• A hydrologist's guide to open science

      Hall, C.A.; Saia, S.M.; Popp, A.L.; Dogulu, N.; Schymanski, S.J.; Drost, N.; Van Emmerik, T.; Hut, R.; The Honors College and Biosystems Engineering Department, University of Arizona (Copernicus GmbH, 2022)
      Open, accessible, reusable, and reproducible hydrologic research can have a significant positive impact on the scientific community and broader society. While more individuals and organizations within the hydrology community are embracing open science practices, technical (e.g., limited coding experience), resource (e.g., open access fees), and social (e.g., fear of weaknesses being exposed or ideas being scooped) challenges remain. Furthermore, there are a growing number of constantly evolving open science tools, resources, and initiatives that can be overwhelming. These challenges and the ever-evolving nature of the open science landscape may seem insurmountable for hydrologists interested in pursuing open science. Therefore, we propose the general "Open Hydrology Principles"to guide individual and community progress toward open science for research and education and the "Open Hydrology Practical Guide"to improve the accessibility of currently available tools and approaches. We aim to inform and empower hydrologists as they transition to open, accessible, reusable, and reproducible research. We discuss the benefits as well as common open science challenges and how hydrologists can overcome them. The Open Hydrology Principles and Open Hydrology Practical Guide reflect our knowledge of the current state of open hydrology; we recognize that recommendations and suggestions will evolve and expand with emerging open science infrastructures, workflows, and research experiences. Therefore, we encourage hydrologists all over the globe to join in and help advance open science by contributing to the living version of this document and by sharing open hydrology resources in the community-supported repository (https://open-hydrology.github.io, last access: 1 February 2022). © Copyright:
    • A mechanistic analysis of tropical Pacific dynamic sea level in GFDL-OM4 under OMIP-I and OMIP-II forcings

      Hsu, C.-W.; Yin, J.; Griffies, S.M.; Dussin, R.; University of Arizona, Department of Geoscience (Copernicus GmbH, 2021)
      The sea level over the tropical Pacific is a key indicator reflecting vertically integrated heat distribution over the ocean. Here, we use the Geophysical Fluid Dynamics Laboratory global ocean-sea ice model (GFDL-OM4) forced by both the Coordinated Ocean-Ice Reference Experiment (CORE) and Japanese 55-year Reanalysis (JRA-55)-based surface dataset for driving ocean-sea ice models (JRA55-do) atmospheric states (Ocean Model Intercomparison Project (OMIP) versions I and II) to evaluate the model performance and biases compared against available observations. We find persisting mean state dynamic sea level (DSL) bias along 9° N even with updated wind forcing in JRA55-do relative to CORE. The mean state bias is related to biases in wind stress forcing and geostrophic currents in the 4 to 9° N latitudinal band. The simulation forced by JRA55-do significantly reduces the bias in DSL trend over the northern tropical Pacific relative to CORE. In the CORE forcing, the anomalous westerly wind trend in the eastern tropical Pacific causes an underestimated DSL trend across the entire Pacific basin along 10° N. The simulation forced by JRA55-do significantly reduces the bias in DSL trend over the northern tropical Pacific relative to CORE. We also identify a bias in the easterly wind trend along 20° N in both JRA55-do and CORE, thus motivating future improvement. In JRA55-do, an accurate Rossby wave initiated in the eastern tropical Pacific at seasonal timescale corrects a biased seasonal variability of the northern equatorial countercurrent in the CORE simulation. Both CORE and JRA55-do generate realistic DSL variation during El Niño. We find an asymmetry in the DSL pattern on two sides of the Equator is strongly related to wind stress curl that follows the sea level pressure evolution during El Niño. © 2021 The Author(s).
    • Assessing local impacts of the 1700 CE Cascadia earthquake and tsunami using tree-ring growth histories: a case study in South Beach, Oregon, USA

      Dziak, R.P.; Black, B.A.; Wei, Y.; Merle, S.G.; Laboratory of Tree-Ring Research, University of Arizona (Copernicus GmbH, 2021)
      We present an investigation of the disturbance history of an old-growth Douglas-fir (Pseudotsuga menziesii) stand in South Beach, Oregon, for possible growth changes due to tsunami inundation caused by the 1700 CE Cascadia Subduction Zone (CSZ) earthquake. A high-resolution model of the 1700 tsunami run-up heights at South Beach, assuming an "L"-sized earthquake, is also presented to better estimate the inundation levels several kilometers inland at the old-growth site. This tsunami model indicates the South Beach fir stand would have been subjected to local inundation depths from 0 to 10 m. Growth chronologies collected from the Douglas-fir stand shows that trees experienced a significant growth reductions in the year 1700 relative to nearby Douglas-fir stands, consistent with the tsunami inundation estimates. The ±1-3-year timing of the South Beach disturbances are also consistent with disturbances previously observed at a Washington state coastal forest g1/4220 km to the north. Moreover, the 1700 South Beach growth reductions were not the largest over the >321-year tree chronology at this location, with other disturbances likely caused by climate drivers (e.g., drought or windstorms). Our study represents a first step in using tree growth history to ground truth tsunami inundation models by providing site-specific physical evidence. © 2021 Robert P. Dziak et al.
    • Assessment of the ParFlow-CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

      O'neill, M.M.F.; Tijerina, D.T.; Condon, L.E.; Maxwell, R.M.; Department of Hydrology and Atmospheric Sciences, University of Arizona (Copernicus GmbH, 2021)
      Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology-land surface model ParFlow-CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance. © 2021 Mary M. F. O'Neill et al.
    • Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

      Ma, P.-L.; Harrop, B.E.; Larson, V.E.; Neale, R.B.; Gettelman, A.; Morrison, H.; Wang, H.; Zhang, K.; Klein, S.A.; Zelinka, M.D.; et al. (Copernicus GmbH, 2022)
      Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future. © 2022 Po-Lun Ma et al.
    • Birth and closure of the Kallipetra Basin: Late Cretaceous reworking of the Jurassic Pelagonian-Axios/Vardar contact (northern Greece)

      Bailey, L.R.; Schenker, F.L.; Giuditta, Fellin, M.; Cobianchi, M.; Adatte, T.; Picotti, V.; Department of Geosciences, University of Arizona (Copernicus GmbH, 2020)
      Some 20 Myr after the Late Jurassic to Early Cretaceous obduction and collision at the eastern margin of Adria, the eroded Pelagonia (Adria) Axios/Vardar (oceanic complex) contact collapsed, forming the Kallipetra Basin, described around the Aliakmon River near Veroia (northern Greece). Clastic and carbonate marine sediments deposited from the early Cenomanian to the end of the Turonian, with abundant olistoliths and slope failures at the base due to active normal faults. The middle part of the series is characterized by red and green pelagic limestones, with a minimal contribution of terrigenous debris. Rudist mounds in the upper part of the basin started forming on the southwestern slope, and their growth competed with a flux of ophiolitic debris, documenting the new fault scarps affecting the Vardar oceanic complex (VOC). Eventually, the basin was closed by overthrusting of the VOC towards the northeast and was buried and heated up to ~ 180 °C. A strong reverse geothermal gradient with temperatures increasing up-section to near 300 °C is recorded beneath the VOC by illite crystallinity and by the crystallization of chlorite during deformation. This syntectonic heat partially reset the zircon fission track ages bracketing the timing of closure just after the deposition of the ophiolitic debris in the Turonian. This study documents the reworking of the Pelagonian Axios/Vardar contact, with Cenomanian extension and basin widening followed by Turonian compression and basin inversion. Thrusting occurred earlier than previously reported in the literature for the eastern Adria and shows a vergence toward the northeast, at odds with the regional southwest vergence of the whole margin but in accordance to some reports about 50 km north. © 2020 Author(s).
    • CABra: A novel large-sample dataset for Brazilian catchments

      Almagro, A.; Oliveira, P.T.S.; Meira Neto, A.A.; Roy, T.; Troch, P.; Department of Hydrology and Atmospheric Sciences, University of Arizona (Copernicus GmbH, 2021)
      In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980-2010) of data and less than 10% of missing records were included. Catchment areas range from 9 to 4 800 000 km2, and the mean daily streamflow varies from 0.02 to 9mmd-1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed, along with the limitations for each of our multiple data sources. CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continentalscale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/(last access: 7 June 2021). © 2021 André Almagro et al.
    • Calculating canopy stomatal conductance from eddy covariance measurements, in light of the energy budget closure problem

      Wehr, R.; Saleska, S.R.; Ecology and Evolutionary Biology, University of Arizona (Copernicus GmbH, 2021)
      Canopy stomatal conductance is commonly estimated from eddy covariance measurements of the latent heat flux (LE) by inverting the Penman-Monteith equation. That method ignores eddy covariance measurements of the sensible heat flux (H) and instead calculates H implicitly as the residual of all other terms in the site energy budget. Here we show that canopy stomatal conductance is more accurately calculated from eddy covariance (EC) measurements of both H and LE using the flux-gradient equations that define conductance and underlie the Penman-Monteith equation, especially when the site energy budget fails to close due to pervasive biases in the eddy fluxes and/or the available energy. The flux-gradient formulation dispenses with unnecessary assumptions, is conceptually simpler, and is as or more accurate in all plausible scenarios. The inverted Penman-Monteith equation, on the other hand, contributes substantial biases and erroneous spatial and temporal patterns to canopy stomatal conductance, skewing its relationships with drivers such as light and vapor pressure deficit. © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.
    • Carbonyl sulfide: Comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach

      Maignan, F.; Abadie, C.; Remaud, M.; Kooijmans, L.M.J.; Kohonen, K.M.; Commane, R.; Wehr, R.; Elliott Campbell, J.; Belviso, S.; Montzka, S.A.; et al. (Copernicus GmbH, 2021)
      Land surface modellers need measurable proxies to constrain the quantity of carbon dioxide (CO2) assimilated by continental plants through photosynthesis, known as gross primary production (GPP). Carbonyl sulfide (COS), which is taken up by leaves through their stomates and then hydrolysed by photosynthetic enzymes, is a candidate GPP proxy. A former study with the ORCHIDEE land surface model used a fixed ratio of COS uptake to CO2 uptake normalised to respective ambient concentrations for each vegetation type (leaf relative uptake, LRU) to compute vegetation COS fluxes from GPP. The LRU approach is known to have limited accuracy since the LRU ratio changes with variables such as photosynthetically active radiation (PAR): while CO2 uptake slows under low light, COS uptake is not light limited. However, the LRU approach has been popular for COS GPP proxy studies because of its ease of application and apparent low contribution to uncertainty for regional-scale applications. In this study we refined the COS GPP relationship and implemented in ORCHIDEE a mechanistic model that describes COS uptake by continental vegetation. We compared the simulated COS fluxes against measured hourly COS fluxes at two sites and studied the model behaviour and links with environmental drivers. We performed simulations at a global scale, and we estimated the global COS uptake by vegetation to be 756 Gg S yr1, in the middle range of former studies (490 to 1335 Gg S yr1). Based on monthly mean fluxes simulated by the mechanistic approach in ORCHIDEE, we derived new LRU values for the different vegetation types, ranging between 0.92 and 1.72, close to recently published averages for observed values of 1.21 for C4 and 1.68 for C3 plants. We transported the COS using the monthly vegetation COS fluxes derived from both the mechanistic and the LRU approaches, and we evaluated the simulated COS concentrations at NOAA sites. Although the mechanistic approach was more appropriate when comparing to high-Temporal-resolution COS flux measurements, both approaches gave similar results when transporting with monthly COS fluxes and evaluating COS concentrations at stations. In our study, uncertainties between these two approaches are of secondary importance compared to the uncertainties in the COS global budget, which are currently a limiting factor to the potential of COS concentrations to constrain GPP simulated by land surface models on the global scale. © 2021 Copernicus GmbH. All rights reserved.
    • Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

      Tebaldi, C.; Debeire, K.; Eyring, V.; Fischer, E.; Fyfe, J.; Friedlingstein, P.; Knutti, R.; Lowe, J.; O'Neill, B.; Sanderson, B.; et al. (Copernicus GmbH, 2021)
      The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: Mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081-2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5-C) reached at the upper end of the 5 %-95% envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5-C of warming compared to the 1850-1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2-C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5-C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s. © 2021 Copernicus GmbH. All rights reserved.
    • Cloud drop number concentrations over the western north atlantic ocean: Seasonal cycle, aerosol interrelationships, and other influential factors

      Dadashazar, H.; Painemal, D.; Alipanah, M.; Brunke, M.; Chellappan, S.; Corral, A.F.; Crosbie, E.; Kirschler, S.; Liu, H.; Moore, R.H.; et al. (Copernicus GmbH, 2021)
      Cloud drop number concentrations (Nd) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing Nd on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-Nd days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-Nd days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing Nd to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to Nd for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-Nd relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of Nd. © Copyright:
    • Cloud phase and macrophysical properties over the Southern Ocean during the MARCUS field campaign

      Xi, B.; Dong, X.; Zheng, X.; Wu, P.; Department of Hydrology and Atmospheric Sciences, University of Arizona (Copernicus GmbH, 2022)
      To investigate the cloud phase and macrophysical properties over the Southern Ocean (SO), the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF2) was installed on the Australian icebreaker research vessel (R/V) Aurora Australis during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign (41 to 69°S, 60 to 160°E) from October 2017 to March 2018. To examine cloud properties over the midlatitude and polar regions, the study domain is separated into the northern (NSO) and southern (SSO) parts of the SO, with a demarcation line of 60°S. The total cloud fractions (CFs) were 77.9%, 67.6%, and 90.3% for the entire domain, NSO and SSO, respectively, indicating that higher CFs were observed in the polar region. Low-level clouds and deep convective clouds are the two most common cloud types over the SO. A new method was developed to classify liquid, mixed-phase, and ice clouds in single-layered, low-level clouds (LOW), where mixed-phase clouds dominate with an occurrence frequency (Freq) of 54.5%, while the Freqs of the liquid and ice clouds were 10.1% (most drizzling) and 17.4% (least drizzling). The meridional distributions of low-level cloud boundaries are nearly independent of latitude, whereas the cloud temperatures increased by ∼1/48K, and atmospheric precipitable water vapor increased from ∼1/45mm at 69°S to ∼1/418mm at 43°S. The mean cloud liquid water paths over NSO were much larger than those over SSO. Most liquid clouds occurred over NSO, with very few over SSO, whereas more mixed-phase clouds occurred over SSO than over NSO. There were no significant differences for the ice cloud Freq between NSO and SSO. The ice particle sizes are comparable to cloud droplets and drizzle drops and well mixed in the cloud layer. These results will be valuable for advancing our understanding of the meridional and vertical distributions of clouds and can be used to improve model simulations over the SO. © 2022 Baike Xi et al.
    • CondiDiag1.0: A flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

      Wan, H.; Zhang, K.; Rasch, P.J.; Larson, V.E.; Zeng, X.; Zhang, S.; Dixon, R.; Department of Hydrology and Atmospheric Sciences, The University of Arizona (Copernicus GmbH, 2022)
      Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods. © Copyright:
    • Controls on the hydraulic geometry of alluvial channels: Bank stability to gravitational failure, the critical-flow hypothesis, and conservation of mass and energy

      Pelletier, J.D.; Department of Geosciences, The University of Arizona (Copernicus GmbH, 2021)
      <p>The bank-full depths, widths, depth-averaged water velocities, and along-channel slopes of alluvial channels are approximately power-law functions of bank-full discharge across many orders of magnitude. What mechanisms give rise to these patterns is one of the central questions of fluvial geomorphology. Here it is proposed that the bank-full depths of alluvial channels are partially controlled by the maximum heights of gravitationally stable channel banks, which depend on bank material cohesion and hence on clay content. The bank-full depths predicted by a bank-stability model correlate with observed bank-full depths estimated from the bends in the stage-discharge rating curves of 387 U.S. Geological Survey gaging stations in the Mississippi River basin. It is further proposed that depth-averaged water velocities scale with bank-full depths as a result of a self-regulatory feedback among water flow, relative roughness, and channel-bed morphology that limits depth-averaged water velocities to within a relatively narrow range associated with Froude numbers that have a weak inverse relationship to bank-full discharge. Given these constraints on channel depths and water velocities, bank-full widths and along-channel slopes consistent with observations follow by conservation of mass and energy of water flow.</p>. © 2021 Copernicus GmbH. All rights reserved.
    • Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations

      Xia, C.-A.; Luo, X.; Hu, B.X.; Riva, M.; Guadagnini, A.; Department of Hydrology and Atmospheric Sciences, University of Arizona (Copernicus GmbH, 2021)
      We employ an approach based on the ensem ble Kalman filter coupled with stochastic moment equa tions (MEs-EnKF) of groundwater flow to explore the de pendence of conductivity estimates on the type of available information about hydraulic heads in a three-dimensional randomly heterogeneous field where convergent flow driven by a pumping well takes place. To this end, we consider three types of observation devices corresponding to (i) multi node monitoring wells equipped with packers (Type A) and (ii) partially (Type B) and (iii) fully (Type C) screened wells. We ground our analysis on a variety of synthetic test cases associated with various configurations of these observation wells. Moment equations are approximated at second order (in terms of the standard deviation of the natural logarithm, Y , of conductivity) and are solved by an efficient transient numerical scheme proposed in this study. The use of an infla tion factor imposed to the observation error covariance ma trix is also analyzed to assess the extent at which this can strengthen the ability of the MEs-EnKF to yield appropri ate conductivity estimates in the presence of a simplified modeling strategy where flux exchanges between monitor ing wells and aquifer are neglected. Our results show that (i) the configuration associated with Type A monitoring wells leads to conductivity estimates with the (overall) best qual ity, (ii) conductivity estimates anchored on information from Type B and C wells are of similar quality, (iii) inflation of the measurement-error covariance matrix can improve conduc tivity estimates when a simplified flow model is adopted, and (iv) when compared with the standard Monte Carlo-based EnKF method, the MEs-EnKF can efficiently and accurately estimate conductivity and head fields. © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.
    • Deep learning rainfall-runoff predictions of extreme events

      Frame, J.M.; Kratzert, F.; Klotz, D.; Gauch, M.; Shelev, G.; Gilon, O.; Qualls, L.M.; Gupta, H.V.; Nearing, G.S.; Department of Hydrology and Water Resources, The University of Arizona (Copernicus GmbH, 2022)
      The most accurate rainfall-runoff predictions are currently based on deep learning. There is a concern among hydrologists that the predictive accuracy of data-driven models based on deep learning may not be reliable in extrapolation or for predicting extreme events. This study tests that hypothesis using long short-term memory (LSTM) networks and an LSTM variant that is architecturally constrained to conserve mass. The LSTM network (and the mass-conserving LSTM variant) remained relatively accurate in predicting extreme (high-return-period) events compared with both a conceptual model (the Sacramento Model) and a process-based model (the US National Water Model), even when extreme events were not included in the training period. Adding mass balance constraints to the data-driven model (LSTM) reduced model skill during extreme events. Copyright: © 2022 Jonathan M. Frame et al.
    • DeepMIP: Model intercomparison of early Eocene climatic optimum (EECO) large-scale climate features and comparison with proxy data

      Lunt, D.J.; Bragg, F.; Chan, W.-L.; Hutchinson, D.K.; Ladant, J.-B.; Morozova, P.; Niezgodzki, I.; Steinig, S.; Zhang, Z.; Zhu, J.; et al. (Copernicus GmbH, 2021)
      We present results from an ensemble of eight climate models, each of which has carried out simulations of the early Eocene climate optimum (EECO, g1/4 50 million years ago). These simulations have been carried out in the framework of the Deep-Time Model Intercomparison Project (DeepMIP; <span classCombining double low line"uri">http://www.deepmip.org, last access: 10 January 2021); thus, all models have been configured with the same paleogeographic and vegetation boundary conditions. The results indicate that these non-CO2 boundary conditions contribute between 3 and 5 g C to Eocene warmth. Compared with results from previous studies, the DeepMIP simulations generally show a reduced spread of the global mean surface temperature response across the ensemble for a given atmospheric CO2 concentration as well as an increased climate sensitivity on average. An energy balance analysis of the model ensemble indicates that global mean warming in the Eocene compared with the preindustrial period mostly arises from decreases in emissivity due to the elevated CO2 concentration (and associated water vapour and long-wave cloud feedbacks), whereas the reduction in the Eocene in terms of the meridional temperature gradient is primarily due to emissivity and albedo changes owing to the non-CO2 boundary conditions (i.e. the removal of the Antarctic ice sheet and changes in vegetation). Three of the models (the Community Earth System Model, CESM; the Geophysical Fluid Dynamics Laboratory, GFDL, model; and the Norwegian Earth System Model, NorESM) show results that are consistent with the proxies in terms of the global mean temperature, meridional SST gradient, and CO2, without prescribing changes to model parameters. In addition, many of the models agree well with the first-order spatial patterns in the SST proxies. However, at a more regional scale, the models lack skill. In particular, the modelled anomalies are substantially lower than those indicated by the proxies in the southwest Pacific; here, modelled continental surface air temperature anomalies are more consistent with surface air temperature proxies, implying a possible inconsistency between marine and terrestrial temperatures in either the proxies or models in this region. Our aim is that the documentation of the large-scale features and model-data comparison presented herein will pave the way to further studies that explore aspects of the model simulations in more detail, for example the ocean circulation, hydrological cycle, and modes of variability, and encourage sensitivity studies to aspects such as paleogeography, orbital configuration, and aerosols. © 2021 Copernicus GmbH. All rights reserved.
    • Detection and quantification of CH4 plumes using the WFM-DOAS retrieval on AVIRIS-NG hyperspectral data

      Borchardt, Jakob; Gerilowski, Konstantin; Krautwurst, Sven; Bovensmann, Heinrich; Thorpe, Andrew K.; Thompson, David R.; Frankenberg, Christian; Miller, Charles E.; Duren, Riley M.; Burrows, John Philip; et al. (Copernicus GmbH, 2021-02-18)
      Methane is the second most important anthropogenic greenhouse gas in the Earth's atmosphere. To effectively reduce these emissions, a good knowledge of source locations and strengths is required. Airborne remote sensing instruments such as the Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) with meter-scale imaging capabilities are able to yield information about the locations and magnitudes of methane sources. In this study, we successfully applied the weighting function modified differential optical absorption spectroscopy (WFMDOAS) algorithm to AVIRIS-NG data measured in Canada and the Four Corners region. The WFM-DOAS retrieval is conceptually located between the statistical matched filter (MF) and the optimal-estimation-based iterative maximum a posteriori DOAS (IMAP-DOAS) retrieval algorithm, both of which were already applied successfully to AVIRIS-NG data. The WFM-DOAS algorithm is based on a first order Taylor series approximation of the Lambert-Beer law using only one precalculated radiative transfer calculation per scene. This yields the fast quantitative processing of large data sets. We detected several methane plumes in the AVIRIS-NG images recorded during the Arctic-Boreal Vulnerability Experiment (ABoVE) Airborne Campaign and successfully retrieved a coal mine ventilation shaft plume observed during the Four Corners measurement campaign. The comparison between IMAP-DOAS, MF, and WFMDOAS showed good agreement for the coal mine ventilation shaft plume. An additional comparison between MF and WFM-DOAS for a subset of plumes showed good agreement for one plume and some differences for the others. For five plumes, the emissions were estimated using a simple cross-sectional flux method. The retrieved fluxes originated from well pads, cold vents, and a coal mine ventilation shaft and ranged between (155 ± 71) kg (CH4) h-1 and (1220 ± 450) kg (CH4) h-1. The wind velocity was a significant source of uncertainty in all plumes, followed by the single pixel retrieval noise and the uncertainty due to atmospheric variability. The noise of the retrieved CH4 imagery over bright surfaces (> 1 μW cm-2 nm-1 sr-1 at 2140 nm) was typically ±2:3 % of the background total column of CH4 when fitting strong absorption lines around 2300 nm but could reach over ±5 % for darker surfaces (> 0.3 μW cm-2 nm-1 sr-1 at 2140 nm). Additionally, a worst case large-scale bias due to the assumptions made in the WFM-DOAS retrieval was estimated to be ±5:4 %. Radiance and fit quality filters were implemented to exclude the most uncertain results from further analysis mostly due to either dark surfaces or surfaces where the surface spectral reflection structures are similar to CH4 absorption features at the spectral resolution of the AVIRIS-NG instrument. © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.
    • Environmental effects on aerosol-cloud interaction in non-precipitating marine boundary layer (MBL) clouds over the eastern North Atlantic

      Zheng, X.; Xi, B.; Dong, X.; Wu, P.; Logan, T.; Wang, Y.; Department of Hydrology and Atmospheric Sciences, University of Arizona (Copernicus GmbH, 2022)
      Over the eastern North Atlantic (ENA) ocean, a total of 20 non-precipitating single-layer marine boundary layer (MBL) stratus and stratocumulus cloud cases are selected to investigate the impacts of the environmental variables on the aerosol-cloud interaction (ACIr) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during 2016-2018. The ACIr represents the relative change in cloud droplet effective radius re with respect to the relative change in cloud condensation nuclei (CCN) number concentration at 0.2ĝ€¯% supersaturation (NCCN,0.2%) in the stratified water vapor environment. The ACIr values vary from -0.01 to 0.22 with increasing sub-cloud boundary layer precipitable water vapor (PWVBL) conditions, indicating that re is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher Nc and PWVBL. The principal component analysis shows that the most pronounced pattern during the selected cases is the co-variations in the MBL conditions characterized by the vertical component of turbulence kinetic energy (TKEw), the decoupling index (Di), and PWVBL. The environmental effects on ACIr emerge after the data are stratified into different TKEw regimes. The ACIr values, under both lower and higher PWVBL conditions, more than double from the low-TKEw to high-TKEw regime. This can be explained by the fact that stronger boundary layer turbulence maintains a well-mixed MBL, strengthening the connection between cloud microphysical properties and the below-cloud CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size spectra and consequently results in an enlargement of re. The enhanced activation of CCN and the cloud droplet condensational growth induced by the higher below-cloud CCN loading can effectively decrease re, which jointly presents as the increased ACIr. This study examines the importance of environmental effects on the ACIr assessments and provides observational constraints to future model evaluations of aerosol-cloud interactions. © Copyright:
    • Evaluation of carbonyl sulfide biosphere exchange in the Simple Biosphere Model (SiB4)

      Kooijmans, L.M.J.; Cho, A.; Ma, J.; Kaushik, A.; Haynes, K.D.; Baker, I.; Luijkx, I.T.; Groenink, M.; Peters, W.; Miller, J.B.; et al. (Copernicus GmbH, 2021)
      The uptake of carbonyl sulfide (COS) by terrestrial plants is linked to photosynthetic uptake of CO2 as these gases partly share the same uptake pathway. Applying COS as a photosynthesis tracer in models requires an accurate representation of biosphere COS fluxes, but these models have not been extensively evaluated against field observations of COS fluxes. In this paper, the COS flux as simulated by the Simple Biosphere Model, version 4 (SiB4), is updated with the latest mechanistic insights and evaluated with site observations from different biomes: one evergreen needleleaf forest, two deciduous broadleaf forests, three grasslands, and two crop fields spread over Europe and North America. We improved SiB4 in several ways to improve its representation of COS. To account for the effect of atmospheric COS mole fractions on COS biosphere uptake, we replaced the fixed atmospheric COS mole fraction boundary condition originally used in SiB4 with spatially and temporally varying COS mole fraction fields. Seasonal amplitudes of COS mole fractions are ∼50-200 ppt at the investigated sites with a minimum mole fraction in the late growing season. Incorporating seasonal variability into the model reduces COS uptake rates in the late growing season, allowing better agreement with observations. We also replaced the empirical soil COS uptake model in SiB4 with a mechanistic model that represents both uptake and production of COS in soils, which improves the match with observations over agricultural fields and fertilized grassland soils. The improved version of SiB4 was capable of simulating the diurnal and seasonal variation in COS fluxes in the boreal, temperate, and Mediterranean region. Nonetheless, the daytime vegetation COS flux is underestimated on average by 8±27 %, albeit with large variability across sites. On a global scale, our model modifications decreased the modeled COS terrestrial biosphere sink from 922 GgSyr-1 in the original SiB4 to 753 GgSyr-1 in the updated version. The largest decrease in fluxes was driven by lower atmospheric COS mole fractions over regions with high productivity, which highlights the importance of accounting for variations in atmospheric COS mole fractions. The change to a different soil model, on the other hand, had a relatively small effect on the global biosphere COS sink. The secondary role of the modeled soil component in the global COS budget supports the use of COS as a global photosynthesis tracer. A more accurate representation of COS uptake in SiB4 should allow for improved application of atmospheric COS as a tracer of local-to global-scale terrestrial photosynthesis. © 2021 Linda M. J. Kooijmans et al.