These findings show the significance of implementing engineering requirements utilizing resilient engineering as a fundamental aspect of evaluating perception sensor performance in real-world scenarios. By incorporating these requirements into autonomous vehicles development we can improve the safety and reliability of these vehicles and accelerate the adoption of autonomous vehicle technology.</div></div>

Abstract Operational agencies face significant challenges related to the verification and evaluation of weather forecasts. These challenges were investigated in a series of online workshops and polls engaging operational personnel from six countries. Five key themes emerged: inadequate verification approaches for both existing and emerging products; incomplete and uncertain observations; difficulties in accurately capturing users’ real-world experiences using simplified metrics; poor communication and understanding of forecasts and complex verification information; and institutional factors such as limited resources, evolving meteorologist roles, and concerns over reputational damage. We identify nearly 50 operationally relevant scientific questions and suggest calls to action. Addressing these needs includes designing forecast systems with verification as a central consideration, enhancing the availability of observations, and developing and adopting community software systems. Additionally, we propose the establishment of an international community comprising environmental and social science researchers, statisticians, verification practitioners, and users to provide sustained support for this collective endeavor.