New Zealand atmospheric river (AR) lifecycles are analyzed to examine the synoptic conditions that produce extreme precipitation and regular flooding. An AR lifecycle tracking algorithm, novel to the region, is utilized to identify the genesis location of New Zealand ARs: the location where moisture fluxes enhance and become distinct synoptic features capable of producing impactful weather conditions. Genesis locations of ARs that later impact New Zealand cover a broad region extending from the Southern Indian Ocean (90°E) into the South Pacific (170°W) with the highest genesis frequency being in the Tasman Sea. The most impactful ARs, associated with heavy precipitation, tend to originate from distinct regions based on landfall location. Impactful North Island ARs tend to originate from subtropical regions to the northwest of New Zealand, while impactful South Island ARs are associated with genesis over southeast Australia. The synoptic conditions of impactful AR genesis are identified with North Island ARs typically associated with a cyclone in the central Tasman Sea along with a distant, persistent low pressure off the coast of West Antarctica. South Island AR genesis typically occurs in conjunction with moist conditions over Australia associated with a zonal synoptic-scale wavetrain. The Madden–Julian oscillation (MJO) is examined as a potential source of variability that modulates New Zealand AR lifecycles. It appears that the MJO modulates AR characteristics, especially during Phase 5, typically bringing more frequent, slow moving ARs with greater moisture fluxes to the North Island of New Zealand.

To study the contributions of cusp outflow coming through the lobes and nightside auroral outflow to the O+ in the plasma sheet, we performed a statistical study of tailward streaming O+ in the lobes, the plasma sheet boundary layer (PSBL) and the plasma sheet (PS), using MMS/HPCA data. Similar spatial distributions demonstrate the entry of cusp-origin O+ from the lobes to the plasma sheet through the PSBL. There is an energy dependence in the lobe O+ spatial distribution, with low-energy O+ streaming near the center in YGSM while high energy (1-3 keV) O+ streams near the flanks. Low energy (< 100 eV) O+ from the nightside auroral oval can be identified in the near-Earth PSBL/PS with high-density (> 0.03 cm-3), and energetic (> 3 keV) streaming O+ with similar density (~0.02 cm-3) is seen further out on the duskside of the PSBL/PS. The rest of the nightside auroral O+ in the PSBL is mixed with O+ coming in from the lobe, and difficult to distinguish. We estimated the inflow and outflow of ions in the plasma sheet between 7-17 RE, using data extracted from previous studies and this work. Comparisons between the estimated fluence suggest that the majority of near-Earth plasma sheet H+ are from cusps and Earthward convection from the distant tail. The O+ in the same region, on the other hand, has a mixed source, with auroral outflow giving the highest contribution.

We will present signal processing techniques based on shape analysis of the time-frequency signatures of chorus elements in the Van Allen Radiation Belts. Specifically, we will employ the Radon transform and the Distance Transform, which are well-known for isolating local shapes and patterns in the image processing literature, to achieve automated detection of the spectral morphology of chorus elements. In particular, we will introduce “shrink-wrapping” techniques that quantify the salient features defining the microstructure of chorus elements. We will present preliminary results based on case studies of the EMFISIS data from the Van Allen Radiation Belts mission.

In the frame of the Europlanet-RI-2020 program, the VESPA (Virtual European Solar and Planetary Access) team has developed a metadata dictionary dedicated to data discovery in solar system sciences. The dictionary is called EPNcore and includes metadata for data coverage (temporal, spatial, spectral…), data content (target, measured parameter…), data origin (instrument, publisher…) and data access (format, URL…). In order to interoperate with the NASA/PDS4, the main archive information model in planetary sciences, it is first necessary to implement the EPNcore dictionary into the PDS4 information model. This is done with setting up a Local Data Dictionary (LDD). The second step deals with the mapping between terms already defined in the PDS4 information model and the EPNcore dictionary. We present the EPNcore LDD and a first version of the term mapping, as well as a prototype interface to query PDS4 from the VESPA portal. The Europlanet H2020 Research Infrastructure project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 654208.

Unlike actual rainfall, the spatial extent of rainfall maps is often determined by administrative and political boundaries. Similarly, data from commercial microwave links (CMLs) is usually acquired on national basis and exchange among countries is limited. Up to now, this has prohibited the generation of transboundary CML-based rainfall maps despite the great extension of networks across the world. We present CML based rainfall maps for the first time, using independent CML data sets from Germany and the Czech Republic. For homogenization we apply three increasingly effective algorithms of filtering and time series interpolation. We show that straightforward algorithms used for homogenisation strongly reduce anomalies in the results. Furthermore, we find that after the homogenization and joint processing, CML-based rainfall maps can be generated which seamlessly visualize a rainfall event traversing the German-Czech border. This displays the potential for large scale (e.g. continental) CML-based rainfall estimation.

Reducing the model spread in free-tropospheric relative humidity (RH) and its response to warming is a crucial step towards reducing the uncertainty in clear-sky climate sensitivity, a step that is hoped to be taken with recently developed global storm-resolving models (GSRMs). In this study we quantify the inter-model differences in tropical present-day RH across GSRMs, making use of DYAMOND, a first 40-day intercomparison. We find that the inter-model spread in tropical mean free-tropospheric RH is reduced compared to conventional atmospheric models, except from the the tropopause region and the transition to the boundary layer. We estimate the reduction to approximately 50-70% in the upper troposphere and 25-50% in the mid troposphere. However, the remaining RH differences still result in a spread of 1.2 Wm-2 in tropical mean clear-sky outgoing longwave radiation (OLR). This spread is mainly caused by RH differences in the lower and mid free troposphere, whereas RH differences in the upper troposphere have a minor impact. By examining model differences in moisture space we identify two regimes with a particularly large contribution to the spread in tropical mean clear-sky OLR: rather moist regimes at the transition from deep convective to subsidence regimes and very dry subsidence regimes. Particularly for these regimes a better understanding of the processes controlling the RH biases is needed.

We present detailed 3-D images of whole mantle P-wave velocity structure beneath Southeast Asia and surrounding regions. The results are obtained by applying an updated global tomographic method to invert ~8 million P, pP, PP, PcP, and Pdiff arrival times from 23,587 earthquakes recorded at 14,136 stations distributed all over the world. Our tomographic model reveals a continuous, thin low-velocity (low-V) zone from the surface to the core-mantle boundary beneath the Hainan hotspot, which may reflect the Hainan plume that exists in the whole mantle. Beneath the Australian slab that has subducted into the lower mantle, a strong low-V anomaly is detected, which may reflect subslab hot mantle upwelling (SHMU) due to return flow of the slab subduction. Our model also shows the distinct shape of subducted slabs in the upper mantle and slab remnants in the lower mantle. In particular, a hole in the subducting Australian slab is revealed at depths of 280–430 km beneath eastern Java. The low-V anomaly in the mantle wedge above the Australian slab is connected with the SHMU through the slab hole, suggesting that mixture of the island arc magma and the SHMU may have caused huge eruptions of the Tambora and Rinjani volcanoes in eastern Java.

We compute stress drops from P and S phase spectra for 534 earthquakes in the source region of the 2014 MW 8.1 Iquique megathrust earthquake in the northern Chilean subduction zone. An empirical Green’s function based method is applied to suitable event pairs selected by template matching of eight years of continuous waveform data. We evaluate the parameters involved in the stress drop estimation, consider the effect of the local velocity structure and apply an empirical linear relation between P and S phase related geometry factors (k values). Data redundancy produced by multiple EGFs and the combination of P and S phase spectra leads to a substantial reduction of uncertainty and robust stress drop estimates. The resulting stress drop values show a well-defined log-normal distribution with a median value of 4.36 MPa; most values range between 0.1-100 MPa. There is no evidence for systematic large scale lateral variations of stress drop. A detailed analysis reveals several regions of increased median stress drop, an increase with distance to the interface, but no consistent increase with depth. This suggests that fault regime and fault strength have a stronger impact on the stress drop behavior than absolute stresses. Interestingly, we find a weak time-dependence of the median stress drop, with an increase immediately before the April 1, 2014 MW 8.1 Iquique mainshock, a continuous reduction thereafter and a subsequent recovery to average values. Additionally, the data set indicates a relatively strong dependence of stress drop on magnitude which extends over the entire analyzed magnitude range.

For catchment-scale streamflow estimation, recently, the preference is shifting towards the use of innovative remote sensing (RS)-based approaches at the remote gauging stations. In this context, this study evaluates the performances of three RS-based models designed with the near-infrared (NIR) bands of Landsat images at the Jenapur outlet of the Brahmani River basin in eastern India. These RS-based models are designed using the spectral behavior of land (C) and water (M) pixels in the NIR region of the electromagnetic spectrum in the presence and absence of water surrounding the streamflow gauging station. Further, the computed pixel ratio (C/M) is used as a parameter for the discharge estimation, in which four years (2009-2013) of Landsat images are used during calibration and three years (2014-2016) of these images are used during validation. Model-I uses the C/M method in which a box-matrix is conceptualized to analyze the optimal location of the land pixel (C0); and subsequently, the time series of C/M is calibrated with the in-situ discharge (Q) time series. The best pixel ratio (C0/M) time series is preprocessed with an exponential smoothing filter to derive the best filtered-pixel ratio (C0/M*) time series, which is used in the regression model to estimate the river discharge. Model-II corresponds to the multi-pixel ratio (MPR) method, where a 3×3 window is used to calculate the average reflectance of both the C and M pixels within the box-matrix, and subsequently, to obtain the best pixel (C0ʹ/Mʹ) ratio as in the case of Model-I to develop the spectral relationship between C0ʹ/Mʹ and Q time series. Model-III uses both the C/M and water width-based function to estimate the streamflow. The performance evaluation of the models is carried out using the Nash-Sutcliffe efficiency, Percentage bias, and Mean absolute error, which reveals that the model performance varies in the order: Model-III > Model-II > Model-I. This proposed RS-based discharge estimation model framework has the potential to be used in many world- rivers with varying cross-sections.

The dynamic topography of the core-mantle boundary (CMB) provides important constraints on dynamic processes in the mantle and core. However, inferences on CMB topography are complicated by the uneven coverage of data with sensitivity to different length scales and strong heterogeneity in the lower mantle. Particularly, a trade-off exists with density variations, which ultimately drive mantle flow and are vital for determining the origin of mantle structures. Here, I review existing models of CMB topography and lower mantle density, focusing on seismological constraints. I develop average models and vote maps with the aim to find model consistencies and discuss what these may teach us about lower mantle structure and dynamics. While most density models image two areas of dense anomalies beneath Africa and the Pacific, their exact location and relationship to seismic velocity structure differs between studies. CMB topography strongly influences the retrieved density structure, which helps to resolve differences between recent studies based on Stoneley modes and tidal measurements. Current CMB topography models vary both in pattern and amplitude and a discrepancy exists between models based on body-wave and normal-mode data. As existing models feature elevated topography below the Large-Low-Velocity Provinces (LLVPs), very dense compositional anomalies may currently be ruled out as possibility. To achieve a similar consistency as observed in lower mantle models of S-wave and P-wave velocity, future studies should combine multiple data sets to break existing trade-offs between CMB topography and density. Important considerations in these studies should be the choice of theoretical approximation and parameterisation. Efforts to develop models of CMB topography consistent with body-wave, normal-mode and geodetic data should be intensified, which will aid in narrowing down possible explanations for the LLVPs and provide additional insights into mantle dynamics.

The decline in global emissions of carbon dioxide due to the COVID-19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID-related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global-scale ΔpCO2 that is attributable to COVID and potentially detectable in observations, but only with much larger emissions reductions than those that have been observed to date.

The El Niño-Southern Oscillation (ENSO) is a natural climate phenomenon that alters the biogeochemical and physical dynamics of the Eastern Tropical Pacific Ocean. Its two phases, El Niño and La Niña, are characterized by decreased and increased coastal upwelling, respectively, which have cascading effects on primary productivity, organic matter supply, and ocean-atmosphere interactions. The Eastern Tropical South Pacific (ETSP) oxygen minimum zone (OMZ) is a source of nitrous oxide (N2O), a potent greenhouse gas, to the atmosphere. While nitrogen cycling in the ETSP OMZ has been shown to be sensitive to ENSO, we present the first study to directly compare N2O distributions during both ENSO phases using N2O isotopocule analyses. Our data show that during La Niña, N2O accumulation increased six-fold in the upper 100 m of the water column, and N2O fluxes to the atmosphere increased up to 100-fold. N2O isotopocule data demonstrated substantial increases in δ18O up to 60.5‰ and decreases in δ15Nβ down to -10.3‰, signaling a shift in N2O cycling during La Niña in the oxycline compared to El Niño. N2O production via the hybrid pathway and incomplete denitrification with overprinting of N2O consumption are likely co-occurring to maintain the high site preference (SP) values (17‰ – 26.7‰), corroborating previous hypotheses. Ultimately, our results illustrate a strong connection between upwelling intensity, biogeochemistry, and N2O flux to the atmosphere, and highlight the importance of repeat measurements in the same region to constrain N2O interannual variability and cycling dynamics under different climate scenarios.

Using three models of upper mantle hydration state, we quantify the subsolidus process of mass redistribution within and out of slabs. We use a numerical model where all major elements in the rock are soluble and mobile. Our transport model achieves high accuracy in predicting the energetics and fluid/rock mass balance of subduction zone processes. We find that most carbonate rich sediments (e.g. eastern Pacific) get depleted in K while they accumulate Al and Si. Patterns of mass and concentration changes are not always correlated, reflecting the antagonistic role of metasomatism versus residual enrichment due to volatile loss. We find that carbon released to subarc depth is 25.7 – 31.4 Mt C/yr, which corresponds to 51.0 to 61.9 % of trench input, confirming previous estimates. However, this decarbonation efficiency is highly heterogeneous. The host slabs of eastern pacific recycle most carbon back to the mantle wedge, while the cold slabs of western pacific inject carbon. Slabs decarbonation efficiencies show different sensitivity to hydration state of the mantle wedge. Transport (water)-limited slabs, which are sensitive to the AUM hydration state, are the most numerous and tend to be the largest C emitters. There are also supply-limited slabs, i.e. not sensitive to the AUM hydration state, e.g. hot (Mexico) and cold (Honshu) slabs. We first show that slabs subducting limestones are sensitive to infiltration of non-volatile elements from underlying igneous sections to drive metasomatic-decarbonation process by promoting garnet growth. These insights inform specific regional targets for studying the cycle of rock-forming elements.

Bays within eastern boundary upwelling systems (EBUS) are ecological hot-spots featuring a diverse range of spatio-temporal dynamics. At the EBUSs’ poleward limit, upwelling occurs in short-lived (<1 week) pulses modulated by synoptic wind variability. The circulations in long, narrow bays can respond to these fluctuations within few hours. The short-term biological response to these pulses was investigated in two of these bays (Rias Baixas, NW-Iberia) with a two-week quasi-synoptic spatio-temporal survey in the summer 2018. A four-day-long upwelling pulse caused deep, nutrient-rich isopycnals to rise into the euphotic zone inside the bays, triggering a rapid (~1.7 days) nutrient uptake and formation of a subsurface chlorophyll maximum (~3.8 days). The phytoplankton biomass was transported rapidly toward deep, offshore waters when the winds weakened. These results suggest that high productivity in narrow bays is controlled by the transient exposure of deep, nutrient-rich waters to light during upwelling pulses.

During the second half of 2019, a series of recurring, moderate geomagnetic storms (Dst ≈ - 70 nT) emerged after a sequence of high-speed solar wind streams (Vsw ≥ 600 km/s) impacted the magnetosphere. During one of these storms, intense substorm activity was also recorded (SML ≈ - 2000 nT on August 31 and September 1), as well as a longer-lasting solar wind pressure pulse. We investigate this series of events, using particle measurements from three missions that recorded significant enhancements of relativistic electron fluxes: the Van Allen Probes, Arase and Galileo 207 & 215 satellites. We use both the flux intensity and the phase space density (PSD) of electrons, along with interplanetary parameters and information on ultra-low frequency (ULF) and chorus wave activity for a detailed analysis of this event. Our study demonstrates the importance of substorm injections, even during moderate or weak geomagnetic storms. The presence of seed electrons at L* = 4-5, in addition to intense ULF and chorus wave activity, seems to result in very efficient electron acceleration to relativistic and ultra-relativistic energies. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 for the SafeSpace project.

England and May (2021) present a model comparison for the forearc thermal structure in subduction zones that employs a finite element modeling technique and a new variation on approximate equations. We have some comments on various claims made in this published paper.

A numerical solute transport model was history matched to a high-resolution monitoring dataset to characterize a multicomponent source of nonaqueous phase liquids (NAPLs) and evaluate the uncertainty of estimated parameters. The dissolution of NAPL mass was simulated using the SEAM3D solute transport model with spatially-varying NAPL saturations and mass transfer rate coefficients, representing the heterogenous architecture of the source zone. Source zone parameters were simultaneously estimated using PEST from aqueous-phase concentrations measured in a multilevel monitoring transect and from mass recovery rates measured at extraction wells during a controlled field experiment. Data-worth analyses, facilitated by PEST ancillary software, linked maximum aqueous-phase concentrations of all compounds to reductions in prior uncertainty of mass transfer coefficients. In turn, transient concentrations of the most soluble NAPL fraction constrained the source mass estimation. Accurately estimating the source mass and reducing prior uncertainties was possible by removing concentrations measured during early NAPL dissolution stages, identified as prior-data conflicts using the iterative ensemble smoother PESTPP-iES. Prior-based Monte Carlo analyses highlighted model limitations for representing sub-grid-scale heterogeneity of source zone architecture and NAPL dissolution, yet history-matching of final dissolution stages measured at multilevel ports eliminated parameter bias and produced long-term projections of source depletion with multistage behavior. Including mass discharge constraints further improved the accuracy of source mass estimation, complementing multilevel monitoring constraints on the source architecture and mass transfer coefficients

The Angstrom-Prescott (A-P) model is widely suggested for estimating solar radiation (Rs) in areas without measured or deficiency of data. The coefficients of this model must be locally calibrated, to calculate evapotranspiration (ET) correctly. The aim of this research was calibration and validation of the coefficients of the A-P model at six meteorological stations across arid and semi-arid regions of Iran. This model was improved by adding the air temperature and relative humidity terms. Besides, the coefficients (’a’ and ‘b’) of the A-P model and improved models was calibrated using some optimization algorithms including Harmony Search (HS) and Shuffled Complex Evolution (SCE). Performance indices, i.e., Root Mean Square Error (RMSE), Mean Bias Error (MBE), and coefficient of determination (R2) were used to analyze the models ability in estimating Rs. The results indicated that the performance of the A-P model had more precision and less error than improved models in all the stations. In addition, the best results were obtained for the A-P model with the SCE algorithm. The RMSE varies between 0.82 and 2.67 MJ m-2 day-1 for the A-P model with the SCE algorithm in the calibration phase. In the SCE algorithm, the values of RMSE had decreased about 4% and 7% for Mashhad and Kerman stations in the calibration phase compared to the HS algorithm, respectively. In other words, the highest decrease of RMSE is related to Kerman station.