A spatial approach to the analysis of convective scale ensemble systems

The use of kilometre-scale ensembles in operational forecasting provides challenges for forecast evaluation and interpretation. New spatial methods for characterising and verifying convection permitting ensembles are developed, and tested on the 12 member Met Office 2.2km resolution UK ensemble. Each ensemble member is regarded as an equally plausible realisation of the true atmospheric state. A novel methodology is presented for spatial ensemble characterisation based on the Fractions Skill Score. Characterising the domain-wide ensemble behaviour, these methods identify useful spatial scales and spin-up times for the model, and demonstrate the upscale growth of errors and forecast differences. The ensemble spread is shown to be highly dependent on the spatial scales considered and the threshold applied to the field. Comparing differently-generated ensemble systems shows the utility of spatial ensemble evaluation techniques for assessing different ensemble perturbation strategies. It is also important to consider location-dependent ensemble behaviour. A new method for calculating the location-dependent spatial agreement of ensemble members is presented. Through comparing with radar observations, the location-dependent spatial skill of the ensemble is also quantified. These methods are verified using an idealised experiment. Six convective cases, and a summer season, are used to demonstrate the methods in an operational context, with links made to physical processes. Overall, the ensemble system is reasonably well-spread spatially. Poorer spread-skill is associated with a low fractional coverage of rain, and low synoptic-scale rain rates. Higher confidence in the location of precipitation is found to the northwest of the UK. To investigate coherent physical structures in the ensemble, the spatial approach was used to inform the calculation of multivariate correlations. Using the spatial approach, physically-meaningful correlations which demonstrate inter-variable relationships are obtained. Overall, the spatial approach is found to give useful information for forecasting, and for the interpretation and evaluation of convection-permitting ensembles

The link between catchment precipitation forecast skill and spread to that of downstream ensemble hydrological forecasts

Operational rainfall and flood forecasting systems across the world are increasingly using ensemble approaches. Such systems are operated by the Flood Forecasting Centre (FFC) and Scottish Flood Forecasting Service (SFFS) across Great Britain producing ensemble gridded hydrological forecasts for the next 5-6 days. In order to maximise the practical day-to-day use of these systems for decision-making and warning, duty hydro-meteorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. In this work, a common verification framework is defined and used in order to understand the relative levels of skill in both rainfall and river flow forecasting systems. A blended 24-member ensemble precipitation forecast, produced by the Met Office, is used to drive the operational distributed hydrological model in ensemble mode. The hydrological forecasts provide output every 15 minutes out to 6 days on a 1km grid. The blended rainfall forecast is a mixture of the 2.2 km MOGREPS-UK ensemble up to 36h and the 32 km global MOGREPS-G ensemble at longer lead-times. The forecasts are interpolated on to a common 2 km grid and the hydrological model used is the Grid-to-Grid model (G2G) developed by the Centre for Ecology & Hydrology. To establish an upper bound on skill, assessments over a daily lead-time interval are studied first, and will be the focus here. Spatial and regional variations in forecast skill are compared between the precipitation (e.g. daily accumulations) and the river flow forecasts. Also of interest is the impact of catchment size and how to pool and present the skill metrics in a meaningful way for end-users. For precipitation, the impact of observation type: gridded gauge-only analyses and a radar-derived (gauge calibrated) precipitation product, is compared to quantify the uncertainty that comes from the observations. Of particular interest is understanding how the spread in the precipitation forecast is modulated by the downstream hydrological model. Is it inflated, does it remain comparable, or is it reduced? The work aims to establish the basis for a real-time monitoring tool that can assist hydro-meteorologists in their interpretation of operational ensemble forecasts, and facilitate associated decision making processes

Forecasting snowmelt flooding over Britain using the Grid-to-Grid model: a review and assessment of methods

In many regions of high annual snowfall, snowmelt modelling can prove to be a vital component of operational flood forecasting and warning systems. Although Britain as a whole does not experience prolonged periods of lying snow, with the exception of the Scottish Highlands, the inclusion of snowmelt modelling can still have a significant impact on the skill of flood forecasts. Countrywide operational flood forecasts over Britain are produced using the national Grid-to-Grid (G2G) distributed hydrological model. For Scotland, snowmelt is included in these forecasts through a G2G snow hydrology module involving temperature-based snowfall/rainfall partitioning and functions for temperature-excess snowmelt, snowpack storage and drainage. Over England and Wales, the contribution of snowmelt is included by pre-processing the precipitation prior to input into G2G. This removes snowfall diagnosed from weather model outputs and adds snowmelt from an energy budget land surface scheme to form an effective liquid water gridded input to G2G. To review the operational options for including snowmelt modelling in G2G over Britain, a project was commissioned by the Environment Agency through the Flood Forecasting Centre (FFC) for England and Wales and in partnership with the Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW). Results obtained from this snowmelt review project will be reported on here. The operational methods used by the FFC and SEPA are compared on past snowmelt floods, alongside new alternative methods of treating snowmelt. Both case study and longer-term analyses are considered, covering periods selected from the winters 2009-2010, 2012-2013, 2013-2014 and 2014-2015. Over Scotland, both of the snowmelt methods used operationally by FFC and SEPA provided a clear improvement to the river flow simulations. Over England and Wales, fewer and less significant snowfall events occurred, leading to less distinction in the results between the methods. It is noted that, for all methods considered,large uncertainties remain in flood forecasts influenced by snowmelt. Understanding and quantifying these uncertainties should lead to more informed flood forecasts and associated guidance information

Towards operational joint river flow and precipitation ensemble verification: considerations and strategies

Operational rainfall and flood forecasting systems across the world are increasingly using ensemble approaches. In Britain such systems are operated by the Flood Forecasting Centre (FFC) over England & Wales and by the Scottish Flood Forecasting Service (SFFS) over Scotland producing ensemble gridded hydrological forecasts out to 5 or 6 days. In order to maximise the practical day-to-day use of these systems for flood guidance and warning, duty hydrometeorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. To help meet this requirement, a common framework for the verification of river flow and precipitation ensembles is developed and demonstrated over Britain for eventual use in an operational flood forecasting setting. The river flow ensembles are obtained from the distributed hydrological model Grid-to-Grid (G2G), configured with national coverage on a 1 km grid and using an ensemble of 15 minute precipitation accumulations as input. The precipitation ensemble consists of operational Numerical Weather Prediction (NWP) forecasts from the Met Office Unified Model. Given the different physical characteristics of river flow and catchment precipitation, and differences in forecast verification methodologies routinely employed by the hydrological and meteorological communities, key considerations for the common verification framework are identified and investigated. These include the appropriateness of different precipitation accumulation periods given timing errors and hydrological response times, the operationally relevant use of river flow and rainfall thresholds for contingency tables and skill scores based on them, and the effects of precipitation observation error on verification. The practical challenges of verification using a limited record of precipitation ensembles, from a system only relatively recently made operational, are highlighted. Methods of obtaining more robust verification statistics, given the available ensembles, are presented and demonstrated for example periods in December 2015. At the regional scale, both river flow and precipitation verification results are shown to be dependent on the locations considered and related to variations in precipitation totals. For river flows, catchment size is found to be a key influence on ensemble performance. It is demonstrated how this behaviour can be used to obtain more-robust river flow verification statistics at sub-regional scales

Catchment-based precipitation and river flow ensemble forecast skill in the presence of observation uncertainty

The use of ensemble forecasts in operational rainfall and flood forecasting systems is rapidly increasing. In the UK, such systems are operated by the Flood Forecasting Centre (FFC) and Scottish Flood Forecasting Service (SFFS) producing ensemble gridded hydrological forecasts out to 6 days. In order to maximise the practical day-to-day use of these systems, for decision-making and warning, duty hydrometeorologists require a sound understanding of both the meteorological and hydrological ensemble forecast skill. A blended Met Office 24-member ensemble precipitation forecast – a mixture of the STEPS nowcast ensemble and STEPS-blended 2.2 km MOGREPS-UK ensemble and 32 km global MOGREPS-G ensemble – drives the Grid-to-Grid (G2G) distributed hydrological model developed by the Centre for Ecology & Hydrology (CEH). G2G uses 15-minute precipitation accumulations as input, and produces river flows at 15-minute intervals on a 1km grid. Phase 1 of the investigation, completed in 2017, formulated and demonstrated a common rainfall and river flow ensemble verification framework. The results gave an initial appreciation of the relative levels of skill in both ensemble rainfall and river flow forecasting systems. In 2018, the verifications of daily and hourly precipitation accumulations will be extended to use 15-minute accumulations. Verifications for three forecast time-horizons – Day 1, Days 2-3 and Days 4-6 – will also be demonstrated. In Phase 1, the sensitivity of verification measures to observation type was illustrated by comparing scores based on radar-only and raingauge-only analyses. Here, in Phase 2, theoretical principles discussed by Ferro (2017) are explored to determine whether a practical application of the theory is possible to gain a more robust measure of forecast performance in the presence of observation uncertainty. Reference Ferro, C.A.T. 2017. Measuring forecast performance in the presence of observation error. Q. J. R. Meteorol. Soc., 143, 2665-2676

The COnvective Precipitation Experiment (COPE): investigating the origins of heavy precipitation in the southwestern UK

A recent field campaign in southwest England used numerical modeling integrated with aircraft and radar observations to investigate the dynamic and microphysical interactions that can result in heavy convective precipitation. The COnvective Precipitation Experiment (COPE) was a joint UK-US field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly due to the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the US. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve NWP model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the UK BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360-deg volume scans over 10 elevation angles approximately every 5 minutes, and was augmented by two UK Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper: (i) provides an overview of the COPE field campaign and the resulting dataset; (ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone; and (iii) explains how COPE data will be used to improve high-resolution NWP models for operational use