Working Groups

SOLARIS-HEPPA Working Groups

The following working groups (WGs) were defined at SOLARIS-HEPPA meetings in 2016 (Matthes et al., 2017; SPARC Newsletter, 48, January 2017).

The WG leaders will coordinate the analyses within their WG. If you are interested in participating in one of the WGs, please get in touch with the respective WG leaders or contact Bernd Funke (bernd <at sign> or Katja Matthes (see link for contact details)

WG1 (Markus Kunze and Gabriel Chiodo): Stratospheric Signal

This WG will analyse the solar irradiance and particle effects on the stratosphere in both historical (1960-2010) and future (2010-2100) simulations, i.e. REF-C1 and REF-C2 CCMI simulations.

WG2 (Klairie Tourpali and Stergios Misios): Surface Signal

This WG will analyse the solar irradiance and particle effects on surface climate taking atmosphere ocean coupling processes into account in both historical (1960-2010) and future (2010-2100) simulations, i.e. CCMI REF-C1 and REF-C2.

Solar cycle signals in the troposphere and surface may result from the influence of the dynamical adjustment of the stratospheric circulation to solar forcing (irradiance and particles). As CCMI models include interactive ocean coupling in the future simulations, the aim is to analyze the solar forcing and related atmosphere-ocean coupling processes in the long (100 yrs) REF-C2 runs, with focus on the North Atlantic region. Solar signals in the troposphere and surface in the coupled runs will be compared to the respective signals in the historical REF-C1, in which SST observations are specified. The analysis methodology will be in accordance to the recommendations of the “Methodological Analysis Group”.

WG3 (Eugene Rozanov, Amanda Maycock, and Alessandro Damiani): Comparison with (satellite) observations

This WG will compare the observed solar signal resulting from solar irradiance and particle forcing in the specified dynamics experiments covering the satellite era from 1980-2010 (CCMI REF-C1SD).

Past studies have identified differences amongst the Solar influence on the Ozone Layer (SOL) between individual chemistry-climate models (CCMs) and between CCMs and various satellite ozone datasets, but it is not clear if these are due to CCM biases and/or uncertainties in the SOL extracted from available observations. The WCRP/SPARC CCMI-1 Activity provides a novel resource to investigate the SOL in the form of historical simulations with meteorology nudged towards reanalysis fields (i.e. REF-C1SD experiments). Within this framework, WG3 aims to:

  • Compare the zonal wind and temperature responses to spectral solar irradiance (SSI) and particle forcing in the CCMI-1 REF-C1SD simulations and evaluate whether they match the respective reanalysis products.
  • Analyze the SOL associated with solar variability diagnosed from the REF-C1SD simulations and compare to the SOL obtained from satellites and REF-C1.
  • Assess whether the use of particular reanalysis products for nudging have an impact on the representation of the SOL.
  • Discern the SOL associated with Energetic Particle Precipitation (EPP) on other chemical constituents at high/middle latitudes.

Analysis methods for extraction of the SOL from model simulationas and observations will be based on recommendations of WG4.

WG4 (Rémi Thiéblemont and William Ball): Methodological Analysis

This WG will do a thorough comparison of existing statistical approaches to analyse solar signals in model and observational data. In a first step a multiple linear regression (MLR) code will be made available on the SOLARIS-HEPPA website. In a second step, the limitations of the MLR will be discussed and other (non-linear) statistical methods will be tested for their applicability to solar signals in the atmosphere.

Solar signals in observations and/or model studies are, and have been for a long time, usually attributed using various versions of two statistical methods: Multiple Linear Regressions (MLR) or Superposed Epoch Analysis (or “compositing”). These methods, however, are not always appropriately justified, and their inherent limitations are usually barely discussed, if at all. Although these methods are appealing due to their simplicity and high physical explanatory power, they can present substantial caveats which may lead to erroneous conclusions, such as signal misattribution.

The working group "Methodological Analysis" aims at assessing different analytical methods used to retrieve solar signals in observations, reanalysis data, as well as single- or multi- model results. The goal is essentially to help climate scientists – with interest in (but not restricted to) Sun-climate connections – to apply and/or design statistical methods as robust and suitable as possible to solve a given problem.

WG5 (Miriam Sinnhuber and Hilde Nesse Tyssøy): Medium Energy Electrons (MEE) Model-Measurement intercomparison

This WG will compare observed chemical responses to MEEs in the mesosphere with available model simulations that account for MEE ionization (e.g., by including the newly available MEE parameterization for CMIP6 (Matthes et al., 2016)).

Energetic particle precipitation is for the first time included as an aspect of solar forcing for the upcoming CMIP-6 scenarios. Chemistry-climate model studies suggest that the impact on stratospheric dynamics might be comparable to the impact of solar spectral variation. While the proton energy input associated with rare solar proton events and its impact on NOY and HOX has fairly well quantified, the energy input of the more frequent energetic electron precipitations events is not yet well established. In particular, the relative contributions of auroral and middle energy electrons to the so-called indirect particle effect are yet not well known.

In this WG, we will compare available forcing estimates (electron ionization rates) impacting the mesosphere and thermosphere. Further, we will compare existing model runs with observations of chemical species known to react to particle forcing (e.g., NO, OH, and ozone) from a number of different satellite observations. These comparisons will complement WG3 by including additional, dedicated model experiments, forcing data, and the analysis of specific events.