Accurate Weather Research Articles

Electrophysiological assessment of water stress in fruit-bearing woody plants

Development and evaluation of a real-time plant water stress sensor, based on the electrophysiological behavior of fruit-bearing woody plants is presented. Continuous electric potentials are measured in tree trunks for different irrigation schedules, inducing variable water stress conditions; results are discussed in relation to soil water content and micro-atmospheric evaporative demand, determined continuously by conventional sensors, correlating this information with tree electric potential measurements.Systematic and differentiable patterns of electric potentials for water-stressed and no-stressed trees in 2 fruit species are presented. Early detection and recovery dynamics of water stress conditions can also be monitored with these electrophysiology sensors, which enable continuous and non-destructive measurements for efficient irrigation scheduling throughout the year.The experiment is developed under controlled conditions, in Faraday cages located at a greenhouse area, both in Persea americana and Prunus domestica plants. Soil moisture evolution is controlled using capacitance sensors and solar radiation, temperature, relative humidity, wind intensity and direction are continuously registered with accurate weather sensors, in a micro-agrometeorological automatic station located at the experimental site.The electrophysiological sensor has two stainless steel electrodes (measuring/reference), inserted on the stem; a high precision Keithley 2701 digital multimeter is used to measure plant electrical signals; an algorithm written in MatLab®, allows correlating the signal to environmental variables. An electric cyclic behavior is observed (circadian cycle) in the experimental plants. For non-irrigated plants, the electrical signal shows a time positive slope and then, a negative slope after restarting irrigation throughout a rather extended recovery process, before reaching a stable electrical signal with zero slope. Well-watered plants presented a continuous signal with daily maximum and a minimum EP of similar magnitude in time, with zero slope. This plant electrical behavior is proposed for the development of a sensor measuring real-time plant water status.

Assessing the potential of an algorithm based on mean climatic data to predict wheat yield

The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3–4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.

Spiro K. Antiochos Receives 2013 John Adam Fleming Medal: Citation

The John Adam Fleming Medal is awarded for “original research and technical leadership in geomagnetism, atmospheric electricity, aeronomy, space physics, and related sciences.” Originality and technical leadership are exactly the characteristics that distinguish the research of Spiro K. Antiochos. Spiro possesses a truly unique combination of physical insight, creativity, and mastery of the concepts and mathematical and numerical tools of space physics. These talents have allowed him to develop completely original theories for major observational problems and to test and refine those theories using sophisticated numerical simulation codes that he himself helped to develop. Spiro's physical insight is especially impressive. He has an uncanny ability to identify the fundamental aspects of complex problems and to see physical connections where others do not. This can sometimes involve ideas that may initially seem counterintuitive to those with less creativity. Many of Spiro's revolutionary advances have opened up whole new areas of study and shaped the course of space physics. Examples include the breakout model for coronal mass ejections (CMEs), the S‐web model for the slow solar wind, and the thermal nonequilibrium model for solar prominences. The breakout model is of special significance to AGU as it strives to promote science for the betterment of humanity. CMEs are enormous explosions on the Sun that can have major “space weather” impacts here on Earth. They affect technologies ranging from communication and navigation systems to electrical power grids. Breakout is the leading theory for why CMEs occur and may one day be the foundation for more accurate space weather forecasting.

Indigenous Knowledge use in seasonal weather forecasting in Tanzania : the case of semi-arid central Tanzania

This paper is based on part of the findings of a PhD study that was carried out to determine how farmers have used indigenous knowledge (IK) to adapt to climate change and variability in the semi-arid region of central Tanzania. Two villages, Maluga and Chibelela, were used as the case studies. The study applied Rogers' (2003) Diffusion of Innovations theory and model. It adopted a predominantly qualitative approach and a post-positivist paradigm. The study population was made up of farmers, agricultural extension officers and the Climate Change Adaptation in Africa project manager. The principal data collection methods were interviews and focus group discussions. The qualitative data collected were subjected to content analysis whereas quantitative data were analysed with the help of SPSS to generate descriptive statistics. The findings revealed that the farmers in the two villages under study perceive conventional information on weather as unreliable and untimely. Consequently, the farmers turned to IK to predict weather patterns and make the necessary farming adjustments. It was established that uncertainty about seasonal weather forecasts is one of the most critical factors which forces farmers to continue using IK. Farmers' knowledge of birds, insects, plants, animals, wind direction and astronomical indicators is used to predict weather patterns. The recommendations include the provision of timely and accurate weather forecast information to the farmers to enhance their coping and adaptation strategies under varying climate conditions; and a clear policy framework on the dissemination of information related to weather patterns in rural Tanzania.

Weather forecasting and dynamic scheduling for a modern cm/mm wave radiotelescope

In order to maximize the productivity of a state of the art scientific instrument, concurrent projects that will be performed by the instrument itself should be scheduled and prioritized appropriately. In the case of radioastronomical facilities, the precedences are set on the basis of many parameters amongst which meteo-climatic variables play a fundamental role. The Sardinia Radio Telescope (SRT) is nearly completed, and soon it will start performing radioastronomical observations in the 0.3–100 GHz frequency range. It is known that centimeter and especially millimeter wavelengths are affected by the atmospheric water vapor content and weather conditions. In order to increase the performances of observations at higher frequencies, detailed knowledge of the climatology of the telescope site is needed, moreover, accurate weather predictions that range several days ahead are particularly useful. Such information is mandatory for the implementation of a dynamic scheduling system through which the observations are scheduled according to the oncoming weather conditions. In this paper we compare the forecasts produced by a numerical weather prediction (NWP) model, provided by the local weather service, to the measurements conducted at the SRT site with ground-based instruments. The comparisons are used to validate the NWPs in order to understand if they could be used for scheduling radioastronomical observations.Our analysis, clearly indicates that the model predictions are representative for the radiotelescope site. Indeed, the forecasts of water vapor and brightness temperatures, made up to 36 hours ahead, are consistent with the on-site measurements; wind forecasts are also correlated to the ground level measurements. In the score analysis we have deducted that the NWP model, on average, is consistent with the measurements more than 65 % of the time, implying that the majority of the radioastronomical observations would be performed in weather conditions which are appropriate to the frequency that is being used. By using the available NWP model and the on-site instrumentation, it is feasible to implement a dynamic scheduling system for the SRT.

Dynamic thermal model of solar PV systems under varying climatic conditions

The operating temperature of photovoltaic (PV) modules plays a central role in the photovoltaic energy conversion process, because the output voltage and, thereby, the produced output power decreases with increasing module temperature. The thermal response of PV modules is dynamic to changes in the climatic conditions affecting to the module. Therefore, a steady state model of module temperature cannot be justified.This paper presents a dynamic thermal model based on the total energy balance in the PV module. Main heat transfer mechanisms between the module and its environment have been modelled theoretical. The model is verified by the measurements data of the TUT solar photovoltaic power station research plant, which contains an accurate weather station, solar radiation measurements and a mesh of irradiance and module temperature measurements. A systematic sensitivity analysis of site-specific parameters was carried out to fine-tune the dynamic thermal model. The model was validated using time series of 1-s measurements data of three summer months and was found to differ less than 2°C from the measured module temperatures 80% of the time.

Radiometric Calibration Accuracy of GOES Sounder Infrared Channels

Quality infrared (IR) radiances and their derived products from the Geostationary Environmental Operational Satellite (GOES) Sounder are very important data sources to weather prediction and nowcasting applications for the continental United States and adjacent ocean regions. With demanding requirements for more accurate weather nowcasting models and climate change studies, it is necessary to assess and improve the radiometric calibration accuracy of the GOES Sounder data. The objective of this paper is to examine the GOES Sounder IR radiometric calibration accuracy, and the diurnal calibration variation using intercalibration with two well-calibrated hyperspectral radiometers onboard low earth orbit satellites, the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite and the Infrared Atmospheric Sounding Interferometer (IASI) on the Metop-A satellite. The results show that most sounder IR channels of GOES-11 through GOES-15 are well calibrated outside of the satellite midnight effect time period, with a less than 0.5 K of mean bias of brightness temperature with respect to IASI. Yet, the impact of the satellite midnight effect on the radiance quality varies greatly at different IR channels among different satellites. Further research is needed to understand the changes of instrument environmental flux on the GOES IR radiance around satellite midnight.

Seasonal variations effect on trauma admissions: Myth or reality?

It has been long hypothesised that the volume of trauma is related to the weather. This hypothesis has been strongly supported by various studies showing this relationship both in adult and paediatric populations. Projection of admission figures based on weather forecasting has the potential to become a significant tool in predicting the short to medium term workload and therefore improve the provision of emergency care. To achieve that, there is a need for more accurate weather forecasting and a better understanding of how weather affects workload. This would allow for evidence based changes in the allocation of resources.

Operation of TUT Solar PV Power Station Research Plant under Partial Shading Caused by Snow and Buildings

A grid connected solar photovoltaic (PV) research facility equipped with comprehensive climatic and electric measuring systems has been designed and built in the Department of Electrical Engineering of the Tampere University of Technology (TUT). The climatic measuring system is composed of an accurate weather station, solar radiation measurements, and a mesh of irradiance and PV module temperature measurements located throughout the solar PV facility. Furthermore, electrical measurements can be taken from single PV modules and strings of modules synchronized with the climatic data. All measured parameters are sampled continuously at 10 Hz with a data-acquisition system based on swappable I/O card technology and stored in a database for later analysis. The used sampling frequency was defined by thorough analyses of the PV system time dependence. Climatic and electrical measurements of the first operation year of the research facility are analyzed in this paper. Moreover, operation of PV systems under partial shading conditions caused by snow and building structures is studied by means of the measured current and power characteristics of PV modules and strings.

Research of Maneuver Ship Meteorological Instrument Data Real-Time Acquisition and Processing System

The maneuver ship meteorological instrument --Data acquisition and transmission means backward, timeliness, The data can not be collected timely and effectively used in meteorological support the status quo, Ship data collection, transmission and processing mechanisms and key technology research in the sea channel under unstable conditions, Makes data center located on the shore a timely and effective manner to get the maneuver ship meteorological instrument data, The ship into the sea motorized automatic weather observation stations, Enhanced the existing meteorological live display system observation data time density Provide more accurate weather forecast, meteorological support command decisions in a timely manner, the dense data services.

The Environmental Impact of El Nino Southern Oscillation Forecasts

Yearly weather variability has an impact on agricultural supply and farmer welfare. More accurate weather predictions may increase net returns for farmers but the indirect environmental impact of forecasts has not been examined. A bioeconomic model including weather information examines the impact of agricultural activities on water quality in Lawrence County, Alabama. This study reveals that if farmers would adopt accurate weather predictions, their net returns may increase by 21% while the nitrogen loss associated with the agricultural activities would reduce by 1.96% in the entire area.

Multischeme ensemble forecasting of surface temperature using neural network over Turkey

The ensemble method has long been used to reduce the errors that are caused by initial conditions and/or parameterizations of models in forecasting problems. In this study, neural network (NN) simulations are applied to ensemble weather forecasting. Temperature forecasts averaged over 2 weeks from four different forecasts are used to develop the NN model. Additionally, an ensemble mean of bias-corrected data is used as the control experiment. Overall, ensemble forecasts weighted by NN with feed forward backpropagation algorithm gave better root mean square error, mean absolute error, and same sign percent skills compared to those of the control experiment in most stations and produced more accurate weather forecasts.

Using the National Digital Forecast Database for model-based building controls

Abstract An accurate short-term weather forecast enhances the performance of model-based control strategies for a building. Most existing short-term forecast methods and models are based on historical archives of weather variables observed about an individual building. This practice leads to ask: 1) Does a short-term forecast model based on a collection of the past data have sufficient potential to predict future behavior, which is inherently random?; 2) If historical data is not available, or if only a limited number of weather variables is available, what are the other alternatives?; and 3) Would it be possible to derive a relevant weather data set from an incomplete historical data-driven model? The National Digital Forecast Database (NDFD) XML may answer these questions. This paper discusses an applicability of the NDFD XML for model-based building control solutions. It also presents a simplified, easily implementable, and reliable method to predict hourly global horizontal solar radiation. The short-term weather forecast method using the NDFD XML shows an outstanding performance of forecasting erratic and sporadic characteristics of weather, particularly when compared to the historical data-driven method. However, its forecast performance is not always accurate due to the inherent irregularity of weather. In order to increase robustness of model-based controls, we recommend that short-term weather forecasts should be considered as possessing scenario uncertainty . Including multiple scenarios into formulation of control problem can effectively describe scenario uncertainty when part of scenarios account for such erratic nature.

Operational profiling of temperature using ground-based microwave radiometry at Payerne: prospects and challenges

Abstract. The motivation of this study is to verify theoretical expectations placed on ground-based microwave radiometer (MWR) techniques and to confirm whether they are suitable for supporting key missions of national weather services, such as timely and accurate weather advisories and warnings. We evaluate reliability and accuracy of atmospheric temperature profiles retrieved continuously by the microwave profiler system HATPRO (Humidity And Temperature PROfiler) operated at the aerological station of Payerne (MeteoSwiss) in the time period August 2006–December 2009. Assessment is performed by comparing temperatures from the radiometer against temperature measurements from a radiosonde accounting for a total of 2107 quality-controlled all-season cases. In the evaluated time period, the MWR delivered reliable temperature profiles in 86% of all-weather conditions on a temporal resolution of 12–13 min. Random differences between MWR and radiosonde are down to 0.5 K in the lower boundary layer and increase to 1.7 K at 4 km height. The differences observed between MWR and radiosonde in the lower boundary layer are similar to the differences observed between the radiosonde and another in-situ sensor located on a close-by 30 m tower. Temperature retrievals from above 4 km contain less than 5% of the total information content of the measurements, which makes clear that this technique is mainly suited for continuous observations in the boundary layer. Systematic temperature differences are also observed throughout the retrieved profile and can account for up to ±0.5 K. These errors are due to offsets in the measurements of the microwave radiances that have been corrected for in data post-processing and lead to nearly bias-free overall temperature retrievals. Different reasons for the radiance offsets are discussed, but cannot be unambiguously determined retrospectively. Monitoring and, if necessary, corrections for radiance offsets as well as a real-time rigorous automated data quality control are mandatory for microwave profiler systems that are designated for operational temperature profiling. In the analysis of a subset of different atmospheric situations, it is shown that lifted inversions and data quality during precipitation present the largest challenges for operational MWR temperature profiling.

Towards the probabilistic Earth‐system simulator: a vision for the future of climate and weather prediction

AbstractThere is no more challenging problem in computational science than that of estimating, as accurately as science and technology allows, the future evolution of Earth's climate; nor indeed is there a problem whose solution has such importance and urgency. Historically, the simulation tools needed to predict climate have been developed, somewhat independently, at a number of weather and climate institutes around the world. While these simulators are individually deterministic, it is often assumed that the resulting diversity provides a useful quantification of uncertainty in global or regional predictions. However, this notion is not well founded theoretically and corresponding ‘multi‐simulator’ estimates of uncertainty can be prone to systemic failure. Separate to this, individual institutes are now facing considerable challenges in finding the human and computational resources needed to develop more accurate weather and climate simulators with higher resolution and full Earth‐system complexity. A new approach, originally designed to improve reliability in ensemble‐based numerical weather prediction, is introduced to help solve these two rather different problems. Using stochastic mathematics, this approach recognizes uncertainty explicitly in the parametrized representation of unresolved climatic processes. Stochastic parametrization is shown to be more consistent with the underlying equations of motion and, moreover, provides more skilful estimates of uncertainty when compared with estimates from traditional multi‐simulator ensembles, on time‐scales where verification data exist. Stochastic parametrization can also help reduce long‐term biases which have bedevilled numerical simulations of climate from the earliest days to the present. As a result, it is suggested that the need to maintain a large ‘gene pool’ of quasi‐independent deterministic simulators may be obviated by the development of probabilistic Earth‐system simulators. Consistent with the conclusions of the World Summit on Climate Modelling, this in turn implies that individual institutes will be able to pool human and computational resources in developing future‐generation simulators, thus benefitting from economies of scale; the establishment of the Airbus consortium provides a useful analogy here. As a further stimulus for such evolution, discussion is given to a potential new synergy between the development of dynamical cores, and stochastic processing hardware. However, it is concluded that the traditional challenge in numerical weather prediction, of reducing deterministic measures of forecast error, may increasingly become an obstacle to the seamless development of probabilistic weather and climate simulators, paradoxical as that may appear at first sight. Indeed, going further, it is argued that it may be time to consider focusing operational weather forecast development entirely on high‐resolution ensemble prediction systems. Finally, by considering the exceptionally challenging problem of quantifying cloud feedback in climate change, it is argued that the development of the probabilistic Earth‐system simulator may actually provide a route to reducing uncertainty in climate prediction. Copyright © 2012 Royal Meteorological Society

Evaluation of weather datasets for building energy simulation

In recent years, calibrated energy modeling of residential and commercial buildings has gained importance in a retrofit-dominated market. Accurate weather data play an important role in this calibration process and projected energy savings. It would be ideal to measure weather data at the building location to capture relevant microclimate variation but this is generally considered cost-prohibitive. There are data sources publicly available with high temporal sampling rates but at relatively poor geospatial sampling locations. To overcome this limitation, there are a growing number of service providers that claim to provide real time and historical weather data necessary for building modeling at 15–40km2 grid across the globe; common variables such as temperature and precipitation have been constructed on ∼1km2 grids [1]. Unfortunately, there is limited documentation from 3rd-party sources attesting to the accuracy of this data. This paper compares provided weather characteristics with data collected from a weather station inaccessible to the service providers. Monthly average dry bulb temperature; relative humidity; direct normal, diffuse and global solar radiation; wind speed and wind direction are statistically compared. Moreover, we ascertain the relative contribution of each weather variable and its impact on building loads. Annual simulations are performed for three different building types, including a closely monitored and automated energy efficient research building. The comparison shows that the difference for an individual variable can be as high as 90%. In addition, annual building energy consumption can vary by ±7% while monthly building loads can vary by ±40% as a function of the provided location's weather data.

한국기상청 영역기상방송(WE-FAX) 서비스 개선에 관한 연구

Even though KMA(Korea Meteorological Administration) has been doing WE-FAX service in past 40 years, most of korean ship`s officers use Japan/USA WE-FAX instead of KMA WE-FAX during passage in the NW Pacific. In this regards, the authors carry out the research on the improvement of KMA WE-FAX service, examining the officers`s opinions to KMA WE-FAX service along with comparing Korea, Japan & USA synoptic weather charts. As a result, it is suggested that (1) Have KMA WE-FAX service known to the officers in the course of education and training, (2) Persuade ocean-going ships to participate VOS to provide more accurate weather charts. (3) Provide additional weather charts such as Wave analysis, Surface forecast and put useful weather informations on weather charts to enhance navigational safety.

Geostatistical Model Averaging for Locally Calibrated Probabilistic Quantitative Precipitation Forecasting

Accurate weather benefit many key societal functions and activities, including agriculture, transportation, recreation, and basic human and infrastructural safety. Over the past two decades, ensembles of numerical weather prediction models have been developed, in which multiple estimates of the current state of the atmosphere are used to generate probabilistic forecasts for future weather events. However, ensemble systems are uncalibrated and biased, and thus need to be statistically postprocessed. Bayesian model averaging (BMA) is a preferred way of doing this. Particularly for quantitative precipitation, biases and calibration errors depend critically on local terrain features. We introduce a geostatistical approach to modeling locally varying BMA parameters, as opposed to the extant method that holds parameters constant across the forecast domain. Degeneracies caused by enduring dry periods are overcome by Bayesian regularization and Laplace approximations. The new approach, called geostatistical model averaging (GMA), was applied to 48-hour-ahead forecasts of daily precipitation accumulation over the North American Pacific Northwest, using the eight-member University of Washington Mesoscale Ensemble. GMA had better aggregate and local calibration than the extant technique, and was sharper on average.

Determination of accuracy level of agricultural spraying application in Sanliurfa/ Turkey

When calibration, spraying height, applied pressure, volume rate, nozzle type and application time of equipment used in pesticide applications are incorrect, this causes the amount of agricultural pesticide applied per unit area to be more or less needed. A survey study was carried out on farmers in order to determine whether or not they adjust application pressure of pesticide equipment, nozzle type, volume rate, spraying height and calibration of spraying equipment needed for pesticide application to have values, and also whether or not they carry out agricultural pesticide application in accurate weather conditions such as wind speed, air temperature, relative humidity, temperature and application time. This research was conducted in 2008 by randomly determining 110 agricultural organizations located in villages in the center of Sanliurfa/Turkey and its districts. Survey study was carried out by taking data from pesticide applications processes made on products such as cotton, wheat, barley, lentils and corn which have been intensely produced in the region. It was determined that in general, farmers operated field sprayer at very high pressures in agricultural pesticide application and they did not adjust travel speed of boom sprayer based on the calibration of pesticide application equipment. Moreover, based on data obtained from survey studies,application operators and farmers did not know values of wind speed, temperature and relative humidity required for agricultural pesticide applications. Key words: Pesticide spraying applications, survey, accuracy level, spraying parameters.

Weather, Climate, and the New Energy Economy

What: more than 100 participants, including representatives of academia, business, and government, discussed the nexus of weather and climate with the energy sector When: 17–21 January 2010 Where: atlanta, georgia t hough the relevance of weather to the energy industry’s predictions of energy demand (load) has long been recognized, only recently has the crucial role of meteorological information in the industry’s predictions of supply (source) been appre ciated. As increasing amounts of renewable energy are being brought onto the electric grid, the need for improved weather observations and forecasts across a range of time scales is growing. At this meeting, discussions centered on creative ways to obtain new measurements, improved models, and other informa tion required to support the instantaneous and con tinuous requirement to balance supply and demand in both traditional and renewable energy. A town-hall meeting, whose keynote speech was delivered by AMS President Tom Karl, kicked off this First Conference by outlining some of the key meteorological problems hindering greater use of renewable energy and the need for collaboration among private, public, and academic sectors. The conference continued with participants discussing the value and speed of delivery of accurate forecasts of temperature, humidity, precipitation, wind speeds, and cloud cover, which influence energy demand for heating, cooling, and lighting, as well as the timing of certain industrial and manufacturing processes that depend on certain weather conditions. Participants attempted to bridge the gap between meteorology and the energy industry by discussing the information that those in the two respective fields need from the other. Meteorologists had the opportunity to learn about unique and challenging aspects of the energy trading market. This market’s incredible volatility, in which energy prices can change by a factor of as much as 3.8 within one day, as well as its possibility for negative prices, meaning that traders actually sometimes pay for others to take excess electricity to keep demand and supply balanced, leads to the prime importance of accurate weather forecasts. Deviations from the day-ahead forecast can lead to sudden and severe changes in market conditions and prices; millions of dollars are made and lost within a period of an hour, based on weather forecasts. The paucity of relevant observations for improving forecasts of winds at turbine heights (~100 m) for onshore and offshore wind power, and of clouds (insolation) and aerosols for solar power, led to discussions of how to fill these data gaps. Techniques using remote sensing by ground-based wind profilers, radars, and AFFILIATION: Marquis—noaa earth System research laboratory CORRESPONDING AUTHOR : melinda marquis, noaa/eSrl, 325 Broadway, Boulder, Co 80305 e-mail: melinda.marquis@noaa.gov