This study assesses the effective climate sensitivity (EffCS) and transient climate response (TCR) derived from global energy budget constraints within historical simulations of 8 CMIP6 global climate models (GCMs). These calculations are enabled by use of the Radiative Forcing Model Intercomparison Project (RFMIP) simulations, which permit accurate quantification of the historical effective radiative forcing. We find that long-term historical energy budget constraints generally underestimate EffCS from CO2 quadrupling and TCR from CO2 ramping, both by 12%, owing to changes in radiative feedbacks and changes in ocean heat uptake efficiency. Atmospheric GCMs forced by observed warming patterns produce lower values of EffCS that are more in line with those inferred from observed historical energy budget constraints. Understanding the discrepancies between modeled and observed historical surface warming patterns remains critical for constraining EffCS and TCR from the historical record.

As part of the (AC)3 Arctic Amplification project, we are studying the influence of specific sea ice conditions like the presence of leads or polynyas on micro- and macrophysical cloud properties such as cloud fraction, altitude, thickness, thermodynamic phase, and their coupling state with respect to the underlying surface during the MOSAiC expedition’s legs 1 to 3. Micro- and macrophysical properties of surface-coupled clouds are analyzed as a function of sea ice concentration (SIC) in the vicinity of the ground-based atmospheric remote-sensing observations onboard the RV Polarstern. Only situations are analyzed where wind favored the transportation of air from location where open sea ice is detected. Cloud microphysical properties are obtained from the CloudNet cloud target classification algorithm which uses the atmospheric remote-sensing instrumentation suite on board of RV Polarstern provided by the US Atmospheric Radiation Measurement (ARM) mobile facility, the TROPOS ship-borne Atmosphere observation suite (OCEANET) and liquid water path retrievals by the University of Cologne. Primarily, the classical Matlab-based CloudNet classifications retrieved by TROPOS are used. Furthermore, the recently released ARM “evaluation” Active Remote Sensing Clouds (ARSCL) data product for the KA-band cloud radar is also evaluated by the new Python CloudNet version developed at the Finish Meteorological Institute. Discrepancies between those two CloudNet versions will be evaluated and reported as feedback for the ARM evaluation data set. High resolution (1-km) merged AMSR2-MODIS satellite retrievals of Sea Ice Concentration by the University of Bremen are used as information for sea ice monitoring. The present contribution only exploits SIC data, however future studies will focus on MOSAiC specific products for the classification of leads. Statistics for the cloud properties as a function of SIC will be presented as first approach to investigate the influence of sea ice conditions to central Arctic clouds.

Titan’s ionosphere hosts a globally distributed non-trivial dusty ion-ion plasma, providing an environment for studies of dusty ionospheres that is in many aspects unique in our solar system. Thanks to the Cassini mission, Titan’s ionosphere also features one of the largest dusty plasma datasets from 126 flybys of the moon over 13 years, from 2004 to 2017. Recent studies have shown that negatively charged dust dramatically alters the electric properties of plasmas, in particular planetary ionospheres. Utilizing the full plasma content of the moon’s ionosphere (electrons, positive ions and negative ions/dust grains), we derive the electric conductivities and define the conductive dynamo region. Our results show that using the full plasma content increases the Pedersen conductivities at ~1300 km altitude by 20% compared to the earlier estimates without charged dust, while the Hall conductivities indicate a reverse Hall effect at ~900 km altitude (closest approach) and below. The dayside conductivities are shown to be factor ~7-9 larger than on the nightside, owing to higher dayside plasma densities.

“Climate tipping elements” often refer to large-scale earth systems with the potential to respond nonlinearly to anthropogenic climate change by transitioning towards substantially different long-term states upon passing key thresholds, frequently referred to as “tipping points.” In some but not all cases, such changes could produce additional greenhouse gas emissions or radiative forcing that could compound global warming. Improving understanding of tipping elements is important for predicting future climate risks. Here we review mechanisms, predictions, impacts, and knowledge gaps associated with ten notable earth systems proposed to be climate tipping elements. We evaluate which tipping elements are more imminent and whether shifts will likely manifest rapidly or over longer timescales. Some tipping elements are significant to future global climate and will likely affect major ecosystems, climate patterns, and/or carbon cycling within the 21st century. However, assessments under different emissions scenarios indicate a strong potential to reduce or avoid impacts associated with many tipping elements through climate change mitigation. Most tipping elements do not possess the potential for abrupt future change within years, and some proposed tipping elements may not exhibit tipping behavior, rather responding more predictably and directly to the magnitude of forcing. Nevertheless, significant uncertainties remain associated with many tipping elements, highlighting an acute need for further research and modeling to better constrain risks.

Nonlinear internal waves (NLIWs) are prevalent on the northern continental shelf south of Hainan Island in the South China Sea. However, our understanding of these NLIWs is still in a preliminary state. In the study, through a synergistic analysis of satellite observations, in situ measurements and numerical simulations, we take a step toward fully elucidating the generation and propagation process of the NLIWs on the northern continental shelf south of Hainan Island. Both mooring and satellite observations suggest that the Xisha Islands remotely generate the NLIWs on the northern continental shelf south of Hainan Island; moreover, more than one source exists in the Xisha Islands. Based on the realistic topography, stratification and tidal forcing, two-dimensional numerical simulations using the MITgcm reveal that the NLIWs observed on the continental shelf can be generated from different sills in Xisha Islands through the internal tidal beam or mixed tidal lee wave regime. Furthermore, the internal tide energy flux estimation suggests that the locally generated internal tides emanating from the continental shelf break play an essential role in the baroclinic energy field of the deep sea while their influence on the baroclinic energy field of the mid-continental shelf can be almost negligible.

Regional data assimilation is conducted for a coastal estuary using the ensemble Kalman filter, real observation data from Ise Bay, Japan, and a simulation model called the Ise Bay Simulator. The applicability and robustness of the method are then examined. We also analyze the relationship between the boundary conditions, which add perturbations and the data assimilation results of water temperature and salinity. A method of creating an ensemble by perturbing three boundary conditions (atmospheric forcing, lateral boundary conditions, river discharge forcing) is then proposed. In situ water temperature and salinity profiles observed at fixed points are assimilated daily. The proposed assimilation method provides stable data assimilation without unnatural values for water temperature and salinity throughout the year. Further, applying a perturbation to the three boundary conditions does not lead to filter divergence, thus indicating good applicability and robustness. Applying a perturbation to the three boundary conditions does not degenerate the ensemble spread. According to a sensitivity experiment, perturbing the atmospheric boundary conditions of air temperature and wind speed increases the ensemble spread of water temperature, especially near the surface layer. Wind speed has the greatest influence on the magnitude of the salinity ensemble spread, and its dominance depends on location. Perturbation of lateral boundary conditions increases the ensemble spread of water temperature and salinity at all water depths near the bay mouth, and the observations are effectively assimilated. Perturbation of river discharge forcing successfully assimilates water temperature and salinity near the estuary.

Recent advances in modeling Rayleigh-Benard convection have demonstrated the existence of turbulent superstructures, whose life and morphology largely varies with Rayleigh (Ra) and Prandtl (Pr) numbers. These structures appear as a two scale phenomena, where small scale rolls organize in larger convection cells, and can be modelled only in 3D on a simulation box characterized by a very large (>10) width/height (W/L) ratio, and sufficiently refined to resolve the boundary layer up to Ra = 108 (>100 divisions in height) and to Ra = 1010 (>200 divisions). To achieve this goal, we use our own 3D Parallel Python implementation of the Lattice Boltzmann Method, tested to run with linear efficiency on thousands of cores. We show the dependency of horizontal fluctuations of RMS of temperature and vertical velocity in the middle of the box and illustrate how the superstructures emerge for W/L ratios of Terrestrial Planets and Super Earths, and quantify the duration of these superstructures and the likely implications for the evolution of their surface features. The effect of the P/T dependent viscosity and thermal conductivity is finally discussed.

Long-term measurements at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) at the North Slope Alaska (NSA) site in Utqiagvik, Alaska and from the Multidisciplinary drifting Observatory for the study of the Arctic Climate (MOSAiC) expedition are being used to study the climatology of clouds containing supercooled liquid (SCL) in the Western and Central Arctic. Classification of cloud hydrometeors in the liquid, ice or mixed phase of the cloud is determined by using the Cloudnet algorithm developed by the Finish Meteorological Institute. We apply the Cloudnet processing chain to a set of ground-based remote sensing measurements from the NSA site and the ARM mobile facility and the TROPOS shipborne atmosphere observation suite (OCEANET) on board of the RV Polarstern research vessel during MOSAiC. In order to accurately detect cloud droplets and SCL layers within mixed-phase clouds, Cloudnet relies on lidar observations. Lidars however suffer from total signal attenuation at a penetration optical depth of about three. Conversely cloud radars with their capability to penetrate multiple liquid layers can be used to expand the identification of cloud phase to the entire vertical column beyond the lidar signal attenuation height by using information of the cloud radar Doppler spectrum. The Leipzig Institute for Meteorology (LIM) recently developed a deep learning approach for reVealing supercOOled liquiD beyOnd lidar attenuatiOn (VOODOO) which benefits from the morphological features in cloud radar Doppler spectra to extract further information related to the existence of SCL using Cloudnet’s target classification as supervisor. The current contribution presents a SCL climatology obtained using Cloudnet for the NSA site along with case-studies for MOSAiC where VOODOO results are contrasted with the standard Cloudnet outputs. Advantages and limitations of both methods will be presented to the scientific community.

One way to test our understanding of the impact of convective processes on the isotopic composition of water vapor and precipitation is to analyze the isotopic mesoscale variations during organized convective systems such as tropical cyclones or squall lines. The goal of this study is to understand these isotopic mesoscale variations with particular attention to isotopic signals in near-surface vapor and precipitation that may be present in observations and in paleoclimate proxies. With this aim, we run cloud resolving model simulations in radiative-convective equilibrium in which rotation or wind shear is added, allowing us to simulate tropical cyclones or squall lines. The simulations capture the robust aspects of mesoscale isotopic variations in observed cyclones and squall lines. We interpret these variations using a simple water budget model for the sub-cloud layer of different parts of the domain. We find that rain evaporation and rain-vapor diffusive exchanges are the main drivers of isotopic depletion within cyclones and squall lines. Horizontal advection spreads isotopic anomalies, thus reshaping the mesoscale isotopic pattern. Variations in near-surface relative humidity and wind speed have a significant impact on d-excess variations within tropical cyclones, but the evaporation of sea spray is not necessary to explain the observed enrichment in the eye. This study strengthens our understanding of mesoscale isotopic variability and provides physical arguments supporting the interpretation of paleoclimate isotopic archives in tropical regions in terms of past cyclonic activity.

Phytoplankton bloom in the Gulf of Elat/Aqaba was studied before mainly using one-dimensional models and observations from the northern Gulf. Thus, the spatial variability within the Gulf and the contribution of physical processes such as horizontal advection to the bloom have not yet been studied. Moreover, various factors such as light limitation are still debated. Here we used a three-dimensional coupled physical-ecological model for the Gulf of Elat/Aqaba to study the mechanisms for phytoplankton bloom throughout the Gulf. We found the southern surface bloom to be higher than the northern surface. In contrast, southern integrated bloom is lower than the northern bloom. These differences are due to spatial variations in the mixed layer depth, which is much deeper in the northern Gulf compared with the south. Moreover, horizontal advection controls phytoplankton integrated biomass during the bloom, a process often neglected when dealing with phytoplankton blooms. Finally, we found that light limits growth of the northern integrated bloom.

Sub-grid topographic heterogeneity has large impacts on surface energy balance and land-atmosphere interactions. However, the impacts of representing sub-grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub-grid topographic representations on surface energy balance, turbulent heat flux and scalar (co-)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub-grid topographic representations in ELM were compared: (1) the default sub-grid structure (D), (2) the recently developed sub-grid topographic structure (T), and (3) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (1) the default plane-parallel radiative transfer scheme (PP) and (2) the parameterization scheme (TOP) that accounts for sub-grid topographic effects on solar radiation. A series of simulations with the three grid structures (D, T and 1KM) and two treatments of solar radiation (TOP and PP) were carried out in the Sierra Nevada, California. There are significant differences between TOP and PP in the 1-km simulated surface energy balance, but the differences in the mean values and standard deviations become small when aggregated to the grid-scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations than the D configuration, and better captures the sub-grid topographic effects on surface energy balance as well as surface boundary conditions. These results underline the importance of representing sub-grid topographic heterogeneities in LSMs and motivate future research to understand the sub-grid topographic effects on land-atmosphere interactions over mountain areas.

Advancing the understanding of watershed dynamics and underpinning scientific studies on the changes in water cycles, ecological patterns, and climate trends often rely on streamflow data acquired at gaging stations operated by various monitoring agencies. The monitoring methods used at these stations are based on empirical or semi-empirical rating curves obtained with statistical analysis uniformly applied to datasets collected in steady and unsteady flows. These one-to-one ratings are subsequently used for estimating steady and unsteady flows, even though, in the latter case, the relationships between flow variables are different for the rising and falling phases of the flow hydrographs. The non-singled relationships are more prominent in lowland areas subjected to high flows, where the streamflow variables display a hysteretic behavior. Recent advances in measurement technologies (e.g., acoustic-, radar-, and image-based), have dramatically transformed our capabilities to conduct in-situ measurements. This paper demonstrates such capabilities by presenting new information extracted from directly measured data and novel algorithms applied to simultaneous measurements of stages and index velocities acquired with a SonTek Side-Looker (pertaining to the family of Horizontal Acoustic Current Profilers-HADCP) at a river location prone to hysteresis. The presented results demonstrate a) the capability of the conventional monitoring methods (i.e., index-velocity approach supported by HADCPs) to capture the dynamics of the unsteady flows, b) the opportunity offered by HADCP measurements to re-think monitoring methods altogether by using directly measured data and their spatial and temporal gradients in conjunction with canonical flow equations (i.e., St Venant Equations) without using ratings, and c) the opportunity to exploit subtle features of the hysteretic behavior for developing short-term forecasting of flood crest magnitude and its arrival time using only in-situ acquired data, without making recourse to hydrologic/hydraulic modeling. Moving away from the traditional empirically based ratings, would unquestionably contribute to reducing uncertainties related to modeling flow routing, thus improving the quality of conventional forecasts.

Improving the representation of plant hydraulic behavior in vegetation and land-surface models is critical for improving our predictions of the impacts of drought stress on ecosystem carbon and water fluxes. Species-specific hydraulic traits play an important role in determining the response of ecosystem carbon and water fluxes to water stress. Here, we present plans for the development of the Finite-difference Ecosystem-scale Tree Crown Hydrodynamics model version 3 (FETCH3), a tree hydrodynamic model which builds upon its predecessors FETCH and FETCH2. FETCH3 simulates water transport through the soil, roots, and xylem as flow through porous media. The model resolves water potentials along the vertical dimension, and stomatal response is linked to xylem water potential. The tree-level model is scaled to the plot scale based on the species composition and canopy structure of the plot, allowing the model to be validated using both tree-level observations (sap flux) and plot-level observations (eddy covariance). We will collect data from multiple sites that have both sap flux and eddy covariance measurements for analysis. The Predictive Ecosystem Analyzer (PEcAn) will be used for optimization of the hydraulic parameters in FETCH3 for different plant types in multiple sites. We plan to use this new modeling framework to examine the interactions among water stress, species-specific hydraulic strategies, and stomatal regulation across different species and ecosystem types.

Dynamic topography, defined as the deflection of the Earth’s surface due to the convecting mantle, causes changes in vertical land motions (VLM). We aim to estimate the effect of dynamic topography on VLM along the North American Atlantic Coast, which is a region where land subsidence influences relative sea-level rise and other coastal hazards. The contribution of dynamic topography to VLM continues to be debated since previous studies show a range in the rate change of dynamic topography for this region, which are in part due to uncertainties in Earth’s rheology. In this investigation, we model global mantle convection to better assess the role of dynamic topography on VLM along the North American Atlantic Coast. We are implementing a time-dependent approach using the finite element code ASPECT (v2.2.0). We constrain our initial temperature conditions using the tomography models SAVANI, GYPSUM, S40RTS, and TX2008 and then explore both linear and non-linear rheological models. The two rheological models allow us to assess differences in the rate change of dynamic topography globally with a nonlinear rheology compared to a linear rheology. We expect this work will allow us to better understand the contribution of dynamic topography to VLM along the North American Atlantic Coast.

Most Earth surface carbonates precipitate out of isotopic equilibrium with their host solution, complicating the use of stable isotopes in paleoenvironment reconstructions. Disequilibrium can arise from exchange reactions in the DIC-H2O system as well as during crystal growth reactions in the DIC-CaCO3 system. Existing models account for kinetic isotope effects in these systems separately but the models have yet to be combined in a general framework. Here, a box model is developed for describing disequilibrium carbon, oxygen, and clumped isotope effects in the CaCO3-DIC-H2O system. The model is applied to inorganic calcite precipitation experiments where there is a known CO2 influx and CaCO3 outflux. The example provided can be adapted to other situations involving CO2 absorption (e.g., corals, foraminifera, high-pH travertines) or degassing (e.g., speleothems, low-pH travertines, cryogenic carbonates) and/or mixing with other DIC sources.

Reconnection in the magnetotail occurs along so-called X-lines, where magnetic field lines tear and detach from plasma on microscopic spatial scales (comparable to particle gyroradii). In 2017–2020 the Magnetospheric MultiScale (MMS) mission detected X-lines in the magnetotail enabling their investigation on local scales. However, the global structure and evolution of these X-lines, critical for understanding their formation and total energy conversion mechanisms, remained virtually unknown because of the intrinsically local nature of observations and the extreme sparsity of concurrent data. Here we show that mining a multi-mission archive of space magnetometer data collected over the last 25+ years and then fitting a magnetic field representation modeled using flexible basis-functions, faithfully reconstructs the global pattern of X-lines; 24 of the 26 modeled X-lines match ($B_z=0$ isocontours are within $\sim2$ Earth radii or $R_E$) or nearly match ($B_z=2$ nT isocontours are within $\sim2 R_E$) the locations of the MMS encountered reconnection sites.

Watersheds serve as natural spatial boundaries whose characteristics are often indicators of the hydrologic processes within them. Watershed characteristics are frequently used as predictors, parameters, or proxies in models of hydrologic and ecologic dynamics. Developments in DEMs over the past decade have resulted in elevation data spanning the globe that allows watershed delineation at arbitrary locations. In tandem, satellite-based observations and large-scale modeling efforts provide many sources of near-global watershed characteristics, e.g. topography, soil types, vegetation, climate, permafrost extent, and many more. However, with growing data availability comes a growing need for tools that can rapidly query and summarize them. We developed River and Basin Profiler (RaBPro), a Python module providing a pipeline to delineate drainage basins for any point on Earth and calculate watershed statistics for practically any geospatial raster dataset. RaBPro makes use of the MERIT-Hydro or HydroBASINS datasets to define watershed polygons, which can be exported in GeoJSON or ESRI shapefile format for further use in GIS software. RaBPro will also generate streamlines and river elevation profiles. Finally, RaBPro calculates statistics over delineated basins using Google Earth Engine (GEE). By taking advantage of GEE’s vast dataset archive and distributed computing system, RaBPro can quickly compute many statistics over even very large basins efficiently and without the need for storing large geo-rasters locally. Additionally, users may upload their own datasets to GEE and create custom statistic functions.

Domain repositories can be an integral part of extensive community support systems that extend from proposal planning and writing, through project initiation and implementation, data collection, management, and archive, to publication of results and access to data by other community members. These long-term relationships are reflected in multiple contributions (data, software, results, papers, …) by community members and recognizing these contributions should be an important community-building best-practice for these repositories. Identifiers for people and organizations are critical for recognizing community members and, equally important, for making connections between them and all of the various objects in the research ecosystem. This Figure demonstrates connections that can made once identifiers are integrated into the research ecosystem. Most domain repositories provide DOIs for datasets in the repository. The metadata for those DOIs can include identifiers for some authors (ORCIDs) along with names of organizations they are affiliated with (affiliations). In practice, most authors in these metadata records do not have ORCIDs but, if they have an ORCID once, that ORCID can be spread across all of the datasets they have contributed to, increasing connectivity across the repository. Affiliations can also be spread across multiple contributions, with some caveats. If identifiers (i.e. RORs) exist and can be found for the affiliated organizations, they can be inserted into the metadata, again increasing connectivity. Many domain repositories maintain lists of research papers that have used data from the archive. Metadata for these papers also provide a potential source for identifiers and affiliations. These can also be harvested and spread across the repository, again improving connectivity. These ideas and techniques were applied to UNAVCO, a repository for data related to geodesy with a well-developed community with over 5000 archived datasets. The connectivity for the repository is below 10% for dataset contributors and 0% for RORs. Applying these techniques can increase the connectivity to 56% for contributors and 49% for RORs.