The vertical structure of the Kuroshio Extension (KE) is investigated using velocity measurements from a subsurface mooring array. Mode decomposition based on climatological Temperature/Salinity (T/S) data shows that the barotropic and first baroclinic normal modes dominate the vertical structure of the zonal flow in the KE. This structure is also well described by the leading mode of Empirical Orthogonal Functions (EOFs) that contains the first two vertical normal modes. Further analysis demonstrates that the projection coefficient of the mooring velocity onto the summed vertical mode could be well represented by the surface geostrophic velocity. Therefore, we propose a dynamic method that relates the surface geostrophic flow and the vertical structure of the zonal flow. The applicability of this method is verified with both reanalysis datasets and estimation from hydrographic data. The findings implicate that the KE transport can be well reproduced by surface geostrophic flow and climatological T/S data only.

Laterite is a red weathering crust developed with various rocks and Quaternary loose sediments as its parent material in the tropics and subtropics regions of the world, and it is also the most widely distributed Quaternary earthy accumulation in China. Since the 1930s, most researchers have believed that the fluvial reticulated laterite in southern China was influenced by the warm and humid climate of the Middle Pleistocene. In recent years, the remains of Paleolithic human activities are often found in the reticulated laterite of southern China. However, the study of laterite chronology is sporadic or there is no critical chronological analysis, which causes uncertainty in the identification and discussion of the ages of reticulated laterite and Paleolithic sites in South China. In this study, a paleolithic site found in fluvial reticulated laterite in South China was systematically tested by quartz optical luminescence dating and geomorphic process analysis. The results show that, (1) The T3 terrace, an archive of hominin activity in the study area, primarily formed between 56 and 11 ka. (2) Reticulated laterite cannot be used simply to determine the ages of the Paleolithic sites found in this stratum, and typical reticulated laterite cannot be used as a marker for climatic stratigraphy and chronostratigraphy. The fluvial reticulated laterite in the southern tropics, under suitable hydrothermal conditions, can form within tens of thousands of years or even within 10 ka. (3) Human activities can also lead to an inversion in the age of reticulated red soil.

The strength of Pacific Walker circulation (PWC) significantly affects the global weather patterns, the distribution of mean precipitation, and modulates the rate of global warming. Different indices have been used to assess the PWC strength. Evaluated on different datasets for various study periods, the indices show large discrepancies between the reported trends. In this study, we performed sensitivity analysis of 10 PWC indices and compared them over the 1951-2020 period using the ERA5 reanalyses. The time series of normalised indices generally agree on the annual-mean PWC strength. The highest correlations (exceeding r=0.9) are between the indices that describe closely linked physical processes. The trends of PWC strength are strongly affected by the choice of representative time period. For the commonly used 1981-2010 period, the trends show strengthening of the PWC. However, trends computed for longer period (i.e. 1951-2020) are mostly neutral, whereas the past two decades (2000-2020) display weakening of the PWC, although it is statistically not significant. The temporal evolution of trends suggests multidecadal variability of PWC strength with a period of about 35 years, implying a continued weakening of the PWC in the next decade.

On Jan. 15, 2022, the Hunga Tonga-Hunga Ha’apai (HT) eruption injected SO2 and water into the middle stratosphere. Shortly after the eruption, the water vapor anomaly moved northward toward and across the equator. This northward movement appears to be due to a Rossby wave forced by the excessive IR water vapor cooling. Following the early eruption stage, persistent mid-stratospheric water vapor and aerosol layers were mostly confined to Southern Hemisphere (SH) tropics (Eq. to 30°S). However, during the spring of 2022, the westerly phase of the tropical quasi-biennial oscillation (QBO) descended through the tropics. The HT water vapor and aerosol anomalies were observed to again split across the equator coincident with the descent of the QBO shear zone. This split occurred because of the enhanced meridional transport circulation associated with the QBO. Neither transport event can be reproduced using MERRA2 assimilated winds.

Pigmentary hematite carries important signals in paleomagnetic and paleoenvironmental studies. However, weak magnetism and the assumption that it has high magnetic coercivity prevents prevents routine identification of the size distribution of pigmentary hematite, especially for fine particle sizes. We present a strategy for estimating joint hematite particle volume and microcoercivity (f (V, Hk0)) distributions from low-temperature demagnetization curves and thermal fluctuation tomography (TFT) of pigmentary hematite in bulk samples of Triassic-Jurassic Inuyama red chert, Japan. The coercivity of the pigmentary hematite increases exponentially with decreasing temperature, following a modified Kneller’s law, where microcoercivity has a wide but approximately symmetric distribution in logarithmic space from ~1 tesla to tens of tesla. All of the red chert samples contain stable single domain (SSD) hematite with 35 - 160 nm diameter; a significant superparamagnetic (SP) hematite population with sizes down to several nanometers also occurs in Jurassic samples. The SP/SSD threshold size is estimated to be 8 - 18 nm in these samples. The fine particle size of the pigmentary hematite is evident in its low median unblocking temperature (194 °C to 529 °C) and, thus, this hematite may contribute to all four paleomagnetic components identified in published thermal magnetization studies of the Inuyama red chert. In this work, uniaxial anisotropy and magnetization switching via coherent rotation are assumed. Uniaxial anisotropy is often dominant in fine-grained hematite, although the dominant anisotropy type should be evaluated before using TFT. This approach is applicable to studies that require knowledge of coercivity and size distributions of hematite pigments.

The information on plasma pressures in the outer part of the inner magnetosphere is important for simulations of the inner magnetosphere and the better understanding of its dynamics. Based on 17-year observations from both CIS and RAPID instruments onboard the Cluster mission, we used machine- learning-based models to predict proton plasma pressures at energies from ~40eV to 4MeV in the outer part of the inner magnetosphere (L*=5-9). The location in the magnetosphere, and parameters of solar, solar wind, and geomagnetic activity from the OMNI database are used as predictors. We trained several different machine-learning-based models and compared their performances with observations. The results demonstrate that the Extra-Trees Regressor has the best predicting performance. The Spearman correlation between the observations and predictions by the model data is about 68%. The most important parameter for predicting proton pressures in our model is the L* value, which is related to the location. The most important predictor of solar and geomagnetic activity is the solar wind dynamic pressure. Based on the observations and predictions by our model, we find that no matter under quiet or disturbed geomagnetic conditions, both the dusk-dawn asymmetry at the dayside with higher pressures at the duskside and the day-night asymmetry with higher pressures at the nightside occur. Our results have direct practical applications, for instance, inputs for simulations of the inner magnetosphere or the reconstruction of the 3-D magnetospheric electric current system based on the magnetostatic equilibrium, and can also provide valuable guidance to the space weather forecast.

Attention is increasingly being turned towards an investigation of extreme hydrometeorological events within the context of land-atmosphere coupling in the wider hydrological cycle, particularly with respect to the identification of compound and seesaw events. To examine these events, accurate soil moisture data are essential. Here, soil moisture from three reanalysis products (ERA5-Land, BARRA and ERA5) are compared to station observations from 12 sites across New Zealand for an average timespan of 18 years. Soil moisture data from all three reanalyses were subsequently used to investigate land-atmosphere coupling with gridded (observational) precipitation and temperature. Finally, compound (co-occurrence of hot and dry) and seesaw (transitions from dry to wet) periods were identified and examined. No best performing reanalysis dataset for soil moisture is evident (min r = 0.78, max r = 0.80). All datasets successfully capture the seasonal and residual component of soil moisture, but not the observed soil moisture trends at each location. Strong coupling between soil moisture and temperature occurs across the predominately energy-limited regions of the lower North Island and entire South Island. Consequently, these regions reveal a high frequency of compound period occurrence and potential shifts in land states to a water limited phase during compound months. A series of seesaw events are also detected for the first time in New Zealand (terminating an average of 17% of droughts), with particularly high frequency of seesaw event occurrence detected in previously identified areas of atmospheric river (AR) activity, indicating the likely wider significance of ARs for drought termination.

The Moho is the interface between crust and mantle, and accurate location of the Moho is important for both resource exploration and deep earth condition and structural change investigations. The Parker-Oldenburg (P-O) method, is simple and efficient and thus has been extensively applied in the frequency domain and for Moho depth inversion. However, Moho fluctuation simulations using the P-O method are not reliable because of the lack of field geographic data constraints during the inversion process and excessively smoothing of data details caused by using a filter to correct the source data signals. To solve those problems, we propose an improved iteration P-O method with variable density, the iterative process is constrained by geological data in the inversion parameters, and the variable depth of the gravity interface is iterated using an equivalent form of upward continuation in the Fourier domain, which is more stable and convergent than downward continuation term in original P-O method. Synthetic experiments indicate that improved method has the better consistency among the simulations than original method, and our improved method has the smallest RMS of 0.59 km. In a real case, we employed the improved method to invert the Moho depth of the South China Sea, and the RMS between our Moho model and the seismological data is the smallest value of 3.87 km. The synthetic experiments and application of the model to the SCS further prove that our method is practical and efficient.

Groundwater recharge can be significantly influenced by the macropores, especially in fine structured soils. However, models considering macropores require a number of additional parameters which are difficult to determine by conventional methods. Thus, inverse modeling is often applied to estimate soil hydraulic and solute transport properties of the unsaturated zone. In this study, an efficient method for recharge prediction and parameter uncertainty quantification by coupling a dual-porosity model (DPM) to the null-space Monte Carlo (NSMC) algorithm was developed, and the impact of uncertainty in the key model parameters on groundwater recharge were analyzed. Recharge estimates were further compared to the one by tritium peak method. Results showed that the estimated recharge was much smaller than the one estimated from the tritium peak method, indicating the possible overestimation of recharge by conventional tritium peak method with piston flow model. Our study further demonstrated that the conventional practice of deriving single set of parameters through inverse modeling could result in biased recharge prediction, and that for the complex subsurface flow and transport models such as the DPM, NSMC method can provide a practical solution for predictive uncertainty analysis.

Optimization models for minimizing pollutant exposure from groundwater resources require time and resources that many communities might not have ready access to due to their economic conditions. In such cases, it might be useful to develop a “rule of thumb” approach for suggestions in case of uncertainties and inadequate means to address these uncertainties. Monte Carlo analysis was performed for a simplified groundwater system and the effects of extraction patterns, distance to pollution source, dispersivity, pollutant pulse period, pore water velocity and decay were examined for minimizing the high pollutant exposure risk from the extracted groundwater. Results indicate that, in a high uncertainty scenario, the best bet for minimizing the risk of high pollutant exposure would be to adopt a frequent extraction pattern and supply the water as a mixture of extractions from multiple wells spread over an area. These findings can be used as a “rule of thumb” wherever time and resources might be the limiting factors.

Previous studies on South China’s convective precipitation forecast focused on the effects of multi-scale dynamics and microphysics parameterizations. However, how the uncertainty in aerosol data might cause errors in quantitative precipitation forecast (QPF) has yet to be investigated. In this case study, we estimate the impact of aerosol uncertainties on the QPF for South China’s severe convection using convection-permitting simulations. The variability range of aerosol concentrations is estimated with past observation for the pre-summer months. Simulation results suggest that the rainfall pattern and intensity change notably when aerosol concentrations are varied. The simulation with low aerosol concentrations produces the most intense precipitation, approximately 50\% stronger than the high-concentration simulation. Decreasing aerosol hygroscopicity also increases precipitation intensity, especially in pristine clouds. The aerosol uncertainty changes alter the number of cloud condensation and ice nuclei, which modifies the altitude and amount of latent heating and thereby modulates convection.

Long-term atmospheric water vapor hydrogen (δ2H), oxygen (δ18O), and deuterium excess (d-excess) can provide unique insights into the land-atmosphere coupling processes. The in-situ measurements of atmospheric water vapor δ2H, δ18O, and d-excess were conducted above a reed wetland of Liaodong Bay (2019-2020). We found significant inter-annual variations in atmospheric water vapor isotopes between the two growing (May-September) seasons. The δ2H, δ18O, and d-excess of atmospheric water vapor exhibited different seasonal and diurnal cycles respect to the vertical (i.e., 1 m, 3 m, and 5 m) measurement heights, especially in 2019. The isotopic differences of atmospheric water vapor among vertical measurement heights were more evident in the daytime (8:00-20:00 LST) than at night (20:00-8:00 LST). Rainfall events had a direct impact on the diurnal patterns of water vapor isotopes, and the influences depended on rainfall intensities. However, only week correlations existed between water vapor isotopes and local meteorological factors (R2 = 0.01-0.16, P < 0.001), such as water vapor concentration (w), relative humidity (RH), and surface air temperature (Ta). Based on the back-air trajectory analyses, the spatial-temporal dynamics of atmospheric water vapor isotopes highly synchronized with monsoon activities. The dominant air masses in this region mainly arose from ocean sources, which contributed to 62.1 ± 12.2% (49.4-84.5%) of the total air moisture. High d-excess consistently followed the strong monsoon activities, suggesting predominating impacts of ocean air masses from the East Asian monsoon region. High-resolution measurements of atmospheric water vapor isotopes will improve our understanding of the hydrological cycles in coastal areas.

The present study focuses on quantifying the impact of the choice of spatio-temporal resolution and hydrology models on the projection of extreme flow and their link to the catchment size. We use two process-based distributed hydrology models forced with a large-ensemble regional climate model (50-member ClimEx dataset) over the 1990-2100 period at different spatio-temporal scales. The extreme summer-fall flow corresponding with each spatio-temporal resolution was extracted by pooling the members together and computing the empirical cumulative distribution function. The results show that by refining the time-step from daily to sub-daily, the summer-fall extreme flow projected over the future period exceeds that of the reference period for the small but not large catchments. By increasing the catchment size, the hydrology model’s contribution to the variability of extreme flow increases. Moreover, the choice of spatial resolution affects the extreme flow’s trend in terms of magnitude, significance, and direction. But no pattern regarding the catchment size and spatial discretization variations exists.

Floods are often disastrous due to underestimation of the magnitude of rare events. When the occurrence of floods follows a heavy-tailed distribution the chance of extreme events is sizable. However, identifying heavy-tailed flood behavior is challenging because of limited data records and the lack of physical support for currently used indices. We address these issues by deriving a new index of heavy-tailed flood behavior from a physically-based description of streamflow dynamics. The proposed index, which is embodied by the hydrograph recession exponent, enables inferring heavy-tailed flood behavior from daily flow records. We test the index in a large set of case studies across Germany. Results show its ability to identify cases with either heavy- or nonheavy-tailed flood behavior, and to evaluate the tail heaviness. Remarkably, the results are robust also for decreasing the lengths of data records. The new index thus allows for assessing flood hazards from commonly available data.

Estimating dissipation timeframes and contaminant mass discharge rates of dense non-aqueous phase liquids (DNAPLs) source zones is of key interest for environmental-management support. Upscaled mathematical modeling of DNAPL dissolution provides a practical approach for assimilating site characterization and downgradient monitoring data to constrain future system behavior. Yet significant uncertainties on predictions of source zone dissipation rates may arise from inadequate or inaccurate conceptual assumptions in parameterization designs. These implications were investigated through upscaled modeling, sensitivity, and uncertainty analyses of high-resolution flow-cell experiments. Sensitivity results emphasized the role of local groundwater velocity and source dimensions in mass transfer scaling by strongly influencing error with respect to DNAPL persistence and dissolution rates. Linear uncertainty analyses, facilitated by PEST ancillary software, demonstrated the worth of monitoring profiles for constraining DNAPL saturations and dispersive mass transfer rates, responsible for source zone longevity. Nonlinear analyses performed with the iterative ensemble smoother PESTPP-iES, facilitated the quantification of unbiased source dissipation uncertainties from DNAPL delineation data. Conversely, monitoring data assimilation without consideration of flow-field heterogeneity and saturation distribution along the flow path biased model predictions. Our analyses provided practical recommendations on upscaled model design to assimilate available site data and support remedial-decision making.

Volcanic seismicity provides essential insights into the behavior of an active volcano across multiple time scales. However, to understand how magma moves as an eruption evolves, better knowledge of the geometry and physical properties of the magma plumbing system is required. In this study, using full-wave ambient noise tomography, we image the 3-D crustal shear-wave velocity structure below GreatSitkin Volcano in the central Aleutian Arc. The new velocity model reveals two low-velocity anomalies, which correlate with the migration of volcanic seismicity. With a partial melt of up to about 30%, these low-velocity anomalies are characterized as mushy magma reservoirs. We propose a six-stage eruption cycle to explain the migration of seismicity and the alternating eruption of two reservoirs with different recharging histories. The findings in this study have broad implications for the dynamics of magma plumbing systems and the structural control of eruption behaviors.Published on GRL on 6/8/2023: https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2022GL102438

Atmospheric motion vectors (AMVs), known as cloud track winds, have positive impacts on global numerical weather forecasts (NWP). In this study, AMVs retrieved from Fengyun-2G and Fengyun-4A are compared in their data quality and impacts on the typhoon forecasts in order to investigate the differences between the first and second generation of the geostationary meteorological satellites of China. This report conducted data evaluation and assimilation-forecasting experiments on FY-2G and FY-4A atmospheric motion vector (AMVs), respectively. The results show that the AMVs data of FY-4A are of better quality than those of FY-2G and assimilating the AMVs of FY-2G and FY-4A have a neutral to slightly positive impacts on typhoon forecasts, which is quite encouraging for the operational use in the future.

Hyperspectral remote sensing is thought to be a useful technology for assessing the condition of inland waters. However, non-optically active water quality parameters are rarely explored in hyperspectral remote sensing applications, despite they are highly valued in the aquatic environment condition. This study intends to evaluate the performance of non-optically active water quality parameters using Zhuhai-1 hyperspectral imagery. Focusing on total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH3-N) and nitrate-nitrogen (NO3-N) in Taipu River, we constructed empirical models to evaluate the precision of water quality inversion from OHS by comparing with Sentinel-2, and determined the sensitive bands of different water quality parameters. The final results showed that the polynomial model based on OHS had the greatest potential in retrieving TN, TP and NH3-N concentration, and the R2 was 0.9678, 0.7924, 0.7682 respectively. The combination of R(510)/R(820) and R(700)/R(806), R(940)/R(820) and R(806)/R(926), R(709)/R(806) and R(746)/R(620) were most sensitive to TN, TP and NH3-N respectively. The OHS and Sentinel-2 both had potential in retrieving NO3-N. The R2 was 0.9791 from OHS and was 0.9513 from Sentinel-2. The sensitive bands of NO3-N were R(596)/R(665) and R(466)/R(580) from OHS, and Red Eage3/Blue and SWIR1/Blue from Sentinel-2. We also analyzed the drivers of the spatial distribution of water quality in Taipu River, the results showed negative impacts of farmland and urban land on water quality, and beneficial impacts of forest land on water quality. This study represented a promising step in hyperspectral remote sensing for retrieving inland non-optically active water quality parameters utilizing Zhuhai-1.