scholarly journals Spatial-Temporal Variation of Aridity Index of China during 1960–2013

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Huiping Huang ◽  
Yuping Han ◽  
Mingming Cao ◽  
Jinxi Song ◽  
Heng Xiao
Keyword(s):  
Temporal Variation ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Aridity Index ◽  
Principal Component ◽  
Kendall Test ◽  
Semiarid Region ◽  
Climate Data ◽  
Gis Technology ◽  
Important Indicator

Aridity index, as the ration of potential evapotranspiration and precipitation, is an important indicator of regional climate. GIS technology, Morlet wavelet, Mann-Kendall test, and principal component analysis are utilized to investigate the spatial-temporal variation of aridity index and its impacting factors in China on basis of climate data from 599 stations during 1960–2013. Results show the following. (1) Boundaries between humid and semihumid region, and semihumid and semiarid region coincide with 400 mm and 800 mm precipitation contour lines. (2) Average annual aridity index is between 3.4 and 7.5 and shows decrease trend with a tendency of –0.236 per decade at 99% confidence level. (3) The driest and wettest month appear in December and July, respectively, in one year. (4) Periods of longitudinal and latitudinal shift of aridity index 1, 1.5, and 4 contours coordinate are 10 and 25 years, 6 and 26 years, and 5 and 25 years, respectively. (5) Four principal components which affect aridity index are thermodynamic factors, water and radiation factors, geographical and air dynamic factors, and evaluation factor, respectively.

scholarly journals Climate Data to Predict Geometry of Cracks in Expansive Soils in a Tropical Semiarid Region

2022 ◽  
Vol 14 (2) ◽  
pp. 675
Author(s):  
Jacques Carvalho Ribeiro Filho ◽  
Eunice Maia de Andrade ◽  
Maria Simas Guerreiro ◽  
Helba Araujo de Queiroz Palácio ◽  
José Bandeira Brasil
Keyword(s):  
Environmental Factors ◽  
Potential Evapotranspiration ◽  
Expansive Soils ◽  
Clay Content ◽  
Field Conditions ◽  
Semiarid Region ◽  
Climate Change Scenarios ◽  
Climate Data ◽  
Morphometric Characteristics ◽  
Very High

The nonlinear dynamics of the determining factors of the morphometric characteristics of cracks in expansive soils make their typification a challenge, especially under field conditions. To overcome this difficulty, we used artificial neural networks to estimate crack characteristics in a Vertisol under field conditions. From July 2019 to June 2020, the morphometric characteristics of soil cracks (area, depth and volume), and environmental factors (soil moisture, rainfall, potential evapotranspiration and water balance) were monitored and evaluated in six experimental plots in a tropical semiarid region. Sixty-six events were measured in each plot to calibrate and validate two sets of inputs in the multilayer neural network model. One set was comprised of environmental factors with significant correlations with the morphometric characteristics of cracks in the soil. The other included only those with a significant high and very high correlation, reducing the number of variables by 35%. The set with the significant high and very high correlations showed greater accuracy in predicting crack characteristics, implying that it is preferable to have fewer variables with a higher correlation than to have more variables of lower correlation in the model. Both sets of data showed a good performance in predicting area and depth of cracks in the soils with a clay content above 30%. The highest dispersion of modeled over predicted values for all morphometric characteristics was in soils with a sand content above 40%. The model was successful in evaluating crack characteristics from environmental factors within its limitations and may support decisions on watershed management in view of climate-change scenarios.

scholarly journals Aridity Trend in the Middle East and the Adjacent Areas

2020 ◽  
Author(s):  
Hossein Sahour ◽  
Mehdi Vazifehdan ◽  
Fahad Alshehri
Keyword(s):  
Middle East ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Kendall Test ◽  
Adjacent Area ◽  
The North ◽  
Percent Increase ◽  
Water Scarce ◽  
Annual Time ◽  
Percent Decrease

Available water resources in the Middle East, as one of the most water-scarce regions of the world, have undergone extra pressure due to climatic change, population growth, and economic development during the past decades. The objective of this study is to detect the trends and quantify the changes in aridity with respect to precipitation and potential evapotranspiration in 20 countries of the Middle East and the adjacent area. A Pixel-wised trend analysis was conducted on precipitation, potential evapotranspiration, and aridity index for 71 years from 1948 to 2018. A nonparametric Mann-Kendall test was used over 14106 points in the study area to detect the trends at monthly and annual time scales. Results showed statistically significant (|Z| >1.96) upward trends in aridity (a downward trend in aridity index) up to 96 percent from December through September in most parts of the region. Aridity in October and November had a downward tendency in most parts of the study area. At the annual time scale, 62.5 percent of the statistically significant trends in aridity were found to be upward (up to 96 percent increase in aridity) due to the combined effects of the decrease in precipitation and the increase in potential evapotranspiration and 37.5 percent of the detected trends were downward (up to 61 percent decrease in aridity). The highest and the lowest trends in aridity were found in the north of Sudan (96 percent increase in aridity) and Eastern Arabia (61 percent decrease in aridity), respectively.

scholarly journals Agroclimatic zonation of Tigray region of Ethiopia based on aridity index and traditional agro-climatic zones

2021 ◽  
Vol 21 (2) ◽  
pp. 176-181
Author(s):  
H. HAFTOM ◽  
A. HAFTU ◽  
K. GOITOM ◽  
H. MESERET
Keyword(s):  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Climate Data ◽  
Climate Services ◽  
Climatic Zones ◽  
Tigray Region ◽  
Agroclimatic Zone ◽  
Elevation Model ◽  
Agroclimatic Zones ◽  
Semi Arid

The aim of this study was to identify the agroclimatic zones of Tigray region based on aridity index and traditional agroclimatic zone using 37-year (1981-2017) spatial climate data downloaded for Tigray region from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) for rainfall and from Enhancing National Climate Services (ENACTS) data for temperature. Arc map 10.3 was used for mapping of all climatic variables and zonation of agro-climatic zones. Potential evapotranspiration (PET) was computed based on Hargreaves formula and the aridity index was computed. Besides, the digital elevation model was downloaded from ASTER data. The aridity map of Tigray divided into three index zones (0.03-0.2, 0.2–0.5 and 0.5–0.65) and five traditional agro-climate zones (<1500,1500-2000,2000- 2500, 2500-3000, >3000 m.a.s.l.) were overlaid, which divided entire region of Tigray into fifteen agroclimatic zones. Hot semi-arid, warm semi-arid, tepid semi-arid and hot arid were the dominant zones in the region.

scholarly journals Regional climate model data used within the SWURVE project – 1: projected changes in seasonal patterns and estimation of PET

2007 ◽  
Vol 11 (3) ◽  
pp. 1069-1083 ◽  
Author(s):  
M. Ekström ◽  
P. D. Jones ◽  
H. J. Fowler ◽  
G. Lenderink ◽  
T. A. Buishand ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Large Temperature ◽  
Hydraulic Systems ◽  
Climate Data ◽  
North West ◽  
North East

Abstract. Climate data for studies within the SWURVE (Sustainable Water: Uncertainty, Risk and Vulnerability in Europe) project, assessing the risk posed by future climatic change to various hydrological and hydraulic systems were obtained from the regional climate model HadRM3H, developed at the Hadley Centre of the UK Met Office. This paper gives some background to HadRM3H; it also presents anomaly maps of the projected future changes in European temperature, rainfall and potential evapotranspiration (PET, estimated using a variant of the Penman formula). The future simulations of temperature and rainfall, following the SRES A2 emissions scenario, suggest that most of Europe will experience warming in all seasons, with heavier precipitation in winter in much of western Europe (except for central and northern parts of the Scandinavian mountains) and drier summers in most parts of western and central Europe (except for the north-west and the eastern part of the Baltic Sea). Particularly large temperature anomalies (>6°C) are projected for north-east Europe in winter and for southern Europe, Asia Minor and parts of Russia in summer. The projected PET displayed very large increases in summer for a region extending from southern France to Russia. The unrealistically large values could be the result of an enhanced hydrological cycle in HadRM3H, affecting several of the input parameters to the PET calculation. To avoid problems with hydrological modelling schemes, PET was re-calculated, using empirical relationships derived from observational values of temperature and PET.

scholarly journals Long Term Spatio-temporal Variations of Seasonal and Decadal Aridity in India

2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Pavan Kumar B ◽  
Bhavani Pinjarla ◽  
P K Joshi ◽  
P S Roy
Keyword(s):  
Water Resource Management ◽  
Arid Zone ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Temporal Variations ◽  
United Nations Environment Programme ◽  
Climate Data ◽  
Land Use Pattern ◽  
Changing Patterns ◽  
Spatio Temporal

A comprehensive analysis of climate data (1958-2018) is carried out at the national scale in India to assess spatiotemporal variation in aridity. The aridity is analyzed using UNEP (United Nations Environment Programme) Aridity Index (AI), which is the ratio between Precipitation (P) and Potential Evapotranspiration (PET). Freely available Terra-Climate database, P and PET variables, offered an unprecedented opportunity for monitoring variations in AI and aridity index anomalies (AIA) at interseasonal and inter-decadal basis. The study also assesses longer term patterns of P and AI anomalies with vegetation anomalies. The results indicate that significant clustered areas with maximum dryness are located at west-central part of India, the state of Maharashtra. Overall, there is a gradual increase in the extent of arid zone during 60-year period and spatially maximum extent of percentage change in aridity area is observed. The change patterns of AI in India are largely driven by the changing patterns of precipitation. The maximum impact of decline in precipitation on AIA was observed during Kharif season frequently, for every 4-5 years during 1972-1992. The pattern repeated in the last few recent years (2013- 2018), the decline in precipitation resulted increased aridity. The study also reveals that the availability and usage of irrigation sources have increased from 2014 to 2018. Thus, despite of less precipitation positive vegetation has been resulted in this period. The findings are important to understand the impacts of climate change on land use pattern, and land and water resource management.

scholarly journals The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

2010 ◽  
Vol 14 (11) ◽  
pp. 2193-2205 ◽  
Author(s):  
J. L. Peña-Arancibia ◽  
A. I. J. M. van Dijk ◽  
M. Mulligan ◽  
L. A. Bruijnzeel
Keyword(s):  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Global Scale ◽  
Tree Cover ◽  
Annual Rainfall ◽  
Ungauged Catchments ◽  
Ongoing Research ◽  
Daily Streamflow ◽  
Terrain Attributes ◽  
Streamflow Data

Abstract. The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m3 s–1) from the Global River Discharge Center (GRDC) and a linear reservoir model were used to obtain baseflow recession coefficients (kbf) for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR) and aridity index (AI) were found to explain 49% of the spatial variation of kbf. The rest of climatic indices and the terrain indices average catchment slope (SLO) and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE), a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for kbf parameterisation in ungauged catchments.

scholarly journals Spatial distribution and temporal variation of microcrustaceans assembly (Cladocera and Copepoda) in different compartments of a reservoir in the brazilian semiarid region

2018 ◽  
Vol 30 (0) ◽  
Author(s):  
Josiane Souza Santos ◽  
Nadson Ressyé Simões ◽  
Sérgio Luiz Sonoda
Keyword(s):  
Spatial Distribution ◽  
Spatial Variation ◽  
Temporal Variation ◽  
Aquatic Macrophytes ◽  
Temporal Dynamics ◽  
Lateral Compartment ◽  
Spatial And Temporal Variation ◽  
Semiarid Region ◽  
Brazilian Semiarid ◽  
Significant Spatial Variation

Abstract Aim: The objective of this study was to investigate the spatial and temporal variation of microcrustacean assemblages of a reservoir in the Brazilian semiarid region. Methods Physical and chemical water variables and samples of microcrustaceans were collected at eight sites of the reservoir between July 2013 and November 2014, in a total of seven campaigns. For this study, the reservoir was categorized in two compartments: lateral and central. Results Limnological variables showed significant temporal variation (PERMANOVA, Pseudo-F = 19.51, p = 0.001). Higher turbidity values and suspended solids were observed in the rainiest months, while during the dry months, we measured higher values of transparency, dissolved oxygen, and chlorophyll-a. It was not found significant spatial variation of limnological variables (PERMANOVA, Pseudo-F = 0.96; p = 0.394). During the study period, ten species were recorded: four Cladocera (Ceriodaphnia cornuta, Daphnia gessneri, Diaphanosoma birgei and Diaphanosoma spinulosum ) three Copepoda Calanoida (Argyrodiaptomus azevedoi, Notodiaptomus cearensis and Notodiaptomus iheringi) and three Copepoda Cyclopoida (Macrocyclops albidus, Thermocyclops minutus and Thermocyclops decipiens). The microcrustacean assemblages showed significant temporal variation (PERMANOVA, Pseudo-F = 4.34; p = 0.001) as well as significant spatial variation (PERMANOVA, Pseudo-F = 9.46; p = 0.001). The highest values of abundance and richness were observed in the lateral compartment, this result is mainly related to the presence of aquatic macrophytes in this region, because the analysis of partial RDA indicated that limnological variables explained only 11% of this variation (Pseudo-F = 2.08, p = 0.001). Conclusions The results suggest that the seasonality of the semiarid is an important factor in the temporal dynamics of the limnological variables, while the aquatic macrophytes play an important role in the spatial distribution of the microcrustacean assembly.

Spurious Grid-Scale Precipitation in the North American Regional Reanalysis

2007 ◽  
Vol 135 (6) ◽  
pp. 2168-2184 ◽  
Author(s):  
Gregory L. West ◽  
W. James Steenburgh ◽  
William Y. Y. Cheng
Keyword(s):  
North American ◽  
Prediction Models ◽  
Weather Prediction ◽  
Regional Climate ◽  
Potential Temperature ◽  
Climate Data ◽  
The North ◽  
North American Regional Reanalysis ◽  
Upper Level ◽  
Regional Reanalysis

Abstract Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.

scholarly journals Hydro-Meteorological Trends in an Austrian Low-Mountain Catchment

Climate ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 122
Author(s):  
Gerald Krebs ◽  
David Camhy ◽  
Dirk Muschalla
Keyword(s):  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Remote Sensing Data ◽  
Kendall Test ◽  
Adaptation Measures ◽  
Mitigation And Adaptation ◽  
Regional Impacts ◽  
Long Term Trends ◽  
Annual Scale

While ongoing climate change is well documented, the impacts exhibit a substantial variability, both in direction and magnitude, visible even at regional and local scales. However, the knowledge of regional impacts is crucial for the design of mitigation and adaptation measures, particularly when changes in the hydrological cycle are concerned. In this paper, we present hydro-meteorological trends based on observations from a hydrological research basin in Eastern Austria between 1979 and 2019. The analyzed variables include air temperature, precipitation, and catchment runoff. Additionally, the number of wet days, trends for catchment evapotranspiration, and computed potential evapotranspiration were derived. Long-term trends were computed using a non-parametric Mann–Kendall test. The analysis shows that while mean annual temperatures were decreasing and annual temperature minima remained constant, annual maxima were rising. Long-term trends indicate a shift of precipitation to the summer, with minor variations observed for the remaining seasons and at an annual scale. Observed precipitation intensities mainly increased in spring and summer between 1979 and 2019. Catchment actual evapotranspiration, computed based on catchment precipitation and outflow, showed no significant trend for the observed time period, while potential evapotranspiration rates based on remote sensing data increased between 1981 and 2019.

Regional biogeographical model of vegetation zones in doctoral programme Regional Biography in Olomouc (Case study for Norway spruce)

2020 ◽  
Author(s):  
Ivo Machar ◽  
Marián Halás ◽  
Zdeněk Opršal
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Climate Data ◽  
Ecological Data ◽  
The Czech Republic ◽  
Climate Conditions ◽  
Vegetation Zones ◽  
Landscape Research

Regional climate changes impacts induce vegetation zones shift to higher altitudes in temperate landscape. This paper deals with applying of regional biogeography model of climate conditions for vegetation zones in Czechia to doctoral programme Regional Geography in Palacky University Olomouc. The model is based on general knowledge of landscape vegetation zonation. Climate data for model come from predicted validated climate database under RCP8.5 scenario since 2100. Ecological data are included in the Biogeography Register database (geobiocoenological data related to landscape for cadastral areas of the Czech Republic). Mathematical principles of modelling are based on set of software solutions with GIS. Students use the model in the frame of the course “Special Approaches to Landscape Research” not only for regional scenarios climate change impacts in landscape scale, but also for assessment of climate conditions for growing capability of agricultural crops or forest trees under climate change on regional level.

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