scholarly journals Analyzing Future Rainfall Variations Over Southern Malay Peninsula Based On CORDEX-SEA Dataset

2021 ◽  
Author(s):  
Xiaosheng Qin ◽  
Chao Dai ◽  
Lilingjun Liu
Keyword(s):  
Large Scale ◽  
Southwest Monsoon ◽  
Mapping Method ◽  
Extreme Condition ◽  
Annual Rainfall ◽  
Study Region ◽  
Rainfall Characteristics ◽  
Long Run ◽  
Far Future

Abstract Gridded rainfall datasets based on various data sources and techniques have emerged to help describe the spatiotemporal features of rainfall patterns over large areas and have gained popularity in many regional/global climatic analyses. This study explored future variations of rainfall characteristics over peninsula Malaysia and Singapore region based on rainfall indices of PRCPTOT, Rx1day, Rx5day, R95pTOT, R1mm, and R20mm, under 9 CORDEX-SEA RCM datasets with RCP8.5 emission scenario. A monthly quantile delta mapping method (MQDM) was adopted for bias-correction of the RCM modelled data. It was indicated that all the studied rainfall indices have long-term variations both temporally and spatially. Generally, the further the future, the higher the variability and uncertainty of indices. For the study region, the relative increments of the medians from RCM models averaged over all climatic zones in the far future are 40.3%, 25.9%, and 4.7% for Rx1day, Rx5day and R95pTOT, respectively. The annual rainfall amount (PRCPTOT) in the long run would likely increase mainly in the northeast coastal zone and drop in most of other areas over the peninsula, with the median being -5.9% averaged over all zones. The frequency of wet days (R1mm) would generally drop over the whole peninsula, with the median averaged over all zones being -6.8% in the far future. The frequency of heavy rains (R20mm) would overall decrease (by -3.4% in average in the far future) but might still notably increase in the northeast zone (NE) at both annual and southwest monsoon. The extreme condition implied from various RCM models would be more alarming. The study result would be useful in revealing the essential spatiotemporal variations of rainfall over the peninsula from short- to long-term futures and supporting large-scale flood risk assessment and adaptation planning.

scholarly journals Low-cost Large Scale Vermicompost Unit

2021 ◽  
Vol 2115 (1) ◽  
pp. 012026
Author(s):  
Sonam Solanki ◽  
Gunendra Mahore
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Small Scale ◽  
Scale Production ◽  
Key Innovation ◽  
Main Challenge ◽  
Long Run ◽  
Large Scale Production ◽  
Term Maintenance

Abstract In the current process of producing vermicompost on a large-scale, the main challenge is to keep the worms alive. This is achieved by maintaining temperature and moisture in their living medium. It is a difficult task to maintain these parameters throughout the process. Currently, this is achieved by building infrastructure but this method requires a large initial investment and long-run maintenance. Also, these methods are limited to small-scale production. For large-scale production, a unit is developed which utilises natural airflow with water and automation. The main aim of this unit is to provide favourable conditions to worms in large-scale production with very low investment and minimum maintenance in long term. The key innovation of this research is that the technology used in the unit should be practical and easy to adopt by small farmers. For long-term maintenance of the technology lesser number of parts are used.

scholarly journals The effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia: An ARDL investigation

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0248743
Author(s):  
Md Mazharul Islam ◽  
Majed Alharthi ◽  
Md Wahid Murad
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Saudi Arabia ◽  
Carbon Emissions ◽  
Annual Rainfall ◽  
Long Term Effects ◽  
Ardl Model ◽  
Long Run ◽  
Unemployment Problem

Objective While macroeconomic and environmental events affect the overall economic performance of nations, there has not been much research on the effects of important macroeconomic and environmental variables and how these can influence progress. Saudi Arabia’s economy relies heavily on its vast reserves of petroleum, natural gas, iron ore, gold, and copper, but its economic growth trajectory has been uneven since the 1990s. This study examines the effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia. Methods Annual time series dataset covering the period 1990–2019 has been extracted from the World Bank and General Authority of Meteorology and Environmental Protection, Saudi Arabia. The Autoregressive Distributed Lag (ARDL) approach to cointegration has served to investigate the long-run relationships among the variables. Several time-series diagnostic tests have been conducted on the long-term ARDL model to check its robustness. Results Saudi Arabia can still achieve higher economic growth without effectively addressing its unemployment problem as both the variables are found to be highly significantly but positively cointegrated in the long-run ARDL model. While the variable of carbon emissions demonstrated a negative effect on the nation’s economic growth, the variables of rainfall and temperate were to some extent cointegrated into the nation’s economic growth in negative and positive ways, respectively. Like most other nations the short-run effects of inflation and population on economic growth do vary, but their long-term effects on the same are found to be positive. Conclusions Saudi Arabia can achieve both higher economic growth and lower carbon emissions simultaneously even without effectively addressing the unemployment problem. The nation should utilize modern scientific technologies to annual rainfall losses and to reduce annual temperature in some parts of the country in order to achieve higher economic growth.

scholarly journals Incorporating large-scale atmospheric variables in long-term seasonal rainfall forecasting using artificial neural networks: an application to the Ping Basin in Thailand

2016 ◽  
Vol 48 (3) ◽  
pp. 867-882 ◽  
Author(s):  
M. S. Babel ◽  
T. A. J. G. Sirisena ◽  
N. Singhrattna
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Large Scale ◽  
Resource Planning ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Rainfall Forecasting ◽  
Artificial Neural ◽  
Atmospheric Variables

Understanding long-term seasonal or annual or inter-annual rainfall variability and its relationship with large-scale atmospheric variables (LSAVs) is important for water resource planning and management. In this study, rainfall forecasting models using the artificial neural network technique were developed to forecast seasonal rainfall in May–June–July (MJJ), August–September–October (ASO), November–December–January (NDJ), and February–March–April (FMA) and to determine the effects of climate change on seasonal rainfall. LSAVs, temperature, pressure, wind, precipitable water, and relative humidity at different lead times were identified as the significant predictors. To determine the impacts of climate change the predictors obtained from two general circulation models, CSIRO Mk3.6 and MPI-ESM-MR, were used with quantile mapping bias correction. Our results show that the models with the best performance for FMA and MJJ seasons are able to forecast rainfall one month in advance for these seasons and the best models for ASO and NDJ seasons are able do so two months in advance. Under the RCP4.5 scenario, a decreasing trend of MJJ rainfall and an increasing trend of ASO rainfall can be observed from 2011 to 2040. For the dry season, while NDJ rainfall decreases, FMA rainfall increases for the same period of time.

scholarly journals COSMIC ACCELERATION AND CONCORDANCE FROM CAUSAL BACKREACTION WITH RECURSIVE NONLINEARITIES

2013 ◽  
Vol 22 (13) ◽  
pp. 1330026 ◽  
Author(s):  
BRETT BOCHNER
Keyword(s):  
Dark Energy ◽  
Large Scale ◽  
Cosmic Acceleration ◽  
Late Time ◽  
Clustering Model ◽  
Hierarchical Nature ◽  
The Universe ◽  
Far Future ◽  
Apparent Acceleration

We review the causal backreaction paradigm, in which the need for Dark Energy is eliminated via the generation of an apparent cosmic acceleration from the causal flow of inhomogeneity information coming in from distant structure-forming regions. The formalism detailed here incorporates the effects of "recursive nonlinearities": the process by which already-established metric perturbations will subsequently act to slow-down all future flows of inhomogeneity information. Despite such effects, we find viable cosmological models in which causal backreaction successfully serves as a replacement for Dark Energy, via the adoption of relatively large values for the dimensionless "strength" of the clustering evolution functions being modeled. These large values are justified by the hierarchical nature of clustering and virialization in the universe, which occurs on multiple cosmic length scales simultaneously; moreover, the clustering model amplitudes needed to match the apparent acceleration can be moderated via the incorporation of a model parameter representing the late-time slow-down of clustering due to astrophysical feedback processes. In summary, an alternative cosmic concordance can be achieved for a matter-only universe in which the apparent acceleration observed is generated entirely by causal backreaction effects. Lastly, considering the long-term fate of the universe, while the possibility of an "eternal" acceleration due to causal backreaction seems unlikely, this conclusion does not take into account the large-scale breakdown of cosmological isotropy in the far future, or the eventual ubiquity of gravitationally-nonlinear perturbations.

Reconstructing crop yield variability in Finland: Long-term perspective of the cultivation history on the agricultural periphery since ad 760

The Holocene ◽  
2016 ◽  
Vol 27 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Heli Huhtamaa ◽  
Samuli Helama
Keyword(s):  
Crop Production ◽  
Wide Spectrum ◽  
Climatic Conditions ◽  
Yield Ratio ◽  
Study Region ◽  
Crop Cultivation ◽  
The North ◽  
Long Run ◽  
High Yields

Lack of documentation on past harvest fluctuations limits the exploration of long-term trends in crop production and agricultural adaptation strategies. A long-term perspective is needed, however, to understand the wide spectrum of potential human responses to environment and climate change. Therefore, we used tree-ring density series as proxy data to reconstruct climate-mediated yield ratio (harvested grain in relation to sown) in central and northern Finland over the period ad 760–2000. The reconstruction explains 50% of the variance in recorded yield ratio variability over the calibration period (ad 1866–1921). The reconstruction illustrated several intervals of increased and reduced yield ratio over the past 13 centuries. The long-term development of the agricultural prerequisites is characterized by distinct intervals defined statistically as ad 760–1106 (highest yield ratios), 1107–1451, 1452–1694, 1695–1911 (lowest yield ratios) and 1912 onwards. The results provide insight into the establishment and development of crop cultivation in the agricultural margin. The reconstruction suggests that continuous crop cultivation was established in the study region during a favourable period of climatic conditions supporting high yields. Thereafter, the climate-mediated yield ratio declined in the long run until the turn of the 20th century. Periods of agricultural transformations, those previously demonstrated in pollen data and historical documents, followed the onsets of the low yield ratio phases indicated by our reconstruction. Thus, we suggest that ever since the establishment of crop cultivation, climate can be considered as an important factor contributing to the development of the agricultural history in the north.

scholarly journals Variability of seasonal and annual rainfall in the River Nile riparian countries and possible linkages to ocean–atmosphere interactions

2015 ◽  
Vol 47 (1) ◽  
pp. 171-184 ◽  
Author(s):  
Charles Onyutha
Keyword(s):  
Large Scale ◽  
Equatorial Region ◽  
Annual Rainfall ◽  
River Nile ◽  
Short Term ◽  
Ocean Atmosphere ◽  
Data Points ◽  
The Difference ◽  
Term Data

Variability analyses for the rainfall over the Nile Basin have been confined mostly to sub-basins and the annual mean of the hydroclimatic variable based on observed short-term data from a few meteorological stations. In this paper, long-term country-wide rainfall over the period 1901–2011 was used to assess variability in the seasonal and annual rainfall volumes in all the River Nile countries in Africa. Temporal variability was determined through temporal aggregation of series rescaled nonparametrically in terms of the difference between the exceedance and non-exceedance counts of data points such that the long-term average (taken as the reference) was zero. The co-occurrence of the variability of rainfall with those of the large-scale ocean–atmosphere interactions was analyzed. Between 2000 and 2012, while the rainfall in the equatorial region was increasing, that for the countries in the northern part of the River Nile was below the reference. Generally, the variability in the rainfall of the countries in the equatorial (northern) part of the River Nile was found to be significantly linked to occurrences in the Indian and Atlantic (Pacific and Atlantic) Oceans. Significant linkages to Niño 4 regarding the variability of both the seasonal and annual rainfall of some countries were also evident.

scholarly journals Rainfall Recovery in North-East Arid Zone of Nigeria: Comparative Analysis of Drought and Post Drought Decades

2021 ◽  
pp. 1-16
Author(s):  
Ahmed Abubakar Jajere ◽  
Adam Modu Abbas ◽  
Ali Abdu
Keyword(s):  
Arid Zone ◽  
Local Population ◽  
Mitigation Strategies ◽  
Annual Rainfall ◽  
Rainfall Characteristics ◽  
North East ◽  
The North ◽  
Sahel Rainfall ◽  
Mean Trend

This study used annual rainfall records from three stations within the North East Arid Zone of Nigeria for the period (1957-2017) to measure the extent of the rainfall recovery by comparing the drought decades and post drought decades rainfall patterns. Monthly rainfall records from Potiskum, Maiduguri and Nguru Stations were used. Descriptive and inferential statistical tools were employed in analysing the data. The findings of the study revealed a significant year-to-year variability in rainfall characteristics around 61 years (1957-2017) averages. The variability was large in 1970s up till 1990s, and lower in 1960s and from 2000 to 2018. Decreasing trend in annual rainfall amount was observed during the study period while a stability in onset and cessation dates were observed. The differences between 1957-1986 and 1987-2017 climatic season were found to be statistically insignificant. The study concluded that the reported rainfall recovery from drought is statistically insignificant and the observed long term mean trend revealed a decreasing trend. Therefore, the theory of Sahel rainfall recovery can be better termed as a ‘’break of the series of drought or decline in frequency and magnitude of occurrence of drought’’ The research recommended the continuations with the drought adaptation and mitigation strategies adopted by local population, decisions makers and organizations following the series Sahelian droughts of 1970s and 1980s.

scholarly journals Spatio -Temporal Long-Term Variability and Trend Analysis of Precipitation and Temperature Series in the Ghataprabha (K3) Sub basin of Krishna Basin

2019 ◽  
Vol 8 (11) ◽  
pp. 2547-2552
Keyword(s):  
India Meteorological Department ◽  
Well Being ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Study Region ◽  
Changing Climate ◽  
Increasing Trend ◽  
Precipitation And Temperature ◽  
Krishna Basin

Changing Climate is one of the most significant ecological issue, with the implications for agricultural production, water resource, energy and some other aspects of human well-being. Analysis of changing climate is important to assess climate-induced changes through the analysis of variability of climatic parameters such as temperature, precipitation, runoff and groundwater to suggest feasible adaptation strategies. This paper aims the long-term variability of rainfall and temperature using gridded daily data obtained from India Meteorological Department with 0.250 resolution from 1901-2016 for precipitation and 10 resolution from 1969-2005 for temperature (re-gridded to IMD 0.250 gridded location) in Ghataprabha sub basin (K3) of Krishna basin. The analysis of variability and trend in precipitation and temperature carried out by using coefficient of variation (CV), rainfall and temperature anomaly and also Mann-Kendall (MK) test was used to detect the time series trend. Statistical analysis of variability and trend in annual, Indian Summer Monsoon (ISMR) rainfall and temperature observed that i) there is an intra and inter annual variability of precipitation in the sub basin ii) test results revealed that the annual and ISMR trend appears to be increased by 0.12 & 0.14, iii) the Mann-Kendal trend test also analysed for annual minimum, mean and maximum temperature over the K3 sub basin (1969-2005) shows increasing trend by 0.06, 0.21 and 0.40. This analysis revealed that, there is an increasing trend in annual rainfall and temperature observed over the study region.

scholarly journals Migration restrictions and long-term regional development: evidence from large-scale expulsions of Germans after World War II

2019 ◽  
Author(s):  
Michael Wyrwich
Keyword(s):  
World War Ii ◽  
Soviet Union ◽  
Regional Development ◽  
Large Scale ◽  
Spatial Equilibrium ◽  
World War ◽  
Temporary Migration ◽  
Common Trend ◽  
Long Run

AbstractThis article investigates the long-run impact of a migration barrier on regional development. The analysis is based on the large-scale expulsion of Germans from Central and Eastern Europe after World War II (WWII). Expellees were not allowed to resettle in the French occupation zone in the first years after the War while there was no such legislation in the other occupation zones (USA; UK; Soviet Union). The temporary migration barrier had long-lasting consequences. In a nutshell, results of a Difference-in-Difference (DiD) analysis show that growth of population and population density were significantly lower even 60 years after the removal of the barrier if a region was part of the French occupation zone. There was a common trend in regional development before the migration barrier became effective. Further analyses suggest that this pattern is driven by different population dynamics in agglomerated areas. The article discusses implications for spatial theory namely whether location fundamentals, agglomeration theories or both affect the spatial equilibrium under certain conditions.

scholarly journals Identifying Ecosystem Function Shifts in Africa Using Breakpoint Analysis of Long-Term NDVI and RUE Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1894
Author(s):  
Thomas P. Higginbottom ◽  
Elias Symeonakis
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Vegetation Index ◽  
Change Point Analysis ◽  
Annual Rainfall ◽  
Small Scale ◽  
Growth Season ◽  
Continental Scale ◽  
Normalised Difference Vegetation Index

Time-series of vegetation greenness data, derived from Earth-observation imagery, have become a key source of information for studying large-scale environmental change. The ever increasing length of such series allows for a range of indicators to be derived and for increasingly complex analyses to be applied. This study presents an analysis of trends in vegetation productivity—measured using the Global Inventory Monitoring and Modelling System third generation (GIMMS3g) Normalised Difference Vegetation Index (NDVI) data—for African savannahs, over the 1982–2015 period. Two annual metrics were derived from the 34 year dataset: the monthly, smoothed NDVI (the aggregated growth season NDVI) and the associated Rain Use Efficiency (growth season NDVI divided by annual rainfall). These indicators were then used in a BFAST-based change-point analysis, allowing the direction of change over time to change and the detection of one major break in the time-series. We also analysed the role of land cover type and climate zone as associations of the observed changes. Both methods agree that vegetation greening was pervasive across African savannahs, although RUE displayed less significant changes than NDVI. Monotonically increasing trends were the most common trend type for both indicators. The continental scale of the greening may suggest global processes as key drivers, such as carbon fertilization. That NDVI trends were more dynamic than RUE suggests that a large component of vegetation trends is driven by precipitation variability. Areas of negative trends were conspicuous by their minimalism. However, some patterns were apparent. In the southern Sahel and West Africa, declining NDVI and RUE overlapped with intensive population and agricultural regions. Dynamic trend reversals, in RUE and NDVI, located in Angola, Zambia and Tanzania, coincide with areas where a long-term trend of forest degradation and agricultural expansion has recently given way to increases in woody biomass. Meanwhile in southern Africa, monotonic increases in RUE with varying NDVI trend types may be indicative of shrub encroachment. However, all these processes are small-scale relative to the GIMMS NDVI data, and reconciling these conflicting drivers is not a trivial task. Our study highlights the importance of considering multiple options when undertaking trend analyses, as different inputs and methods can reveal divergent patterns.

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