Downscaling Research Papers - Academia.edu (original) (raw)

Background and purpose: The large-scale computational network of planetary models are not able to predict climatic variables on a regional scale. In other words, these models are affected by processes with a smaller scale than the model network in providing predictions of regional precipitation. Therefore, the model outputs should convert into a regional scale. The research purpose is to investigate the different configurations of the WRF model in the simulation of 5-days rainfall in March 17 to 22 March 2019 in Golestan province, which has caused devastating floods and heavy damage in the province.
Materials and Methods: The observation and quality control precipitation data was analyzed in 13 synoptic stations of Golestan province for a 5-days period from March 17 to 22 March 2019 in the form of 24 Hours (From 06 UTC the day before to 06 UTC the next day) and 6 hours (00, 06, 12 and 18 UTC are 3:30, 9:30, 15:30 and 21:30 local time, respectively). Also, two types of input data including initial condition data and boundary condition data were used in the WRF model. The boundary condition data was GFS data with 0.5-degree resolution. Furthermore, two domains were used in WRF model, 1) the large (mother) with a horizontal resolution of 18 km and 2) internal domain, which is the main domain and has 6 km horizontal resolution.
Results: Two configuration was selected which showed better output results. The 5-days cumulative precipitation data which caused the flood show that the maximum 24-hour precipitation during the 5-days period is 06:00 UTC on March 18 to 06:00 UTC March 19 and the maximum cumulative rainfall of 6 hours is related to 06 to 12 UTC on March 18, 2019. Subsequently, by study similar research in Iran, different configurations for precipitation prediction were extracted and modeled. Then, in order to determine the accuracy of the model, the values obtained from the model in different configurations were compared with the values of synoptic stations. To ensure this comparison, MAE, d, R and ENS test statistics were used.
Conclusion: The results showed that the WRF model overestimate the precipitation data in most stations. In both configurations, results convey the precipitation cores well illustrated and the model accuracy was good enough in predicting precipitation. In maximum values of precipitation, the configuration of the first type show better results. Overall, the first type configuration performed more accurate than the second type configuration.

- by
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- Downscaling, Simulation, WRF model, Precipitation
- by Manuela D'Amen
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- Earth Sciences, Biogeography, Downscaling, Biological Sciences

Background and Objectives: Temperature and rainfall are two important meteorological variables, especially in arid and semi-arid areas. As a result, determining the value of these variables, their changes and prediction of these phenomena are necessary for more precise planning in the management of agricultural, economic and social sectors. Nowadays, incompatibility of temporal and spatial scales required in investigated models on the effect of climate change with GCM outputs and the need to assess the change trend in meteorological threshold variables at the regional scale has led to develop various downscaling methods. So, the aim of this study is the comparative comparison of data mining models in downscaling of rainfall and temperature based on data of NCEP general circulation model.
Material and Methods: The study area in this research is bazoft- e- Samsami watershed. This basin is one of the northern Karun sub-basins located in the northwest of Chaharmahal and Bakhtiari province. Marghak rain gauge and hydrometric stations are located at its outlet.
In this study, the performance and efficiency of four methods including decision tree (M5), Nearest Neighbor (KNN), Multilayer Perceptron (MLP) and Simple linear regression (SLR) were evaluated for modeling monthly rainfall and temperature of Marghak station during the training period of 1971-1990 and The 1991-2000 test period using NCEP output parameters.
Results: Monthly rainfall modeling results using mentioned models showed that the output of all models except the KNN model provides negative values for rainfall. The rainfall prediction by M5 model in January, March, April and December is lower than the observed values (P). This situation is also somewhat seen in other models. Also, given that the minimum rainfall is zero, it can be concluded from the low predicted values rather than observed values that the maximum limit of rainfall with these models is not well predicted. The prediction of rainfall by all models in all months except May has a lower standard deviation than the observed values (P).
The predicted results of monthly temperature also showed that only MLP output provides negative values for the temperature, which can be due to the extrapolation and generalizationin in MLP method. Also, The standard deviation obtained from all models in January, February, March, April, July, August, October, November and December is more than standard deviation of observed temperature. The results of statistical analyzes also showed that M5 than the other models in the test stage according to RMSE, MBE and R2 have better estimates for rainfall and monthly temperature. Although the results of determination coefficient (R2) in the test stage for monthly temperature estimation are weaker than monthly rainfall.
Conclusion:
The results of the efficiency of four models of KNN, M5, SLR and MLP in monthly rainfall and temperature modeling in Marghak meteorological station with NCEP output data showed that these models were weak in downscaling the monthly rainfall and temperature. Therefore, despite the relative superiority of M5 model compared to other models, the use of these data mining models is not recommended to predict rainfall and temperature variables in Margak station.

Changes in global climate will have significant impact on local and regional hydrological regimes, which will in turn affect ecological, social and economical systems. However, climate-change impact studies on hydrologic regime have been relatively rare until recently, mainly because Global Circulation Models, which are widely used to simulate future climate scenarios, do not provide hourly or daily rainfall reliable enough

- by Yonas Dibike and +1
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- Climate Change, Hydrology, Time Series, Climate
- by Martin Dresler
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- Cognitive Science, Downscaling, Memory Consolidation, Memory
- by Hyun-han Kwon
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- Environmental Engineering, Civil Engineering, Climate Change, Downscaling
- by Abrham Belay
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- Downscaling
- by Zhifeng Liu
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- Water quality, Downscaling, Soil moisture, REMEDHUS
- by IJERD Editor
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- Climate Change, Atmospheric Science, Hydrology, Climatology

Abstract This first paper of the two-part series focuses on demonstrating the accuracy of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (?1-km) and 0.25° (?25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

- by Yiwen Mei and +1
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- Downscaling, Land Surface Modeling, High Mountain Asia

Este trabajo propone un modelo mediante el cual los bancos comerciales pueden vender productos y servicios financieros a gran escala a la microempresa. El planteamiento de dicho modelo es el resultado de la revisión de alguna parte de la literatura disponible en relación con el tema y de un aporte personal. El modelo parte de la base de que es la banca comercial grande la llamada a vender los productos y servicios financieros a gran escala a la microempresa implementando la banca microempresarial y penetrando este segmento de mercado o, como se dice en la jerga mercadotécnica internacional, haciendo downscaling. Se identifica un conjunto de variables críticas y se plantea cómo ellas deben ser definidas para aumentar considerablemente la probabilidad de que la comercialización de productos y servicios financieros a gran escala a la microempresa sea viable y sostenible en el tiempo.
Finalmente se analiza los resultados correspondientes al Estudio de Oportunidad para el proyecto “Productos y servicios financieros a gran escala para la microempresa colombiana”, a la luz del modelo propuesto y siguiendo la metodología para el estudio de proyectos de la Organización de las Naciones Unidas para el Desarrollo Industrial (ONUDI).

This research paper explains the effect of the dimensions of Gate-all-around Si nanowire tunneling field effect transistor (GAA Si-NW TFET) on ON/OFF current ratio, drain induces barrier lowering (DIBL), sub-threshold swing (SS), and threshold voltage (VT). These parameters are critical factors of the characteristics of tunnel field effect transistors. The Silvaco TCAD has been used to study the electrical characteristics of Si-NW TFET. Output (gate voltage-drain current) characteristics with channel dimensions were simulated. Results show that 50nm long nanowires with 9nm-18nm diameter and 3nm oxide thickness tend to have the best nanowire tunnel field effect transistor (Si-NW TFET) characteristics.

- by Faris Taha
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- Materials Science, Nanowire, Nanotechnology, Downscaling

This paper presents a new Copula-based method for further downscaling regional climate simulations. It is developed, applied and evaluated for selected stations in the alpine region of Germany. Apart from the common way to use Copulas to model the extreme values, a strategy is proposed which allows to model continous time series. In this paper, we focus on the positive pairs of observed and modelled (RCM) precipitation.
As the concept of Copulas requires independent and identically distributed (iid) random variables, meteorological fields are transformed using an ARMA-GARCH time series model. The dependence structures between modelled and observed precipitation are conditioned on the prevailing large-scale weather situation. The impact of the altitude of the stations and their distance to the surrounding modelled grid cells is analyzed.
Based on the derived theoretical Copula models, stochastic rainfall simulations are performed, finally allowing for bias corrected and locally refined RCM simulations.

- by Patrick Laux
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- Statistics, Alpine Research, Applied Statistics, Modeling

Coupled Atmosphere-Ocean General Circulation Models demonstrate good skill in simulating large scale circulations. However this output is not very useful to study local impacts, as its spatial resolution is courser than the scale of local impacts. It is very important to consider this issue when studying, for instance, climate impacts on human activities, coastal-marine biodiversity and tropical coral reefs. In general terms, there have been two different approaches to deal with this scale and information difference: the dynamic and the statistic downscaling methods. In this work, the basic climate elements are presented and the possible physical causes of atmospheric changes are discussed. Also, a summary of the main physical concepts that define the climate system as well as the climate and climate variability of a region with respect to the mean atmospheric state and the general aspects of the problem of climate change with emphasis on regional scales, is presented. In addition, this study describes the methodological schemes of the downscaling process and presents a discussion of downscaling advantages and disadvantages, while providing applications for regional weather and climate as well as for socio-economic benefits in coastal, agricultural and tourism activities, among others.

- by Eric J Alfaro
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- Downscaling
- by Shouquan Cheng
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- Downscaling

The current study describes a technique for downscaling climatological data in areas with limited or no grid data. In cases where grid data are unavailable and the researcher is called to operate on a regional or in the mesoscale and produce detailed and not coarse results, this technique can be a helping hand. It constitutes a combination of statistical downscaling through multi-linear regression techniques and dynamical downscaling by employing Geographical Information Systems, and it can be used in order to spatially interpolate with high resolution various climatological variables. The application of the described technique was applied on 3 agricultural areas that present different climate conditions and are characterised by complex topography. The results indicated that the current technique delivered very sufficient results as the adjusted coefficient (R 2) appears with high values in almost every case. Areas characterized by Mediterranean type of climate with hot summers (Csa) showed the strongest presumption against null hypothesis; while areas characterized by a combination of different Mediterranean climate types (Csa and Csb) used the most coefficients in the multi-linear procedure and produced relatively good results. Areas facing continental climate conditions delivered satisfactorily results, although most of the examined coefficients are presented with medium presumption against null hypothesis. Concluding, the described technique can be used for every type of climate in almost every terrain for the accurate representation of various climatological variables in the mesoscale.

- by Spyros Paparrizos
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- Climate Change, Climatology, Downscaling, Greece

This study investigates the climate change impact on the changes of mean and extreme flows under
current and future climate conditions in the Omerli Basin
of Istanbul, Turkey. The 15 regional climate model output
from the EU-ENSEMBLES project and a downscaling
method based on local implications from geophysical
variables were used for the comparative analyses. Automated calibration algorithm is used to optimize the parameters of Hydrologiska Byråns Vattenbalansavdel-ning
(HBV) model for the study catchment using observed
daily temperature and precipitation. The calibrated HBV
model was implemented to simulate daily flows using
precipitation and temperature data from climate models
with and without downscaling method for reference
(1960–1990) and scenario (2071–2100) periods. Flood
indices were derived from daily flows, and their changes
throughout the four seasons and year were evaluated by
comparing their values derived from simulations corresponding to the current and future climate. All climate
models strongly underestimate precipitation while downscaling improves their underestimation feature particularly for extreme events. Depending on precipitation input from
climate models with and without downscaling the HBV
also significantly underestimates daily mean and extreme
flows through all seasons. However, this underestimation
feature is importantly improved for all seasons especially
for spring and winter through the use of downscaled
inputs. Changes in extreme flows from reference to future
increased for the winter and spring and decreased for the
fall and summer seasons. These changes were more significant with downscaling inputs. With respect to current
time, higher flow magnitudes for given return periods will
be experienced in the future and hence, in the planning of
the Omerli reservoir, the effective storage and water use
should be sustained.

- by Fatih Kara
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- Climate Change, Hydrology, Downscaling, Geographic Information Systems (GIS)
- by Ramzah Dambul
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- Geography, Environmental Science, Geology, Climatology
- by Peter Cox
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- Environmental Science, Evaluation, Climate, Carbon Cycle
- by Basanta Nameirakpam and +1
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- Modeling, Electrostatics, Numerical Analysis, Downscaling
- by Raimundo Real
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- Diversity, Downscaling, Biological Sciences, Sampling

We assessed the potential impacts of land-use changes resulting from a change in the current biofuel policy on biodiversity in Europe. We evaluated the possible impact of both arable and woody biofuel crops on changes in distribution of 313 species pertaining to different taxonomic groups. Using species-specific information on habitat suitability as well as land use simulations for three different biofuel policy options, we downscaled available species distribution data from the original resolution of 50 to 1 km. The downscaled maps were then applied to analyse potential changes in habitat size and species composition at different spatial levels. Our results indicate that more species might suffer from habitat losses rather than benefit from a doubled biofuel target, while abolishing the biofuel target would mainly have positive effects. However, the possible impacts vary spatially and depend on the biofuel crop choice, with woody crops being less detrimental than arable crops. Our results give an indication for policy and decision makers of what might happen to biodiversity under a changed biofuel policy in the European Union. The presented approach is considered to be innovative as to date no comparable policy impact assessment has been applied to such a large set of key species at the European scale.

- by Wim Ozinga
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- European Union, Biodiversity, Downscaling, Land Use Change
- by Gabriel Vecchi and +1
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- Downscaling, Multidisciplinary, Sea surface temperature, Trajectory

Climate change impacts are dependent on changes in air temperature, rainfall (frequency and amount) and climate indices, which are highly certain. Climate extreme indices are important metrics that are used to communicate the impacts of climate change. The CORDEX African-domain RCM (SMHI-RCA4) run by seven CMIP5 (CCCma-CanESM2, IPSL-IPSL-CM5A-MR, MIROC-MIROC5, MPI-M-MPI-ESM-LR, NCC-NorESM1-M, MOHC-HadGEM2-ES and NOAA-GFDL-GFDL-ESM2M) and two representative concentration pathways (RCP4.5 and RCP8.5) were used in this study. The future climate change is analysed relative to 2020–2050/1970–2000 using a multi-model ensemble projection. Selected climate indices were analysed using a multi-model ensemble of CMIP5 GCMs (GFDL-ESM2G, HadGEM2-ES and IPSL-CM5A-MR). The climate data operators (CDOs) were used in merging and manipulating the modelled (RCM) data and ETCCDI climate indices. The Mann–Kendall was used to compute the trends in time-series data at p < 0.05. Results indicate that te...

- by Kabwe Mubanga
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- Engineering, Earth Sciences, Environmental Science, Climate Change

In recent decades, the increase in temperature has caused widespread climate change all over the world, especially in arid and semi-arid regions of Iran and Yazd province. The purpose of this study is to project climate change in Yazd province using the CanESM2 model and new emission scenarios (RCP) during 2021-2050 (near future) and 2051-2080 (distant future) and to study the trend of changes in the baseline period using the Mann-Kendall test. The statistical indices of R2, RMSE, and NSE were used to evaluate the performance of the CanESM2 model. According to the results, the model had an appropriate performance for projecting precipitation and temperature in the future period and was classified into good and very good classes in terms of capability. Investigating the trend of the annual change of temperature and precipitation in the baseline period showed that the temperature had an increasing trend under most scenarios and stations, while the trend of the change of precipitation was no significant. The results of temperature changes in Yazd province indicated an increase of 2.2, 1.2, and 2.5 °C during 2021-2050 and 2.28, 3.19, and 4.77°C during 2051-2080 under RCP2, RCP4.5, and RCP8.5 scenarios, respectively. Changes in precipitation in Yazad province during the winter season showed a decrease in precipitation by 32, 26, and 34% during 2021-2050 and by 32, 32, and 5% during 2051-2080 under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively.

- by Journal of Desert Management
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- Downscaling, Temperature, Precipitation, Mann-Kendall Test
- by Nicole Mölders and +1
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- Evaluation, Downscaling

As climate change could have considerable influence on hydrology and corresponding water management, appropriate climate change inputs should be used for assessing future impacts. Although the performance of regional climate models (RCMs)... more

- by Wetterhall Fredrik
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- Management, Civil Engineering, Climate Change, Hydrology
- by Francesca Ventura
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- Earth Sciences, Decision Making, Climate variability, Modeling
- by Serge Rambal
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- Remote Sensing, Modeling, Climate, Risk assessment
- by Jesus Joel Molina Duarte
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- Zoology, Wildlife Biology, Downscaling, Hunting
- by Raul Vaca
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- Plant Biology, Downscaling, Random Forests, Spatial resolution

- by Eric Harmsen and +2
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- Civil Engineering, Climate Change, Mass Spectrometry, Water Engineering

A statistical strategy to deduct regional~scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique. The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It is shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM). The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous "2 CO~'' doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of l mm/month,

- by Hans von Storch and +1
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- Statistics, Climate, Downscaling, Iberia

Outputs of regional climate model MM5
have been compared with observations
in situ over Coco’s Island, Costa Rica.
Observational data were collected during
three different expeditions to the island,
in October 2007, April 2008 and March
2009. The real time model forecast system
for Coco’s Island used a 4 domain grid
configuration of 90, 30, 10, and 3,3 km
horizontal resolutions (42x47, 76x85,
100x121, 73x73 points, respectively) with
35 vertical model layers.
The system generates forecasts up to 48
hours, every three hours. The model is
initialized using the National Center for
Environmental Prediction (NCEP) global
forecast system (GFS) data as initial and
lateral boundary conditions every six
hours with two way nesting dynamics. No
data assimilation are applied. The chosen
physical configuration has shown better
performance in the most humid periods
than periods with high precipitation.
Such results are showed in relative humidity
and precipitation forecasts, confirming the
relationship among these variables in the
zone. Nevertheless simulation of short
wave radiation didn’t show proper values
for the region. Simulation of temperature
was agreed with others experiments. Wind
seems to be better simulated in middle
levels than boundary layer.

- by Eric J Alfaro
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- Downscaling
- by Norman Miller
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- Civil Engineering, Climate Change, Mass Spectrometry, Puerto Rico

This study assesses the impacts of climate change on water resources over Mbarali River sub-catchment using high resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment Regional Climate Models (CORDEX_RCMs). Daily rainfall, minimum and maximum temperatures for historical climate (1971-2000) and for the future climate projection (2011-2100) under two Representative Concentration Pathways RCP 8.5 and RCP 4.5 were used as input into the Soil and Water Assessment Tool (SWAT) hydrological model to simulate stream flows and water balance components for the Mbarali River sub-catchment. The impacts of climate change on hydrological conditions over Mbarali river catchment were assessed by comparing the mean values of stream flows and water balance components during the present (2011-2040), mid (2041-2070) and end (2071-2100) centuries with their respective mean values in the baseline (1971-2000) climate condition. The results of the study indicate that, in...

- by edmund ishengoma
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- Engineering, Environmental Science, Climate Change, Hydrology

Climate change has many impacts on all environmental processes and society. In this study, three models selected from Coupled Model Intercomparison Project Phase 6 (CMIP6) including ACCESS-CM2, HadGEM3-GC31-LL, and NESM3 are validated. The best model (i.e. ACCESS-CM2) is selected to simulate the climatic parameters of the Sari Station using the latest emission scenarios called "shared socioeconomic pathways (SSP)." The LARS-WG is adopted for downscaling, and two emission scenarios SSP2-4.5 and SSP5-8.5 are used for two periods 2041-2060 and 2081-2100, respectively. Several statistical tests are conducted including F-test, T-student, Kolomogrov-Smirnov, coefficient of determination (R 2), and root mean square error (RMSE) to validate the LARS-WG model. The verification results indicate the efficiency of the LARS-WG model. The Man-Kendal and Sen's slope tests are adopted to determine the trend of climatic observational parameters. In general, the results show that the average temperature change increases in the range of 1.16-4.09 °C and also the average annual rainfall increases by 24-36 percent. The Sen's slope results in terms of maximum and minimum temperatures show an ascending trend in this parameter, but it is descending in the rainfall. Since long-term climate change is one of the factors affecting groundwater and surface resources, it is necessary to develop proper management strategies for the future, preserving ecosystems, and adapting humans to these changes.

- by Rasmus Benestad
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- Downscaling, Atmospheric sciences, Uncertainty, Regional Climate Modeling
- by Philippe Gachon
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- Environmental Engineering, Civil Engineering, Climatology, Downscaling

A problem that is common in agriculture but not very publicized, thanks to the absence of victims, is the rollover of Centre Pivot and Lateral Move irrigation systems. These accidents are due to particularly-strong winds acting on the spans, and they are potentially very destructive for the installations. Also, the restoration phase of the installations requires always an intervention of lifting of the machinery on the field, with a potential further damage to crops (setting) and land (compaction). Given the basic inevitability of the phenomenon, due to atmospheric events, these rollovers could be however limited e.g. by proposing a system design granting a higher stability. Therefore, we have firstly modelled the rollover dynamics of these systems, considering the geometry, the masses, the forces acting on them (wind, gravity), the position of the centre of gravity. Then, thanks to morphometry, we have investigated booms’ stability as a consequence of a proportional or not-proportional alteration of the system sizes, in particular: the upscaling of supports, done by some manufacturers, and the lengthening of spans, often required by customers. Morphometry is a method born in biology, typically used to describe and analyse statistically the shape variations within and among samples of organisms as a result of growth, experimental treatments or evolution. As the idea of evolutionary adaptation is intrinsic in the technical evolution of human-made systems (models, variants) operated by manufacturers, also artificial systems can be studied or improved via the morphometry, as operated here. The output of this study is a physical model of rollover and a sensitivity analysis of a reference configuration for an irrigation boom. Thanks to these analyses, we were able to demonstrate, for example, how a scaling-up of boom supports, respectful of geometric ratios, can increase the system stability despite the elevation of the pressure point of the wind on the frame.

- by Fabrizio Mazzetto and +1
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- Mechanical Engineering, Agricultural Engineering, Mechanics, Irrigation

High resolution soil moisture information is vital for a number of applications such as water management, hydrological and climatic modelling. The available point-scale in-situ measurements and coarse-resolution (around40 km) satellite retrievals are unable to capture the sub-basin and sub-paddock scale spatial variability of soil moisture. Improving the spatial resolution of satellite soil moisture products through downscaling is a feasible solution to this problem. Thermal data based soil moisture downscaling methods perform better in semi-arid/arid regions, i.e. most of Australia. A regression model based on the thermal inertia relationship between the diurnal temperature difference (DeltaT) and daily mean soil moisture (muSM) was developed in this study to estimate soil moisture at a high spatial resolution. The soil temperature and soil moisture estimates were extracted from the land surface model (LSM)-based Global Land Data Assimilation System (GLDAS) dataset (around25 km). The GLDAS data from 2000 to 2015 over the southeastern Australia were employed in this process. The DeltaT-muSM relationship is modulated by the vegetation density. The regression algorithms were tested over a 40 40 km area in the Upper Hunter Region of southeastern Australia. This area was cleared mostly by cropping and grazing, representing the

- by indishe senanayake
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- Remote Sensing, Downscaling, Soil moisture, Soil Moisture and Remote Sensing
- by Andreas Fischlin
- •
- Climate Change, Productivity, Downscaling, Global Change Biology
- by HyunHan Kwon
- •
- Environmental Engineering, Civil Engineering, Climate Change, Downscaling
- by Donaldi Permana
- •
- Downscaling
- by Shie-yui Liong
- •
- Environmental Engineering, Civil Engineering, Climate Change, Downscaling
- by Mahdi Zarghami
- •
- Earth Sciences, Climate Change, Downscaling