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This technical paper presents an efficient and performance-oriented method to model reactive mass transport processes in environmental and geotechnical subsurface systems. The open source scientific software packages OpenGeoSys and IPhreeqc have been coupled, to combine their individual strengths and features to simulate thermohydro-mechanical-chemical coupled processes in porous and fractured media with simultaneous consideration of aqueous geochemical reactions. Furthermore, a flexible parallelization scheme using MPI (Message Passing Interface) grouping techniques has been implemented, which allows an optimized allocation of computer resources for the node-wise calculation of chemical reactions on the one hand, and the underlying processes such as for groundwater flow or solute transport on the other hand. The coupling interface and parallelization scheme have been tested and verified in terms of precision and performance. [ABSTRACT FROM AUTHOR]

We investigated the number of references per page for different European Geosciences Union journals, which share the same text formatting. Although the journals formally all focus on geoscience, different disciplines are covered, from ocean science and biogeosciences to the technical description of numerical model development. In this study, we show that the number of references per page is remarkably constant across these journals. In addition, this value has remained constant in the last decade, despite the consistent increase in the number of pages and in the number of references in almost all journals considered. Independently of the quality of the references used in an article, we show that for the EGU (European Geosciences Union) journals the average number of references per page is 3.82 (1.87-6.18 at 90% confidence level). This reveals that there is a consensus regarding optimum reference density, which depends on the journal's layout and not on the journal's discipline. [ABSTRACT FROM AUTHOR]

Atmospheric Methane (CH4) is generated as a standard product in recent version of the hyperspectral Atmospheric Infrared Sounder (AIRS-V6) aboard NASA's Aqua satellite at the NASA Goddard Earth Sciences Data and Information Services Center (NASA/GES/DISC). Significant improvements in AIRS-V6 was expected but without a thorough validation. This paper first introduced the improvements of CH4 retrieval in AIRS-V6 and some characterizations, then presented the results of validation using ∼1000 aircraft profiles from several campaigns spread over a couple of years and in different regions. It was found the mean biases of AIRS CH4 at layers 343-441 and 441-575 hPa are -0.76 and -0.05% and the RMS errors are 1.56 and 1.16%, respectively. Further analysis demonstrates that the errors in the spring and in the high northern latitudes are larger than in other seasons or regions. The error is correlated with Degree of Freedoms (DOFs), particularly in the tropics or in the summer, and cloud amount, suggesting that the "observed" spatiotemporal variation of CH4 by AIRS is imbedded with some artificial impact from the retrieval sensitivity in addition to its variation in reality, so the variation of information content in the retrievals needs to be taken into account in data analysis of the retrieval products. Some additional filtering (i.e. rejection of profiles with obvious oscillation as well as those deviating greatly from the norm) for quality control is recommended for the users to better utilize AIRS-V6 CH4, and their implementation in the future versions of the AIRS retrieval algorithm is under consideration. [ABSTRACT FROM AUTHOR]

In 2008, the first volume of the European Geosciences Union (EGU) journal Geoscientific Model Development (GMD) was published. GMD was founded because we perceived there to be a need for a space to publish comprehensive descriptions of numerical models in the geosciences. The journal is now well established, with the submission rate increasing over time. However, there are several aspects of model publication that we believe could be further improved. In this editorial we assess the lessons learned over the first few years of the journal's life, and describe some changes to GMD's editorial policy, which will ensure that the models and model developments are published in such a way that they are of maximum value to the community. These changes to editorial policy mostly focus on improving the rigour of the review process through a stricter requirement for access to the materials necessary to test the behaviour of the models. Throughout this editorial, "must" means that the stated actions are required, and the paper cannot be published without them; "strongly encouraged" means that we encourage the action, but papers can still be published if the criteria are not met; "may" means that the action may be carried out by the authors or referees, if they so wish. We have reviewed and rationalised the manuscript types into five new categories. For all papers which are primarily based on a specific numerical model, the changes are as follows: - The paper must be accompanied by the code, or means of accessing the code, for the purpose of peer-review. If the code is normally distributed in a way which could compromise the anonymity of the referees, then the code must be made available to the editor. The referee/ editor is not required to review the code in any way, but they may do so if they so wish. - All papers must include a section at the end of the paper entitled "Code availability". In this section, instructions for obtaining the code (e.g. from a supplement, or from a website) should be included; alternatively, contact information should be given where the code can be obtained on request, or the reasons why the code is not available should be clearly stated. - We strongly encourage authors to upload any user manuals associated with the code. - For models where this is practicable, we strongly encourage referees to compile the code, and run test cases supplied by the authors where appropriate. - For models which have been previously described in the "grey" literature (e.g. as internal institutional documents), we strongly encourage authors to include this grey literature as a supplement, when this is allowed by the original authors. - All papers must include a model name and version number (or other unique identifier) in the title. It is our perception that, since Geoscientific Model Development (GMD) was founded, it has become increasingly common to see model descriptions published in other more traditional journals, so we hope that our insights may be of general value to the wider geoscientific community. [ABSTRACT FROM AUTHOR]

The article presents a study which aims to describe the influence of different characteristics of assimilation system on the surface ozone in Europe. It states that the evaluation of the background error covariance matrix (BECM) was emphasized. The result of the study shows that the data assimilation system was efficient in bring the model assimilations closer to observations.

A numerical model based on Radial Basis Function-generated Finite Differences (RBFFD) is developed for simulating the Global Electric Circuit (GEC) within the Earth's atmosphere, represented by a 3-D variable coefficient linear elliptic PDE in a sphericallyshaped volume with the lower boundary being the Earth's topography and the upper boundary a sphere at 60 km. To our knowledge, this is (1) the first numerical model of the GEC to combine the Earth's topography with directly approximating the differential operators in 3-D space, and related to this (2) the first RBF-FD method to use irregular 3-D stencils for discretization to handle the topography. It benefits from the mesh-free nature of RBF-FD, which is especially suitable for modeling high-dimensional problems with irregular boundaries. The RBF-FD elliptic solver proposed here makes no limiting assumptions on the spatial variability of the coefficients in the PDE (i.e. the conductivity profile), the right hand side forcing term of the PDE (i.e. distribution of current sources) or the geometry of the lower boundary. [ABSTRACT FROM AUTHOR]

Over the anthropocene methane has increased dramatically. Wetlands are one of the major sources of methane to the atmosphere, but the role of changes in wetland emissions is not well understood. The Community Land Model (CLM) of the Community Earth System Models contains a module to estimate methane emissions from natural wetlands and rice paddies. Our comparison of CH4 emission observations at 16 sites around the planet reveals, however, that there are large discrepancies between the CLM predictions and the observations. The goal of our study is to adjust the model parameters in order to minimize the root mean squared error (RMSE) between model predictions and observations. These parameters have been selected based on a sensitivity analysis. Because of the cost associated with running the CLM simulation (15 to 30 min on the Yellowstone Supercomputing Facility), only relatively few simulations can be allowed in order to find a near optimal solution within an acceptable time. Our results indicate that the parameter estimation problem has multiple local minima. Hence, we use a computationally efficient global optimization algorithm that uses a radial basis function (RBF) surrogate model to approximate the objective function. We use the information from the RBF to select parameter values that are most promising with respect to improving the objective function value. We show with pseudo data that our optimization algorithm is able to make excellent progress with respect to decreasing the RMSE. Using the true CH4 emission observations for optimizing the parameters, we are able to significantly reduce the overall RMSE between observations and model predictions by about 50 %. The CLM predictions with the optimized parameters agree for northern and tropical latitudes more with the observed data than when using the default parameters and the emission predictions are higher than with default settings in northern latitudes and lower than default settings in the tropics. [ABSTRACT FROM AUTHOR]

The Emission Scenario Projection (ESP) method produces future-year air pollutant emissions for mesoscale air quality modeling applications. We present ESP v2.0, which expands upon ESP v1.0 by spatially allocating future-year emissions to account for projected population and land use changes. In ESP v2.0, US Census Division-level emission growth factors are developed using an energy system model. Regional factors for population-related emissions are spatially disaggregated to the county level using population growth and migration projections. The county-level growth factors are then applied to grow a base-year emission inventory to the future. Spatial surrogates are updated to account for future population and land use changes, and these surrogates are used to map projected county-level emissions to a modeling grid for use within an air quality model. We evaluate ESP v2.0 by comparing US 12 km emissions for 2005 with projections for 2050. We also evaluate the individual and combined effects of county-level disaggregation and of updating spatial surrogates. Results suggest that the common practice of modeling future emissions without considering spatial redistribution over-predicts emissions in the urban core and under-predicts emissions in suburban and exurban areas. In addition to improving multi-decadal emission projections, a strength of ESP v2.0 is that it can be applied to assess the emissions and air quality implications of alternative energy, population and land use scenarios. [ABSTRACT FROM AUTHOR]

Models used to investigate impacts of climatic changes on spatio-temporal vegetation dynamics need to balance required accuracy with computational feasibility. To enhance the computational efficiency of these models, upscaling methods are required that maintain key fine-scale processes influencing vegetation dynamics. In this paper, an adjustable method – the dynamic two-layer classification concept (D2C) – for the upscaling of time- and space-discrete models is presented. D2C aims to separate potentially repetitive calculations from those specific to single grid cells. The underlying idea is to extract processes that do not require information about a grid cell's neighbourhood to a reduced-size non-spatial layer, which is dynamically coupled to the original two-dimensional layer. The size of the non-spatial layer is thereby adaptive and depends on dynamic classifications according to pre-specified similarity criteria. I present how D2C can be used in a model implementation on the example of TreeMig-2L, a new, efficient version of the intermediate-complexity forest-landscape model TreeMig. To discuss the trade-off between computational expenses and accuracy, as well as the applicability of D2C, I compare different model stages of TreeMig-2L via simulations of two different application scenarios. This comparison of different model stages demonstrates that applying D2C can strongly reduce computational expenses of processes calculated on the new non-spatial layer. D2C is thus a valuable upscaling method for models and applications in which processes requiring information about the neighbourhood constitute the minor share of the overall computational expenses. [ABSTRACT FROM AUTHOR]

The System for Automated Geoscientific Analyses (SAGA) is an open-source Geographic Information System (GIS), mainly licensed under the GNU General Public License. Since its first release in 2004, SAGA has rapidly developed from a specialized tool for digital terrain analysis to a comprehensive and globally established GIS platform for scientific analysis and modeling. SAGA is coded in C++ in an object oriented design and runs under several operating systems including Windows and Linux. Key functional features of the modular organized software architecture comprise an application programming interface for the development and implementation of new geoscientific methods, an easily approachable graphical user interface with many visualization options, a command line interpreter, and interfaces to scripting and low level programming languages like R and Python. The current version 2.1.4 offers more than 700 tools, which are implemented in dynamically loadable libraries or shared objects and represent the broad scopes of SAGA in numerous fields of geoscientific endeavor and beyond. In this paper, we inform about the system's architecture, functionality, and its current state of development and implementation. Further, we highlight the wide spectrum of scientific applications of SAGA in a review of published studies with special emphasis on the core application areas digital terrain analysis, geomorphology, soil science, climatology and meteorology, as well as remote sensing. [ABSTRACT FROM AUTHOR]

The problem of model complexity has been lively debated in environmental sciences as well as in the forest modelling community. Simple models are less input demanding and their calibration involves a lower number of parameters, but they might be suitable only at local scale. In this work we calibrated a simplified ecosystem process model (PRELES) to data from multiple sites and we tested if PRELES can be used at regional scale to estimate the carbon and water fluxes of Boreal conifer forests. We compared a multi-site (M-S) with site-specific (S-S) calibrations. Model calibrations and evaluations were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. To evaluate model performances BMC results were combined with more classical analysis of model-data mismatch (M-DM). Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 10 sites of Finland and Sweden were used in the study. Calibration results showed that similar estimates were obtained for the parameters at which model outputs are most sensitive. No significant differences were encountered in the predictions of the multi-site and site-specific versions of PRELES with exception of a site with agricultural history (Alkkia). Although PRELES predicted GPP better than evapotranspiration, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Our analyses underlined also the importance of using long and carefully collected flux datasets in model calibration. In fact, even a single site can provide model calibrations that can be applied at a wider spatial scale, since it covers a wide range of variability in climatic conditions. [ABSTRACT FROM AUTHOR]

Reliable numerical simulation plays a critical role in climate change study. The reliability includes bitwise identical reproducibility, i.e. bitwise identical result of numerical simulation can be reproduced. It is important to Earth system modeling and has already been used intra modeling groups for the model development. However, it is rarely considered in a wider range even worldwide. To help achieve the worldwide bitwise identical reproducibility, we introduce the detailed implementations for the bitwise identical reproducibility on the Community Coupler (C-Coupler) platform, a uniform runtime software environment that configures, builds and runs the models in the same manner. Moreover, we share a series of experiences and suggestions regarding the bitwise identical reproducibility. We believe that these implementations, experiences and suggestions can be easily extended to other model software platforms and can prospectively advance the model development and scientific researches in the future. [ABSTRACT FROM AUTHOR]

The International Polar Year 2007-2008 was a synchronized effort to simultaneously collect data from polar regions. Being the fourth in a row of IPYs, the demand for interdisciplinarity and new data products was high. However, despite of all the research done on land, people, ocean, ice and atmosphere and the large amount of data collected, no central archive or portal was created for IPY data. In order to address these issues, a concerted effort between PANGAEA - Data Publisher for Earth and Environmental Science, the ICSU World Data System (WDS), and the International Council for Scientific and Technical Information (ICSTI) was undertaken to extract data resulting from IPY publications for long-term preservation. 1380 IPY-related references were collected. Out of these, only 450 contained accessible data. All data was extracted, quality checked, annotated with metadata and uploaded to PANGAEA. The 450 articles dealt with a multitude of IPY topics - plankton biomass, water chemistry, ice thickness, whale sightings, Inuit health, alien species introductions by travelers or tundra biomass change - to mention just a few. Both, the Arctic and the Antarctic were investigated in the articles, and all realms (land, people, ocean, ice and atmosphere) and a wide range of countries were covered. The data compilation can now be found with the identifier doi:10.1594/PANGAEA.150150 and individually searched for using the PANGAEA search engine (www.pangaea.de) and adding "+project:ipy". With this effort, we hope to improve the visibility, accessibility and long-term storage of IPY data for future research and new data products. [ABSTRACT FROM AUTHOR]

Modeling fire as an integral part of an Earth system model (ESM) is vital for quantifying and understanding fire-climate-vegetation interactions on a global scale and from an Earth system perspective. In this study, we introduce to the Community Earth System Model (CESM) the new global fire parameterization proposed by Li et al. (2012), now with a more realistic representation of the anthropogenic impacts on fires, with a parameterization of peat fires, and with other minor modifications. The improved representation of the anthropogenic dimension includes the first attempt to parameterize agricultural fires, the economic influence on fire occurrence, and the socioeconomic influence on fire spread in a global fire model; also an alternative scheme for deforestation fires. The global fire parameterization has been tested in CESM1's land component model CLM4 in a 1850-2004 transient simulation, and evaluated against the satellite-based Global Fire Emission Database version 3 (GFED3) for 1997-2004. The simulated 1997-2004 average global totals for the burned area and fire carbon emissions in the new fire scheme are 338Mha yr -1 and 2.1 PgCyr -1. Its simulations on multi-year average burned area, fire seasonality, fire interannual variability, and fire carbon emissions are reasonable, and show better agreement with GFED3 than the current fire scheme in CESM1 and modified CTEM-FIRE. Moreover, the new fire scheme also estimates the contributions of global fire carbon emissions from different sources. During 1997-2004, the contributions are 8% from agricultural biomass burning, 27% from tropical deforestation and degradation fires, 5% from global peat fires (3.7% from tropical peat fires), and 60% from other fires, which are close to previous assessments based on satellite data, government statistics, or other information sources. In addition, we investigate the importance of direct anthropogenic influence (anthropogenic ignitions and fire suppression) on global fire regimes during 1850-2004, using CESM1 with the new fire scheme. Results show that the direct anthropogenic impact is the main factor driving the trends of global burned area in the whole period and fire carbon emissions only before ~1870. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to achieve a better understanding of the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely-sensed vegetation activity to provide a firm set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits) specifically considers the robustness of information given the uncertainties in both data and evaluation analysis. In addition, we provide a baseline benchmark, a minimum test that the model under consideration has to pass, to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI-Earth system model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite based vegetation activity data allows to pinpoint specific model failures that would not be possible by the sole use of atmospheric CO2 observations. [ABSTRACT FROM AUTHOR]

Since the Last Glacial Maximum, boreal wetlands have accumulated substantial amounts of peat, estimated at 180-621 Pg of carbon. Wetlands have significantly affected the atmospheric greenhouse gas composition in the past and will play a significant role in future changes of atmospheric CO2 and CH4 concentrations. In order to investigate those changes with an Earth System Model, biogeochemical processes in boreal wetlands need to be accounted for. Thus, a model of peat accumulation and decay was developed and included in the land surface model JSBACH of the Max Planck Institute Earth System Model (MPI-ESM). Here, we present the evaluation of model results from 6000 yrBP to the preindustrial period. Over this period of time, in the model 240 Pg of peat carbon accumulated in the areas north of 40° N. Simulated peat accumulation rates agree well with those reported for boreal wetlands. The model simulates CH4 emissions of 49.3 Tg yr-1 for 6000 yr BP and 51.5 Tg yr-1 for preindustrial times. This is within the range of estimates in the literature, which range from 32 to 112 Tg yr-1 for boreal wetlands. The modeled methane emission for West Siberian Lowlands and Hudson Bay Lowlands agree well with observations. The rising trend of methane emissions over the last 6000 yr is in agreement with measurements of Antarctic and Greenland ice cores. [ABSTRACT FROM AUTHOR]

The article presents a study which focuses on the development of an algorithm for the representation of large spectral variations of albedo over vegetation surfaces based on Moderate Resolution Imaging Spectrometer (MODIS) observations. The traditional approaches for estimating the MODIS enhanced vegetation albedo (MEVA) are outlined. It also emphasizes the significance of MEVA in understanding climate processes and climate change.

We present here a high resolution surface water pH dataset obtained in the Northwest European shelf seas in summer 2011. This is the first time that pH has been measured at such a high spatial resolution (10 measurements h-1) in this region. The aim of our paper is to investigate the carbonate chemistry dynamics of the surface water using pH and ancillary data. The main processes controlling the pH distribution along the ship's transect, and their relative importance, were determined using a statistical approach. The study highlights the impact of biological activity, temperature and riverine inputs on the carbonate chemistry dynamics of the shelf seas surface water. For this summer cruise, the biological activity formed the main control of the pH distribution along the cruise transect. Variations in chlorophyll and nutrients explained 29% of the pH variance along the full transect and as much as 68% in the northern part of the transect. In contrast, the temperature distribution explained ca. 50% of the pH variation in the Skagerrak region. Riverine inputs were evidenced by high dissolved organic carbon (DOC) levels in the Strait of Moyle (northern Irish Sea) and the southern North Sea with consequent remineralisation processes and a reduction in pH. The DOC distribution described 15% of the pH variance along the full transect. This study highlights the high spatial variability of the surface water pH in shelf seawaters where a range of processes simultaneously impacts the carbonate chemistry. [ABSTRACT FROM AUTHOR]

Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a setup of the WRF model that minimizes systematic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable setup: the horizontal resolution, the PBL parameterization scheme and the way WRF is nested to the driving dataset. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model setups, but sharing the same driving dataset. The results show that the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis and spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model skill is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields. [ABSTRACT FROM AUTHOR]

Isostasy is one of the oldest and most widely applied concepts in the geosciences, but the geoscientific community lacks a coherent, easy-to-use tool to simulate flexure of a realistic (i.e. laterally heterogeneous) lithosphere under an arbitrary set of surface loads. Such a model is needed for studies of mountain-building, sedimentary basin formation, glaciation, sea-level change, and other tectonic, geodynamic, and surface processes. Here I present gFlex, an open-source model that can produce analytical and finite difference solutions for lithospheric flexure in one (profile) and two (map view) dimensions. To simulate the flexural isostatic response to an imposed load, it can be used by itself or within GRASS GIS for better integration with field data. gFlex is also a component with the Community Surface Dynamics Modeling System (CSDMS) and Landlab modeling frameworks for coupling with a wide range of Earth-surface-related models, and can be coupled to additional models within Python scripts. As an example of this in-script coupling, I simulate the effects of spatially variable lithospheric thick ness on a modeled Iceland ice cap. Finite difference solutions in gFlex can use any of five types of boundary conditions: 0-displacement, 0-slope (i.e. clamped); 0-slope, 0-shear; 0-moment, 0-shear (i.e. broken plate); mirror symmetry; and periodic. Typical calculations with gFlex require ≪1s to ~ 1 min on a personal laptop computer. These characteristics - multiple ways to run the model, multiple solution methods, multiple boundary conditions, and short compute time - make gFlex an effective tool for flexural isostatic modeling across the geosciences. [ABSTRACT FROM AUTHOR]

Observational gaps limit our understanding of particle flux attenuation through the upper mesopelagic because available measurements (sediment traps and radiochemical tracers) have limited temporal resolution, are labor-intensive, and require ship support. Here, we conceptually evaluate an autonomous, optical proxy-based method for high-resolution observations of particle flux. We present four continuous records of particle flux collected with autonomous, profiling floats in the western Sargasso Sea and the subtropical North Pacific, as well as one shorter record of depth-resolved particle flux near the Bermuda Atlantic Time series Study (BATS) and Oceanic Flux Program (OFP) sites. These observations illustrate strong variability in particle flux over very short (~1 day) timescales, but at longer timescales they reflect patterns of variability previously recorded during sediment trap time series. While particle flux attenuation at BATS/OFP agreed with the canonical power-law model when observations were averaged over a month, flux attenuation was highly variable on timescales of 1-3 days. Particle fluxes at different depths were decoupled from one another and from particle concentrations and chlorophyll fluorescence in the immediately-overlying surface water, consistent with horizontal advection of settling particles. We finally present an approach for calibrating this optical proxy in units of carbon flux, discuss in detail the related, inherent physical and optical assumptions, and look forward toward the requirements for the quantitative application of this method in highly time-resolved studies of particle export and flux attenuation. [ABSTRACT FROM AUTHOR]

The article discusses a study which presents results of a newly developed isotope scheme within the ECHAM5-JSBACH model, which has been developed by combining two separate components, the atmosphere model ECHAM5 and the land surface scheme "Jena Scheme for Biosphere-Atmosphere Interaction in Hamburg" (JSBACH). It is noted that ECHAM5 is an Atmosphere General Circulation Model (AGCM)and JSBACH model calculates terrestrial boundary conditions for ECHAM5 over the land surface.

Global geopotential models (GGMs) are widely used in earth sciences, especially in geodesy and geophysics. In this paper, we aim at studying GGMs' capability in the geoidal height estimation at the geographical region of Iran. This will include verification of both satellite-only and combined GGMs. To compute the geoidal height at a point, keeping the longitude and latitude constant, we change its ellipsoidal height until the GGM-derived gravity potential at the resulting height equals the geoid's potential value. In this process, we consider the topographic bias effect once the computation of the potential is inside the topographic masses. As the benchmark for the performance analysis of GGMs, we use the known geoidal heights of 841GPS/Levelling stations with a country-wide distribution. The results indicate that the XGM2019e_2159 (n_max=2190) GGM is the best combined and the GO_CONS_GCF_2_DIR_R5 (n_max=330) GGM is the best satellite-only model for the computation of geoidal heights in the study area, Iran. [ABSTRACT FROM AUTHOR]

We present the new 3.5 version of the Louvain-la-Neuve sea ice model (LIM) integrated in NEMO 3.6. The main novelty is the improvement of model robustness and versatility for a wide range of applications, from global to regional scales. Several modifications to the code were required. First, the time stepping scheme of the model was changed from parallel to sequential (ice dynamics first, then thermodynamics). Such a scheme enables to diagnose the different physical processes responsible for exchanges through the air–ice–ocean interfaces, as well as the online inspection of mass, heat and salt conservation properties of the code. In the course of these developments, several minor conservation leaks were found and fixed, so that LIM3.5 is exactly conservative. Second, lateral boundary conditions for regional ice-covered configurations have been implemented. To illustrate the new capabilities, two simulations are performed. One is a global simulation at a nominal 2° resolution forced by atmospheric climatologies and is found reasonably realistic although no specific tuning was done. The other is a regional simulation at 2 km resolution around the Svalbard Archipelago in the Arctic Ocean, with prescribed conditions at the four boundaries including tides. The simulation is able to resolve small-scale features and transient events such as the opening and closing of coastal polynyas. The ice mass budgets for both simulations are illustrated and mostly differ by the strength of ice formation in open water. LIM3.5 now forms a solid base for future scientific studies and model developments. [ABSTRACT FROM AUTHOR]

The stable carbon isotope composition of dissolved inorganic carbon (δ13CDIC) in seawater was measured in samples collected during two cruises in the Northeastern Atlantic and Nordic Seas from June to August 2012. One cruise was part of the UK Ocean Acidification research programme, and the other was a repeat hydrographic transect of the Extended Ellett Line. In combination with measurements made of various other variables on these and other cruises, these data can be used to constrain the anthropogenic component of DIC in the interior ocean, and also assist in determining the influence of biological carbon uptake on surface ocean carbonate chemistry. The measurements have been processed, quality-controlled and submitted to an in-preparation global compilation of seawater δ13CDIC data, and are available from the British Oceanographic Data Centre. The observed δ13CDIC values fall in a range from -0.58 to +2.37%0, relative to the Vienna Peedee Belemnite standard. From duplicate samples collected during both cruises, the precision for the 552 results is 0.07‰, which is similar to other published studies of this kind. Data doi:10.5285/09760a3a-c2b5-250b-e053-6c86abc037c0 (Northeastern Atlantic), doi:10.5285/09511dd0-51db-0e21-e053-6c86abc09b95 (Nordic Seas). [ABSTRACT FROM AUTHOR]

Ecosystem process models are important tools for determining the interactive effects of global change and disturbance on forest carbon dynamics. Here we evaluated and improved terrestrial carbon cycling simulated by the Community Land Model (CLM4), the land model portion of the Community Earth System Model (CESM1.0.4). Our analysis was conducted primarily in Oregon forests using FLUXNET and forest inventory data for the period 2001-2006. We go beyond prior modeling studies in the region by incorporating regional variation in physiological parameters from > 100 independent field sites in the region. We also compare spatial patterns of simulated forest carbon stocks and net primary production (NPP) at 15 km resolution using data collected from federal forest inventory plots (FIA) from > 3000 plots in the study region. Finally, we evaluate simulated gross primary production (GPP) with FLUXNET eddy-covariance tower data at wet and dry sites in the region. We improved model estimates by making modifications to CLM4 to allow physiological parameters (e.g. foliage carbon to nitrogen ratios and specific leaf area), mortality rate, biological nitrogen fixation, and wood allocation to vary spatially by plant functional type (PFT) within an ecoregion based on field plot data in the region. Prior to modifications, default parameters resulted in underestimation of stem biomass in all forested ecoregions except the Blue Mountains and annual NPP was both over and underestimated. After modifications, model estimates of mean NPP fell within the observed range of uncertainty in all ecoregions (two-sided p-value = 0.8) and the underestimation of stem biomass was reduced. This was an improvement from the default configuration by 50% for stem biomass and 30% for NPP. At the tower sites, modeled monthly GPP fell within the observed range of uncertainty at both sites for the majority of the year, however summer GPP was underestimated at the Metolius semi-arid pine site and spring GPP was overestimated at the Campbell River mesic Douglas-fir site, indicating GPP may be an area for further improvement. The low bias in summer maximum GPP at the semi-arid site could be due to seasonal response of Vcmax to temperature and precipitation while overestimated spring values at the mesic site could be due to response of Vcmax to temperature and daylength. [ABSTRACT FROM AUTHOR]

The timing and length of burning seasons in different parts of the world depend on climate, land cover characteristics, and human activities. In this study, global fire data from satellite-based instruments are used in conjunction with global gridded distributions of agricultural land cover types (defined as the sum of cropland and pasture area) to separate the seasonality of agricultural burning practices from that of non-agricultural fire. The results presented in this study show that agricultural and non-agricultural land experience broadly different fire seasonality patterns that are not always linked to climate conditions. We highlight these differences on a regional basis, examining variations in both agricultural land cover and associated cultural practices to help explain our results. While we discuss two land cover categories, the methods can be generalized to derive seasonality for any number of land uses or cover types. This will be useful as global fire models evolve to be fully interactive with land use and land cover change in the next generation of Earth system models. [ABSTRACT FROM AUTHOR]

The article discusses the Hadley Centre Global Environment Model version 2 (HadGEM2) family of climate configurations that comprises a range of specific model configurations. It offers a detailed descriptions and evaluations of HadGEM2 family members and its overall performance using a set of model metrics. It notes that HadGEM2 family of configurations includes atmosphere and ocean components with well-resolved stratosphere and earth-system.

A regional air-quality forecast system's model of surface ozone variability based on cloud coverage is evaluated using satellite-observed cloud fraction (CF) information and a surface air-quality monitoring system. We compared CF and daily maximum ozone from the National Oceanic and Atmospheric Administration's National Air Quality Forecast Capability (NOAA NAQFC) with CFs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the U.S. Environmental Protection Agency's AirNow surface ozone measurements during May to October 2014. We found that observed surface ozone shows a clear (negative) correlation with the MODIS CFs, showing around 1 ppb decrease for 10% MODIS CF change over the Contiguous United States, while the correlation of modeled surface ozone with the model CFs is much weaker, showing only -0.5 ppb per 10% NAQFC CF change. Further, daytime CF differences between MODIS and NAQFC are correlated with modeled surface-ozone biases between AirNow and NAQFC, showing -1.05 ppb per 10% CF change, implying that spatial- and temporal-misplacement of the modeled cloud field might have biased modeled surface ozone-level. Current NAQFC cloud fields seem to be too bright compared to MODIS cloud fields (mean NAQFC CF = 0.38 and mean MODIS CF = 0.55), contributing up to 35% of surface-ozone bias in the current NAQFC system. [ABSTRACT FROM AUTHOR]

In the geosciences, data are acquired, processed, analysed, modelled and interpreted in order to generate knowledge. Such a complex procedure is affected by uncertainties related to the objective (e.g. the data, technologies and techniques employed) as well as the subjective (knowledge, skills and biases of the geoscientist) aspects of the knowledge generation workflow. Unlike in other scientific disciplines, uncertainty and its impact on the validity of geoscientific outputs have often been overlooked or only discussed superficially. However, for geological outputs to provide meaningful insights, the uncertainties, errors and assumptions made throughout the data acquisition, processing, modelling and interpretation procedures need to be carefully considered. This special issue illustrates and brings attention to why and how uncertainty handling (i.e. analysis, mitigation and communication) is a critical aspect within the geosciences. In this introductory paper, we (1) outline the terminology and describe the relationships between a number of descriptors often used to characterise and classify uncertainty and error, (2) present the collection of research papers that together form the special issue, the idea for which stems from a 2018 European Geosciences Union's General Assembly session entitled "Understanding the unknowns: recognition, quantification, influence and minimisation of uncertainty in the geosciences", and (3) discuss the limitations of the "traditional" treatment of uncertainty in the geosciences. "The efforts of many researchers have already cast much darkness on the subject, and it is likely that, if they continue, we will soon know nothing about it at all." – Mark Twain [ABSTRACT FROM AUTHOR]

The article discusses the process of creating parameterisations for geophysical models. It states that an approach to parameterising models uses a developed computer program known as iGen that analysis the source code of high-resolution model. Moreover, the IGen is capable of producing parameterisations that run typical order of magnitude faster than high-resolution models and has the potential to become an important tool for model development.

Floods are the most frequent, costliest natural disasters having devastating consequences on people, infrastructure, and the ecosystem. During flood events near real-time satellite imagery has proven to be an efficient management tool for disaster management authorities. However one of the challenges is accurate classification and segmentation of flooded water. The generalization ability of binary segmentation using threshold split-based method, is limited due to the effects of backscatter, geographical area, and time of image collection. Recent advancements in deep learning algorithms for image segmentation has demonstrated excellent potential for improving flood detection. However, there have been limited studies in this domain due to the lack of large scale labeled flood event dataset. In this paper, we present two deep learning approaches, first using a UNet and second, using a Feature Pyramid Network (FPN), both based on a backbone of EfficientNet-B7, by leveraging publicly available Sentinel-1 dataset provided jointly by NASA Interagency Implementation and Advanced Concepts Team, and IEEE GRSS Earth Science Informatics Technical Committee. The dataset covers flood events from Nebraska, North Alabama, Bangladesh, Red River North, and Florence. The performances of both networks were evaluated with multiple training, testing, and validation. During testing, the UNet model achieved the meanIOU score of 75.06% and the FPN model achieved the meanIOU score of 75.76%. [ABSTRACT FROM AUTHOR]

High-resolution bathymetry provides critical information to marine geoscientists. Bathymetric big data help characterise the seafloor and its benthic habitats, understand sedimentary records, and support the development of offshore engineering infrastructures. From September 27th to October 20th, 2022, the new CNR Research Vessel GAIA BLU explored the seafloor of the Naples and Pozzuoli Gulfs, and the Amalfi coastal area (Tyrrhenian Sea, Italy) from 50 to more than 2000 m water depth, acquiring about 5000 km2 of multi beam echosounder data. This area is particularly vulnerable to abrupt changes driven by the dynamics of several volcanic complexes, active in the area, and by human-induced impacts reflecting the proximity to the highly populated and touristic coastal area of Naples and nearby famous islands. For these reasons, the seafloor of the area needs to be known and constantly monitored. The digital bathymetric data previously available are restricted to the shallow highly dynamic area of the Gulf of Naples and appear fragmented as they were acquired in successive years, with different goals thereby using a variety of devices, with markedly different spatial resolutions. In this paper, we present bathymetric maps of the Gulf of Naples and adjacent slope basins at unprecedented resolution using three state-of-the-art multi beam echosounders. These high-resolution data highlight the technological advances of geophysical surveys achieved over the last 20 years and contribute to assessing the most dynamic areas where changes in the seafloor over time can be quantified. The new digital multi-resolution bathymetric products are openly accessible via Marine Geosciences Data System MGDS (refer to section Data Availability, Table 8, for datasets and products DOIs), perfectly matching the FAIR (Findable, Accessible, Interoperable and Reusable) and Open Science Principles. [ABSTRACT FROM AUTHOR]

JAXA has developed and implemented earth observation (EO) dashboard jointly with ESA and NASA. The development of the JAXA dashboard, along with the "Earth-graphy" website and the newly developed "JAXA Earth API" service, demonstrate JAXA's commitment to providing climate change and earth science information to users worldwide. The EO dashboard serves as a platform to deliver valuable data and information related to climate change. The WMS/WMTS technology allows users to visualize and interact with geospatial information by providing web-based mapping services. This technology enhances the user experience by enabling the display of satellite imagery, overlays, and other geospatial data layers within the EO dashboard. To further facilitate the efficient use of satellite data, JAXA has developed the JAXA Earth API service. This service offers a user-friendly interface for accessing and utilizing JAXA's Earth observation satellite image data. By providing an easy-to-use format, JAXA aims to promote the effective utilization of satellite data and encourage its widespread use. Overall, the development and operation of the JAXA dashboard, with its integration of COG format data, WMS/WMTS technology, Python-based API. This paper introduces the status of development of JAXA Earth Observation dashboard with COG format data, WMS/WMTS technology, phyton based API and JAXA Earth Observation missions. [ABSTRACT FROM AUTHOR]

Estimating the impact of different sources of uncertainty along the modelling chain is an important skill graduates are expected to have. Broadly speaking, educators can cover uncertainty in hydrological modelling by differentiating uncertainty in data, model parameters and model structure. This provides students with insights on the impact of uncertainties on modelling results and thus on the usability of the acquired model simulations for decision making. A survey among teachers in the Earth and environmental sciences showed that model structural uncertainty is the least represented uncertainty group in teaching. This paper introduces a computational exercise that introduces students to the basics of model structure uncertainty through two ready-to-use modelling experiments. These experiments require either Matlab or Octave, and use the open-source Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) and the open-source Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) data set. The exercise is short and can easily be integrated into an existing hydrological curriculum, with only a limited time investment needed to introduce the topic of model structure uncertainty and run the exercise. Two trial applications at the Technische Universität Dresden (Germany) showed that the exercise can be completed in two afternoons or four 90 min sessions and that the provided setup effectively transfers the intended insights about model structure uncertainty. [ABSTRACT FROM AUTHOR]

Texture is a fundamental soil property for multiple applications in environmental and earth sciences. Knowing its spatial distribution allows a better understanding of the response of soil conditions to changes in the environment, such as land use. This paper describes the technical development of Colombia's first texture maps, obtained via a spatial ensemble of national and global digital soil mapping products. This work compiles a new database with 4203 soil profiles, which were harmonized at five standard depths (0–5, 5–15, 15–30, 30–60, and 60–100 cm) and standardized with additive log ratio (ALR) transformation. A compilation of 83 covariates was developed and harmonized at 1 km 2 of spatial resolution. Ensemble machine learning (EML) algorithms (MACHISPLIN and landmap) were trained to predict the distribution of soil particle size fractions (PSFs) (clay, sand, and silt), and a comparison with SoilGrids (SG) products was performed. Finally, a spatial ensemble function was created to identify the smallest prediction errors between EML and SG. Our results are the first effort to build a national texture map (clay, sand, and silt fractions) based on digital soil mapping in Colombia. The results of EML algorithms showed that their accuracies were very similar at each standard depth, and were more accurate than SG. The largest improvement with the spatial ensemble was found at the first layer (0–5 cm). EML predictions were frequently selected for each PSF and depth in the total area; however, SG predictions were better when increasing soil depth in some specific regions. The final error distribution in the study area showed that sand presented higher absolute error values than clay and silt fractions, specifically in eastern Colombia. The spatial distribution of soil texture in Colombia is a potential tool to provide information for water-related applications, ecosystem services, and agricultural and crop modeling. However, future efforts need to improve aspects such as treating abrupt changes in the texture between depths and unbalanced data. Our results and the compiled database (10.6073/pasta/3f91778c2f6ad46c3cc70b61f02532db, , 10.6073/pasta/d6c0bf5847aa40836b42dcc3e0ea874e,) provide new insights to solve some of the aforementioned issues. [ABSTRACT FROM AUTHOR]

The papers that are here presented and summarised represent the recent scientific contributions of some authors coming from different countries and working in the fields of monitoring, modelling, mapping and design of mitigation measures against mass movements. The authors had the opportunity to present their recent advancements, discuss each other needs and set forth future research requirements during the 2009 EGU General Assembly, so that their scientific contributions can be considered the result of the debates and exchanges that were set among scientists and researchers, either personally or during the review phase since that date. In this resume, the scientific papers of the special issue are divided according to different thematic areas and summarised. The most innovative scientific approaches proposed in the special issue, regarding the monitoring methodologies, simulation techniques and laboratory equipment are described and summarised. The obtained results are very promising to keep on future research at a very satisfactory level. [ABSTRACT FROM AUTHOR]

Discusses the changes made to the "Hydrology and Earth System Sciences" with the staff's adoption of a completely new way of scientific publishing. Opportunities being offered by the journal; Qualities as a fully Web-based journal; Impact of the transition.

Spatial thinking represents an ongoing challenge in geoscience education, but concrete manipulatives can bridge this gap by illustrating abstract concepts. In an undergraduate optical mineralogy lab session, TotBlocks were used to illustrate how crystal structures influence properties such as cleavage and pleochroism. More abstracted properties, e.g., extinction angles, were increasingly difficult to illustrate using this tool. [ABSTRACT FROM AUTHOR]

The increased interest in subsurface development (e.g., unconventional hydrocarbon, engineered geothermal systems (EGSs), waste disposal) and the associated (triggered or induced) seismicity calls for a better understanding of the hydro-seismo-mechanical coupling in fractured rock masses. Being able to bridge the knowledge gap between laboratory and reservoir scales, controllable meso-scale in situ experiments are deemed indispensable. In an effort to access and instrument rock masses of hectometer size, the Bedretto Underground Laboratory for Geosciences and Geoenergies ("BedrettoLab") was established in 2018 in the existing Bedretto Tunnel (Ticino, Switzerland), with an average overburden of 1000 m. In this paper, we introduce the BedrettoLab, its general setting and current status. Combined geological, geomechanical and geophysical methods were employed in a hectometer-scale rock mass explored by several boreholes to characterize the in situ conditions and internal structures of the rock volume. The rock volume features three distinct units, with the middle fault zone sandwiched by two relatively intact units. The middle fault zone unit appears to be a representative feature of the site, as similar structures repeat every several hundreds of meters along the tunnel. The lithological variations across the characterization boreholes manifest the complexity and heterogeneity of the rock volume and are accompanied by compartmentalized hydrostructures and significant stress rotations. With this complexity, the characterized rock volume is considered characteristic of the heterogeneity that is typically encountered in subsurface exploration and development. The BedrettoLab can adequately serve as a test-bed that allows for in-depth study of the hydro-seismo-mechanical response of fractured crystalline rock masses. [ABSTRACT FROM AUTHOR]

Coarse-resolution climate and weather forecast models cannot accurately parameterize small-scale, nonlinear processes without accounting for subgrid-scale variability. To do so, some models integrate over the subgrid variability analytically. Although analytic integration methods are attractive, they can be used only with physical parameterizations that have a sufficiently simple functional form. Instead, this paper introduces a method to integrate subgrid variability using a type of Monte Carlo integration. The method generates subcolumns with suitable vertical correlations and feeds them into a microphysics parameterization. The subcolumn methodology requires little change to the parameterization source code and can be used with a wide variety of physical parameterizations. Our subcolumn generator is multivariate, which is important for physical processes that involve two or more hydrometeor species, such as accretion of cloud droplets by rain drops. In order to reduce sampling noise in the integrations, our subcolumn generator employs two variance-reduction methods, namely importance and stratified (Latin hypercube) sampling. For this reason, we name the subcolumn generator the Subgrid Importance Latin Hypercube Sampler (SILHS). This paper tests SILHS in interactive, single-column simulations of a marine stratocumulus case and a shallow cumulus case. The paper then compares simulations that use SILHS with those that use analytic integration. Although the SILHS solutions exhibit considerable noise from time step to time step, the noise is greatly damped in most of the timeaveraged profiles. [ABSTRACT FROM AUTHOR]

The developments in the geospatially-enabled mobile communication technologies have opened new horizons in many fields of geosciences research, especially in those where data collection, processing and interpretation are time consuming and costly. Being one of these research fields, natural hazards also require high spatiotemporal data density and distribution, which is extremely difficult to obtain and also equally essential to secure the main assumptions of these researches and thus yield to proper conclusions. These problems can be solved with the help of citizen science (CitSci) methods and the volunteer geographical information (VGI). These two terms are complementary, or intertwined, and mutually benefit from each other for achieving their goals. This paper investigates the developments in CitSci and VGI with a specific focus of natural hazard researches and gives a brief overview of the literature. The importance of their use in natural hazards, open research areas and future aspects are also analysed. Based on the previous experiences and analyses, the authors foresee that such investigations would help researchers to utilize CitSci and VGI in their studies, and thus benefit the advantages of both approaches and improve the quality of their data. On the other hand, the growing interest of citizen scientists for supporting scientific processes could be steered to the fields where most help is needed. Specifically, detection of ground deformations after earthquakes is explained here and a simple mobile app developed for landslide data collection is briefly depicted as use case. [ABSTRACT FROM AUTHOR]

Presents a reply of A. Leinweber et al. to a comment on their study which focused on the role of nitrogen-fixation to simulate the pCO2 observations from the Baltic Sea. Uncertainty about compliance with the standards of the referee for the study; Views on the significance of elevated carbon-nitrogen ratios in OM; Assumption of lateral processes to be negligible as a first approximation.

Comments on a study conducted by W. Knorr et al. which focused on the available evidence for the temperature dependence of soil organic carbon. Importance of understanding the climate sensitivity of soil respiration; Observations on the construction of statements in the study; Views on the examination of the stability of soil pool at varying temperatures.

Ensemble geophysical datasets are foundational for research to understand the Earth System in an uncertainty-aware context, and to drive applications that require quantification of uncertainties, such as probabilistic hydro-meteorological estimation or prediction. Yet ensemble estimation is more challenging than single-value spatial interpolation, and open-access routines and tools are limited in this area, hindering the generation and application of ensemble geophysical datasets. A notable exception in the last decade has been the Gridded Meteorological Ensemble Tool (GMET), which is implemented in FORTRAN and has typically been configured for ensemble estimation of precipitation, mean air temperature, and daily temperature range, based on station observations. GMET has been used to generate a variety of local, regional, national and global meteorological datasets, which in turn have driven multiple retrospective and real-time hydrological applications. Motivated by an interest in expanding GMET flexibility, application scope and range of methods, we have developed a Python based Geospatial Probabilistic Estimation Package (GPEP) that offers GMET functionality along with additional methodological and usability improvements, including variable independence and flexibility, an efficient alternative cross validation strategy, internal parallelization, and the availability of the scikit-learn machine learning library for both local and global regression. This paper describes GPEP and illustrates some of its capabilities using several demonstration experiments, including the estimation of precipitation, temperature, and snow water equivalent ensemble analyses on various scales. [ABSTRACT FROM AUTHOR]

For the last 4 years, the School of Civil Engineering & Geosciences at Newcastle University, UK adapted mobile devices as learning approach only for undergraduate within Geomatics. All incoming students were given a mobile device as learning tool, which was supposed to be there main way to accessing teaching material. This paper will present how students adopted the mobile devices and how their learning has changed using mobile devices. It will highlight which apps can be used in a Geomatics teaching environment to engage students in their learning and teaching environment. The paper will furthermore look into apps which help students within the area of Photogrammetry and Remote Sensing, such as the Autodesk 123D catch up or the Remote RDP app to remotely control surveying instrumentations, such as laser scanners. Those apps are easy tools to engage students within digital learning environment which the students are familiar with. The paper will show how students embrace the technology but also current limitation of using those within Higher education establishments, such as sufficient Wifi and student support for using mobile devices. [ABSTRACT FROM AUTHOR]

Lidars are uniquely capable of collecting high-precision and high spatiotemporal resolution observations that have been used for atmospheric process studies from the ground, aircraft, and space for many years. The Aeolus mission, the first space-borne Doppler wind lidar, was developed by the European Space Agency (ESA) and launched in August 2018. Its novel Atmospheric LAser Doppler INstrument (ALADIN) observes profiles of the component of the wind vector and aerosol/cloud optical properties along the instrument's line-of-sight (LOS) direction on a global scale. A total of two airborne lidar systems have been developed at NASA Langley Research Center in recent years that collect measurements in support of several NASA Earth Science Division focus areas. The coherent Doppler Aerosol WiNd (DAWN) lidar measures vertical profiles of LOS velocity along selected azimuth angles that are combined to derive profiles of horizontal wind speed and direction. The High Altitude Lidar Observatory (HALO) measures high resolution profiles of atmospheric water vapor (WV) and aerosol and cloud optical properties. Because there are limitations in terms of spatial and vertical detail and measurement precision that can be accomplished from space, airborne remote sensing observations like those from DAWN and HALO are required to fill these observational gaps and to calibrate and validate space-borne measurements. Over a 2-week period in April 2019, during their Aeolus Cal/Val Test Flight campaign, NASA conducted five research flights over the eastern Pacific Ocean with the DC-8 aircraft. The purpose was to demonstrate the following: (1) DAWN and HALO measurement capabilities across a range of atmospheric conditions, (2) Aeolus Cal/Val flight strategies and comparisons of DAWN and HALO measurements with Aeolus, to gain an initial perspective of Aeolus performance, and (3) ways in which atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, WV, and aerosol profile observations, coupled with numerical model and other remote sensing observations. This paper provides a brief description of the DAWN and HALO instruments, discusses the synergistic observations collected across a wide range of atmospheric conditions sampled during the DC-8 flights, and gives a brief summary of the validation of DAWN, HALO, and Aeolus observations and comparisons. [ABSTRACT FROM AUTHOR]

This paper assesses the changing norms of water use known as the duty of water. It is a case study in historical socio-hydrology, or more precisely the history of socio-hydrologic ideas, a line of research that is useful for interpreting and anticipating changing social values with respect to water. The duty of water is currently defined as the amount of water reasonably required to irrigate a substantial crop with careful management and without waste on a given tract of land. The historical section of the paper traces this concept back to late 18th century analysis of steam engine efficiencies for mine dewatering in Britain. A half-century later, British irrigation engineers fundamentally altered the concept of duty to plan large-scale canal irrigation systems in northern India at an average duty of 218 acres per cubic foot per second (cfs). They justified this extensive irrigation standard (i.e., low water application rate over large areas) with a suite of social values that linked famine prevention with revenue generation and territorial control. The duty of water concept in this context articulated a form of political power, as did related irrigation engineering concepts such as "command" and "regime." Several decades later irrigation engineers in the western US adapted the duty of water concept to a different socio-hydrologic system and norms, using it to establish minimum standards for private water rights appropriation (e.g., only 40 to 80 acres per cfs). While both concepts of duty addressed socio-economic values associated with irrigation, the western US linked duty with justifications for, and limits of, water ownership. The final sections show that while the duty of water concept has been eclipsed in practice by other measures, standards, and values of water use efficiency, it has continuing relevance for examining ethical duties and for anticipating, if not predicting, emerging social values with respect to water. [ABSTRACT FROM AUTHOR]