Downloads
Hopcroft and Valdes, (2019),
On the role of dust-climate feedbacks during the mid-Holocene,
Geophysical Research Letters, 46, doi:10.1029/2018GL080483..
HadGEM2-ES simulations
Hopcroft et al., (2018),
Bayesian analysis of the glacial-interglacial methane increase constrained by stable isotopes and Earth System modelling
Geophysical Research Letters, 46, HadGEM2-ES simulations
Hopcroft et al., (2017),
Multi vegetation model evaluation of the Green Sahara climate regime
Geophysical Research Letters, 44, in press, Vegetation model outputs from JULES, LPJ and SDGVM.
Kageyama et al., (2017). The PMIP4 Last Glacial Maximum experiments,
Geoscientific Model Developement. Pre-industrial and LGM dust emissions, loading, optical depth and concentration, and SW and LW radiation fluxes:
PMIP4_website
Hopcroft & Valdes (2015)
, How well do simulated last glacial maximum tropical temperatures constrain equilibrium climate sensitivity?
Geophysical Research Letters, 42(13), 5533-5539, Climate sensitivity values and PMIP coupled model tropical surface temperature anomalies
Hopcroft et al., (2015).
Last glacial maximum radiative forcing from mineral dust aerosols in an Earth System model,
Journal of Geophysical Research, 120(16), 8186-8205, HadGEM2-A climate model data is available for download here. Hopcroft & Valdes (2014). Last Glacial Maximum constraints on the Earth System Model HadGEM2-ES, Climate Dynamics, doi:10.1007/s00382-014-2421-0. HadGEM2-A and HadGEM2-ES climate model data is available for download here. Melton et al., (2013). Present state of global wetland extent and wetland methane modelling: conclusions from a model intercomparison project (WETCHIMP), Biogeosciences, 10, 753-788, doi:10.5194/bg-10-753-2013.
SDGVM transient CH4 emisssions for the years 1981-2009 (experiment 2) are available here Hopcroft et al., (2011). Simulating idealized Dansgaard-Oeschger events and their potential impacts on the global methane cycle, Quaternary Science Reviews, 30, 23-24, 3258-3268, doi:10.1016/j.quascirev.2011.08.01. FAMOUS transient climate model output is available for download here. Hopcroft et al., (2007). Inference of past climate from borehole temperature data using Bayesian Reversible Jump Markov chain Monte Carlo, Geophysical Journal International, 171(3), 1430-1439, doi:10.1111/j.1365-246X.2007.03596.x. C++ software for implementing the Bayesian borehole inversion method which uses a Reversible Jump Markov chain Monte Carlo algorithm is freely available here.
and outputs from several other models including SDGVM are available from the WETCHIMP page.