Journal of Earth System Science最新文献

Abstract

This study aims to assess the accuracy of three satellite-derived products (IMERG-F, CHIRPS and PERSIANN CDR) in quantifying the erosivity of rainfall. A network of 14 gauge stations is utilized to estimate the R-factor in west-central Morocco between 2001 and 2020. This evaluation is conducted at the basin, and the pixel scale is based on five statistical metrics. The present research showed that rainfall intensity and the topographic characteristic of terrain could highly affect the performance of SPPs in estimating the R-factor; the results show that the estimations become less accurate either in high altitudes or in high rainfall intensities. Furthermore, the findings indicate that CHIRPS outperforms the other datasets, particularly at the basin scale where the relative bias is close to 0, with a minimum error and a Nash coefficient of about 0.62, followed by the IMERG-F product, while PERSIANN CDR has the lowest performance. Overall, this study’s outcome yields valuable insights into the applicability of CHIRPS product in estimating rainfall erosivity factor in scarcely gauged areas characterized by a complex climate and topography.

Research highlights

• The rainfall erosivity factor was calculated using three satellite precipitation products.

• CHIRPS product exhibited the best performance in estimating rainfall erosivity in Tensift watershed.

• The performance of SPPs in estimating R factor is highly affected by the altitudes and the climatic caracteristics of the study area.

• The vulnerability maps were created to identify regions threatened by water erosion according to the three products.

Biodiversity reserves are a crucial in-situ method to conserve biodiversity hotspots as they are sensitive to climate change. The Nanda Devi Biosphere Reserve (NDBR) in the western Himalayas is enriched with diverse endemic flora and fauna and endorses the second-highest mountain peak in the world. However, in the recent decade, this region has potentially warmed at an alarming rate. With 36 temperature and precipitation indices from high-resolution 40-year data from ERA5 reanalysis and CHIRPS, this paper assesses the state of warming and extreme climatic events. Apart from the indices, Landsat (NASA/USGS, USA) and QuickSCAT (ISRO, India) were utilized to assess the region’s response to climate change. An increase of 0.73ºC in the last decade for minimum, 0.26°C for maximum temperatures was observed, with the highest anomaly of 1.7°C in 2016. The reserve’s vegetation pattern has changed with the vegetative region’s dispersal towards the north and higher elevations. In the year 2000, the area without any vegetation covered 79% of the total area, which declined to a mere 23.8% in the year 2020, equivalent to a 70% decline in the area. Similarly, the area with very dense region covered only 0.02% of the total area in the year 2000, and in the year 2020, it increased to 109%. Snow cover seems to be worst affected in the region with dense snow cover declining maximum by 2020. From coverage of 12.3% of the total area of the reserves, it was reduced to a mere 0.02%, showing a decline of nearly 100% in the region. Our findings show that although protected areas are meant to be resilient to external anthropogenic intrusions, they are highly susceptible to the intrinsic forces of induced climate change. We suggest that reserve managers enable robust measures to identify the distribution of vulnerable species and introduce new methods to preserve the pristine hotspot region.

In the Earth’s atmosphere, greenhouse gases (GHGs) and reactive trace gases are essential components of chemistry–climate interactions. These trace gases are emitted from both natural and anthropogenic sources over terrestrial and marine regions. Air–sea exchange is the dominant process controlling the distribution of several important trace gases over remote marine regions. Although the ocean–atmosphere interface covers ~70% of the Earth’s surface, the quantitative air–sea exchange of reactive trace gases is estimated over the limited oceanic regions. The production and air–sea exchange of trace gases are controlled by physical conditions at both sides of the interface and ocean biogeochemistry. The northern Indian Ocean (NIO) experiences strong seasonal monsoon winds and intense tropical cyclones. Consisting of the Arabian Sea and the Bay of Bengal, it is one of the most biologically productive regimes of the world ocean and home to the intense oxygen minimum zone (OMZ) of the Arabian Sea with dissolved oxygen concentrations. Thus, the NIO offers a unique system to investigate the air–sea exchange processes of reactive trace gases. So far, most of the studies of air–sea exchange of trace gases is focused on the Atlantic and Pacific Oceans, while studies over the northern Indian Ocean are very limited and reported mainly for CH₄, CO₂ and N₂O. Although progress has been made in recent years, studies of air–sea exchange of reactive trace gases such as non-methane hydrocarbon (NMHCs), oxygen-, sulfur- and halogen-containing hydrocarbons remain scarce. This paper addresses the current understanding of air–sea exchange processes and fluxes of reactive trace gases, including NMHCs, dimethyl sulfide (DMS), oxygenated volatile organic compounds (OVOCs), halocarbons, carbon monoxide (CO) and ozone (O₃) in the northern Indian Ocean. This review summarizes the studies on the air–sea exchange of trace gases over the northern Indian Ocean and common parametrization approaches used to estimate the air–sea flux of gases. Flux range for ethene (3–10.35 µmol m^–2 d^–1), isoprene (0.215–0.172 µmol m^–2 d^–1), acetaldehyde (–6.75–11.35 µmol m^–2 d^–1), acetone (–9–9 µmol m^–2 d^–1), DMS (0.03–41.4 µmol m^–2 d^–1) and CO (1.4–5.4 µmol m^–2 d^–1) over the NIO were summarized from various in-situ and modelling studies. The paper addresses the importance of the northern Indian Ocean apropos the production and exchange of reactive trace gases, the knowledge gaps and the future scientific scope. Additionally, it emphasizes the need for a multidisciplinary study of oceanic reactive trace gas cycling and its impact on regional atmospheric chemistry over the northern Indian Ocean.

With the launch of very high resolution (VHR) satellites such as the Cartosat-2S series, Cartosat-3, WorldView-series, Pleiades-Neo series in the recent past, high resolution digital surface models (DEMs) with ~1 m grid interval can be generated using high resolution stereo images using the approach of digital photogrammetry. These high resolution DEMs are very handy for applications in city modelling, change detection, disaster management, infrastructure planning and so on. In this study, high resolution DEM is generated at a grid interval of 1 m using Cartosat-2S across-track images (0.65 m resolution) and WorldView-3 in-track stereo images (0.31 m resolution) over a small region over Mumbai. Both the generated DEMs are compared with each other in qualitative and quantitative ways and their relative accuracies are evaluated towards accurate city modelling.

In terms of natural disasters, lightning is India's most devastating threat, causing over 2500 casualties per year, according to the latest annual report of the National Crime Record Bureau. When compared to numbers reported from other parts of the world, this one is significantly higher. Bihar ranks as one of the most vulnerable Indian states in terms of lightning-related casualties and injuries. Lightning-related casualties and injuries in lightning hotspots in Bihar, India, are analysed and presented for the first time using the casualty and injury data received from the field offices of the Disaster Management Department, Government of Bihar. Also, the spatial and temporal patterns and causes of lightning deaths in the state of Bihar have been linked to the intra-annual cloud-to-ground lightning strike frequency distribution. During 2017–2022, on average, there were 271 human casualties and 57.2 lightning injuries every year because of lightning in the small state of Bihar. The casualty rate per million per year was 2.65 during the period under study, which is higher than India's average (2.55). Lightning-related damages peaked from May to September, with June and July having the most (58.8% of total casualties and 59.43% of total injuries). Most of these casualties and injuries (about 76.8%) caused by lightning occurred from 1230 to 1830 IST. Several hotspots, mainly in the southern and eastern parts of the state, have been identified. Most of the casualties occurred in rural settings. Men between the age groups of 11–15 and 41–45 living in rural areas were particularly vulnerable. The authors contend that lightning mitigation actions and education campaigns regarding the risks associated with lightning should be undertaken with urgent priority to reduce the lightning casualty rate in the state of Bihar, India.

Studying rainfall patterns is very important because agricultural production and flood conditions depend on proper water management. Therefore, accurately identifying trends in climate scenarios is essential to achieve this goal. This study, therefore, analyses rainfall trends using the Mann–Kendall test (MKT), modified Mann–Kendall test (MMKT), Spearman rank correlation (SRC), Şen slope estimator (SSE), and innovative trend analysis method (ITAM). This investigation analyses annual, monsoon, autumn, summer, and winter rainfall trends using the most extensive hydrometeorological time series from 1901 to 2020. Five such methods of trend analysis use 120 years of gridded meteorological data from the India Meteorological Department for the neighbouring four river basins Kangsabati, Keliaghai, Silabati, and Dwarkeswer in east India. For the winter period, no significant trend is detected using the MKT, MMKT, SRC, and SSE. While the ITAM detects a significant trend at 88% of grid points of the study area. During other seasons, the MKT, MMKT, SRC and SSE notice trends for 76% of grid points with less significance than the ITAM method. Overall results obtained using the ITAM and MMKT methods are proved to be more effective in detecting sensitive trends. This study can serve as scientific support for the identification and strategic mitigation of climatic change impacts on water management to reduce the risk of climate change.

The antiplane deformation of a two layered model consisting of a homogeneous, elastically isotropic (HEI) stratum of finite thickness lying on a HEI substratum occurring from a buried inclined strike-slip fault (ISF) situated in the stratum has been studied. The stratum is in welded contact with the substratum having different rigidity. The integral expressions for the deformation field occurring from a long strike-slip line dislocation for the antiplane strain case have been obtained using Fourier transform approach. The integrals have been solved analytically by expanding the denominator into a finite sum of exponential terms (FSET) using least square method. Further, the deformation is obtained for a long buried ISF of finite width via integrating over the width of line dislocation. The variation of the displacement has been computed graphically with respect to the epicentral distance as well as with depth.

Urban agglomerations across the world have witnessed haphazard and unprecedented growth in the recent past, giving rise to urban sprawling. This study analyses the spatio-temporal growth dynamics of 16 major Indian cities (population above one million) using remote sensing approaches. Land Use and Land Cover (LULC) thematic datasets are considered for the years 2005, 2010, 2015, and 2021. The variability of the five LULC classes, viz., urban built-up, vegetation, water body, agriculture, and barren land, implied that urban expansion mostly took place at the cost of barren lands. The urbanised landscape mainly portrayed dispersive outward growth since the beginning of the 21st century, with significant compaction (infill urban growth) near the urban core in recent years. The results derived through Shannon’s Entropy, spatial metrics, and urban density gradient analysis (in eight directions) indicated the same. Population density variation with respect to the horizontal urban growth and dynamics in each considered direction, further supported the concept of overcrowded city centres and sprawled outskirts. Besides population density, other factors that could be associated with urbanisation include the local environment, meteorology, and some geophysical characteristics.

The diurnal cycle of total hydrometeor availability and its associated patterns of atmospheric circulation is studied over a connected Andes–Amazon (A–A) system in the central region of Peru during the summer season. Surface precipitation depends on the amount of hydrometeors that occur in the atmosphere and its atmospheric dynamics. Hydrometeors and the precipitation efficiency index were estimated using radar of the core satellite of the GPM system (N-GPM) for the period 2014–2022. The atmospheric dynamics were analyzed using the regional Weather Research and Forecasting (WRF) model. According to the results, the Andes mountain range produces precipitation at a surface level more efficiently during the afternoon and early evening hours (12–19 LT) due to the convergence of the thermal mesoscale circulations transporting moisture fluxes from the east and west. Both generate convective multicells along the Andes mountain range. The circulation from the west intensifies during the day, causing the displacement of the chain of convective multicells towards the east and producing hydrometeors and intense precipitations in the inter-Andean valleys. The A–A transition zone is more efficient in producing precipitation during the early hours of the day (00–07 LT) due to an increase in the northern circulation associated with the low-level jets and a change in the magnitude of the horizontal winds. Northerly winds enter the A–A transition zone with increased intensity and leave with reduced intensity. This mechanism is driven by the effect of the topographical barrier and the masses of cold air located in high areas on the eastern flank of the Andes. These factors generate significant updrafts and, therefore, the formation of storm clouds with high concentrations of hydrometeors and precipitation on the surface.

In this work, it is shown that early warning signals were recorded prior to a 6.4 magnitude earthquake that took place on December 29, 2020, near the Croatian city of Petrinja. The study relied on analyzing property changes in small-scale probability density fluctuations in three parameters of the Earth’s magnetic field: X, Y and Z. The applied technique made it possible to identify a set of these precursors in intervals ranging from two and a half days to one day to less than one hour before this event. It has been observed that the three magnetic variation stations located at distances of approximately 300, 1000, and 1500 km from the epicenter exhibit significant differences in the occurrence of early warning signs and critical phenomena during an impending earthquake. These differences are related to the intensity and frequency of the effects observed at each station.