Showing papers on "Weather station published in 2013"

The urban weather generator

Abstract: The increase in air temperature produced by urbanization, a phenomenon known as the urban heat island (UHI) effect, is often neglected in current building energy simulation practices. The UHI effect can have an impact on the energy consumption of buildings, especially those with low internal heat gains or with an inherent close interaction with the outdoor environment (e.g. naturally-ventilated buildings). This paper presents an urban weather generator (UWG) to calculate air temperatures inside urban canyons from measurements at an operational weather station located in an open area outside a city. The model can be used alone or integrated into existing programmes in order to account for the UHI effect in building energy simulations. The UWG is evaluated against field data from Basel (Switzerland) and Toulouse (France). The error of UWG predictions stays within the range of air temperature variability observed in different locations of the same urban area.

Impact of derived global weather data on simulated crop yields.

Abstract: Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method.

Quantifying urban heat island intensity in Hong Kong SAR, China

Abstract: This paper addresses the methodological concerns in quantifying urban heat island (UHI) intensity in Hong Kong SAR, China. Although the urban heat island in Hong Kong has been widely investigated, there is no consensus on the most appropriate fixed point meteorological sites to be used to calculate heat island intensity. This study utilized the Local Climate Zones landscape classification system to classify 17 weather stations from the Hong Kong Observatory’s extensive fixed point meteorological observation network. According to the classification results, the meteorological site located at the Hong Kong Observatory Headquarters is the representative urban weather station in Hong Kong, whereas sites located at Tsak Yue Wu and Ta Kwu Ling are appropriate rural or nonurbanized counterparts. These choices were validated and supported quantitatively through comparison of long-term annual and diurnal UHI intensities with rural stations used in previous studies. Results indicate that the rural stations used in previous studies are not representative, and thus, the past UHI intensities calculated for Hong Kong may have been underestimated.

Mapping Occupational Heat Exposure and Effects in South-East Asia : Ongoing Time Trends 1980-2011 and Future Estimates to 2050

Abstract: A feature of climate impacts on occupational health and safety are physiological limits to carrying out physical work at high heat exposure. Heat stress reduces a workers work capacity, leading to lower hourly labour productivity and economic output. We used existing weather station data and climate modeling grid cell data to describe heat conditions (calculated as Wet Bulb Globe Temperature, WBGT) in South-East Asia. During the hottest month in this region (March) afternoon WBGT levels are already high enough to cause major loss of hourly work capacity and by 2050 the situation will be extreme for many outdoor jobs.

Urban heat island and differences in outdoor comfort levels in Glasgow, UK

Abstract: From extensive outdoor comfort campaigns, preliminary outdoor comfort ranges have been defined for the local population of Glasgow, UK, in terms of two thermal indices: ‘Temperature Humidity Sun Wind’ (THSW) and ‘Physiological Equivalent Temperature’ (PET). A series of measurements and surveys was carried out from winter through summer 2011 during 19 monitoring campaigns. For data collection, a Davis Vantage Pro2 weather station was used, which was equipped with temperature and humidity sensors, cup anemometer with wind vane, silicon pyranometer and globe thermometer. From concurrent measurements using two weather stations, one located close to the city core and another located at a rural setting, approximately at a 15-km distance from the urban area of Glasgow, comparisons were made with regard to thermal comfort levels and to urban–rural temperature differences for different periods of the year. It was found that the two selected thermal indices (THSW and PET) closely correlate to the actual thermal sensation of respondents. Moreover, results show that the urban site will have fewer days of cold discomfort, more days of ‘neutral’ thermal sensation and slightly higher warm discomfort. The most frequent urban heat island intensity was found to be around 3° C, whereas the fraction of cooling to heating degree-hours for a Tbase of 65 °F was approximately 1/12th.

Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

Abstract: Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM) 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE). The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP), the Climate Prediction Center Morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS)) were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

High resolution climate data for Austria in the period 2008–2040 from a statistical climate change model

Abstract: Climate change data for Austria have been produced for the period from 2008 to 2040, with a temporal/spatial resolution of 1 d and 1 km2. The climate change data are based on historical daily weather station data from 1975 to 2007, and linear regression modelling with repeated bootstrapping. The spatial resolution is based on 60 climate clusters which represent homogenous climates with respect to mean annual precipitation sums and mean annual temperatures from the period 1961 to 1990. For each climate cluster, a regression model fit has been performed and extrapolated for the period 2008–2040. The integral parts of our regression model are: (1) the extrapolation of the observed linear temperature trend from 1975 to 2007, by using an average national trend of approximately 0.05 °C per year derived from a homogenized dataset, and (2) the repeated bootstrapping of historical temperature residuals, and of the observations for some other weather parameters, such as solar radiation, precipitation, relative humidity and wind speed. Thus, we ensure consistent physical, spatial and temporal correlations. Precipitation scenarios have been developed to account for any possible wider range of precipitation patterns. These scenarios include increased/decreased annual precipitation sums, as well as unchanged annual precipitation sums, but with different seasonal distributions. These climate change data are available at: http://www.landnutzung.at/Klima_Daten.html Copyright © 2012 Royal Meteorological Society

Analysis of the Urban Thermal Fingerprint of the City of Trento in the Alps

Abstract: The temperature contrasts typically marking urban heat island (UHI) effects in the city of Trento, Italy, located in an Alpine valley and inhabited in its inner urban area by a population of about 56 000, are investigated. Time series of air temperature data, collected at an urban weather station, in the city center, and at five extraurban stations are compared. The latter are representative of rural and suburban areas, both on the valley floor and on the valley sidewalls. It is found that the extraurban weather stations, being affected by different local-scale climatic conditions, display different temperature contrasts with the urban site. However, the diurnal cycle of the UHI is characterized by similar patterns of behavior at all of the extraurban weather stations: the UHI intensity is stronger at night, whereas during the central hours of the day an “urban cool island” is likely to occur. The diurnal maximum UHI intensity turns out to be typically of order 3°C, but under particularly favorabl...

Temporal and spatial analyses of temperature in a French wine-producing area: the Loire Valley

Abstract: Global warming is causing earlier phenological dates for vines and changes in the quality of wines all around the world. To understand how vines are liable to react to future climate evolution, the climate of viticultural areas needs to be known as accurately as possible. In this article, temporal evolution and spatial variability of temperature in the wine producing area of the Loire Valley were analysed with a multi-scalar approach. First, the regional evolution of temperature and bioclimatic indices were studied over the past 60 years in the wine-producing area of the Loire Valley and showed a general warming at all locations in the regional weather station network (Meteo-France). Secondly, temperature data from weather stations located within the vineyards between Angers and Saumur were studied for the year 2010 and underlined spatial variability of temperature between the different plots according to the different topoclimates. Finally, particular attention was paid to the Coteaux du Layon vineyards (sweet wine producing appellation) where 21 temperature data loggers were set up in the vine rows to study climate at local scale. The study showed, in particular, that the spatial variability of temperature and bioclimatic indices in these vineyards was greater than those observed at larger scales. Copyright © 2012 Royal Meteorological Society

Calculation of Air Temperatures above the Urban Canopy Layer from Measurements at a Rural Operational Weather Station

Abstract: Urban canopy models (UCMs) are being used as urban-climate prediction tools for different applications including outdoor thermal comfort and building energy consumption. To take advantage of their low computational cost, UCMs are often forced offline without being coupled to mesoscale atmospheric simulations, which requires access to meteorological information above the urban canopy layer. This limits the use of UCMs by other scientific and professional communities, such as building engineers and urban planners, who are interested in urban-climate prediction but may not have access to mesoscale simulation results or experimental meteorological data. Furthermore, the conventional offline use of UCMs neglects the fact that the urban boundary layer can be affected by the surface and that the same forcing conditions may not be suitable for studying different urban scenarios. This paper presents a physically based and computationally efficient methodology to calculate forcing air temperatures for UCMs from meteorological data measured at operational weather stations. Operational weather stations are available for most cities in the world and are usually located in open areas outside the cities. The proposed methodology is satisfactorily evaluated against me-soscale atmospheric simulations and field data from Basel, Switzerland, and Toulouse, France.

Assessment of daytime outdoor comfort levels in and outside the urban area of Glasgow, UK.

Abstract: To understand thermal preferences and to define a preliminary outdoor comfort range for the local population of Glasgow, UK, an extensive series of measurements and surveys was carried out during 19 monitoring campaigns from winter through summer 2011 at six different monitoring points in pedestrian areas of downtown Glasgow. For data collection, a Davis Vantage Pro2 weather station equipped with temperature and humidity sensors, cup anemometer with wind vane, silicon pyranometer and globe thermometer was employed. Predictions of the outdoor thermal index PET (physiologically equivalent temperature) correlated closely to the actual thermal votes of respondents. Using concurrent measurements from a second Davis Vantage Pro2 weather station placed in a rural setting approximately 15 km from the urban area, comparisons were drawn with regard to daytime thermal comfort levels and urban–rural temperature differences (∆Tu-r) for the various sites. The urban sites exhibited a consistent lower level of thermal discomfort during daytime. No discernible effect of urban form attributes in terms of the sky-view factor were observed on ∆Tu-r or on the relative difference of the adjusted predicted percentage of dissatisfied (PPD*).

Experimental assessment of the solar energy potential in the gulf of Tunis, Tunisia

Abstract: This work carries out the availability of the global solar radiation over the site of Borj-Cedria in the gulf of Tunis (36°43′04″N latitude and 10°25′41″E longitude), Tunisia. Global solar radiation variability was assessed on hourly, daily, monthly and seasonal scales. Solar potential in the gulf of Tunis was evaluated using the solar radiation data collected by the meteorological NRG weather station installed in the Center of Research and Technologies of Energy (CRTEn) in the Borj-Cedria area. The collected measurements during the last three years (2008, 2009 and 2010) were based on 10 min time step. These data have allowed us to evaluate the global solar flux, the sun duration, the yearly and the seasonal frequency distribution of the global solar radiation. Moreover, a conventional model has been used to estimate the hourly solar radiation on a horizontal plane and it has been validated by experimental measurements in specific days. The results show that the global solar radiation predicted by the conventional model has a good agreement with the experimental data during the clear sky conditions with a mean absolute percentage error (MAPE) of 4.1%. However, the limitation of the conventional model appears under the cloudy sky weather which is proved by the highest value of relative error percentage reaching 14.26% occurred during the autumnal equinox day.

Characterizing uncertainty in species distribution models derived from interpolated weather station data

Abstract: Species distribution models (SDMs) are used to generate hypotheses regarding the potential distributions of species under different environmental conditions, such as forecasts of species range shifts in response to climate change and predictions of invasive species range expansions. However, an accurate description of species' geographic ranges as a function of the environment requires that species observations and climatic variables are measured at the same spatial and temporal resolution, which is usually not the case. Weather station data are interpolated and these resulting continuous data layers are incorporated into SDMs, often without any uncertainty assessment. Here we quantify the effects of three unrelated but complementary aspects of uncertainty in weather station interpolations on SDM performance using MaxEnt. We examine the influence of topographic heterogeneity, interannual variability, and distance to station on the over- and under-prediction of modeled North American bird distributions. Our species observations are derived from presence-absence information for 20 bird species with well-known distributions. These three metrics of uncertainty in interpolated weather station data have varying contributions to over- and under-prediction errors in SDMs. Topographic heterogeneity had the highest contribution to omission errors; the lowest contribution to commission errors was from Euclidean distance to station. The results confirm the importance of establishing an appropriate relational basis in time and space between species and climatic layers, providing key operational criteria for selection of species observations fed into SDMs. Our findings highlight the importance of identifying weather stations locations used in interpolated products, which will allow a characterization of some aspects of uncertainty and identification of regions where users need to be particularly careful when making a decision based on a SDM.

Modern climate of the Cát Tiên National Park (Southern Vietnam): Climatological data for ecological studies

Abstract: A method of using the standard network weather station data for local ecosystem research is considered on the example of the modern climate of the Cat Tien National Park (Southern Vietnam) and local climate change in 1980–2010. Special attention is focused on the environmental parameters, which play a role of the limiting factors. It is shown that the climate of Southern Vietnam responds with statistical significance to global climate change. Suggestions about the possible reactions of tropical monsoon forest ecosystem to climate change are given.

An analysis of the meteorological variables leading to apparent temperature in Australia: Present climate, trends, and global warming simulations

Abstract: This study is a comprehensive analysis of thermal comfort and apparent temperature around Australia. It includes a long-term historical trend analysis using observational weather station data, in which it was found that eight out of the ten chosen urban locations experienced warming trends in temperature and/or the apparent temperature over the second half of the twentieth century. Annual trends in temperature and apparent temperature were studied spatially across Australia using high resolution ERA Interim reanalysis data over the period 1979 to 2010. The reanalysis revealed that generally the apparent temperature is warming faster than the air temperature, amplifying the expected exposure to discomfort due to global warming in the subtropical region. Future apparent temperature trends were explored using high resolution Coupled Model Intercomparison Project 3 model data to assess the impacts of global warming on human comfort. A best practice model for the Australian climate was used as well as best case and worst case scenario models selected using the Commonwealth Scientific and Industrial Research Organisation Representative Climate Futures framework. It was found that at 2070 using the A1B emissions scenario the temperature is projected to warm faster than the apparent temperature by up to 1 °C in central Australia, suggesting that the cooling power of the wind can partially offset the impacts of global warming. This occurs in conjunction with the accelerated drying predicted to occur in many areas of Australia in future climates. Finally, the impact of the El Nino Southern Oscillation and the Southern Annular Mode on the spatial characteristics of the temperature and apparent temperature around Australia was studied. This revealed that the inherent atmospheric humidity variability of these large-scale processes resulted in milder thermal comfort conditions across Australia regardless of whether the temperature was anomalously warm or cool. Using an apparent temperature framework, this study looks into many facets of the Australian climate uncovering knowledge that is useful for risk assessments as well as future urban planning.

Evaluation of weather-based rice yield models in India

Abstract: The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India Initially, the results were obtained using 4 years (1994–1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner However, SIMRIW requires fine tuning for better results/decision making

A small unmanned aerial system (UAS) for coastal atmospheric research: preliminary results from New Zealand

Abstract: Experiments conducted in the low-altitude coastal atmosphere in New Zealand have demonstrated the potential of a new unmanned aerial system (UAS) for meteorological research. The Kahu unmanned aerial vehicle flies autonomously using GPS and pre-programmed waypoints, collecting observations of air temperature and relative humidity that are relayed to a ground-station near-instantaneously. Experiments conducted in the Hauraki Gulf, Auckland, show that the Kahu's radio transmission system can successfully transmit data across the ocean surface at distances up to 25 km. Accuracy of the meteorological data collected by the UAS was assessed via a direct comparison with weather station sensors and radiosonde soundings at heights of up to 500 m in the Bay of Plenty. Close agreement between the UAS, radiosonde and weather station data suggests that the Kahu UAS has considerable scope as a new field research tool in New Zealand, capable of providing reliable atmospheric data that can complement and even su...

Real-time flood forecasting coupling different postprocessing techniques of precipitation forecast ensembles with a distributed hydrological model. The case study of may 2008 flood in western Piemonte, Italy

Abstract: . In this work, we compare the performance of an hydrological model when driven by probabilistic rain forecast derived from two different post-processing techniques. The region of interest is Piemonte, northwestern Italy, a complex orography area close to the Mediterranean Sea where the forecast are often a challenge for weather models. The May 2008 flood is here used as a case study, and the very dense weather station network allows us for a very good description of the event and initialization of the hydrological model. The ensemble probabilistic forecasts of the rainfall fields are obtained with the Bayesian model averaging, with the classical poor man ensemble approach and with a new technique, the Multimodel SuperEnsemble Dressing. In this case study, the meteo-hydrological chain initialized with the Multimodel SuperEnsemble Dressing is able to provide more valuable discharge ranges with respect to the one initialized with Bayesian model averaging multi-model.

Computational intelligence models for solar radiation prediction

Abstract: The modeling of solar radiation for forecasting its availability is a key tool for managing photovoltaic (PV) plants and, hence, is of primary importance for energy production in a smart grid scenario. However, the variability of the weather phenomena is an unavoidable obstacle in the prediction of the energy produced by the solar radiation conversion. The use of the data collected in the past can be useful to capture the daily and seasonal variability, while measurement of the recent past can be exploited to provide a short term prediction. It is well known that a good measurement of the solar radiation requires not only a high class radiometer but even a correct management of the instrument. In order to reduce the cost related to the management of the monitoring apparatus, a solution could be to evaluate the PV plant performance using data collected by public weather station installed near the plant. In this paper, two computational intelligence models are challenged; two different ground global horizontal radiation dataset have been used: the first one is based on the data collected by a public weather station located in a site different to that one of the plant, the second one, used to validate the results, is based on data collected by a local station.

Hydrologic Effects of Size and Location of Fields Converted from Drained Pine Forest to Agricultural Cropland

Abstract: Hydrological effects of land-use change are of great concern to ecohydrologists and watershed managers, especially in the Atlantic coastal plain of the southeastern United States. The concern is attributable to rapid population growth and the resulting pressure to develop forested lands. Many researchers have studied these effects in various scales, with varying results. An extended watershed-scale forest hydrologic model, calibrated with 1996–2000 data, was used to evaluate long-term hydrologic effects of conversion to agriculture (corn–wheat–soybean cropland) of a 29.5-km2 intensively managed pine-forested watershed in Washington County in eastern North Carolina. Fifty years of weather data (1951–2000) from a nearby weather station were used for simulating hydrology to evaluate effects on outflows, evapotranspiration, and water table depth compared with the baseline scenario. Other simulation scenarios were created for each of five different percentages (10, 25, 50, 75, and 100%) of land-use con...

Road weather station acting as a wireless service hotspot for vehicles

Abstract: The European Eureka/Celtic Plus project CoMoSeF (Co-operative Mobility Services of the Future) aims to create co-operative mobility solutions (including devices and applications), feasible for large scale deployment. In practice this means combined vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I), communication system employing interactive example services related to safety and weather information exchange. In this paper we present FMI (Finnish Meteorological Institute) approach to employ CoMoSef vehicular networking entity by creating a specific service hotspot for vehicles bypassing the combined Road Weather Station (RWS)/Road Side Unit (RSU). Local road weather and route weather (a special type of weather service tailored for dedicated road stretches, constructed both from FMI meteorological systems data and the data collected from local RWSs) are the obvious services offered, but in addition to them there is a variety of services available, from specialized weather data into more general traffic information and local accident warnings. The ultimate aim is to provide data to vehicles regardless of their communication devices available. The supported media at the moment consists of IEEE 802.11p and traditional Wi-Fi communication operated through special vehicle computer, Android-based tablet PC or standard laptop computer, but it is expected to be supplemented at least with iPad- and Jolla-devices, respectively.

Prediction of yield and biomass productions: A remedy to climate change in semi-arid regions of Zimbabwe

Abstract: Received 11 February, 2013 Received in revised form 11 March, 2013 Accepted 18 March, 2013 One of the imminent threats posed by climate variability and change is food security in Zimbabwe's semi -arid regions like Masvingo. As an adaptive strategy crop forecasting was employed to improve crop productivity. The objective of the study was to investigate climatic characteristics responsible for yields in the maize, sorghum and millet crop varieties and to calibrate Food and Agriculture Organization (FAO)-AquaCrop model for crop forecasting purposes. AquaCrop simulation results were used together with empirical ones to see if the model could be relied on in crop forecasting. Seeds for the three crops were sown at the same time and were observed for five months from 1 November 2011 to 31 March 2012. Crop management practices were employed. An automated weather station was recording the soil moisture, air temperature and net radiation for the five months. The climatic data recorded by the station was used as input data in the model and it predicted yields for the crops. Comparison between simulated and observed parameters of the water balance, biomass production and final yield were used for the calibration of the model. The model gave a slightly higher harvest index (HI) (ratio of yield to biomass) than what had been obtained in the experimental treatments, with a 10% margin. The information from the station and model provided optimum temperatures and water requirements which essentially uphold water use efficiency especially where automated irrigation based on air temperatures is implemented. The results from this publication are from the first year stage only and therefore are subject to improvement.

Modeling and Forecasting Systems for Fusarium Head Blight and Deoxynivalenol Content in Wheat in Argentina

Abstract: In Argentina, wheat Fusarium Head Blight (FHB) is predominantly caused by Fusarium graminearum, being deoxynivalenol (DON) the main associated mycotoxin. The sporadic weather-induced nature of FHB in the Pampas region led to the development of weather-based disease and DON forecasting systems. Infective events were identified by head wetting resulting from syncronic occurrence of precipitation and high relative humidity, around wheat anthesis. Retrospective model predictions were able to identify synoptic situations and meteorological predictors of increasing space-temporal scale (for developing specific short-range and seasonal weather forecasts), regarding the disease. In the north-eastern quadrant of the Pampas region, greater disease levels were expected with greater August Southern Annular Mode values and dominance of meridional north-northeastern atmospheric circulation in September. In the southern, the Southern Oscillation index and variables associated to blocking action situations in the south (October), strongly helped to explain disease variability. Climate change impact was assessed retrospectively analyzing the trend lines of FHB incidence predictions (1931–2010), which showed light positive slopes, larger towards southern Pampas region. Prospectively, the anomaly map resulting from the difference between disease incidence estimated by future meteorological data (2071–2100, A2 scenario) and baseline climate (1961–1990), presented positive deviations in the southern Pampas region. The spatial distribution of model-based FHB incidence values using only land weather station network data was compared satisfactorily with those using both land and satellite data. Conclusions derived from FHB forecasting systems and specific weather forecasts are being used to assist producers in disease control measures to be employed.

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

Abstract: A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.