Ten new insights in climate science 2024.

The years 2023 and 2024 were characterized by unprecedented warming across the globe, underscoring the urgency of climate action. Robust science advice for decision makers on subjects as complex as climate change requires deep cross- and interdisciplinary understanding. However, navigating the ever-expanding and diverse peer-reviewed literature on climate change is enormously challenging for individual researchers.

Are Northern Hemisphere boreal forest fires more sensitive to future aerosol mitigation than to greenhouse gas-driven warming?

Considerable interest exists in understanding how climate change affects wildfire activity. Here, we use the Community Earth System Model version 2 to show that future anthropogenic aerosol mitigation yields larger increases in fire activity in the Northern Hemisphere boreal forests, relative to a base simulation that lacks climate policy and has large increases in greenhouse gases. The enhanced fire response is related to a deeper layer of summertime soil drying, consistent with increased downwelling surface shortwave radiation and enhanced surface evapotranspiration.

Past and future trends of diurnal temperature range and their correlation with vegetation assessed by MODIS and CMIP6.

Temperature anomalies and changes in the diurnal temperature range (DTR) are expected to pose physiological challenges to biota; hence, both spatial and temporal variations in DTR provide important insights into temperature-induced stress in humans, animals, and vegetation. Furthermore, vegetation could dampen temperature variability. Here, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data of Land Surface Temperature (LST) to evaluate the global variation in DTR and its rate of change in spatial and temporal scales for the two decades spanning from 2001 to 2020.

Earlier emergence of a temperature response to mitigation by filtering annual variability.

The rate of global surface warming is crucial for tracking progress towards global climate targets, but is strongly influenced by interannual-to-decadal variability, which precludes rapid detection of the temperature response to emission mitigation. Here we use a physics based Green's function approach to filter out modulations to global mean surface temperature from sea-surface temperature (SST) patterns, and show that it results in an earlier emergence of a response to strong emissions mitigation. For observed temperatures, we find a filtered 2011-2020 surface warming rate of 0.

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections.

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone.

Global Radiative Impacts of Black Carbon Acting as Ice Nucleating Particles.

Black carbon (BC) aerosols from incomplete combustion generally warm the climate, but the magnitudes of their various interactions with climate are still uncertain. A key knowledge gap is their role as ice nucleating particles (INPs), enabling ice formation in clouds. Here we assess the global radiative impacts of BC acting as INPs, using simulations with the Community Earth System Model 2 climate model updated to include new laboratory-based ice nucleation parameterizations.

Delayed emergence of a global temperature response after emission mitigation.

A major step towards achieving the goals of the Paris agreement would be a measurable change in the evolution of global warming in response to mitigation of anthropogenic emissions. The inertia and internal variability of the climate system, however, will delay the emergence of a discernible response even to strong, sustained mitigation. Here, we investigate when we could expect a significant change in the evolution of global mean surface temperature after strong mitigation of individual climate forcers.

Efficacy of Climate Forcings in PDRMIP Models.

Quantifying the efficacy of different climate forcings is important for understanding the real-world climate sensitivity. This study presents a systematic multimodel analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models.

Frequency of extreme precipitation increases extensively with event rareness under global warming.

The intensity of the heaviest extreme precipitation events is known to increase with global warming. How often such events occur in a warmer world is however less well established, and the combined effect of changes in frequency and intensity on the total amount of rain falling as extreme precipitation is much less explored, in spite of potentially large societal impacts. Here, we employ observations and climate model simulations to document strong increases in the frequencies of extreme precipitation events occurring on decadal timescales.

Quantifying the Importance of Rapid Adjustments for Global Precipitation Changes.

Different climate drivers influence precipitation in different ways. Here we use radiative kernels to understand the influence of rapid adjustment processes on precipitation in climate models. Rapid adjustments are generally triggered by the initial heating or cooling of the atmosphere from an external climate driver.

Understanding Rapid Adjustments to Diverse Forcing Agents.

Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail.

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption.

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.

A PDRMIP multi-model study on the impacts of regional aerosol forcings on global and regional precipitation.

Atmospheric aerosols such as sulfate and black carbon (BC) generate inhomogeneous radiative forcing and can affect precipitation in distinct ways compared to greenhouse gases (GHGs). Their regional effects on the atmospheric energy budget and circulation can be important for understanding and predicting global and regional precipitation changes, which act on top of the background GHG-induced hydrological changes. Under the framework of the Precipitation Driver Response Model Inter-comparison Project (PDRMIP), multiple models were used for the first time to simulate the influence of regional (Asian and European) sulfate and BC forcing on global and regional precipitation.

Sensible heat has significantly affected the global hydrological cycle over the historical period.

Globally, latent heating associated with a change in precipitation is balanced by changes to atmospheric radiative cooling and sensible heat fluxes. Both components can be altered by climate forcing mechanisms and through climate feedbacks, but the impacts of climate forcing and feedbacks on sensible heat fluxes have received much less attention. Here we show, using a range of climate modelling results, that changes in sensible heat are the dominant contributor to the present global-mean precipitation change since preindustrial time, because the radiative impact of forcings and feedbacks approximately compensate.

Carbon dioxide physiological forcing dominates projected Eastern Amazonian drying.

Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyse the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature-driven circulation changes, but the magnitude is uncertain.

Climate Impacts From a Removal of Anthropogenic Aerosol Emissions.

Limiting global warming to 1.5 or 2.0°C requires strong mitigation of anthropogenic greenhouse gas (GHG) emissions.

Aerosol Absorption: Progress Towards Global and Regional Constraints.

Purpose Of Review: Some aerosols absorb solar radiation, altering cloud properties, atmospheric stability and circulation dynamics, and the water cycle. Here we review recent progress towards global and regional constraints on aerosol absorption from observations and modeling, considering physical properties and combined approaches crucial for understanding the total (natural and anthropogenic) influences of aerosols on the climate.

Recent Findings: We emphasize developments in black carbon absorption alteration due to coating and ageing, brown carbon characterization, dust composition, absorbing aerosol above cloud, source modeling and size distributions, and validation of high-resolution modeling against a range of observations.

Rapid adjustments cause weak surface temperature response to increased black carbon concentrations.

We investigate the climate response to increased concentrations of black carbon (BC), as part of the Precipitation Driver Response Model Intercomparison Project (PDRMIP). A tenfold increase in BC is simulated by 9 global coupled-climate models, producing a model-median effective radiative forcing (ERF) of 0.82 (ranging from 0.

PDRMIP: A Precipitation Driver and Response Model Intercomparison Project, Protocol and preliminary results.

As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for.