A brief review of random forests for water scientists and practitioners and their recent history in water resources
Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …
to gain prominence in water resources applications. However, existing applications are …
A perturbed parameter ensemble of HadGEM3-GC3. 05 coupled model projections: part 2: global performance and future changes
K Yamazaki, DMH Sexton, JW Rostron… - Climate Dynamics, 2021 - Springer
This paper provides a quantitative assessment of large-scale features in a perturbed
parameter ensemble (PPE) of Met Office Unified Model HadGEM-GC3. 05 in coupled global …
parameter ensemble (PPE) of Met Office Unified Model HadGEM-GC3. 05 in coupled global …
Identifying and removing structural biases in climate models with history matching
We describe the method of history matching, a method currently used to help quantify
parametric uncertainty in climate models, and argue for its use in identifying and removing …
parametric uncertainty in climate models, and argue for its use in identifying and removing …
Does model calibration reduce uncertainty in climate projections?
Uncertainty in climate projections is large as shown by the likely uncertainty ranges in
equilibrium climate sensitivity (ECS) of 2.5–4 K and in the transient climate response (TCR) …
equilibrium climate sensitivity (ECS) of 2.5–4 K and in the transient climate response (TCR) …
Exploring the Venus global super-rotation using a comprehensive general circulation model
The atmospheric circulation in Venus is well known to exhibit strong super-rotation.
However, the atmospheric mechanisms responsible for the formation of this super-rotation …
However, the atmospheric mechanisms responsible for the formation of this super-rotation …
Model structure in observational constraints on transient climate response
The transient climate response (TCR) is a highly policy-relevant quantity in climate science.
We show that recent revisions to TCR in the IPCC 5th Assessment Report have more impact …
We show that recent revisions to TCR in the IPCC 5th Assessment Report have more impact …
Evolving Bayesian emulators for structured chaotic time series, with application to large climate models
We develop Bayesian dynamic linear model Gaussian processes for emulation of time
series output for computer models that may exhibit chaotic behavior, but where this behavior …
series output for computer models that may exhibit chaotic behavior, but where this behavior …
Propagation of error and the reliability of global air temperature projections
P Frank - Frontiers in Earth Science, 2019 - frontiersin.org
The reliability of general circulation climate model (GCM) global air temperature projections
is evaluated for the first time, by way of propagation of model calibration error. An extensive …
is evaluated for the first time, by way of propagation of model calibration error. An extensive …
Finding plausible and diverse variants of a climate model. Part II: development and validation of methodology
The usefulness of a set of climate change projections largely depends on how well it spans
a range of outcomes consistent with known uncertainties. Here, we present exploratory work …
a range of outcomes consistent with known uncertainties. Here, we present exploratory work …
[HTML][HTML] Lower-tropospheric mixing as a constraint on cloud feedback in a multiparameter multiphysics ensemble
Lower-Tropospheric Mixing as a Constraint on Cloud Feedback in a Multiparameter
Multiphysics Ensemble in: Journal of Climate Volume 29 Issue 17 (2016) Jump to Content …
Multiphysics Ensemble in: Journal of Climate Volume 29 Issue 17 (2016) Jump to Content …