Earth and Environmental Sciences

Abstract. FRIDA is a new contribution to the portfolio of integrated assessment models (IAMs) that address the climate – energy – economy – and society nexus. The FRIDA acronym stands for Feedback-based knowledge Repository for IntegrateD Assessments. Naming it a “knowledge repository” signals that the FRIDA model is never finished; it represents the current state of knowledge of the development team at any given time. FRIDA was developed through the European Horizon project WorldTrans – Transparent Assessments for Real People (2022–2026). The journal Geoscientific Model Development has given us space to document FRIDA, including its submodules and spin-offs, in a special GMD collection (https://gmd.copernicus.org/articles/collection12.html, last access: 18 May 2026). This brief paper is the introduction to the GMD FRIDA collection of papers. The purpose of the introductory paper, written by the project lead on behalf of the consortium, is to provide the conceptual and institutional context for the original model and to make explicit the initial design requirements that guide FRIDA's ongoing development as a living knowledge repository. FRIDA is implemented as a computationally efficient system-dynamics model and is accompanied by an Interactive Learning Environment. This combination makes it suitable not only for research, but also for education and broader outreach. In particular, FRIDA can be used in interdisciplinary climate science courses to show how individual disciplines (e.g. climatology, economics, demography) are tightly interwoven within the coupled climate–human system, thereby lowering the barrier to entry for users beyond the IAM community. What sets FRIDA apart from traditional IAMs is its shift from exogenous, narrative-based scenarios to a fully feedback-driven framework, in which human activities and climate change co-evolve within a single system of equations. By explicitly representing these two-way feedbacks, FRIDA accounts for the impacts that climate change has already begun to exert on human systems; without them, projections of the human activities that drive climate change will become increasingly unreliable. Preliminary results suggest that including these feedbacks lead to systematically less optimistic projections than conventional IAM baselines.

Abstract. Climate change is expected to increase the frequency and severity of Multi-Year Droughts (MYDs), but their impacts on vegetation remain poorly understood. While satellite records offer valuable insights, they only cover recent decades, limiting the number of MYDs available for analysis. The dynamic global vegetation model LPJmL-5 can simulate vegetation dynamics under varying climate conditions and over longer temporal scales than are typically available from satellite observations. However, its ability to capture vegetation responses to drought, including MYDs, has not yet been systematically evaluated against observation-based datasets. In this study, we benchmark LPJmL-5 against MODIS-derived gross primary production (GPP) to assess how well the model reproduces vegetation responses to drought. We find that LPJmL-5 captures the key temporal and spatial dynamics of drought-related GPP observed by MODIS, although notable differences remain. In particular, LPJmL-5 tends to overestimate vegetation response at the onset of MYDs and shows some rapid recovery behaviour, resulting in muted overall drought impacts. Vegetation responses also vary by type: drought dynamics in croplands are captured relatively well, whereas responses in boreal and temperate vegetation are underestimated in magnitude. These discrepancies appear to be linked to simplified model representations of vegetation stress and mortality, which limit long-term vegetation loss. Beyond drought conditions, LPJmL-5 reproduces absolute GPP values reasonably well in some regions, but performance declines in parts of the Southern Hemisphere and in cropland-dominated areas. This suggests that general GPP simulation performance is not necessarily linked to performance during drought conditions. Overall, this benchmarking highlights strengths and limitations in how LPJmL-5 represents vegetation responses to drought and provides a foundation for future studies of vegetation responses to multi-year droughts.

Abstract Early warnings for climate tipping points should clearly convey their significant uncertainties, to maintain transparency and avoid perceptions of overstatement. This includes doubts about the existence of climate tipping points, which must often be assumed a priori in order to assess their early-warning signals, as well as doubts about their proximity. When such uncertainties are not clearly communicated, both updated assessments and continued absence of detected tipping can erode public trust and scientific credibility concerning future warnings for climate tipping. Moreover, this could even be misinterpreted by the public as more general ignorance about impacts of climatic change. So, perceived overstatement in this context may weaken support for climate policy in general. We stress that regardless of uncertain climate tipping points, climate action is already imperative because of the undisputed impacts of climate change. Also, an overemphasis on uncertain tipping points may sometimes obscure well-established evidence for the urgent need for climate policy. Despite strong mathematical foundations, Earth system complexity and unresolved uncertainties constrain the application and communication of tipping-point theory, highlighting the need for further elaboration. The uncertainty of climate tipping points furthermore underscores the need for adaptive planning, considering both tipping-point and non-tipping point scenarios, while safeguarding that climate policy remains based on scientific evidence.

Abstract Organic farming systems have expanded across North America, yet the drivers and magnitude of soil N 2 O fluxes remain understudied. To quantify organic fertilizer-induced N 2 O and identify key management and environmental drivers, we conducted a meta-analysis with 315 observations from 43 North American field studies. We also extracted 68 covariates representing crop type and properties, nitrogen inputs and management practices, hydrology, soil properties, topography, climate, and remote sensing indices to model N 2 O fluxes. Categorical comparisons showed that swine manure and liquid amendments produced significantly (P < 0.05) higher emissions and emission factors (EFs) than other amendment types and forms. Corn had the highest monthly area-scaled emissions (0.36 kg N ha -1 month -1 ) among all crops. Significant differences also occurred across photosynthetic pathway (C4 > C3), life cycle (annual > perennial), and plant type (monocot > dicot) for emissions and EF. Tile-drainage did not significantly affect any N 2 O metrics, but differences were observed between irrigated and non-irrigated sites, likely reflecting variation in the completeness of the denitrification process. Random Forest (RF) models identified remote sensing indices as the strongest predictors (up to 25% importance) of emissions and EFs, followed by soil chemical properties (19%), climate (17%), and soil physical properties (16%). The RF results also showed that organic fertilizer-induced N 2 O emissions can be estimated (R 2 = 0.54, 0.72, and 0.69 for area and yield-scaled monthly emissions and EFs) with key environmental and management factors. EF comparisons with IPCC Tier-1 benchmarks indicated that the 2006 benchmark (1%) might overestimate EFs, while the 2019 dry region (0.5%) benchmark overestimates EFs and the 2019 wet region benchmark (0.6%) underestimates EFs. The meta-analysis and modeling results provide a basis for researchers, policymakers, and farmers to refine N 2 O estimates, target high-emission drivers, and improve nitrogen management in organic systems.

Study region National Groundwater Recharge Observing System (NGROS) sites, Australia Study focus Identifying controls on groundwater recharge occurrences remains a central challenge in hydrology. Although broad consensus exists on key variables influencing recharge, there is less agreement on their relative importance and whether observed relationships are causal or merely correlative. Existing studies rely on approaches limited in capturing non-linear behavior or only capture single measures of association without addressing causal linkages. This study quantifies both correlative and causal relationships between key variables and potential groundwater recharge occurrences across nine NGROS sites. NGROS is the first dedicated sensor network to observe groundwater recharge at event scale in underground spaces across Australia. Using high-resolution drip monitoring data as direct indicators of recharge events, relationships between recharge occurrences and potential drivers, including precipitation, soil moisture, evapotranspiration (ET), and vegetation dynamics (NDVI), were quantified using both correlation-based and causality-oriented analyses, including first application of Convergent Cross Mapping (CCM) to identify causal linkages influencing recharge occurrences. New hydrological insights Results show that soil moisture and vegetation are the strongest predictors of recharge occurrences. ET shows moderate seasonal importance, particularly during austral autumn, but remains secondary overall. Although daily rainfall shows weak association, cumulative precipitation over 6–7 days shows stronger predictive association. Soil moisture also has longer response lags (> 3 weeks) compared to rainfall (7–10 days).

Abstract Blue-green infrastructure (BGI)—engineered, nature-based stormwater controls such as bioretention cells and green roofs—can reduce combined sewer overflows (CSOs). However, hydrological performance can decline over time through sediment deposition and clogging. Despite this, catchment-scale studies commonly assume stationary BGI performance, potentially underestimating CSO volumes and associated risks. This study integrates spatial sensitivity analysis with dynamic deterioration modelling to examine where and when BGI performance loss most affects CSO volumes.

A semi-Markov chain model simulated condition-state transitions for individual BGI assets, coupled with EPA SWMM to assess CSO mitigation over time in a realistic case study. Under the modelled parameters, the difference in system-level CSO volume between fully functioning and fully failing BGI reached 18% by the end of the study period. Critically, while most assets exert minimal influence, a subset of high-leverage BGI assets disproportionately governs CSO volumes—primarily determined by asset size and capture ratio. Furthermore, early performance losses are masked by annual rainfall variability, introducing significant delays before failures become detectable through CSO measurements alone.

These findings indicate that effective monitoring requires asset-level rather than system-level observation. Targeting a high-leverage subset of BGI can substantially reduce monitoring effort while preserving CSO performance. This study demonstrates how such critical assets can be identified and contributes a methodology for explicitly incorporating BGI deterioration dynamics into catchment-scale models. These findings enable risk-informed monitoring and maintenance prioritisation, treating BGI as a dynamic rather than static component of urban drainage management.

Abstract The Yangtze River Basin (YRB) is historically prone to frequent summer droughts caused by local land-atmosphere feedbacks and large-scale circulation. This study focuses on the decadal variation of the intraseasonal decline of soil moisture in the YRB, which has demonstrated a significant decadal shift in summer soil moisture occurred around 2009, characterized by an intensified decline of soil moisture with a prolonged duration, from about 30 days before 2009 to nearly 50 days after 2009. Diagnostic analysis shows that sensible heat flux (SH) is the more dominant factor driving the intraseasonal decline of soil moisture in the YRB compared with latent heat flux. Since 2009. the mechanism of positive feedback of SH has shifted from a dual-factor mode by wind speed and temperature to a one-factor mode solely by temperature. The transition rooted in large-scale circulation shifts forced by sea surface temperature anomalies (SSTAs). Beyond the internal variability of the western pacific subtropical high, the superposition of Arctic-amplification-triggered wave train and decadal warming of mid-latitude Pacific plays a decisive role. Before 2009, these two types of oceanic forcings jointly induced an anticyclonic circulation anomaly on the northern or southern side of the YRB. But after 2009, this circulation anomaly tended to completely cover the YRB, triggering relatively stronger subsidence currents and continuous high temperatures in the YRB, providing a powerful circulation background condition for the temperature single-factor driven SH positive feedback process.

Study region Jiuzhaigou Valley is a UNESCO World Heritage Site renowned for its outstanding scenic and ecological values, preserving important forest ecosystems and high biodiversity, and it is also recognized as a UNESCO Biosphere Reserve. Study focus To provide a mechanistic resistance parameter applicable to obstacle-rich channel reaches (tree stems and pier-like elements), we conducted long-duration quasi-steady flume experiments of debris flows passing a single circular cylinder using a recirculating system. Drag forces were measured under controlled mixture properties and flow regimes and converted to drag coefficient C d . In addition, we provide an application framework that links the experimentally derived mean drag coefficient to an equivalent reach-scale Manning roughness for obstacle- or forest-belt-rich reaches, enabling implementation in depth-averaged routing models, pending field-scale calibration and validation. New hydrological insights for the region The results show that Froude-number-only descriptions are insufficient for debris-flow interactions with cylindrical obstacles when geometric effects become important. The drag coefficient depends systematically on the depth-to-diameter ratio, reflecting a transition from front-dominated loading to flow diversion and shear-influenced interaction along the cylinder. Incorporating depth–diameter scaling and viscous control yields a practical, physically based drag closure for a single cylinder under quasi-steady motion. This closure provides an element-scale basis for a preliminary upscaling framework for obstacle-induced resistance in channel-routing calculations in Jiuzhaigou-type catchments.

Abstract Log jams enhance hydraulic and geomorphic diversity in river corridors. Channel‐spanning log jams induce backwatering, increase local flow heterogeneity, promote sediment deposition, and improve aquatic habitat diversity. Despite their increasing popularity in river restoration, predicting their hydraulic effects remains a challenge. We developed a model to predict dimensionless head loss through log jams for sub‐bankfull flows as traditional backwater methods are limited in variable natural channels. We developed the model from historical flume studies and tested the model application on field data from natural jams. As solid volume fraction increased, we found that dimensionless head loss also increased. Field application of our model successfully predicted head loss in naturally occurring log jams. Roughness values (Manning's and Darcy‐Weisbach ) varied but generally decreased with increased unit discharge. Our approach for determining head loss and roughness allows for better prediction and design of the localized hydraulic impacts of log jams.

Abstract. South China, a densely populated region frequently affected by transported biomass burning aerosol (BBA), requires sensitive remote sensing observations to characterize these plumes. Laser-induced fluorescence (LIF) lidar is a powerful tool for detecting fluorescent aerosol and has recently been demonstrated effective in identifying transported BBA over Europe, while its applications in South China remain scarce. Here, we present LIF lidar observations of fluorescent aerosol conducted at Nanping, South China. The detected fluorescent layer was relatively weak, with a fluorescence signal intensity more than two orders of magnitude lower than the N2 Raman signal intensity (maximum spectral fluorescence backscatter coefficient ≈0.16×10-5 Mm−1 sr−1 nm−1). Nevertheless, it showed a distinct spectral signature compared with typical urban aerosol. Integration of multi-source datasets suggests that the long-range transported BBA emitted by weak fire activity in the Indo-China Peninsula (ICP) was a major contributor to the fluorescent layer. Furthermore, the concurrent presence of BBA and enhanced water vapor indicated a humid environment favorable for aerosol processing. Consistent with the high sensitivity of LIF lidar reported in previous studies, our observations show that weak, long-range transported BBA from the ICP can be observed over South China during periods of relatively weak fire activity, thereby offering new insights into their transport mechanisms and potential environmental impacts.

Abstract Greenland atmospheric blocking, a persistent anticyclonic pattern, strongly influences local and regional weather and climate. It is known to significantly exacerbate Greenland ice sheet melt and mass loss in summer as well as influence atmospheric conditions over the North Atlantic. Greenland blocking has been observed to increase in intensity since the summer of 2000s, but this trend has partly reversed after 2012. This decadal variability is highly correlated with the negative phase of the North Atlantic Oscillation (NAO), the dominant pattern of climate variability in the North Atlantic. However, summer NAO shows different temporal variation in June in comparison with later summer months, i.e., July and August. In this study, we analyse the individual summer months in turn to evaluate differences between their respective spatial patterns of Greenland blocking events. We use different approaches including a Self-Organising Map (SOM) to evaluate individual blocking days, and an event-based analysis to assess the development of blocking events over the course of 7 days. The results show that spatial patterns of Greenland blocking are similar between July and August but are distinctly different in June. In particular, Greenland blocking in June is strongly related to cyclonic wave breaking over the eastern Atlantic. Our analysis using wave activity flux of the zonally varying mean flow reveals a distinct pattern of wave energy and pseudo-momentum associated with cyclonic wave breaking prior to Greenland blocking high anomalies in June, in contrast to the other two summer months. This might partially explain the difference in the spatial patterns and evolution of blocking in June compared with July and August.

• Extension of PASTIS-R dataset with Sentinel-1 SLC data for multimodal agricultural mapping. • Reflection symmetry of agricultural targets makes dual-pol decomposition features redundant with backscatter coefficients. • Interferometric coherence boosts robustness under severe optical cloud cover. • In multimodal fusion, biased coherence matches elaborately processed alternatives, simplifying operational deployment. • Coherence gains transfer across held-out regions, with larger marginal contributions under regional distribution shifts.

Abstract Accurate quantification of emission reductions from jurisdictional-scale forest mitigation efforts depends, among many other things, on selecting appropriate durations for the reference period, which determines the historical baseline, and the crediting period, during which performance is measured. Selecting the durations of these periods is problematic. Periods that are too long may not adequately represent deforestation rates in countries where these rates are changing, as rates from the distant past may no longer reflect conditions during the crediting period; periods that are too short are sensitive to interannual variability. Carbon standards and reporting frameworks currently have varying requirements (e.g., 5- or 10-year periods), but the implications of reference and crediting period durations remain underexplored.

Using a global remote sensing dataset of deforestation rates for 71 tropical countries and territories from 1990 to 2025, we evaluated how the duration of reference and crediting period durations affect changes in deforestation rates, using a sliding window approach. We compared deforestation rates during hypothetical crediting periods against historical rates during hypothetical reference periods for all possible combinations of period durations for each country. We report the period durations that minimized the difference between the two rates, which we call the Reference-Crediting Period Discrepancy (RCPD). We did this for all countries together, then for countries with and without deforestation trends, and finally for each country separately.

Both very short and very long reference periods resulted in high RCPD. On average, the lowest RCPD (51%) occurred at a 12-year reference and 7-year crediting period, and a 10-year reference and 5-year crediting period were almost as good as optimal (56% RCPD). Shorter reference periods were worse; a 5-year reference period gave an average RCPD of 69%. Stratifying countries based on detected trends resulted in shorter optimal periods for countries with a trend and longer periods for countries dominated by noise, as expected, with a slight reduction in RCPD (50%). Customizing period durations for each country reduced average RCPD to 11%, but carbon crediting requires a more standardized approach. These results suggest that longer reference periods (10 or more years) are better than shorter ones, especially for countries without a trend in their historical deforestation rates.

Abstract Urbanization in tropical regions is expanding rapidly. In Indonesia, the new capital city, Ibu Kota Nusantara, located on the island of Borneo, represents a major regional development aimed at balancing rapid urban growth with climate resilience. Understanding how the development of Ibu Kota Nusantara affects heat stress during heatwave events is therefore critical for climate-informed urban planning in this tropical environment. We employed high resolution (1 km) Weather Research and Forecasting simulations coupled with the Building Effect Parameterization urban scheme to analyze 12 historical heatwave events spanning different climate modes, comparing current land cover with urban development scenarios agreed by the Indonesian government. Across all simulations, urbanization led to 2m air temperature increases of 0.2°C to 1.8°C, driven by substantial decreases in latent heat flux exceeding 60 W m⁻² and corresponding increases in sensible heat flux of 30 to 50 W m⁻². However, Wet Bulb Globe Temperature increased by only 0.1°C to 0.5°C in eastern coastal areas and decreased in central and western Ibu Kota Nusantara, as relative humidity reductions of 2% to 14% offset the warming effect on physiological heat stress. Modes of climate variability systematically modulated these outcomes, with wetter conditions producing stronger humidity compensation than drier conditions. Climate-informed urban design and adaptation to help manage heat stress in Ibu Kota Nusantara should therefore consider strategies to moderate temperature increases, without increasing humidity.

• GLASS, MODIS, and PML were used to analyze mountain GPP-ET dynamics. • GPP increased then declined with elevation, while ET showed weaker dependence. • GPP-ET coupling was strongest at middle elevations during growing seasons. • GPP-ET coupling was strongest at low elevations during non-growing seasons. • Inter-product inconsistency showed topographic and temporal amplification.

Abstract The Yarlung Tsangpo Grand Canyon (YGC), a major moisture channel to the Tibetan Plateau, features a complex and poorly understood precipitation structure. This study pioneers the use of China's FengYun-3G Precipitation Measurement Radar (FY-3G PMR) to analyze the precipitation structure over the YGC during a plateau vortex event on 28 June 2024. Results reveal a dual-peak vertical structure with maxima at 2 km ASL and near the 5.5 km ASL 0°C layer. Vortex development enhances ice production aloft, intensifying mixed-phase precipitation and warm-rain processes below. While stratiform precipitation dominates in frequency over the YGC, convective precipitation is 2–3 times more intense with a broader particle spectrum. Orographic lifting on northern slopes triggers intense convection with extreme precipitation rates (>10 mm/hr). This study demonstrates FY-3G PMR's capability to resolve fine-scale precipitation structures over the plateau area, providing critical insights for further application of PMR over complex terrain.

Abstract Hydroclimatic risks in semi-arid Patagonia are intensifying under climate change, exposing the limitations of top-down approaches and underscoring the need for integrative and context-sensitive frameworks. This article identifies and analyzes hydroclimatic risks in the Chubut River Basin, Patagonia, Argentina, through an interdisciplinary and participatory design that integrates scientific information with local knowledge, territorial histories, and gender and diversity perspectives. Methodologically, the study is organized into four steps—Integration, Synthesis, Conceptualization, and Products—guided by two cross-cutting axes: gender and diversity, and environmental communication. The integration step developed five lines of evidence: hydroclimatic context, socio-political context, hydroclimatic risk with gender and diversity perspective, archaeological and historical territorial perspectives, and present and future territorial perspectives. These lines combine original analyses, previous research, and literature review with local perspectives gathered through interviews, participatory workshops, and engagement processes with governmental, community, and educational actors. Workshops, inspired by principles of Latin American popular education and popular feminism, created horizontal spaces for dialogue, knowledge co-production, and the identification of key themes. Reflexive debriefings, triangulation, and participant validation reinforced the credibility and transferability of results. The synthesis step integrated these diverse perspectives into a set of core ideas grounded in situated socio-environmental knowledge. These core ideas informed the conceptualization stage, where narratives and key messages were developed using a qualitative interpretive approach aligned with mixed-methods perspectives. The final stage translated these narratives into communication and educational products, including policy briefs, infographics, journalistic materials, videos, and a pedagogical toolbox, all supported by environmental communication principles. The study demonstrates how climatic variability, territorial processes, governance arrangements, and gender inequalities shape water quality and availability. Throughout all stages, the transversal incorporation of gender and diversity perspectives and environmental communication strengthened the co-production of context-sensitive insights, fostered trust, expanded access to climate information, and contributed to more inclusive and participatory water governance.