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Adrian Semple, Michael Thurlow, and Sean Milton

Abstract

The case of a small vigorous cyclone crossing the United Kingdom on 1 November 2009 is investigated. Met Office Global Model forecasts at the time displayed a marked change in solutions at a forecast range of 72 h, with those at longer ranges being more representative of the correct solution and those at shorter ranges only gradually migrating toward it. The strong bimodal nature of the Global Model forecasts is enough to overwhelmingly dominate the solutions from the Met Office Global Ensemble on which it is based. An investigation into the case is used as a vehicle for developing an experimental method determining the critical location of assimilated data leading to the largest impact on forecast consistency and the origins of the bimodal solutions. It allows the identification of one global positioning system radio occultation (GPSRO) and three surface observations located around the developing low that have conclusively led to the degradation in forecast skill. An assessment of these observations concludes that they are of relatively good quality and correctly assimilated. The case is suggested to be an example of forecast degradation as a result of the addition of growing errors by the data assimilation scheme.

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Chunlei Liu, Richard P. Allan, Malcolm Brooks, and Sean Milton

Abstract

Forecasts of precipitation and water vapor made by the Met Office global numerical weather prediction (NWP) model are evaluated using products from satellite observations by the Special Sensor Microwave Imager/Sounder (SSMIS) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) for June–September 2011, with a focus on tropical areas (30°S–30°N). Consistent with previous studies, the predicted diurnal cycle of precipitation peaks too early (by ~3 h) and the amplitude is too strong over both tropical ocean and land regions. Most of the wet and dry precipitation biases, particularly those over land, can be explained by the diurnal-cycle discrepancies. An overall wet bias over the equatorial Pacific and Indian Oceans and a dry bias over the western Pacific warm pool and India are linked with similar biases in the climate model, which shares common parameterizations with the NWP version. Whereas precipitation biases develop within hours in the NWP model, underestimates in water vapor (which are assimilated by the NWP model) evolve over the first few days of the forecast. The NWP simulations are able to capture observed daily-to-intraseasonal variability in water vapor and precipitation, including fluctuations associated with tropical cyclones.

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Michael Vellinga, Dan Copsey, Tim Graham, Sean Milton, and Tim Johns

Abstract

We evaluate the impact of adding two-way coupling between atmosphere and ocean to the Met Office deterministic global forecast model. As part of preoperational testing of this coupled NWP configuration we have three years of daily forecasts, run in parallel to the uncoupled operational forecasts. Skill in the middle and upper troposphere out to T + 168 h is generally increased compared to the uncoupled model. Improvements are strongest in the tropics and largely neutral in midlatitudes. We attribute the additional skill in the atmosphere to the ability of the coupled model to predict sea surface temperature (SST) variability in the (sub)tropics with greater skill than persisted SSTs as used in uncoupled forecasts. In the midlatitude, ocean skill for SST is currently marginally worse than persistence, possibly explaining why there is no additional skill for the atmosphere in midlatitudes. Sea ice is predicted more skillfully than persistence out to day 7 but the impact of this on skill in the atmosphere is difficult to verify. Two-way air–sea coupling benefits tropical cyclone forecasts by reducing median track and central pressure errors by around 5%, predominantly from T + 90 to T + 132 h. Benefits from coupling are largest for large cyclones, and for smaller storms coupling can be detrimental. In this study skill in forecasts of the Madden–Julian oscillation does not change with two-way air–sea coupling out to T + 168 h.

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Maria João Carvalho, Sean F. Milton, and José M. Rodríguez

Abstract

In this study, we evaluate the ability of the MetUM to reproduce the Silk Road (SR) and Europe–China (EC) teleconnection patterns and their relationship with precipitation over China. The SR and EC patterns are the main modes of interannual variability of July upper-tropospheric meridional wind. The three main factors to the formation of these patterns are analyzed: 1) the tropical precipitation anomalies, which act as a forcing mechanism; 2) the emission of Rossby waves in the Mediterranean–Caspian Sea region; and 3) the basic state of the tropospheric jet over Eurasia. It was found that the model has some difficulty reproducing the main modes of variability in atmosphere-only mode (SR and EC pattern correlation of 0.31 and 0.54, respectively) with some improvement in coupled mode (pattern correlations of 0.56 and 0.44, respectively). Relaxation experiments were used to assess the impact that improving circulation in key regions has on the teleconnections. It was found that nudging wind and temperatures in the forcing regions within the tropics improved the Silk Road pattern whereas nudging in the region where the jet transitions between the North Atlantic Ocean and Eurasian continent—correcting the basic state—had the most impact on the EC teleconnection pattern. This suggests that while the Silk Road pattern is more sensitive to changes in the forcing, the Europe–China pattern is more sensitive to the basic state.

Open access
Matt Hawcroft, Sally Lavender, Dan Copsey, Sean Milton, José Rodríguez, Warren Tennant, Stuart Webster, and Tim Cowan

Abstract

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods. During the first week of February, when the event had its greatest impact in northwest Queensland, record-breaking precipitation accumulations were observed in several locations, accompanied by strong winds, substantial cold maximum temperature anomalies, and related wind chill. In spite of the extreme nature of the event, the monthly rainfall outlook for February issued by Australia’s Bureau of Meteorology on 31 January provided no indication of the event. In this study, we evaluate the dynamics of the event and assess how predictable it was across a suite of ensemble model forecasts using the Met Office numerical weather prediction (NWP) system, focusing on a 1-week lead time. In doing so, we demonstrate the skill of the NWP system in predicting the possibility of such an extreme event occurring. We further evaluate the benefits derived from running the ensemble prediction system at higher resolution than used operationally at the Met Office and with a fully coupled dynamical ocean. We show that the primary forecast errors are generated locally, with key sources of these errors including atmosphere–ocean coupling and a known bias associated with the behavior of the convection scheme around the coast. We note that a relatively low-resolution ensemble approach requires limited computing resources, yet has the capacity in this event to provide useful information to decision-makers with over a week’s notice, beyond the duration of many operational deterministic forecasts.

Open access
Jian Li, Haoming Chen, Xinyao Rong, Jingzhi Su, Yufei Xin, Kalli Furtado, Sean Milton, and Nina Li

Abstract

A high-impact extreme precipitation event over the Yangtze River valley (YRV) in the midsummer of 2016 is simulated using the Climate System Model of Chinese Academy of Meteorological Sciences (CAMS-CSM). After validation of the model’s capability in reproducing the climatological features of precipitation over the YRV, the Transpose Atmospheric Model Intercomparison Project (T-AMIP)–type experiment, which runs the climate model in the weather forecast mode, is applied to investigate the performance of the climate model in simulating the spatial and temporal distribution of rainfall and the related synoptic circulation. Analyses of T-AMIP results indicate that the model realistically reproduces the heavy rainfall centers of accumulated precipitation amount along the YRV, indicating that the climate model has the ability to simulate the severity of the extreme event. However, the frequency–intensity structure shows similar biases as in the AMIP experiment, especially the underestimation of the maximum hourly intensity. The simulation of two typical heavy rainfall periods during the extreme event is further evaluated. The results illustrate that the model shows different performances during periods dominated by circulation systems of different spatial scales. The zonal propagation of heavy rainfall centers during the first two days, which is related to the eastward movement of the southwest vortex, is well reproduced. However, for another period with a smaller vortex, the model produces an artificial steady heavy rainfall center over the upwind slope of the mountains rather than the observed eastward movement of the precipitation centers.

Open access
Phil P. Harris, Sonja S. Folwell, Belen Gallego-Elvira, José Rodríguez, Sean Milton, and Christopher M. Taylor

Abstract

Soil moisture availability exerts control over the land surface energy partition in parts of Europe. However, determining the strength and variability of this control is impeded by the lack of reliable evaporation observations at the continental scale. This makes it difficult to refine the broad range of soil moisture–evaporation behaviors across global climate models (GCMs). Previous studies show that satellite observations of land surface temperature (LST) during rain-free dry spells can be used to diagnose evaporation regimes at the GCM gridbox scale. This relative warming rate (RWR) diagnostic quantifies the increase in dry spell LST relative to air temperature and is used here to evaluate a land surface model (JULES) both offline and coupled to a GCM (HadGEM3-A). It is shown that RWR can be calculated using outputs from an atmospheric GCM provided the satellite clear-sky sampling bias is incorporated. Both offline JULES and HadGEM3-A reproduce the observed seasonal and regional RWR variations, but with weak springtime RWRs in central Europe. This coincides with sustained bare soil evaporation (Ebs) during dry spells, reflecting previous site-level JULES studies in Europe. To assess whether RWR can discriminate between surface descriptions, the bare soil surface conductance and the vegetation root profile are revised to limit Ebs. This increases RWR by increasing the occurrence of soil moisture–limited dry spells, yielding more realistic springtime RWRs as a function of antecedent precipitation but poorer relationships in summer. This study demonstrates the potential for using satellite LST to assess evaporation regimes in climate models.

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Andrew Brown, Sean Milton, Mike Cullen, Brian Golding, John Mitchell, and Ann Shelly

In recent years there has been a growing appreciation of the potential advantages of using a seamless approach to weather and climate prediction. However, what exactly should this mean in practice? To help address this question, we document some of the experiences already gathered over 25 years of developing and using the Met Office Unified Model (MetUM) for both weather and climate prediction. Overall, taking a unified approach has given enormous benefits, both scientific and in terms of efficiency, but we also detail some of the challenges it has presented and the approaches taken to overcome them.

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Steven C. Hardiman, Ian A. Boutle, Andrew C. Bushell, Neal Butchart, Mike J. P. Cullen, Paul R. Field, Kalli Furtado, James C. Manners, Sean F. Milton, Cyril Morcrette, Fiona M. O’Connor, Ben J. Shipway, Chris Smith, David N. Walters, Martin R. Willett, Keith D. Williams, Nigel Wood, N. Luke Abraham, James Keeble, Amanda C. Maycock, John Thuburn, and Matthew T. Woodhouse

Abstract

A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.

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Adam A. Scaife, Elizabeth Good, Ying Sun, Zhongwei Yan, Nick Dunstone, Hong-Li Ren, Chaofan Li, Riyu Lu, Peili Wu, Zongjian Ke, Zhuguo Ma, Kalli Furtado, Tongwen Wu, Tianjun Zhou, Tyrone Dunbar, Chris Hewitt, Nicola Golding, Peiqun Zhang, Rob Allan, Kirstine Dale, Fraser C. Lott, Peter A. Stott, Sean Milton, Lianchun Song, and Stephen Belcher

Abstract

We present results from the first 6 years of this major UK government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between UK and Chinese climate scientists and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modelling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over three hundred peer reviewed studies generated jointly by UK and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skilful predictions of important aspects of Chinese climate such as East Asian Summer Monsoon rainfall. In addition, the development of improved modelling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real time climate services. Participation of dozens of institutes through sub-projects in this programme, which is governed by the Met Office Hadley Centre, the China Meteorological Administration and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services.

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