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At least 19 records

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest↗

Boundary-Layer-Coupled and Decoupled Clouds in Global Storm-Resolving Models: Comparisons With the ARM Observations

The accurate representation of interactions between clouds and planetary boundary layer (PBL) is a persistent challenge in climate models, critical for simulating surface energy budget. The emergence of kilometer-grid-scale global storm resolving models (GSRMs) offers the potential for enhanced details of PBL processes in these complex interactions. This study evaluates the representation of PBL-coupled and decoupled clouds in nine GSRM simulations against extensive ground-based observations by the Department of Energy Atmospheric Radiation Measurement (ARM) program, across six sites encompassing diverse regimes such as marine and continental environments in tropics and midlatitude. By differentiating coupling based on the relative positions between cloud bases and PBL tops, our analysis focuses on the simulation of PBL height, cloud frequency, position and vertical extent. The GSRMs generally exhibit commendable agreements with observed cloud structures and PBL diurnal cycles across different ARM sites. In contrast to the relatively consistent representation of decoupled clouds, discrepancies exist between the simulated and the observed coupled clouds, particularly in areas of intense convection, for example, over tropical rainforests and mountainous regions. These biases are probably associated with the models' tendency to underestimate the boundary layer humidity and the frequency of coupled clouds within different ranges of PBL heights. This study underscores the importance for continuous improvements in the representation of boundary layer and convection within these global kilometer-grid-scale models.

54 ENVIRONMENTAL SCIENCES↗

Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model

Abstract This study develops a surrogate‐based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near‐surface air temperature (T2m). Average physics uncertainties are determined to be 1.5C for LST and T2m over land, and 1.9C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations alone are the dominant sources of uncertainty (45%–53%), while lake and land parameterizations account for 33% and 38% of the uncertainty of LST and T2m over land respectively. Interactions of atmosphere physics parameterizations with those of the land and lake contribute to an additional 13%–17% of the total variance. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model's surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model.

54 ENVIRONMENTAL SCIENCES↗

Contrasting biological production trends over land and ocean

Terrestrial and marine ecosystems constitute the primary components of the Earth’s biosphere, yet their photosynthetic productions are typically studied separately, which limits understanding of planetary carbon uptake and biosphere health. Here, in this study, using multiple satellite-derived products, we identify contrasting net primary production (NPP) trends between land and ocean, probably reflecting their differential sensitivity to climate warming, especially in tropical regions. Planetary NPP shows an overall increase of 0.11 ± 0.13 PgC yr −1 (P = 0.05) from 2003 to 2021, driven by a significant terrestrial enhancement of 0.20 ± 0.07 PgC yr −1 (P < 0.001) and partially offset by an oceanic decline of −0.12 ± 0.12 PgC yr −1 (P = 0.07). While land contributes to the strong upwards NPP trend, the interannual variability in global NPP is predominantly driven by the ocean, especially during strong El Niño–Southern Oscillation events. Our findings highlight the resilience and potential vulnerability of biosphere primary productivity in a warming climate, calling for integrated land–ocean monitoring and assessment to support climate mitigation initiatives.

54 ENVIRONMENTAL SCIENCES↗

CMIP7 data request: land and land ice priorities and opportunities

The Land and Land Ice Theme in the Coupled Model Intercomparison Project Phase 7 (CMIP7) represents the current understanding of physical processes in land surface ecosystems, hydrology, cryosphere, and their physical interactions with other Earth system components. Simulations from Earth system models (ESMs) could provide crucial information for assessing planetary safety, such as critical tipping elements, and be used to inform climate risks for improving climate impact assessments and policy decisions. This paper presents a collaborative effort to identify scientific opportunities in the Land and Land Ice Theme of the CMIP7 Data Request. The proposed opportunities build upon advances in ESMs, including new freshwater system and land ice processes being included in CMIP7, as well as the scientific community's demand for high-frequency and sub-grid-scale land surface outputs. In total, 25 variable groups that contain 716 variables have been identified to be potentially available to the broad scientific audience for performing analysis in land–atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology. Key reflections from this data request effort include advocacy for closer engagement between the user community and modeling groups, reduction in the technical barriers to tracking existing parameters and defining new variables, and more streamlined variable management. These will be essential to enhance the usability and reliability of CMIP7 outputs for climate and Earth system research and applications to a broad audience that relies on the CMIP7 endeavor.

Li, Yue [Univ. of California, Los Angeles, CA (Uni↗

Reimagining Earth in the Earth System

Abstract Terrestrial, aquatic, and marine ecosystems regulate climate at local to global scales through exchanges of energy and matter with the atmosphere and assist with climate change mitigation through nature‐based climate solutions. Climate science is no longer a study of the physics of the atmosphere and oceans, but also the ecology of the biosphere. This is the promise of Earth system science: to transcend academic disciplines to enable study of the interacting physics, chemistry, and biology of the planet. However, long‐standing tension in protecting, restoring, and managing forest ecosystems to purposely improve climate evidences the difficulties of interdisciplinary science. For four centuries, forest management for climate betterment was argued, legislated, and ultimately dismissed, when nineteenth century atmospheric scientists narrowly defined climate science to the exclusion of ecology. Today's Earth system science, with its roots in global models of climate, unfolds in similar ways to the past. With Earth system models, geoscientists are again defining the ecology of the Earth system. Here we reframe Earth system science so that the biosphere and its ecology are equally integrated with the fluid Earth to enable Earth system prediction for planetary stewardship. Central to this is the need to overcome an intellectual heritage to the models that elevates geoscience and marginalizes ecology and local land knowledge. The call for kilometer‐scale atmospheric and ocean models, without concomitant scientific and computational investment in the land and biosphere, perpetuates the geophysical view of Earth and will not fully provide the comprehensive actionable information needed for a changing climate.

Meteorology & Atmospheric Sciences↗

Increased frequency of planetary wave resonance events over the past half-century

We demonstrate a tripling in the frequency of planetary wave resonance events over the past halfcentury, coinciding with the rise in persistent boreal summer weather extremes. This increase aligns with changes in the underlying climate conditions favoring these events, including amplified Arctic warming and land-sea thermal contrast. We also observe increased prevalence of resonant amplification events following the mature phase of strong El Niño events, suggesting that such events may precondition the mean state conditions in ways that favor large-scale quasi-stationary wave patterns and quasi-resonant wave amplification. Since the impact of anthropogenic warming on quasi-resonant amplification is not well captured by current-generation climate models, it is likely that models are underpredicting the potential increase, indicating even greater risk of persistent extreme summer weather events with ongoing warming.

Arctic amplification↗

Quantifying Uncertainties in Modeling Wind Resource Data from Different PBL Schemes in the WRF Model: A Case Study Over the Puerto Rico Region

This study examines the modeling uncertainty of wind resource data stemming from the use of various planetary boundary layer (PBL) parameterizations available in the Weather Research and Forecasting (WRF) model. WRF-based wind simulations spanning 20 years at 3-km resolution using 11 different PBL schemes are used to objectively investigate the uncertainty in modeling wind speed for land-based wind (LBW) and offshore wind (OSW) locations in Puerto Rico. The uncertainty in the wind modeling for the 20-year dataset is quantified using the spread index (SI) and standard deviation (SD). For virtual LBW and OSW sites, the SI and SD values are analyzed as calculated across various spatial and temporal scales. Because the PBL's atmospheric stability conditions can be characterized into two dominant categories, the study focuses on analyzing the SI and SD for daytime (mainly unstable PBL conditions) and nighttime (mainly stable PBL conditions). For wind shear (10 m-200 m) at the OSW and LBW sites, WRF-based numerical experiments indicate the following SI (or SD) ranges: 39%-94% (0.74 m/s-1.44 m/s) during the daytime for OSW, 50%-75% (0.68 m/s-1.19 m/s) during the daytime for LBW, 37%-60% (0.73 m/s-1.12 m/s) during the nighttime for OSW, and 57%-143 % (0.65 m/s-1.43 m/s) during the nighttime for LBW. While a high SI is observed when modeling LBW during the nighttime, there are notable modeling uncertainties during the daytime on the leeward side of the orographic barriers for Puerto Rico.

17 WIND ENERGY↗

Applied genomics for industrially relevant microalgal strain development & optimization: characterizing genotype-phenotype relationships towards scalable environment-enhancing energy systems

Multiple planetary boundaries considered a safe operating space for humanity have been exceeded in recent years, with twice as many boundaries transgressed in 2023 as in 2009. Bioenergy systems are unique in that they can interact with and improve many of the transgressed boundaries directly, including multiple geochemical cycles, water and land use, and climate change. Among bioenergy systems, microalgae-based environment enhancing energy (E 2 -energy) are promising bioenergy systems for drop-in biofuels, valuable materials, chemicals and therapeutics, while making deep emission cuts and remediating wastewater, all without competing for agricultural resources.

09 BIOMASS FUELS↗

Performance of reanalysis and mesoscale models off the coast of Hawai'i

The eastern Hawai'i coast in the United States is characterized by considerable wind resource fuelled by persistent trade winds, making it an important area for energy research. The need is strong for reanalyses and higher-resolution regional simulations where observations have been historically limited, such as Hawai'i's offshore environments. However, studies using offshore observations in other parts of the world have shown that significant errors can occur in reanalyses and wind datasets, which can lead to inaccurate estimates of wind energy generation, payback periods, and extreme weather risks at project locations. The degree of such errors is influenced by a number of factors, including spatial resolution and the handling of processes within the planetary boundary layer (PBL). In this work, we provide a wind resource characterization from year-long lidar buoy measurements off the eastern coast of O'ahu, Hawai'i, an environment previously unobserved at the rotor level, and use the characterization to evaluate the performance of two simulation datasets. The O'ahu deployment location is meteorologically unique and less complex than land-based wind resource characterizations, being strongly characterized by trade winds with minimal land–atmosphere interaction influences. Despite the unique and fairly consistent meteorological conditions, we hypothesize that distinct simulation datasets will exhibit diverse ranges of errors similar to those that have been seen for other offshore locations. We find the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) to strongly underestimate observed wind speeds at the O'ahu location (bias = −1.54 m s −1 at a height of 140 m above sea level), while a regional Weather Research and Forecasting Model (WRF) simulation produced by the University of Hawai'i (UH-WRF) provides a significantly smaller wind speed bias (−0.25 m s −1 ), highlighting the value of running regional, higher-resolution simulations. The large bias noted for ERA5 is driven by significant underestimation of fast wind speeds (>9 m s −1 ), which the study site is largely characterized by, along with discontinuities in the ERA5 diurnal cycle. We also speculate that the relative sparsity of observations for data assimilation in this remote part of the world could influence the performance of ERA5 and that challenges with characterizing island effects could impact the performance of both datasets.

17 WIND ENERGY↗

Air-coupled tsunamis generated from impacts and airbursts: Our understanding before Hunga-Tonga Hunga-Ha'apai

The effort to prevent or mitigate the effects of an impact on Earth is known as planetary defense. A significant component of planetary defense research involves risk assessment. Much of our understanding of the risk from near-Earth objects comes from the geologic record in the form of impact craters, but not all asteroid impacts are crater-forming events. Small asteroids explode before reaching the surface, generating an airburst, and most impacts into the ocean do not penetrate the water to form a crater in the sea floor. The risk from these non-crater-forming ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall threat. We are currently working to better understand impact scenarios that can generate dangerous tsunamis. One of the suggested mechanisms for the production of asteroid–generated tsunamis is by direct coupling of the pressure wave to the water, analogous to the means by which a moving weather front can generate a meteotsunami. To test this hypothesis, we ran a series of airburst simulations and provided time-resolved pressure and wind profiles to use as source functions for tsunami models. We used the CTH hydrocode to model the various airburst scenarios to compare to the results of other simulations and provide time dependent boundary conditions as input to shallow-water wave propagation codes. The strongest and most destructive meteotsunamis are generated by atmospheric pressure oscillations with amplitudes of only a few hPa1 (mbar), corresponding to changes in sea level of a few cm. The resulting wave is strongest when there is a resonance between the ocean and the atmospheric forcing. A Proudman resonance takes place when the atmospheric disturbance’s translational speed (U) equals the longwave phase speed $\sqrt{gh}$ of shallow water wave. Coupling is strongest when the Froude number (Fr=U/c) is unity. A weather front propagates much slower than the speed of sound, so meteotsunamis are most common and dangerous in shallow bodies of water such as the Mediterranean Sea or Lake Michigan. By contrast, the blast wave from an airburst or crater-forming impact propagates at a speed faster than a tsunami in the deepest ocean, and a Proudman resonance cannot be achieved even though the overpressures are orders of magnitude greater. However, blast wave profiles are N-waves in which a sharp shock wave leading to overpressure is followed by a more gradual rarefaction to a much longer-duration underpressure phase. Even though the blast outruns the water wave it is forcing, the tsunami should continue to be driven by the out-of-resonance gradient associated with the suction phase, which may depend strongly on the details of the airburst or impact scenario. The open question is whether there are any conditions under which such an airburst-driven tsunami can be dangerous enough to contribute to the overall impact risk. We have also identified other potential mechanisms for airburst-generated tsunamis: 1) reaction force at the surface from the plume ejected into space, which carries significant momentum, 2) expanding toroidal vortices at the surface, which travel more slowly than the shock wave and can generate a Proudman resonance in relatively shallow ocean (such as continental shelf), and 3) steam explosion from seawater ablation by a “Type II” (Libyan Desert Glass-type) airburst in which the hot vapor jet descends to the surface. On January 15, 2022, the Hunga-Tonga Hunga-Ha’apai volcano, located approximately 60 km north of Tongatapu, the main island of Tonga, violently erupted with a powerful explosion, culminating the period of volcanic activity that started in December of 2021. This event and resulting tsunamis provided an existence proof for the air pressure wave coupling mechanism we proposed. It also suggests that it can be stronger and more significant over much greater distances than we contemplated, leading to global tsunamis associated with impact events on land as well as in the water. Large atmospheric explosions generate global Lamb waves with larger amplitudes, longer periods, and slower speeds than the local and regional blast waves we modeled prior to that event. This paper reviews our analysis and modeling of airburst-driven tsunamis prior to the 2022 Hunga-Tonga Hunga-Ha’apai tsunami, which was the subject of two presentations at the 2023 Planetary Defense Conference and is the subject of another paper currently in preparation.

54 ENVIRONMENTAL SCIENCES↗

Changes in the Regional Water Cycle and Their Impact on Societies

ABSTRACT Changes in “blue water”, which is the total supply of fresh water available for human extraction over land, are quite closely related to changes in runoff or equivalently precipitation minus evaporation, . This article examines how climate change‐driven recent past and future changes in the regional water cycle relate to blue water availability and changes in human blue water demand. Although at the largest scales theoretical and numerical model predictions are in broad agreement with observations, at continental scales and below models predict large ranges of possible future and runoff especially at the scale of individual river catchments and for shorter timescale subseasonal floods and droughts. Nevertheless, it is expected that the occurrence and severity of floods will increase and that of droughts may increase, possibly compounded by human‐driven non‐climatic changes such as changes in land use, dam water impoundment, irrigation and extraction of groundwater. Contemporary assessments predict that increases in 21st century human water extraction in many highly‐populated regions are unlikely to be sustainable given projections of future . To reduce uncertainty in future predictions, there is an urgent need to improve modeling of atmospheric, land surface and human processes and how these components are coupled. This should be supported by maintaining the observing network and expanding it to improve measurements of land surface, oceanic and atmospheric variables. This includes the development of satellite observations stable over multiple decades and suitable for building reanalysis datasets appropriate for model evaluation.

54 ENVIRONMENTAL SCIENCES↗

Remote sensing of planetary boundary layer from ground and space: Structure, thermodynamics, and boundary layer clouds

The planetary boundary layer (PBL) is a critical interface between Earth's surface and atmosphere, influencing atmospheric convection, weather patterns, and air quality. Recognized by the 2017 National Academies of Sciences, Engineering, and Medicine Earth Science Decadal Survey as an Incubation Targeted Observable, high-quality and effective observation of the PBL has become a priority. This paper reviews surface-based and satellite remote sensing techniques for characterizing PBL features, including PBL height (PBLH), boundary layer thermodynamics, turbulence, and boundary layer clouds (BLCs). These elements are treated as interconnected aspects of the PBL system, while recognizing that different instruments retrieve different physical manifestations of the PBL. The review summarizes recent advances and limitations in Micro-Pulse Lidar (MPL), Doppler lidar, Raman lidar, Differential Absorption Lidar (DIAL), ceilometers, wind profilers, GNSS Radio Occultation, radar, and hyperspectral sounders. These observations help trace dynamic processes within the PBL and link PBL structure to broader weather and climate processes. The review also highlights persistent observational gaps over oceans, remote land, and polar regions, where continuous surface-based profiling is sparse. By comparing instrument capabilities, practical limitations, and interpretation issues, this review emphasizes the need for integrated remote sensing approaches and careful definition of the retrieved PBL quantities.

Boundary layer clouds↗

Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models

Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the EarthSHAB Stratospheric Solar Hot Air Balloon Flight Prediction Model Using Balloon Trajectory Data

Abstract The heliotrope is a solar balloon design which is constructed out of painter’s plastic, and the exterior is coated in charcoal powder. Darkening the plastic gives the balloon a high solar absorptance, which allows it to ascend into the lower stratosphere and float for hours at a time. The balloons have previously been used to lift scientific instruments into the stratosphere to study chemical explosions, earthquakes, and stratospheric aerosols. They have also been proposed as a platform for planetary exploration. Flight predictions are crucial to preflight planning to reduce safety risks and meet flight objectives. However, there exists a wide range of possible flight paths due to varying environmental conditions and solar balloon configurations. EarthSHAB is one such software that was designed to support flight planning using the weather forecasts and balloon properties to predict the flight path of a solar balloon. We compare EarthSHAB-simulated flight paths to a set of observed flight paths for the 3.5-m diameter heliotrope design called the “Cloudskimmer.” Using the criteria that the modeled paths must fall within 5% of the observations to be considered successful, we found that EarthSHAB successfully predicted the Cloudskimmer ascent rate and average float altitude 10% and 90% of the time, respectively. We also found that the average difference in the observed and predicted landing locations was 97 km and landing times were 54 ± 38 min. Significant deviations between the observed and predicted ascent rates and excursions at float were found to be associated with heavy payloads and convective cloud development, respectively. Significance Statement Solar balloons are used to lift scientific instruments into the lower stratosphere for hours at a time to study chemical explosions, earthquakes, stratospheric aerosols, and more. The flight paths of solar balloons can be difficult to predict due to variability in their design and surrounding environment. We evaluate the accuracy of EarthSHAB, a software that predicts the altitude profile and horizontal trajectory of a solar balloon using inputs such as the weather, balloon size, and balloon mass. Our results suggest that for the balloon design used in this study, EarthSHAB is best suited for modeling the behavior of balloons with lightweight payloads that do not fly within or directly above clouds.

Lien, Jessica M. [Sandia National Laboratories, Al↗

Climatology of Cloud‐Land‐Surface Coupling Across Different ARM Sites

Land-atmosphere interactions play a critical role in the evolution and formation of low-level clouds. The different states of coupling between low-level clouds and the surface are uncertain, primarily over continental regions, where complex thermodynamics complicates their investigation. This study uses observations from the Atmospheric Radiation Measurement User Facility to explore cloud-surface coupling and perform a climatological analysis of this interaction in five countries across three continents. The results reveal consistent coupling thresholds and average percentages across the five sites, with coupled clouds accounting for 66% of the cases and decoupled clouds for 34%. Thermodynamic and dynamic evaluations show distinct differences between coupled and decoupled clouds. Coupled clouds are characterized by humid environments, in which vertical motions connect the surface and lower atmosphere to the cloud base, conditions that favor the formation of boundary layer clouds. Decoupled clouds prefer to occur in a drier and colder environment with vertical motions inside the boundary layer being detached from the cloud base, under which boundary layer clouds are hard to form. Coupled clouds peak during warmer hours and seasons, and vice versa for decoupled clouds. This study underscores the complexity of cloud-land-surface interactions and paves the way for further investigations into cloud formation and evolution under different atmospheric environments.

54 ENVIRONMENTAL SCIENCES↗

A Scale‐Dependent Analysis of the Barotropic Vorticity Budget in a Global Ocean Simulation

Abstract The climatological mean barotropic vorticity budget is analyzed to investigate the relative importance of surface wind stress, topography, planetary vorticity advection, and nonlinear advection in dynamical balances in a global ocean simulation. In addition to a pronounced regional variability in vorticity balances, the relative magnitudes of vorticity budget terms strongly depend on the length‐scale of interest. To carry out a length‐scale dependent vorticity analysis in different ocean basins, vorticity budget terms are spatially coarse‐grained. At length‐scales greater than 1,000 km, the dynamics closely follow the Topographic‐Sverdrup balance in which bottom pressure torque, surface wind stress curl and planetary vorticity advection terms are in balance. In contrast, when including all length‐scales resolved by the model, bottom pressure torque and nonlinear advection terms dominate the vorticity budget (Topographic‐Nonlinear balance), which suggests a prominent role of oceanic eddies, which are of km in size, and the associated bottom pressure anomalies in local vorticity balances at length‐scales smaller than 1,000 km. Overall, there is a transition from the Topographic‐Nonlinear regime at scales smaller than 1,000 km to the Topographic‐Sverdrup regime at length‐scales greater than 1,000 km. These dynamical balances hold across all ocean basins; however, interpretations of the dominant vorticity balances depend on the level of spatial filtering or the effective model resolution. On the other hand, the contribution of bottom and lateral friction terms in the barotropic vorticity budget remains small and is significant only near sea‐land boundaries, where bottom stress and horizontal viscous friction generally peak.

Khatri, Hemant↗

Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index

Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model – Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (R dark ). We ran global and point simulations varying the canopy gradient of R dark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of R dark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of R dark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in R dark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.

59 BASIC BIOLOGICAL SCIENCES↗