Showing papers on "Longitude published in 2022"

An Observational Investigation of Spatiotemporally Contiguous Heatwaves in China From a 3D Perspective

Abstract: Understanding the evolution of heatwaves is important for their prediction, mitigation, and adaptation. While most studies focused on either their temporal variability at individual station (or grid point) or the spatial variation over fixed durations, their daily joint evolution over space and time remains largely unexplored. Here, we investigate multi-dimensional characteristics of spatiotemporally contiguous heatwaves across China during 1961–2018 using observational data from a 3D perspective (i.e., latitude×longitude×time). Results obtained by the 3D identification show that large contiguous heatwaves in China exhibit distinct characteristics in different geographical locations and time periods. Heatwaves in northern areas prefer to move from west to east at a faster speed, persist longer, and have greater extent and intensity than southern heatwaves, which are generally originated from the east and move westward. It is also found that contiguous heatwaves are growing in frequency, magnitude, areal extent, duration, and traveling distance across China.

A Machine-Learning Approach for Prediction of Water Contamination Using Latitude, Longitude, and Elevation

Abstract: One of the significant issues that the world has faced in recent decades has been the estimation of water quality and location where safe drinking water is available. Due to the unexpected nature of the mode of water contamination, it is not easy to analyze the quality and maintain it. Some machine-learning techniques are used for predicting contaminating factors but there is no technique that can predict the contamination using latitude, longitude, and elevation. The main aim of this paper is to put factors such as water body location and elevation, which are used as inputs, into the different machine-learning techniques that predict the contamination. The results are reviewed and analyzed according to groundwater contamination and the chemical composition of the groundwater location. Non-changeable factors such as latitude, longitude, and elevation are used to predict pH, temperature, turbidity, dissolved oxygen hardness, chlorides, alkalinity, and chemical oxygen demand. Such a study has not been conducted in the past where location-based factors are used to predict the water contamination of any area. This research focuses on creating a relationship between the location base factors affecting the water contamination in a given area.

The Rhine River basin

Abstract: The British Isles, comprising the United Kingdom (Scotland, England, Wales, and Northern Ireland) and the Republic of Ireland, lies at the northwest Atlantic seaboard of Europe. The latitude and longitude ranges from around 50°N to 61°N and 2°E to 11°W. As the landmasses of mainland Britain and the island of Ireland are small, the sea is always close, and the rivers are small in comparison with continental Europe. Despite this, the area has marked differences in climate, geology, and population densities that result in a diverse range of rivers with distinctive physical, chemical, and ecological characteristics and varying degrees of human impact.

Seasonal Variation of Thermospheric Composition Observed by NASA GOLD

Abstract: We examine characteristics of the seasonal variation of thermospheric composition using column number density ratio ∑O/N2 observed by the NASA Global Observations of Limb and Disk (GOLD) mission from low-mid to mid-high latitudes. We also use ∑O/N2 derived from the Global Ultraviolet Imager (GUVI) limb measurements onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite and estimated by the NRLMSISE-00 empirical model to aid our investigation. We found that the ∑O/N2 seasonal variation is hemispherically asymmetric: in the southern hemisphere, it exhibits the well-known annual and semiannual pattern, with highs near the equinoxes, and primary and secondary lows near the solstices. In the northern hemisphere, it is dominated by an annual variation, with a minor semiannual component with the highs shifting toward the wintertime. We also found that the durations of the December and June solstice seasons in terms of ∑O/N2 are highly variable with longitude. Our hypothesis is that ion-neutral collisional heating in the equatorial ionization anomaly region, ion drag, and auroral Joule heating play substantial roles in this longitudinal dependency. Finally, the rate of change in ∑O/N2 from one solstice season to the other is dependent on latitude, with more dramatic changes at higher latitudes.

The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy

Abstract: Abstract. The dependence of rainfall on elevation has frequently been documented in the scientific literature and may be relevant in Italy, due to the high degree of geographical and morphological heterogeneity of the country. However, a detailed analysis of the spatial variability of short-duration annual maximum rainfall depths and their connection to the landforms does not exist. Using a new, comprehensive and position-corrected rainfall extreme dataset (I2-RED, the Improved Italian-Rainfall Extreme Dataset), we present a systematic study of the relationship between geomorphological forms and the average annual maxima (index rainfall) across the whole of Italy. We first investigated the dependence of sub-daily rainfall depths on elevation and other landscape indices through univariate and multivariate linear regressions. The results of the national-scale regression analysis did not confirm the assumption of elevation being the sole driver of the variability of the index rainfall. The inclusion of longitude, latitude, distance from the coastline, morphological obstructions and mean annual rainfall contributes to the explanation of a larger percentage of the variance, even though this was in different ways for different durations (1 to 24 h). After analyzing the spatial variability of the regression residuals, we repeated the analysis on geomorphological subdivisions of Italy. Comparing the results of the best multivariate regression models with univariate regressions applied to small areas, deriving from morphological subdivisions, we found that “local” rainfall–topography relationships outperformed the country-wide multiple regressions, offered a uniform error spatial distribution and allowed the effect of morphology on rainfall extremes to be better reproduced.

Hemispherically Asymmetric Evolution of Nighttime Ionospheric Equatorial Ionization Anomaly in the American Longitude Sector

Abstract: The Global-scale Observation of Limb and Disk (GOLD) mission observed distinct post-sunset, hemispherically asymmetric evolution of the equatorial ionization anomaly between 40° and 50°W on 19 November 2018, with the southern crest shifting poleward but the northern crest remaining in the same latitude region. The Whole Atmosphere Community Climate Model-eXtended captured this phenomenon. Diagnostic analysis revealed that this asymmetric evolution was due to the hemispheric asymmetry in plasma transport by E × B drifts and neutral winds. In the Northern hemisphere, northward neutral wind transport dominated around sunset (20 UT near 45°W), causing the crest to be at lower altitudes and decay faster. After pre-reversal enhancement (PRE) occurred at 20 UT in the northern hemisphere, E × B and neutral wind transport largely balanced each other, and the crest remained in the same latitude region. In the southern hemisphere EIA crest, PRE occurred around 1 hr later than the one in the north. The northward neutral wind transported the plasma to higher altitudes with less recombination. E × B transport augmented the neutral wind transport after 21 UT, lifting and pushing the crest poleward. The magnetic field configuration (large declination) and the resultant occurrence time difference in PRE between 40°W and 50°W not only play critical roles in the asymmetric evolution of the two crests, but also makes it possible for this phenomenon to be observed in the GOLD field-of-view.

Unseasonal super ionospheric bubble and scintillations seeded by the 2022 Tonga Volcano Eruption related perturbations

Abstract: The Hunga-Tonga volcano eruption at 04:14:45 UT on 15 January 2022 produced various waves propagating globally, disturbing the background atmosphere and ionosphere. Coinciding with the arrival of perturbation waves, several equatorial plasma bubbles (EPBs) were consecutively generated at post-sunset hours over the East/Southeast Asian region, with the largest extension to middle latitudes. These EPBs caused intense L-band amplitude scintillations at middle-to-low latitudes, with signal fading depths up to ~16 dB. Considering the very rare occurrence of EPBs during this season in East/Southeast Asian sector and the significantly modulated background ionosphere, we believe that the perturbation waves launched by the volcano eruption triggered the generation of unseasonal super EPBs. The ionospheric perturbations linked with the 2022 Tonga volcano eruption propagated coincidently through the East/Southeast Asia longitude sector near sunset, modulated the equatorial F region bottomside plasma density and acted as the seeding source for the generation of unseasonal super bubbles. Our results implicate that volcano eruption could indirectly affect the satellite communication links in the region more than ten thousand kilometers away.

Survey of Orion Disks with ALMA (SODA). I. Cloud-level demographics of 873 protoplanetary disks

Abstract: Context. Surveys of protoplanetary disks in nearby star-forming regions (SFRs) have provided important information on their demo- graphics. However, due to their sample sizes, these surveys cannot be used to study how disk properties vary with the environment. Aims. We conduct a survey of the unresolved millimeter continuum emission of 873 protoplanetary disks identified by Spitzer in the L1641 and L1647 regions of the Orion A cloud. This is the largest such survey yet, allowing us to identify even weak trends in the median disk mass as a function of position in the cloud and cluster membership. The sample detection rates and median masses are also compared to those of nearby ( < 300pc) SFRs. Methods. The sample was observed with the Atacama Large Millimeter / submillimeter Array (ALMA) at 225GHz, with a median rms of 0 . 08mJybeam − 1 , or 1 . 5M ⊕ . The data were reduced and imaged using an innovative parallel data processing approach. Results. We detected 58% (502 / 873) of the observed disks. This includes 20 disks with dust masses > 100M ⊕ , and two objects associated with extended dust emission. By fitting a log-normal distribution to the data, we infer a median disk dust mass in the full sample of 2 . 2 + 0 . 2 − 0 . 2 M ⊕ . In L1641 and L1647, median dust masses are 2 . 1 + 0 . 2 − 0 . 2 M ⊕ and 2 . 6 + 0 . 4 − 0 . 5 M ⊕ , respectively. Conclusions. The disk mass distribution of the full sample is similar to that of nearby low-mass SFRs at similar ages of 1 − 3Myr. We find only weak trends in disk (dust) masses with galactic longitude and between the Young Stellar Object (YSO) clusters identified in the sample, with median masses varying by (cid:46) 50%. Di ff erences in age may explain the median disk mass variations in our subsamples. Apart from this, disk masses are essentially constant at scales of ∼ 100pc. This also suggests that the majority of disks, even in di ff erent SFRs, are formed with similar initial masses and evolve at similar rates, assuming no external irradiation, with disk mass loss rates of ∼ 10 − 8 M (cid:12) yr − 1 .

Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data

Abstract: China has a great wealth of lake resources over a great spatial extent and these lakes are highly sensitive to climate changes through their heat and water budgets. However, little is known about the changes in lake surface water temperature (LSWT) across China under the climate warming conditions over the past few decades. In this study, MODIS land surface temperature (LST) data were used to examine the spatial and temporal (diurnal, intra-annual, and inter-annual) variations in LSWT of China's lakes during 2001-2016. Our results indicated that 169 large lakes included in the study exhibited an overall increasing trend in LSWT, with an average rate of 0.26 °C/decade. The increasing rate of nighttime LSWT is 0.31 °C/decade, faster than that of daytime temperature (0.21 °C/decade). Overall, 121 (71.6%) lakes showed an increase in daytime temperature with a mean rate of 0.38 °C/decade, while the rest 48 (28.4%) lakes decreased in temperature with a mean rate of - 0.21 °C/decade. We also quantitatively analyzed the relationship of the lake surface temperature and diurnal temperature differences (DTDs) with geographical location, topography, and lake morphometry by utilizing multivariate regression analysis. Our analysis suggested that the geographical location (latitude and longitude) and topography (altitude) were primary driving factors in explaining the national lake water temperature variation (P < 0.001), which were also mediated by morphometric factors such as lake surface area and volume. Moreover, the diurnal lake temperature variations were significantly correlated with altitude, latitude, and lake surface area (R2 = 0.426, P < 0.001). Correlation analyses of LSWT trend and air temperature trend for each lake indicated that LSWT was positively correlated with air temperature in both daytime and nighttime for most lakes.

Regional Ionospheric Corrections for High Accuracy GNSS Positioning

Abstract: Centimetre-level accurate ionospheric corrections are required for a high accuracy and rapid convergence of Precise Point Positioning (PPP) GNSS positioning solutions. This research aims to evaluate the accuracy of a local/regional ionospheric delay model using a linear interpolation method across Australia. The accuracy of the ionospheric corrections is assessed as a function of both different latitudinal regions and the number and spatial density of GNSS Continuously Operating Reference Stations (CORSs). Our research shows that, for a local region of 5° latitude ×10° longitude in mid-latitude regions of Australia (~30° to 40° S) with approximately 15 CORS stations, ionospheric corrections with an accuracy of 5 cm can be obtained. In Victoria and New South Wales, where dense CORS networks exist (nominal spacing of ~100 km), the average ionospheric corrections accuracy can reach 2 cm. For sparse networks (nominal spacing of >200 km) at lower latitudes, the average accuracy of the ionospheric corrections is within the range of 8 to 15 cm; significant variations in the ionospheric errors of some specific satellite observations during certain periods were also found. In some regions such as Central Australia, where there are a limited number of CORSs, this model was impossible to use. On average, centimetre-level accurate ionospheric corrections can be achieved if there are sufficiently dense (i.e., nominal spacing of approximately 200 km) GNSS CORS networks in the region of interest. Based on the current availability of GNSS stations across Australia, we propose a set of 15 regions of different ionospheric delay accuracies with extents of 5° latitude ×10° longitude covering continental Australia.

Spatial distribution of meteorological factors controlling stable isotopes in precipitation in Northern Chile

Abstract: • The meteorological variables are correlated with altitude, latitude and longitude. • Temperature, altitude, latitude and longitude control the δ 18 O of precipitation. • Unrecorded rainfall in sampling points is obtained by means of correlation models. • These models are useful if the available data are scarce and discontinuous in time. • Aquifer recharge zones are identified by estimating δ 18 O values with these models. A knowledge of the evolution of isotopic composition of air masses humidity and precipitation in the Western Cordilleras of the Central Andes is still incomplete. This study contributes to a better understanding of the factors that control the δ 18 O and δ 2 H contents in precipitation water in the north of Chile, above 2000 m a.s.l.. This paper deals with: (1) the relevant effects and processes that control the spatial (longitude, latitude and altitude) distribution of stable isotope contents of precipitation events in northern Chile, (2) the influence of local meteorological variables: temperature, precipitation and relative humidity on the δ 18 O and δ 2 H of precipitation, and (3) the estimation of these meteorological and isotopic variables at specific sites. To achieve these objectives, the relationships between geospatial and meteorological values are identified and analysed, followed by the estimation with empirical models. These estimation models (linear and non-linear) are obtained after examining, validating and calibrating techniques to find the best fit. This results in models for temperature, relative humidity and precipitation for each month of the year. In the same way, three isotopic models are derived from the spatial and meteorological variables (summer, winter and annual). Temperature has been shown to be controlled to a greater extent by altitude and latitude, while relative humidity is by latitude and precipitation in summer is by altitude and latitude. Monthly meteorological variables have been estimated throughout the study area. Precipitation δ 18 O and δ 2 H are controlled mainly by temperature and altitude and to a lesser extent by latitude, longitude and precipitation. In the same way, three isotopic models are derived from the spatial and meteorological variables: summer, winter and annual. This opens a new perspective of precipitation and its isotopic contents, but also allows the calculation of runoff and aquifer recharge and the path for linking future precipitation and aquifer recharge through their isotopic composition.

Ensemble Simulations of the 2012 July 12 Coronal Mass Ejection with the Constant-turn Flux Rope Model

Abstract: Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 2012 July 12 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in post-eruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hr. We further estimate the average subjective uncertainties in the GCS fittings by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5.°74, 11.°23, 24.°71, and 11.4%, respectively. Using these, we have created 77 ensemble members for the 2012 July 12 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hr for the 2012 July 12 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 2012 July 12 CME, whereas the uncertainties in longitude and tilt can introduce relatively large spread in the magnetic field predicted at Earth.

Geologic Context of the OSIRIS-REx Sample Site from High-resolution Topography and Imaging

Abstract: Abstract The OSIRIS-REx spacecraft collected a surface sample from Hokioi crater (55.8° N, 42.3° E; diameter ∼20 m) on the asteroid Bennu in 2020 October. We explore the geology of the sample collection site, known as Nightingale, by using digital terrain models, relative albedo maps, and images collected by the OSIRIS-REx spacecraft. Hokioi crater sits at the northwest edge of an older, larger (120 m diameter) crater between two north–south ridges respectively located at roughly 0° and 90° longitude, between which unconsolidated material generally migrates from the geopotential high at the north (+ Z ) pole to the geopotential low at the equator. The impact that formed Hokioi crater exposed relatively unweathered, fine-grained dark material that we observe within and ejected beyond the crater. The regional slope and steep crater walls to the north of the Nightingale site have enabled a mix of the dark debris and brighter material (which may include carbonates and/or exogenic basalts) surrounding Hokioi crater to migrate onto the crater floor, where the sample was collected; some of this material may be old ejecta excavated from up to 10 m depth when the 120 m diameter crater formed. We therefore expect the OSIRIS-REx sample to include materials of varying brightnesses, compositions, and exposure ages, derived primarily from the 0°–90° longitude quadrant and from as deep as 10 m. The sample may also include material derived from the impactor that formed Hokioi crater. We expect it to have low cohesion (≪0.6 Pa) and a friction angle between 32° and 39°.

Earthquake Early Warning System Using Ncheck and Hard-Shared Orthogonal Multitarget Regression on Deep Learning

Abstract: Realizing an effective earthquake early warning system (EEWS) in the case of extensive regions and noisy signals is challenging, particularly in East Java, Indonesia. This letter proposes the rapid detection of the p-wave arrival and determination of the earthquake’s hypocenter and magnitude using deep learning. The Ncheck algorithm is used for noise handling for picking the p-arrival on a multistation waveform as a form of picking target window prediction (PTWP). Then, multitarget regression (MTR) with a hard-shared orthogonal optimization model is proposed for earthquake parameter determination. The data sets used contained data of earthquakes recorded at three stations from the Indonesian seismic network in East Java; 2009–2017 data were used for training and validation, and 2019 data were used for real-time testing. The results show that the PTWP for picking p-arrival has a mean absolute error (MAE) of 0.12 s, and the MTR for earthquake magnitude, longitude, latitude, depth, and origin time detection shows MAEs of 0.21 M, 9.44, 18.72, 27.81 km, and 2.78 s, respectively.

Estimating the Near-Ground PM2.5 Concentration over China Based on the CapsNet Model during 2018-2020

Abstract: Fine particulate matter (PM2.5) threatens human health and the natural environment. Estimating the near-ground PM2.5 concentrations accurately is of great significance in air quality research. Statistical and deep-learning models are widely used for estimating PM2.5 concentration based on remotely sensed aerosol optical depth (AOD) products. Deep-learning models can effectively express the nonlinear relationship between AOD, parameters, and PM2.5. This study proposed a capsule network model (CapsNet) to address the spatial differences in PM2.5 concentration distribution by introducing a capsule structure and dynamic routing algorithm for the first time, which integrates AOD, surface PM2.5 measurements, and auxiliary variables (e.g., normalized difference vegetation index (NDVI) and meteorological parameters). Moreover, we examined the longitude and latitude of pixels as input parameters to reflect spatial location information, and the results showed that the introduction of longitude (LON) and latitude (LAT) parameters improved the model fitting accuracy. The coefficient of determination (R2) increased by 0.05 ± 0.01, and the root mean square error (RMSE), mean relative error (MRE), and mean absolute error (MAE) decreased by 3.30 ± 1.0 μg/m3, 8 ± 3%, and 1.40 ± 0.2 μg/m3, respectively. To verify the accuracy of our proposed CapsNet, the deep neural network (DNN) model was executed. The results indicated that the R2 values of the validation dataset using CapsNet improved by 4 ± 2%, and RMSE, MRE, and MAE decreased by 1.50 ± 0.4 μg/m3, ~5%, and 0.60 ± 0.2 μg/m3, respectively. Finally, the effects of seasons and spatial region on the fitting accuracy were examined separately from 2018 to 2020. With respect to seasons, the model performed more robustly in the cold season. In terms of spatial region, the R2 values exceeded 0.9 in the central-eastern region, while the accuracy was lower in the western and coastal regions. This study proposed the CapsNet model to estimate PM2.5 concentrations for the first time and achieved good accuracy, which could be used for the estimation of other air contaminants.

Patches of Magnetic Switchbacks and Their Origins

Abstract: Parker Solar Probe (PSP) has shown that the solar wind in the inner heliosphere is characterized by the quasi omnipresence of magnetic switchbacks (“switchback” hereinafter), local backward bends of magnetic field lines. Switchbacks also tend to come in patches, with a large-scale modulation that appears to have a spatial scale size comparable to supergranulation on the Sun. Here we inspect data from the first 10 encounters of PSP focusing on different time intervals when clear switchback patches were observed by PSP. We show that the switchbacks modulation, on a timescale of several hours, seems to be independent of whether PSP is near perihelion, when it rapidly traverses large swaths of longitude remaining at the same heliocentric distance, or near the radial-scan part of its orbit, when PSP hovers over the same longitude on the Sun while rapidly moving radially inwards or outwards. This implies that switchback patches must also have an intrinsically temporal modulation most probably originating at the Sun. Between two consecutive patches, the magnetic field is usually very quiescent with weak fluctuations. We compare various parameters between the quiescent intervals and the switchback intervals. The results show that the quiescent intervals are typically less Alfvénic than switchback intervals, and the magnetic power spectrum is usually shallower in quiescent intervals. We propose that the temporal modulation of switchback patches may be related to the “breathing” of emerging flux that appears in images as the formation of “bubbles” below prominences in the Hinode/SOT observations.

Longitudinally Modulated Dynamo Action in Simulated M-dwarf Stars

Abstract: M-dwarf stars are well known for the intense magnetic activity that many of them exhibit. In cool stars with near-surface convection zones, this magnetic activity is thought to be driven largely by the interplay of convection and the large-scale differential rotation and circulations it establishes. The highly nonlinear nature of these flows yields a fascinatingly sensitive and diverse parameter space, with a wide range of possible dynamics. We report here on a set of three global MHD simulations of rapidly rotating M2 (0.4 M ⊙) stars. Each of these three models established nests of vigorous convection that were highly modulated in longitude at low latitudes. Slight differences in their magnetic parameters led each model to disparate dynamo states, but the effect of the convective nest was a unifying feature. In each case, the action of longitudinally modulated convection led to localized (and in one case, global) reversals of the toroidal magnetic field, as well as the formation of an active longitude, with enhanced poloidal field amplitudes and flux emergence.

HRLT: a high-resolution (1 d, 1 km) and long-term (1961–2019) gridded dataset for surface temperature and precipitation across China

Abstract: Abstract. Accurate long-term temperature and precipitation estimates at high spatial and temporal resolutions are vital for a wide variety of climatological studies. We have produced a new, publicly available, daily, gridded maximum temperature, minimum temperature, and precipitation dataset for China with a high spatial resolution of 1 km that covers a long-term period (1961 to 2019). It has been named the HRLT, and the dataset is publicly available at https://doi.org/10.1594/PANGAEA.941329 (Qin and Zhang, 2022). In this study, the daily gridded data were interpolated using comprehensive statistical analyses, which included machine learning methods, the generalized additive model, and thin plate splines. It was based on the 0.5∘ × 0.5∘ gridded dataset from the China Meteorological Administration, together with covariates for elevation, aspect, slope, topographic wetness index, latitude, and longitude. The accuracy of the HRLT daily dataset was assessed using observation data from meteorological stations across China. The maximum and minimum temperature estimates were more accurate than the precipitation estimates. For maximum temperature, the mean absolute error (MAE), root mean square error (RMSE), Pearson's correlation coefficient (Cor), coefficient of determination after adjustment (R2), and Nash–Sutcliffe modeling efficiency (NSE) were 1.07 ∘C, 1.62 ∘C, 0.99, 0.98, and 0.98, respectively. For minimum temperature, the MAE, RMSE, Cor, R2, and NSE were 1.08 ∘C, 1.53 ∘C, 0.99, 0.99, and 0.99, respectively. For precipitation, the MAE, RMSE, Cor, R2, and NSE were 1.30 mm, 4.78 mm, 0.84, 0.71, and 0.70, respectively. The accuracy of the HRLT was compared to those of three other existing datasets, and its accuracy was either greater than the others, especially for precipitation, or comparable in accuracy, but with higher spatial resolution or over a longer time period. In summary, the HRLT dataset, which has a high spatial resolution, covers a longer period of time and has reliable accuracy.

A voxel-based three-dimensional framework for flash drought identification in space and time

Abstract: Flash drought (FD) is an extreme event causing severe impacts on ecosystems and agriculture due to its fast velocity of evolution and high frequency. Here, we develop a voxel-based three-dimensional FD (V3DFD) method to track the spatio-temporal dynamics of FD based on the soil moisture (SM) decline method proposed by Yuan et al. (2019). The key idea of V3DFD is that FD is identified in terms of the connectivity of drought voxels (i.e., cubes with width, length and height representing latitude, longitude and time, respectively) in 3D space instead of directly forming the drought events by merging drought clusters. The V3DFD is systematically evaluated and compared with the commonly used 3D severity-area-duration (SAD) method in four provinces in China: Guangdong (GD), Guangxi (GX), Guizhou (GZ), and Yunnan (YN). Results show that V3DFD can better reflect the dynamic development and recovery of FD events compared with SAD. Regional analyses indicate that FD occurs more frequent with a larger intensity and longer duration in GD and GX than YN and GZ. The onset (terminal) of FD in YN occurs mostly in April-May (April-June). The onset of FD in GX and GD is scattered at the intra-annual scale, but the terminal occurs mostly in November. In addition, the first FD event in a year is mostly located during April-May in YN and GZ, while the last FD event of a year occurs mostly during October-November in GX and GD.

Determining the Beaming of Io Decametric Emissions: A Remote Diagnostic to Probe the Io‐Jupiter Interaction

Abstract: We investigate the beaming of 11 Io-Jupiter decametric (Io-DAM) emissions observed by Juno/Waves, the Nançay Decameter Array, and NenuFAR. Using an up-to-date magnetic field model and three methods to position the active Io Flux Tube (IFT), we accurately locate the radiosources and determine their emission angle θ from the local magnetic field vector. These methods use (a) updated models of the IFT equatorial lead angle, (b) ultraviolet (UV) images of Jupiter's aurorae, and (c) multi-point radio measurements. The kinetic energy Ee− of source electrons is then inferred from θ in the framework of the Cyclotron Maser Instability. The precise position of the active IFT achieved from methods (b and c) can be used to test the effective plasma density of the Io torus. Simultaneous radio/UV observations reveal that multiple Io-DAM arcs are associated with multiple UV spots and provide the first direct evidence of an Io-DAM arc associated with a trans-hemispheric beam UV spot. Multi-point radio observations probe the Io-DAM sources at various altitudes, times and hemispheres. Overall, θ varies a function of frequency (altitude), by decreasing from 75°−80° to 70°−75° over 10−40 MHz with slightly larger values in the northern hemisphere, and independently varies as a function of time (or longitude of Io). Its uncertainty of a few degrees is dominated by the error on the longitude of the active IFT. The inferred values of Ee− also vary as a function of altitude and time. For the 11 investigated cases, they range from 3 to 16 keV, with a 6.6 ± 2.7 keV average.

Concurrent effects of Martian topography on the thermosphere and ionosphere at high northern latitudes

Abstract: Abstract Martian topography modulated non-migrating tides play important roles in the upper atmosphere and thus in the ionosphere through their coupling, especially in their longitude variations. In this study, the neutral scale height ( H n ) and ionospheric peak electron density ( N m M 2 ) and height ( h m M 2 ) retrieved from the MGS radio occultation measurements were used to investigate the coupling between the Martian thermosphere and ionosphere under the forcing of topography modulated tides by investigating their concurrent longitude variations. A segment of the measurements with fixed local time was selected to analyze the relationships between the longitude variations of the parameters in detail. Longitude variations of the thermosphere and ionosphere are significant though topographic fluctuations are not very prominent at high northern latitudes. Longitude fluctuations of H n and N m M 2 are nearly in anti-phase and percentage fluctuation amplitudes of H n are nearly twice as large as those of N m M 2 , which indicate the non-migrating tide forced coupling between the ionosphere and thermosphere conforms to the Chapman theory, and suggests longitude variation of N m M 2 can be used as a quantitative indicator for that of the thermal structure in the lower thermosphere. Longitude variation phases of H n and h m M 2 are also discrepant. That is due to tide vertical propagation since H n and h m M 2 depend on the atmospheric thermal structures at different height levels. The thermosphere and ionosphere show longitude variations due to the topography; however, they are dominated by inconsistent longitude components. This implies discrepant exciting and propagating efficiencies of various topography modulated tides. Graphical Abstract

Impact and synergies of GIM error estimates on the VTEC interpolation and single-frequency PPP at low latitude region

Abstract: Abstract The vertical total electron content (VTEC) is one of the key quantities to describe variations of the ionosphere and can be provided to users to correct the ionospheric disturbances for GNSS (Global Navigation Satellite System) positioning. The VTEC values and the corresponding standard deviations are routinely provided in the so-called Global Ionosphere Maps (GIM), with a typical time resolution of 2 h (and up to 15 min) on regular grids with 2.5º resolution in latitude and 5º resolution in longitude. To determine the ionospheric corrections from the GIMs for positioning applications, an interpolation has to be applied to the VTEC grid values, which generally degenerates the final VTEC accuracy. In this context, the typically applied bi-linear interpolation of the VTEC values is calculated by introducing a new weighting scheme by means of the standard deviation maps in the ionospheric domain. In the sequel, the impact of the use of the VTEC uncertainties for the interpolation procedure is applied to the GIMs of different centers and assessed in the ionospheric and in the positioning domain. For the assessment of the GIM in the ionospheric domain, the VTEC values calculated are compared with VTEC directly obtained from the given GIM, i.e., without interpolation. In the positioning domain, the impact of the VTEC uncertainties is analyzed by means of single-frequency precise point positioning (PPP), considering four Brazilian stations in challenging regions. The use of the standard deviation values in positioning provides a significant improvement in periods of high solar flux, especially for stations in the region under more intense ionospheric effect (mean rates of improvements up to 47%).

Ionospheric Nighttime Enhancements at Low Latitudes Challenge Performance of the Global Ionospheric Maps

Abstract: In this study, two ionospheric nighttime enhancement (INE) events at low latitudes are selected to investigate their spatial features through the observations from Global Navigation Satellite System (GNSS) receivers and ionosondes. For the first time, we present the detailed spatial pictures of premidnight and postmidnight INEs under geomagnetically quiet conditions. The two INE events have the maximum extents of about 11° × 34° and 17° × 25° (longitude × latitude), respectively. Dramatic latitudinal and longitudinal features are revealed in the two INEs. We perform a comparison between the products of Global Ionospheric Maps (GIMs) and total electron content (TEC) measurement from GNSS receivers. However, GIMs fail to capture the TEC distribution during INEs owing to their limited spatial and temporal resolution. Considering the extent of INEs from the observations, the spherical harmonic (SH) expansion adopted by the GIM models needs to upgrade the degree and order to 36. The pixel-based methods developed from two GIM models are required to reduce their grid size for higher spatial resolution. The recommended time interval is shorter than 30 min. Among seven GIMs, CODG and JPLG maps generally have the best performance in reproducing the latitudinal structure of the ionosphere.

Global assessment of spatiotemporal variability of wet, normal and dry conditions using multiscale entropy-based approach

Abstract: Abstract In recent decades, human-induced climate change has caused a worldwide increase in the frequency/intensity/duration of extreme events, resulting in enormous disruptions to life and property. Hence, a comprehensive understanding of global-scale spatiotemporal trends and variability of extreme events at different intensity levels (e.g., moderate/severe/extreme) and durations (e.g., short-term/long-term) of normal, dry and wet conditions is essential in predicting/forecasting/mitigating future extreme events. This article analyses these aspects using estimates of a non-stationary standardized precipitation evapotranspiration index corresponding to different accumulation periods for 0.5° resolution CRU grids at globe-scale. Results are analyzed with respect to changes in land-use/landcover and geographic/location indicators (latitude, longitude, elevation) at different time scales (decadal/annual/seasonal/monthly) for each continent. The analysis showed an (i) increasing trend in the frequency/count of both dry and wet conditions and variability of dry conditions, and (ii) contrasting (decreasing) trend in the variability of wet conditions, possibly due to climate change-induced variations in atmospheric circulations. Globally, the highest variability in the wet and dry conditions is found during the Northern hemisphere's winter season. The decadal-scale analysis showed that change in variability in dry and wet conditions has been predominant since the 1930s and 1950s, respectively and is found to be increasing in recent decades.