 Subjects -> GEOGRAPHY (Total: 493 journals)
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- Climate of Syria Based on Cordex Simulations: Present and Future
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Abstract: Regional climate models are widely used to assess current and future impacts of climate change. In this study, we evaluate the performance of regional climate models from the Coordinated Regional Climate Downscaling Experiment programme integrated over the following three CORDEX domains: AFR, MNA and WAS. Four meteorological variables (temperature, precipitation, solar radiation and cloud cover) were evaluated over Syria at a grid spacing of 0.44°. The performance of five models in simulating the present climate characteristics (1989–2008) is evaluated with respect to the observations: CRU, ERA5 reanalysis and SARA and CLARA satellite data. We find that the mini-ensemble captures well the general spatial patterns and annual cycles of the selected variables. Anotheraim of this study was to assess the expected change of the mentioned four climate variables over Syria under the moderate emission scenario (RCP4.5) and the high emission scenario (RCP8.5) in the near future (2031–2050) and in the far future (2080–2099) with respect to the present climate (1989–2008). The simulations show a decreasing trend in cloud cover (between 6% and 10%) and precipitation (up to 9%) by mid and late century, regardless of the forcing scenarios. The simulations show a pronounced warming over Syria, which is expected to reach 6 °C by the end of the twenty-first century following the high greenhouse gas concentration scenario (RCP8.5). Furthermore, such an increase, combined with a decrease in precipitation, will shift Syria’s climate towards a more arid one.
PubDate: 2023-09-11
- Biostimulants in the Soil–Plant Interface: Agro-environmental
Implications—A Review-
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Abstract: Soil degradation is a global environmental problem that puts at risk food security. Improving soil health is, therefore, a major challenge for sustainable agriculture. Biostimulants are products consisting of microorganisms or substances that stimulate plant metabolism, enhance crop performance, and increase plant resistance to biotic and abiotic stresses. A viable approach to reducing chemical inputs is using biostimulants to ensure improved production yield and quality. Humic substances, seaweed extracts, hydrolysed proteins and amino acids, plant extracts, inorganic compounds, beneficial microorganisms, chitosan and other biopolymers are the major categories of biostimulants discussed in this review. Through various mechanisms, such as nutrient absorption enhancement, root growth stimulation, antioxidant activity, and soil structure improvement, these biostimulants have an impact on the interface between soils and plants. Apart from soil degradation, soil and water pollution due to high concentrations of potentially toxic elements (PTEs) is also an important issue. Phytoremediation has the potential to be an effective and environmentally friendly approach for soil remediation and regeneration. Biostimulants have shown encouraging results in the field of phytoremediation by increasing plant biomass, enhancing metal accumulation in plant tissues, as well as improving the overall efficacy of removing PTEs from contaminated soils. The specific mechanisms through which biostimulants contribute to phytoremediation include metal complexion, stabilization and transport to non-vital plant compartments. However, those agro-environmental beneficial effects of biostimulants on degraded soils have not been thoroughly reviewed to date. Therefore, the aim of this review was to present a comprehensive study concerning the use of biostimulants and their interaction in the soil–plant interface under different conditions. This review presents the state of the art about the agricultural and environmental applications of biostimulants to soils as a sustainable agronomic tool to improve soil health and ameliorate PTE contaminated soils.
PubDate: 2023-09-02
- Impact of different land use and land cover in simulation of tropical
cyclones over Bay of Bengal-
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Abstract: This study presents an assessment on the impact of different Land Use/Land Cover datasets in simulating the movement and severity of three extremely severe cyclonic storms, namely Phailin (2013), Hudhud (2014) and Fani (2019), which developed over the Bay of Bengal (BoB). For this purpose, the Advanced Research Weather and Forecasting System (WRF) is selected and the model is forced with necessary input parameters. Two sets of numerical experiment are conducted. The first set of experiments uses U.S. Geological Survey Land Use/Land Cover datasets, and the WRF model is integrated with four different land surface parameterization schemes. The second set of experiments uses the Indian satellite IRS P6 AWiFS-derived Land Use/Land Cover obtained from the National Remote Sensing Centre (here after; AWiFS), and WRF model is integrated with four different land surface parameterization schemes. The model simulated track, mean sea-level pressure, wind, and rainfall are analysed and verified with available observation as obtained from India Meteorological Department and NASA Global Precipitation Measurement. The dynamics and thermodynamic structure are analysed in terms of model simulated vorticity and equivalent potential temperature during the landfall of the system. The results suggested that the use of AWiFS Land Use/Land Cover improves the simulation of track of all the cyclones during and after the landfall of the system. Also, it significantly reduces the landfall point error for all the land surface parameterization schemes except with thermal diffusion scheme. The AWiFS experiments could simulate both the spatial and station rainfall reasonably well. Also, it could simulate the intensity and thermodynamic structure of the cyclone reasonably well.
PubDate: 2023-08-09
- Urbanisation and Geographical Signatures in Observed Air Temperature
Station Trends Over the Mediterranean and the Middle East–North Africa-
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Abstract: We update observed temperature trends in the Mediterranean and the Middle East–North Africa (MENA) region, assess their temporal and spatial features and investigate possible influences from urbanisation. Monthly mean temperature time-series of 370 stations are acquired from the CRUTEM4.6 and GSOD datasets and converted into suitable format for statistical analysis. The calculated annual and seasonal temperature linear trends for 1981–2020 indicate a strong warming with a MENA station average annual trend equal to \(0.36 ^\circ {\hbox {C}}\) /decade and a faster warming rate for spring ( \(0.43 ^\circ {\hbox {C}}\) /decade) and summer ( \(0.45 ^\circ {\hbox {C}}\) /decade). These trends are correlated with longitude, revealing faster warming rates over the eastern Mediterranean and Middle East. The stations are characterised as rural or urban centre with the use of the Global Human Settlement Model (GHS-SMOD) spatial grid that accounts for population, city size and shape for the year 2000. The trend derived for the urban centre stations is an annually averaged \(0.1 ^\circ {\hbox {C}}\) /decade greater than for the rural or all stations, and more prominent during summer and autumn. Hence a discernible, but small, urbanisation signature is revealed.
PubDate: 2023-07-01
DOI: 10.1007/s41748-023-00348-y
- Statistical Trend Analysis of Major Climatic Factors over Chhattisgarh
State, India-
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Abstract: Long-term changes in climatic variables have led to many past climatic disasters, and thus it is important to analyze the trends in the change of important climatic factors. For a better understanding of the climate of one of the Indian states, viz. Chhattisgarh, an exhaustive statistical trend analysis has been done on the major climatic factors such as rainfall, temperature, relative humidity, and potential evapotranspiration for the long-term records of the state. The non-parametric test popularly known as the Mann–Kendall (MK) trend test and Sen’s slope estimator for monthly, monsoon period, and annual data series are conducted in this study. Pettit’s homogeneity test and Standard Normal Homogeneity Test (SNHT) are conducted for change point detection. A regression analysis has also been done to validate the obtained results from Sen’s slope. The significance of the increasing and decreasing trends of the considered climatic factors is assessed based on the p-value. The results showed a decreasing trend in the annual rainfall and 1961 was detected as the change point year in the rainfall data. The negative slope obtained from the regression analysis indicated a downward trend in annual rainfall similar to Sen’s slope. The results showed a negative (downward) trend in rainfall for most of the months except for January, March, April, and September where an increasing (positive) trend is obtained while the trend in the month of July and the monsoon season is significantly decreasing as the obtained p-value is less than α (5% significance level i.e., 0.05). The temperature data analysis showed an increasing trend for most of the months except for January, May, and June while the months of September, October, and November and annual temperature are significantly increasing in the state of Chhattisgarh. The annual relative humidity data has a significantly increasing trend also, the increasing trend is found in all the months but is insignificant. The annual potential evapotranspiration data showed an increasing trend but the trend is insignificant. There is a positive (increasing) trend for all the months, with September, October, and November having a significant trend, while the months of January, May, and June have decreasing trend. The data of temperature, relative humidity, and potential evapotranspiration were found to be homogeneous by the Pettitt test and SNHT. The results of Sen’s slope were found in agreement with linear regression for all the data series. These trend assessments of major climatic factors may help policymakers in managing water resources projects for various purposes by speculating the possible future climatic conditions and improving our capacity to respond to natural calamities in the state.
PubDate: 2023-06-29
DOI: 10.1007/s41748-023-00345-1
- The ENSO Fingerprint on Bangladesh Summer Monsoon Rainfall
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Abstract: In South Asia (SA), the boreal summer monsoon (June to September; JJAS) and the El Niño-Southern Oscillation (ENSO) are connected, though different areas in SA respond differently to ENSO. In this paper, a new 41-year (1981 to 2021) high-resolution gridded rainfall dataset (ENACTS-BMD; Enhancing National Climate Services for Bangladesh Meteorological Department) is used to investigate the linkage between the Bangladesh Summer Monsoon Rainfall (BSMR) and ENSO. Observed BSMR shows a weak positive correlation (r = + 0.21, not statistically significant at the 5% level) with sea surface temperatures (SST) in the central-eastern (Niño3.4) Pacific region. Among the eight El Niño events, seven of them corresponded to above-normal BSMR. However, during the 11 La Niña events, the relationship was more varied, with above-normal BSMR occurring in seven instances. These findings highlight an asymmetric relationship between BSMR and ENSO. Furthermore, BSMR is negatively correlated (r = − 0.47 statistically significant at the 5% level) with Indian Summer Monsoon Rainfall (ISMR: 75°–85oE, 18°–30oN). The potential physical mechanism can be outlined as follows: during El Niño, the Walker circulation tends to be weakened, resulting in a weakening of the summer monsoon circulation, which in turn reduces the intensity of easterly winds along the Bangladesh Himalayan foothills. Subsequently, a lower-level anomalous cyclonic circulation is established, facilitating the convergence of moisture within the boundary layer. This, in turn, leads to intensified rainfall over Bangladesh and the surrounding regions during El Niño. Seasonal forecast models do not adequately capture BSMR and ENSO, BSMR and circulation, and BSMR and ISMR inverse correlations. While the observed BSMR-ENSO relationship is complex and teleconnections are weak, awareness of the inverse relationship with ISMR and the incorrect model behavior could be useful in the context of seasonal BSMR predictions.
PubDate: 2023-06-13
DOI: 10.1007/s41748-023-00347-z
- SBAS-InSAR/GNSS Surface Deformation Assessment in Arid Environments of
Najran, Saudi Arabia-
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Abstract: Multiple surface fissures were reported over the last few years within the Najran valley, southern Saudi Arabia. The earth fissures have been observed mainly in the vicinity of agricultural territories. This study maps the surface deformation of Najran valley using geodetic data and investigates the underlying mechanisms. Indeed, we use Interferometric Synthetic Aperture Radar (InSAR) technique with standard Sentinel-1 Geocoded UNWrapped interferogram (GUNW) products acquisition from 2016 to 2022 and processed by Advanced Rapid Imaging and Analysis (ARIA) project using InSAR Scientific Computing Environment (ISCE). We generate displacement time series using the Miami INsar Time series software in Python language (MintPy). The result shows a rate of subsidence within the Najran valley ranging between 0.2 and 0.6 cm/yr. We processed the Najran GNSS station with time series extended from 2017 to 2022 to validate the observed displacement field. We analyze groundwater variation and soil properties to interpret the results. This assessment verifies that the potential drivers of subsidence might be due to an excessive withdrawal of groundwater, with the potential contribution of other factors related to the sequence of drought and moisture in the soil layer. The presence of a fine-grained layer of soil (clay) suggests a potential impact on the observed deformation. The observed signal and potential underlying mechanism represent one of the classical problems in arid regions worldwide, our investigation is crucial to improve the environmental assessment of Najran valley, which may mitigate any potential future hazards.
PubDate: 2023-06-05
DOI: 10.1007/s41748-023-00346-0
- Correction to: Spatio‑temporal Change of Glacier Surging and
Glacier‑dammed Lake Formation in Karakoram Pakistan-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-021-00281-y
- Correction to: Dynamics and Characterization of Aeolian Dust Deposition
from a Burned Shrubland at Chubut Coastal Patagonia in Argentina-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00299-w
- Correction to: A Review of the Neoproterozoic Global Glaciations and a
Biotic Cause of Them-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00316-y
- Correction to: Bioplastic from Renewable Biomass: A Facile Solution for a
Greener Environment-
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PubDate: 2023-06-01
DOI: 10.1007/s41748-021-00280-z
- Analysis of Precipitation and Temperature Trends Under the Impact of
Climate Change Over Ten Districts of Jimma Zone, Ethiopia-
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Abstract: This study aimed to investigates the precipitation and temperature trends over ten districts of Jimma zone in the twenty-first century using observed and model simulation data sets. The precipitation and temperature trends are analyzed for the reference (1981–2010) and two future periods, namely, mid-century (2031–2060), and end-century (2071–2100) using Innovative Trend Analysis. For future period, we analyzed the ensemble mean of precipitation and temperature based on data from four high resolution models, namely, High-Resolution Hamburg Climate Model 5, Regional Atmospheric Climate Model (RACMO22T), Climate Limited-Area Modeling Community (CCLM4), and the Rossby Centre Regional Atmospheric Model (RCA4). Based on the analysis, the annual, summer and autumn rainfall trend during the reference period are − 4.079 mm/year, 2.147 mm/year, and − 1.639 mm/year, respectively. The winter rainfall reveals a negative trend (− 0.135 mm/year) during the reference period. However, the winter rainfall shows a positive trend (0.465 mm/year and 0.067 mm/year) towards the end-century period under RCP4.5 and RCP8.5 scenarios. On the contrary, the autumn rainfall showed consistent decreasing trend during the two future periods. The maximum increasing trend (1.376 mm/year) in annual rainfall was obtained during the mid-century period under RCP4.5 scenario, whereas the maximum annual decreasing rainfall trend was obtained during the mid-century period under RCP8.5 scenario (− 0.649 mm/year). The minimum temperature showed significant increasing trend throughout the study periods. However, the maximum temperature showed decreasing trend during annual and winter in the mid-century period under RCP4.5 and RCP8.5 scenarios. The highest increasing trend of the minimum temperature was during winter and autumn, while the highest increasing trend of the maximum temperature was during the summer and autumn seasons. The result further indicate that the minimum temperature increment was faster as compared to the maximum temperature. The study can be used as a first-hand information to develop efficient adaptation policies and mitigation measures that aids to combat the adverse impact of climate change.
PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00322-0
- Shallow Groundwater Thermal Response to Land Surface Energy Dissipation
and Potential Implications on the Use of Heat as a Tracer-
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Abstract: This paper investigated and demonstrated the fundamental role of riparian and terrestrial zone heat balances on the use of thermal gradients to characterize and parameterize groundwater systems. The riparian area aquifer (RAA) includes vegetative cover, comprising a forest of lush Acacia karroo together with some reed, sedges, and forbs. On the other hand, terrestrial area aquifer (TAA) is non-forested. The result illustrated the riparian area suppresses groundwater temperature by an average of 2 °C compared to TAA during summer. These signals were found to uniformly dampen temperature anomalies resulting from lateral groundwater inflow from TAA in summer. The impact of lateral groundwater flow from the TAA was only observed in winter, where the effect of latent heat was cancelled out because plants had undergone dormancy. Consequently, the study concluded that the riparian groundwater temperature is more sensitive to the riparian energy balance. To this effect, riparian vegetative cover can considerably complicate the interpretation of the shallow groundwater thermal regime across hydrologic landscapes with varying surface vegetative architecture. Therefore, analyzing thermals signals may require correcting the “false” groundwater geothermal signals due to vegetative cover. The recommendation is that isolating the contributions of these signals should be independently constrained (e.g., introducing thermal data offset) to strengthen the plausibility of heat in parameterizing groundwater systems.
PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00294-1
- Evaluation of Spatio-Temporal Dynamics of Guyana’s Mangroves Using
SAR and GEE-
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Abstract: Mangrove forests are vital in many ways to coastal communities. The forests prevent coastal erosion, produce nutrients and organic matter, serve as a sink for carbon, nitrogen, and phosphorus, maintain water quality, and support food production for habitat biodiversity. However, these systems are threatened by urban development and have sea-level rise as a result of climate change. Such is evident in Guyana coastal areas where there had been a reduction of mangroves coverage from approximately 80,000 ha in 1980 to 22,000 ha in 2010 and 26,115 ha in 2019. One of the measures to restrict the depletion of this vital ecosystem is through an aggressive programme of mangrove replanting and restoration by the Government of Guyana. To monitor and measure the spatio-temporal effectiveness of this management effort require effective and advanced technologies, which remote-sensing capabilities can provide. In this study, the synthetic aperture radar (SAR) imagery was used for the mapping of mangrove regeneration and dynamics. The producer’s accuracy of the mangrove classification for each year was 96%, 95%, 97%, 99%, and 99% in 1996, 2007, 2010, 2016, and 2019, respectively, and the users’ accuracy was 95%, 95%, 95%, 99%, and 99%, respectively, demonstrated that this can be used for the monitoring spatio-temporal response of mangroves. The analysis of diameter at breast height and the heights of the mangroves also show the spatial and temporal trend of gains and losses of biomass as derived from the allometric equations of the analysed SAR images. The findings show the effectiveness of the methodology used to monitor changes and to estimate the biomass. This study could be a useful guide for planning future coastal restoration projects at the sample study sites, assist in community resilience in the face of sea-level rise and climate change, and support policymakers in multi-policy coordination involving the management of the Guyana coastal retreat.
PubDate: 2023-06-01
DOI: 10.1007/s41748-021-00277-8
- Evaluation of Desertification in the Middle Moulouya Basin (North-East
Morocco) Using Sentinel-2 Images and Spectral Index Techniques-
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Abstract: This article focuses on the quantitative assessment of desertification in the Middle Moulouya basin located in the North-East of Morocco. Indeed, this study aimed to map the degree of desertification at the level of the basin in 2018 using the Sentinel-2 image. To do this, we have adopted a methodology based on several stages. First, we extracted the spectral indices, in particular, the NDVI, the albedo, the TGSI and the MSAVI. Then, different combinations of these indices were the subject of a linear regression analysis (NDVI–albedo, MSAVI–albedo, albedo–TGSI and TGSI–MSAVI) to use the best correlated combinations to construct the feature space. The results obtained showed that the NDVI–albedo and MSAVI–albedo combinations are the best correlated with respective correlation coefficients of r = − 0.73 and r = − 0.76, respectively. As a result, they were used to propose the desertification degree index (DDI) by exploiting the NDVI–albedo and MSAVI–albedo feature spaces. Finally, a desertification map was generated for the entire basin. It has five degrees of desertification (extreme, severe, moderate, low, non-desertification). According to our results, the situation of desertification in the basin is alarming. Indeed, 86.86% of the study area is located in the moderate to extreme desertification class. While only 12.25% and 0.89% fall in the low and no desertification categories, respectively. The MSAVI–albedo model gave a high overall accuracy of 93.75%, so it is perfectly effective for the quantitative analysis and monitoring of desertification at the level of the basin studied.
PubDate: 2023-06-01
DOI: 10.1007/s41748-022-00327-9
- Structural Changes in Temperature and Precipitation in MENA Countries
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Abstract: This paper evaluates the extent of climate variability in the Middle East and North Africa (MENA) region using time series structural change tests. The MENA region is highly susceptible to climate change, being one of the driest and most water-scarce regions in the world. The study aims to identify structural breaks in temperature and precipitation time series from 1901 to 2012. Specifically, a statistical analysis is performed based on a structural change model (Bai and Perron 1998, 2003a) for temperature and precipitation across 19 countries. The results indicate significant structural changes in temperature and precipitation patterns during the observation period, and suggest that climate variability has indeed begun to occur in all study area, with 1990 marking a turning point in terms of global warming. North African countries, Qatar, and the United Arab Emirates experienced a large number of breaks in temperature variables between 1901 and 2012, while other countries experienced fewer breaks. With regards to the seasonal aspect of precipitation, the individual rainfall Seasonality Index results demonstrate strong seasonal variability of rainfall from one year to another. Results show that rainfall in MENA countries is irregular throughout the year and that it ranges from seasonal to extremely seasonal throughout the study period. These findings have important implications for water resources management, agriculture, human health, and ecosystems in the region.
PubDate: 2023-05-06
DOI: 10.1007/s41748-023-00344-2
- Spatial and Temporal Distribution of Black Carbon in Peru from the
Analysis of Biomass Burning Sources and the Use of Numerical Models-
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Abstract: The spatial and temporal distribution of biomass burning in Peru and neighboring countries was analyzed during the 2018–2020 period, with emphasis on 2019. To determine the glaciers most affected by BC as a consequence of vegetation burning, simulations were carried out with the WRF-CHEM model, and to diagnose the origin of BC particles received by the Huaytapallana glacier, backward trajectories were built with the HYSPLIT model. It was found that, during the studied period, the burning of biomass emitted large amounts of BC into the atmosphere, while the number of fires in Peru began its most notable increase in the month of July, with maxima between August and September. Comparisons of the number of outbreaks with the Aerosol Optical Depth (AOD) measured at the Huancayo observatory showed a significant correlation. The Ucayali region is the one that contributes the greatest number of outbreaks and the greatest emissions are produced in the south of Loreto. The WRF model showed that the concentrations in July are still low in relation to the August–October period. The mountain ranges that received the greatest impact from BC emissions were Huaytapallana, Huagoruncho, and Vilcabamba. BC transport is mainly oriented from north to south, moving the particles from the areas of greatest burning to the glaciers located in the center and south of the country. BC concentrations over the Cordillera Blanca were lower. The diagnosis of the backward trajectories corroborated the results of WRF-CHEM and showed trajectories mostly from the north.
PubDate: 2023-04-08
DOI: 10.1007/s41748-023-00342-4
- Land Surface Temperature Relationship with the Land Use/Land Cover Indices
Leading to Thermal Field Variation in the Turkish Republic of Northern
Cyprus-
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Abstract: The increase in the Land Surface Temperature (LST) caused by global warming and extreme weather events is significantly increasing Urban Hot Spots (UHS) while impacting the environmental quality within urban areas. In this research, with the help of Landsat 5, 7, and 8 satellite images, the evolution of Land Use/Cover (LULC), LST, and Surface Urban Heat Island (SUHI) in the Turkish Republic of Northern Cyprus (TRNC) between the years 1985 and 2020 is examined. The main aim is to evaluate how these variables, together with the Normalized Difference Built-up Index (NDBI), Urban Index (UI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Built Index, and Proportion Vegetation (PV) have influenced the variability of the UHS and the level of thermal comfort according to the Thermal Field Variance Index (UTFVI). The results report significant average rises of the variables: LST (6.62 °C), SUHI (0.97 °C), UHS (8.61%) of the UI and NDBI indices and class 6 of UTFVI (88.53%) that are related to the variability of the LULC corroborated by statistical analysis. Our results provide valuable information on the future development of urban areas in Northern Cyprus to make them more resilient and sustainable to rising temperatures.
PubDate: 2023-03-23
DOI: 10.1007/s41748-023-00341-5
- Land Use Land Cover Change and Related Drivers have Livelihood
Consequences in Coastal Bangladesh-
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Abstract: Land Use Land Cover (LULC) changes differ based on geographic position, while different kinds of natural and physical components accelerate the changes along with impacts on surroundings and demographic background. Bangladesh has been experiencing significant changes in landscape settings, facilitating changes in people’s livelihoods. To understand the changing pattern of livelihood in coastal areas of Bangladesh, it is crucial to detect the LULC changes, including the influence of related drivers. Following the background, this study was conducted in Batiaghata Upazila of Khulna district to assess the LULC changes using RS and GIS techniques over 30 years (1990–2019). With the help of 15 key informant interviews and 2 focus group discussions, this study delves into the driving forces behind the ever-evolving changes in LULC. From the impact on the livelihood patterns of different groups of people, this study uncovers the mysteries behind these changes. Findings unveiled a tale of transformation in the study area. As the years passed, there was a decline in agriculture (7.6%) and fallow land (15.66%), and a surge in water bodies (20.68%) from 1990 to 2019. These significant changes in land use paint a picture of an ever-evolving landscape. From the devastating effects of natural disasters to the pursuit of profit and the drive for industrial advancement, a multitude of drivers are fueling the changes in land use. As literacy rates rise and temperatures fluctuate, the landscape is undergoing a transformation driven by these powerful forces. The ripple effects of LULC changes can be felt throughout the community, leaving a wake of disrupted livelihoods in its path. As opportunities narrow and marginalized groups feel the squeeze, it's crucial for stakeholders to act. By examining the changes in LULC and livelihoods aims to pave the way for a more sustainable future in coastal Bangladesh.
PubDate: 2023-02-11
DOI: 10.1007/s41748-023-00339-z
- Climatology, Variability, and Trend of the Winter Precipitation over Nepal
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Abstract: Winter precipitation accounts for ~ 5% of interannual spatial variability during the last five decades (1960–2015), with the largest variability in the western and central regions of Nepal. The temporal variability shows a relatively higher degree of variability after the 1990s. In this study, the dominant modes of winter precipitation pattern, trend and their association with oceanic and atmospheric patterns were investigated over the southern slope of the central Himalaya, Nepal. The increasing trend (< 1 mm/year) of winter precipitation is found only over the highlands of the western and central regions, whereas decreasing trend or no trend in most of the areas over the country. Further, two dominant modes of winter precipitation were observed through Empirical Orthogonal Function (EOF) analysis. The first leading mode (EOF1) shows a monopole pattern with 42.9% variability with strong loading over the western and central regions, whereas the second mode (EOF2) shows a heterogeneous pattern, accounting for 18.9% of the total variance. Further, the EOF1 pattern is remotely influenced by El Niño-Southern Oscillation (ENSO) and locally through Indian Ocean Basin Mode (IOBM) patterns. It is also observed that the EOF2 mode has a close relationship with the North Atlantic Oscillation (NAO), modulating the wave train and propagating eastward to the western Himalayas.
PubDate: 2023-01-24
DOI: 10.1007/s41748-023-00338-0
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