Anthropogenic activity drives extensive tropical deforestation, particularly in Southeast Asia where 16% of total forest cover was lost between 2000 and 2020. While land surface changes significantly affect the atmosphere, their net impact on convective clouds is not well-constrained. Here, we use satellite data to provide the first observational evidence that long-term deforestation in Southeast Asia robustly alters cloud properties, and that the magnitude of this response depends on the atmospheric environment. Deforestation drives a shift towards more widespread, shallower clouds during the daytime, with amplified effects in dry inland areas compared with moist coastal regions. Aerosols only weakly modulate the cloud fraction response, but offset the cloud top height response to deforestation, suggesting the influence of aerosol indirect effects. We conclude that the local signature of forest loss is not uniform, and regional differences in climatology must be considered when assessing deforestation impacts on clouds and the climate system.

Since 2007, the National Academy for Sciences Engineering and Medicine (NASEM) has recommended priorities for Earth Science research and investment every ten years. The Decadal Survey balances the continuation of essential climate variable time series against unmet measurement needs and new Earth Observations made possible by technological breakthroughs. The next survey (2027-2028, DS28) must anticipate the observational needs of the 2030s-2040s, a world increasingly dominated by climate extremes and a rapidly changing Earth system. Here, we identify the critical Earth Observation needs for a hotter, more extreme world where expect challenges in maintaining a safe operating space.

This article addresses the intricate interactions between climate change and the spread of infectious diseases, highlighting key scientific perspectives. The mechanisms through which climate change influences the epidemiology of these diseases are examined, considering climatic variables, changes in vector patterns, and pathogen adaptation. Additionally, the relationship between extreme weather events and the occurrence of epidemic outbreaks is explored. Findings reveal the necessity of integrated approaches and public health policies to mitigate emerging impacts on global health.

Global climate change is often thought of as a steady and approximately predictable physical response to increasing forcings, which then requires commensurate adaptation. But adaptation has practical, cultural and biological limits, and climate change may pose unanticipated global hazards, sudden changes or other surprises, as may societal adaptation and mitigation responses. We outline a strategy for better accommodating these challenges by making climate science more integrative, in order to identify and quantify known and novel physical risks even–or especially–when they are highly uncertain, and to explore risks and opportunities associated with mitigation and adaptation responses by engaging across disciplines. This improves the chances of anticipating potential surprises and identifying and communicating “safe landing” pathways that meet UN Sustainable Development Goals and guide humanity toward a better future.

Observed increases in wildfire activity across the contiguous United States, which have occurred amid a warming climate and expanding residential footprint within flammable landscapes, illustrate the urgency of understanding near-future changes in fire regimes. Here, we use a statistical model including future projections of both human population distribution and atmospheric conditions from climate models to predict the number, size, and cumulative area burned by wildfires. We find an overall increase in both the number of fires (+56%) and total burned area (+60%) during 2020-2060 relative to a 1984-2019 baseline, as well as ubiquitous increases in area burned (+63%) by the largest fires. Additionally, we predict the emergence of observationally unprecedented fire frequency in eastern U.S. locations where wildfire was rare historically (+71%), and unprecedented increases in the size of the largest fires in the Western U.S. where fires were historically common—underscoring the need to prepare for more frequent and severe fire even in communities unaccustomed to them.

Existing stochastic rainfall generators (SRGs) are typically limited to relatively small domains due to spatial stationarity assumptions, hindering their usefulness for flood studies in large basins. This study proposes StormLab, an SRG that simulates precipitation events at 6-hour and 0.03° resolution in the Mississippi River Basin (MRB). The model focuses on winter and spring storms caused by strong water vapor transport from the Gulf of Mexico—the key flood-generating storm type in the basin. The model generates anisotropic spatiotemporal noise fields that replicate local precipitation structures from observed data. The noise is transformed into precipitation through parametric distributions conditioned on large-scale atmospheric fields from a climate model, reflecting both spatial and temporal nonstationarity. StormLab can produce multiple realizations that reflect the uncertainty in fine-scale precipitation arising from a specific large-scale atmospheric environment. Model parameters were fitted for each month from December-May, based on storms identified from 1979-2021 ERA5 reanalysis data and AORC precipitation. Validation showed good consistency in key storm characteristics between StormLab simulations and AORC data. StormLab then generated 1,000 synthetic years of precipitation events based on 10 CESM2 ensemble simulations. Empirical return levels of simulated annual maxima agreed well with AORC data and displayed bounded tail behavior. To our knowledge, this is the first SRG simulating nonstationary, anisotropic high-resolution precipitation over continental-scale river basins, demonstrating the value of conditioning such stochastic models on large-scale atmospheric variables. The simulated events provide a wide range of extreme precipitation scenarios that can be further used for design floods in the MRB.

A document by Raj Pandya. Click on the document to view its contents.

Examination of historical simulations from CMIP6 models shows substantial pre-industrial to present-day changes in ocean heat (ΔH), salinity (ΔS), oxygen (ΔO2), dissolved inorganic carbon (ΔDIC), chlorofluorocarbon-12 (ΔCFC12), and sulfur hexafluoride (ΔSF6). The spatial structure of the changes and the consistency among models differ among tracers: ΔDIC, ΔCFC12, and ΔSF6 all are largest near the surface, are positive throughout the thermocline with weak changes below, and there is good agreement amongst the models. In contrast, the largest ΔH, ΔS, and ΔO2 are not necessarily at the surface, their sign varies within the thermocline, and there are large differences among models. These differences between the two groups of tracers are linked to climate-driven changes in the ocean transport, with this tracer “redistribution” playing a significant role in changes in ΔH, ΔS, and ΔO2 but not the other tracers. Tracer redistribution is prominent in the southern subtropics, in a region where apparent oxygen utilization and ideal age indicate increased ventilation time scales. The tracer changes are linked to a poleward shift of the peak Southern Hemisphere westerly winds, which causes a similar shift of the subtropical gyres, and anomalous upwelling in the subtropics. This wind - tracer connection is also suggested to be a factor in the large model spread in some tracers, as there is also a large model spread in wind trends. A similar multi-tracer analysis of observations could provide insights into the relative role of the addition and redistribution of tracers in the ocean.

Diapycnal mixing in the ocean interior is largely fueled by internal tides. Mixing schemes that represent the breaking of internal tides are now routinely included in ocean and earth system models applied to the modern and future. However, this is more rarely the case in climate simulations of deep-time intervals of the Earth, for which estimates of the energy dissipated by the tides are not always available. Here, we present and analyze two IPSL-CM5A2 earth system model simulations of the Early Eocene made under the framework of DeepMIP. One simulation includes mixing by locally dissipating internal tides, while the other does not. We show how the inclusion of tidal mixing alters the shape of the deep ocean circulation, and thereby of large-scale biogeochemical patterns, in particular dioxygen distributions. In our simulations, the absence of tidal mixing leads to a deep North Atlantic basin mostly disconnected from the global ocean circulation, which promotes the development of a basin-scale pool of oxygen-deficient waters, at the limit of complete anoxia. The absence of large-scale anoxic records in the deep ocean posterior to the Cretaceous anoxic events suggests that such an ocean state most likely did not occur at any time across the Paleogene. This highlights how crucial it is for climate models applied to the deep-time to integrate the spatial variability of tidally-driven mixing as well as the potential of using biogeochemical models to exclude aberrant dynamical model states for which direct proxies do not exist.

In this study, we employed random forest machine learning classification to assess the current state of glaciers in the western United States using Sentinel-2A satellite imagery. By analyzing Sentinel-2A imagery from September 2020 and comparing it to the RGI inventory, the study determined the current conditions of the glaciers. Our findings unveiled a significant reduction in both glacier area and volume in the western United States since the mid-20th century. Currently, the region hosts 4091 glaciers spanning seven states, covering a total area of 432.01 km2 with a corresponding volume of 9.02 km3. During the study period, a loss of 237.07 km2 in glacier area was observed, representing a 35.43% decrease when contrasted with the RGI boundaries. The volume lost during this period amounted to 4.9 km3, roughly equivalent to 4.7 gigatons of water. Among the states, Washington experienced the most significant glacier area reduction, with a loss of 130.06 km2. Notably, glaciers in the North Cascade Range of Washington, such as those in Mt. Baker and Mt. Shuksan, now cover, on average, only 85% of their original glacier boundaries with ice and snow at the conclusion of the 2020 hydrological year. Major glaciers, including the White River glacier, West Nooksack glacier, and White Chuck glacier, have lost more than 50 percent of their original area.

A document by Omon Obarein. Click on the document to view its contents.

A document by Charlie Mydlarz. Click on the document to view its contents.

This work introduces the results of an intensive 15-day surface observation campaign of methane (CH4) and adapts a new analytical method to compute and attribute CH4 emissions. The selected area has a high atmospheric concentration of CH4 (campaign-wide minimum/mean/standard deviation/max observations: 2.0, 2.9, 1.3, and 16 ppm) due to a rapid increase in the mining, production, and use of coal over the past decade. Observations made in concentric circles at 1km, 3km, and 5km around a high production high gas coal mine were used with the mass conserving model free emissions estimation approach adapted to CH4, yielding emissions of 0.73, 0.28, and 0.15 ppm/min respectively. Attribution used a 2-box mass conserving model to identify the known mine’s emissions from 0.042-5.3 ppm/min, and a previously unidentified mine’s emission from 0.22-7.9 ppm/min. These results demonstrate the importance of quantifying the spatial distribution of methane in terms of control of regional-scale CH4 emissions.

Precipitation projections in transient climate change scenarios have been extensively studied over multiple climate model generations. Although these simulations have also been used to make projections at specific Global Warming Levels (GWLs), dedicated simulations are more appropriate to study changes in a stabilising climate. Here, we analyse precipitation projections in six multi-century experiments with fixed atmospheric concentrations of greenhouse gases, conducted with the UK Earth System Model (UKESM) and which span a range of GWLs between 1.5 and 5°C of warming. Regions are identified where the sign of precipitation trends in high-emission transient projections is reversed in the stabilisation experiments. For example, stabilisation reverses a summertime precipitation decline across Europe. This precipitation recovery occurs concurrently with changes in the pattern of Atlantic sea surface temperature trends due to a slow recovery of the Atlantic Meridional Overturning Circulation in the stabilisation experiments, along with changes in humidity and atmospheric circulation.

The Arctic is notable as a region where the greatest rate of increase in precipitation associated with global warming is anticipated. The Arctic precipitation simulated by the Coupled Model Intercomparison Project phase 6 multimodels showed a strong increasing trend in the recent past since the 1980s as a result of the continued strengthening of greenhouse gas forcing. Meanwhile, the suppression by aerosol forcing, which dominated in earlier periods, has been leveled off. From an energetic perspective, the constraining factors of increased atmospheric radiative cooling and reduced heat transport from lower latitudes contributed equally to the recent increase in Arctic precipitation. Future Arctic precipitation will change in proportion to the temperature change, but the fractional contributions of the constraining factors will remain stable across various scenarios. The implications for the doubling of the Arctic amplification factor of precipitation changes relative to that of temperature changes are also discussed.

Shifts in Southern Ocean (SO, $40 - 85^{o}S$) shortwave cloud feedback ($SW_{FB}$) toward more positive values are the dominant contributor to higher effective climate sensitivity (ECS) in Coupled Model Intercomparison Project phase 6 (CMIP6) models. To provide an observational constraint on the SO $SW_{FB}$, we use a simplified physical model to connect SO $SW_{FB}$ with the response of column-integrated liquid water mass (LWP) to warming and the susceptibility of albedo to LWP in 50 CMIP5 and CMIP6 GCMs. In turn, we predict the responses of SO LWP using a cloud-controlling factor (CCF) model. The combination of the CCF model and radiative susceptibility explains about $50$\% of the variance in the GCM-simulated $SW_{FB}$ in the SO. Observations of SW radiation fluxes, LWP, and CCFs from reanalysis are used to constrain the SO $SW_{FB}$. The response of SO LWP to warming is constrained to $2.76\ -\ 4.19$ $g\ m^{-2}\ K^{-1}$, relative to a GCM prior of $0.64\ -\ 9.33$ $g\ m^{-2}\ K^{-1}$. The susceptibility of albedo to LWP is constrained to be $0.43\ -\ 0.90$ $ (kg\ m^{-2})^{-1}$, relative to $0.30\ -\ 3.91$ $(kg\ m^{-2})^{-1}$. The overall constraint on the contribution of SO to global mean $SW_{FB}$ is $-0.168\ -\ 0.051$ $W\ m^{-2}\ K^{-1}$, relative to $-0.277\ -\ 0.270$ $ W m^{-2} K^{-1}$. In summary, observations suggest SO $SW_{FB}$ is less likely to be as extremely positive as predicted by some CMIP6 GCMs, but more likely to range from moderate negative to weakly positive.

The global carbon dioxide (CO2) concentration has shown a consistent and substantial increase over the years, representing the dominant component of greenhouse gases (GHGs). Hence, there is an urgent demand to accurately quantify a broad spectrum of CO2 concentration at a fine-scale level to aid policymakers in making informed decisions. Consequently, we present a novel method aimed at addressing the scarcity of ground-based data, enabling the generation of a globally large-scale, continuous CO2 concentration data product.In consideration of the requirements for temporal and spatial coverage of remote sensing imagery, we opt for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, which provides daily surface reflectance of MODIS bands 1 to 7 at resolutions of 500m and 1km.Carbon satellites have developed rapidly and performed well in retrieving the vertically integrated atmospheric column CO2(XCO2) concentrations, which can provide independent top-down CO2 concentration evaluations. Here, the new generated Orbiting Carbon Observatory 3 (OCO-3) with 1.6 km×2.2 km (across × along track) resolution is added three Near Infrared (NIR) wavelength bands, which guarantees a higher accuracy of XCO2 than OCO-2.In this study, we propose a regression model-based method that leverages MODIS data and OCO-3 XCO2 data for training regression models and predicting CO2 concentrations. The proposed method enables rapid establishment of the relationship between MODIS surface reflectivity and CO2 concentration, facilitating the generation of continuous CO2 concentration maps over a large geographical area. Moreover, it offers reliable information for regions lacking ground-based CO2 measurements, such as suburban areas.Additionally, to validate the accuracy of the generated XCO2 data product, we utilize the Total Carbon Column Observing Network (TCCON) as an essential validation source. Upon evaluation, it was observed that the relative errors for each month of the year 2020 at the respective TCCON  sites consistently remained below 2%.  This finding suggests that the proposed method possesses the potential for expansion to additional geographical regions and temporal spans, whilst sustaining a high level of precision.

A document by Antoine Hermant. Click on the document to view its contents.

Recent advances in regional climate modelling include finer-scale simulations that can partially resolve deep convective processes. These convection-permitting models can help provide insight on how regional distributions of hazardous convection could evolve in possible future climates. However, the use of these models for representing climatologies of severe wind gusts related to convection has not been explored in detail, including for Australian regional climate. As a result, future projections of this hazard have mostly been estimated using changes in the large-scale environment from global climate models, with significant uncertainties related to this method. Here, we present findings on the ability of a regional, convection-permitting climate model in representing severe wind gusts associated with convection in southeastern Australia. We also examine future changes in the frequency and intensity of severe convective wind events as represented by this convection-permitting model, and compare these with changes in the large-scale environment from the global climate model that forces these simulations.

A document by Sushel Unninayar. Click on the document to view its contents.

Marine Isotope Stage (MIS) 5c, between ~106,000 and ~93,000 years ago, represents an important warm period on Earth in which the current anthropogenic warming can be contextualized. Although viewed as a pronounced interstadial, its climate expression is regionally disparate, with different regions on Earth showing evidence of either cooler conditions than modern-day or warmer conditions than modern-day. It is therefore important to expand temperature reconstructions to different regions on Earth to gain a better picture of climate dynamics during MIS 5c. In Alaska, there are no quantitative temperature reconstructions for MIS 5c, vastly limiting our knowledge of temperature changes in this climatically sensitive high-latitude region. Here, we fill-in this gap by providing the first quantitative temperatures from MIS 5c in Alaska using hydrogen isotopes from fluid inclusions in precisely dated speleothems. We find that regional temperatures during MIS 5c were within error of modern-day (2021 CE) temperatures, likely representing the most recent time period that regional temperatures were as high as modern-day.

A document by Hao Zhou. Click on the document to view its contents.

An attempt has been made to quantitatively analyze different degrees of environmental drought events, given the limited scientific understanding of environmental droughts, which hinders practical assessment efforts. This study thus aims to rigorously develop and assess the applicability of a novel heuristic method in conjunction with creating an Environmental Drought Index \cite{Srivastava_2023}. The heuristic method evaluates the combined influences of drought duration and water shortage levels, providing crucial insights into the environmental flow requirements amidst climate change. The Minimum in-stream Flow Requirements (MFR) is first defined as the threshold value essential for sustaining the river basin's ecological functions, aligning with Tennant’s environmental flow concept. Establishing MFR enables a balance between water resource utilization and ecological preservation, fostering sustainable water management. To comprehensively assess the eco-status, the study defined the High Flow Season (HFS) and the Low Flow Season (LFS). Drought status is then determined by comparing MFR with observed streamflow rate, quantifying negative differences as environmental droughts. Drought Duration Length (DDL) and Water Shortage Level (WSL) are introduced as functions of environmental drought. DDL categorizes consecutive months into four classes: DDL 1 (1-3 months), DDL 2 (4-6 months), DDL 3 (7-12 months), and DDL 4 (>12 months). WSL is determined by the most significant water deficit observed during DDL, classified into four categories: WSL 1 (<40%), WSL 2 (40-60%), WSL 3 (60-80%), and WSL 4 (>80%). Integrating DDL and WSL yields an index classifying environmental drought events into slight, moderate, severe, and extreme levels. The index value is obtained by comparing DDL and WSL values and selecting the maximum. The study enhances the scientific rigor of environmental drought identification and analysis, contributing to understanding drought impacts and effective mitigation strategies.  

The paper presents a new method for the decomposition of the horizontal wind divergence among the linear wave solutions on the sphere: inertia-gravity (IG), mixed Rossby-gravity (MRG), Kelvin and Rossby waves. The work is motivated by the need to quantify the vertical velocity and momentum fluxes in the tropics where the distinction between the Rossby and gravity regime, present in the extratropics, becomes obliterated. The new method decomposes divergence and its power spectra as a function of latitude and pressure level. Its application on ERA5 data in August 2018 reveals that the Kelvin and MRG waves made about 6% of the total divergence power in the upper troposphere within 10S-10N, that is about 25% of divergence. Their contribution at individual zonal wavenumbers k can be much larger; for example, Kelvin waves made up to 24% of divergence power at synoptic k in August 2018. The relatively small roles of the Kelvin and MRG waves in tropical divergence power are explained by decomposing their kinetic energies into rotational and divergent parts. The Rossby wave divergence power is 0.3-0.4% at most, implying up to 6% of global divergence due to the beta effect. The remaining divergence is about equipartitioned between the eastward- and westward-propagating IG modes in the upper troposphere, whereas the stratospheric partitioning depends on the background zonal flow. This work is a step towards a unified decomposition of the momentum fluxes that supports the coexistence of different wave species in the tropics in the same frequency and wavenumber bands.