High resolution global climate modelling; the UPSCALE project, a large simulation campaign

Abstract

Abstract. The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985–2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environmental Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the high performance computing center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE dataset. This dataset is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.

Projected changes in medicanes in the HadGEM3 N512 high-resolution global climate model

“…The simulations were performed as part of the UPSCALE project (UK on PRACEweather resolving Simulations of Climate for globAL Environmental risk), a collaborative project between the National Centre for Atmospheric Science-Climate (NCAS) at the University of Reading, and the UK Met Office Hadley Centre (Mizielinski et al 2014). The N512 HadGEM3-GA3 model has a horizontal grid resolution of approximately 25 km (Fig.…”

Tropical Cyclones in the UPSCALE Ensemble of High-Resolution Global Climate Models*

“…To address such issues, a long-standing collaboration exists between the Met Office and the University of Reading to develop ''weather resolving'' climate models, which are able to capture typical weather features such as fronts and atmospheric rivers (as found in a weather forecast) while also being integrated over multidecadal time scales (Shaffrey et al 2009;Strachan et al 2013;Demory et al 2014;Mizielinski et al 2014). Many other groups are also progressing quickly in this direction, often using higher-resolution components of existing weather/seasonal forecasting or climate models (e.g., Zhao et al 2009;Murakami and Sugi 2010;Wehner et al 2010;Manganello et al 2012;Rathmann et al 2013;Bacmeister et al 2013), as significant progress in model scalability, supercomputing, data storage, and processing capacity become available.…”

The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale

“…1: total global precipitation is remarkably resolution invariant, which points to a very robust constraint provided by global longwave cooling in all model simulations, producing precipitation estimates within the range of significant and persistent observational uncertainty [see estimates by GPCP vs Wild et al (2015) vs Stephens et al (2012)]. Further, increasing the resolution in the Hadley Centre Global Environment Model, version 3 (HadGEM3), atmospheric general circulation model (GCM) (GA3; Mizielinski et al 2014) from about 100 to 25 km changes the model estimate of precipitation partitioning. Land versus sea distribution of precipitation agrees with the findings in Demory et al (2014); additionally, for the land portion, global (rugged) mountain precipitation increases by about 15%, and available observations, which are sparse over complex terrain, are hardly able to assess these model estimates.…”