JULES

JULES (Joint UK Land Environment Simulator) is a land-surface parameterisation model scheme describing soil-vegetation-atmosphere interactions.[1] JULES is a community lead[citation needed] project which evolved from MOSES, the United Kingdom Meteorological Office (Met Office) Surface Exchange Scheme.[2] It can be used as a stand-alone model or as the land surface part of the Met Office Unified Model.[2] JULES has been used to help decide what tactics would be effective to help meet the goals of the Paris Agreement.[3] As well as use by the Met Office climate modelling group[4] a number of studies have cited JULES and used it as a tool to assess the effects of climate change, and to simulate environmental factors from groundwater to carbon in the atmosphere.[5][6][7][8][9] JULES has been described as the most accurate global carbon budget model of net ecosystem productivity, because it has more years of data than other models.[10]

## References

1. ↑ "Joint UK Land Environment Simulator (JULES)" (in en). https://jules.jchmr.org/.
2. ↑ 2.0 2.1 "Joint UK Land Environment Simulator (JULES)". https://www.metoffice.gov.uk/research/approach/collaboration/jwcrp/jules.
3. ↑ Phelan, Matthew (7 August 2018). "Meeting Paris Agreement Global Warming Goals May Require Lots More Forests" (in en). https://www.inverse.com/article/47846-beccs-v-forests-a-computer-simulation-like-that-one-rocky-movie.
4. ↑ "Climate impacts" (in en). https://www.metoffice.gov.uk/research/climate/earth-system-science/climate-impacts.
5. ↑ Osborne, T.; Gornall, J.; Hooker, J.; Williams, K.; Wiltshire, A.; Betts, R.; Wheeler, T. (October 2014). "JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator". Geoscientific Model Development Discussions 7 (5): 6773–6809. doi:10.5194/gmdd-7-6773-2014. Bibcode: 2014GMDD....7.6773O. http://centaur.reading.ac.uk/39973/1/gmd-8-1139-2015.pdf.
6. ↑ Best, M. J.; Pryor, M.; Clark, D. B.; Rooney, G. G.; Essery, R. L. H.; Ménard, C. B.; Edwards, J. M.; Hendry, M. A. et al. (2011). "The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes" (in en). Geoscientific Model Development 4 (3): 677–699. doi:10.5194/gmd-4-677-2011. ISSN 1991-9603. Bibcode: 2011GMD.....4..677B. http://centaur.reading.ac.uk/34587/.
7. ↑ Yuan, Wenping; Zheng, Yi; Piao, Shilong; Ciais, Philippe; Lombardozzi, Danica; Wang, Yingping; Ryu, Youngryel; Chen, Guixing et al. (2019-08-01). "Increased atmospheric vapor pressure deficit reduces global vegetation growth" (in en). Science Advances 5 (8): eaax1396. doi:10.1126/sciadv.aax1396. ISSN 2375-2548. PMID 31453338. Bibcode: 2019SciA....5.1396Y.
8. ↑ Yin, Yuanyuan; Tang, Qiuhong; Wang, Lixin; Liu, Xingcai (2016-02-12). "Risk and contributing factors of ecosystem shifts over naturally vegetated land under climate change in China" (in en). Scientific Reports 6 (1): 20905. doi:10.1038/srep20905. ISSN 2045-2322. PMID 26867481. Bibcode: 2016NatSR...620905Y.
9. ↑ Batelis, Stamatis-Christos; Rahman, Mostaquimur; Kollet, Stefan; Woods, Ross; Rosolem, Rafael (2020). "Towards the representation of groundwater in the Joint UK Land Environment Simulator" (in en). Hydrological Processes 34 (13): 2843–2863. doi:10.1002/hyp.13767. ISSN 1099-1085. Bibcode: 2020HyPr...34.2843B.
10. ↑ Davies-Barnard, Taraka; Meyerholt, Johannes; Zaehle, Sönke; Friedlingstein, Pierre; Brovkin, Victor; Fan, Yuanchao; Fisher, Rosie A.; Jones, Chris D. et al. (2020). "Nitrogen Cycling in CMIP6 Land Surface Models: Progress and Limitations". Biogeosciences (Preprint) 17 (20): 5129. doi:10.5194/bg-17-5129-2020. Bibcode: 2020BGeo...17.5129D. https://bg.copernicus.org/preprints/bg-2019-513/bg-2019-513-RC2-supplement.pdf.

## External links

* Official website
* Joint UK Land Environment Simulator (JULES) Documentation on Github
* The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations

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Atmospheric, oceanographic, cryospheric, and climate models

Model types

* Atmospheric model
* Oceanographic model
* Cryospheric model
* Climate model
* Numerical weather prediction
* Tropical cyclone forecast model
* Atmospheric dispersion modeling
* Chemical transport model
* Upper-atmospheric models
* Ensemble forecasting
* Model output statistics
* Meteorological reanalysis
* Parametrization

Specific models

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Regional and mesoscale atmospheric|

* NAM
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Regional and mesoscale oceanographic|

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Atmospheric dispersion|

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Chemical transport|

* CLaMS
* MOZART
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Land surface parametrization|

* JULES
* CLASS
* ISBA

Cryospheric models|

* CICE

Discontinued|

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