Abstract

Abstract. The improved and updated Coupled Arctic Prediction System (CAPS) is evaluated using a set of Pan-Arctic prediction experiments for the year 2018. CAPS is built on the Weather Research and Forecasting model (WRF), the Regional Ocean Modeling System (ROMS), the Community Ice CodE (CICE), and a data assimilation based on the local error subspace transform Kalman filter. We analyze physical processes linking improved and changed physical parameterizations in WRF, ROMS, and CICE to changes in the simulated Arctic sea ice state. Our results show that the improved convection and boundary layer schemes in WRF result in an improved simulation of downward radiative fluxes and near-surface air temperature, which influences the predicted ice thickness. The changed tracer advection and vertical mixing schemes in ROMS reduce the bias in sea surface temperature and change ocean temperature and salinity structure in the surface layer, leading to improved evolution of the predicted ice extent (particularly correcting the late ice recovery issue in the previous CAPS). The improved sea ice thermodynamics in CICE have noticeable influences on the predicted ice thickness. The updated CAPS can better predict the evolution of Arctic sea ice during the melting season compared with its predecessor, though the prediction still has some biases at the regional scale. We further show that the updated CAPS can remain skillful beyond the melting season, which may have a potential value for stakeholders to make decisions for socioeconomic activities in the Arctic.

Highlights

  • Over the past few decades, the extent of Arctic sea ice has decreased rapidly and entered a thinner and younger regime associated with global climate change (e.g., Kwok, 2018; Serreze and Meier, 2019)

  • We focus on the Rapid Refresh (RAP) physics in the Weather Research and Forecasting Model (WRF) model, the oceanic tracer advection scheme in the Regional Ocean Modeling System (ROMS) model, and sea ice thermodynamics in the Community Ice CodE (CICE) model, and investigate physical processes linking them to Arctic sea ice simulation and prediction

  • Initial and boundary conditions for the WRF and ROMS models are generated from the Climate Forecast System version 2 (CFSv2, Saha et al, 2014) operational forecast archived at National Centers for Environmental Prediction (NCEP)

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Summary

Introduction

Over the past few decades, the extent of Arctic sea ice has decreased rapidly and entered a thinner and younger regime associated with global climate change (e.g., Kwok, 2018; Serreze and Meier, 2019). The second question we want to answer in this paper is to what extent different advection schemes can change the simulation of upper ocean thermal structure and Arctic sea ice prediction. Following Y20, here we test the 2018 prediction experiment with six localization radii for the data assimilation, which shows very similar temporal evolution of the total Arctic sea ice extent for the July experiment relative to that of Y20, it (red solid line) predicts slightly less ice extent than that of Y20 (blue line) (Supplement Fig. S2) In this study, this configuration is designated as the reference for the following assessment of the updated CAPS (hereafter Y20_MOD). For the comparison of spatial distribution, SIC, ERA5, and OISST are interpolated to the model grid

Experiment designs and methodology
Impacts of the RAP physics in the WRF model
Impacts of the tracer advection in ROMS model
Impacts of sea ice thermodynamics in the CICE model
Prediction skill of CAPS at longer timescales
Conclusions and discussions
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