scholarly journals Spatial Pattern of the Unidirectional Trends in Thermal Bioclimatic Indicators in Iran

2019 ◽  
Vol 11 (8) ◽  
pp. 2287 ◽  
Author(s):  
Sahar Hadi Pour ◽  
Ahmad Abd Wahab ◽  
Shamsuddin Shahid ◽  
Xiaojun Wang
Keyword(s):  
Data Series ◽  
Self Similarity ◽  
Meteorological Forcing ◽  
Mk Test ◽  
Spatio Temporal ◽  
Grid Points ◽  
The Persian Gulf ◽  
Almost All ◽  
Bioclimatic Indicators ◽  
Natural Cycles

Changes in bioclimatic indicators can provide valuable information on how global warming induced climate change can affect humans, ecology and the environment. Trends in thermal bioclimatic indicators over the diverse climate of Iran were assessed in this study to comprehend their spatio-temporal changes in different climates. The gridded temperature data of Princeton Global Meteorological Forcing with a spatial resolution of 0.25° and temporal extent of 1948–2010 was used for this purpose. Autocorrelation and wavelets analyses were conducted to assess the presence of self-similarity and cycles in the data series. The modified version of the Mann–Kendall (MMK) test was employed to estimate unidirectional trends in 11 thermal bioclimatic indicators through removing the influence of natural cycles on trend significance. A large decrease in the number of grid points showing significant trends was noticed for the MMK in respect to the classical Mann–Kendall (MK) test which indicates that the natural variability of the climate should be taken into consideration in bioclimatic trend analyses in Iran. The unidirectional trends obtained using the MMK test revealed changes in almost all of the bioclimatic indicators in different parts of Iran, which indicates rising temperature have significantly affected the bioclimate of the country. The semi-dry region along the Persian Gulf in the south and mountainous region in the northeast were found to be more affected in terms of the changes in a number of bioclimatic indicators.

Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: implications for ecosystem-based fisheries management

2020 ◽  
Vol 637 ◽  
pp. 117-140 ◽  
Author(s):  
DW McGowan ◽  
ED Goldstein ◽  
ML Arimitsu ◽  
AL Deary ◽  
O Ormseth ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Gulf Of Alaska ◽  
Data Series ◽  
Limited Information ◽  
Important Species ◽  
Multiple Data ◽  
Spatial And Temporal Dynamics ◽  
Spawning Areas ◽  
Spatio Temporal

Pacific capelin Mallotus catervarius are planktivorous small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, limited information is available on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affect their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially indexed data from multiple independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicate that the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

scholarly journals Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Yongxiao Ge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
River Runoff ◽  
Temporal Trends ◽  
Temporal Distribution ◽  
Trend Test ◽  
Data Series ◽  
Mk Test ◽  
Comparison Results ◽  
Innovative Trend Analysis

This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the “peak” values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for “low” values, and 40 time series (44.94%) showed increasing patterns for “medium” values. According to the “low”, “medium”, and “peak” values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating “low”, “medium”, and “peak” values.

Changing Work and Work-Related Travel and the Impact of Covid-19

2021 ◽  
Vol 47 (3) ◽  
pp. 336-354
Author(s):  
Kiron Chatterjee ◽  
Fiona Crawford
Keyword(s):  
Health Outcomes ◽  
Digital Age ◽  
Data Series ◽  
Work Related ◽  
Policy Interventions ◽  
Working Practices ◽  
Key Features ◽  
The Uk ◽  
Almost All ◽  
The Impact

The nature of work was undergoing dramatic change before the pandemic as the digital age continued to transform all sectors of society. In this paper we describe pre-pandemic trends in types of work, the workforce and working arrangements in the UK. We show how these changes were having gradual yet significant impacts on commuting and other work-related travel which were apparent in national travel data series. Key features of these impacts were increasing diversification and flexibility in work travel. We bring together findings on how working practices and travel have been altered by the pandemic and report expectations and opinions on its longer-term legacies. The pandemic has accelerated pre-pandemic trends and led to a shift in how work is performed for almost all sectors of the economy – but grasping the opportunity for this to contribute to deep carbon reductions from transport and to improve equity and health outcomes will require carefully directed policy interventions.

Spatio-temporal variability of temperature and potential evapotranspiration over India

2016 ◽  
Vol 7 (4) ◽  
pp. 810-822 ◽  
Author(s):  
P. Sonali ◽  
D. Nagesh Kumar
Keyword(s):  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Grid Point ◽  
Rank Correlation ◽  
Trend Detection ◽  
Detection Analysis ◽  
Change Impact ◽  
Spatio Temporal ◽  
Grid Points ◽  
Significant Factors

Worldwide, major changes in the climate are expected due to global warming, which leads to temperature variations. To assess the climate change impact on the hydrological cycle, a spatio-temporal change detection study of potential evapotranspiration (PET) along with maximum and minimum temperatures (Tmax and Tmin) over India have been performed for the second half of the 20th century (1950–2005) both at monthly and seasonal scale. From the observed monthly climatology of PET over India, high values of PET are envisioned during the months of March, April, May and June. Temperature is one of the significant factors in explaining changes in PET. Hence seasonal correlations of PET with Tmax and Tmin were analyzed using Spearman rank correlation. Correlation of PET with Tmax was found to be higher compared to that with Tmin. Seasonal variability of trend at each grid point over India was studied for Tmax, Tmin and PET separately. Trend Free Pre-Whitening and Modified Mann Kendall approaches, which consider the effect of serial correlation, were employed for the trend detection analysis. A significant trend was observed in Tmin compared to Tmax and PET. Significant upward trends in Tmax, Tmin and PET were observed over most of the grid points in the interior peninsular region.

scholarly journals A Critical Analysis of Mercosur Countries’ Trade Relationships with the United States and China

2016 ◽  
Vol 10 (1) ◽  
pp. 163
Author(s):  
M. Anaam Hashmi
Keyword(s):  
United States ◽  
International Trade ◽  
Trade Deficit ◽  
The United States ◽  
Data Series ◽  
The European Union ◽  
Full Member ◽  
Strategic Goals ◽  
Almost All ◽  
Export Industries

The Mercosur trade alliance formed in 1991 is composed of six full member countries. Historically, Mercosur member countries have been engaged in international trade with the United States, Japan, and the European Union, but recently, China has become a dominant player in the region, with increased foreign direct investment and international trade. Chinese commercial and trade involvement was followed by a visit to the region by President Jiang Zemin in 2001; therefore, this study relied on a 2000–2015 data series. Chinese enterprises are competing well with U.S. corporations in almost all Mercosur member countries. A majority of Mercosur members had a trade deficit with China in recent years, suggesting that Mercosur members cannot leverage their export industries and are losing their competitiveness. The future of the Mercosur-China trade relationship is bright because both sides require each other’s products. Future involvement also depends on the Chinese government’s strategic goals, and the competitiveness of U.S. corporations.

scholarly journals Water vapor pressure trends in south and southwest Iran

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 335-348
Author(s):  
YOUNES KHOSRAVI ◽  
HASAN LASHKARI ◽  
HOSEIN ASAKEREH
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Vapor Pressure ◽  
Water Vapor Pressure ◽  
Sen’S Slope Estimator ◽  
Sen’S Slope ◽  
Ground Station ◽  
Mk Test ◽  
Slope Estimator ◽  
The Persian Gulf

Recognitionanddetectionofclimaticparameters inhave animportant role inclimate change monitoring. In this study, the analysis of oneofthe most importantparameters, water vapor pressure (WVP), was investigated. For this purpose, two non-parametric techniques, Mann-Kendall and Sen's Slope Estimator, were used to analyze the WVP trend and to determine the magnitude of the trends, respectively. To analyze these tests, ground station observations [10 stations for period of 44 years (1967-2010)] and gridded data [pixels with the dimension of 9 × 9 km over a 30-year period (1981-2010)] in South and SouthwestofIran were used. By programming in MATLAB software, the monthly, seasonal and annual WVP time series were extracted and MK and Sen's slope estimator tests were done. The results of monthly MK test on ground station observations showed that the significant downward trends are more considerable than significant upward trends. It also showed that the WVP highest frequency was more in warm months, April to September and the highest frequency of significant trends slope was in February and May. The spatial distribution of MK test of monthly gridded WVP time series showed that the upward trends were detected mostly in western zone and near the Persian Gulf in August. On the other hand, the downward trends through months. The maximum and minimum values of positive trends slope occurred in warm months and cold months, respectively. The analysis of the MK test of the annual WVP time series indicated the upward significant trends in the southeast and southwest zones of study area.  

scholarly journals Study on the spatial-temporal variation in evapotranspiration in China from 1948 to 2018

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Feng Zhang ◽  
Mengqing Geng ◽  
Qiulan Wu ◽  
Yong Liang
Keyword(s):  
Spatial Variation ◽  
Temporal Variation ◽  
Basic Research ◽  
Variation Coefficient ◽  
Data Sets ◽  
The North ◽  
Mk Test ◽  
Increasing Trend ◽  
Land Data Assimilation System ◽  
Almost All

Abstract It is of great significance for the efficient utilization of water resources and the construction of the ecological environment in China to fully understand the evolution process of the spatial-temporal pattern of evapotranspiration (ET). With the use of the v2.0 and v2.1 ET data sets combined with the Global Land Data Assimilation System and Noah model, this paper selects pixels as the basic research object to analyse the spatial-temporal variation in ET in China during the 71 years from 1948 to 2018. We first applied the TFPW-MK test to study the annual ET trend in China throughout the 71-year period, including the ET trend of each month from January to December and the annual total ET trend. Moreover, we examined the spatial variation in these trends. In addition, we calculated the variation coefficient of the time series of each pixel’s ET throughout the 71-year period and the variation coefficient of the spatial distribution of ET in each year to analyse the spatial-temporal fluctuations in ET in the study area. Finally, the Hurst index was adopted to evaluate the future ET trend. Based on these analyses, we observed the following novel spatial-temporal characteristics of ET: from 1948 to 2018, (1) the ET in most regions covered by 89.5% of all pixels in China exhibits an increasing trend. (2) The ET trend in China varies greatly with the change in months, and many regions show the most or least obvious increasing trend (or decreasing trend) at different times. (3) The area with an increasing trend is the largest in May and the smallest in December, and more than half of the pixels in all months of a year reveal an increasing trend. (4) In the northeast, west and south regions of China, the monthly fluctuation in the ET trend is relatively large, which indicates that the ET trend in these regions is greatly affected by the month. (5) The fluctuation in ET in China is larger in the north than it is in the south and larger in the west than it is in the east. The most stable fluctuation occurs in East China. (6) The ET trend of almost all the pixels in the study area remains consistent from 1948 to 2018, and there are large areas with a notable continuity. This results in the spatial variation in ET in the study area increasing.

A Frequency-Domain, Finite-Order Representation of a Catenary Riser’s Dominant Nonlinear Dynamics

2013 ◽  
Author(s):  
Dimitris C. Kazangas ◽  
Nikolaos I. Xiros ◽  
Ioannis K. Chatjigeorgiou
Keyword(s):  
Frequency Domain ◽  
Dynamic Equilibrium ◽  
Nonlinear Partial Differential Equations ◽  
Bending Moment ◽  
Data Series ◽  
Test Case ◽  
Domain Identification ◽  
Spatio Temporal ◽  
Value Decomposition ◽  
Nonlinear Signal

A numerical simulation and system identification approach to the dynamic equilibrium of a catenary riser has been developed. A finite DOF representation of the dominant dynamics is constructed using frequency domain identification by applying nonlinear signal theory techniques on response data series when exciting the structure with sinusoidal motions at the top. Data series are obtained through numerical integration of a finite differences simulation model on the basis of the six nonlinear partial differential equations describing the riser dynamics. Dynamic equilibrium is mathematically formulated by the very same equations that implicate both geometric and hydrodynamic nonlinearities; the latter are depicted by Morison’s formula. Thus, spatio-temporal series are generated for riser bending moments induced by sinusoidal heave motions of various amplitudes and frequencies. These data are consequently transformed to the frequency domain where complex Singular Value Decomposition is applied in order to derive the full nonlinear spectrum. The significant harmonics of the riser’s spectrum for the bending moment on the 2D plane of reference are demonstrated to be the three lower odd harmonics and a set of orthogonal modes for these three significant harmonics is derived. The methodology proposed is finally applied to a typical test case for validation.

scholarly journals Mesocell Study Area Snow Distributions for the Cold Land Processes Experiment (CLPX)

2008 ◽  
Vol 9 (5) ◽  
pp. 957-976 ◽  
Author(s):  
Glen E. Liston ◽  
Christopher A. Hiemstra ◽  
Kelly Elder ◽  
Donald W. Cline
Keyword(s):  
Snow Water Equivalent ◽  
Distribution Patterns ◽  
Snow Accumulation ◽  
Meteorological Model ◽  
Meteorological Forcing ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Snow Water ◽  
Grid Points ◽  
Evolution Modeling

Abstract The Cold Land Processes Experiment (CLPX) had a goal of describing snow-related features over a wide range of spatial and temporal scales. This required linking disparate snow tools and datasets into one coherent, integrated package. Simulating realistic high-resolution snow distributions and features requires a snow-evolution modeling system (SnowModel) that can distribute meteorological forcings, simulate snowpack accumulation and ablation processes, and assimilate snow-related observations. A SnowModel was developed and used to simulate winter snow accumulation across three 30 km × 30 km domains, enveloping the CLPX mesocell study areas (MSAs) in Colorado. The three MSAs have distinct topography, vegetation, meteorological, and snow characteristics. Simulations were performed using a 30-m grid increment and spanned the snow accumulation season (1 October 2002–1 April 2003). Meteorological forcing was provided by 27 meteorological stations and 75 atmospheric analyses grid points, distributed using a meteorological model (MicroMet). The simulations included a data assimilation model (SnowAssim) that adjusted simulated snow water equivalent (SWE) toward ground-based and airborne SWE observations. The observations consisted of SWE over three 1 km × 1 km intensive study areas (ISAs) for each MSA and a collection of 117 airborne gamma observations, each integrating area 10 km long by 300 m wide. Simulated SWE distributions displayed considerably more spatial heterogeneity than the observations alone, and the simulated distribution patterns closely fit the current understanding of snow evolution processes and observed snow depths. This is the result of the MicroMet/SnowModel’s relatively finescale representations of orographic precipitation, elevation-dependant snowmelt, wind redistribution, and snow–vegetation interactions.

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