Ocean primary production constitutes approximately half of global biospheric production, affecting both fisheries productivity and biogeochemical cycling. Although climate change is predicted to affect the ocean's biological productivity, the extent of the global impact is poorly quantified. Assessing changes in the ocean biosphere using remote sensing data is challenged by the relatively short length of the observational record, restricting our ability to disentangle fluctuations in internal variability from forced anthropogenic trends. Additionally, the majority of ocean circulation models with embedded biogeochemistry do not skillfully predict observational records of ocean chlorophyll at ocean time series locations. To overcome these limitations, we have constructed a synthetic ensemble of global ocean chlorophyll concentration. By employing statistical resampling methods to the SeaWiFS and MODIS ocean color datasets and creating surrogate climate modes of ENSO and PDO, we quantify the range of internal climate variability in the 20 year observational record and create multiple alternate realities for the possible evolution of the ocean biosphere over time. Our synthetic ensemble can be used for a variety of purposes, including diagnosing patterns of internal variability and emergence of anthropogenic trends in observed chlorophyll, and validating Earth system model representation of such variability.

Venus is commonly known as the beautiful Evening Star of the night sky. Despite its bulk composition and size being similar (Interior ESI 0.98) to those of Earth, Venus is an extremely hot and dry planet, with temperatures ranging from 630 - 740K. With the current physical conditions, a potential areal biosphere could exist on the sulphuric acid-dominated clouds, providing moderate temperatures and pressures due to high altitudes. A theorised Iron or Sulphur metabolism could support exotic life in these extremely acidic (pH 0) conditions. The past habitability for regular life could be connected to the present habitability for exotic life through possible evolution, extending the possible Habitability timeline. Due to its smaller orbital distance (0.7 AU), Venus could have been the first habitable planet in the solar system, with optimistic models showing that Venus may have had a complex atmosphere and a liquid ocean for around 2 billion years, before the moist runaway greenhouse effect transformed the planet. High values for the D/H ratio and carbon abundance, combined with Venus’s slow rotation rate indicate the potential for biological life developing in Past Venus’s possible Earth-like conditions. These models were analysed from a perspective of Habitability, along with probable evolution into the present exotic life.

Terrestrial primary productivity plays a pivotal role as a forcing factor of atmospheric CO2 and drives biospheric carbon dynamics. India is one of the largest GHGs emitters, yet less is understood in carbon cycling in terrestrial ecosystems. Here we explored the trend and magnitude of gross and net productivities of India for the last two decades (2000 – 2019) by integrating satellite observation from MODIS, remote sensing-based CASA model and twenty DGVMs from the TRENDY ensemble. Preliminary results exhibited a unimodal response across the data products with an overall positive trend and a declining decadal trend for 2010 – 2019. Alongside, the SPEI drought severity index across various ecological zones indicated India was more positively sensitive to wet span than the dry. We found that the ecosystems were drastically shifting their nature to C source with a positive trend in the productivities and were mediated by the changing climate. The analysis also revealed the increasing decadal amplitude of GPP by 0.0884 Pg C/Year, NBP by 0.0096 Pg C/Year, NEP by 0.0195 Pg C/Year, NPP by 0.0448 Pg C/Year and NEE by 0.0161 Pg C/Year. CASA underestimated the magnitudes but with the temporal synchronisation of the ensemble. Seasonal variability across the agro-ecological zones was more sensitive and was an offset for the declining productivities in the primaeval forests of India. The monsoon season contributed to the interannual variability of India. Higher uncertainty in productivities was observed in the high greening areas, whereas it contradicted NBP by reflecting a stable trend. Our results underscore the nature of C variability in the terrestrial ecosystems of India; and, they indicate that C release has reacted stronger than the C uptake, which was substantially inferred from NEE across the ecological zones.

Extremely halophilic archaea are microbes that thrive under very high salinities (>20% NaCl) and are almost exclusively placed in the class Halobacteria. In addition to their characteristic preference for high salinity and moderately high temperatures, many species of this class are resistant to desiccation, vacuum, and radiation, making them interesting targets for Astrobiological studies as model organisms and particularly relevant for the study of Mars, as highlighted by several authors. This class has a wide environmental range and includes species that live in salty biotopes such as salterns, salted foods, subterranean halite, lakes, or even in deep-sea brines in a list that includes several analogue sites. One current bottleneck of research with this group is the dispersed nature of data associated with its species. Our study partly addresses this by compiling phenotypic information and records of astrobiological experiments for all Halobacteria. We have established a database (HAPIE- Halophilic Archaea Phenotypic Information Explorer) that allows us to quickly compare different species as well as analyse trends and identify knowledge gaps and research opportunities. Our study identified gaps in coverage and knowledge (both at the level of taxonomy and range of tested parameters) and assisted us in defining new testing priorities.

Urban water utilities are increasingly exploring cooperative regional water supply investment and management strategies due to climate change and growing demands. Theoretically, regional cooperative agreements promise improved resource efficiency by realizing economies of scale, adding flexibility for achieving improved supply reliability, and, ideally, limiting individual and collective financial risks. However, there has been little research exploring how implementation uncertainties in the partners’ cooperative actions shape infrastructure investment and management pathways’ robustness and drive counterparty risks. Counterparty risks potentially exacerbate collaborating partners’ vulnerability to the supply and financial challenges they initially sought to mitigate through cooperation. To address these concerns, we introduce the Safe Operating Spaces for Deeply Uncertain Water Supply Pathways (DUSOS Pathways) framework. The framework, demonstrated on the multi-city Sedento Valley benchmarking test case, facilitates the formal characterization of the effects of implementation uncertainty within cooperative regional water supply investment and management policy pathways. Results demonstrate the path-dependent effects of implementation uncertainties in short-term operational drought mitigation instruments and long-term infrastructure investments. Our analysis further reveals the potential for increased regional conflict due to asymmetries between partners’ vulnerabilities to the actions of cooperating partners that can be exacerbated by other deeply uncertain factors that reduce their robustness (e.g., demand growth rates). The study finally delineates safe operating spaces, beyond which utilities experience robustness degradation and increased vulnerabilities to future uncertainties to guide implementation of cooperative policy pathways. Overall, this framework is broadly applicable to regional systems seeking to navigate complex cooperative regional water supply investment and management policy pathways.

Directional discontinuities (DDs) are defined as abrupt changes of the magnetic field orientation. We use observations from ESA’s Cluster mission to compile a database of events: 4216 events are identified in January-April 2007, and 5194 in January-April 2008. Localized time-scale images depicting angular changes are created for each event, and a preliminary classification algorithm is designed to distinguish between: simple - isolated events, and complex - multiple overlapping events. In 2007, 1806 events are pre-classified as simple, and 2410 as complex; in 2008, 1997 events are simple, and 3197 are complex. A supervised machine learning approach is used to recognize and predict these events. Two models are trained: one for 2007, which is used to predict the results in 2008, and vice-versa for 2008. To validate our results, we investigate the discontinuity occurrence rate as a function of spacecraft location. When the spacecraft is in the solar wind, we find an occurrence rate of ~2 DDs per hour and a 50/50 % ratio of simple/complex events. When the spacecraft is in the Earth’s magnetosheath, we find that the total occurrence rate remains around 2 DDs/h, but the ratio of simple/complex events changes to ~25/75 %. This implies that about half of the simple events observed in the solar wind are classified as complex when observed in the magnetosheath. This demonstrates that our classification scheme can provide meaningful insights, and thus be relevant for future studies on interplanetary discontinuities.

Soil and Water Assessment Tool (SWAT) is one of the widely used hydrological models, especially it has been successfully applied for the assessment of the impact of land use land cover and best management practices scenarios. But it is less applicable for type of research that requires integration or optimization with other models since it cannot update the land-use and best management practice information efficiently and it should be run separately when results for the multiple watersheds are needed. These days, the attention on the water security has been growing and interdisciplinary works desires integration of the hydrological model with other models are being highlighted. Thus, there are needs of development of the surrogate model which is computationally efficient and applicable to multiple watersheds. In this research, we propose the surrogate model of the SWAT with novel machine learning techniques such as random forest model. As a first step, the models are trained with the SWAT data from one watershed, which is a Maumee River Watersheds. Models for flow, mineral phosphorus, total nitrogen, total phosphorus, and sediment transport are built separately, and the model performance was above satisfactory level based on R-squared value, Nash-Sutcliffe efficiency, and percent bias. In addition, the surrogate models were tested for the different best management practices adoption scenarios and were trained additional data to make the model valid for the wide range of the best management practices adoption ratios. Finally, the surrogate models were expanded to multiple watersheds, by training SWAT results from Huron River Watersheds and River Raisin and they evaluated with the R-squared value. High R-squared values indicated that the surrogate model could be used in place of SWAT.

1.0 Abstract :Plastic pollution is a growing environmental problem that affects ecosystems worldwide. With a population of over 1.4 billion people, Africa has the potential to be a major contributor to the global plastic waste crisis, generating an estimated 17 million tons of plastic waste annually. The impact of plastic pollution in Africa is particularly severe, with large quantities of plastic waste ending up in rivers and oceans, leading to the death of marine life and the destruction of ecosystems. Although policies aimed at reducing plastic waste exist in many African countries, their effectiveness has been limited due to poor governance, inadequate resources, and a lack of focus on the root causes of plastic pollution. To effectively address plastic pollution, sustainable solutions such as the circular economy, innovative technology, public awareness, and international collaboration are needed.2.0 Introduction :Plastic pollution is an urgent and escalating environmental problem that affects ecosystems across the globe. While plastic production has increased rapidly in recent years, with an estimated 300 million tons produced each year [1], much of this plastic ends up in the ocean and other bodies of water. Plastics currently make up to 85% of marine trash, and this percentage is expected to triple by 2040 [2]. This is particularly concerning for Africa, which has a population of over 1.4 billion people in 2022 [3], and generates an estimated 17 million tons of plastic waste each year [4]. With a projected population of 2.5 billion by 2050 [4], the demand for plastics, especially single-use plastics (SUP), is likely to increase further. Unfortunately, the effects of SUP pollution are particularly severe in Africa, where enormous volumes end up in rivers and seas, killing marine life and destroying ecosystems [4].While many African nations have regulations in place to reduce SUP waste, their efficacy has been limited. Some regulations focus on banning SUP, but enforcement has been difficult due to inadequate funding and poor governance. Furthermore, these policies do not address the underlying issues that contribute to SUP pollution, such as inadequate recycling infrastructure and deficient waste management systems. Between 1990 and 2017, 230 metric tons of plastics, including SUP, entered Africa, with the highest proportion going to Egypt, Nigeria, South Africa, Algeria, Morocco, and Tunisia [5]. Primary plastic manufacture in eight African nations produced only 15 metric tons between 2009 and 2015 [5]. Much of this waste ends up in the ocean, leading to negative impacts on marine ecosystems and local communities. Inadequate waste management systems and poor public awareness exacerbate the problem, leading to the accumulation of plastic waste, particularly SUP, in landfills and oceans. It is therefore obvious that current policies alone are not enough to comprehensively address the issue of SUP pollution in Africa. This commentary aims to shed light on the impact of SUP on the marine ecosystem, highlight the current policies and strategies to reduce SUP in Africa, and explore sustainable solutions to reduce SUP pollution in Africa

While most rivers and lakes follow predictable principles of hydrology and geology, a few defy the rules. Some rivers diverge rather than converge; some rivers flow two directions; some lakes have not one but two outlets; some watersheds have ambiguous boundaries. The scientific literature on these exceptions is sparse, scattered, and, in some cases, conflicting. We provide an authoritative overview of nine unusual natural drainages in North and South America, including river bifurcations and bifurcation lakes: Casiquiare River, Arroyo Partido, Wayambo River, Atchafalaya River, North Two Ocean Creek, Divide Creek, Committee’s Punch Bowl, Echimamish River, and Wollaston Lake. Most instances are found on flatlands and saddles. Some watershed boundaries are still unresolved or even dynamic, suggesting river formation in progress. We discuss the exploration, geophysical settings, hydrology, ecology, use, and management of these extraordinary drainages.

The Undergraduate Student Instrumentation Project (USIP) was a NASA program to engage undergraduate students in rigorous scientific research, for the purposes of innovation and developing the next generation of professionals in space research. The program is student led and executed from initial ideation of research objectives to the design and deployment of scientific payloads. The University of Houston was selected twice to participate in the USIP programs. The first program (USIP_UH I) ran from 2013 to 2016. USIP_UH II ran from 2016 to 2019. USIP_UH I (USIP_UH II) at the University of Houston was composed of eight (seven) research teams developing six (seven), distinct, balloon-based scientific instruments. This project was a for-credit course two years in duration. The program has been so successful in terms of improved student career outcomes the University has decided to continue the project with purely local funding. The pandemic has produced a substantial instructional challenge since this project is a lab class! The virtual classroom that we designed to meet this need provides tools for ongoing collaboration, revisions, storage, project planning, systems engineering, and a tool to request immediate feedback from faculty and fellow researchers. Additionally, the classroom provides an ongoing place to store data from different students for many years. New students can use this continuity in a consistent and secure way. We also provided tools for conferencing and communication. A combination of several tools were selected and customized to meet this need. These tools include Google Classroom, Microsoft Teams, Slack, Git, Groupme, and Zoom.

Recent breakthroughs in artificial intelligence (AI), and particularly in deep learning (DL), have created tremendous excitement and opportunities in the earth and environmental sciences communities. To leverage these new ‘data-driven’ technologies, however, one needs to understand the fundamental concepts that give rise to DL and how they differ from ‘process-based’, mechanistic modelling. This paper revisits those fundamentals and addresses 10 questions often posed by earth and environmental scientists with the aid of a real-world modelling experiment. The overarching objective is to contribute to a future of AI-assisted earth and environmental sciences where DL models can (1) embrace the typically ignored knowledge base available, (2) function credibly in ‘true’ out-of-sample prediction, and (3) handle non-stationarity in earth and environmental systems. Comparing and contrasting earth and environmental problems with prominent AI applications, such as playing chess and trading in stock markets, provides critical insights for better directing future research in this field.

Densely spaced GPR and complex resistivity measurements on a 30,000 square meters site in a region of enigmatic sinkhole occurrences in unconsolidated Quaternary sediments have featured unexpected and highlighting results from both a meteorite impact research and an engineering geology point of view. The GPR measurements and a complex resistivity/IP electrical imaging revealed extended subrosion depressions related with a uniformly but in various degrees of intensity deformed loamy and gravelly ground down to at least 10 m depth. Two principle observations could be made from both the GPR high-resolution measurements and the more integrating resistivity and IP soundings with both petrophysical evidences in good complement. Subrosion can be shown to be the result of prominent sandy-gravelly intrusions and extrusions typical of rock liquefaction processes well known to occur during strong earthquakes. Funnel-shaped structures with diameters up to 25 m near the surface and reaching down to the floating ground water level at 10 m depth were measured. GPR radargrams could trace prominent gravelly-material transport bottom-up within the funnels. Seen in both GPR tomography and resistivity/IP sections more or less the whole investigated area is overprinted by wavy deformations of the unconsolidated sediments with wavelengths of the order of 5 - 10 m and amplitudes up to half a meter, likewise down to 10 m depth. Substantial earthquakes are not known in this region. Hence, the observed heavy underground disorder is considered the result of the prominent earthquake shattering that must have occurred during the Holocene (Bronze Age/Celtic era) Chiemgau meteorite impact event that produced a 60 km x 30 km sized crater strewn field directly hosting the investigated site. Depending on depth and size of floating aquifers local concentrations of rock liquefaction and seismic surface waves (probably LOVE waves) to produce the wavy deformations could develop, when the big disintegrated meteoroid (a loosely bound asteroid or a comet of roughly estimated 1 km size) hit the ground. The observations in the Chiemgau area emphasize that studied paleoliquefaction features and wavy deformations (e.g. seismites) need not necessarily have originated solely from paleoseismicity but can provide a recognizable regional impact signature.

Fossil fuel combustion, land use change and other human activities have increased the atmospheric carbon dioxide (CO2) abundance by about 50% since the beginning of the industrial age. The atmospheric CO2 growth rates would have been much larger if natural sinks in the land biosphere and ocean had not removed over half of this anthropogenic CO2. As these CO2 emissions grew, uptake by the ocean increased in response to increases in atmospheric CO2 partial pressure (pCO2). On land, gross primary production (GPP) also increased, but the dynamics of other key aspects of the land carbon cycle varied regionally. Over the past three decades, CO2 uptake by intact tropical humid forests declined, but these changes are offset by increased uptake across mid- and high-latitudes. While there have been substantial improvements in our ability to study the carbon cycle, measurement and modeling gaps still limit our understanding of the processes driving its evolution. Continued ship-based observations combined with expanded deployments of autonomous platforms are needed to quantify ocean-atmosphere fluxes and interior ocean carbon storage on policy-relevant spatial and temporal scales. There is also an urgent need for more comprehensive measurements of stocks, fluxes and atmospheric CO2 in humid tropical forests and across the Arctic and boreal regions, which are experiencing rapid change. Here, we review our understanding of the atmosphere, ocean, and land carbon cycles and their interactions, identify emerging measurement and modeling capabilities and gaps and the need for a sustainable, operational framework to ensure a scientific basis for carbon management.

In August 2017, a smoke plume from wildfires in British Columbia and the Northwest Territories recirculated and persisted over northern Canada for over two weeks. We compared a full-factorial set of NASA Goddard Institute for Space Studies ModelE simulations of the plume to satellite retrievals of aerosol optical depth and carbon monoxide, finding that ModelE performance was dependent on the model configuration, and more so on the choice of injection height approach, aerosol scheme and biomass burning emissions estimates than to the choice of horizontal winds for nudging. In particular, ModelE simulations with free-tropospheric smoke injection, a mass-based aerosol scheme and high fire NOx emissions led to unrealistically high aerosol optical depth. Using paired simulations with fire emissions excluded, we estimated that for 16 days over an 850 000 km2 region, the smoke decreased planetary boundary layer heights by between 253 m and 547 m, decreased downward shortwave radiation by between 52 Wm-2 and 172 Wm-2, and decreased surface temperature by between 1.5 oC and 4.9 oC, the latter spanning an independent estimate from operational weather forecasts of a 3.7 oC cooling. The strongest surface climate effects were for ModelE configurations with more detailed aerosol microphysics that led to a stronger first indirect effect.

Radiation-topography interaction plays an important role in the surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of radiation-topography interaction over the TP. Land-atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for radiation-topography interaction overall improves E3SM’s performance in simulating surface climate. The winter cold bias in air temperature decreases from -4.48 K to -3.70 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP’s radiation-topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts.

Following the Hunga Tonga–Hunga Ha’apai (HTHH) eruption in January 2022, a significant reduction in stratospheric hydrochloric acid (HCl) was observed in the Southern Hemisphere mid-latitudes during the latter half of 2022, suggesting potential chlorine activation. The objective of this study is to comprehensively understand the substantial loss of HCl in the aftermath of HTHH. Satellite measurements along with a global chemistry-climate model are employed for the analysis. We find strong agreement of 2022 anomalies between the modeled and the measured data. The observed tracer-tracer relations between N2O and HCl indicate a significant role of chemical processing in the observed HCl reduction, especially during the austral winter of 2022. Further examining the roles of chlorine gas-phase and heterogeneous chemistry, we find that heterogeneous chemistry emerges as the primary driver for the chemical loss of HCl, with the reaction between HOBr and HCl on sulfate aerosols identified as the dominant loss process.

We present a new metric for braiding intensity to characterize multi-thread systems (e.g., braided and anastomosing rivers) called the Entropic Braiding Index, eBI. This metric is a generalization of the widely used Braiding Index (BI) which is simply the average count of intercepted channels per cross-section. The co-existence of diverse channels (widely different widths and discharges) within river cross-sections distorts the information conveyed by BI, since its value does not reflect the diversity and natural variability of the system. Moreover, the fact that BI is extremely sensitive to resolution (BI increases at higher resolution as smaller scale channels can be resolved) challenges its applicability. eBI, addresses these main drawbacks of BI. eBI is rooted in the concept of Shannon Entropy, and its value can be intuitively interpreted as the equivalent number of equally important (in terms of discharge) channels per cross-section. Thus, if the channels observed in a multi-thread system are all carrying the same amount of discharge, eBI has the same value of BI. On the other hand, if a very dominant channel in terms of discharge co-exists with much smaller channels, eBI would take a value slightly larger than 1 (note that the actual value would depend on the number of small channels and their relative size with respect to the dominant channel). We present a comparative study of BI and eBI for different multi-thread rivers obtained from numerical simulations and remote-sensing data and for different discharge stages. We also provide evidence of the robustness of eBI in contrast to BI when a given river system is studied under different resolutions. Finally, we explore the potential of eBI as a metric to characterize different types of multi-thread systems and their stability.

Due to heavy urbanisation, approaches in greener cities are required. This is addressed by a number of initiatives, including seeing the city as an ecosystem, and the dialogue between economy and ecology. Sustainable and resilient cites mean connection between the city and the landscape, bringing the landscape into the city, for example through nature based solutions such as green walls or through more open spaces which are green, such as urban parks. In this context the landscape quality of the city can be judged. The renewable energy in the city can relate to solar energy of the passive house which can be a house of heavy geomaterials. In this contribution the authors present their approach to sustainable and resilient cities, including the first author’s approach to renewable energy and landscape quality. The first author would like to thank the Inclusiveness Target Countries grant scheme for supporting participation in the conference to represent the COST Action TU1401 (http://www.cost-rely.eu/).