Tropical cyclone tracking and verification techniques for Met Office numerical weather prediction models

Transcription

1 METEOROLOGICAL APPLICATIONS Meteorol. Appl. 24: 1 8 (2017) Published online 13 December 2016 in Wiley Online Library (wileyonlinelibrary.com) DOI: /met.1599 Tropical cyclone tracking and verification techniques for Met Office numerical weather prediction models J. T. Heming* Foundation Science, Global Model Evaluation and Development, Met Office, Exeter, UK ABSTRACT: The Met Office has been objectively verifying tropical cyclone (TC) forecast tracks from its global numerical weather prediction model for many years and also produces TC forecast guidance in real time from both the deterministic and ensemble configurations of the model. An essential component of these processes is a system to automatically identify TCs in the model analysis and track them in the model forecast. This paper describes the history of TC tracking in Met Office models and gives details of the current technique used both within the TC forecast verification system and in the production of real-time forecast guidance products. KEY WORDS tropical cyclone; tracking; numerical models; verification Received 18 November 2015; Revised 4 May 2016; Accepted 18 June Introduction Tracking tropical cyclones (TCs) in numerical weather prediction (NWP) models in order to identify their position and intensity is essential both for post-event model evaluation and for the generation of forecast guidance products in real time. Various techniques are used by modelling centres around the world (e.g. Vitart and Stockdale, 2001; van der Grijn, 2002; Tallapragada et al., 2013). In the present paper the methods used by the Met Office are discussed, starting with an overview of previous methods and concluding with a detailed discussion of the method currently in use. 2. History of TC tracking at the Met Office In the late 1980s the Met Office first started giving attention to the TC track forecasts from its deterministic global NWP model. At this time real-time TC track forecasts were provided in text format guidance messages to other meteorological services, initially just the Australian Bureau of Meteorology but later expanding to cover all regions of the world that experience TCs. These forecast guidance messages were produced by manual inspection of mean sea-level pressure (MSLP) forecast charts and entry of the model s forecast positions in a text template by a forecaster. Some basic verification of TC forecast track errors was also undertaken by hand at this time. However, as the profile and usage of Met Office TC forecasts increased it became apparent that this manual method of tracking was impractical if all TCs were to be tracked in twice daily forecasts out to 5 days ahead. Hence, in the early 1990s work was undertaken to develop an automated tracking technique which interrogated the model fields and produced datasets of forecast positions as well as various measures of track error. * Correspondence: J. T. Heming, Met Office, FitzRoy Road, Exeter, Devon, EX1 3PB, UK. julian.heming@metoffice. gov.uk This article is published with the permission of the Controller of HMSO and the Queen s Printer for Scotland. A critical element of any TC tracker is deciding the primary model field or fields used for tracking. At the time the first automated tracker was developed, the Met Office Global Model (MOGM) had a relatively coarse horizontal resolution (about 90 km at mid-latitudes). A simple TC initialization technique was in operation at the time, although it was only used at the discretion of the forecaster if time allowed. Consequently TCs were often both analysed and forecasted as weak features in the MSLP field. For example, at 1200 UTC 23 August 1992 Hurricane Andrew was a compact category 5 hurricane with central pressure of 933 hpa and sustained winds of near 145 kn as it crossed the Bahamas. However, the MOGM analysed a rather broad and shallow area of low pressure with a minimum value of 1013 hpa (Figure 1). Weaker storms were often depicted as nothing more than shallow waves and hence were hard to track consistently in the MOGM s MSLP field. It was found that the relative vorticity (RV) field at 850 hpa (850RV) provided a more distinct representation of the centre of the TC in the model that could be tracked easily by an automated system. Hence this field was chosen as the basis for the TC tracker. An outline of the TC tracker and verification technique developed at this time can be found in Heming (1994). For most well developed TCs moving over open ocean, the location of the maximum 850RV and minimum MSLP in the model are fairly closely collocated. However, on occasions 850RV can give unrealistic locations of the TC centre. For example, when TCs pass over large islands with high orography or as they start to undergo extra-tropical transition, the 850RV field in the model forecast can develop two maxima close to the TC centre or the 850RV maximum can migrate some distance from the minimum in the MSLP and low level wind fields. Figures 2 and 3 show some examples of these effects. In Figure 2, Typhoon Sinlaku was forecasted to be positioned close to Taiwan. The 850RV field had become annular with two distinct centres, the first of which was close to the northern tip of the island (closest to the point of lowest MSLP) and another stronger centre was located over the southern tip. Whilst neither of these local maxima in 850RV may be a perfect representation of the forecast centre of the TC, the latter was considered the better 2016 Crown Copyright, Met Office

2 2 J. T. Heming Figure 1. Met Office Global Model mean sea-level pressure analysis of Hurricane Andrew at 1200 UTC 23 August representation since it was closer to the point of minimum MSLP. However, the TC tracker fixed the centre of the TC on the southernmost 850RV centre since it took no account of the MSLP field. In Figure 3, Hurricane Hanna was undergoing extra-tropical transition as it made landfall over the northeastern United States and eastern Canada. As it started to acquire frontal characteristics, the maximum in 850RV migrated northeastwards along the developing frontal zone some distance from the minimum in MSLP. The latter was considered a better representation of the centre of the TC at this time, but the TC tracker fixed it to the point of highest 850RV well to the northeast. Following its development, the TC tracker was initially used in the verification of TC track forecasts from the MOGM. At this time, real-time guidance was still produced by hand. In 1994 a new technique for initialization of TCs in the MOGM was developed (Heming et al., 1995). This resulted in a 30% reduction in TC track errors in the MOGM and led to a greater demand for forecast guidance from the model in real time. Thus, in order to satisfy this demand, a first guess guidance product was developed in This product was automatically generated using essentially the same TC tracker as used for TC forecast verification. The first guess guidance was checked over by a forecaster and any anomalies in the automatically produced track (e.g. for reasons stated earlier in this section) were amended before the guidance was issued as a bulletin via the Global Telecommunications System. In 2006 the Met Office started producing experimental ensemble forecasts of TC tracks using its MOGREPS-15 system, later to be superseded by its MOGREPS-G system (Bowler et al., 2008). The TC tracker in operation at the time was again used to produce TC tracks from each of the 24 ensemble members, which were then used to generate products such as strike probability charts. However, unlike for the deterministic forecasts, it was impractical to check manually each of the 24 tracks produced by the system. This gave rise to situations where automated products were occasionally based on unrealistic representations of the TC track. For example, Figure 4 shows the ensemble TC tracks for Typhoon Jangmi for one particular run of MOGREPS-15 in Some tracks show a lurch towards the north of Taiwan as a result of the point of highest 850RV shifting well to the north of the point of lowest MSLP in the model fields. Some tracks then dipped south into the South China Sea whilst others showed erratic tracks towards the northeast as they followed various 850RV centres associated with an elongating TC circulation. In order to produce more realistic real-time forecast tracks in cases such as this a more robust TC tracker was required, which could also be used for post-event verification. The Met Office original univariate approach to tracking TCs was in contrast to the National Centers for Environmental Prediction who use any or all of MSLP, 850 and 700 hpa RV and geopotential height to track TCs (Tallapragada et al., 2013). The method used by the European Centre for Medium-range Weather Forecasts identifies TCs by examination of the 850RV field, but then fixes the TC centre to the nearest local MSLP minimum (Vitart and Stockdale, 2001; van der Grijn, 2002). In 2008, it was decided that the latter principle would be adopted in the new Met Office methodology as it would permit continued usage of 850RV to track TCs, since 850RV gives a strong signal of the approximate centre of the TC even for weak systems. However, fixing the centre of the TC to the nearest local MSLP minimum was expected to overcome some of the issues highlighted earlier. A change to this bivariate approach was implemented in Subsequent enhancements to the system such as the introduction of a closed isobar check would make the tracker far more robust and usable in a fully automated production system without the need for any human checking or intervention. Sections 3 and 4 describe how the current TC tracking methodology is applied to post-event TC forecast verification and real-time guidance production. 3. TC forecast verification: the current method This section describes the current method used for tracking and verifying both the track and intensity of TCs in Met Office models, both global and regional Observed positions The model s analysed and forecast TC positions can only be verified if an observed position is available. In real time, observed

3 3 Tropical cyclone tracking and verification in Met Office models 120 E 130 E 30 N Relative Vorticity shading ( 10 6 per s) N E 130 E Figure 2. Met Office Global Model 144 h forecast of Typhoon Sinlaku valid at 0000 UTC 15 September Contours of mean sea-level pressure in hectopascals and shading of highest values of 850 relative vorticity (higher values shaded darker). 70 W 60 W Relative Vorticity shading ( 10 6 per s) N W 60 W Figure 3. Met Office Global Model 24 h forecast of Hurricane Hanna valid at 1200 UTC 7 September Contours of mean sea-level pressure in hectopascals and shading of highest values of 850 relative vorticity (higher values shaded darker). positions are collected from a variety of TC warning centres which include the six TC Regional Specialized Meteorological Centres at Miami, Honolulu, Tokyo, New Delhi, La Réunion and Fiji. In addition, data are also collected from the TC warning centres in Australia and the Joint Typhoon Warning Center. These data are received in a variety of bulletin formats such as BUFR, CREX and plain text and are machine read into a database ready for use by the verification scheme Crown Copyright, Met Office When verification is carried out immediately after the event, observed positions collected in real time must be used. However, at the end of each season many of the TC warning centres reanalyse data, some of which may not have been available in real time, and produce best track data for each TC. These data usually correct any inaccuracies in the positions given in real time and can thus be used to provide more accurate verification statistics once they become available, usually some months after Meteorol. Appl. 24: 1 8 (2017)

4 4 J. T. Heming 30 N 20 N 110 E 120 E 130 E Figure 4. MOGREPS-15 ensemble forecast for Typhoon Jangmi from 1200 UTC 26 September Twenty-four separate forecast tracks shown. the end of the TC season in the region in question. Best track data from the World Meteorological Organization s Regional Specialized Meteorological Centres for TC prediction are preferred and are obtained from the IBTrACS database (Knapp et al., 2010). Observed positions are usually available every 6 or sometimes 3 h during the lifetime of each TC. If an observed position is not available exactly at the hours used as the nominal data time of model forecast runs (0000 and 1200 UTC) a linearly interpolated value is calculated. An observed position must be available up to 6 h before (or after) the data time and a second position no more than 12 h after (or before) the data time for this interpolation to proceed. In addition to the observed position, the observed maximum sustained wind and central pressure are stored along with other data such as recent direction and speed of movement of the TC. A threshold for observed maximum sustained wind is available to enable verification of forecasts only when the TC was at or above this threshold at both the data time and the verifying time. Thus, for example, only forecasts for TCs of tropical storm strength or greater are verified if this threshold is set to 35 kn. It is worth noting that whilst the term observation is used to describe the data obtained from the TC warning centres it is acknowledged that this mostly represents a best estimate of the TC s position given the data available Analysed positions The centre of a TC in the model analysis is determined by starting a search from the observed position of the TC (actual or interpolated) at the data time. A search is made within an adjustable radius (nominally set to 2 ) for the grid point with the highest value of 850RV. Once this point has been located a further search is initiated, starting from the grid point of maximum 850RV, for the nearest grid point with a local minimum MSLP within an adjustable radius (nominally set to 2 ). In order to identify a more precise location of the TC centre in the model analysis a surface fitting technique is used. This involves examining a 5 5 grid of model grid points centred on the previously determined grid point of lowest MSLP. A fourth order estimate of the gradients between the grid points is used to produce values of MSLP on a fine grid (typically points) inside each model grid box. The lowest value of MSLP and the corresponding location from this fine grid are used as the TC centre in the analysis. This technique was developed since historically global models had grid lengths which were many times larger than 0.1, which is the usual degree of accuracy used in communication of TC positions. However, more recently global model grid spacings are typically in the range and regional model grid spacings even smaller. Thus there is now less need for this surface fitting technique since the native model grid spacing is close to the desired degree of accuracy. In the model analysis, there is no effective threshold of either 850RV or MSLP which must be met to determine that a TC is analysed if there is an observation valid at this time Forecast positions If no observed position (actual or interpolated) is available at the forecast validity time (VT), then no search is made for a forecast position. However, if an observed position does exist, a search is then made for the TC in the forecast. First, the 6 h forecast is examined. Since there is no forecast track history to use at this time, a search centre is defined as the observed position at the VT. As for the analysis, a search is then made for the highest value of 850RV within an adjustable radius (nominally set to 3 ) of the observed position. This is followed by a search for the local minimum of MSLP within an adjustable radius (nominally set to 3 ) of the point of maximum 850RV. Since the track error in a 6 h forecast is typically near 50 km in the MOGM, then a search radius of 3 ( 300 km) around the

5 Tropical cyclone tracking and verification in Met Office models 5 observed position is considered adequate to capture the forecast position. Tracking then continues at 6 h intervals through to the end of the forecast. At forecast lead times of 12 h or greater, the initial search centre is defined using an extrapolation of the forecast track for the previous 6 h. So, for example, the search centre for the 60 h forecast position is defined by extrapolating the TC s forecast movement between its 48 and 54 h positions for another 6 h. The same methodology of searching for the 850RV maximum followed by the local MSLP minimum and surface fitting to get an accurate position is used. Unlike in the analysis, further criteria are applied to determine if a forecast TC centre has been found. The maximum 850RV must be above and the minimum MSLP must be below predetermined thresholds. These thresholds are tuneable for different resolution models. For example, a higher resolution regional model will have a higher 850RV threshold than the MOGM. The MOGM, with a grid spacing of approximately 17 km, has its 850RV threshold set to s 1. However, for regional models in the tropics with a grid spacing close to 4 km, the threshold of s 1 is found to be more appropriate. Past experience has shown that the thresholds need retuning whenever a change in model resolution is made. Tuning is usually done on an empirical basis by finding a threshold for use with the new model resolution which yields similar results to that of the model at its old resolution. However, if the new model configuration also contains changes in addition to resolution, allowance is made for the fact that it may have different characteristics in predicting TC formation. The TC centre located thus far also needs to pass a closed isobar check for tracking to continue. This involves checking the MSLP at eight points on a defined radius around the point of lowest MSLP to ensure that they are all higher than the MSLP at the centre of the TC by a defined value. The values of the closed isobar radius and closed isobar pressure difference are tuneable to the model. Typical values used for the MOGM are 3.0 radius and 1.5 hpa pressure difference. If these criteria are met a closed isobar is considered to be found and tracking continues. This aspect of the tracker was first introduced in One other option exists to adjust the tracking criteria in cases of large monsoon gyres, such as those which sometimes develop in the western North Pacific. In these circumstances the central pressure of the TC in the model can be low enough to permit tracking, but the 850RV may not attain the tracking threshold due to the broad flabby nature of the low pressure area and slack pressure gradients. Thus the tracker includes the option to relax the 850RV tracking threshold by a defined value if the model s central pressure for the TC is lower than the MSLP threshold by a defined value. The option also exists to increase the closed isobar radius in such circumstances. This allows monsoon gyres and other similar horizontally large tropical low pressure systems to be tracked even though they may not pass all the basic tracking checks. One further option is available to prevent verification of forecasts polewards of a defined latitude. This is typically set to a value of 50. It is very rare for a TC to still be defined as a tropical system at latitudes higher than this, but this check acts as a back stop to prevent any non-tropical systems being tracked and verified if it is deemed inappropriate. Thus, a TC forecast will usually be verified until the warning centre deems it extra-tropical or post-tropical and stops producing observed track data. This procedure is repeated at 6 h steps throughout the forecast until the last forecast lead time to be verified has been reached. CTE ATE Fc1 DPE Ob0 : Previous observed position Ob1 : Current observed position Fc1 : Observed position matching Ob1 DPE : Direct Positional Error CTE : Cross Track Error ATE : Along Track Error Ob1 Ob0 Figure 5. Diagrammatic explanation of measures of tropical cyclone track forecast error Measures of track forecast error Having established the forecast position (in terms of a latitude and longitude) for each forecast lead time, these can be used (in conjunction with the observed positions at the same VTs) to produce a variety of error statistics Direct positional error The simplest form of track error can be described as the direct positional error (DPE). This is simply the great circle distance between the observed and forecast positions at the same VT. DPE can give a basic indication of the track forecast error in the model forecast, but yields no information on the directional bias of the forecast, i.e. whether the forecast was too fast, too slow or had a bias to the left or right of the observed track. In addition, the DPE value alone may not always indicate the skill of the model in forecasting a TC since in some regions TC tracks are more predictable than in others and individual TCs which take a straight-running track should be easier to forecast than those which take more complex tracks. In order to assess some of these forecast track characteristics a number of other measures of error are calculated Cross-track and along-track error The DPE can be visualized as the hypotenuse of a triangle whose other sides comprise the component of track error across the track and the component along the track. This is shown diagrammatically in Figure 5. The cross-track error (CTE) is the component of the error perpendicular to the observed track. It is calculated by extrapolating the line joining the observed position at the VT and the observed position 12 h earlier and identifying the point where this is intersected at right-angles by a line drawn from the forecast position at the VT. The great circle distance between the forecast position and this point of intersection is defined as the CTE. This value is deemed to be positive if the forecast position lies to the right (left) of the extrapolated observed track looking in the observed direction of motion of the TC in the northern (southern) hemisphere. Thus for a TC moving from east to west (i.e. not yet recurved), a positive CTE would indicate that the model had a polewards bias in its forecast track.

6 6 J. T. Heming The along-track error (ATE) is the component of the error along the observed track. It is calculated by extrapolating the line joining the observed position at the VT and the observed position 12 h earlier and identifying the point where this is intersected at right-angles by a line drawn from the forecast position at the VT (as for the calculation of CTE). However, the ATE value is the great circle distance between the observed position at the VT and this point of intersection. The ATE value is deemed to be positive if the point of intersection lies ahead of the observed position at the VT looking in the observed direction of motion. Thus a positive ATE would indicate that the model has a fast bias in its forecast track. Since CTE and ATE depend on the existence of an observed position 12 h prior to the VT, they cannot be calculated for the first analysed position of a TC Track skill score Statistical models exist which forecast the tracks of TCs up to 5 days ahead using methods based on past climatology in the area and persistence. These are known as CLIPER models and are generally accepted as a benchmark against which NWP models can be assessed (Neumann, 1972; Aberson, 1998). The CLIPER model is able to produce forecast positions at corresponding times to those produced by NWP models. Thus CLIPER DPE values can be calculated. If the NWP model DPE values are smaller, the NWP model is said to show skill over CLIPER. Track skill score is defined as a percentage value as shown in Equation (1): trackskill score = {(CLIPER DPE NWP model DPE) CLIPER DPE} 100% (1) Positive skill indicates that the NWP model forecast is better than CLIPER. Negative skill indicates that the CLIPER forecast is better than the NWP model. The version of CLIPER used requires knowledge of the observed position of a TC 12 and 24 h before the VT of the forecast being verified. Hence, CLIPER statistics cannot be calculated for the first 24 h of a TC s life Measures of intensity forecast error Whilst the verification of track forecasts can be achieved in a straightforward manner by identifying the centre of the TC using 850RV and MSLP, verification of TC intensity raises a number of challenges. As shown in Figure 1, global models in the past were unable to represent the true intensity of a mature TC, primarily owing to their relatively coarse horizontal resolution. Even now, with many global models having a horizontal grid spacing of 20 km or finer, model analyses or forecasts are often not able to represent the true near-surface wind speed or MSLP near the core of the TC. This is particularly the case for intense TCs with large pressure gradients near their centre or small TCs where the radius of hurricane force winds may only be of the order of one model grid length. Thus, whilst calculation of model errors in near-surface wind and MSLP is undertaken, it is supplemented by the calculation of intensity tendency which just evaluates the model s skill in predicting weakening or strengthening. As with the verification of forecast position the term observation is used to describe a best estimate of the TC s intensity given the data available. It is usual for TC warning centres to output wind speed as their primary metric of intensity with standard wind pressure relationships (e.g. Knaff and Zehr, 2007; Courtney and Knaff, 2009) used to ascertain a value of central pressure Intensity error Calculation of intensity error is undertaken for both central pressure and maximum wind speed. The value of lowest MSLP diagnosed in the model s analysis and forecast fields using the method described above is compared to the observed value of MSLP obtained from TC warning centres at the VT to calculate an error. For maximum wind speed, the model s 10 m wind field is examined and the highest value within a defined search radius (nominally set to 4 ) of the point of lowest MSLP is compared to the maximum sustained wind value obtained from TC warning centres. Verification of maximum sustained wind is problematical since the model 10 m wind field is not directly equivalent to the observed maximum sustained wind. Furthermore, different agencies use different averaging periods to define their values of observed maximum sustained wind. However, verification of wind speed in this way can provide a useful indication of long term trends in model accuracy if applied in a consistent way even if the actual values of error are subject to uncertainty. Once errors have been calculated for each individual forecast, mean absolute errors and biases can be calculated for all forecasts being verified. The mean absolute error gives an indication of the size of the error irrespective of its sign. The bias accounts for sign and indicates whether the model forecasts are on average too weak or too strong Intensity tendency skill score In addition to calculation of mean absolute errors and biases, NWP model predictions of intensity tendency can be calculated by examination of the change in central pressure in successive forecast time steps (usually 12 h apart) and comparing this with the change in observed central pressure as reported in observations. If the model predicted strengthening (weakening) between two successive time steps (e.g. between the 24 and 36 h forecast time steps) and the observations showed strengthening (weakening) over the same time period, then it is considered a hit. However, if the model s forecast tendency was opposite to that in the observations, it is considered a miss. For the purpose of comparison observed and forecast MSLP to the nearest whole hectopascal is used. Observed MSLP values are usually reported to the nearest whole hectopascal, although sometimes to the nearest 5 hpa. As a result of using integer values, it is possible that two successive forecasts or observations can have the same value. In such cases as this, the forecast is considered a hit. Having established the numbers of hits and misses, it is possible to calculate a hit rate and skill score relative to chance using Equations (2) and (3): hit rate (%) = 100 {hits (hits + misses)} (2) intensity tendency skill score (%) = (hit rate 50) 2 (3) On the basis of this formula, if the model scored 80 hits in 100 cases then its intensity tendency skill score (ITSS) would be 60% indicating that it scored 60% more hits than chance (which would score 50 hits out of 100). If the model scored just 40 hits in 100 cases (worse than chance) then its ITSS would be 20%. Thus if the ITSS is greater than zero the forecast is deemed to show some skill in forecasting intensity tendency. The ITSS can have any value from 100% to +100%.

7 Tropical cyclone tracking and verification in Met Office models 7 The intensity tendency hit rates can be split into cases where the TC was observed to be strengthening and those where the TC was observed to be weakening. Thus two separate scores of strengthening skill and weakening skill can also be calculated. This can provide a useful measure of whether the model has a systematic bias in either spinning up or spinning down TCs. For example, these skill measures were used to diagnose that an upgrade to the MOGM made in 2002 eliminated a weakening bias which had previously been present in the model (Heming and Greed, 2002) Cyclogenesis verification In real time the prediction of tropical cyclogenesis (the formation of TCs during the forecast) is made using the methodology described in Section 4.2. At present, objective verification of tropical cyclogenesis predictions from numerical models does not form part of the system being described here. However, in the past the Met Office has provided data from its global model for use in the evaluation of NWP model tropical cyclogenesis predictions (Chan and Kwok, 1999; Pasch et al., 2006). More recently the MOGM is included in ongoing comparisons of NWP model predictions of tropical cyclogenesis in the Atlantic and eastern North Pacific undertaken jointly at the University at Albany and Florida State University. The methodology used in this work involves classification of each model forecast TC as a hit, miss, false alarm, early genesis event or late genesis event. Full details are available in Halperin et al. (2013, 2016) Ensemble forecast verification Although the same method is used for tracking TCs in both the deterministic MOGM and the ensemble prediction system (MOGREPS-G), some verification measures described above are of limited use in ensemble predictions due to the probabilistic nature of the forecasts. A TC verification system specific to ensembles is under development and will include the use of measures such as relative operating characteristics, reliability and relative economic value diagrams (WMO, 2013). Full details of this system will be published in due course, but preliminary details are available in Titley and Stretton (2016) Met Office TC forecast verification products The Met Office uses many of the techniques described above to verify track and intensity for every long forecast from the MOGM (168 h forecasts produced every 12 h) for every TC globally. Seasonal summaries on forecast performance are published twice per year (for northern and southern hemispheres) and time series of forecast performance date back as far as All TC forecast verification results are regularly updated and are available via the Met Office website at tropicalcyclone. 4. Real-time TC forecast guidance: the current method The basic principles of tracking TCs in real time are the same as for forecast verification described in the previous section. However, the technique differs for the following reasons: the technique used for verification requires an observed position at the analysis time; this is not available in real time for TCs that form during the forecast; the technique used for verification requires an observed position corresponding to the first forecast time step; this is not available for any real-time forecasts. The differences in technique for tracking TCs in Met Office models in real time are described in this section. The technique is used for both the deterministic global model (MOGM) and the ensemble prediction system (MOGREPS-G) in the production of a variety of forecast products TCs that already exist at the analysis time TCs that exist at the time of the model analysis are identified by interrogation of bulletins issued by a wide variety of TC warning agencies around the globe. This includes bulletins issued for weak tropical disturbances in their formative stages of development. As long as the bulletin contains a positional fix and a maximum sustained wind it will be used. The observed positions of TCs in these bulletins are used as search centres for locating TCs in the model analysis. The same technique is used as described in Section 3.2. For the first forecast (typically a 6 h forecast) a search centre is derived by taking the observed position in the analysis and the recent movement vector as described in the TC bulletin from the TC warning agency. On a presumption that the observed recent movement continued for the following 6 h a search centre is derived for the 6 h forecast position. The centre of the TC in the model field is then derived using the same method as described in Section 3.3. For subsequent forecasts (12 h and beyond) the search centre is derived from an extrapolation of the forecast movement in the previous 6 h, in common with the method described in Section 3.3. As for TC verification there exists an option to prevent TCs being tracked polewards of a defined latitude. For the production of real-time guidance it may be appropriate to relax this threshold to allow TCs to be tracked beyond the point at which they would probably have become extra-tropical or post-tropical. This then allows the forecast centre receiving the guidance to use its own judgement as to when the transition has taken place TCs predicted to form during the forecast For TCs which are predicted to form during the forecast, a starting time and position needs to be identified for each unique TC so that the TC can be tracked using the same technique as used in verification. To achieve this, a method has been developed to identify TCs from model fields. First, the model s 850RV and MSLP fields are interrogated to determine if a potential TC exists. A number of criteria must be met to ensure only genuine TCs are identified. The first three criteria are similar to those used in TC forecast verification. The 850RV must be above a predetermined threshold. For detection of formation, this threshold is set to a higher value than in subsequent forecast time steps to prevent TCs being detected and then dropped in quick succession when the 850RV difference fluctuates close to the threshold value. The nearest point of lowest MSLP (within a 3 radius of a local 850RV maximum) must be below a predetermined threshold. A closed isobar check is applied in the same way as for TC forecast verification (also introduced in 2013). For detection of formation, the threshold of pressure difference between the TC centre and the closed isobar is set to a higher value than in subsequent forecast time steps to prevent TCs being detected

8 8 J. T. Heming and then dropped in quick succession when the pressure difference fluctuates close to the threshold value. The TC centre detected must be equatorwards of 37.5 latitude. This restriction allows detection of most circulations which are tropical in nature. The IBTrACS database of worldwide historical TC activity (Knapp et al., 2010) indicates that in the last 50 years (the approximate era of satellite coverage) only six TCs have ever formed polewards of this latitude. The TC centre must be over or very close to sea points in the model. The grid point closest to the potential TC centre and the eight adjacent model grid points are tested against the model s land sea mask. If four of these grid points are sea then a TC is detected. Otherwise it is considered that the development is over land and is not detected or tracked. The TC centre must be over sea with a model analysed sea surface temperature (SST) above a predetermined threshold. Some TC trackers include checks for the presence of a warm core, but this is not done in the Met Office system. As a safeguard to prevent low latitude winter storms from being detected an SST check is used. This threshold has a default value of 26.5 C but is varied regionally. For example, the threshold is 2 C lower in the North Atlantic due to the propensity for higher latitude tropical or subtropical storms to develop in this region over slightly cooler SSTs. If all these conditions are met a TC is considered to have been detected in the model forecast. This process is carried out independently for the model analysis and each forecast time step at 6 h intervals. At this stage each TC that meets these criteria will have been detected in multiple forecast time steps. The next stage in the process is to identify the earliest position for each unique TC and then run the tracker starting from this position. To achieve this TC positions at successive time steps (6 h apart) are compared with each other. If their positions are less than 5 of latitude or longitude from each other they are considered to relate to the same TC and the position at the later forecast time step is eliminated. This process is repeated for every pair of positions 6 h apart. At the end of the process just one position (the earliest) remains for each unique TC in the model forecast. Each of these unique positions is then used as a starting point for tracking the TC through the remainder of the forecast using the techniques previously described. 5. Summary The Met Office has run a tropical cyclone tracker since the 1990s which is able to undertake the dual functions of verifying the track and intensity forecasts of past numerical weather prediction (NWP) model forecasts (operational and development) and also producing forecast tracks and intensities in real time for current NWP model forecasts. The initial univariate (850 relative vorticity) version of the tracker was superseded in 2009 by a bivariate (850 relative vorticity and mean sea-level pressure) version. This underwent further development including the introduction of a closed isobar check such that by 2013 the tracker was robust enough to run in a totally automated way without human intervention and contains tuneable parameters which allow it to be used for both global model forecasts and higher resolution regional model forecasts. It is also used on both deterministic and ensemble prediction systems and is the foundation for the production of a variety of verification statistics and real-time forecast products. References Aberson SD Five-day tropical cyclone track forecasts in the North Atlantic Basin. Weather Forecasting 13: Bowler NE, Arribas A, Mylne KR, Robertson KB, Beare SE The MOGREPS short-range ensemble prediction system. Q. J. R. Meteorol. 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