LARS-WG is a model simulating time-series of daily weather at a single site. It can be used:

• to generate long time-series suitable for the assessment of agricultural and hydrological risk;
• to provide the means of extending the simulation of weather to unobserved locations;
• to serve as a computationally inexpensive tool to produce daily site-specific climate scenarios for impact assessments of climate change.

LARS-WG version 5.0 includes climate scenarios based on the fourteen Global Climate Models (GCMs) which have been used in the latest IPCC 4th Assessment Report (2007). This large datasets of predictions of future climate was produced by leading modelling groups worldwide who performed a set of coordinated climate experiments in which numerous GCMs have been run for a common set of experiments and various emission scenarios. Multi-model ensembles allow to explore the uncertainty in climate predictions resulting from structural differences in the global climate model design as well as uncertainty in variations of initial conditions or model parameters. The new version also improves simulation of extreme weather events, such as extreme daily precipitation and long dry spells or heat waves. LARS-WG has been well validated in diverse climates around the world.

• Racsko P, Szeidl L & Semenov MA (1991) A serial approach to local stochastic weather models. Ecological Modelling, 57 :27-41 (djvu)
• Semenov MA & Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change, 35: 397-414 (pdf)
• Semenov MA, Brooks RJ, Barrow EM & Richardson CW (1998) Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research, 10:95-107 (pdf)
• Semenov MA & Brooks RJ(1999) Spatial interpolation of the LARS-WG weather generator in Great Britain. Climate Research, 11:137-148 (pdf)
• Lawless C & Semenov MA (2005) Assessing lead-time for predicting wheat growth using a crop simulation model. Agricultural and Forest Meteorology, 135:302-313 (pdf)
• Semenov MA & Doblas-Reyes FJ (2007) Utility of dynamic seasonal weather forecasts in predicting crop yield. Climate Research, 34:71-81 (pdf)
• Semenov MA (2007) Development of high-resolution UKCIP02-based climate change scenarios in the UK. Agricultural and Forest Meteorology, 144:127-138 (pdf)
• Semenov MA (2008) Simulation of weather extreme events by stochastic weather generator. Climate Research, 35:203-212 (pdf)
• Semenov MA (2009) Impacts of climate change on wheat in England and Wales. Royal Society Interface, 6:343-350 (pdf)