The Impacts of Climate Change on Irrigated Agriculture in Southern Portugal

Climate change projections point to increasing air temperature and reduced precipitation in southern Portugal, which would affect farming systems. This study aims to assess the impacts of climate change on irrigated agriculture in southern Portugal. These impacts were assessed by combining climate model data with a soil water balance model and a numerical model for the design of irrigation systems. Meteorological data from two weather stations were used along with three climate models (HadRM3P, HIRHAMh and HIRHAMhh; 2071–2100). The crop rotations studied included sugar beet–maize–tomato–wheat and sunflower–wheat–barley. Two adaptation measures were considered: (i) maintaining the current crop varieties; (ii) using new crop varieties. The results from the considered climate change scenarios indicated that the impacts of climate change on irrigation requirements depend on the adopted adaptation measures. On average, the seasonal irrigation requirements increased by 13–70% when new crop varieties were used and by −13 to 7% when the current crop varieties were maintained. The impacts of climate change on irrigation system design were considerable, with the design flow rate increasing by 5–24%.

Panicum maximum cv. Tanzânia: climate trends and regional pasture production in Brazil.

Projected change in forage production under a range of climate scenarios is important for the evaluation of the impacts of global climate change on pasture-based livestock production systems in Brazil. We evaluated the effects of regional climate trends on Panicum maximum cv. Tanzânia production, predicted by agro-meteorological model considering the sum of degree days and corrected by a water availa bility index. Data from Brazilian weather stations (1963?2009) were considered as the current climate (baseline), and future scenarios, based on contrasting scenarios interms of increased temperature and atmospheric CO2 concentrations (high and low increases), were determined for 2013?2040 (2025 scenario) and for 2043?2070 (2055 scenario). Predicted baseline scenarios indicated that there are regional and seasonal variations in P. maximum production related to variation intemperature and water availability during the year. Production was lower in the Northeast region and higher in the rainforest area. Total annual productionunder future climate scenarios was predicted toincrease by up to 20% for most of the Brazilian area, mainly due to temperature increase, according to each climate model and scenario evaluated. The highest increase in forage production is expected to be in the South, Southeast and Central-west areas of Brazil. In these regions, future climate scenarios will not lead to changes in the seasonal production, with largerincreases in productivity during the summer. Climate risk is expected to decrease, as the probability of occurrence of low forage productions will be lower. Due to the predicted increase in temperature and decrease in rainfall in the Northeast area, P. maximum production is expected to decrease, mainly when considering scenarios based on the PRECIS model for the 2055 scenario.

Energy balances in sugar cane, coffee and natural vegetation in the northeastern side of the São Paulo state, Brazil

Under land and climate change scenarios, agriculture has experienced water competitions among other sectors in the São Paulo state, Brazil. On the one hand, in several occasions, in the northeastern side of this state, nowadays sugar-cane is expanding, while coffee plantations are losing space. On the other hand, both crops have replaced the natural vegetation composed by Savannah and Atlantic Coastal Forest species. Under this dynamic situation, geosciences are valuable tools for evaluating the large-scale energy and mass exchanges between these diffe rent agro-ecosystems and the lower atmosphere. For quantification of the energy balance components in these mixed agro-ecosystems, the bands 1 and 2 from the MODIS product MOD13Q1 we re used throughout SA FER (Surface Algorithm for Evapotranspiration Retrieving) algorithm, which was applied together with a net of 12 automatic weather stations, during the year 2015 in the main sugar cane and coffee growing regions, located at the no rtheastern side of the state. The fraction of the global solar radiation (R G ) transformed into net radiation (Rn) was 52% for sugar cane and 53% for both, coffee and natural vegetation. The respective annual fractions of Rn used as λ E were 0.68, 0.87 and 0.77, while for the sensible heat (H) fluxes they were 0.27, 0.07 and 0.16. From April to July, heat advection raised λ E values above Rn promoting negative H, however these effects were much and less strong in coffee and sugar cane crop s, respectively. The smallest daily Rn fraction for all agro-ecosystems was for the soil heat flux (G), with averages of 5%, 6% and 7% in sugar cane, coffee and natural vegetation. From the energy balance analyses, we could conclude that, sugar-cane crop presented lower annual water consumption than that for coffee crop , what can be seen as an advantage in situations of water scarcity. However, the replacement of natural vegetation by su gar cane can contribute for warming th e environment, while when this occur with coffee crop there was noticed co oling conditions. The large scale modeling satisfactory results confirm the suitability of using MODIS products togeth er with weather stations to study the energy balance components in mixed agro-ecosystems under land-use and climate change conditions.

Evapotranspiration: Present and Future Challenges

The thesis first explored and evaluated some of the most used models that were developed to account for the effect of CO2 on evapotranspiration. This review depicts the complexity of the modeling procedure and underlines the advantages and shortcomings of each model. Then, the projected climate change in the near future (2021-2050) in different locations in Emilia-Romagna (Italy) was studied, with an emphasis on the opposite effect of an increase in both air temperature and CO2 levels on ETo. The case study used reanalysis data as a surrogate to historical weather stations measurements and an ensemble of regional climate models (RCMs) for the future projections. Results show that higher CO2 levels moderated the increase in ETo that accompanies an increase in air temperature, taking in consideration the change in other weather variables i.e. solar radiation, wind speed and dew point temperature. The outcomes of this study show that considering the CO2 fertilization effect when calculating reference evapotranspiration might give a more realistic estimation of water use efficiency and irrigation requirements in Emilia-Romagna and a better analysis of the future availability and distribution of water resources in the region. Finally, data from a model forecasting reference evapotranspiration (FRET) and the different variables involved in its calculation for the state of California (USA) were compared with similar data from the regional weather station network (CIMIS) to evaluate their accuracy and reliability. The evaluation was done in locations with different microclimates and included also sample irrigation schedules developed using FRET ETo. The obtained results demonstrate that FRET ETo forecasts are a viable alternative to traditional ETo measurements with some differences depending on the climatic condition of the location considered in this study. This implies that FRET could be replicated in other areas with similar climate settings.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Associations involving delays (particularly long delays) between certain weather parameters and geomagnetic activity

Four sunspot-minimum periods (1963-1966, 1971-1977, 1983-1987 and 1992-1997) have been examined for the results which are presented. Using several different weather parameters, tropospheric gravity waves, enhanced cold fronts and two rainfall data sets in Eastern Australia, associations at reasonably high levels of significance have been found with enhanced geomagnetic activity (EGA). Statistically this EGA involved either short delays of several days or long delays of about 20 days. The geomagnetic parameters used were (a) the AE index (b) the hourly H component for a number of stations and (c) the daily K-P-sum value. The K-P-sum analyses have shown that the EGA associated with the delays form part of four or five cycles of recurrent geomagnetic activity for 27-day periodicities. Furthermore statistically two recurrent cycles are found to exist concurrently, one apparently related to the short delays and the other to the long delays. Periodicities of 13.5 days are created because the two sets are displaced from each other by approximately this interval. A brief reference is made to the 13.5 periodicity known to exist for geomagnetic activity and the evidence in the literature for active regions on the sun to be displaced by 180 degrees of solar longitude.

Analysis of the wind field and heat budget in an alpine lake basin during summertime fair weather conditions

Observational data collected in the Lake Tekapo hydro catchment of the Southern Alps in New Zealand are used to analyse the wind and temperature fields in the alpine lake basin during summertime fair weather conditions. Measurements from surface stations, pilot balloon and tethersonde soundings, Doppler sodar and an instrumented light aircraft provide evidence of multi-scale interacting wind systems, ranging from microscale slope winds to mesoscale coast-to-basin flows. Thermal forcing of the winds occurred due to differential heating as a consequence of orography and heterogeneous surface features, which is quantified by heat budget and pressure field analysis. The daytime vertical temperature structure was characterised by distinct layering. Features of particular interest are the formation of thermal internal boundary layers due to the lake-land discontinuity and the development of elevated mixed layers. The latter were generated by advective heating from the basin and valley sidewalls by slope winds and by a superimposed valley wind blowing from the basin over Lake Tekapo and up the tributary Godley Valley. Daytime heating in the basin and its tributary valleys caused the development of a strong horizontal temperature gradient between the basin atmosphere and that over the surrounding landscape, and hence the development of a mesoscale heat low over the basin. After noon, air from outside the basin started flowing over mountain saddles into the basin causing cooling in the lowest layers, whereas at ridge top height the horizontal air temperature gradient between inside and outside the basin continued to increase. In the early evening, a more massive intrusion of cold air caused rapid cooling and a transition to a rather uniform slightly stable stratification up to about 2000 m agl. The onset time of this rapid cooling varied about 1-2 h between observation sites and was probably triggered by the decay of up-slope winds inside the basin, which previously countered the intrusion of air over the surrounding ridges. The intrusion of air from outside the basin continued until about mid-night, when a northerly mountain wind from the Godley Valley became dominant. The results illustrate the extreme complexity that can be caused by the operation of thermal forcing processes at a wide range of spatial scales.

The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.

Physical oceanography of CTD stations in the Persian Gulf

The following tables show physical and chemical data observed by the "Meteor" in the Persian Gulf and the Strait of Hormus. This study was performed in accordance with the general programme of the International Indian Ocean Expedition (IIOE) during the oeriod from March 25th until April 16th, 1965. The water temperature was measured by reversing thermometers; in most cases two instruments were used simultaneously. The absolute mean temperature difference of this double measurement is 0.0153 °C. The salinity was determined both by salinometer and by titration. In this case of the density, the specific volume anomaly, the dynamic depth anomaly, the sound velocity and the interpolation for standard depths were carried out by the National Oceanographic Data Center (NODC), Washington.

Daily river stages at river gage stations on the principal rivers of the United States.

Mode of access: Internet.