Antarctic ice sheets play an important role in global sea-levels and climate changes. Snowmelt information with high spatial resolution on the surface of ice sheets is of great significance to the study of global climate change. Currently, the spatial resolution of snowmelt detection results based on low-frequency data from microwave radiometers is low, and accurate freeze-thaw changes cannot be obtained. The spatial resolution of Advanced Microwave Scanning Radiometer-2(AMSR-2)89GHz data is at least twice that of other microwave channels, but vulnerable to atmospheric water vapour. This paper proposes a method to detect snowmelt on the Antarctic ice sheet based on 89GHz data. First, according to the stable relationship of the polarization ratio(PR)of 89GHz and 36GHz data under clear, cloudless weather, the affected 89GHz data were selected. Then, the functional relationship between 36 GHz data and the unaffected 89 GHz data was obtained. Finally, the modified 89 GHz data were applied to snowmelt detection on the Antarctic ice sheet. The average detection accuracy of this method in six automatic weather stations was 91%, while the average detection accuracy of the cross-polarized gradient ratio algorithm(XPGR)was 74%. The experimental results show that the modified 89GHz data have a high accuracy in detecting snowmelt in Antarctic ice sheets.

Seismic time-lapse studies are generally concerned with variations in a specific target zone, situated inside an otherwise static medium. In seismic monitoring the entire reflection response at the surface needs to be remodeled for every change in the target zone. Ideally, however, only the response of the target zone is remodeled, which is then inserted into the stationary response of the surrounding medium. Such an insertion is relatively straightforward when solely primary reflections are considered, but more complicated when internal multiples are introduced. The data-driven Marchenko method retrieves the responses to virtual sources inside the subsurface, and fully accounts for all orders of multiple scattering. Wapenaar and Staring (2018), therefore, use the method to predict the reflection response at the Earth’s surface for different target-zone scenarios, from a single reflection response at the surface and a model of the changing target zone. This is achieved in two steps. First, the responses of the static overand underburden are resolved from the reflection response. Second, the newly modeled response from the target zone is inserted. While this methodology was originally only tested for laterally invariant media, we show how it can be extended for laterally inhomogeneous media. A 2D model is considered to compare the performance of the Marchenko-based replacement with a remodeled response of the entire medium. The results show that the method accurately captures the different arrivals in the reflection response, including the multiples, aside from minor differences in amplitude. We conclude that the method can be used to more efficiently model reflection responses of variable target zones, therefore, enabling more effective modeling for time-lapse monitoring.

A newly developed physics-based earthquake simulation algorithm was applied to a seismogenic model in the Central Apennines Region. This model was derived from the last version of the Database of the Individual Seismogenic Sources (DISS), from which 54 seismogenic faults have been recognized. This simulator allowed the compilation of a synthetic seismic catalog lasting 100,000 years, and containing more than 300,000 events of 4.0

An unusual event of three characteristically different plasma structures on a geomagnetically quiet night (Ap = 4) of 08 July 2018 has been investigated in this paper using an all-sky imager installed at Hanle, Leh Ladakh (32.7°N, 78.9°E; Mlat. ~24.1°N), India. These structures include a freshly generated electrified MSTID (EMSTID), ambiguous plasma depletions, and a northward propagating non-electrified MSTID. One of the most fascinating aspects of this event was the lack of mutual interaction between the three structures, even though they existed simultaneously and propagated in different directions. They individually underwent evolution, distortion, and dissipation separately. One of the structures was an EMSTID, which got generated within the imager’s field-of-view (FOV) and evolved with time. As time progressed, different strip-like structures travelled southwestward, merged with each other to form the EMSTID and disappeared later. The second structure was plasma depletions which appeared in the southeastern part of the FOV. They eventually merged into a single band. The merged band evolved with time, extended further northward, and dissipated later. Along with these, a very rare non-electrified MSTID structure with east-west aligned fronts was observed which propagated northward. Its fronts underwent distortion, became curved and dissipated. In this study, we have explored the role of electrodynamics and neutral dynamics behind the observed unique features of the three plasma structures.

Magnetosheath jets are localized high-dynamic pressure pulses originating at Earth’s bow shock and propagating earthward through the magnetosheath. Jets can influence magnetospheric dynamics upon impacting the magnetopause; however a significant fraction dissipate before reaching it. In this study we present a database of 13,096 jets observed by the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft from 2008–2018, spanning a solar cycle. Each jet is associated with upstream solar wind conditions from OMNI. We statistically examine how solar wind conditions control the likelihood of jets forming at the shock, and the conditions favorable for jets to propagate through the magnetosheath and reach the magnetopause. We see that, for each solar wind quantity, these two effects are separate, but when combined, we find that jets are nearly 12 times more likely to reach and potentially impact the magnetopause when the interplanetary magnetic field (IMF) is at a low cone angle, and approximately 5 times more likely during fast solar wind. Low IMF magnitude, high Alfvén Mach number, and low density approximately double the number of jets at the magnetopause, while plasma beta and dynamic pressure display no net effect. Due to the strong dependence on wind speed, we infer that jet impact rates may be solar cycle dependent as well as vary during solar wind transients. This is an important step towards forecasting the space weather effects of magnetosheath jets, as it allows for predictions of jet impact rates based on measurements of the upstream solar wind.

Every breath we take reminds us we require oxygen. Crucially, whilst there is wider research into the oceanic impact of climate change, including warming and acidification, and on oxygen content of oceans, there is very little research into the specific impact of acidification and related carbon dioxide changes on marine photosynthetic oxygen production. Oceans are underappreciated. Marine sources provide 40-70% of our oxygen. Many post-Cambrian explosion historic extinction events appear to be related to oxygen levels or anoxic ocean die-off. Were research to be commissioned, that provides clear evidence of risk to oceanic oxygen production and therefore atmospheric oxygen levels, the conclusions could be far-reaching, including identifying potential tipping points that may result in human extinction. The probability of an inadequate human response to risks is increased by; time lags of “many hundreds, if not thousands, of years” in ocean warming and in acidification; underestimation of the greater interdependence of marine ecosystems; the non-visibility of change, combined with lack of public comprehension that once major change ‘hysteresis’ has taken place, it may be impossible to reverse the ecological ‘regime change’. Importantly, in the current ‘Anthropocene’, net oxygen production from land sources is now limited due to fossil fuel use, as well as farming and logging practices, which recycle and or exploit reserves rather than sequestering net carbon. The health of net oceanic global oxygen production cannot be assumed from the presumed dominance of photosynthetic marine bacteria in ocean blooms as the impact of mixotrophs and anoxygenic bacteriochlorophyll photosynthetic bacteria is often not represented in related system modelling. Currently, most public focus is on global warming as reflected in weather and related consequences, which are not viewed as immediate threats to day-to-day life, living standards or indeed survival. In contrast, were research to bear out the possibilities of oxygen depletion or potential for an oxygen-related extinction risk, and particularly in relation to ocean acidification, the danger may be better understood leading to more cohesive public demand for action in finding alternative fuel sources.

Mapping high permeability sand occurrences in clayey till is fundamental for protecting the underlying drinking water resources. Crosshole ground penetrating radar (GPR) amplitude data have the potential to differentiate between sand and clay, and can provide 2D subsurface models with a decimeter-scale resolution. We develop a probabilistic straight-ray-based inversion scheme, where we account for the forward modeling error arising from choosing a straight-ray forward solver. The forward modeling error is described by a Gaussian probability distribution and included in the total noise model by addition of covariance models. Due to the linear formulation, we are able to decouple the inversion of traveltime and amplitude data and obtain results fast. We evaluate the approach through a synthetic study, where synthetic traveltime and amplitude data are inverted to obtain slowness and attenuation tomograms using several noise model scenarios. We find that accounting for the forward modeling error is fundamental to successfully obtain tomograms without artifacts. This is especially the case for inversion of amplitude data since the structure of the noise model for the forward modeling error is significantly different from the other data error models. Overall, inversion of field data confirms the results from the synthetic study; however, amplitude inversion performs slightly better than traveltime inversion. We are able to characterize a 0.4 - 0.6 m thick sand layer as well as internal variations in the clayey till matching observed geological information from borehole logs and excavation.

An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlight the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).

Farmers in the indigenous Andean community of Cañar, Ecuador rely on an abundant wet season each growing year and are concerned that their wet seasons are becoming less rainy. The normal seasonal rainfall pattern in this region, the Andes of southern Ecuador, is driven primarily by the seasonal migration of the Intertropical Convergence Zone (ITCZ). Existing scientific literature suggests that the ITCZ’s seasonal migration pattern could be affected by anthropogenic climate change, thereby impacting the seasonal precipitation in the region. This study explores the possibility that the ITCZ’s migration pattern has already changed, which would validate the concerns of the Cañari people. This is accomplished by tracking the movement of the ITCZ over the past few decades using Outgoing Longwave Radiation (OLR) data. No obvious trend in the seasonal mean position of the ITCZ has been detected. However, OLR maps indicate an abnormal ITCZ signature during strong warm phases of the El Niño-Southern Oscillation (ENSO), consistent with previous studies. The interannual variability in the region’s seasonal precipitation is also associated with varying phases of ENSO. An additional component of this study is the development of a statistical model using ENSO indices as input, among other atmospheric indices, to provide seasonal precipitation forecasts for the tropical Andean wet season each year. Besides ENSO, another potentially useful index for seasonal prediction is the phase of the Quasi-Biennial Oscillation, which has been linked to precipitation variability in the tropics. The seasonal forecasting model is expected to help Ecuadorian highland farmers decide which of their crops to plant each year, based on the water needs of each crop.

The Mansurov Effect is related to the interplanetary magnetic field (IMF) and its ability to modulate the global electric circuit, which is further hypothesized to impact the polar troposphere through cloud generation processes. In this paper we investigate the connection between IMF By-component and polar surface pressure by using daily ERA5 reanalysis for geopotential height since 1980. Previous studies have shown to produce a significant 27-day cyclic response during solar cycle 23. However, when appropriate statistical tests are applied, the correlation is not significant at the 95\% level. Our results also show that data from three other solar cycles, which have not been investigated before, produce similar cyclic responses as during solar cycle 23, but with seemingly random offset in the timing of the signal. We examine the origin of the cyclic pattern occurring in the super epoch/lead lag regression methods commonly used to support the Mansurov hypothesis in all recent papers, as well as other phenomena in this community. By generating random normally distributed noise with different levels of temporal autocorrelation, and using the real IMF By-index as forcing, we show that the methods applied to support the Mansurov hypothesis up to now, are highly susceptible, as cyclic patterns always occurs as artefacts of the methods. This, in addition to the lack of significance, suggests that there is no adequate evidence in support of the Mansurov Effect.

We develop an existing 1-D photochemistry model to include a comprehensive description of organic chemistry on Mars that includes the oxidation products of methane (CH$_4$) and ethane (C$_2$H$_6$), a longer-chain hydrocarbon that can be used to differentiate between abiotic and biotic surface releases of CH$_4$. We find that CH$_4$ is most volatile between 20–50 km during Mars’ northern summer, where the local atmospheric CH$_4$ lifetime lowers to 25–60 years. We study atmospheric formaldehyde (HCHO) and formic acid (HCOOH), as the two common oxidation products of CH$_4$ and C$_2$H$_6$, and acetaldehyde (CH$_3$CHO) and acetic acid (CH$_3$COOH) as unique products of C$_2$H$_6$. We focus our analysis of these gases at Mars’ aphelion and perihelion at latitudes between -30$^{\circ}$ and 30$^{\circ}$, altitudes from the surface to 70 km, and from a homogeonous initial condition of 50 pptv of CH$_4$ and C$_2$H$_6$. From this initial condition, CH$_4$ produces HCHO in a latitude-independent layered structure centred at 20–30 km at aphelion with column-averaged mixing ratios of 10$^{-4}$ pptv, and oxidation of C$_2$H$_6$ produces HCHO at 10$^{-2}$ pptv. Formic acid has an atmospheric lifetime spanning 1–10 sols below 10 km that shows little temporal or zonal variability, and is produced in comparable abundances (10$^{-5}$ pptv) by the oxidation of C$_2$H$_6$ and CH$_4$. We also find that oxidation of 50 pptv of C$_2$H$_6$ results in 10$^{-3}$ pptv of CH$_3$CHO and 10$^{-4}$ pptv of CH$_3$COOH. Subsequent UV photolysis of this CH$_3$CHO results in 10$^{-4}$ pptv of atmospheric CH$_4$, potentially representing a new atmospheric source of Martian CH$_4$.

Convective Quasi-Equilibrium (CQE) is often adopted as a useful closure assumption to summarize the effects of unresolved convection on large-scale thermodynamics, while existing efforts to observationally validate CQE largely rely on specific spatial domains or sites rather than the source of CQE constraints—deep convection. This study employs a Lagrangian framework to investigate leading temperature perturbation patterns near deep convection, of which the centers are located by use of an ensemble of satellite measurements. Temperature perturbations near deep convection with high peak precipitation are rapidly adjusted towards the CQE structure within the two hours centered on peak precipitation. The top 1% precipitating deep convection constrains the neighboring free-tropospheric leading perturbations up to 8 degrees. Notable CQE validity beyond a 1-degree radius is observed when peak precipitation exceeds the 95th percentile. These findings suggest that only a small fraction of deep convection with extreme precipitation shapes tropical free-tropospheric temperature patterns dominantly.

A document by 張澤宇. Click on the document to view its contents.

The Magnetic Pileup Boundary or Induced Magnetosphere Boundary (IMB) has been an enigma in Mars aeronomy. Previously dubbed the planetopause, magnetopause, ion-composition boundary, and protonopause, identification of this unique plasma region has been marked by difficulty. In this case study, we used data from the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission to identify IMB crossings and configurations during the month of September 2017 with a particular focus on the 10 September 2017 solar events. It was concluded that the ICME had no statistically significant impact on the IMB standoff locations. This study also investigated the effects of upstream dynamic pressure, thermal pressure from the magnetosheath, magnetic pressure from the Magnetic Pileup Region (MPR), thermal pressure associated with the ionosphere, and Extreme Ultraviolet (EUV) irradiance on the IMB during September 2017. We have found that during the 163 IMB crossings, magnetic pressure in the MPR and thermal pressure in the ionosphere had the largest influence on the IMB standoff distance.

Firstly, we re-tune an algorithm based on empirical orthogonal functions (EOF) for globally retrieving the chlorophyll a concentration (Chl-a) of phytoplankton functional types (PFTs) from multi-sensor merged ocean color (OC) products. The re-tuned algorithm, namely EOF-SST hybrid algorithm, is improved by: (i) using 30% more matchups between the updated global in situ pigment database and satellite remote sensing reflectance (Rrs) products, and (ii) including sea surface temperature (SST) as an additional input parameter. In addition to the Chl-a of the six PFTs (diatoms, haptophytes, dinoflagellates, green algae, prokaryotes and Prochlorococcus), the fractions of prokaryotes and Prochlorococcus Chl-a to total Chl-a (TChl-a), are also retrieved by the EOF-SST hybrid algorithm. Matchup data are further separated for low and high temperature regimes based on different PFT dependences on SST, to establish the SST-separated hybrid algorithms which further shows improved performance as compared to the EOF-SST hybrid algorithm. The per-pixel uncertainty of the retrieved TChl-a and PFT products is estimated by taking into account the uncertainties from both input data and model parameters through Monte Carlo simulations and analytical error propagation. The uncertainty assessment provided within this study sets the ground to extend the long-term continuous satellite observations of global PFT products by transferring the algorithm and its method to determine uncertainties to similar OC products until today. Satellite PFT uncertainty is also essential to evaluate and improve coupled ecosystem-ocean models which simulate PFTs, and furthermore can be used to directly improve these models via data assimilation.

Charge exchange between hot ions and cold neutral atoms is an important effect in ring current loss processes on magnetized planets. In this letter, we investigate the spatial distribution of charge exchange loss contributions to terrestrial ring current decay using data from the Van Allen Probes. These contributions were calculated by dividing local energetic neutral atom energy density escape rates by local ring current energy density decay rates. The results exhibit clear MLT and L dependence, with larger contributions observed nightside during the recovery phase of geomagnetic storms. The contribution of H+; peaked at L~4 during early recovery phases and was stronger at higher L shells during late recovery phases, while O+; decreased slightly with L shell. Possible explanations for this inhomogeneous distribution are also discussed. The asymmetric exospheric hydrogen density distribution may cause the inhomogeneous distribution in the MLT, while the L dependence may be related to the charge exchange cross-section and the ion energy flux. These results provide the first spatial distribution of charge exchange contributions, which is helpful for understanding local terrestrial ring current evolution.

The week 3-6 averaged winter North Atlantic Oscillation (NAO) predictive skill in a state-of-the-art coupled climate prediction system is attributed to two principle sources: upper and lower boundary conditions linked to the stratosphere and El Niño-Southern Oscillation (ENSO), respectively. A 20-member ensemble of 45-day reforecasts over 1999-2015 is utilized, together with uninitialized simulations with the atmospheric component of the prediction system forced with observed radiative forcing and lower boundary conditions. NAO forecast skill for lead times out to six weeks is higher following extreme stratospheric polar vortex conditions (weak and strong vortex events) compared to neutral states. Enhanced week 3-6 NAO predictive skill for weak vortex events results primarily from stratospheric downward coupling to the troposphere, while enhanced skill for strong vortex events can be partly attributed to lower boundary forcing related to the ENSO phenomenon. Implications for forecast system development and improvement are discussed.

The reservoirs play a crucial role in the development of civilization as they facilitate the storage of water for multiple purposes like hydroelectric power generation, flood control, irrigation, and drinking water etc. In order to effectively meet these multiple purposes, the knowledge of the inflow in the reservoir is essential. Apart from the historical data, future prediction of the inflows is also necessary especially in context of climate change. A two-step algorithm for the prediction of reservoir inflow to enable meticulous planning and execution of daily reservoir operation keeping the historical variation of inflow in account has been proposed. The developed algorithm takes into account the patterns in the historic inflow data using the time series analysis along with the variability in the climatic patterns using the different predictors in the machine learning model with a small error. The first step uses time series model, Auto Regressive Integrated Moving Average (ARIMA) method to forecast the monthly inflows, which are then used as the targets in the second step for the month-wise daily forecasting of the inflows using the two types of ensemble models, namely, averaging and boosting models in machine learning. The averaging ensemble models were found to perform better than the boosting ensemble models for maximum number of months. The yearly results show an error of less than 5% between actual and predicted values for all the test cases, showing the precision in the developed algorithm.