A document by Hao Zhou. Click on the document to view its contents.

Changes in atmospheric pressure continuously ventilate soils and snowpacks. This physical process, known as pressure pumping, is a major factor in the exchange fluxes of H2O, CO2 and other trace gases between the soil and atmosphere. Thus models of pressure pumping are relevant to many areas of critical importance. This study compares the three principal models used to describe pressure pumping. Beginning with the fundamental physical principles and whether the flow field is compressible or incompressible, these models are categorized as linear parabolic (one model – compressible) or nonlinear hyperbolic (two models – incompressible). Using observed soil surface pressure data, measured vertical profiles of soil permeability and standard linear analysis and numerical methods, this study shows that nonlinear models produce advective velocities that are one to two orders of magnitude greater than those associated with the linear model. Incorporating soil temperature and moisture dynamics made very little difference to the linear model, but a significant difference in the nonlinear models suggesting that advective velocities induced by pressure changes associated with soil heating and moisture dynamics may not always be small enough to ignore. All numerical results are sensitive to the frequency of the pressure forcing, which was band-pass filtered into low, mid and high frequencies with the greatest model differences at low frequencies. Partitioning the pressure forcing and model responses helped to establish that mid-frequency weather-related phenomena (empirically identified as inertia gravity waves and solitons) are important drivers of gas exchange between the soil and the atmosphere.

Realistic representation of detailed rainfall characteristics on local scale by current state-of-the-art climate models remains a key challenge, especially on sub-daily timescales. In this research, the convection-permitting Weather Research and Forecasting (WRF) model configured with 1.5 km grid spacing is used to simulate precipitation on sub-daily timescales over the Yangtze River Delta Region of China for continuous 10 years (2005–2014). The simulations are compared to rain gauge observations, reanalysis data, and the simulations of a lower resolution WRF with 9 km grid spacing that has a parameterization of convection. The results show that precipitation over the region can be well captured by using the convection-permitting model (CPM). Furthermore, the intensity, duration and coverage of these precipitation events can be more accurately described by the CPM. On the convection timescales of 1–4 hours, especially for heavy rainfall events, the CPM is more accurate than the convection-parameterized model in capturing the short-duration events, which may be related to its better account of physical processes related with the convection on the convection-permitting scale. In addition, the extreme events which are more localized and with short-duration can be represented better by the CPM while the convection-parameterized model tends to produce widespread precipitation events covering more grid cells than observed. Biases of the simulation by the 9-km mesh convection-parameterized mode appear to be related to the deficiencies in the representation of convections.

A document by Pratik Shukla. Click on the document to view its contents.

Unsteady land-sea breezes (LSBs) resulting from time-varying surface thermal contrasts Δθ(t) are explored in the presence of a constant synoptic pressure forcing, Mg, when the latter is oriented from sea to land (α=0°), versus land to sea (α=180°). Large eddy simulations reveal the development of four distinctive regimes depending on the joint interaction between (Mg, α) and Δθ(t) in modulating the fine-scale dynamics. Time lags, computed as the shifts that maximize correlation coefficients of the dynamics between transient and the corresponding steady state scenarios at Δθ=Δθmax, are found to be significant and to extend 2 hours longer for α=0° compared to α=180°. These diurnal dynamics result in non-equilibrium flows that behave differently over the two patches for both α’s. Turbulence is found to be out of equilibrium with the mean flow, and the mean itself is found to be out of equilibrium with the thermal forcing. The sea surface heat flux is consistently more sensitive than its land counterpart to the time-varying external forcing Δθ(t), and more so for synoptic forcing from land-to-sea (α=180°). Hence, although the land reaches equilibrium faster, the sea patch is found to exert a stronger control on the final turbulence-mean flow equilibrium response. Finally, vertical velocity profile at the shore and shore-normal velocity transects at the first grid level are shown to encode the multiscale regimes of the LSBs evolution, and can thus be used to identify these regimes using k-means clustering.

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.

This study was conducted to examine, at the county level, the relationship between pediatric cancers incidence rate and atrazine and nitrate mean concentrations in surface and groundwater. A negative binomial regression analysis was performed to investigate the association between central nervous system (CNS) tumors, leukemia, lymphoma, and atrazine and nitrate mean concentrations in surface and groundwater. The age-adjusted brain and other CNS cancers incidence was higher than the national average in 63% of the Nebraska counties. After controlling for nitrate concentrations in surface and groundwater, counties with atrazine concentrations between 0.95 - 2.82 µg/L in both surface and groundwater had a higher incidence rate for pediatric cancers (brain and other CNS, leukemia, and lymphoma) compared to counties with surface and groundwater atrazine concentrations in the reference group (0.00 - 0.13 µg/L). Additionally, compared to counties with groundwater nitrate concentrations between 0 and 2 mg/L (reference group), counties with groundwater nitrate concentrations between 2.1 and 5 mg/L (group 2) had a higher incidence rate for pediatric brain and other CNS cancers (IRR=13.25; 95% CI: 13.00-13.50), leukemia (IRR=6.13; 95% CI: 6.02-6.26), and lymphoma (IRR=11.53; 95% CI: 11.32-11.75) after adjusting for all covariates in the model. While these findings do not indicate a causal relationship, they suggest that atrazine and nitrate may pose a significant risk relative to the genesis of pediatric brain and CNS cancers, leukemia, and lymphoma.

A document by Abdullah Alharthi. Click on the document to view its contents.

The opacity of clouds at Alert, Canada have been shown by measurements of their infrared irradiances to change with the day-to-day solar wind input to the global atmospheric electric circuit, as well as to the inputs of global thunderstorms and magnetic storms. These cloud changes appear to be the cause of surface pressure changes in the Arctic and Antarctic that have long been observed to correlate with the solar wind sector structure. We analyze large data sets of cloud irradiances and surface pressures, and find differences in the responses to 2, 4, or more sectors per 27-day solar rotation. There are seasonal variations, with sign reversal in the summer, which we interpret as due to changing geometry of solar insolation input. The correlation coefficients that were shown to be statistically significant at near the 95% confidence level for all-year, all sector types show further increases for just winter months and for just 2-sector intervals. The phase relationship of the pressure responses compared to those of the cloud responses are consistent but not understood. There are also interannual variations, whose cause has yet to be determined. A parameterization of the potential distribution near the magnetic poles and out through the high latitude ionospheric region affected by solar wind inputs has been made, giving correlations of IR irradiance and pressure with these parameterizations stronger than with those for the IMF B alone. The effects analyzed are an indication of more extensive influences of global atmospheric electricity on cloud microphysics and cloud development.

Global warming is causing more extreme precipitation events and variability in rainfall patterns, which are affecting the timing of peak rainfall occurrence and impacting the hydrological cycle in evolving climates. This study examines spatial rainfall trends across India during the Indian Summer Monsoon (ISM) period from 2001 to 2020, utilizing GSMaP_ISRO data. Analysis reveals a significant rise of 2 mm/day in rainfall over west central India from 2011 to 2020. Additionally, an investigation into the timing of peak rainfall demonstrates an early (late) peak over the Indo-Gangetic Plain (central India) in recent years, likely influenced by changes in aerosol loading. The present results suggest a significant shift in rainfall peak time with potential implications for agriculture,hydrology and disaster management.

Monsoon onset over the South China Sea occurs in April--May, marking the start of the wet season over East Asia. Nevertheless, skillful prediction of onset timing remains an open challenge. Recently, theoretical studies using idealized models have revealed feedbacks at work during the seasonal transitions of the Hadley cells, and have shown that these are relevant to monsoon onset over Asia. Here I hypothesize that monsoon onset occurs earlier in years when the atmosphere over the South China Sea is already in a state where these feedbacks are more easily triggered. I find that local anomalies in lower-level moist static energy in the preceding Jan--March are well correlated with South China Sea Monsoon onset timing. This relationship remains consistent on decadal timescales, while correlations with other teleconnections vary, and is used to develop a simple forecast model for onset timing that shows skill competitive with that of more complex models.

\sout\sout The sedimentary successions of several basins of Europe show evidence of widespread Late Jurassic aridification that is considered a long-standing conundrum in paleoclimate modeling. The distinctive feature of this event is that it appears concentrated in a discrete time interval between the Kimmeridgian (Late Jurassic) and the Berriasian (Early Cretaceous), and that it extended to eastern and southern-central Asia for a total of ~10Mkm2 in roughly the same time interval. Climate modeling has not provided a convincing explanation for this event. We compiled and reviewed paleomagnetic data from several continents including Adria, the African promontory, showing that this large-scale aridification was produced by an abrupt and transient southward migration of Eurasia towards arid tropical latitudes, while its demise coincided with a ‘retromotion’ to more humid northern latitudes in the Early Cretaceous. This movement is part of a global plate motion event, most likely due to True Polar Wander, that profoundly affected the depositional environments, the ecosystems, and the architecture of sedimentary basins worldwide.

We evaluated the performance of three global evapotranspiration (ET) models using the multiple sets of LAI and meteorological data from 1982 to 2017, and investigated the uncertainty in ET simulations from the model structure and forcing data. The three ET models were the Simple Terrestrial Hydrosphere model (SiTH), Priestly-Taylor Jet Propulsion Laboratory model (PT-JPL ) and MODIS ET algorithm (MOD16). Comparing the observed with simulated monthly ET by the three models over 43 Fluxnet sites, we found that SiTH overestimates ET for forests, but it performed better than the other two models over short vegetation. MOD16 and PT-JPL models performed well for forests, but poorly in dryland biomes. At the catchment scale, all models perform well expect over some tropical and high latitudinal catchments. At the global scale, SiTH highly overestimated ET in tropics, while PT-JPL underestimated ET between 30°N and 60°N and MOD16 underestimated ET between 15°S and 30°S. This study also revealed that the estimated ET by PT-JPL were largely influenced by the uncertainty in meteorological data, while the estimated ET by SiTH and MOD16 were relatively non-sensitive to the forcing data sets. In addition, the results suggested that the long-term variations in estimated ET trend were greatly influenced by the uncertainty in LAI data.

This study builds on Huntley and Ryan (2018) and related prior works on channels and estuaries by considering solutions for the same subtidal dynamics but with alternative integral flow constraints. Prior solutions do not have a truly two-dimensional (2D) flow field, as axial changes in the axial flow are implied. Three constraint types are considered: the Constant case with spatially constant density gradients constrained with section-integrated flow (as in prior works), Semi-Variable case with a constant axial density gradient and laterally variable lateral density gradient constrained with depth-integrated lateral flow, and Variable case with spatially variable density gradients in both directions constrained with depth-integrated axial and lateral flows. The Semi-Variable and Variable cases can produce solutions with truly 2D flow if the depth-integrated lateral flow is set to zero everywhere. Differences among solutions are illustrated with idealized and realistic applications from Huntley and Ryan (2018). For the idealized application, the Constant case and the Semi-Variable case with 2D flow have clear differences in axial velocity and stark contrasts in lateral flow (and density gradients). For the Nares Strait application, the Variable case with observed depth-averaged axial and lateral velocities is best able to represent the fastest observed down-channel velocities, the weak reversed flow on one side of the channel, and the observed lateral flow structure. Overall, selecting different integral constraints on flow conspicuously changes the subtidal flow, opens up new possibilities for truly 2D flow solutions, and provides additional flexibility for representing observed conditions in realistic situations.

Current state-of-the art procedures for studying modeled submesoscale oceanographic features have made a strong assumption of independence between features identified at different times. Therefore, all submesoscale eddies identified in a time series were studied in aggregate. Statistics from these methods are illuminating but oversample identified features and cannot determine the lifetime evolution of the transient submesoscale processes. To this end, the authors apply the Topological Feature Tracking (TFT) algorithm to the problem of identifying and tracking submesoscale eddies over time. TFT allows a user to identify submesoscale eddies as critical points on a set of time-ordered scalar fields and associate the points between consecutive timesteps. The procedure yields tracklets which represent spatio-temporal displacement of eddies. Thus the time-dependent behavior of submesoscale eddies can be studied. We analyze the submesoscale eddy dataset produced by TFT, which yields unique, time-varying statistics on this currently underexplored phenomenon.

Increased emissions of methane (CH4) have contributed to global temperature rise since pre-industrial times by 0.3-0.8C. Reducing these emissions is crucial to mitigate climate change. Various sources produce CH4 with distinguishable isotopic compositions, allowing CH4 source identification using CH4, δ13C and δ2H values. This study reports continuous measurements of CH4 mole fraction, δ13C and δ2H for eight months in Cluj-Napoca, Romania. An automated extraction and purification system, coupled to an isotope ratio mass spectrometer alternately measured δ13C and δ2H of CH4 with 20-minute time resolution at the campus of the Babe.s-Bolyai University. In addition, samples from the vicinity of the continuous measurement location were measured to isotopically characterise CH4 sources in the region.   The time series show a pronounced diurnal cycle, characterised by CH4 elevations during the night, occasionally superimposed on multi-day events. From these elevations, we identified three main CH4 emission categories: CH4 similar in isotopic composition to Transylvanian biogenic gas, biogenic emissions from rivers and wastewater, predominantly observed during the summer and a third source emitting δ13C-enriched CH4 in winter, likely of pyrogenic origin. Simulations with the FLEXPART-COSMO model underestimated the CH4 mole fractions in winter and with eastern wind (city centre), indicating that the emission inventory is not granular enough to represent the city centre. The strong underestimation in winter suggests that the emission inventory did not include the pyrogenic winter source. Despite this, when the model accurately estimated the CH4 mole fraction, it also predicted the isotopic compositions well.

Seepage boundary conditions are commonly used in groundwater simulations to allow groundwater to discharge at the upper surface of the model when groundwater head exceeds atmospheric pressure. However, the extent and transient behavior of the seepage zone is often unknown a priori and is difficult to predict. A mathematical description of the boundary condition is straightforward, such that head is equivalent to elevation only when groundwater flow indicates a seepage condition, which is a mixed conditional Dirichlet and Neumann boundary condition. This standard representation of the boundary condition has been successfully implemented and applied in a real-world context by most groundwater models. However, it is rarely reported that convergence is only guaranteed when both the efflux and zero pressure conditions are simultaneously satisfied, often requiring unnecessarily small timestep sizes, which results in low computational efficiency. This study suggests a continuous differentiable equation as an alternative to model the seepage boundary. The new formulation is derived by analogy to the first-order exchange equation, which is commonly used to represent the interactions between surface water and groundwater flow in integrated hydrologic simulations. The results of this study suggest that mixed Dirichlet and Neumann boundary conditions can be effectively converted into a Robin boundary condition, which is a head-dependent flux condition that incorporates appropriate physical considerations. This new approach has the potential to significantly improve the accuracy and efficiency of groundwater flow simulations and can help to advance the understanding of subsurface hydrology.

Path dependent corrections relative to traveltimes have been demonstrated to improve event locations. Using available global velocity models, direction-based station corrections can be estimated in a region without calibration data. In this study, traveltime corrections have been obtained for 117 broadband seismic stations around southern Thailand, Peninsular Malaysia, Singapore and Sumatra region of Indonesia. A total of 82,325 first-arrival waves are obtained from 15,212 earthquakes that have occurred around the Sumatra Subduction Zone over five decades (1964 – 2018). The dataset is a combination of arrival time data from the Bulletin of International Seismological Centre and waveforms from the Incorporated Research Institutions for Seismology. A newly developed algorithm for three-dimensional ray tracing is used to compute traveltimes and raypaths. The corrections are based on the IASP91/AK135 velocity models at four back-azimuthal directions. The estimated residuals in seconds (s) ranges from -2.15 to 2.25 s for stations distributed around southern Thailand and a range of -0.76 to 1.60 s for stations within Peninsular Malaysia. A range of 0.59 to 1.08 s for stations within Singapore and -1.52 to 2.46 s for stations distributed around Sumatra (in Indonesia). Station PSI in Sumatra Island recorded the highest number with 4877 arrivals. Stations LEM, KLM and KGM show consistent high residual values at all calculated angles and distances. The result of this study will support routine location of hypocentral parameters within the region. The scheme is being implemented for use in the forward computational process of seismic tomographic inversion in the study area.