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 15 Global Climate Models (GCMs)
which have been used in the IPCC 4AR (2007). This large dataset of future climate projections was produced by leading modelling groups worldwide who performed a set of coordinated climate experiments in which GCMs have been run for a common set of experiments and 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, long dry spells and heat waves. LARS-WG has been well validated in diverse climates around the world.
- Semenov MA , Pilkington-Bennett S, Calanca P (2013) Validation of ELPIS 1980-2010 baseline scenarios using the European Climate Assessment observed dataset. Climate Research 51(1) 1-9 (pdf)
- Calanca P, Semenov MA (2013) Local-scale climate scenarios for impact studies and risk assessments: integration of early 21st century ENSEMBLES projections into the ELPIS database Theor.Appl.Climatol, 113:445-455
- Semenov MA, Stratonovitch P(2010) The use of multi-model ensembles from global climate models for impact assessments of climate change. Climate Research 41:1-14 (pdf)
- Semenov MA, Donatelli M, Stratonovitch P, Chatzidaki E, and Baruth B. (2010) ELPIS: a dataset of local-scale daily climate scenarios for Europe. Climate Research 44:3-15 (pdf)
- Semenov MA (2008) Simulation of weather extreme events by stochastic weather generator. Climate Research, 35:203-212 (doi)
- Semenov MA (2007) Development of high-resolution UKCIP02-based climate change scenarios in the UK. Agricultural and Forest Meteorology, 144:127-138 (doi)
- Semenov MA & Brooks RJ(1999) Spatial interpolation of the LARS-WG weather generator in Great Britain. Climate Research, 11:137-148 (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, Barrow EM (1997) Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change, 35: 397-414 (doi)
- Racsko P, Szeidl L & Semenov MA (1991) A serial approach to local stochastic weather models. Ecological Modelling, 57 :27-41 (doi)