Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Distribución horizontal de la anchoveta peruana con relación a variables ambientales en el período 1986 - 2000

Se analizó la distribución horizontal de la anchoveta Engraulis ringens utilizando sistemas de información geográfica. Los datos fueron obtenidos de los cruceros de evaluación hidroacústica de recursos pelágicos realizados durante los veranos de 1986 al 2000. Los resulitados indican que la distribución horizontal de la anchoveta está asociada a parámetros oceanográficos superficiales del mar, como rangos de temperatura, salinidad y clorofila a; sin embargo,parece ser que el parámetro más importante es la salinidad.

Neuromuscular adaptations in endurance-trained boys and men

Competitive sports participation in youth is becoming increasingly more common in the Western world. It is widely accepted that sports participation, specifically endurance training, is beneficial for physical, psychomotor, and social development of children. The research on the effect of endurance training in children has focused mainly on healthrelated benefits and physiological adaptations, particularly on maximal oxygen uptake. However, corresponding research on neuromuscular adaptations to endurance training and the latter's possible effects on muscle strength in youth is lacking. In children and adults, resistance training can enhance strength and mcrease muscle activation. However, data on the effect of endurance training on strength and neuromuscular adaptations are limited. While some evidence exists demonstrating increased muscle activation and possibly increased strength in endurance athletes compared with untrained adults, the neuromuscular adaptations to endurance training in children have not been examined. Thus, the purpose of this study was to examine maximal isometric torque and rate of torque development (RID), along with the pattern of muscle activation during elbow and knee flexion and extension in muscle-endurancetrained and untrained men and boys. Subjects included 65 males: untrained boys (n=18), endurance-trained boys (n=12), untrained men (n=20) and endurance-trained men (n=15). Maximal isometric torque and rate of torque development were measured using an isokinetic dynamometer (Biodex III), and neuromuscular activation was assessed using surface electromyography (SEMG). Muscle strength and activation were assessed in the dominant arm and leg, in a cross-balanced fashion during elbow and knee flexion and extension. The main variables included peak torque (T), RTD, rate of muscle activation (Q30), Electro-mechanical delay (EMD), time to peak RTD and co-activation index. Age differences in T, RTD, electro-mechanical delay (EMD) and rate of muscle activation (Q30) were consistently observed in the four contractions tested. Additionally, Q30, nonnalized for peak EMG amplitude, was consistently higher in the endurancetrained men compared with untrained men. Co-activation index was generally low in all contractions. For example, during maximal voluntary isometric knee extension, men were stronger, had higher RTD and Q30, whether absolute or nonnalized values were used. Moreover, boys exhibited longer EMD (64.8 ± 18.5 ms vs. 56.6 ± 15.3 ms, for boys and men respectively) and time to peak RTD (112.4 ± 33.4 ms vs. 100.8 ± 39.1 ms for boys and men, respectively). In addition, endurance-trained men had lower T compared with untrained men, yet they also exhibited significantly higher nonnalized Q30 (1.9 ± 1.2 vs. 1.1 ± 0.7 for endurance-trained men and untrained men, respectively). No training effect was apparent in the boys. In conclusion, the findings demonstrate muscle strength and activation to be lower in children compared with adults, regardless of training status. The higher Q30 of the endurance-trained men suggests neural adaptations, similar to those expected in response to resistance training. The lower peak torque may su9gest a higher relative involvement oftype I muscle fibres in the endurance-trained athletes. Future research is required to better understand the effect of growth and development on muscle strength and activation patterns during dynamic and sub-maximal isometric contractions. Furthennore, training intervention studies could reveal the effects of endurance training during different developmental stages, as well as in different muscle groups.

Étude du rôle des régions variables 4 et 5 dans les changements de conformation de la gp120 du VIH-1

Le VIH infecte les cellules par fusion de sa membrane avec la membrane de la cellule cible. Cette fusion est effectuée par les glycoprotéines de l'enveloppe (Env) qui sont synthétisées en tant que précurseur, gp160, qui est ensuite clivé en gp120 et gp41. La protéine gp41 est la partie transmembranaire du complexe de l'enveloppe et l’ancre à la particule virale alors que la gp120 assure la liaison au récepteur cellulaire CD4 et corécepteur CCR5 ou CXCR4. Ces interactions successives induisent des changements de conformation d’Env qui alimentent le processus d'entrée du virus conduisant finalement à l'insertion du peptide de fusion de la gp41 dans la membrane de la cellule cible. La sous-unité extérieure gp120 contient cinq régions variables (V1 à V5), dont trois (V1, V2 et V3) étant capables d’empêcher l’adoption spontanée de la conformation liée à CD4. Cependant, le rôle de régions variables V4 et V5 vis-à-vis de ces changements de conformation reste inconnu. Pour étudier leur effet, des mutants de l'isolat primaire de clade B YU2, comprenant une délétion de la V5 ou une mutation au niveau de tous les sites potentiels de N-glycosylation de la V4 (PNGS), ont été générés. L'effet des mutations sur la conformation des glycoprotéines d'enveloppe a été analysé par immunoprécipitation et résonance de plasmon de surface avec des anticorps dont la liaison dépend de la conformation adopté par la gp120. Ni le retrait des PNGS de la V4 ni la délétion de V5 n’a affecté les changements conformationnels d’Env tels que mesurés par ces techniques, ce qui suggère que les régions variables V1, V2 et V3 sont les principaux acteurs dans la prévention de l’adoption de la conformation lié de CD4 d’Env.

Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al‐SiCp metal matrix composites and ANOVA analysis

Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon carbide particles (SiCp) in reinforcement phase, ie Al‐SiCp type MMC, have gained popularity in the re‐cent past. In this competitive age, manufacturing industries strive to produce superior quality products at reasonable price. This is possible by achieving higher productivity while performing machining at optimum combinations of process variables. The low weight and high strength MMC are found suitable for variety of components

Interpretation of wind components as compositional variables

The classical statistical study of the wind speed in the atmospheric surface layer is made generally from the analysis of the three habitual components that perform the wind data, that is, the component W-E, the component S-N and the vertical component, considering these components independent. When the goal of the study of these data is the Aeolian energy, so is when wind is studied from an energetic point of view and the squares of wind components can be considered as compositional variables. To do so, each component has to be divided by the module of the corresponding vector. In this work the theoretical analysis of the components of the wind as compositional data is presented and also the conclusions that can be obtained from the point of view of the practical applications as well as those that can be derived from the application of this technique in different conditions of weather

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A Bayesian approach to estimate sensible and latent heat over vegetated land surface

Sensible and latent heat fluxes are often calculated from bulk transfer equations combined with the energy balance. For spatial estimates of these fluxes, a combination of remotely sensed and standard meteorological data from weather stations is used. The success of this approach depends on the accuracy of the input data and on the accuracy of two variables in particular: aerodynamic and surface conductance. This paper presents a Bayesian approach to improve estimates of sensible and latent heat fluxes by using a priori estimates of aerodynamic and surface conductance alongside remote measurements of surface temperature. The method is validated for time series of half-hourly measurements in a fully grown maize field, a vineyard and a forest. It is shown that the Bayesian approach yields more accurate estimates of sensible and latent heat flux than traditional methods.

Indicators of nitrate in wetland surface and soil-waters: interactions of vegetation and environmental factors

This paper describes a new bio-indicator method for assessing wetland ecosystem health: as such, the study is particularly relevant to current legislation such as the EU Water Framework Directive, which provides a baseline of the current status Of Surface waters. Seven wetland sites were monitored across northern Britain, with model construction data for predicting, eco-hydroloplical relationships collected from five sites during 1999, Two new sites and one repeat site were monitored during 2000 to provide model test data. The main growing season for the vegetation, and hence the sampling period, was May-August during both years. Seasonal mean concentrations of nitrate (NO3-) in surface and soil water samples during 1999 ranged from 0.01 to 14.07 mg N 1(-1), with a mean value of 1.01 mg N 1(-1). During 2000, concentrations ranged from trace level (<0.01 m- N 1(-1)) to 9.43 mg N 1(-1), with a mean of 2.73 mg N 1(.)(-1) Surface and soil-water nitrate concentrations did not influence plant species composition significantly across representative tall herb fen and mire communities. Predictive relationships were found between nitrate concentrations and structural characteristics of the wetland vegetation, and a model was developed which predicted nitrate concentrations from measures of plant diversity, canopy structure and density of reproductive structures. Two further models, which predicted stem density and density of reproductive structures respectively, utilised nitrate concentration as one of the independent predictor variables. Where appropriate, the models were tested using data collected during 2000. This approach is complementary to species-based monitoring, representing a useful and simple too] to assess ecological status in target wetland systems and has potential for bio-indication purposes.

When can we expect extremely high surface temperatures?

In the Essence project a 17-member ensemble simulation of climate change in response to the SRES A1b scenario has been carried out using the ECHAM5/MPI-OM climate model. The relatively large size of the ensemble makes it possible to accurately investigate changes in extreme values of climate variables. Here we focus on the annual-maximum 2m-temperature and fit a Generalized Extreme Value (GEV) distribution to the simulated values and investigate the development of the parameters of this distribution. Over most land areas both the location and the scale parameter increase. Consequently the 100-year return values increase faster than the average temperatures. A comparison of simulated 100-year return values for the present climate with observations (station data and reanalysis) shows that the ECHAM5/MPI-OM model, as well as other models, overestimates extreme temperature values. After correcting for this bias, it still shows values in excess of 50°C in Australia, India, the Middle East, North Africa, the Sahel and equatorial and subtropical South America at the end of the century.

The relationship between land–ccean surface temperature contrast and radiative forcing

Previous work has demonstrated that observed and modeled climates show a near-time-invariant ratio of mean land to mean ocean surface temperature change under transient and equilibrium global warming. This study confirms this in a range of atmospheric models coupled to perturbed sea surface temperatures (SSTs), slab (thermodynamics only) oceans, and a fully coupled ocean. Away from equilibrium, it is found that the atmospheric processes that maintain the ratio cause a land-to-ocean heat transport anomaly that can be approximated using a two-box energy balance model. When climate is forced by increasing atmospheric CO2 concentration, the heat transport anomaly moves heat from land to ocean, constraining the land to warm in step with the ocean surface, despite the small heat capacity of the land. The heat transport anomaly is strongly related to the top-of-atmosphere radiative flux imbalance, and hence it tends to a small value as equilibrium is approached. In contrast, when climate is forced by prescribing changes in SSTs, the heat transport anomaly replaces ‘‘missing’’ radiative forcing over land by moving heat from ocean to land, warming the land surface. The heat transport anomaly remains substantial in steady state. These results are consistent with earlier studies that found that both land and ocean surface temperature changes may be approximated as local responses to global mean radiative forcing. The modeled heat transport anomaly has large impacts on surface heat fluxes but small impacts on precipitation, circulation, and cloud radiative forcing compared with the impacts of surface temperature change. No substantial nonlinearities are found in these atmospheric variables when the effects of forcing and surface temperature change are added.

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

The surface urban energy and water balance scheme (SUEWS): evaluation in Los Angeles and Vancouver

An urban energy and water balance model is presented which uses a small number of commonly measured meteorological variables and information about the surface cover. Rates of evaporation-interception for a single layer with multiple surface types (paved, buildings, coniferous trees and/or shrubs, deciduous trees and/or shrubs, irrigated grass, non-irrigated grass and water) are calculated. Below each surface type, except water, there is a single soil layer. At each time step the moisture state of each surface is calculated. Horizontal water movements at the surface and in the soil are incorporated. Particular attention is given to the surface conductance used to model evaporation and its parameters. The model is tested against direct flux measurements carried out over a number of years in Vancouver, Canada and Los Angeles, USA. At all measurement sites the model is able to simulate the net all-wave radiation and turbulent sensible and latent heat well (RMSE = 25–47 W m−2, 30–64 and 20–56 W m−2, respectively). The model reproduces the diurnal cycle of the turbulent fluxes but typically underestimates latent heat flux and overestimates sensible heat flux in the day time. The model tracks measured surface wetness and simulates the variations in soil moisture content. It is able to respond correctly to short-term events as well as annual changes. The largest uncertainty relates to the determination of surface conductance. The model has the potential be used for multiple applications; for example, to predict effects of regulation on urban water use, landscaping and planning scenarios, or to assess climate mitigation strategies.

Retrievals of sea surface temperature from infrared imagery: origin and form of systematic errors

We show that retrievals of sea surface temperature from satellite infrared imagery are prone to two forms of systematic error: prior error (familiar from the theory of atmospheric sounding) and error arising from nonlinearity. These errors have different complex geographical variations, related to the differing geographical distributions of the main geophysical variables that determine clear-sky brightness-temperatures over the oceans. We show that such errors arise as an intrinsic consequence of the form of the retrieval (rather than as a consequence of sub-optimally specified retrieval coefficients, as is often assumed) and that the pattern of observed errors can be simulated in detail using radiative-transfer modelling. The prior error has the linear form familiar from atmospheric sounding. A quadratic equation for nonlinearity error is derived, and it is verified that the nonlinearity error exhibits predominantly quadratic behaviour in this case.