Dissolved oxygen controls important processes in lakes, from chemical reactions to organism community structure and metabolism. In shallow lakes, small volumes allow for large fluctuations in dissolved oxygen concentrations, and the oxygen regime can greatly affect ecosystem-scale processes. We used high frequency dissolved oxygen measurements to examine differences in oxygen regimes between two alternative stable states that occur in shallow lakes. We compared annual oxygen regimes in four macrophyte-dominated, clear state lakes to four phytoplankton-dominated, turbid state lakes by quantifying oxygen concentrations, anoxia frequency, and measures of whole-lake metabolism. Oxygen regimes were not significantly different between lake states throughout the year except for during the winter under-ice period. During winter, clear lakes had less oxygen, higher frequency of anoxic periods, and higher oxygen depletion rates. Oxygen depletion rates correlated positively with peak summer macrophyte biomass. Due to lower levels of oxygen, clear shallow lakes may experience anoxia more often and for longer duration during the winter, increasing the likelihood of experiencing fish winterkill. These observations have important implications for shallow lake management, which typically focuses efforts on maintaining the clearwater state.

Hurricanes bring heavy rain and induce catastrophic flooding. The damage and fatalities underscore the urgency for understanding and improving the hydrological forecasts. Here we build an integrated hydrological framework in support of decision making, specifically for heavy rainfall caused by tropical storms. We apply different ensemble approaches for short-lived tropical storms (e.g., Tropical Storm Imelda) and long-lasting and major hurricanes (e.g., Hurricane Harvey). To drive the WRF-Hydro/National Water Model (NWM), atmospheric inputs are derived from the dynamical ensemble prediction based on Hurricane Weather Research and Forecasting (HWRF) for Hurricane Harvey. For short-lived tropical storms, which do not have operational hurricane forecast from regional dynamical models, we manually generate an ensemble forecast from a deterministic weather forecast from the Global Forecast System (GFS) and perturb the precipitation intensity and location according to the new runs from the High-Resolution Rapid Refresh (HRRR). On top of the current operational forecast from NWM, both of our approaches generate more than 20 separate forecasts (ensemble members) to address uncertainties in atmospheric dynamics, specifically for tropical storms and hurricanes. We evaluate the storm track, precipitation, and streamflow over the hurricane-prone areas of Texas. By linking ensemble weather forecasts to hydrological forecasts, we seek to provide a more comprehensive understanding of the underlying models and support advanced research on flood resilience for critical infrastructures.

Development is well-advanced for the next version of the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG), labeled Version 07. IMERG is a key output of the U.S. GPM Science Team, and V07 will be the second generation in which data from both the Tropical Rainfall Measuring Mission (TRMM) and GPM projects are combined into a single, uniformly processed record, currently starting in June 2000. This presentation will show several examples of successes and challenges in V06, and use these to illuminate the upgrades that have been pursued for V07. For example, the V06 IMERG near-real-time products (Early and Late Runs) show regional biases because they do not have climatological calibration (despite the documentation), and this will be done in V07. As well, the time series of precipitation-rate histograms shows a seam in the transition from TRMM calibration to GPM Core Observatory calibration at the start of June 2014. V07 will benefit from better continuity in the input calibration datasets across that boundary. A third issue is that the Kalman filter used in IMERG a) introduces a variable amount of smoothing, and b) depends on relatively simple measures of input data quality. Both of these are revisited in V07. We will report the status of IMERG Version 07 processing as of the conference time, and introduce some topics that are being considered for the future, including improved uncertainty estimates, addition of sub-monthly gauge information, and strategies for incorporating precipitation estimates from multiple, relatively short-lived small satellites.

Of the major coastal land change mechanisms responsible for relative sea-level change, tectonic subsidence is generally quoted as ranging from < mm/yr to 1 cm/yr. However, we documented coseismic and ongoing post-earthquake surface displacements from continuous GPS and tide gauge/altimetry data that indicated rapid subsidence on two of the major Samoan Islands of 12 - 20 cm during and following the 8.1 2009 Tonga-Samoa earthquake. Earlier results and our modeling of GRACE-derived gravimetric data provided a preliminary forecast of future relative sea-level rise through rapid land subsidence [Han et al., 2019]. Of course these numerical forecasts of time-dependent deformation are only as good as our input observations and our assumed rheological models. As part of our current NASA Earth Surface and Interior study, we are obtaining a wider range of data to constrain and test alternate models of ongoing postseismic deformation across American Samoa and Upolu, Samoa: (1) times series of altimetry plus tide gauge data processed to complement the cGPS data available to provide high-temporal resolution, point measurements of uplift/subsidence, (2) InSAR derived observations of surface deformation across the highly vegetated Samoan Islands, (3) evaluating and using NASA satellite lidar data (ICESat-I & ICESat-II, GEDI) for fusion with multi-source topographic data sets and for estimating topographic change on the decadal time scale. We are evaluating and using these new observations to better understand and separate out local, island-wide, and multi-island subsidence patterns and to evaluate the high impact of rising sea-level in a tectonically active region.

The Brewer-Dobson Circulation (BDC) determines the distribution of long-lived trac- ers in the stratosphere; therefore, their changes can be used to diagnose changes in the BDC. We evaluate decadal (2005-2018) trends of nitrous oxide (N2O) in two versions of the Whole Atmosphere Chemistry-Climate Model (WACCM) by comparing them with measurements from four Fourier transform infrared (FTIR) ground-based instruments, the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and with a chemistry-transport model (CTM) driven by four different reanalyses. The limited sensitivity of the FTIR instruments can hide negative N2O trends in the mid-stratosphere because of the large increase in the lowermost stratosphere. When applying ACE-FTS measurement sampling on model datasets, the reanalyses from the European Centre for Medium Range Weather Forecast (ECMWF) compare best with ACE-FTS, but the N2O trends are consistently exaggerated. The N2O trends obtained with WACCM disagree with those obtained from ACE-FTS, but the new WACCM version performs better than the previous above the Southern Hemisphere in the stratosphere. Model sensitivity tests show that the decadal N2O trends reflect changes in the stratospheric transport. We further investigate the N2 O Transformed Eulerian Mean (TEM) budget in WACCM and in the CTM simulation driven by the latest ECMWF reanalysis. The TEM analysis shows that enhanced advection affects the stratospheric N2O trends in the Tropics. While no ideal observational dataset currently exists, this model study of N2O trends still provides new insights about the BDC and its changes because of the contribution from relevant sensitivity tests and the TEM analysis.

Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water, and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human-natural system interactions as well as institutionally-aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision-relevant model outputs that adequately capture the multi-sector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a sub-basin of the Colorado river. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.

Data Assimilation (DA) is a powerful tool to optimally combine uncertain model simulations and observations. Among DA techniques, the Particle Filter (PF) has gained attention for its capacity to deal with non-linear systems and for its relaxation of the Gaussian assumption. However, the PF may suffer from degeneracy and sample impoverishment. In this study, we propose an innovative approach, based on a Tempered Particle Filter (TPF), aiming at mitigating PFs issues, thus extending over time the assimilation benefits. Flood probabilistic maps derived from Synthetic Aperture Radar data are assimilated into a flood forecasting model through an iterative process including a particle mutation in order to keep diversity within the ensemble. Results show an improvement of the model forecasts accuracy, with respect to the Open Loop (OL): on average the RMSE of water levels decrease by 80% at the assimilation time and by 60% two days after the assimilation. A comparison with the Sequential Importance Sampling (SIS), is carried out showing that although SIS performances are generally comparable to the TPF ones at the assimilation time, they tend to decrease more quickly. For instance, on average TPF-based RMSE are by 20% lower compared to the SIS-based ones two days after the assimilation. The application of the TPF determines higher CSI values compared to the SIS. On average the increase in performances lasts for almost 3 days after the assimilation. Our study provides evidence that the application of the variant of the TPF enables more persistent benefits compared to the SIS.

A westward-propagating Rossby-like wave signal is found to explain a large fraction of the intraseasonal variance in cloud brightness over the western hemisphere. A series of diagnostic criteria suggest that this wave is a moisture mode: its moisture anomalies dominate the distribution of moist static energy (MSE) and are in phase with the precipitation anomalies; and the thermodynamic equation obeys the weak temperature gradient approximation. The wave propagates westward due to zonal moisture advection by the mean flow and is maintained by radiative heating and meridional moisture advection. These properties compare favorably with the westward propagating Rossby mode in an equatorial beta-plane model with prognostic moisture, mean meridional moisture gradient, and mean zonal wind. These results underscore the importance of water vapor in the dynamics of slowly evolving tropical systems, and the limitations of dry shallow water theory that rely on a “reduced equivalent depth” to represent moist dynamics.

A map of surface molecular water was derived from long slit spectroscopy of the south polar region of the Moon using the Faint Object infraRed CAmera for the SOFIA Telescope (FORCAST) spectrometer on the Stratospheric Observatory for Infrared Astronomy (SOFIA). Mean water abundances detected are about 250 µg/g over that of a mare reference surface at Mare Fecunditatis. Water abundances are locally anticorrelated with temperature and latitude. The distribution of water is consistent with derivation of water from pre-existing hydroxyl subsequently trapped in impact glass, provided hydroxyl increases with latitude as some models and measurements suggest. The detected water cannot be in equilibrium with the exosphere because insufficient water is present to maintain the surface abundance. The data are also consistent with a high latitude water-bearing mineral host that may be a precursor to recently detected high latitude hematite.

Viscous fingering occurs when a less viscous fluid is injected into a rock matrix saturated with a more viscous fluid. Our past research using the Rothman-Keller (RK) color gradient Lattice Boltzmann Method (LBM) for immiscible two phase flow has allowed us to study viscous fingering morphology and the complex saturation phase space as a function of the fluid’s properties (wettability of the injected fluid and viscosity ratio). In this past work, we found that the primary factor affecting the saturation at breakthrough – when the injected fluid has passed through the entire model – was the viscosity ratio, and the secondary effect was the wettability. Here, we present an extension of our LBM model to enable convection-diffusion to be simulated, thereby allowing us to vary the viscosity of the injected fluid, and mimicking the practice in Enhanced Oil Recovery (EOR) using polymer additives after breakthrough as a means of increasing the viscosity ratio and thus the eventual oil yield. The basic RK multiphase LBM models two fluid number densities moving and colliding on a discrete lattice, where a second collision term is used to model cohesion within each fluid, and contains an extra “recoloring step” to ensure fluid segregation. Here, we model an additional number density representing the concentration of a polymer additive, which affects the viscosity of the injected fluid. The Peclet number – rate of advection to diffusion of the polymer solution – is used to set the diffusion coefficient of the polymer concentration number density and hence, the relaxation time in the LBM for the polymer diffusion process. We present tests to demonstrate the method in which we increase the polymer concentration of the injected fluid after a given time and study the effect on the viscous fingering morphology and saturation evolution. This work demonstrates that the RK color gradient multiphase LBM can be used to study complex viscous fingering behavior associated with injection of water with polymer additives, which can have major scientific and practical significance.

In the publication Troshichev et al. (2006) on the Polar Cap (PC) indices, PCN and PCS, an error was made by using components of the Interplanetary Magnetic Field (IMF) in their Geocentric Solar Ecliptic (GSE) representation instead of the prescribed Geocentric Solar Magnetospheric (GSM) representation for calculations of index scaling parameters. The mistake has caused a trail of incorrect relations and wrong conclusions extending since 2006 up to now (2020) which should be discontinued, for instance, by issuing a corrigendum note from the authors. The present contribution explains the error and discusses in an extended example its consequences for one of the publications that has referred to the invalid scaling parameter set. Further investigations reported here of the PC index versions recommended by the International Association for Geomagnetism and Aeronomy (IAGA) indicate occurrences of similar problems in the present derivation of index scaling parameters.

Earth observation of waterbodies through time is a powerful tool in understanding both the location of waterbodies and their temporal dynamics. Water Observations from Space (WOfS), developed and well-tested in Australia, is a service providing historical surface water observations derived from Landsat satellite imagery from 1987 to present day. WOfS provides better understanding of where water is usually present; where it is seldom observed; and where inundation of the surface has been occasionally observed by satellite. We applied the WOfS algorithm to Africa and validated its accuracy through image interpretation of satellite and aerial imagery using an online tool created by the NASA Servir program, Collect Earth Online. The Digital Earth Africa Product Development Task Team, composed of four regional geospatial organisations RCMRD, AfriGIST, AGRHYMET and OSS, conducted the validation campaign and provided both the regional expertise and experience required for a continental-scale validation effort. In order to understand the accuracy and bias of the WOfS algorithm in Africa at both the continental-scale and regional zones, we generated 2900 sample points covering the continent including the main islands and distributed them into 7 Agro-ecological zones. We assessed whether the point was flooded, dry, or cloud covered, for 12 months in 2018, resulting in 34,800 assessed observations. As water information is available through WOfS in near real-time, it can be used for environmental monitoring, flood mapping, monitoring planned water releases, and management of water resources in highly regulated systems. WOfS is expected to be used by ministries and state departments of agriculture and water management in countries, international organizations, academia and the private sector.

Surface wave energy and dissipation are observed across the surf zone. Utilizing the concept of surface rollers, a new scaling is introduced to obtain the energy flux and dissipation related to rollers from Doppler velocities measured by a shore-based X-band marine radar. The dissipation of wave energy and hence the transformation of the incoming wave height (or energy) is derived using the coupled wave and roller energy balance equations. Results are compared to in-situ wave measurements obtained from a wave rider buoy and two bottom mounted pressure wave gauges. A good performance in reproducing the significant wave height is found yielding an overall root-mean-square error of 0.23 m and a bias of -0.13 m. This is comparable to the skill of numerical wave models. In contrast to wave models, however, the radar observations neither require knowledge of the bathymetry nor the incident wave height. Along a 1.5 km long cross-shore transect on a double-barred, sandy beach in the southern North Sea, the highest dissipation rates are observed at the inner bar over a relatively short distance of less than 100 m. During the peak of a medium-severe storm event with significant wave heights over 3 m, about 50% of the incident wave energy flux is dissipated at the outer bar.

This paper compares the characteristics of the monthly mean AIRS Version-6 and CERES_EBAF Edition 4.0 OLR data sets over a 14-year overlap period, September 2002 through August 2016. These comparisons include spatial plots of monthly mean OLR climatologies and spatial plots of OLR Average Rates of Change (ARCs), representative of the slopes of the linear least squares fits to anomaly time series. This paper also compares spatial plots of El Niño Correlations (ENCs) of the AIRS OLR and CERES OLR anomaly time series. ENCs represent temporal correlations of anomaly time series with an El Niño Index that we define in this paper. In addition, we show ARCs and ENCs of select derived AIRS geophysical parameters that help explain OLR variability in space and time. There are separate AIRS data sets that use data observed only in ascending Aqua orbits (AIRS) and data observed only in descending Aqua orbits (AIRS). An additional data set of AIRS products exists based on observations made in both orbits (AIRS). There is excellent agreement between the ARCs of CERES OLR and the ARCs of AIRS OLR down to the 1˚ by 1˚ longitude spatial scale. The AIRS OLR product displays a positive global mean monthly mean bias compared to CERES OLR of roughly 3.0 W/m that is essentially constant in space and time. The largest differences between AIRS OLR and CERES OLR monthly climatologies and anomaly time series occur in regions where the diurnal differences of AIRS OLR are largest.

Based on experimental results of recent years, this article presents a qualitative description of a possible mechanism (termed the Mechanism) covering the main stages of lightning initiation, starting before and including the initiating event, followed by the initial electric field change (IEC), followed by the first few initial breakdown pulses (IBPs). The Mechanism assumes initiation occurs in a region of ≈1 km with average electric field E≥0.3 MV/(m∙atm), which contains, because of turbulence, numerous small ‘E-volumes’ of 10^-4-10^-3 m with E≥3 MV/(m∙atm). The Mechanism allows for lightning initiation by either of two observed types of events: a high power VHF event such as a Narrow Bipolar Event, or a weak VHF event. According to the Mechanism, both types of initiating events are caused by a group of relativistic runaway electron avalanche particles (where the initial electrons are secondary particles of an extensive air shower) passing through many ‘E-volumes’, thereby causing the nearly simultaneous launching of many positive streamer flashes. Due to ionization-heating instability, unusual plasma formations (UPFs) appear along the streamers’ trajectories of the streamers. These UPFs combine into three-dimensional (3D) networks of hot plasma channels during the IEC, resulting in its observed weak current flow. The subsequent development and combination of two (or more) of these 3D networks of hot plasma channels then causes the first IBP. Each subsequent IBP is caused when another 3D network of hot plasma channels combines with the chain of networks caused by earlier IBPs.

Iron is present in magmas at concentrations ranging from less than 1 wt% to more 8 than 10 wt% in two valence state. In general, Fe2+ is a network modifier in the melt structure while Fe3+ is a weak network former. The ratio Fe3+/(Fe3+ + Fe2+) depends on temperature, pressure, oxygen fugacity and melt composition. Parametric models allow its calculation, but the complex links between melt composition, iron oxidation state and coordination can be further rationalized using a ionic-polymeric model. Constraining concentration and oxidation state of iron is critical for determining magma density and viscosity, which drive exchanges of matter and heat in the Earth. At high pressures, changes in the coordination of elements, including iron, yield a stiffening and densification of magmas, potentially influencing dynamic and geochemical processes. Near surface, crystallization of Fe-bearing phases changes the residual melt composition, including iron content and oxidation state as well as volatile concentration, ultimately driving large changes in density and viscosity of magmas, and, hence, in the dynamic of fluid flow in volcanic systems. The complex interplay between magma iron content and oxidation state, major element chemistry, crystal and volatile content thus can play a large role on the dynamic of volcanic systems.

A dynamic one-dimensional model of the freezing of first-year sea ice with a snow cover is presented along with Matlab code. The model is based on historical models in the literature, and is primarily intended to design a computational tool that accurately simulates transient temperature changes within growing sea ice. This may complement temperature data at various depths and times in growing sea ice. The model is validated by comparing the simulated ice temperature profile and growth rate to thermistor temperature profiles measured in 1997 in McMurdo Sound, Antarctica. This comparison shows evidence of platelet ice growth. Despite this, an accuracy of ±0.4 o C is achieved throughout the entire ice temperature profile, when comparing simulated transient temperatures to data. The model is also used, with the inclusion of a 15mm thick snow layer, to correct a previously observed discrepancy between ice growth rates measured via banding structures in ice cores and the predictions of a steady state ice growth model.

The nonlinear effect of the summer SE wind and density on the 3D structures of the full Lagrangian residual velocity (LRV) was quantified for a general nonlinear system, using Jiaozhou Bay, China (JZB), as the test site. In the tidally energetic JZB, the basic patterns of the wind- and density-driven full LRV were found to be consistent with simplified semi-analytical solutions but highly dependent on the initial times. The wind-driven full LRVs detected at different tidal phases showed similar laterally sheared, three-layer circulation, but the main branches could migrate across nearly half of the inner bay. The density-driven, clockwise flow dominated the western inner bay at low tide, while almost disappearing at high tide. The effect of density generally enhanced outward flow in the surface layer and inward flow in the bottom layer. Along-trajectory, integrated momentum balances indicated that viscosity was the main force responsible for the time-dependence of the wind-driven full LRV, while viscosity and the barotropic and baroclinic pressure gradients were the main drivers of the intra-tidal variations in the density-driven full LRV. Generally, the summer wind and density had opposing effects, although their influence was weaker than that of the tide and could not change the patterns of the tide-driven full LRV. The results indicated that when the effects of wind and density on the coastal circulation of tidally energetic waters are analysed, both the 3D structures and the possibility of a high initial tidal phase dependency should be considered.