Office Global Seasonal Forecast System Research Articles

Seasonal and interannual variation of equatorial waves in ERA5 and GloSea5

AbstractThis study presents an analysis of the equatorial waves in the ERA5 reanalysis and forecasts of the Met Office Global Seasonal Forecast System version 5 (GloSea5), by projecting dynamical fields onto theoretical equatorial wave modes. The seasonal and interannual variation of equatorial wave activity in GloSea5 is evaluated against ERA5 waves. We find that in ERA5 the seasonal and spatial variations of eastward‐moving Kelvin wave activity are mainly determined by the ambient zonal flow, with wave activity being stronger in easterlies than westerlies. For the westward‐moving mixed Rossby–gravity waves and equatorial Rossby waves, the seasonal and spatial variations of the upper‐tropospheric wave activity are determined by both the ambient flow and extratropical forcing with stronger wave activity generally in the westerlies, whilst the lower‐tropospheric wave activity is related to the ambient flow and tropical convection. In GloSea5, the Kelvin wave activity is not well simulated in the upper troposphere, and in general the wave activity and wave‐related convective signal are too weak. In contrast, GloSea5 performs better for the westward‐moving equatorial waves, including their Doppler‐shifted eastward‐moving components, despite a significant overestimation in the Atlantic and African region. The phase of ENSO has a substantial impact on equatorial waves in both ERA5 and GloSea5. The mechanism of the impact is through changes in the ENSO‐related ambient flow, upper‐tropospheric extratropical forcing, and tropical convection. GloSea5 can capture the low‐level Kelvin wave–ENSO relationship reasonably well, with stronger wave activity over the eastern Pacific in El Niño, although the ENSO‐driven variation is too weak. The wave–ENSO relationship for westward‐moving waves is well represented in GloSea5, especially in the upper‐level eastern‐Pacific westerly duct region in the extended boreal winter and the low‐level Indo‐Pacific in all seasons. We conclude that in GloSea5 the representation of the wave–ENSO teleconnection is the key driver for the performance of interannual variability in the wave activity.

Large-scale circulation patterns and their influence on European winter windstorm predictions

Severe winter windstorms are amongst the most damaging weather events for Europe and show significant interannual variability. While surface variables (temperature, precipitation) have been successfully predicted for some time now, predictability of severe windstorms caused by extra-tropical cyclones remains less well explored. This study investigates windstorm prediction skill of the UK Met Office Global Seasonal Forecast System Version 5 (GloSea5) for the Northeast-Atlantic and European region. Based on an objective Lagrangian tracking of severe, damage relevant windstorms, three storm parameters are analysed: windstorm frequency and two intensity measures. Firstly, skill based on direct tracking of simulated windstorms is diagnosed. Significant positive skill for storm frequency and intensity is found over an extended area at the downstream end of the storm track, i.e., from the UK to southern Scandinavia. The skill for frequency agrees well with previous studies for older model versions, while the results of event-based intensity are novel. Receiver Operating Characteristic Curves for three smaller regions reveal significant skill for high and low storm activity seasons. Second, skill of windstorm characteristics based on their multi-linear regressions to three dominant large-scale circulation patterns [i.e., the North Atlantic Oscillation (NAO), the Scandinavian Pattern (SCA), and the East-Atlantic Pattern (EA)] are analysed. Although these large-scale patterns explain up to 80% of the interannual variance of windstorm frequency and up to 60% for intensity, the forecast skill for the respectively linear-regressed windstorms do not show systematically higher skill than the direct tracking approach. The signal-to-noise ratio of windstorm characteristics (frequency, intensity) is also quantified, confirming that the signal-to-noise paradox extends to windstorm predictions.

Predictability of European winter 2020/2021: Influence of a mid‐winter sudden stratospheric warming

AbstractBoreal winter (December–February) 2020/2021 in the North Atlantic/European region was characterised by a negative North Atlantic Oscillation (NAO) index. Although this was captured within the ensemble spread of predictions from the Met Office Global Seasonal forecast system (GloSea5), with 17% of ensemble members predicting an NAO less than zero, the forecast ensemble mean was shifted towards a positive NAO phase. The observed monthly NAO anomalies were particularly negative in January and February, following an early January sudden stratospheric warming (SSW), and a prolonged period of Phase 6 or 7 of the Madden Julian Oscillation (MJO) in late January/early February. In contrast, predictions showed the expected teleconnection from the observed La Niña, with a positive NAO signal resulting from a weakening of the Aleutian Low leading to a reduction in tropospheric wave activity, an increase in polar vortex strength and a reduced chance of an SSW. Forecasts initialised later in the winter season successfully predicted the negative NAO in January and February once the SSW and MJO were within the medium range timescale. GloSea5 likely over‐predicted the strength of the La Niña which we estimate caused a small negative bias in the SSW probability. However, this error is smaller than the uncertainty in SSW probability from the finite forecast ensemble size, emphasising the need for large forecast ensembles. This case study also demonstrates the advantage of continuously updated lagged ensemble forecasts over a ‘burst’ ensemble started on a fixed date, since a change in forecast signal due to events within the season can be detected early and promptly communicated to users.

Western North Pacific Tropical Cyclones in the Met Office Global Seasonal Forecast System: Performance and ENSO Teleconnections

AbstractThe performance of the Met Office Global Seasonal Forecast System (GloSea5-GC2) for tropical cyclone (TC) frequency for the western North Pacific (WNP) in July–October is evaluated, using 23 years of ensemble forecasts (1993–2015). Compared to observations, GloSea5 overpredicts the climatological TC frequency in the eastern WNP and underpredicts it in the western and northern WNP. These biases are associated with an El Niño–type bias in TC-related environmental conditions (e.g., low-level convergence and steering flow), which encourages too many TCs to form throughout the tropical Pacific and slows TC propagation speed. For interannual TC frequency variability, GloSea5 overestimates the observed negative TC–ENSO teleconnection in the western and northern WNP, associated with an eastward shift in the ENSO teleconnection to environmental conditions. Consequently, GloSea5 fails to predict interannual TC variability in the northeast WNP (south of Japan); performance is higher in the southwest WNP (e.g., the South China Sea) where the sign of the TC–ENSO teleconnection is correct. This study suggests the need to reduce biases in environmental conditions and associated ENSO teleconnections in GloSea5 to improve the TC prediction performance in the NWP.

Predictability of the Western North Pacific Subtropical High Associated with Different ENSO Phases in GloSea5

The western North Pacific subtropical high (WNPSH) dominates the summer climate over East Asia. The intensity, position, and shape of WNPSH influence the spatiotemporal distributions of precipitation, temperature, and tropical cyclone activities in this region. This paper intends to investigate the performance of the UK Met Office Global Seasonal forecast system version 5 (GloSea5) in simulation/prediction of the WNPSH based on a hindcast dataset. Analyses of the hindcast data show a systematic bias in the mean circulation over West Pacific, with negative geopotential height anomalies over the western North Pacific (WNP) and cyclonic anomalies in the 850-hPa winds and water vapor transport, indicating a weakening and eastward shift of the WNPSH. Despite the model’s bias in the climatology, it well captured the interannual variability of the monthly and seasonal-mean intensity of the WNPSH and the position of its ridge line in boreal summer from 1993 to 2015. The seasonal hindcasts indicate that there is significant prediction skill at up to three-month lead time for both the intensity and position of the WNPSH ridge line. The relationship between the WNPSH and different phases of the El Niño-Southern Oscillation (ENSO) in both the observational data and GloSea5 hindcasts was then investigated. The model captured the summer WNPSH anomalies well during most of the ENSO phases, except in the La Niña decaying and neutral summers. The intensity of the anticyclone in the WNP is weak in the decaying phase of El Niño in the GloSea5 hindcasts compared with the reanalysis data. GloSea5 is capable of representing the lagged teleconnection between El Niño events in the previous winter and the intensity of the WNPSH in the following summer. Regression analysis reveals weakened negative sea surface temperature anomalies (SSTAs) over the WNP in GloSea5, which reduced the gradient between the tropical western Pacific and the tropical Indian Ocean, resulting in a weaker easterly anomaly and stronger westerly anomaly, contributing to the weak anomalous anticyclone over the WNP and the weakened WNPSH relative to the reanalysis data.

Verification of the 2019 GloSea5 Seasonal Tropical Cyclone Landfall Forecast for East China

A prototype climate service was developed and trialled in early 2019 to provide seasonal forecast of the June-July-August (JJA) tropical cyclone (TC) landfall risk for the East China region ahead of the forthcoming typhoon season. Test forecasts were produced in both March and April 2019 and a final forecast was released to the China Meteorological Administration (CMA) on 1 May 2019. The trial service was produced by using the Met Office Global Seasonal forecast system (GloSea5), and a forecast of the western Pacific subtropical high (WPSH) index was used to infer the TC landfall risk based on a simple linear regression between historical model WPSH indices and observed TC landfalls in East China. The forecast method shows significant skill for forecasting the JJA TC landfall risk in East China with up to three-month lead time, with the greatest skill for predictions initialized in May. The 2019 forecast provided good guidance of the near-average TC activity observed in East China in JJA 2019. Success of the forecast adds confidence to an improved climate service ahead of the 2020 typhoon season.

Impact of Indo-Pacific warm pool Hadley circulation on the seasonal forecast performance for summer precipitation over the western North Pacific

The western North Pacific summer climate affects the densely populated East Asian countries, while seasonal forecasting over these regions remains challenging for dynamical models. This study evaluates the effect of the spring Indo-Pacific warm pool (IPWP) Hadley circulation on the forecast performance for summer western North Pacific (WNP) precipitation in the Met Office Global Seasonal Forecast System (GloSea5). GloSea5 skillfully predicts IPWP Hadley circulation, but has moderate forecast skill for summer WNP precipitation. Compared to observations, the significant relationship between the spring IPWP Hadley circulation and the summer WNP precipitation is overestimated in most hindcast members and in the ensemble mean. Furthermore, we confirmed that the forecast ensemble members with a stronger such regional circulation–precipitation relationship have better forecast performance for the summer WNP precipitation, suggesting the importance of such a relationship for the seasonal forecast of WNP precipitation. These results also imply the need to further investigate other important factors for the WNP precipitation, the effects of which may be suppressed by the overestimated regional circulation–precipitation relationship in GloSea5.

Skill of Seasonal Rainfall and Temperature Forecasts for East Africa

AbstractSkillful seasonal forecasts can provide useful information for decision-makers, particularly in regions heavily dependent on agriculture, such as East Africa. We analyze prediction skill for seasonal East African rainfall and temperature one to four months ahead from two seasonal forecasting systems: the U.S. National Centers for Environmental Prediction (NCEP) Coupled Forecast System Model, version 2 (CFSv2), and the Met Office (UKMO) Global Seasonal Forecast System, version 5 (GloSea5). We focus on skill for low or high temperature and rainfall, below the 25th or above the 75th percentile, respectively, as these events can have damaging effects in this region. We find skill one month ahead for both low and high rainfall from CFSv2 for December–February in Tanzania, and from GloSea5 for September–November in Kenya. Both models have higher skill for temperature than for rainfall across Ethiopia, Kenya, and Tanzania, with skill two months ahead in some cases. Performance for rainfall and temperature change in the two models during certain El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) phases, the impacts of which vary by country, season, and sometimes by model. While most changes in performance are within the range of uncertainty due to the relatively small sample size in each phase, they are significant in some cases. For example, La Niña lowers performance for Kenya September–November rainfall in CFSv2 but does not affect skill in GloSea5.

Seasonal Predictability of the Winter North Atlantic Oscillation From a Jet Stream Perspective

AbstractThe winter North Atlantic Oscillation (NAO) has varied on interannual and decadal timescales over the last century, associated with variations in the speed and latitude of the eddy‐driven jet stream. This paper uses hindcasts from two operational seasonal forecast systems (the European Centre for Medium‐range Weather Forecasts's seasonal forecast system, and the U.K. Met Office global seasonal forecast system) and a century‐long atmosphere‐only experiment (using the European Centre for Medium‐range Weather Forecasts's Integrated Forecasting System model) to relate seasonal prediction skill in the NAO to these aspects of jet variability. This shows that the NAO skill realized so far arises from interannual variations in the jet, largely associated with its latitude rather than speed. There likely remains further potential for predictability on longer, decadal timescales. In the small sample of models analyzed here, improved representation of the structure of jet variability does not translate to enhanced seasonal forecast skill.

Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector

AbstractThe skill and reliability of forecasts of winter and summer temperature, wind speed, and irradiance over China are assessed using the Met Office Global Seasonal Forecast System, version 5 (GloSea5). Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. It was found that, although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skillfully forecast around the coast of the South China Sea, related to skillful forecasts of the El Niño–Southern Oscillation. Such information could improve seasonal estimates of offshore wind-power generation. In a similar way, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar-power estimation. Skill in predicting summer temperatures, which derives from an upward trend, is shown over much of China. The region around Beijing, however, retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of the results presented here will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising.

Exploring the feasibility of empirical, dynamical and combined probabilistic rainy season onset forecasts for São Paulo, Brazil

ABSTRACTThis study investigates the feasibility and presents an assessment of probabilistic rainy season onset forecasts for São Paulo, Brazil, located in a region with a well‐defined wet season from mid‐austral spring (October) to austral autumn (March/April). The probabilistic forecasts were produced with (1) a simple empirical Cox‐regression model using July Niño‐3 index as predictor, (2) the dynamical coupled atmosphere‐land‐surface‐ocean‐sea‐ice model used in the UK Met Office Global Seasonal Forecast System (GloSea5) and (3) a procedure that combines the empirical and dynamical model onset probabilistic forecasts. The probabilistic forecast assessment was performed over the 1996–2009 retrospective forecast period for the event rainy season onset earlier (or later) than the historical (mean) onset date. The three investigated approaches resulted in similar discrimination ability of around 80%, which represents the probability of the probabilistic forecasts correctly distinguishing earlier from a later than mean onsets, suggesting good potential for rainy season onset forecasts for São Paulo. The robustness of this assessment for an extended period (longer than 1996–2009) and for a region (20°S, 25°S, 45°W, 55°W) that includes the city of São Paulo was checked, reinforcing the validity of the obtained results at both local and regional scales.

Boreal summer sub-seasonal variability of the South Asian monsoon in the Met Office GloSea5 initialized coupled model

Boreal summer sub-seasonal variability in the Asian monsoon, otherwise known as the monsoon intra-seasonal oscillation (MISO), is one of the dominant modes of intraseasonal variability in the tropics, with large impacts on total monsoon rainfall and India’s agricultural production. However, our understanding of the mechanisms involved in MISO is incomplete and its simulation in various numerical models is often flawed. In this study, we focus on the objective evaluation of the fidelity of MISO simulation in the Met Office Global Seasonal forecast system version 5 (GloSea5), an initialized coupled model. We analyze a series of nine-member hindcasts from GloSea5 over 1996–2009 during the peak monsoon period (July–August) over the South-Asian monsoon domain focusing on aspects of the time-mean background state and air–sea interaction processes pertinent to MISO. Dominant modes during this period are evident in power spectrum analysis, but propagation and evolution characteristics of the MISO are not realistic. We find that simulated air–sea interactions in the central Indian Ocean are not supportive of MISO initiation in that region, likely a result of the low surface wind variance there. As a consequence, the expected near-quadrature phase relationship between SST and convection is not represented properly over the central equatorial Indian Ocean, and northward propagation from the equator is poorly simulated. This may reinforce the equatorial rainfall mean state bias in GloSea5.

Seasonal predictive skill of intraseasonal synoptic type variability over the Cape south coast of South Africa by making use of the Met Office Global Seasonal Forecast System 5

ABSTRACTThe skill in predicting intraseasonal characteristics of synoptic type occurrences at the seasonal time scale over the all‐year rainfall region of South Africa (35°–33°S and 21°–27°E) is assessed by utilizing an ensemble of simulations performed using the GloSea5 coupled ocean–atmosphere model. Hindcasts of daily sea‐level pressure fields of 14 austral spring [September–October–November (SON)] and summer [December–January–February (DJF)] seasons, initialized in August and November, respectively, are analysed. The skill assessment is achieved through the use of self‐organizing maps. Deterministic and probabilistic assessment of synoptic type frequency forecasts indicate that intraseasonal circulation variability over the Cape south coast region is marginally predictable at seasonal time scales, more so during SON than DJF. In particular, the results obtained demonstrate that there is potential for the skillful seasonal prediction of the anomalous frequency of occurrence of high‐impact rainfall events associated with cut‐off lows within SON seasons.

A Bayesian Framework for Verification and Recalibration of Ensemble Forecasts: How Uncertain is NAO Predictability?

Abstract Predictability estimates of ensemble prediction systems are uncertain because of limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that provides a simple 6-parameter representation of ensemble forecasting systems and the corresponding observations. The framework is probabilistic and thus allows for quantifying uncertainty in predictability measures, such as correlation skill and signal-to-noise ratios. It also provides a natural way to produce recalibrated probabilistic predictions from uncalibrated ensembles forecasts. The framework is used to address important questions concerning the skill of winter hindcasts of the North Atlantic Oscillation for 1992–2011 issued by the Met Office Global Seasonal Forecast System, version 5 (GloSea5), climate prediction system. Although there is much uncertainty in the correlation between ensemble mean and observations, there is strong evidence of skill: the 95% credible interval of the correlation coefficient of [0.19, 0.68] does not overlap zero. There is also strong evidence that the forecasts are not exchangeable with the observations: with over 99% certainty, the signal-to-noise ratio of the forecasts is smaller than the signal-to-noise ratio of the observations, which suggests that raw forecasts should not be taken as representative scenarios of the observations. Forecast recalibration is thus required, which can be coherently addressed within the proposed framework.

Seasonal forecasting of groundwater levels in principal aquifers of the United Kingdom

Summary To date, the majority of hydrological forecasting studies have focussed on using medium-range (3–15 days) weather forecasts to drive hydrological models and make predictions of future river flows. With recent developments in seasonal (1–3 months) weather forecast skill, such as those from the latest version of the UK Met Office global seasonal forecast system (GloSea5), there is now an opportunity to use similar methodologies to forecast groundwater levels in more slowly responding aquifers on seasonal timescales. This study uses seasonal rainfall forecasts and a lumped groundwater model to simulate groundwater levels at 21 locations in the United Kingdom up to three months into the future. The results indicate that the forecasts have skill; outperforming a persistence forecast and demonstrating reliability, resolution and discrimination. However, there is currently little to gain from using seasonal rainfall forecasts over using site climatology for this type of application. Furthermore, the forecasts are not able to capture extreme groundwater levels, primarily because of inadequacies in the driving rainfall forecasts. The findings also show that the origin of forecast skill, be it from the meteorological input, groundwater model or initial condition, is site specific and related to the groundwater response characteristics to rainfall and antecedent hydro-meteorological conditions.

Skillful Seasonal Prediction of the Southern Annular Mode and Antarctic Ozone

Abstract Using 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 significantly influenced by stratospheric anomalies that descend with time and are coupled with the troposphere. This effect allows skillful statistical forecasts of the October mean SAM to be produced based only on midstratosphere anomalies on 1 August. Together, these results both demonstrate a significant advance in the skill of seasonal forecasts of the Southern Hemisphere and highlight the importance of accurate modeling and observation of the stratosphere in producing long-range forecasts.

Global Seasonal forecast system version 5 (GloSea5): a high‐resolution seasonal forecast system

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.

Predictability of Cold Spring Seasons in Europe

Abstract The seasonal predictability of cold spring seasons (March–May) in Europe from hindcasts/forecasts of three operational coupled general circulation models (CGCMs) is investigated. The models used in the investigation are the Met Office Global Seasonal Forecast System (GloSea), the ECMWF System-2 (S2), and the NCEP Climate Forecast System (CFS). Using the relative operating characteristic score and the Brier skill score the long-term prediction skill for spring 2-m temperature in the lower quintile (20%) is assessed. Over much of central and eastern Europe the predictive skill is found to be high. The skill of the Met Office GloSea and ECMWF S2 models significantly surpasses that of damped persistence over much of Europe but the NCEP CFS model outperforms this reference forecast only over a small area. The higher potential predictability of cold spring seasons in eastern relative to southwestern Europe can be attributed to snow effects as areas of high skill closely correspond with the climatological snow line, and snow is shown in this paper to be linked to cold spring 2-m temperatures in eastern Europe. The ability of the models to represent snow cover during the melt season is also investigated. The Met Office GloSea and the ECMWF S2 models are able to accurately mimic the observed pattern of monthly snow-cover interannual variability, but the NCEP CFS model predicts too short a snow season. Improvements in the snow analysis and land surface parameterizations could increase the skill of seasonal forecasts for cold spring temperatures.