Search Results (99)

Near space refers to the atmospheric region 20–100 km above Earth’s surface, encompassing the stratosphere, mesosphere, and part of the thermosphere. This region is susceptible to surface and upper atmospheric disturbances, and the atmospheric temperature and humidity profiles can finely characterize its complex environment. To analyze the relationship between changes in temperature and humidity profiles and natural activities, this study utilizes 18 years of temperature and water vapor data from the TIMED/SABER and AURA/MLS instruments to investigate the variations in temperature and humidity with altitude, time, and spatial distribution. In addition, multiple linear regression analysis is used to examine the impact mechanisms of solar activity, the El Niño–Southern Oscillation (ENSO), and the Quasi-Biennial Oscillation (QBO) on temperature and humidity. The results show that in the mid- and low-latitude regions, temperature and water vapor reach their maxima at an altitude of 50 km, with values of 265 K and 8–9 × 10⁻⁶ ppmv, respectively; the variation characteristics differ across latitudes and altitudes, with a clear annual cycle; the feedback effects of solar activity and the ENSO index on temperature and humidity in the 20–40 km atmospheric layer are significantly different. Among these factors, solar activity is the most significant influence on temperature and water vapor, with response coefficients of −0.2 to −0.16 K/sfu and 0.8 to 4 × 10⁻⁶ ppmv/sfu, respectively. Secondly, in the low-latitude stratospheric region, the temperature response to ENSO is approximately −1.5 K/MEI, while in the high-latitude region, a positive response of 3 K/MEI is observed. The response of water vapor to ENSO varies between −1 × 10⁻⁷ and −4 × 10⁻⁷ ppmv/sfu. In the low-latitude stratospheric region, the temperature and humidity responses to the QBO index exhibit significant differences, ranging from −1.8 to −0.6 K/10 m/s. Additionally, there are substantial differences in responses between the polar regions and the low-latitude equatorial region. Finally, a three-dimensional model coefficient was constructed to illustrate the influence of solar activity, ENSO, and QBO on temperature and humidity in the near space. The findings of this study contribute to a deeper understanding of the temperature and humidity variation characteristics in near space and provide valuable data and model references for predicting three-dimensional parameters of temperature and humidity in this region. Full article

Hydrokinetic tidal energy is one of the few marine renewable energy resources with sufficiently mature technology for commercial exploitation. However, several parameters affect its exploitability, such as the minimum speed threshold, ambient turbulence levels, or tidal asymmetry, to name but a few. These parameters are particularly important in regions with lower mean speeds than those in first-generation sites, such as the North Sea. The Gulf of California is one of those regions. In this paper, a Delft3D Flexible Mesh Suite (Delft3D FM) model in barotropic configuration is set up over the Gulf of California using a flexible mesh with resolution varying from O (500 m) in the deep regions to O (10 m) in the coastal regions. A simulation is run over the year of 2020, with a tidal forcing of 75 components. The model is validated at four tidal gauge locations and four Acoustic Doppler Current profiler (ADCP) locations. The speed, U, and tidal power density ($TPD$) indicators used for the validation were the annual means, the annual means for speeds above the 0.5 m s⁻¹ threshold, the annual means of the spring tide maxima, and the annual maxima. The contour maps of the annual means, that is, the annual means for speeds above the $0.5$ m s⁻¹ threshold, allow us to identify tidal energy hot spots throughout the Gulf of California, particularly in the Great Island region (GIR). In this region, these hot spots have higher U and $TPD$ values, in agreement with previous studies. The patterns of circulation around Tiburón Island and San Esteban Island on the East, and Ángel de la Guarda Island and San Lorenzo Island on the West, the four islands in the region with the highest tidal energy potential, are also discussed while recognizing that Tiburón Channel, between Tiburón Island and San Esteban Island, has proved to be the best siting location, based on the technical results obtained so far. The hot spots sites are further characterized by computing the tidal asymmetry in these small regions, showing the locations of the sites with smallest asymmetry, which would be the best for tidal energy exploitation. The hot spots around San Esteban Island are particularly important because they have the largest $TPD$ in the GIR, with the model predicting a $TPD$ on the order of 500–1000 W m⁻². Here, complementary field measurements obtained with two ADCPs, close to San Esteban Island, one at 15 m depth, SEs (shallow region), and the other at 60 m depth, SEd (deep region), produced $TPD$s of 1200 W m⁻² and 400 W m⁻², respectively. The analysis of the vertical profiles and the tidal asymmetry over the vertical shows the importance of developing 3D models in future investigations. Full article

Chicken coccidiosis causes annual losses exceeding GBP 10 billion globally. The most pathogenic species for domestic fowls including Eimeria tenella, E. acervulina, and E. maxima, can lead to gastrointestinal issues ranging from mild to fatal. In this study, stages of E. tenella and freshly isolated chicken heterophils were co-cultured for 180 min. These interactions were analyzed using live 3D holotomographic and confocal microscopy. We observed that E. tenella stages were entrapped by heterophils and heterophil extracellular traps (HETs). Notably, different HET phenotypes, specifically sprHETs and aggHETs, were induced regardless of the stage. Furthermore, the quantification of extracellular DNA release from co-cultures of heterophils and sporozoites (ratio 1:1) for 180 min demonstrated a significantly higher release (p = 0.04) compared to negative controls. In conclusion, research on the chicken innate immune system, particularly fowl-derived HETs, remains limited. More detailed investigations are needed, such as exploring the time-dependent triggering of HETs, to establish a standard incubation time for this pathogen defense mechanism. This will enhance our understanding of its role in parasite survival or death during HET confrontation. Full article

The normalized difference vegetation index (NDVI) can depict the status of vegetation growth and coverage in grasslands, whereas coarse spatial resolution, cloud cover, and vegetation phenology limit its applicability in fine-scale research, especially in areas covering various vegetation or in fragmented landscapes. In this study, a methodology was developed for obtaining the 30 m annual maximum NDVI to overcome these shortcomings. First, the Landsat NDVI was simulated by fusing Landsat and MODIS NDVI by using the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), and then a single-peaked symmetric logistic model was employed to fit the Landsat NDVI data and derive the maximum NDVI in a year. The annual maximum NDVI was then used as a season-independent substitute to monitor grassland variation from 2001 to 2022 in a typical area covering the major vegetation types in the Qinghai Lake Basin. The major conclusions are as follows: (1) Our method for reconstructing the NDVI time series yielded higher accuracy than the existing dataset. The root mean square error (RMSE) for 91.8% of the pixels was less than 0.1. (2) The annual maximum NDVI from 2001 to 2022 exhibited spatial distribution characteristics, with higher values in the northern and southern regions and lower values in the central area. In addition, the earlier vegetation growth maximum dates were related to the vegetation type and accompanied by higher NDVI maxima in the study area. (3) The overall interannual variation showed a slight increasing trend from 2001 to 2022, and the degraded area was characterized as patches and was dominated by Alpine kobresia spp., Forb Meadow, whose change resulted from a combination of permafrost degradation, overgrazing, and rodent infestation and should be given more attention in the Qinghai Lake Basin. Full article

To improve the utilization of satellite-based data and promote their development, this analysis comprehensively evaluates the performance of GSMaP Near-real-time Gauge-adjusted Rainfall Product version 6 (GSMaP_GNRT6) data in depicting precipitation over China from 2001 to 2020 by comparing four precipitation indices—accumulated precipitation, number of rainy days and rainstorm days, and precipitation maxima—with daily precipitation data from 2419 stations across China on monthly and annual time scales. The results show that the GSMaP-GNRT6 data effectively capture the overall spatial pattern of the four precipitation indices, but biases in the spatial distribution of the number of rainy days from July to September and the precipitation maxima during the wintertime are evident. A general underestimation of GSMaP-GNRT6 data is observed in the average for China. The annual precipitation amount, the number of rainy days and rainstorm days, and the precipitation maxima based on the GSMaP-GNRT6 data are 17.6%, 35.5%, 31.6% and 11.8% below the station observations, respectively. The GSMaP-GNRT6 data better depict the precipitation in eastern China, with the errors almost halved. And obvious overestimation of the number of rainstorm days and precipitation maxima occurs in western China, reaching up to 60%. Regarding the accumulated precipitation, the number of rainstorm days and the precipitation maxima, the GSMaP-GNRT6 data show an almost consistent interannual variation and increasing trends that are consistent with the station observations. However, the magnitude of the increasing trend based on the GSMaP-GNRT6 data is larger, especially at the beginning of the 21st century. Conversely, a considerable discrepancy in the annual variation and an almost opposite trend can be observed in the number of rainy days between the GSMaP-GNRT6 data and the station observations. Full article

Design flood estimation is an essential step in many water engineering design tasks such as the planning and design of infrastructure to reduce flood damage. Flood frequency analysis (FFA) is widely used in estimating design floods when the at-site flood data length is adequate. One of the problems in FFA with an annual maxima (AM) modeling approach is deciding how to handle smaller discharge values (outliers) in the selected AM flood series at a given station. The objective of this paper is to explore how the practice of censoring (which involves adjusting for smaller discharge values in FFA) affects flood quantile estimates in FFA. In this regard, two commonly used probability distributions, log-Pearson type 3 (LP3) and generalized extreme value distribution (GEV), are used. The multiple Grubbs and Beck (MGB) test is used to identify low-flow outliers in the selected AM flood series at 582 Australian stream gauging stations. It is found that censoring is required for 71% of the selected stations in using the MGB test with the LP3 distribution. The differences in flood quantile estimates between LP3 (with MGB test and censoring) and GEV distribution (without censoring) increase as the return period reduces. A modest correlation is found (for South Australian catchments) between censoring and the selected catchment characteristics (correlation coefficient: 0.43), with statistically significant associations for the mean annual rainfall and catchment shape factor. The findings of this study will be useful to practicing hydrologists in Australia and other countries to estimate design floods using AM flood data by FFA. Moreover, it may assist in updating Australian Rainfall and Runoff (national guide). Full article

This study develops a wavelet maxima-based methodology to extract anomalous signals from microwave brightness temperature (MBT) observations for seismogenic activity. MBT, acquired via satellite microwave radiometry, enables subsurface characterization penetrating clouds. Five surface categories of the epicenter area were defined contingent on position (oceanic/terrestrial) and ambient traits (soil hydration, vegetal covering). Continuous wavelet transform was applied to preprocess annualized MBT readings preceding and succeeding prototypical events of each grouping, utilizing optimized wavelet functions and orders tailored to individualized contexts. Wavelet maxima graphs visually portraying signal intensity variations facilitated the identification of aberrant phenomena, including pre-seismic accrual, co-seismic perturbation, and postseismic remission signatures. The casework found 10 GHz horizontal-polarized MBT optimally detected signals for aquatic and predominantly humid/vegetative settings, whereas 36 GHz horizontal-polarized performed best for arid, vegetated landmasses. Quantitative machine learning methods are warranted to statistically define selection standards and augment empirical forecasting leveraging lithospheric stress state inferences from sensitive MBT parametrization. Full article

The variability of the dissolved methane content in coastal zones is an important component of the biogeochemical cycle in the marine ecosystem. The objective of this study is to investigate the seasonal variability of dissolved methane distribution in the aerobic shallow coastal zone through the example of the small bay in the northeastern Black Sea. This study is based on the direct observations carried out during a long-term monitoring program conducted in the bay from 1999 to 2016. The seasonal and inter-annual variability of the dissolved methane pattern is considered under the climatic conditions as well as under the influence of extreme flood. The seasonal range of the dissolved methane content variability in the shallow part of the northeastern Black Sea is 1–2 orders of magnitude higher compared with the areas remote from the coast. The dissolved methane content in Golubaya Bay in summer is an order of magnitude higher than the winter values. In particular, local methane maxima located near the river and stream mouths and in the central bottom part of the bay have a well-shown seasonal cycle. The extreme flood conditions observed in July 2012 resulted in high methane concentrations 2 months after the flood event, when the surface concentrations of the dissolved CH₄ exceeded the equilibrium with the atmospheric values by a factor of 400. The obtained results provide a unique opportunity to estimate the scale of the biogeochemical processes in marine coastal environments under the influence of climatic and extreme conditions. Full article

This analysis uses both atmospheric CO₂ concentrations and the accompanying δ¹³C isotopic measurements of CO₂ over 40 years from 1978 to 2015 observed at ten different latitudes from 90° S to 82 °N. Atmospheric CO₂ is separated into two components of CO₂ attributable to deep ocean and to plant (including fossil fuel) sources. The isotopic values assigned to the two components are δ¹³C = 0‰ and −26‰, respectively. The latitude variations in residual source component CO₂ show the ocean source component peaking at the equator. This contrasts with the residual plant source component that peaks in the Arctic Circle region. Seasonal comparisons show no change in the ocean component peaking at the equator and no significant changes in its variation with latitude, while the plant component shows seasonal changes of the order of 15 ppm at high latitudes. The ocean component shows clear anomalous behavior in the three years following the 1989 Pacific Ocean regime shift (a shift independently identified from the changed biological time series). By contrast, the residual plant component shows a correlation in the timing of maxima in its annual variations with the timing of El Nino events over the time span of 1985–2015. It also shows a discontinuity in annual variation coinciding with the 1995 AMO phase change. We conclude that the ocean and plant components of atmospheric CO₂ relate to independent sources of atmospheric CO₂ and have approximately equal magnitudes. The observations are consistent with a hypothesis that variations in the ocean components have an origin from upwelling water from deep ocean currents, and variations in plant components are dominated by a combination of fossil fuel CO₂, phytoplankton productivity, and forest and peat fires, which primarily occur in the northern hemisphere. Full article

This article studies the intra-annual and long-term variability in the maximum daily precipitation totals and their association with atmospheric circulation in Kraków. It investigates daily precipitation maxima by year and by month. The research is based on daily precipitation totals in the years 1863–2021 and draws on the calendar of atmospheric circulation types by Niedźwiedź. It examines the frequency of precipitation maxima in individual months and their variation from one year to another. No statistically significant trend of change in precipitation over the study period has been found. All annual maximum daily precipitation totals in Kraków fall into the category of heavy precipitation (>10 mm), and almost 99% qualify as very heavy (>20 mm). In the summer months, these are about 3–4 times higher than in winter. The share of the daily precipitation maximum in the monthly total exceeds 30% in all months. The maximum daily precipitation occurring on 5 August 2021 was the highest in the period that extends from the start of instrumental measurements. The study period saw 12 cases of maximum precipitation that belong to ‘flood-inducing’ categories (over 70 mm/day). Such cases of the very heaviest precipitation occurred in cyclonic situations: Cc, Bc, Nc, NEc, Ec and SEc. Most spring and summer maxima were seen on days with a cyclonic circulation. The instances of high daily precipitation in the Kraków area led to the flooding of residential and historic buildings, as well as of municipal infrastructure. Full article

Rainfall intensity–duration–frequency (IDF) relationships are crucial in the design and management of hydraulic structures. At the core of the assumption for IDF development is that the statistics of past rainfall events will represent future rainfall events. It has been proven that climate change is a major trigger for non-stationarity; therefore, the assumption is untenable. This work is aimed at considering the impact of climate change in the development of IDF curves for a city. To account for this non-stationarity, an RCM was combined with measured data through a climate factor (CF) to develop a rainfall IDF for the coastal city of Calabar. The baseline and future climatic periods of the RCM were 1971–2010 and 2021–2060, respectively. The annual maxima series (AMS) were disaggregated and fitted to the Gumbel distribution. Results revealed that the magnitude of trend for the measured AMS and measured annual rainfall are −0.351 and +3.628, respectively. A CF value of 0.86 was obtained, and a generalized non-stationary rainfall IDF model was derived. When compared to models from similar studies, this model has conserved values with r² = 1 and an error margin of ±6% for all return periods. This will introduce economy in the design of hydraulic structures. Excess runoffs in Calabar were, therefore, related to frequent short-duration rainfall with low intensities. Full article

We analysed changes in magnitude and timing of the largest annual observed daily flow (Amax), in each water year, for 596 stations in high-value water resource catchments and flood risk locations across Australia. These stations are either included in the Bureau of Meteorology’s Hydrologic Reference Stations or used in its operational flood forecasting services. Monotonic trend (which is either consistently increasing or decreasing) analyses of the magnitude and timing of flood peaks (estimated using Amax) were performed using the Theil–Sen and Mann–Kendall approaches and circular statistics to identify the strength of seasonality and timing. We analysed regional significance across different drainage divisions using the Walker test. Monotonic decreasing trends in Amax flood magnitude were found in the Murray–Darling River Basin and in other drainage divisions in Victoria, southwest and midwest of Western Australia and South Australia. No significant obvious pattern in Amax magnitude was detected in northern Queensland, coastal NSW, central Australia and Tasmania. Monotonic increasing trends were only found in the Tanami–Timor Sea Coast drainage division in northern Australia. Monotonic trends in Amax magnitude were regionally significant at the drainage division scale. We found two distinct patterns in flood seasonality and timing. In the northern and southern parts of Australia, flood peaks generally occur from February to March and August to October, respectively. The strength of this seasonality varies across the country. Weaker seasonality was detected for locations in the Murray–Darling River Basin, and stronger seasonality was evident in northern Australia, the southwest of Western Australia, South Australia, Victoria and Tasmania. The trends of seasonality and timing reveal that in general, flood peaks have occurred later in the water year in recent years. In northern Australia, flood peaks have generally occurred earlier, at a rate of 12 days/decade. In Victoria, New South Wales and Tasmania, the trends in timing are generally mixed. However, in the southwest of Western Australia, the largest change in timing was evident, with Amax peaks commencing later at a rate of 15 days/decade. Decadal variability in flood timing was found at the drainage division scale as well. Most stations show a decreasing trend in Amax magnitude, but how that trend is associated with the change in timing is not clear. Full article

Regional studies of precipitation changes over Europe show that its eastern part is characterized by small changes in annual precipitation and insignificant aridity trends compared to central and southern Europe. However, a frequency analysis over the past 30 years showed statistically significant increasing dryness trends in eastern Europe and an increase in the occurrence of extremely high rainfall as well as prolonged no-rain intervals during the warm season. The largest increase in aridity was observed in the western and central parts of Belarus. During 1990–2020, the frequency of dry periods doubled in all river basins along the Black, Caspian, and Baltic Sea water divide areas of eastern Europe. From 1970 to 1990, there were high streamflow rates during the winter low-flow season. Consequently, over the past 50 years, in spring, we observed here a continued decrease in maximal discharges across all river basins. In summer, we detected a statistically significant increase in the number of days with anticyclonic weather over eastern Europe, a decrease in rainfall duration by 15–20%, an increase in daily precipitation maxima by 20–30%, and an increase in the number of days with a low relative humidity by 1–4 days per decade. Full article

Intensity–duration–frequency (IDF) curves of precipitation are a reference decision support tool used in hydrology. They allow the estimation of extreme precipitation and its return periods. Typically, IDF curves are estimated using univariate frequency analysis of the maximum annual intensities of precipitation for different durations. It is then assumed that the annual maxima of different durations are independent to simplify the parameter estimation. This strong hypothesis is not always verified for every climatic region. This study examines the effects of the independence hypothesis by proposing a multivariate model that considers the dependencies between precipitation intensities of different durations. The multivariate model uses D-vine copulas to explore the intraduration dependencies. The generalized extreme values distribution (GEV) is considered a marginal model that fits a wide range of tail behaviors. An illustration of the proposed approach is made for historical data from Moncton, in the province of New Brunswick (Eastern Canada), with climatic projections made through three scenarios of the Representative Concentration Pathway (RCP). Full article

Temporal variability of rainfall is extreme in the rangelands of northern Australia and occurs at annual, decadal, and even longer timescales. To maintain long-term productivity of the rangelands of northern Australia under highly variable rainfall conditions, suitable land management practices are assessed using rangeland biophysical models, e.g., GRASP (GRASs Production). The daily maxima of the 15 min rainfall intensity (I15) are used to predict runoff and moisture retention in the model. The performance of rangeland biophysical models heavily relies on the I15 estimates. As the number of pluviograph stations is very limited in northern Australian rangelands, an empirical I15 model (Fraser) was developed using readily available daily climate variables, i.e., daily rainfall total, daily diurnal temperature range, and daily minimum temperature. The aim of this study is to estimate I15 from daily rainfall totals using a well-established disaggregation scheme coupled with the Bartlett–Lewis rectangular pulse (BLRP) model. In the absence of pluviograph data, the BLRP models (RBL-E and RBL-G) were calibrated with the precipitation statistics estimated using the Integrated Multi-satellitE Retrievals for GPM (global precipitation measurement) (IMERG; 30 min, 0.1° resolution) precipitation product. The Fraser, RBL-E, and RBL-G models were assessed using 1 min pluviograph data at a single test site in Darwin. The results indicated that all three models tended to underestimate the observed I15, while a serious underestimation was observed for RBL-E and RBL-G. The underestimation by the Fraser, RBL-E, and RBL-G models consisted of 23%, 38%, and 50% on average, respectively. Furthermore, the Fraser model represented 29% of the variation in observed I15, whereas RBL-E and RBL-G represented only 7% and 11% of the variation, respectively. A comparison of RBL-E and RBL-G suggested that the difference in the spatial scales of IMERG and pluviograph data needs to be addressed to improve the performance of RBL-E and RBL-G. Overall, the findings of this study demonstrate that the BLRP model calibrated with IMERG statistics has the potential for estimating I15 for the GRASP biophysical model once the scale difference between IMERG and point rainfall data is addressed. Full article