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30 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics↗
DOE OSTI2021

Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances

Vegetation processes are fundamentally limited by nutrient and water availability, the uptake of which is mediated by plant roots in terrestrial ecosystems. While tropical forests play a central role in global water, carbon, and nutrient cycling, we know very little about tradeoffs and synergies in root traits that respond to resource scarcity. Tropical trees face a unique set of resource limitations, with rock-derived nutrients and moisture seasonality governing many ecosystem functions, and nutrient versus water availability often separated spatially and temporally. Root traits that characterize biomass, depth distributions, production and phenology, morphology, physiology, chemistry, and symbiotic relationships can be predictive of plants’ capacities to access and acquire nutrients and water, with links to aboveground processes like transpiration, wood productivity, and leaf phenology. In this review, we identify an emerging trend in the literature that tropical fine root biomass and production in surface soils are greatest in infertile or sufficiently moist soils. We also identify interesting paradoxes in tropical forest root responses to changing resources that merit further exploration. For example, specific root length, which typically increases under resource scarcity to expand the volume of soil explored, instead can increase with greater base cation availability, both across natural tropical forest gradients and in fertilization experiments. Also, nutrient additions, rather than reducing mycorrhizal colonization of fine roots as might be expected, increased colonization rates under scenarios of water scarcity in some forests. Efforts to include fine root traits and functions in vegetation models have grown more sophisticated over time, yet there is a disconnect between the emphasis in models characterizing nutrient and water uptake rates and carbon costs versus the emphasis in field experiments on measuring root biomass, production, and morphology in response to changes in resource availability. Closer integration of field and modeling efforts could connect mechanistic investigation of fine-root dynamics to ecosystem-scale understanding of nutrient and water cycling, allowing us to better predict tropical forest-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Divergent trait controls on soluble sugars and starch underlie global strategies of tree carbohydrate storage

Nonstructural carbohydrate (NSC) stores buffer tree metabolism, osmotic regulation, and defense, thereby mediating tolerance and survival under climate extremes. Yet, the functional and evolutionary determinants of interspecific variation in NSC remain elusive, limiting understanding and prediction of forest carbon allocation and mortality under global change. Here, we present a cross-species synthesis of NSC concentrations across multiple organs for 281 woody species from 102 mixed forest communities worldwide, where we quantified species-specific deviations from community means to disentangle intrinsic trait effects from environmental and methodological variation. We found phylogenetic signals in NSC deviations, with coniferous gymnosperms and evergreen species consistently maintaining lower stem soluble sugars and starch concentrations than co-occurring angiosperms and deciduous species, respectively. A global pattern emerged where greater stomatal sensitivity to leaf water potential was associated with declines in the relative concentrations of both sugars and starch. In contrast, xylem hydraulic safety traits showed weak and organ-dependent relationships with NSC concentrations. Sugars increased with photosynthetic capacity and declined with wood density, whereas starch showed the reverse pattern, which aligned with the distinct functional-metabolic roles of sugars and starch. By integrating trait-based ecology with a community-centered framework, our study provides global evidence that stomatal regulation, photosynthetic capacity, specific leaf area, and wood density jointly govern interspecific NSC variation, through contrasting effects on sugars and starch. These are among the most broadly measured traits globally, thus the emergent carbohydrate–trait relationships can have broad applications toward understanding and predicting forest growth and survival under climate change.

tropic system↗
NASA NTRS2022

Model Spread in Tropical Low Cloud Feedback Tied to Overturning Circulation Response to Warming

Among models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6), here we show that the magnitude of the tropical low cloud feedback, which contributes considerably to uncertainty in estimates of climate sensitivity, is intimately linked to tropical deep convection and its effects on the tropical atmospheric overturning circulation. First, a reduction in tropical ascent area and an increased frequency of heavy precipitation result in high cloud reduction and upper-tropospheric drying, which increases longwave cooling and reduces subsidence weakening, favoring low cloud reduction (Radiation-Subsidence Pathway). Second, increased longwave cooling decreases tropospheric stability, which also reduces subsidence weakening and low cloudiness (Stability-Subsidence Pathway). In summary, greater high cloud reduction and upper-tropospheric drying (negative longwave feedback) lead to a more positive cloud feedback among CMIP6 models by contributing to a greater reduction in low cloudiness (positive shortwave feedback). Varying strengths of the two pathways contribute considerably to the intermodel spread in climate sensitivity.

Atmospheric dynamics↗
DOE OSTI2026

Future Projection of Tropical Upper-Tropospheric Troughs and Implications for Tropical Cyclone Activity

Summertime tropical upper-tropospheric troughs (TUTTs) provide a unified framework to better understand how extratropical and tropical forcings jointly modulate basin-scale tropical cyclone (TC) activity. In this study, we examine future changes in TUTTs and their implications for TC activity. Multimodel ensemble-mean projections from 45 Coupled Model Intercomparison Project phase 6 (CMIP6) models suggest a contraction of the Pacific TUTT and an expansion of the Atlantic TUTT as the climate warms. Consistently, future changes in environment-based TC indices indicate that the large-scale conditions will become more favorable for TC genesis and intensification over the central North Pacific but less favorable over the tropical North Atlantic and Gulf of Mexico. Utilizing a TC-permitting large-ensemble dataset [i.e., the Database for Policy Decision-Making for Future Climate Change (d4PDF)] that adequately captures the observed interannual TUTT–TC relationships, we further confirm the impacts of projected TUTT changes on the TC activity in a warmer climate. In contrast, the TUTT–TC relationship is poorly represented in most CMIP6 High-Resolution Model Intercomparison Project (HighResMIP) models; such deficiencies call for caution when assessing future TC risk based on explicitly tracked TCs in these models. Additionally, CMIP6 projections show large intermodel spread in TUTT changes, implying uncertainty in projected TC activity, especially over the central-to-eastern Pacific and the North Atlantic. This intermodel spread is associated with interhemispheric sea surface temperature warming asymmetry, which leads to a meridional shift of the intertropical convergence zone (ITCZ) and the simultaneous weakening or strengthening of TUTTs in the North Pacific and North Atlantic. The potential contributions of anthropogenic aerosol forcing and oceanic circulation to this interhemispheric warming asymmetry are briefly examined.

Climate Change↗
NASA NTRS2013

Colors of Jupiter's large anticyclones and the interaction of a Tropical Red Oval with the Great Red Spot in 2008

The nature and mechanisms producing the chromophore agents that provide color to the upper clouds and hazes of the atmospheres of the giant planets are largely unknown. In recent times, the changes in red coloration that have occurred in large- and medium-scale Jovian anticyclones have been particularly interesting. In late June and early July 2008, a particularly color-intense red tropical oval interacted with the Great Red Spot (GRS) leading to the destruction of the red tropical oval and cloud dispersion. We present a detailed study of the tropical vortices, usually white but sometimes red, and a characterization of their color spectral signatures and dynamics. From the spectral reflectivity in methane bands we study their vertical cloud structure compared to that of the GRS and BA. Using two spectral indices we found a near-correlation between anticyclones cloud top altitudes and red color. We present detailed observations of the interaction of the red oval with the GRS and model simulations of the phenomena that allow us to constrain the relative vertical extent of the vortices. We conclude that the vertical cloud structure, vertical extent and dynamics of Jovian anticyclones are not the causes of their coloration. We propose that the red chromophore forms when background material (a compound or particles) is entrained by the vortex, transforming into red once inside the vortex due to internal conditions, exposure to ultraviolet radiation or to the mixing of two chemical compounds that react inside the vortex, confined by a potential vorticity ring barrier.

red color↗
NASA NTRS2020

An Overview of CMIP5 and CMIP6 Simulated Cloud Ice, Radiation Fields, Surface Wind Stress, Sea Surface Temperatures and Precipitation over Tropical and Subtropical Oceans

The potential links between ice water path (IWP), radiation, circulation, sea surface temperature (SST) and precipitation over the Pacific and Atlantic Oceans resulting from the falling ice radiative effects (FIREs) are examined from present day model outputs of CMIP5 and CMIP6. The latter is divided into two subsets with (SON6) and without FIREs (NOS6) as more models with FIREs are included in CMIP6 than in CMIP5. Improvement in floating cloud ice (~20 g m-2) is noticeable over convective regions in CMIP6 relative to CMIP5. The inclusion of FIREs in SON6 subset may contribute to reduce biases of overestimated outgoing longwave radiation and downward surface shortwave and overestimated reflected shortwave at the top of the atmosphere (TOA) by magnitudes of 4?8 W m-2 over convective regions against CERES, compared to NOS6 subset. The reduced biases in radiative fluxes in convective regions stabilize the atmosphere and lead to circulation, SST, cloud and precipitation changes over the trade-wind regions, as seen from improved radiative fluxes (4?15 W m-2), surface wind stress biases, SST (0.2?0.8 K) and precipitation (1 mm day-1) biases. The significant improvement from NOS6 to SON6 leads to improved multi-model means for CMIP6 relative to CMIP5 for radiation fields over the trade wind regions but the degradation over convective zones is attributed to NOS6 subset. The results suggest that other sources of uncertainty and deficiencies in climate models may play significant roles for reducing discrepancies although FIREs, via radiation-circulation coupling, may be one of the factors that help to reduce regional biases.

Jui-Lin F Li↗
DOE OSTI2026

Amazonian fog harbors viable microbes

Fog formation over tropical forests remains poorly characterized, despite its potential role in bioaerosol dispersion and ecosystem processes. Here, we analyzed fog samples collected at the Amazon Tall Tower Observatory using flow cytometry and culture-based techniques to characterize viable microbial communities. Microbial cell concentrations varied over an order of magnitude across 13 fog events, reaching up to 8 × 104 cells per ml of fog water. Flow cytometry consistently detected metabolically active cells, while culturing and mass spectrometry-based identification yielded eight viable bacterial species and seven fungal taxa. The bacteria Serratia marcescens, Ralstonia pickettii and Sphingomonas paucimobilis exhibited seasonal variations in prevalence. The fungal species identified were primarily mesophilic saprophytes and endophytes, commonly associated with soil and plant surfaces. Our findings indicate that fog harbors viable microbes, including Serratia marcescens and Ralstonia pickettii, which may imply a relevance of fog for microbial dispersal, colonization and nutrient cycling in the Amazon rainforest.

Godoi, Ricardo H. (ORCID:0000000247744870)↗
DOE OSTI2026

Assessing the Impact of a Forest Canopy on Near-Surface Wind Statistics

Representing the forest canopy in atmospheric numerical models should improve simulated winds within and above the canopy up to a few hundred meters above the ground. Here, in this study, we implement a forest canopy parameterization into the Weather Research and Forecasting (WRF) Model in a large-eddy simulation (LES) mode by applying drag forces across multiple layers within the canopy height. We use unique observations from the Lidar Experiments for Assessing Flow over Forests (LEAFF) field campaign at the Wind River Experimental Forest (WREF) in the U.S. Pacific Northwest to evaluate model performance. In a 2-day case study, the canopy parameterization improved wind predictions both within and above the canopy, particularly during the daytime and at finer grid resolution. Without it, winds were frequently overpredicted above the canopy. Similarly, derived quantities such as the wind shear index also yielded estimates closer to observations with the canopy parameterization implemented. These findings suggest that representing the canopy using drag forces alone can improve simulated mean winds up to 200 m above the surface. Furthermore, second-order statistical moments of wind were more sensitive to canopy density than first-order moments, especially during the daytime. This increased sensitivity and the improved daytime performance in wind speed—evidenced by the lowest bias from observations (3% compared to 20% over diurnal cycle)—imply that winds above the canopy layer are strongly influenced by how well turbulence above the canopy is modeled. The results of this study can serve as a foundation for parameterizing forest canopy effects in coarser weather forecast models.

Energy - Wind↗
DOE OSTI2024

Case study of UAS ignition of prescribed fire in a mixedwood on the William B. Bankhead National Forest, Alabama

Abstract Background For at least four decades, practitioners have recognized advantages of aerial versus ground ignition for maximizing the effectiveness of prescribed fires. For example, larger areas can be ignited in less time, or ignition energy may be variously targeted over an area in accordance with the uneven distribution of fuels. The maturation of wireless communication, geopositioning systems, and unmanned aerial systems (UAS) has enhanced those advantages, and UAS approaches also provide further advantages relative to helicopter ignitions, such as reduced risk to human safety, lower operating costs, and higher operational flexibility. In a long running study at the Bankhead National Forest in northcentral Alabama, prescribed fire has been used for nearly 20 years. Most of the burns have been hand-ignited via drip torches, while some have been aerially ignited via helicopter. In March 2022, for the first time, a UAS was used to ignite prescribed fires across a landscape that included a long-term research stand. This field note relates comparisons of both fire behavior and fuel consumption metrics for the UAS-ignited burn versus previous burns on the same stand, and versus burns of other research stands in the same year. Results The UAS-ignited prescribed fire experienced burn effects similar to those from ground-ignited prescribed fires on the same stand in previous years, as well as those from ground-ignited prescribed fires on other stands in the same year. Conclusion This post hoc analysis suggests that UAS ignition approaches may be sufficient for achieving prescribed burn goals, thereby enabling practitioners to realize the advantages offered by that ignition mode.

Environmental Sciences & Ecology↗
DOE OSTI2025

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional microscopy is a practical tool for diagnosis and screening ofSchistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection ofS. haematobiumthat combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. We collected BF and DF images of urine samples, many of them containingS. haematobiumeggs, during two different field studies in Côte d’Ivoire using a mobile phone-based microscope, the SchistoScope. We then trained separate egg-detection ML models and compared the patient-level performance of BF and DF models alone to combinations of BF and DF models, using annotations from trained microscopists as the gold standard. We found that models trained on DF images, and almost all BF and DF combinations, performed significantly better than models trained on BF images only. When models were trained on images from the first field study (n = 349 patients, 748 images of each contrast), patient-level classification performance on patient images from the second study (n = 375 patients, 752 images of each contrast) met the WHO Diagnostic Target Product Profile (TPP) sensitivity and specificity for the monitoring and evaluation use case (sensitivity for all models and combinations was >75% when evaluated at a confidence score threshold that resulted in specificity >96.5%). When we used images from both field studies for the training set, performance of the models was improved. Overall, this work shows that the use of DF and BF increases the performance of ML models on images from devices with low-cost optics, while retaining the portability, power, and time-to-results of the WHO’s diagnostic TPP. DF requires no additional sample preparation and does not increase the complexity of the imaging system. It thus offers a practical means to improve performance of automated diagnostics forS. haematobiumas well as other microscopy-based diagnostics.

Infectious Diseases↗
NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗
DOE OSTI2026

Scattering theory of frequency-entangled biphoton states facilitated by cavity polaritons

The use of quantum light to probe exciton properties in semiconductor and molecular nanostructures typically occurs in the low-intensity regime. A substantial enhancement of exciton-photon coupling can be achieved with photonic cavities, where excitons hybridize with cavity modes to form polariton states. Here, to provide a theoretical framework for interpreting emerging experimental efforts in this direction, we develop a scattering theory describing the interaction of frequency-entangled photon pairs with cavity polariton and bipolariton states under various coupling regimes. Employing the Tavis-Cummings model in combination with our scattering approach, we present a quantitative analysis of how the interaction of the entangled photon pair with the polariton or bipolariton modifies its joint spectral amplitude (JSA). Specifically, we examine the effects of the cavity-mode steady-state population, exciton-cavity coupling strength, and different forms of the input photon JSA. Our results show that the entanglement entropy of the scattered photons is highly sensitive to the interplay between the input JSA and the spectral line shapes of the polariton resonances, emphasizing the cavity filtering effects. We suggest that biphoton-scattering quantum light spectroscopy best serves as a sensitive probe of polariton and bipolariton states in the photon-vacuum cavity state. Our approach is not only robust to various regimes of cavity-exciton coupling, but also amenable to extensions beyond the Tavis-Cummings model, enabling the representation of a broad class of molecular systems and solid state quantum materials.

36 MATERIALS SCIENCE↗
NASA NTRS2026

Effects of Multisensory Virtual Reality Nature on Affect, Presence, and Restorativeness

Virtual reality (VR) can provide access to restorative environments and sensory stimulation for individuals in isolated, confined, and extreme environments. We developed a nature-based VR intervention featuring three scenes (Garden, Forest, Beach) and examined the effects of multisensory augmentation with location-based olfactory, wind, and thermal stimuli (VR+OWT). Over a two-week period, fifty-one participants were assigned to a no-intervention control, standard audiovisual VR, or augmented VR (VR+OWT) condition. Data collection included weekly assessments of affect, stress, and cognitive performance; post-VR measures of affect, presence, and perceived restorativeness; and open-ended feedback. Both VR and VR+OWT groups produced immediate and sustained reductions in negative affect with no sustained systematic benefits on cognitive performance. The addition of olfactory, wind, and thermal stimuli enhanced presence for some scenes; however, feedback indicated that sensory mismatches and stimulus intensity occasionally detracted from the experience and may have contributed to lower coherence ratings in the VR+OWT group. In contrast, the perceived restorativeness of the VR environment was driven primarily by scene content (Garden vs Forest vs Beach) rather than the level of sensory stimulation. These findings support the potential of virtual nature to promote well-being and underscore the importance of coherence across sensory modalities for multisensory augmentation.

Virtual Reality Intervention↗
DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗
DOE OSTI2026

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗
NASA NTRS2026

Updated global and regional trends of stratospheric ozone profiles

We present updated evaluation of stratospheric ozone profile trends in the 60° S–60°N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. The trends are evaluated using the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) regression model. Analyses of satellite data confirm the statistically significant positive ozone trends in the period 2000–2024 in the upper stratosphere of ~1–3% per decade, with larger trends at mid-latitudes compared to the tropics. The trends are slightly positive or close to zero in the middle stratosphere, and mostly negative, -1 to -2% per decade, in the lower stratosphere, but they are not statistically significant. The morphology and magnitude of ozone trends are similar to previous analyses (2000–2020 trends). Ozone trends in 2000–2024 predicted by chemistry-climate model simulations are in good agreement with combined satellite trends. In the upper stratosphere, models predict a slightly stronger ozone recovery than observations. In the lower stratosphere, both models and satellite observations report negative trends in the tropics, while modelled ozone trends are slightly positive at mid-latitudes. Ozone profile trends over several stations estimated from ground-based records capture the same overall vertical pattern of ozone trends as merged gridded satellite datasets. Analyses of regional ozone profile trends in 2003–2024 using merged satellite datasets confirmed the previous observations of a longitudinal structure in ozone trends in the NH mid-latitude stratosphere, with positive trends over Scandinavia and negative trends over Siberia. However, the magnitude of this dipole-like structure is reduced compared to previous analyses.

trends↗