Earth System Research Articles

Navigating ecological novelty towards planetary stewardship: challenges and opportunities in biodiversity dynamics in a transforming biosphere.

Human-induced global changes, including anthropogenic climate change, biotic globalization, trophic downgrading and pervasive land-use intensification, are transforming Earth's biosphere, placing biodiversity and ecosystems at the forefront of unprecedented challenges. The Anthropocene, characterized by the importance of Homo sapiens in shaping the Earth system, necessitates a re-evaluation of our understanding and stewardship of ecosystems. This theme issue delves into the multifaceted challenges posed by the ongoing ecological planetary transformation and explores potential solutions across four key subthemes. Firstly, it investigates the functioning and stewardship of emerging novel ecosystems, emphasizing the urgent need to comprehend the dynamics of ecosystems under uncharted conditions. The second subtheme focuses on biodiversity projections under global change, recognizing the necessity of predicting ecological shifts in the Anthropocene. Importantly, the inherent uncertainties and the complexity of ecological responses to environmental stressors pose challenges for societal responses and for accurate projections of ecological change. The RAD framework (resist-accept-direct) is highlighted as a flexible yet nuanced decision-making tool that recognizes the need for adaptive approaches, providing insights for directing and adapting to Anthropocene dynamics while minimizing negative impacts. The imperative to extend our temporal perspective beyond 2100 is emphasized, given the irreversible changes already set in motion. Advancing methods to study ecosystem dynamics under rising biosphere novelty is the subject of the third subtheme. The fourth subtheme emphasizes the importance of integrating human perspectives into understanding, forecasting and managing novel ecosystems. Cultural diversity and biological diversity are intertwined, and the evolving relationship between humans and ecosystems offers lessons for future stewardship. Achieving planetary stewardship in the Anthropocene demands collaboration across scales and integration of ecological and societal perspectives, scalable approaches fit to changing, novel ecological conditions, as well as cultural innovation. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Intensified surface chlorophyll responses to the Indian ocean dipole under greenhouse warming

Abstract The Indian Ocean Dipole (IOD) has been proposed to be a key driver of biological processes in the Indian Ocean (IO) in the present climate. Given the expected influence of global warming on both the properties of the IOD and the biogeochemistry within the IO, a key question arises: How will the relationship between the IOD and surface chlorophyll evolve in a warming climate? Here, utilizing simulations from the Coupled Model Intercomparison Project (CMIP) Phase 6 Earth System models, our findings reveal a notable intensification in the IOD-chlorophyll relationship under greenhouse warming. This intensification is linked to an increase in surface chlorophyll during the June to November period of positive IOD years in the southeastern IO (SEIO). Interestingly, our analysis indicates a substantial rise in IOD-related chlorophyll levels in a warming climate, despite a marked decrease in IOD-induced upwelling in the SEIO. The shallower thermocline leads to an increase in the mean nutrient concentration in the subsurface layer, thereby facilitating an enhanced anomalous nutrient supply to the surface layer, which contributes to increased surface chlorophyll. Our study highlights the consequential effects of IOD on chlorophyll dynamics and underscores the need for improved coupled models to advance our understanding of biophysical interactions in the IO in response to global warming.

Projected changes in ultraviolet index and UV doses over the twenty-first century: impacts of ozone and aerosols from CMIP6.

This study evaluated the health-related weighted ultraviolet radiation (UVR) due to the total ozone content (TOC) and the aerosol optical depth (AOD) changes. Clear-sky Ultraviolet Index (UVI), daily doses, and exposure times for erythema induction (Dery and Tery) and vitamin D synthesis (DvitD and TvitD) were computed by a radiative transfer estimator. TOC and AOD data were provided by six Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). For projections, we consider four Shared Socioeconomic Pathways scenarios-SSPs (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5)-and two time-slices (near: 2041-2060 and far future: 2081-2100). UVR projections showed pronounced changes for the summer hemispheres in the far future. TOC increases in mid- and high latitudes of the Southern Hemisphere caused decreases in UVR at the summer solstice. However, projections did not indicate sun-safe exposure conditions in South America, Australia, and Southern Africa. On the contrary, exposure around solar noon from 10 to 20min will still be sufficient to induce erythema in skin type III individuals throughout this century. In southern Argentina and Chile, the UVR insufficiency for vitamin D synthesis at solar noon in skin type III remains the same during this century at the winter solstice. In the Northern Hemisphere, UVI and Dery at the summer solstice should remain high (UVI ≥ 8; Dery ~ 7.0kJm-2) in highly populated locations. Above 45 °N, UVR levels cannot be enough to synthesize vitamin D in skin type III during the boreal winter. Our results show that climate change will affect human health through excess or lack of solar UVR availability.

Mid-Holocene West African monsoon rainfall enhanced in EC-Earth simulation with dynamic vegetation feedback

AbstractProxy records have shown that the Mid-Holocene was a period of humid conditions across West Africa, with an enhanced West African Monsoon (WAM) and vegetated conditions in areas currently characterized by desert, often referred to as the Green Sahara. However, General Circulation Models regularly struggle with recreating this strengthened Mid-Holocene monsoon in West Africa. Vegetation feedbacks has long been viewed as an essential process modulating the monsoon variability in West Africa, and simulations using prescribed vegetation to recreate a Green Sahara have shown a strengthened WAM and increased rainfall. However, simulations with prescribed vegetation in Sahara represent an idealized vegetation cover and do not take any environmental heterogeneity into account. Furthermore, this only represents a one-directional forcing by the vegetation on the climate rather than the full vegetation feedback. To address this, we have simulated the Mid-Holocene (~ 6 ka) climate using the Earth System Model EC-Earth3-Veg. The results show that coupled dynamic vegetation reproduces an apparent enhancement of the WAM, with the summer rainfall in the Sahel region increasing by 15% compared to simulations with a prescribed modern vegetation cover. Vegetation feedbacks enhance the warming of the Sahara region, deepens the Sahara Heat Low, results in increased rainfall and strengthens monsoonal flow across West Africa. However, the enhancement is still below what can be viewed in proxy reconstructions, highlighting the role of model limitation and biases and the importance of investigating other processes, such as the interactive aerosol-albedo feedback.

Wide range of possible trajectories of North Atlantic climate in a warming world.

Decadal variability in the North Atlantic Ocean impacts regional and global climate, yet changes in internal decadal variability under anthropogenic radiative forcing remain largely unexplored. Here we use the Community Earth System Model 2 Large Ensemble under historical and the Shared Socioeconomic Pathway 3-7.0 future radiative forcing scenarios and show that the ensemble spread in northern North Atlantic sea surface temperature (SST) more than doubles during the mid-twenty-first century, highlighting an exceptionally wide range of possible climate states. Furthermore, there are strikingly distinct trajectories in these SSTs, arising from differences in the North Atlantic deep convection among ensemble members starting by 2030. We propose that these are stochastically triggered and subsequently amplified by positive feedbacks involving coupled ocean-atmosphere-sea ice interactions. Freshwater forcing associated with global warming seems necessary for activating these feedbacks, accentuating the impact of external forcing on internal variability. Further investigation on seven additional large ensembles affirms the robustness of our findings. By monitoring these mechanisms in real time and extending dynamical model predictions after positive feedbacks activate, we may achieve skillful long-lead North Atlantic decadal predictions that are effective for multiple decades.

Exploration and Maintenance of Homeomorphic Orbit Revs in the Elliptic Restricted Three-Body Problem

A novel station-keeping strategy leveraging periodic revolutions of homeomorphic orbits in the Elliptic Restricted Three-Body Problem within the pulsating frame is presented. A systemic approach founded on arc-length continuation is presented for the discovery, computation, and classification of periodic revolutions that morph from their traditional circular restricted three-body counterparts to build an a priori dataset. The dataset is comprehensive in covering all possible geometric architectures of the restricted problem. Shape similarity is quantified using Hausdorff distance and works as a filter for the station-keeping algorithm in relation to appropriate target conditions. Finally, an efficient scheme to quantify impulsive orbit maintenance maneuvers that minimize the total fuel cost is presented. The proposed approach is salient in its generic applicability across any elliptic three-body system and any periodic orbit family. Finally, average annual station-keeping costs using the described methodology are quantified for selected “orbits of interest” in the cis-lunar and the Sun–Earth systems. The robustness and efficacy of the approach instill confidence in its applicability for realistic mission design scenarios.

Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)

Abstract. Machine learning (ML) algorithms can be used in Earth system models (ESMs) to emulate sub-grid-scale processes. Due to the statistical nature of ML algorithms and the high complexity of ESMs, these hybrid ML ESMs require careful validation. Simulation stability needs to be monitored in fully coupled simulations, and the plausibility of results needs to be evaluated in suitable experiments. We present the coupling of SuperdropNet, a machine learning model for emulating warm-rain processes in cloud microphysics, with ICON (Icosahedral Nonhydrostatic) model v2.6.5. SuperdropNet is trained on computationally expensive droplet-based simulations and can serve as an inexpensive proxy within weather prediction models. SuperdropNet emulates the collision–coalescence of rain and cloud droplets in a warm-rain scenario and replaces the collision–coalescence process in the two-moment cloud microphysics scheme. We address the technical challenge of integrating SuperdropNet, developed in Python and PyTorch, into ICON, written in Fortran, by implementing three different coupling strategies: embedded Python via the C foreign function interface (CFFI), pipes, and coupling of program components via Yet Another Coupler (YAC). We validate the emulator in the warm-bubble scenario and find that SuperdropNet runs stably within the experiment. By comparing experiment outcomes of the two-moment bulk scheme with SuperdropNet, we find that the results are physically consistent and discuss differences that are observed in several diagnostic variables. In addition, we provide a quantitative and qualitative computational benchmark for three different coupling strategies – embedded Python, coupler YAC, and pipes – and find that embedded Python is a useful software tool for validating hybrid ML ESMs.

Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

Abstract. Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

Pan‐Arctic distribution modeling reveals climate‐change‐driven poleward shifts of major gelatinous zooplankton species

AbstractAnthropogenic activities, including climate change, are hypothesized to cause increases in gelatinous zooplankton population sizes and blooms. In the most rapidly changing ecosystem, the Arctic Ocean, this hypothesis has not yet been verified, and gelatinous zooplankton is commonly excluded from large‐scale modeling studies. Our modeling study is based on an extensive biogeographic dataset, aggregating from four open‐source databases (Ocean Biodiversity Information System, Global Biodiversity Information Facility, Jellyfish Database Initiative, and PANGAEA). It includes data on eight of the most reported gelatinous zooplankton taxa of the pan‐Arctic region (Aglantha digitale, Sminthea arctica, Periphylla periphylla, Cyanea capillata, Oikopleura vanhoeffeni, Fritillaria borealis, Mertensia ovum, and Beroe spp.). By coupling three‐dimensional species distribution models with oceanographic components from the Max Planck Institute Earth System Model (MPI‐ESM1.2), run for historical (1950–2014) and future (2050–2099) periods under the shared socioeconomic pathway SSP370 scenario forcing, we identified species with expanding or contracting habitat ranges in response to climate change. Our projections indicated a general tendency for gelatinous zooplankton distributions to shift, with varying degrees of suitable habitat expansion (largest for the scyphozoan C. capillata ~ +180%) or contraction (largest for the hydrozoan Sm. arctica ~ −15%). Seven of the eight species modeled, which—similar to the majority of gelatinous taxa occurring in the Arctic Ocean—predominantly represented arcto‐boreal and boreal taxa, are projected to shift to northern latitudes. Hence, profound impacts on the Arctic marine environment and associated ecosystem services can be expected.

Future changes in spatially compounding hot, wet or dry events and their implications for the world’s breadbasket regions

Recent years were characterized by an increase in spatially co-occurring hot, wet or dry extreme events around the globe. In this study we analyze data from multi-model climate projections to analyze the occurrence of spatially compounding events and area affected in future climates under scenarios at +1.5 ∘C, +2.0 ∘C, +3.0 ∘C and higher levels of global warming using Earth System Model simulations from the 6th Phase of the Coupled Model Intercomparison Project. Since spatially compounding extreme events can strongly amplify societal impacts as economic supply chains are increasingly interdependent, we want to highlight that the world’s breadbasket regions are projected to be particularly affected by an increase in spatially co-occurring hot, wet or dry extreme events, posing risks to the global food security. We show that the spatial extent of top-producing agricultural regions being potentially threatened by climate extremes will increase drastically if global mean temperatures shift from +1.5 ∘C to +2.0 ∘C. Further we identify a large increase in the projected global land area concurrently affected by hot, wet or dry extremes with increased global warming posing risk to other industries and sectors in addition to the agricultural sector.

Effects of Surface Turbulence Flux Parameterizations on the MJO: The Role of Ocean Surface Waves

Abstract This study investigates the sensitivity of the Madden–Julian oscillation (MJO) to changes to the bulk flux parameterization and the role of ocean surface waves in air–sea coupling using a fully coupled ocean–atmosphere–wave model. The atmospheric and ocean model components of the Energy Exascale Earth System Model (E3SM) are coupled to a spectral wave model, WAVEWATCH III (WW3). Two experiments with wind speed–dependent bulk algorithms (NCAR and COARE3.0a) and one experiment with wave-state-dependent flux (COR3.0a-WAV) were conducted. We modify COARE3.0a to include surface roughness calculated within WW3 and also account for the buffering effect of waves on the relative difference between air-side and ocean-side momentum flux. Differences in surface fluxes, primarily caused by discrepancies in drag coefficients, result in significant differences in MJO’s properties. While COARE3.0a has better convection–circulation coupling than NCAR, it exhibits anomalous MJO convection east of the date line. The wave-state-dependent flux (COR3.0-WAV) improves the MJO representation over the default COARE3.0 algorithm. Strong easterlies over the Pacific Ocean in COARE3.0a enhance the latent heat flux (LHFLX). This is responsible for the anomalous MJO propagation after the date line. In COR3.0a-WAV, waves reduce the anomalous easterlies, leading to a decrease in LHFLX and MJO dissipation after the date line. These findings highlight the role of surface fluxes in MJO simulation fidelity. Most importantly, we show that the proper treatment of wave-induced effects in bulk flux parameterization improves the simulation of coupled climate variability.

Aerosol impacts on the East Asian winter monsoon: Insights from TaiESM1 and CMIP6 simulations

AbstractThe East Asian winter monsoon (EAWM) is an important climate pattern in Southeast Asia. This study delved into the aerosol effects on the EAWM by analysing simulations conducted with the Taiwan Earth System Model version 1 (TaiESM1) model, part of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our assessment, validated against observational and reanalysis data, revealed that TaiESM1 effectively replicates the robust circulation of the EAWM and aerosol concentrations, placing its performance above average level among CMIP6 models. Notably, the simulated global mean aerosol optical thickness exhibited an approximately 20% increase from 1850 to 2014. The increased aerosols corresponded to a weakened Aleutian Low and an intensified Siberian High, leading to a weakened EAWM in the lower atmosphere over extratropical areas. In addition, the cooling across the Northern Hemisphere might affect enhanced northerly winds at approximately 10°N, which are situated in the southern part of the EAWM. An analysis of the near‐surface temperature budget indicated that the aerosol‐induced cooling in East China and India was primarily driven by changes in shortwave and longwave radiation fluxes, albeit slightly offset by sensible heat and latent heat fluxes. Furthermore, our study also reveals that while the mechanisms through which anthropogenic aerosols affect the northern portion of the EAWM vary across most CMIP6 models, their impacts on the tropical region remain consistent.

The effects of bathymetry on the long-term carbon cycle and CCD

The shape of the ocean floor (bathymetry) and the overlaying sediments provide the largest carbon sink throughout Earth's history, supporting ~one to two orders of magnitude more carbon storage than the oceans and atmosphere combined. While accumulation and erosion of these sediments are bathymetry dependent (e.g., due to pressure, temperature, salinity, ion concentration, and available productivity), no systemic study has quantified how global and basin scale bathymetry, controlled by the evolution of tectonics and mantle convection, affects the long-term carbon cycle. We reconstruct bathymetry spanning the last 80 Myr to describe steady-state changes in ocean chemistry within the Earth system model LOSCAR. We find that both bathymetry reconstructions and representative synthetic tests show that ocean alkalinity, calcite saturation state, and the carbonate compensation depth (CCD) are strongly dependent on changes in shallow bathymetry (ocean floor ≤600 m) and on the distribution of the deep marine regions (>1,000 m). Limiting Cenozoic evolution to bathymetry alone leads to predicted CCD variations spanning 500 m, 33 to 50% of the total observed variations in the paleoproxy records. Our results suggest that neglecting bathymetric changes leads to significant misattribution to uncertain carbon cycle parameters (e.g., atmospheric CO2 and water column temperature) and processes (e.g., biological pump efficiency and silicate-carbonate riverine flux). To illustrate this point, we use our updated bathymetry for an Early Paleogene C cycle case study. We obtain carbonate riverine flux estimates that suggest a reversal of the weathering trend with respect to present-day, contrasting with previous studies, but consistent with proxy records and tectonic reconstructions.

The role of the basic state in the climate response to future Arctic sea ice loss

There is great uncertainty in the atmospheric circulation response to future Arctic sea ice loss, with some models predicting a shift towards the negative phase of the North Atlantic Oscillation (NAO), while others predicting a more neutral NAO response. We investigate the potential role of systematic model biases in the spread of these responses by modifying the unperturbed (or ‘control’) climate (hereafter referred to as the ‘basic state’) of the Canadian Earth system model version 5 (CanESM5) in sea ice loss experiments based on the protocol of the Polar Amplification Model Intercomparison Project. We show that the presence or absence of the stratospheric pathway in response to sea ice loss depends on the basic state, and that only the CanESM5 version that shows a weakening of the stratospheric polar vortex features a strong negative NAO response. We propose a mechanism that explains this dependency, with a key role played by the vertical structure of the winds in the region between the subtropical jet and the stratospheric polar vortex (‘the neck region winds’), which determines the extent to which anomalous planetary wave activity in response to sea ice loss propagates away from the polar vortex. Our results suggest that differences in the models’ basic states could significantly contribute to model spread in the simulated atmospheric circulation response to sea ice loss, which may inform efforts to narrow the uncertainties regarding the impact of diminishing sea ice on mid-latitude climate.

Assessing CESM2 Clouds and Their Response to Climate Change Using Cloud Regimes

Abstract The Community Earth System Model, version 2 (CESM2), has a very high climate sensitivity driven by strong positive cloud feedbacks. To evaluate the simulated clouds in the present climate and characterize their response with climate warming, a clustering approach is applied to three independent satellite cloud products and a set of coupled climate simulations. Using k-means clustering with a Wasserstein distance cost function, a set of typical cloud configurations is derived for the satellite cloud products. Using satellite simulator output, the model clouds are classified into the observed cloud regimes in both current and future climates. The model qualitatively reproduces the observed cloud configurations in the historical simulation using the same time period as the satellite observations, but it struggles to capture the observed heterogeneity of clouds which leads to an overestimation of the frequency of a few preferred cloud regimes. This problem is especially apparent for boundary layer clouds. Those low-level cloud regimes also account for much of the climate response in the late twenty-first century in four shared socioeconomic pathway simulations. The model reduces the frequency of occurrence of these low-cloud regimes, especially in tropical regions under large-scale subsidence, in favor of regimes that have weaker cloud radiative effects.

Ediacaran marine animal forests and the ventilation of the oceans.

The rise of animals across the Ediacaran-Cambrian transition marked a step-change in the history of life, from a microbially dominated world to the complex macroscopic biosphere we see today.1,2,3 While the importance of bioturbation and swimming in altering the structure and function of Earth systems is well established,4,5,6 the influence of epifaunal animals on the hydrodynamics of marine environments is not well understood. Of particular interest are the oldest "marine animal forests,"7 which comprise a diversity of sessile soft-bodied organisms dominated by the fractally branching rangeomorphs.8,9 Typified by fossil assemblages from the Ediacaran of Mistaken Point, Newfoundland,8,10,11 these ancient communities might have played a pivotal role in structuring marine environments, similar to modern ecosystems,7,12,13 but our understanding of how they impacted fluid flow in the water column is limited. Here, we use ecological modeling and computational flow simulations to explore how Ediacaran marine animal forests influenced their surrounding environment. Our results reveal how organism morphology and community structure and composition combined to impact vertical mixing of the surrounding water. We find that Mistaken Point communities were capable of generating high-mixing conditions, thereby likely promoting gas and nutrient transport within the "canopy." This mixing could have served to enhance local-scale oxygen concentrations and redistribute resources like dissolved organic carbon. Our work suggests that Ediacaran marine animal forests may have contributed to the ventilation of the oceans over 560 million years ago, well before the Cambrian explosion of animals.

Planetary Boundaries Nurturing the Grand Narrative of the Right to a Healthy Environment?

The profound changes in Earth systems dynamics are affecting the health of the entire planet and the realization of a broad range of human rights. In this paper, we propose that the grand narrative of human rights including the legal right to a clean, healthy and sustainable environment recognized by the United Nations in 2022 requires the acknowledgment of the interconnected challenges posed by planetary crises. We discuss how planetary boundaries (PB) research can provide evidence-based arguments and clarify State duties concerning their international human rights law commitments. The economic, social and cultural rights are deeply connected with the right to a healthy environment. Human rights to water, food, or health, for example, can all be understood in the context of Earth systems change. Civil and political rights go beyond individuals to include also collective action and participation to tackle planetary social-ecological challenges. Gaps remain in human rights law concerning some of the PBs, which risks overlooking the interconnected drivers of ecosystem degradation. Clearer legal standing and justification for legal demands, for example concerning the impacts of water use, land use and deforestation, are needed to tackle PB overshoot. States must act at various spaces including the global economic systems and the global supply chains of goods and services for humanity to reach planetary safe and just spaces. Weaving international human rights law and advances at various geographical scales on the right to a healthy environment with PB provides a powerful tool for defending the prerequisites of good life for everyone, everywhere.

A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015

Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

A comprehensive analysis of uncertainties in warm rain parameterizations in climate models based on in situ measurements

Abstract Because of the coarse grid size of Earth system models (ESM), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision-coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 kilometers and time steps on the order of 20-30 minutes. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally-resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semi-analytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rain-water tendency simulated by the SCE is roughly linear for time steps smaller than 10 minutes, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 minutes. After considering all uncertainties, the grid-mean and time-averaged rain-water tendency based on the parameterization schemes are mostly within a factor of 4 of the local benchmark results simulated by SCE.

In-depth characterization of particulate matter in a highly polluted urban environment at the foothills of Himalaya-Karakorum Region.

In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth's system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10µm, i.e., PM10 are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM10 samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24h average PM10 mass concentration along with standard deviation was investigated to be 586.83 ± 217.70µg/m3, which was around 13 times greater than the permissible limit of the world health organization (45µg/m3) and 4 times the Pakistan national environmental quality standards for ambient PM10 (150µg/m3). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90µg/m3, respectively. Water-soluble ions K+ and OC show a substantial association (R = 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of PM10, which are vital for preparing an air quality management plan in the urban environment of Peshawar.