• 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.
    • 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:
    • 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.
    • 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.
    • Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields

      Vergopolan, N.; Xiong, S.; Estes, L.; Wanders, N.; Chaney, N.W.; Wood, E.F.; Konar, M.; Caylor, K.; Beck, H.E.; Gatti, N.; et al. (Copernicus GmbH, 2021)
      Soil moisture is highly variable in space and time, and deficits (i.e., droughts) play an important role in modulating crop yields. Limited hydroclimate and yield data, however, hamper drought impact monitoring and assessment at the farm field scale. This study demonstrates the potential of using field-scale soil moisture simulations to support highresolution agricultural yield prediction and drought monitoring at the smallholder farm field scale. We present a multiscale modeling approach that combines HydroBlocks a physically based hyper-resolution land surface model (LSM) with machine learning. We used HydroBlocks to simulate root zone soil moisture and soil temperature in Zambia at 3 h 30 m resolution. These simulations, along with remotely sensed vegetation indices, meteorological data, and descriptors of the physical landscape (related to topography, land cover, and soils) were combined with district-level maize data to train a random forest (RF) model to predict maize yields at district and field scales (250 m). Our model predicted yields with an average testing coefficient of determination (R2) of 0.57 and mean absolute error (MAE) of 310 kgha-1 using year-based cross-validation. Our predicted maize losses due to the 2015 2016 El Niño drought agreed well with losses reported by the Food and Agriculture Organization (FAO). Our results reveal that soil moisture is the strongest and most reliable predictor of maize yield, driving its spatial and temporal variability. Soil moisture was also a more effective indicator of drought impacts on crops than precipitation, soil and air temperatures, and remotely sensed normalized difference vegetation index (NDVI)-based drought indices. This study demonstrates how field-scale modeling can help bridge the spatial-scale gap between drought monitoring and agricultural impacts. © 2021 Author(s).
    • Geophysical constraints on the properties of a subglacial lake in northwest Greenland

      Maguire, R.; Schmerr, N.; Pettit, E.; Riverman, K.; Gardner, C.; Dellagiustina, D.N.; Avenson, B.; Wagner, N.; Marusiak, A.G.; Habib, N.; et al. (Copernicus GmbH, 2021)
      In this study, we report the results of an active-source seismology and ground-penetrating radar survey performed in northwestern Greenland at a site where the presence of a subglacial lake beneath the accumulation area has previously been proposed. Both seismic and radar results show a flat reflector approximately 830-845ĝ€¯m below the surface, with a seismic reflection coefficient of -0.43ĝ€¯±ĝ€¯0.17, which is consistent with the acoustic impedance contrast between a layer of water and glacial ice. Additionally, in the seismic data we observe an intermittent lake bottom reflection arriving between 14-20ĝ€¯ms after the lake top reflection, corresponding to a lake depth of approximately 10-15ĝ€¯m. A strong coda following the lake top and lake bottom reflections is consistent with a package of lake bottom sediments although its thickness and material properties are uncertain. Finally, we use these results to conduct a first-order assessment of the lake origins using a one-dimensional thermal model and hydropotential modeling based on published surface and bed topography. Using these analyses, we narrow the lake origin hypotheses to either anomalously high geothermal flux or hypersalinity due to local ancient evaporite. Because the origins are still unclear, this site provides an intriguing opportunity for the first in situ sampling of a subglacial lake in Greenland, which could better constrain mechanisms of subglacial lake formation, evolution, and relative importance to glacial hydrology. © Author(s) 2021.
    • Global transpiration data from sap flow measurements: The SAPFLUXNET database

      School of Natural Resources and the Environment, University of Arizona (Copernicus GmbH, 2021)
      Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80% of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50% of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56% of the datasets. Many datasets contain data for species that make up 90% or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr"R package-designed to access, visualize, and process SAPFLUXNET data-is available from CRAN. © 2021 Rafael Poyatos et al.
    • Hack distributions of rill networks and nonlinear slope length-soil loss relationships

      Doane, T.H.; Pelletier, J.D.; Nichols, M.H.; Department of Geoscience, University of Arizona (Copernicus GmbH, 2021)
      Surface flow on rilled hillslopes tends to produce sediment yields that scale nonlinearly with total hillslope length. The widespread observation lacks a single unifying theory for such a nonlinear relationship.We explore the contribution of rill network geometry to the observed yield length scaling relationship. Relying on an idealized network geometry, we formally develop probability functions for geometric variables of contributing area and rill length. In doing so, we contribute towards a complete probabilistic foundation for the Hack distribution. Using deterministic and empirical functions, we then extend the probability theory to the hydraulic variables that are related to sediment detachment and transport. A Monte Carlo simulation samples hydraulic variables from hillslopes of different lengths to provide estimates of sediment yield. The results of this analysis demonstrate a nonlinear yield length relationship as a result of the rill network geometry. Theory is supported by numerical modeling, wherein surface flow is routed over an idealized numerical surface and a natural surface from northern Arizona. Numerical flow routing demonstrates probability functions that resemble the theoretical ones. This work provides a unique application of the Scheidegger network to hillslope settings which, because of their finite lengths, result in unique probability functions. We have addressed sediment yields on rilled slopes and have contributed towards understanding Hack s law from a probabilistic reasoning. © 2021 BMJ Publishing Group. All rights reserved.
    • Hilltop curvature as a proxy for erosion rate: Wavelets enable rapid computation and reveal systematic underestimation

      Struble, W.T.; Roering, J.J.; Department of Geosciences, University of Arizona (Copernicus GmbH, 2021)
      Estimation of erosion rate is an important component of landscape evolution studies, particularly in settings where transience or spatial variability in uplift or erosion generates diverse landform morphologies. While bedrock rivers are often used to constrain the timing and magnitude of changes in baselevel lowering, hilltop curvature (or convexity), CHT, provides an additional opportunity to map variations in erosion rate given that average slope angle becomes insensitive to erosion rate owing to threshold slope processes. CHT measurement techniques applied in prior studies (e.g., polynomial functions), however, tend to be computationally expensive when they rely on high-resolution topographic data such as lidar, limiting the spatial extent of hillslope geomorphic studies to small study regions. Alternative techniques such as spectral tools like continuous wavelet transforms present an opportunity to rapidly document trends in hilltop convexity across expansive areas. Here, we demonstrate how continuous wavelet transforms (CWTs) can be used to calculate the Laplacian of elevation, which we utilize to estimate erosion rate in three catchments of the Oregon Coast Range that exhibit varying slope angle, slope length, and hilltop convexity, implying differential erosion. We observe that CHT values calculated with the CWT are similar to those obtained from 2D polynomial functions. Consistent with recent studies, we find that erosion rates estimated with CHT from both CWTs and 2D polynomial functions are consistent with erosion rates constrained with cosmogenic radionuclides from stream sediments. Importantly, our CWT approach calculates curvature at least 103 times more quickly than 2D polynomials. This efficiency advantage of the CWT increases with domain size. As such, continuous wavelet transforms provide a compelling approach to rapidly quantify regional variations in erosion rate as well as lithology, structure, and hillslope sediment transport processes, which are encoded in hillslope morphology. Finally, we test the accuracy of CWT and 2D polynomial techniques by constructing a series of synthetic hillslopes generated by a theoretical nonlinear transport model that exhibit a range of erosion rates and topographic noise characteristics. Notably, we find that neither CWTs nor 2D polynomials reproduce the theoretically prescribed CHT value for hillslopes experiencing moderate to fast erosion rates, even when no topographic noise is added. Rather, CHT is systematically underestimated, producing a power law relationship between erosion rate and CHT that can be attributed to the increasing prominence of planar hillslopes that narrow the zone of hilltop convexity as erosion rate increases. As such, we recommend careful consideration of measurement length scale when applying CHT to estimate erosion rate in moderate to fast-eroding landscapes, where curvature measurement techniques may be prone to systematic underestimation. © Copyright:
    • Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase i (LS4P-I): Organization and experimental design

      Xue, Y.; Yao, T.; Boone, A.A.; Diallo, I.; Liu, Y.; Zeng, X.; Lau, W.K.M.; Sugimoto, S.; Tang, Q.; Pan, X.; et al. (Copernicus GmbH, 2021)
      Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called "Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction"(LS4P) as the first international grass-roots effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land-atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regional climate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond East Asia and its S2S prediction. Preliminary studies and analysis have also shown that LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems. © 2021 Yongkang Xue et al.
    • Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements

      Harper, A.B.; Williams, K.E.; Mcguire, P.C.; Duran Rojas, M.C.; Hemming, D.; Verhoef, A.; Huntingford, C.; Rowland, L.; Marthews, T.; Breder Eller, C.; et al. (Copernicus GmbH, 2021)
      Drought is predicted to increase in the future due to climate change, bringing with it myriad impacts on ecosystems. Plants respond to drier soils by reducing stomatal conductance in order to conserve water and avoid hydraulic damage. Despite the importance of plant drought responses for the global carbon cycle and local and regional climate feedbacks, land surface models are unable to capture observed plant responses to soil moisture stress. We assessed the impact of soil moisture stress on simulated gross primary productivity (GPP) and latent energy flux (LE) in the Joint UK Land Environment Simulator (JULES) vn4.9 on seasonal and annual timescales and evaluated 10 different representations of soil moisture stress in the model. For the default configuration, GPP was more realistic in temperate biome sites than in the tropics or high-latitude (cold-region) sites, while LE was best simulated in temperate and high-latitude (cold) sites. Errors that were not due to soil moisture stress, possibly linked to phenology, contributed to model biases for GPP in tropical savanna and deciduous forest sites. We found that three alternative approaches to calculating soil moisture stress produced more realistic results than the default parameterization for most biomes and climates. All of these involved increasing the number of soil layers from 4 to 14 and the soil depth from 3.0 to 10.8 m. In addition, we found improvements when soil matric potential replaced volumetric water content in the stress equation (the &quot;soil14_psi&quot; experiments), when the critical threshold value for inducing soil moisture stress was reduced (&quot;soil14_p0&quot;), and when plants were able to access soil moisture in deeper soil layers (&quot;soil14_dr&z.ast;2&quot;). For LE, the biases were highest in the default configuration in temperate mixed forests, with overestimation occurring during most of the year. At these sites, reducing soil moisture stress (with the new parameterizations mentioned above) increased LE and increased model biases but improved the simulated seasonal cycle and brought the monthly variance closer to the measured variance of LE. Further evaluation of the reason for the high bias in LE at many of the sites would enable improvements in both carbon and energy fluxes with new parameterizations for soil moisture stress. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES or as a general way to improve land surface carbon and water fluxes in other models. In addition, using soil matric potential presents the opportunity to include plant functional type-specific parameters to further improve modeled fluxes. &copy; 2021 Anna B. Harper et al. © 2021 International Union of Crystallography. All rights reserved.
    • Measurement report: Firework impacts on air quality in Metro Manila, Philippines, during the 2019 New Year revelry

      Rose Lorenzo, G.; Angela Bañaga, P.; Obiminda Cambaliza, M.; Templonuevo Cruz, M.; Azadiaghdam, M.; Arellano, A.; Betito, G.; Braun, R.; Corral, A.F.; Dadashazar, H.; et al. (Copernicus GmbH, 2021)
      Fireworks degrade air quality, reduce visibility, alter atmospheric chemistry, and cause short-term adverse health effects. However, there have not been any comprehensive physicochemical and optical measurements of fireworks and their associated impacts in a Southeast Asia megacity, where fireworks are a regular part of the culture. Sizeresolved particulate matter (PM) measurements were made before, during, and after New Year 2019 at the Manila Observatory in Quezon City, Philippines, as part of the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex). A high-spectral-resolution lidar (HSRL) recorded a substantial increase in backscattered signal associated with high aerosol loading ∼ 440m above the surface during the peak of firework activities around 00:00 (local time). This was accompanied by PM2:5 concentrations peaking at 383.9 μgm-3. During the firework event, watersoluble ions and elements, which affect particle formation, growth, and fate, were mostly in the submicrometer diameter range. Total (>0:056 μm) water-soluble bulk particle mass concentrations were enriched by 5.7 times during the fireworks relative to the background (i.e., average of before and after the firework). The water-soluble mass fraction of PM2:5 increased by 18.5% above that of background values. This corresponded to increased volume fractions of inorganics which increased bulk particle hygroscopicity, kappa (κ), from 0.11 (background) to 0.18 (fireworks). Potassium and non-sea-salt (nss) SO2-4 contributed the most (70.9 %) to the water-soluble mass, with their mass size distributions shifting from a smaller to a larger submicrometer mode during the firework event. On the other hand, mass size distributions for NO3- , Cl-, and Mg2+ (21.1% mass contribution) shifted from a supermicrometer mode to a submicrometer mode. Being both uninfluenced by secondary aerosol formation and constituents of firework materials, a subset of species were identified as the best firework tracer species (Cu, Ba, Sr, K+, Al, and Pb). Although these species (excluding K+) only contributed 2.1% of the total mass concentration of watersoluble ions and elements, they exhibited the highest enrichments (6.1 to 65.2) during the fireworks. Surface microscopy analysis confirmed the presence of potassium/chloride-rich cubic particles along with capsule-shaped particles in firework samples. The results of this study highlight how firework emissions change the physicochemical and optical properties of water-soluble particles (e.g., mass size distribution, composition, hygroscopicity, and aerosol backscatter), which subsequently alters the background aerosol's respirability, influence on surroundings, ability to uptake gases, and viability as cloud condensation nuclei (CCN). © Author(s) 2021.