Research Article | Open Access
AirTemperature: Extensible Software Library to Generate Air Temperature Data
The development of a set of reusable libraries to support custom applications has become a goal in biophysical modeling projects. This is true for weather modeling as well. AirTemperature is a software component providing a collection of deterministic and stochastic approaches to generate atmospheric temperature data on daily and hourly time steps. Data generated on a daily time step consist of maximum and minimum air temperature and dew point temperature. Hourly estimations include air and dew point temperatures. The software design allows for extension of the models implemented without recompiling the component. The component, inclusive of hypertext help documentation files, is released as compiled .NET2 version, allowing application development in either programming environment. A sample client and a sample extension project using AirTemperature are provided as source code. A sample Web service and a Web application are also developed as examples of possible use of the component.
- J. F. Reynolds and B. Acock, “Modularity and genericness in plant and ecosystem models,” Ecological Modelling, vol. 94, no. 1, pp. 7–16, 1997.
- P. Papajorgji, H. W. Beck, and J. L. Braga, “An architecture for developing service-oriented and component-based environmental models,” Ecological Modelling, vol. 179, no. 1-2, pp. 61–76, 2004.
- B. Timothy, An Introduction to Object-Oriented Programming, Addison-Wesley, Reading, Mass, USA, 2nd edition, 1997.
- L. Carlini, G. Bellocchi, and M. Donatelli, “A library to generate synthetic precipitation data,” Agronomy Journal, vol. 98, no. 5, pp. 1312–1317, 2006.
- M. Donatelli, G. Bellocchi, and L. Carlini, “Sharing knowledge via software components: models on reference evapotranspiration,” European Journal of Agronomy, vol. 24, no. 2, pp. 186–192, 2006.
- M. Donatelli, L. Carlini, and G. Bellocchi, “A software component for estimating solar radiation,” Environmental Modelling and Software, vol. 21, no. 3, pp. 411–416, 2006.
- R. Confalonieri, G. Bellocchi, and M. Donatelli, “A software component to compute agro-meteorological indicators,” Environmental Modelling and Software. In press.
- M. Donatelli, G. Bellocchi, E. Habyarimana, S. Bregaglio, R. Confalonieri, and B. Baruth, “CLIMA, a modular weather generator,” in Proceedings of the 18th World IMACS Congress and MODSIM International Congress on Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, R. S. Anderssen, R. D. Braddock, and L. T. H. Newham, Eds., pp. 852–858, Cairns, Australia, July 2009, http://www.mssanz.org.au/modsim09/C3/donatelli_C3a.pdf.
- M. Donatelli, G. Bellocchi, E. Habyarimana, R. Confalonieri, and F. Micale, “An extensible model library for generating wind speed data,” Computers and Electronics in Agriculture, vol. 69, no. 2, pp. 165–170, 2009.
- D. P. Holzworth, N. I. Huth, and P. G. de Voil, “Simplifying environmental model reuse,” Environmental Modelling and Software, vol. 25, no. 2, pp. 269–275, 2010.
- P. A. Bernstein, T. Bergstraesser, J. Carlson, S. Pal, P. Sanders, and D. Shutt, “Microsoft repository version 2 and the open information model,” Information Systems, vol. 24, no. 2, pp. 71–98, 1999.
- G. Booch, J. Rumbaugh, and I. Jacobson, The Unified Modeling Language User Guide, Addison-Wesley, Reading, Mass, USA, 1999.
- C. Szypersky, D. Gruntz, and S. Murer, Component Software—Beyond Object-Oriented Programming, Addison-Wesley, London, UK, 2nd edition, 2002.
- R. M. Argent, A. Voinov, T. Maxwell et al., “Comparing modelling frameworks—a workshop approach,” Environmental Modelling and Software, vol. 21, no. 7, pp. 895–910, 2006.
- J.-E. Bergez, P. Debaeke, J.-M. Deumier et al., “MODERATO: an object-oriented decision tool for designing maize irrigation schedules,” Ecological Modelling, vol. 137, no. 1, pp. 43–60, 2001.
- P. B. Woodbury, R. M. Beloin, D. P. Swaney, B. E. Gollands, and D. A. Weinstein, “Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems,” Ecological Modelling, vol. 150, no. 3, pp. 211–238, 2002.
- J. M. Aaslyng, J. B. Lund, N. Ehler, and E. Rosenqvist, “IntelliGrow: a greenhouse component-based climate control system,” Environmental Modelling and Software, vol. 18, no. 7, pp. 657–666, 2003.
- R. Matthews, “The People and Landscape Model (PALM): towards full integration of human decision-making and biophysical simulation models,” Ecological Modelling, vol. 194, no. 4, pp. 329–343, 2006.
- T. M. Shenk and A. B. Franklin, Modeling in Natural Resource Management: Development, Interpretation, and Application, Edited Island Press, Washington, DC, USA, 2001.
- H. S. Mavi, Agrometeorology: Principles and Applications of Climate Studies in Agriculture, Haworth Press, Binghamton, NY, USA, 2004.
- M. Donatelli and A. E. Rizzoli, “A design for framework-independent model components of biophysical systems,” in Proceedings of the International Congress on Environmental Modelling and Software (IEMS '08), M. Sànchez-Marrè, J. Béjar, J. Comas, A. E. Rizzoli, and G. Guariso, Eds., vol. 2, pp. 727–734, Barcelona, Spain, July 2008.
- R. D. Harmel, G. Johnson, and C. W. Richardson, “The GEM experience: weather generator technology development in the USDA,” Bulletin of the American Meteorological Society, vol. 83, no. 7, pp. 954–957, 2002.
- A. D. Nicks and G. A. Gander, “Cligen: a weather generator for climate inputs to water resources and other models,” in Proceedings of the 5th International Conference on Computer in Agriculture, D. G. Watson, F. S. Zanueta, and T. V. Harrison, Eds., pp. 3–94, American Society of Agricultural Engineers, Orlando, Fla, USA, February 1994.
- C. W. Richardson and D. A. Wright, “WGEN: a model for generating daily weather variables,” Tech. Rep. ARS-8, U.S. Department of Agriculture, Agricultural Research Service, Washington, DC, USA, 1984.
- G. L. Johnson, C. L. Hanson, S. P. Hardegree, and E. B. Ballard, “Stochastic weather simulation: overview and analysis of two commonly used models,” Journal of Applied Meteorology, vol. 35, no. 10, pp. 1878–1896, 1996.
- M. A. Semenov, R. J. Brooks, E. M. Barrow, and C. W. Richardson, “Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates,” Climate Research, vol. 10, no. 2, pp. 95–107, 1998.
- C. O. Stöckle, R. L. Nelson, M. Donatelli, and F. Castellvì, “ClimGen: a flexible weather generation program,” in Proceedings of the 2nd International Symposium Modelling Cropping Systems, M. Bindi, M. Donatelli, J. Porter, and M. K. van Ittersum, Eds., pp. 229–230, Florence, Italy, July 2001.
- F. Danuso, “Climak: a stochastic model for weather data generation,” Italian Journal of Agronomy, vol. 6, pp. 57–71, 2002.
- C. O. Stöckle, Atmosphere: Derived Climate Variables and Time Interpolation, BSysE 562 lecture, Pullman, Wash, USA, 2002.
- E. Linacre, Climate Data and Resources: A Reference and Guide, Routledge, London, UK, 1992.
- C. W. Richardson, “Stochastic simulation of daily precipitation, temperature, and solar radiation,” Water Resources Research, vol. 17, no. 1, pp. 182–190, 1981.
- J. Remund and J. Page, “Chain of algorithms: short- and longwave radiation with associated temperature prediction resources,” SoDa Deliverable D5-2-2/3. Internal document, 2002.
- G. S. Campbell, Soil Physics with BASIC: Transport Models for Soil-Plant Systems, Elsevier, Amsterdam, The Netherlands, 1985.
- J. Goudriaan and H. H. van Laar, Modelling Potential Crop Growth Processes, Kluwer Academic Publishers, London, UK, 1994.
- J. E. Ephrath, J. Goudriaan, and A. Marani, “Modelling diurnal patterns of air temperature, radiation wind speed and relative humidity by equations from daily characteristics,” Agricultural Systems, vol. 51, no. 4, pp. 377–393, 1996.
- C. H. Porter, N. B. Pickering, J. W. Jones, and G. Hoogenboom, “Weather module in DSSAT v. 4.0 documentation and source code listing,” Agricultural and Biological Engineering Department Research Report 2000-1203, University of Florida, Gainesville, Fla, USA, 2000.
- C. Gracia, S. Sabaté, and A. Sánchez, GOTILWA+: A Forest Growth Simulation Model. Model Documentation and User's Guide, Center for Ecological Research and Forestry Applications, Barcelona, Spain, 2003.
- D. Dumortier, “Prediction of air temperatures from solar radiation,” Tech. Rep. SoDa-5-2-4, CNRS-ENTPE, 2002.
- E. T. Linacre, “A simple formula for estimating evaporation rates in various climates, using temperature data alone,” Agricultural Meteorology, vol. 18, no. 6, pp. 409–424, 1977.
- J. V. Iribarne and W. L. Godson, Atmospheric Thermodynamics, D. Reidel, 1981.
- J. S. Kimball, S. W. Running, and R. Nemani, “An improved method for estimating surface humidity from daily minimum temperature,” Agricultural and Forest Meteorology, vol. 85, no. 1-2, pp. 87–98, 1997.
- R. G. Allen, L. S. Pereira, D. Raes, and M. Smith, “Crop evapotranspiration: guidelines for computing crop water requirements,” Irrigation & Drainage Paper 56. UN-FAO, Rome, Italy, 1998.
- K. G. Hubbard, R. Mahmood, and C. Carlson, “Estimating daily dew point temperature for the northern Great Plains using maximum and minimum temperature,” Agronomy Journal, vol. 95, no. 2, pp. 323–328, 2003.
- Meteotest, Meteonorm version 5.0. The global meteorological database for engineers, planners and education. Software and data on CD-ROM, James and James, London, UK, 2003.
- B. Meyer, Object-Oriented Software Construction, Prentice-Hall, Upper Saddle River, NJ, USA, 2nd edition, 1997.
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