Warm sea surface temperature (SST) anomalies have been observed in the subtropical North Pacific around Hawaii in the recent decade, appearing from 2013. We examined the formation mechanisms of the warm SST anomalies in terms of relative contribution of atmospheric surface forcing and oceanic dynamics, using the latest reanalysis products from ECMWF (ERA5 for atmosphere and ORAS5 for ocean). Results of the mixed layer temperature budget diagnosis in the target area (10-20˚N and 180˚-160˚W) indicates that contributions from anomalous latent heat fluxes to the subtropical SST anomalies are dominant. Oceanic advective contributions are relatively small, dampen the SST anomalies, and are negatively correlated (r = –0.38) with the latent heat fluxes. For example, the +1.0K SST increased from 2011 to 2015 results from +1.5K contributions from sum of surface heat flux and –0.5K from meridional oceanic advection. The anti-correlation between atmospheric forcing and oceanic meridional advection reflects co-variations of wind-driven latent heat flux and meridional Ekman advection due to the weakening of the zonal component of the surface winds.

Transformation of light to dense waters by atmospheric cooling is key to the Atlantic Meridional Overturning in the Subpolar Gyre. Convection in the center of the Irminger Gyre determines the transformation of the densest waters east of Greenland. We present a 19-year (2002-2020) weekly time series of hydrography and convection in the central Irminger Sea based on (bi-)daily mooring profiles supplemented with Argo profiles. A 70-year annual time series of shipboard hydrography shows that this mooring period is representative of longer term variability. The depth of convection varies strongly from winter to winter (288-1500 dbar), with a mean March climatogical mixed layer depth of 470 dbar and a mean maximum density reached of 27.70 ± 0.05 kg m-3. The densification of the water column by local convection directly impacts the sea surface height in the center of the Irminger Gyre and thus large-scale circulation patterns. Both the observations and a Price-Weller-Pinkel (PWP) mixed layer model analysis show that the main cause of interannual variability in mixed layer depth is the strength of the winter atmospheric surface forcing. Its role is three times as important as that of the strength of the maximum stratification in the preceeding summer. Strong stratification as a result of a fresh surface anomaly similar to the one observed in 2010 can weaken convection by approximately 170 m on average, but changes in surface forcing will need to be taken into account as well when considering the evolution of Irminger Sea convection under climate change.

Dissolved rare earth elements (REE) and neodymium isotopic compositions (εNd) were intensively used to evaluate water mass mixing and lithogenic inputs in oceans. The South China Sea (SCS) is the largest marginal sea and a key region for reconstructing past hydrological changes in the West Pacific; however, its REE and εNd distribution are still not well established. This study investigated dissolved REE concentration and εNd distribution at four water stations in the northern and central SCS to better constrain the εNd distribution and REE cycle in the SCS. The results show relatively high concentrations of REE in surface seawater due to the terrigenous inputs. Seasonal variability in the middle REE enrichment is observed, suggesting a controlling role of the lateral mixing of water masses in the REE fractionation. The decreased REE concentrations in bottom water are mainly attributed to the re-suspended particle scavenging. Surface seawater εNd varies from -2.8±0.3 to -6.7±0.3, implying a significant modification due to riverine inputs. The intermediate water is characterized by a slightly negative εNd compared to the North Pacific Intermediate Water (NPIW) suggesting a vertical mixing between the intermediate and deep water within the SCS. εNd of deep water shows a narrow range from -3.4±0.3 to -4.2±0.3 (mean value of ~-3.8), supporting the presence of Pacific Deep Water (PDW) in the deep SCS basins nowadays. εNd of deep water in the SCS behaves conservatively along its pathway from the West Pacific to the SCS even though particle scavenging occurs in bottom water.

A global, sun-blocking catastrophe like nuclear war, an asteroid strike, or super volcano eruption spells disaster for most aspects of life as we know it. There have been many studies on how differing magnitudes of sun-blocking catastrophes would affect the global climate, and many mention the effects of this cold, dark climate on forests and cropping systems. However, few studies have solely focused on the effects of nuclear winter on forests in terms of food, resources, and decomposition. Forests already provide over a billion people with food and fuel for their livelihoods. In this review we connect how prehistoric catastrophes affected the world's forests to how a current day catastrophe may affect forest health, forest resource availability, and wood decomposition rates. We briefly discuss how forest resources may be used in this post-catastrophe climate for food and fuel in an energy and fuel depleted world. We use this information to make policy and education suggestions to prepare for future catastrophes, build resilience from smaller local disasters, prepare for the many effects of climate change, and discourage nuclear weapon stockpiling.

A new solution method is given for the general multiple collocation problem formulated in terms of the covariance equations. By a logarithmic transformation, the covariance equations reduce to ordinary linear equations that can be handled using standard methods. Solution by matrix inversion has the advantage that the analytical solutions can be reconstructed. The method can be applied to each determined or overdetermined subset of the covariance equations. It is demonstrated on quintuple collocations of ocean surface vectors winds obtained from buoys, three scatterometers and model forecasts, with representativeness errors estimated from differences in spatial variances. The results are in good agreement with those from quadruple collocation analyses reported elsewhere. The average of the solutions from all determined subsets of the covariance equations equals the least-squares solution of all equations. The standard deviation of all solutions from determined subsets agrees with the accuracy found in earlier triple and quadruple collocation studies, but the difference between minimum and maximum value is much larger. It is shown that this is caused by increased statistical noise in more complex solutions. The averages of the error covariances are close to zero, with a few exceptions that may point at small deficiencies in the underlying error model. Precise accuracy estimates are needed to decide to what extent statistical noise explains the spreading in the results and what is the role of deficiencies in the underlying error model.

Continental-scale river hydrodynamic modeling is useful for understanding the global hydrological cycle, and model evaluation is essential for robust calibration and assessing model performance. Although many models have been robustly evaluated using several variables separately, methods for the integrated multivariable evaluation of models have yet to be established. Here, we propose an evaluation method using the overall basin skill score (OSK), based on considering the spatial distribution of different variables via a sub-basin approach. The OSK approach integrates multiple variables to overcome observation-related limitations, such as the distinct temporal and spatial dimensions and unit of measurement unique to each variable, thus judging model performance objectively at the sub-basin and basin scales. As a case study, the global river model, CaMa-Flood, was evaluated using three variables¾discharge, water surface elevation, and flooded area¾for the Amazon Basin, focusing on the impact of using different types of baseline topography data (SRTM and MERIT digital elevation models [DEMs]). CaMa-Flood with the MERIT DEM performed robustly well over a wide range of river depth parameters with a maximum OSK of 0.51 against 0.46 for the SRTM DEM. Single-variable evaluation for all three variables proved inadequate due to low sensitivity for river bathymetry, with good performance outcomes potentially arising for the wrong reasons. This study confirmed that model evaluation using this method enables a balanced evaluation of different variables and a robust estimation of the best parameter set. The proposed method proved useful for flexible, integrated multivariable model evaluation, with modifications allowed per the user’s requirements.

The main objectives of the study were to examine the magnitude and rate of the current status of Accacian decurrens expansions, to identify the driving force of the local communities to shift, crops to tree plantation land use, to evaluate its economic benefits and its problems and opportunities for the sustainable future tree plant production in Fagita Lekoma district. ArcGIS 10.4 and ERDAS Imagine 2014 software was used for spatial analysis and land use classification. Landsat images were used to generate the land use maps by using the maximum likelihood algorithm of supervised classification. The results show that cultivated lands, grasslands, and wetlands are declining while forests and settlements are increasing. Forest cover was the most widespread land use, increasing by 210% during the study year. The conversion rate of forest land is 15.1%, which is the highest value in the general study period of the district. The rationale behind the expansion of forest land use is the introduction and spread of new species of trees known as Accacian decurrens plantations. Accacian decurrens forestation is the main cause of the change of use, system from arable land to forest system. These plantation-based land uses have been shown to be a way to increase economic benefits, employment opportunities and reduce soil erosion and increase soil fertility in the area.

Flow in the Earth’s mantle causes preferred orientation of crystals called Lattice/Crystal Preferred orientation (LPO or CPO). This preferred orientation is one of the main reasons why seismic anisotropy is observed. Seismic anisotropy observations could therefore be used to constrain the mantle flow in geodynamic models through tracking CPO evolution, and computing the resulting elastic tensor and the ansiotropy predicted at the surface. Even though there are many types of CPO models, only a few studies include CPO calculations due to the complexity and computational cost. Here we implemented an extended version of the CPO model D-Rex into the open source community geodynamics code ASPECT. We show that the implementation is correct, how to use it and that it is feasible and important to use in large 3D models. We also show that it is important to calculate CPO, especially for models focusing on plate boundary of smaller scale flow because the resulting elastic directions can greatly deviate from the flow direction. The added infrastructure will also allow for future enhancement, testing and even replacement of the CPO model.

Near-horizontal shore platforms display highly irregular plan shapes, but little is known about the way in which these irregularities influence the significant wave height (Hs) on the platforms and the frequency components of the nearshore wave field. We use a nonlinear Boussinesq wave model to conduct harmonic and bispectral mode decomposition analyses, studying the control of concave and convex platform edges over wind (WW: 0.125 - 0.33 Hz), swell (SW: 0.05 - 0.125 Hz) and infragravity (IG: 0.008 - 0.05 Hz) frequencies. For breaking and non-breaking waves, increasing the platform edge concavity intensified wave divergence and subsequent attenuation of SW and IG across the outer platforms, reducing by up to 25%. Increasing the platform edge convexity intensified focusing and amplification of SW and WW over the outer platforms, increasing by up to 18% and 55% for breaking and non-breaking waves. In the presence of breaking, IG amplification depended on the generation of wave divergence across the inner platform, a condition determined by a critical convex curvature threshold (Κ=1.8) balancing wave focusing from refraction and defocusing from breaking. We find that convex curvature can determine the relative dominance of WW, SW and IG across platforms. Alongshore, coherent wave interactions governed IG stationary patterns defined by a node near the platform centreline and two antinodes on either side of concave edges. A node was generated at the platform centreline, and two antinodes were observed on either side of the convex edges for Κ>1.8, with the opposite pattern observed for Κ<1.8.

The Ensemble Streamflow Prediction (ESP) framework combines a probabilistic forecast structure with process-based models for water supply predictions. However, process-based models require computationally intensive parameter estimation, increasing uncertainties and limiting usability. Motivated by the strong performance of deep learning models, we seek to assess whether the Long Short-Term Memory (LSTM) model can provide skillful forecasts and replace process-based models within the ESP framework. Given challenges in implicitly capturing snowpack dynamics within LSTMs for streamflow prediction, we also evaluated the added skill of explicitly incorporating snowpack information to improve hydrologic memory representation. LSTM-ESPs were evaluated under four different scenarios: one excluding snow and three including snow with varied snowpack representations. The LSTM models were trained using information from 664 GAGES-II basins during WY1983-2000. During a testing period, WY2001-2010, 80% of basins exhibited Nash-Sutcliffe Efficiency (NSE) above 0.5 with a median NSE of around 0.70, indicating satisfactory utility in simulating seasonal water supply. LSTM-ESP forecasts were then tested during WY2011-2020 over 76 western US basins with operational NRCS forecasts. A key finding is that in high snow regions, LSTM-ESP forecasts using simplified ablation assumptions performed worse than those excluding snow, highlighting that snow data do not consistently improve LSTM-ESP performance. However, LSTM-ESP forecasts that explicitly incorporated past years’ snow accumulation and ablation performed comparably to NRCS forecasts and better than forecasts excluding snow entirely. Overall, integrating deep learning within an ESP framework shows promise and highlights important considerations for including snowpack information in forecasting.

We have recently introduced a modification of the multiple signal classification (MUSIC) method for synthetic aperture radar. This method depends on a tunable, user-defined parameter, ε, that allows for quantitative high-resolution imaging. It requires however, relative large single-to-noise ratios (SNR) to work effectively. Here, we first identify the fundamental mechanism in that method that produces high-resolution images. Then we introduce a modification to Kirchhoff Migration (KM) that uses the same mechanism to produces tunable, high-resolution images. This modified KM method can be applied to low SNR measurements. We show simulation results that demonstrate the features of this method.

The Nansha Islands comprise the largest atoll archipelago in the South China Sea that accommodates 15% of global atolls. In contrast to the reef flats of the Indo-Pacific region that commonly have grown close to modern sea level, a considerable portion of the atoll rims here consists of reef flats as deep as 6-20 m. To better understand whether these deep reefs are relict features abandoned by sea-level rise or host to modern physical reworking, we conducted an 8.5-month mooring observation of hydrodynamics on the 12-m-deep southwest-facing reef flat of Tiexian reef. These measurements show a predominance of seasonal-varying strong waves and stable currents, in line with short-term observations at three other deep-reef-flats nearby. While the reef flat was protected from the northeast monsoon from January to May, the southwest monsoon from June to September resulted in prolonged exposure to large waves and more vigorous cross-flat currents (mean Hs of 1.3 m; orbital velocity 0.22 m/s), resulting in consistently large near-bed shear stresses (mean of 0.6 N/m2 on reef sediments and maximum of 18.9 N/m2 on coral reefs) that are capable of entraining sediment for almost the entire monsoon season. Assuming a mere ratio of 1-10% mobile sediment would result in rim height deflation on the order of 0.5-5 cm/y. Such values similar to potential rates of reef accretion imply that modern processes could play a significant role in the maintenance of the deep reef flats, which can be surprisingly active environments with living coral colonies and coral debris coverage.

North of the Denali Fault, the collision between the Yakutat block with North America is accommodated by a fold-thrust belt that gives rise to the northern Alaska Range foothills. At the western end of the belt, the Kantishna Hills anticline hosts prominent microseismicity and surface deformation, together interpreted as active folding of the Kantishna Hills anticline above a midcrustal detachment. Here, we test for such a detachment by using anisotropy-aware receiver functions to image fabric contrasts within the crust and comparing the depths of such contrasts to seismicity statistics. Seismic stations near the crest of the Kantishna Hills anticline and near its southern flank show a single strong contrast in dipping fabric at depths of 12 and 13 km, near where the microseismicity clusters at depth and consistent with a detachment plane beneath the fold. A minimum in b-value at 10-13 km depth is consistent with seismicity on the detachment, compatible with the imaged anisotropic contrast, while off-fault seismicity is shallower, deeper, and limited to smaller magnitudes. South-dipping imbricate thrusts in schist characterize the northern Alaska Range foothills structure and support our interpretation of the observed anisotropy as reflecting SSW-SSE-dipping foliation above a detachment at ~10-13 km depth that may exploit existing crustal weaknesses along more subtle fabric contrasts observed in the seismically quiescent region north of the actively deforming belt.

The RBSP and the Arase satellites have different inclinations and sometimes they fly both near the equator and off the equator on the same magnetic field line, simultaneously. Such conjunction events give us opportunities to compare the electron density at different latitudes. In this study, we analyzed the plasma waves observed by Arase and RBSP-A or B during the three conjunction events during and after the 7 Sep 2017 storm event. The electron number density at the satellite positions were estimated from frequencies of the UHR emissions obtained by the HFA/PWE onboard the Arase and the Waves instrument onboard RBSP, respectively. During the three conjunction events, the satellites passed through the plume, inner trough (the narrow region with low electron density between main body of the plasmasphere and the plume), plasmatrough with variable electron density, and partially-refilled plasmasphere. The power-law index m for the inner trough and plume was inferred to be 6~8 and ~0, respectively. This is interpreted to mean that the trough was close to collisionless and the plume was near diffusive equilibrium. In the plasmatrough with the varying density, both the high-density and low-density regions had m~0. The low-density portion of this region may have a different origin from the inner trough, because of the different m-indices. For the partially-refilled plasmasphere in the storm recovery phase, the power-law index m showed negative values, meaning that the density in the equatorial plane was higher than at higher latitudes.

Inter-variable dependencies are key properties to characterise many climate phenomena - such as compound events - and their future changes. Yet, climate simulations often have statistical biases. Hence, univariate (1dBC) and multivariate bias correction (MBC) methods are regularly applied. Inter-variable properties (e.g., correlations) can be altered by BC corrections. Then, it is necessary to assess how hypotheses of BC methods on climate change affect the adjustments. This can lead to better choices of BC methods. Here, we investigate whether an MBC method should try reproducing, preserving or modifying the changes in rank correlations between daily temperature and precipitation over Europe. An original “perfect model experiment” is set up and applied to two different climate simulation ensembles over 2001-2100: 40 runs from the CESM global climate model and 11 runs from the CMIP6 exercise. The results highlight that, within the multi-run single GCM ensemble (CESM), accounting for correlation changes bring valuable information for long-term projections but that a stationary hypothesis provides less biased correlations, up to medium-term projections (2060). For the multi-model ensemble (CMIP6), the non-stationary hypothesis provides larger biases than the stationary approach, up to the end of the century. Not correcting the model rank correlations (1dBC) provides the worst results. Whenever an ensemble is available, the best results come from accounting for the “robust’ part of the change signal (i.e., average change from different runs). This pleads for using ensembles and their robust information, in order to perform robust bias corrections.

Pool-riffle sediment and flow dynamics have been studied for many years, but there has been relatively little investigation on how field observations might be influenced by the variability of pool-riffle morphologies. In this letter we present a database of quantitative and qualitative measurements from sites where pool-riffle morphologies have been studied and apply two morphologic classifications that compare a) discharge and slope, and b) specific stream power and a representative coarse bed particle size. The classifications show that pool-riffles appear in different positions relative to mobility and morphologic transitions, which indicates that they occur within different flow and sediment regimes. Patterns in the distribution of studied pool-riffles show useful trends as well as an important diversity, the appreciation of which may help to clarify the importance of different flow and sediment transport phenomenon that underlie pool-riffle mechanics.

Meandering gravel-bed rivers tend to exhibit bed surface sorting patterns with coarse particles located in pools and fine particles on bar tops. The mechanism by which these patterns emerge has been explored in sand-bed reaches; however, for gravel-bed meandering channels it remains poorly understood. Here we present results from a flume experiment in which bed morphology, velocity, sediment sorting patterns, and bed load transport were intensively documented. The experimental channel is 1.35 meters wide, 15.2 meters long, and its centerline follows a sine-generated curve with a crossing angle of 20 degrees. Water and sediment input were held constant throughout the experiment and measurements were collected under quasi-equilibrium conditions. Boundary shear stress calculated from near-bed velocity measurements indicates that in a channel with mild sinuosity, deposition of fine particles on bars is a result of divergent shear stress at the inside bend of the channel, downstream of the apex. Boundary shear stress in the upstream half of the pool was below critical for coarse particles (>8 mm), leading to an armored pool. Inward directed selective transport was responsible for winnowing of fine particles in the pool. Fine and coarse sediment followed similar trajectories through the meander bend, which contrasts earlier studies of sand-bedded meanders where the loci of fine and coarse particles cross paths. This suggests a different sorting mechanism for gravel bends. This experiment shows that a complex interaction of quasi-equilibrium bed topography, selective sediment transport, and secondary currents are responsible for the sorting patterns seen in gravel-bed, meandering channels.

The Neoproterozoic tectonics of South China is crucial for understanding its evolution history throughout the assembly and disintegration of Rodinia. Herein, we employ integrally tectono-magmatic records over the period of ~1.0-0.6 Ga from the northern Yangtze block, combining with available geochemical and geological data, to investigate the secular tectonic evolution of the craton. Early Neoproterozoic intra-oceanic subduction may have initiated at ~1.0-0.9 Ga after a long-period of late Mesoproterozoic passive margin. A flare-up of magmatism at ~900 Ma attributed to continental arc magmatism that led to increased crustal reworking during episodes of arc compression and lithospheric thickening, and subsequently enhanced juvenile mantle input during the transition to extensional back-arc rift modes. The isotope–time pattern displays cyclic trends shifting towards less radiogenic values and then progression to more radiogenic, near-depleted mantle isotope compositions, indicating alternation regimes of contractional and extensional tectonics due to repeatedly slab advancing and rollback. The occurrence of volumetrically-large radiogenic isotope-depleted calc-alkaline rocks associations, low-δ18O and bimodal rocks along the Yangtze-block continental margin likely indicates rapid reworking of juvenile crust within a composite tectonic setting involving both arcs and rifts, which may maintain until the end of calc-alkaline arc magmatism at ~730-720 Ma and ultimately evolved into an anorogenic rifted passive margin setting, as revealed by the deposition of massive ~720-620 Ma syn-rift Yaolinghe-group volcanic-sedimentary sequence and intraplate-like magmatism. Collectively, prolonged (~1.0-0.7 Ga) suprasubduction-related magmatism traces accretion to the Yangtze-block margin, and thus likely indicates a paleogeographically peripheral position of South China in Rodinia.