This article describes the UK Met Office Global Seasonal forecast system version 5 (GloSea5). GloSea5 upgrades include an increase in horizontal resolution in the atmosphere (N216-0.7 • ) and the ocean (0.25 • ), and implementation of a 3D-Var assimilation system for ocean and sea-ice conditions. GloSea5 shows improved year-to-year predictions of the major modes of variability. In the Tropics, predictions of the El Niño-Southern Oscillation are improved with reduced errors in the West Pacific. In the Extratropics, GloSea5 shows unprecedented levels of forecast skill and reliability for both the North Atlantic Oscillation and the Arctic Oscillation. We also find useful levels of skill for the western North Pacific Subtropical High which largely determines summer precipitation over East Asia.
This paper reviews recent literature concerning a wide range of processes through which climate change could potentially impact global-scale agricultural productivity, and presents projections of changes in relevant meteorological, hydrological and plant physiological quantities from a climate model ensemble to illustrate key areas of uncertainty. Few global-scale assessments have been carried out, and these are limited in their ability to capture the uncertainty in climate projections, and omit potentially important aspects such as extreme events and changes in pests and diseases. There is a lack of clarity on how climate change impacts on drought are best quantified from an agricultural perspective, with different metrics giving very different impressions of future risk. The dependence of some regional agriculture on remote rainfall, snowmelt and glaciers adds to the complexity. Indirect impacts via sea-level rise, storms and diseases have not been quantified. Perhaps most seriously, there is high uncertainty in the extent to which the direct effects of CO2 rise on plant physiology will interact with climate change in affecting productivity. At present, the aggregate impacts of climate change on global-scale agricultural productivity cannot be reliably quantified.
ABSTRACT. We have determined the ice mass evolution of the Antarctic and Greenland ice sheets (AIS and GIS) and
A multimodel, multiresolution set of simulations over the period 1950–2014 using a common forcing protocol from CMIP6 HighResMIP have been completed by six modeling groups. Analysis of tropical cyclone performance using two different tracking algorithms suggests that enhanced resolution toward 25 km typically leads to more frequent and stronger tropical cyclones, together with improvements in spatial distribution and storm structure. Both of these factors reduce typical GCM biases seen at lower resolution. Using single ensemble members of each model, there is little evidence of systematic improvement in interannual variability in either storm frequency or accumulated cyclone energy as compared with observations when resolution is increased. Changes in the relationships between large-scale drivers of climate variability and tropical cyclone variability in the Atlantic Ocean are also not robust to model resolution. However, using a larger ensemble of simulations (of up to 14 members) with one model at different resolutions does show evidence of increased skill at higher resolution. The ensemble mean correlation of Atlantic interannual tropical cyclone variability increases from ~0.5 to ~0.65 when resolution increases from 250 to 100 km. In the northwestern Pacific Ocean the skill keeps increasing with 50-km resolution to 0.7. These calculations also suggest that more than six members are required to adequately distinguish the impact of resolution within the forced signal from the weather noise.
Abstract. The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems. Overall GC2 is shown to be an improvement on the configurations used currently, particularly in terms of modes of variability (e.g. mid-latitude and tropical cyclone intensities, the Madden–Julian Oscillation and El Niño Southern Oscillation). A number of outstanding errors are identified with the most significant being a considerable warm bias over the Southern Ocean and a dry precipitation bias in the Indian and West African summer monsoons. Research to address these is ongoing.
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