Met Office Research Articles

ECMWF and UK Met Office Offshore Blowing Winds: Impact of Horizontal Resolution and Coastal Orography

AbstractWe analyze the performance of the European Centre for Medium‐Range Weather Forecasts (ECMWF) and UK Met Office (UKMO) meteorological models in predicting offshore blowing wind in coastal areas. Our attention is mainly on the Mediterranean coast, up to 200 km distance from the shore. We compare forecast neutral winds with Advanced Scatterometer measurements. The results indicate that the ECMWF forecasts systematically underestimate wind speed with respect to scatterometer data, while the UKMO model tends to overestimate. A cross‐analysis suggests that, better than fetch, model biases are a function of the model horizontal discretization, hence of the number of grid steps the wind runs over the sea. The steepness and roughness of the land orography before entering the sea, together with the related drag parameters, appear to have a strong role in determining the coastal offshore wind values. Surface drag over land tends to reduce the related wind speed, and it takes a few grid points to adjust to the smooth sea surface conditions. This is supported by a detailed study with a high resolution grid, but different orography resolutions. In these simulations, practically identical coastal wind speed distributions are found when the subgrid orography schemes are switched off. Vertical cross‐sections of potential temperature and wind in bora and mistral conditions illustrate the strong role of gravity waves, wind channeling and turbulent diffusion in coastal numerical weather prediction. Besides local wave modeling, this may be relevant for offshore wind farms, typically situated within 5–50 km from the coast.

First validation of high-resolution satellite-derived methane emissions from an active gas leak in the UK

Abstract. Atmospheric methane (CH4) is the second-most-important anthropogenic greenhouse gas and has a 20-year global warming potential 82 times greater than carbon dioxide (CO2). Anthropogenic sources account for ∼ 60 % of global CH4 emissions, of which 20 % come from oil and gas exploration, production and distribution. High-resolution satellite-based imaging spectrometers are becoming important tools for detecting and monitoring CH4 point source emissions, aiding mitigation. However, validation of these satellite measurements, such as those from the commercial GHGSat satellite constellation, has so far not been documented for active leaks. Here we present the monitoring and quantification, by GHGSat's satellites, of the CH4 emissions from an active gas leak from a downstream natural gas distribution pipeline near Cheltenham, UK, in the spring and summer of 2023 and provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys. We also use a Lagrangian transport model, the UK Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME), to estimate the flux from both satellite- and ground-based observation methods and assess the leak's contribution to observed concentrations at a local tall tower site (30 km away). We find GHGSat's emission estimates to be in broad agreement with those made from the in situ measurements. During the study period (March–June 2023) GHGSat's emission estimates are 236–1357 kg CH4 h−1, whereas the mobile surface measurements are 634–846 kg CH4 h−1. The large variability is likely down to variations in flow through the pipe and engineering works across the 11-week period. Modelled flux estimates in NAME are 181–1243 kg CH4 h−1, which are lower than the satellite- and mobile-survey-derived fluxes but are within the uncertainty. After detecting the leak in March 2023, the local utility company was contacted, and the leak was fixed by mid-June 2023. Our results demonstrate that GHGSat's observations can produce flux estimates that broadly agree with surface-based mobile measurements. Validating the accuracy of the information provided by targeted, high-resolution satellite monitoring shows how it can play an important role in identifying emission sources, including unplanned fugitive releases that are inherently challenging to identify, track, and estimate their impact and duration. Rapid, widespread access to such data to inform local action to address fugitive emission sources across the oil and gas supply chain could play a significant role in reducing anthropogenic contributions to climate change.

How do operational meteorologists perceive model performance for elevated convection?

AbstractOperational Meteorologists (OMs) in the Met Office have a perception that elevated convection is not well represented in kilometre‐scale models, which are generally associated with an improved representation of convection. Here, we consider why there may be a problem with representing elevated convection and consider how OMs judge the model to be poor so often. Three OMs have subjectively scored and classified observed elevated convection cases over the UK from 2017 to 2020. Continental plumes (warm, moist, air coming from the near continent or Africa) account for 73% of the cases. The most frequent errors are associated with (i) location, (ii) organisation, (iii) timing and (iv) intensity of the convection. Thus, OMs perceive that the biggest problem with predicting elevated convection is constraining the location of the convective events. The location errors are particularly prevalent for events coming to the UK from the near continent. The location errors are most frequently identified for flow regimes coming from the near continent in weakly forced synoptic conditions. The identification of this problem enables the specific targeting of research into continental plumes (for UK elevated convection) but also raises questions around the role of lateral boundary conditions in the forecasts of elevated convection.

The Met Office: Taking TikTok by storm

The Met Office has a remit to communicate with all citizens of the UK, providing them with weather information to stay safe and thrive. This considerable task requires the team to be innovative in its approach and consider all possible channels. While weather is a national obsession for many, reaching younger audiences has historically been difficult for the Met Office. With a strong track record of success on more traditional social media platforms such as Twitter, Facebook and Instagram, the Met Office spotted an opportunity in 2020 to leverage a new, developing channel: TikTok. This fast-growing platform could not be ignored as a key channel to reach that much sought-after younger audience. This paper outlines the journey the Met Office has taken towards building an award-winning TikTok channel. From tentative experimentation to finally realising a shared purpose with learning content, the channel has grown from less than 100 followers to nearly 280,000 in three years, received over 2.6 million likes, partnered with other brands, and mastered the live format. A recent video on climate change received 7.2 million video views. The Met Office’s work has been recognised by awards from The Drum, The Chartered Institute of Public Relations and The UK Social Media Awards, to name but a few. This paper also includes a case study on how TikTok played a pivotal role in communicating rare, red weather warnings in 2022, how the Met Office overcame security challenges posed by the platform, and hints and tips for success.

Localized General Vertical Coordinates for Quasi‐Eulerian Ocean Models: The Nordic Overflows Test‐Case

AbstractA generalized methodology to deploy different types of vertical coordinate system in arbitrarily defined time‐invariant local areas of quasi‐Eulerian numerical ocean models is presented. After detailing its characteristics, we show how the general localization method can be used to improve the representation of the Nordic Seas overflows in the UK Met Office NEMO‐based eddy‐permitting global ocean configuration. Three z*‐levels with partial steps configurations localizing different types of hybrid geopotential/terrain‐following vertical coordinates in the proximity of the Greenland‐Scotland ridge are implemented and compared against a control configuration. Experiments include a series of idealized and realistic numerical simulations where the skill of the models in computing pressure forces, reducing spurious diapycnal mixing and reproducing observed properties of the Nordic Seas overflows are assessed. Numerical results prove that the localization approach proposed here can be successfully used to embed terrain‐following levels in a global geopotential levels‐based configuration, provided that the localized vertical coordinate chosen is flexible enough to allow a smooth transition between the two. In addition, our experiments show that deploying localized terrain‐following levels via the multi‐envelope method allows the crucial reduction of spurious cross‐isopycnal mixing when modeling bottom intensified buoyancy driven currents, significantly improving the realism of the Nordic Seas overflows simulations in comparison to the other configurations. Important hydrographic biases are found to similarly affect all the realistic experiments and a discussion on how their interaction with the type of localized vertical coordinate affects the realism of the simulated overflows is provided.

Tropical Cyclone Changes in Convection‐Permitting Regional Climate Projections: A Study Over the Shanghai Region

AbstractChanges in tropical cyclones due to greenhouse‐gas forcing in the Shanghai area have been studied in a double‐nesting regional model experiment using the Met Office convection‐permitting model HadREM3‐RA1T at 4 km resolution and the regional model HadREM3‐GA7.05 at 12 km for the intermediate nest. Boundary conditions for the experiment have been constructed from HadGEM2‐ES, a General Circulation Model (GCM) from the 5th Coupled Model Intercomparison Project (CMIP5), directly using high‐frequency data for the atmosphere (6‐hourly) and the ocean (daily), for the historical period (1981–2000) and under the Representative Concentration Pathway 8.5 (2080–2099). These choices identify one of the warmest climate scenarios available from CMIP5. Given the direct use of GCM data for the baseline, large scale conditions relevant for tropical cyclones have been analyzed, demonstrating a realistic representation of environmental conditions off the coast of eastern China. GCM large scale changes show a reduction in wind shear in addition to the expected strong increase in sea‐surface temperature. Tropical cyclones from the 4 km historical simulation have a negative bias in intensity, not exceeding Category 4, and a wet bias in the rainfall associated with these cyclones. However, there is a clear improvement in cyclone intensity and rainfall at 4 km in comparison with the 12 km simulation. Climate change responses in the 4 km simulation include an extension of the tropical cyclone season, and strong increases in frequency of the most intense cyclones (approximately by a factor of 10) and associated rainfall. These are consistent with the results from the 12 km simulation.

Cover Photograph

Front cover: Storm Eunice was named by the Met Office on 14 February 2022 and rare red weather warnings were issued on the 17th and 18th for parts of southern England. This photograph of the lighthouse at Newhaven harbour, on the Sussex coast, was taken at the peak of the storm at around high tide on 18 February 2022 (1216 utc). That day, a gust of 122mph was recorded at The Needles on the Isle of Wight. (© Christopher Ison – WPOTY entry 2022) image

The use of idealised experiments in testing a new convective parametrization: Performance of CoMorph‐A

AbstractCoMorph is a new mass‐flux convection parametrization under development at the Met Office designed for use within the Unified Model and its successor model, LFRic. Use of a three‐dimensional idealised model enables controlled tests of the performance of the scheme across different regimes. This includes the interaction between the physical parametrizations and the resolved dynamics, allowing study of the emergent organisation of convection on the resolved scale. A selection of well‐known cases is revisited here, with the purpose of documenting the extent to which CoMorph captures a range of important, but challenging, behaviour such as the diurnal cycle and sensitivity to tropospheric moisture. Simulations using CoMorph‐A, a new physics package, that has been demonstrated to perform well at numerical weather prediction (NWP) and climate scales, are compared against the current global atmosphere configuration and high‐resolution results. In addition to an entirely new convection scheme, the package of changes includes significant changes to the cloud, microphysics, and boundary‐layer parametrizations. Recognising that CoMorph‐A is the first version of a scheme that will continue to be substantially developed and to obtain good performance, compromises in tuning have had to be made. These idealised tests therefore show what works well in this configuration, and what areas will require further work. As such, it is quite a demanding testbed and could be viewed as some of the equipment required for a “convective playground”.

Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1

Abstract. Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs).

The Impact of the Tropical Sea Surface Temperature Variability on the Dynamical Processes and Ozone Layer in the Arctic Atmosphere

Tropical sea surface temperature (SST) variability, mainly driven by the El Niño–Southern Oscillation (ENSO), influences the atmospheric circulation and hence the transport of heat and chemical species in both the troposphere and stratosphere. This paper uses Met Office, ERA5 and MERRA2 reanalysis data to examine the impact of SST variability on the dynamics of the polar stratosphere and ozone layer over the period from 1980 to 2020. Particular attention is paid to studying the differences in the influence of different types of ENSO (East Pacific (EP) and Central Pacific (CP)) for the El Niño and La Niña phases. It is shown that during the CP El Niño, the zonal wind weakens more strongly and changes direction more often than during the EP El Niño, and the CP El Niño leads to a more rapid decay of the polar vortex (PV), an increase in stratospheric air temperature and an increase in the concentration and total column ozone than during EP El Niño. For the CP La Niña, the PV is more stable, which often leads to a significant decrease in Arctic ozone. During EP La Niña, powerful sudden stratospheric warming events are often observed, which lead to the destruction of PV and an increase in column ozone.

Digitizing observations from the 1861–1875 Met Office Daily Weather Reports using citizen scientist volunteers

AbstractWe describe the transcription and quality control processes for rescuing around 570,000 sub‐daily and daily weather observations which were recorded in the UK Met Office Daily Weather Reports during the 1861–1875 period. These data are from the start of coordinated weather observations and were collected with the aim of making the first‐ever weather forecasts. The observations were rescued thanks to 3500 volunteers and include sub‐daily sea‐level pressure, dry and wet bulb temperatures, daily maximum and minimum temperatures, and daily rainfall amounts from 70 different locations across Western Europe, and one in Canada. We highlight how these observations will be used to fill gaps in existing pressure and temperature datasets and use two case studies to show how the pressure observations will likely better constrain the atmospheric circulation during two severe storms. We also compare a sub‐sample of the newly rescued observations with data that were previously digitized for a small number of locations for the same dates, finding good agreement in general, although some discrepancies remain.

Decisions with weather warnings when waiting is an option

We use laboratory experiments to study decisions with a two-stage weather warning system that varies in the reliability of early warnings. The warning system is based on one used by the Met office since 2011: A risk matrix where the rows and columns represent probability levels and damage levels, respectively. Participants can choose between a safe but costly option and a risky but free option. They can make their decisions based on an unreliable early warning or wait for a more reliable warning, however, waiting makes the safe option more expensive. We find that increasing the reliability of the early warning generally leads participants to wait less and, surprisingly, the reliability of the early warning has a significant impact on the decision they make after waiting and receiving the more reliable warning.

The influence of resolved convective motions on scalar dispersion in hectometric‐scale numerical weather prediction models

AbstractThe UK Met Office has a 300‐m grid length numerical weather prediction (NWP) model running routinely over London and, in research mode, city‐scale hectometric grid length NWP has become commonplace. It is important to understand how moving from kilometre‐ to hectometre‐scale grid length NWP influences boundary‐layer vertical mixing. For a clear‐sky convective boundary layer (CBL) case study, using 55‐ and 100‐m grid length NWP, we demonstrate that CBL vertical mixing of passive scalar is almost fully resolved. Passive scalar converges near the surface after emission from an idealised pollution ground source representing city‐scale emissions, and is transported in updrafts preferentially into the upper boundary layer. Approximately 8 km downstream of the source edge, this causes lower near‐surface concentrations compared with 1.5‐km grid length NWP, where vertical mixing is fully parameterised. This demonstrates that resolving ballistic‐type dispersion, which is not typically represented in NWP vertical mixing parameterisations, can have a leading‐order influence on city‐scale near‐surface pollution concentration. We present a simple analytical model that is able to capture diffusive and ballistic dispersion behaviour in terms of effective timescales. The timescale controlling how long it takes passive scalar to become well mixed in the CBL is times longer for 1.5‐km compared with 100‐ and 55‐m grid length NWP.

Use of ZDR columns for early detection of severe convection within the operational radar network of the United Kingdom

AbstractDifferential reflectivity () columns were observed using a Met Office three‐dimensional radar composite. An algorithm for automatic detection of columns was developed, based on dB and dBZ. Across three case days, detected columns were found to precede severe convection in tracked convective cells with a range of lead times from 0 to 20 min depending on the case day. Requiring maxima above 1.4 dB and 30 dBZ of and respectively was an appropriate second condition for all three cases although the skill in the early detection of severe convection varied across case days. Despite the high probability of detections, the high false alarm rate accompanied by low critical success index and data latency limit performance based on the three cases considered in this study. Nevertheless, the ability to detect columns in operational radar data with a useful lead time prior to severe convection in certain conditions is a promising development towards advancing nowcasting of severe convection in the United Kingdom.

A seamless blended multi‐model ensemble approach to probabilistic medium‐range weather pattern forecasts over the UK

AbstractThis paper describes a new seamless blended multi‐model ensemble configuration of an existing probabilistic medium‐ to extended‐range weather pattern forecasting tool (called Decider) run operationally at the Met Office. In its initial configuration, the tool calculated and presented probabilistic weather pattern forecast information for five individual ensemble forecasting systems, which varied in terms of their number of ensemble members, horizontal resolution, update frequencies and forecast lead time. This resulted in multiple forecasts for the same validity time which varied in terms of forecast skill depending on the lead time in question. This presented challenges for end‐users (e.g., operational meteorologists) in terms of knowing which forecast output is best to use and at which lead time, as well as knowing what to do in situations where forecasts varied between ensembles. To get around these challenges, a new seamless blended multi‐model ensemble configuration has been implemented operationally, comprising of output from five separate ensembles, and provides a single best forecast from day one out to day 45. Objective verification for a set of eight weather pattern groups covering forecasts initialized over a 6‐year period (2017–2022) shows that the seamless blended multi‐model ensemble forecasts are at least as good as, if not better than the best performing individual model.

Jumpiness in Ensemble Forecasts of Atlantic Tropical Cyclone Tracks

Abstract We investigate the run-to-run consistency (jumpiness) of ensemble forecasts of tropical cyclone tracks from three global centers: ECMWF, the Met Office, and NCEP. We use a divergence function to quantify the change in cross-track position between consecutive ensemble forecasts initialized at 12-h intervals. Results for the 2019–21 North Atlantic hurricane season show that the jumpiness varied substantially between cases and centers, with no common cause across the different ensemble systems. Recent upgrades to the Met Office and NCEP ensembles reduced their overall jumpiness to match that of the ECMWF ensemble. The average divergence over the set of cases provides an objective measure of the expected change in cross-track position from one forecast to the next. For example, a user should expect on average that the ensemble mean position will change by around 80–90 km in the cross-track direction between a forecast for 120 h ahead and the updated forecast made 12 h later for the same valid time. This quantitative information can support users’ decision-making, for example, in deciding whether to act now or wait for the next forecast. We did not find any link between jumpiness and skill, indicating that users should not rely on the consistency between successive forecasts as a measure of confidence. Instead, we suggest that users should use ensemble spread and probabilistic information to assess forecast uncertainty, and consider multimodel combinations to reduce the effects of jumpiness. Significance Statement Forecasting the tracks of tropical cyclones is essential to mitigate their impacts on society. Numerical weather prediction models provide valuable guidance, but occasionally there is a large jump in the predicted track from one run to the next. This jumpiness complicates the creation and communication of consistent forecast advisories and early warnings. In this work we aim to better understand forecast jumpiness and we provide practical information to forecasters to help them better use the model guidance. We show that the jumpiest cases are different for different modeling centers, that recent model upgrades have reduced forecast jumpiness, and that there is not a strong link between jumpiness and forecast skill.

Comparison of probabilistic forecasts of extreme precipitation for a global and convection‐permitting ensemble and hybrid statistical–dynamical method based on equatorial wave information

AbstractRecent work has demonstrated that skilful hybrid statistical–dynamical forecasts of heavy rainfall events in Southeast Asia can be made by combining model forecasts of the phases and amplitudes of Kelvin, Rossby, and westward‐moving Rossby gravity waves with climatological rainfall statistics conditioned on these waves. This study explores the sensitivity of this hybrid forecast to its parameter choices and compares its skill in forecasting extreme rainfall events in the Philippines, Malaysia, Indonesia, and Vietnam to that of the Met Office Global and Regional Ensemble Prediction System (MOGREPS). The hybrid forecast is found to outperform both the global and convection‐permitting ensemble in some regions when forecasting the most extreme events; however, for less extreme events, the ensemble is found more skilful. A weighted blend of the MOGREPS forecasts and the hybrid forecast was found to have the highest skill of all for almost all definitions of extreme event and in most regions. To quantify the influence of errors in the predicted wave state on the skill of the hybrid forecast, the skill of a hypothetical best‐case forecast was also calculated using reanalysis data to specify the wave amplitudes and phases. This best‐case forecast indicates that errors in the forecasts of all wave types reduce the skill of hybrid forecast; however, the reduction in skill is largest for Kelvin waves. The skill in convection‐permitting models is greater than for global models in the regions where Kelvin waves dominate, but the added value of limited‐area high‐resolution forecasts is hampered by the poor representation of Kelvin waves in the parent global model.

The effect of diurnal warming of sea‐surface temperatures on the propagation speed of the Madden–Julian oscillation

AbstractThe diurnal warm layer in the upper ocean develops during low surface winds and high incoming solar radiation conditions, often increasing sea‐surface temperatures (SSTs) by up to 1°C. The suppressed phase of the Madden–Julian Oscillation (MJO) favours the formation of such a layer. Here, we analyse the coupled ocean–atmosphere and atmosphere‐only numerical weather prediction systems of the UK Met Office to reveal that important differences arise from the representation of the diurnal warm layer in the coupled model. Though both models are skilful in predicting the MJO to at least a 7‐day lead time, the coupled model predicts approximately 12% faster MJO RMM phase speed propagation than the atmosphere‐only model due to the ability to resolve diurnal warming in the upper ocean that rectifies onto MJO‐associated SST anomalies. The diurnal warming of SST (dSST) in the coupled model leads to an increase in daily mean SST compared with the atmosphere‐only model persisted foundation SST. The strength of the dSST in the coupled model is modulated by MJO conditions. During suppressed MJO conditions on lead day 1, the dSST is enhanced, leading to 0.2°C warmer daily mean MJO‐associated SST anomalies and increased convection in the coupled model by lead day 7. During active MJO convection, the dSST is suppressed, leading to 0.1°C colder MJO‐associated SST anomalies in the coupled model and reduced convection by lead day 7. This variability in dSST further amplifies the MJO propagation speed, underlining the importance of the two‐way feedback between the MJO and the diurnal cycle of SST and the need to accurately represent this process in coupled models.

A comparison of Rosenbrock–Wanner and Crank–Nicolson time integrators for atmospheric modelling

AbstractNonhydrostatic atmospheric models often use semi‐implicit temporal discretisations in order to negate the time‐step limitation of explicitly resolving the fast acoustic and gravity waves. Solving the resulting system to machine precision using Newton's method is considered prohibitively expensive, and so the nonlinear solver is typically truncated to a fixed number of iterations, often using an approximate Jacobian matrix that is reassembled only once per time step. The present article studies the impact of using various third‐order, four stage Rosenbrock–Wanner schemes, where integration weights are chosen to meet specific stability and order conditions, in comparison to a Crank–Nicolson time discretisation, as is done in the UK Met Office's LFRic model. Rosenbrock–Wanner schemes present a promising alternative on account of their ability to preserve their temporal order with only an approximate Jacobian, and may be constructed to be stiffly‐stable, so as to ensure the decay of fast unresolved modes. These schemes are compared for the 2D rotating shallow‐water equations and the 3D compressible Euler equations at both planetary and nonhydrostatic scales and are shown to exhibit improved results in terms of their energetic profiles and stability. Results in terms of computational performance are mixed, with the Crank–Nicolson method allowing for longer time steps and faster time to solution for the baroclinic instability test case at planetary scales, and the Rosenbrock–Wanner methods allowing for longer time steps and faster time to solution for a rising bubble test case at nonhydrostatic scales.

Anthropogenic Influence on Decadal Changes in Concurrent Hot and Dry Events over China around the Mid-1990s

The frequency and duration of observed concurrent hot and dry events (HDEs) over China during the growing season (April–September) exhibit significant decadal changes across the mid-1990s. These changes are characterized by increases in HDE frequency and duration over most of China, with relatively large increases over southeastern China (SEC), northern China (NC), and northeastern China (NEC). The frequency of HDEs averaged over China in the present day (PD, 1994–2011) is double that in the early period (EP, 1964–81); the duration of HDEs increases by 60%. Climate experiments with the Met Office Unified Model (MetUM-GOML2) are used to estimate the contributions of anthropogenic forcing to HDE decadal changes over China. Anthropogenic forcing changes can explain 60%–70% of the observed decadal changes, suggesting an important anthropogenic influence on HDE changes over China across the mid-1990s. Single-forcing experiments indicate that the increase in greenhouse gas (GHG) concentrations dominates the simulated decadal changes, increasing the frequency and duration of HDEs throughout China. The change in anthropogenic aerosol (AA) emissions significantly decreases the frequency and duration of HDEs over SEC and NC, but the magnitude of the decrease is much smaller than the increase induced by GHGs. The changes in HDEs in response to anthropogenic forcing are mainly due to the response of climatological mean surface air temperatures. The contributions from changes in variability and changes in climatological mean soil moisture and evapotranspiration are relatively small. The physical processes associated with the response of HDEs to GHG and AA changes are also revealed.