Craig MacLachlan

Skillful long‐range prediction of European and North American winters

This work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the UK Public Weather Service research program, and the European Union Framework 7 SPECS project. Leon Hermanson was funded as part of his Research Fellowship by Willis as part of Willis Research Network (WRN).

The GloSea4 Ensemble Prediction System for Seasonal Forecasting

AbstractSeasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Nino–Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Nino-3.4 SST forecasts starting in November. Global ENSO teleconnections an...

The Sub-seasonal to Seasonal Prediction (S2S) Project Database

AbstractDemands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days).The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been co...

Predictability of the quasi‐biennial oscillation and its northern winter teleconnection on seasonal to decadal timescales

The predictability of the quasi-biennial oscillation (QBO) is examined in initialized climate forecasts extending out to lead times of years. We use initialized retrospective predictions made with coupled ocean-atmosphere climate models that have an internally generated QBO. We demonstrate predictability of the QBO extending more than 3 years into the future, well beyond timescales normally associated with internal atmospheric processes. Correlation scores with observational analyses exceed 0.7 at a lead time of 12 months. We also examine the variation of predictability with season and QBO phase and find that skill is lowest in winter. An assessment of perfect predictability suggests that higher skill may be achievable through improved initialization and climate modeling of the QBO, although this may depend on the realism of gravity wave source parameterizations in the models. Finally, we show that skilful prediction of the QBO itself does not guarantee predictability of the extratropical winter teleconnection that is important for surface winter climate prediction.

The Influence of Surface Forcings on Prediction of the North Atlantic Oscillation Regime of Winter 2010/11

AbstractDecember 2010 was unusual both in the strength of the negative North Atlantic Oscillation (NAO) intense atmospheric blocking and the associated record-breaking low temperatures over much of northern Europe. The negative North Atlantic Oscillation for November–January was predicted in October by 8 out of 11 World Meteorological Organization Global Producing Centres (WMO GPCs) of long-range forecasts. This paper examines whether the unusual strength of the NAO and temperature anomaly signals in early winter 2010 are attributable to slowly varying boundary conditions [El Nino–Southern Oscillation state, North Atlantic sea surface temperature (SST) tripole, Arctic sea ice extent, autumn Eurasian snow cover], and whether these were modeled in the Met Office Global Seasonal Forecasting System version 4 (GloSea4). Results from the real-time forecasts showed that a very robust signal was evident in both the surface pressure fields and temperature fields by the beginning of November. The historical reforec...

Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems

This study assesses the skill of boreal winter Arctic Oscillation (AO) predictions with state-of-the-art dynamical ensemble prediction systems (EPSs): GloSea4, CFSv2, GEOS-5, CanCM3, CanCM4, and CM2.1. Long-term reforecasts with the EPSs are used to evaluate how well they represent the AO and to assess the skill of both deterministic and probabilistic forecasts of the AO. The reforecasts reproduce the observed changes in the large-scale patterns of the Northern Hemispheric surface temperature, upper level wind, and precipitation associated with the different phases of the AO. The results demonstrate that most EPSs improve upon persistence skill scores for lead times up to 2 months in boreal winter, suggesting some potential for skillful prediction of the AO and its associated climate anomalies at seasonal time scales. It is also found that the skill of AO forecasts during the recent period (1997–2010) is higher than that of the earlier period (1983–1996).

The Representation of Atmospheric Blocking and the Associated Low-Frequency Variability in Two Seasonal Prediction Systems

AbstractPrimarily as a response to boundary forcings, certain components of the atmospheric intraseasonal variability are potentially predictable. Particularly referring to the extratropics, the current generation of seasonal forecasting systems is making advancements in predicting these components by realistically initializing many components of the climate system, using higher resolution and utilizing large ensemble sizes.The operational seasonal prediction system of the Met Office (UKMO) and the corresponding system of the Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) are analyzed in terms of their representation of different aspects of extratropical low-frequency variability. The UKMO system achieves unprecedented high scores in predicting the winter mean phase of the North Atlantic Oscillation (NAO; correlation 0.62) and the Pacific–North American pattern (PNA; correlation 0.82). The CMCC system, despite its smaller ensemble size and coarser resolution, also exhibits significant skill (0....

Skillful Seasonal Prediction of the Southern Annular Mode and Antarctic Ozone

AbstractUsing a set of seasonal hindcast simulations produced by the Met Office Global Seasonal Forecast System, version 5 (GloSea5), significant predictability of the southern annular mode (SAM) is demonstrated during the austral spring. The correlation of the September–November mean SAM with observed values is 0.64, which is statistically significant at the 95% confidence level [confidence interval: (0.18, 0.92)], and is similar to that found recently for the North Atlantic Oscillation in the same system. Significant skill is also found in the prediction of the strength of the Antarctic stratospheric polar vortex at 1 month average lead times. Because of the observed strong correlation between interannual variability in the strength of the Antarctic stratospheric circulation and ozone concentrations, it is possible to make skillful predictions of Antarctic column ozone amounts. By studying the variation of forecast skill with time and height, it is shown that skillful predictions of the SAM are signific...

Predictions of Climate Several Years Ahead Using an Improved Decadal Prediction System

AbstractDecadal climate predictions are now established as a source of information on future climate alongside longer-term climate projections. This information has the potential to provide key evidence for decisions on climate change adaptation, especially at regional scales. Its importance implies that following the creation of an initial generation of decadal prediction systems, a process of continual development is needed to produce successive versions with better predictive skill. Here, a new version of the Met Office Hadley Centre Decadal Prediction System (DePreSys 2) is introduced, which builds upon the success of the original DePreSys. DePreSys 2 benefits from inclusion of a newer and more realistic climate model, the Hadley Centre Global Environmental Model version 3 (HadGEM3), but shares a very similar approach to initialization with its predecessor. By performing a large suite of reforecasts, it is shown that DePreSys 2 offers improved skill in predicting climate several years ahead. Differenc...

Skillful seasonal prediction of Yangtze river valley summer rainfall

China suffers from frequent summer floods and droughts, but seasonal forecast skill of corresponding summer rainfall remains a key challenge. In this study, we demonstrate useful levels of prediction skill over the Yangtze river valley for summer rainfall and river flows using a new high resolution forecast system. Further analysis of the sources of predictability suggests that the predictability of Yangtze river valley summer rainfall corresponds to skillful prediction of rainfall in the deep tropics and around the Maritime Continent. The associated dynamical signals favor increased poleward water vapor transport from South China and hence Yangtze river valley summer rainfall and river flow. The predictability and useful level of skill demonstrated by this study imply huge potential for flooding and drought related disaster mitigation and economic benefits for the region based on early warning of extreme climate events.