A Library to Generate Synthetic Precipitation Data

Carlini, Laura; Bellocchi, Gianni; Donatelli, Marcello

doi:10.2134/agronj2005.0210

Cited by 6 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Garbrecht and Zhang (2003) showed that because of inherent characteristics of random number generators, screening the generated precipitation to ensure representation of the climate of interest allows for shorter simulation duration and greater ability to simulate subtle changes in precipitation such as those associated with seasonal forecasts. Carlini et al (2006) developed a library to generate synthetic precipitation data for future crop modeling applications.…”

Section: Historical Overview and Discussionmentioning

confidence: 99%

Winds of Change: A Century of Agroclimate Research

Steiner

Hatfield²

2008

Agronomy Journal

View full text Add to dashboard Cite

Climate has been of primary concern from the beginning of agricultural research. Early in the 20th century, climatology and agronomy evolved separately, focusing primarily on production agriculture and crop adaptation. Concepts developed include thermal units and water use efficiency. The integrated discipline of agroclimatology developed in the mid‐20th century. As theoretical understanding evolved, numerous papers related to agroclimatology were named Citation Classics. Spectral properties of plants and soils were identified that underpin today's remote sensing technologies. Commercialization of instrumentation enhanced our ability to efficiently collect data using standardized methods. Private and public‐sector partnerships advanced research capacity. Later in the 20th century, research focus shifted toward integrating knowledge into crop growth and agronomic models. Remote sensing provided capacity to gain theoretical and practical understanding of regional scale processes. In the early 21st century, recognition of earth as a system along with inter‐related human systems is driving research and political agendas. There is a pressing need to change our data‐rich to an information‐rich environment. The emerging cyberinformatics field along with natural resource and agricultural system models allow us to apply climate information to assessments and decision support related to water supply, production, environmental management, and other issues. Solutions to today's problems require interdisciplinary and multi‐sectoral teams. While needs have never been greater, fewer universities maintain critical mass required to offer advance degrees in agroclimatology. It will be increasingly important that agrclimatology attract top students and provide training and practical experience in conducting integrated systems research, communications, and team skills.

show abstract

Section: Historical Overview and Discussionmentioning

confidence: 99%

Winds of Change: A Century of Agroclimate Research

Steiner

Hatfield²

2008

Agronomy Journal

View full text Add to dashboard Cite

show abstract

“…In order to possibly include legacy data sources into newly developed systems, object-oriented development has emerged steadily as a paradigm that focuses on granularity, productivity, and low maintenance [3]. Several papers have been recently published in agroecological journals [4][5][6][7][8][9][10] targeting at reusable dynamic link libraries either within the Microsoft.NET framework (http://www.microsoft.com/NET/) or using the SUN Java platform (http://java.sun.com/). Such solutions reflect a style of programming referred to as component-oriented programming that has become the leading methodology in developing systems in a variety of domains, including agroecological modeling [2].…”

Section: Introductionmentioning

confidence: 99%

“…This is the reason why component-oriented tools have been recently developed to fit this need, that is, ET for calculating evapotranspiration and related variables [5], GSRad for estimating synthetic values of solar radiation [6], Rain [4] for generating precipitation data, and Wind [9] for generating wind speed data. The components mentioned provide a set of alternate models to estimate variables specific for the domain targeted and are implemented using a software architecture which promotes reusability [21].…”

Section: Introductionmentioning

confidence: 99%

AirTemperature: Extensible Software Library to Generate Air Temperature Data

Donatelli¹,

Bellocchi²,

Habyarimana³

et al. 2010

SRX Computer Science

Self Cite

View full text Add to dashboard Cite

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.

show abstract