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Bureau Research Report - 027

Case studies for fog at Melbourne Airport

Belinda Roux September 2017

CASE STUDIES FOR FOG AT MELBOURNE AIRPORT

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Case studies for fog at Melbourne Airport

Belinda Roux

Bureau Research Report No. 027

September 2017

National Library of Australia Cataloguing-in-Publication entry

Author: Belinda Roux Title: Case studies for fog at Melbourne Airport ISBN: XXX-X-XXX-XXXXX-X Series: Bureau Research Report – BRR027


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Enquiries should be addressed to: Belinda Roux: Bureau of Meteorology GPO Box 1289, Melbourne Victoria 3001, Australia [email protected]:

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The Bureau of Meteorology advise that the information contained in this publication comprises general

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or in whole) and any information or material contained in it.


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Contents

Executive Summary ...................................................................................................... 1

1. Introduction .......................................................................................................... 2

2. Region description and observations ............................................................... 2

3. NWP model setup ................................................................................................ 4

4. Case study: 2 June 2016 ..................................................................................... 6

5. Case study: 4 December 2015 .......................................................................... 16

6. Case study: 23 May 2015 .................................................................................. 22

7. Conclusions ....................................................................................................... 27

8. Acknowledgements ........................................................................................... 27

9. References ......................................................................................................... 27


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List of Figures

Figure 1: Map of topography (m) and AWS locations in the Melbourne region ...................................... 3

Figure 2: MSLP analysis over Australia for 2 June 2016 at 1800 UTC .................................................. 6

Figure 3: Observed vertical profiles of temperature, dewpoint temperature and winds for 11 UTC (top) and 23 UTC (bottom) at Melbourne airport ..................................................................... 7

Figure 4: Time series of observations from Melbourne airport AWS (YMML) for 2 June 2016............... 8

Figure 5: ACCESS-C2 time series at Melbourne Airport for 2 June 2016. The model base time is 0000 UTC, 2 June 2016. ........................................................................................................ 8

Figure 6: ACCESS-C2 model level wind fields over Melbourne for 11 UTC (left) and 21 UTC (right) at 13 m (bottom), 293 m (middle) and 900 m (top) above ground level for 2 June 2016. The shades are model topography in meters and the location of Melbourne airport is denoted with a red cross ..................................................................................................... 9

Figure 7: ACCESS-C2 north-south (top) and east-west (bottom) cross sections of wind (barbs), temperature (black contours) and vertical motion (orange contours up, green contours down) for 11 UTC (left) and 21 UTC (right). Melbourne airport is denoted with a red cross. ................................................................................................................................... 10

Figure 8: Time series of the ACCESS-1 (top) and ACCESS-C2 (bottom) vertical profile of relative humidity (shades), horizontal winds (barbs) and vertical winds in pa/s (red contours negative, blue contours positive) at Melbourne airport for 2 June 2016. ............................... 11

Figure 9: Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) temperature (red), dewpoint temperature (blue), visibility (orange) and winds (light green) against observations (dashed lines and dark green wind barbs) at Melbourne airport for 2 June 2016. .................................................................................................................................... 12

Figure 10: Himawari-8 night microphysics image (left) and LIFR probability (right) for 21 UTC 0n 2 June 2016. The position of Melbourne airport is indicated with a cross. ............................... 13

Figure 11: ACCESS-C1 (left) and C2 (right) visibility (shades, km) and fog fraction (contours) for 2100 UTC on 2 June 2016. Observations of visibility (in km) are plotted in dark green ........ 13

Figure 12: ACCESS-C1 (left) and C2 (right) dewpoint depression (shades) and 10 m winds (barbs) for 2100 UTC on 2 June 2016. Observations are plotted in dark green .................... 14

Figure 13: ACCESS-R2 (left) and R1 (right) visibility (shades, km) and fog fraction (contours) for 21 UTC on 2 June 2016. Observations of visibility (in km) are plotted in green .................... 14

Figure 14: Visibility and fog fraction (top) and DPD and winds (bottom) for ACCESS-C1 (left) and ACCESS-C2 (right) for 0100 UTC on 3 June 2016. Observations are plotted in green. ....... 15

Figure 15: MSLP analysis over Australia for 1800 UTC on 4 December 2015 ..................................... 16

Figure 16: Satellite products for 1800 UTC. On the left is the Himawari-8 night microphysics image, the middle shows the Geocat LIFR probabilities and on the right is the MTSAT-7 picture of fog and low cloud. ................................................................................................. 16

Figure 17: Time series of observations from Melbourne airport AWS (YMML) for 0100 UTC 4 December to 0300 UTC 5 December 2015 (1200 LST 4 Dec to 1400 LST 5 Dec). Sunrise is at 1851 UTC (0551 LST). ..................................................................................... 17

Figure 18: Observed vertical profiles of temperature, dewpoint temperature and winds for 11 UTC (top) and 23 UTC (bottom) at Melbourne airport ................................................................... 18

Figure 19: Visibility and fog fraction (top) and DPD and winds (bottom) for ACCESS-C1 (left) and ACCESS-C2 (right) for 1800 UTC on 4 December 2015. Observations are plotted in green. ................................................................................................................................... 19


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Figure 20: Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) temperature (red), dewpoint temperature (blue), visibility (orange) and winds (light green) against observations (dashed lines and dark green wind barbs) at Melbourne airport for 4 December 2015 (sunrise is at 1851 UTC). ........................................................................... 20

Figure 21:Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) vertical profile of relative humidity (shades), horizontal winds (barbs) and vertical winds in pa/s (red contours negative, blue contours positive) at Melbourne airport for 4 December 2015 (sunrise is at 1851 UTC). ..................................................................................................... 21

Figure 22: MSLP analysis over Australia for 1800 UTC on 23 May 2015 ............................................ 22

Figure 23: Time series of observed (top), ACCESS-C1 (middle) and ACCESS-C2 (bottom) variables at Melbourne Airport on 23 May 2015.Sunrise is at 2119 UTC, 23 May (0719 LST, 24 May). ....................................................................................................................... 23

Figure 24: Observed vertical profiles of temperature, dewpoint temperature and winds for 11 UTC (top) and 23 UTC (bottom) at Melbourne airport ................................................................... 24

Figure 25: Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) vertical profile of relative humidity (shades), horizontal winds (barbs) and vertical winds in pa/s (red contours negative, blue contours positive) at Melbourne airport for 23 May 2015 ................ 25

Figure 26: Satellite images for 1825 (left) and 2254 (right) over Victoria on 23 May 2015 ................... 26

Figure 27: Visibility and fog fraction (top) and DPD and winds (bottom) for ACCESS-C1 (left) and ACCESS-C2 (right) for 2300 UTC on 23 May 2015 (0900 LST, 24 May). Observations are plotted in green. ............................................................................................................. 26


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EXECUTIVE SUMMARY

Numerical modelling case studies of three fog events at Melbourne airport have been conducted to compare the soon to be operational ACCESS-City model (ACCESS-C2) with the current operational ACCESS-C1 and to investigate processes of fog formation at the airport.

The first fog event was 6 June 2016 where fog formed in a Melbourne eddy situation at 0600 LST and lasted for 2.5 hours. ACCESS-C2 simulated the mesoscale processes very well and gave a more realistic fog fraction around Melbourne than ACCESS-C1, in spite of the prediction of erroneous low visibilities in northern Victoria.

The second event was 4 December 2015, a less common summer fog which formed around 0430 LST and lasted two hours. Both models simulated the temperature and wind fields well but failed to simulate the sudden increase in dewpoint temperature with the onset of fog in the morning. ACCESS-C2 did not simulate fog at the airport but it did reduce the visibility to about 6 km.

The third fog event was 23 May 2015. Low cloud formed during the night which gradually lowered to fog at 0900 LST. The fog was reported for less than an hour but it is a fairly common scenario and significant to forecast as the time of fog coincides with the morning peak at Melbourne airport. The models did not forecast the low cloud lowering into fog at the airport but ACCESS-C2 did indicate a lowering to the ground of high relative humidity (>80 %) at the same time.

In general, ACCESS-C2 simulates the variables such as temperature, dewpoint temperature and wind better than ACCESS-C1, but the visibility and fog fraction in ACCESS-C2 might be erroneous due to the inappropriate use of the total aerosol variable. This emphasises the importance of investigating aerosols in the model in Australia, which may become even more important as the model resolution increases and the UK Met Office further integrates aerosols into model processes.

1. INTRODUCTION

Three case studies for fog at Melbourne airport during 2015 and 2016 are conducted. The aims of the case studies are twofold. The performance of the city scale numerical weather prediction (NWP) model in conditions favourable for fog formation is evaluated in detail and at the same time the processes of fog formation in Melbourne are investigated.

Melbourne airport has an average of 12.6 fog events per year (for the period 1972-2014 and visibility less than 1000 m), with a greater prevalence of fog in the colder months (April to September). One of the more common situations in which fog can form is the Melbourne eddy, also known as the Spillane eddy. This eddy forms in light easterly/north-easterly synoptic wind conditions where the Australian Alps to the north-east of Melbourne act as a barrier and cooler moist air is circulated from Port Phillip Bay to the airport (Spillane, 1978).

The case studies have been conducted using an experimental version of the soon to be operational city scale model (APS2 ACCESS-C) which hereafter will be referred to as ACCESS-C2. This city model was nested in the APS2 ACCESS-R (ACCESS-R2) model, which became operational in July 2016. Results are compared to output from the current city scale model (APS1 ACCESS-C), referred to here as ACCESS-C1. As all three case study dates were prior to July 2016, the operational city scale model was nested in APS1 ACCESS-R (ACCESS-R1). The base time for all model runs is 0000 UTC.

Section 2 gives a description of the region and observations used for verification, while section 3 provides an overview of the numerical weather prediction (NWP) modelling at the Bureau of Meteorology. The case studies are discussed in sections 4 to 6 with concluding remarks in section 7.

2. REGION DESCRIPTION AND OBSERVATIONS

A map of the topography of Melbourne and the surrounding area with locations of the Bureau's automatic weather stations (AWS) is given in


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Figure 1. Available AWS locations are indicated with black crosses and for reference the Melbourne airport (YMML), Kilmore Gap (KMG) and Laverton Airport (YLVT) weather stations are marked. The weather in Melbourne is influenced by Port Phillip Bay to the south and the mountain ranges to the north, especially in the lighter wind conditions associated with fog. To validate the model, 10 minute automatic weather station (AWS) observations of screen temperature (T), dewpoint temperature (Td), 10-m winds, mean sea level pressure (MSLP) and visibility (where available) together with the 30 minute ceilometer means of cloud heights and coverage are used. Note that the reported 10 minute visibility observations are capped at 10 km, so the maximum visibility will appear to be 10 km even though the actual visibility may be much higher. Other data used in the case studies include vertical profiles of temperature, dewpoint temperature and winds from balloon flights at Melbourne airport taken at 1100 UTC and 2300 UTC. In addition, the Bureau's national 6 hourly mean sea level pressure (MSLP) analysis over Australia and satellite imagery from the Multi-functional Transport Satellites (MTSAT) and its successor Himawari-8 are used when available.

Figure 1: Map of topography (m) and AWS locations in the Melbourne region

MTSAT are geostationary weather satellites operated by the Japan Meteorological Agency (JMA) and the Bureau received imagery from these satellites from 2005 to early 2016. Images highlighting fog and low cloud were developed by Weymouth (2006), using the brightness temperature difference of the infrared and near infrared channels from MTSAT (Barras & Miao, 2011; Boneh et al., 2015). In late 2015 images from Himawari-8, JMA's new geostationary satellite, became available. Himawari-8 has a higher spatial and temporal resolution as well as more channels than MTSAT. The night microphysics product combines multiple satellite channels to monitor the evolution of night-time fog and stratus. More detail on this product is

available from (Zeschke, 2015). The Geostationary Cloud Algorithm Testbed (Geocat) fog and low cloud (FLS) products (Calvert & Pavolonis, 2010) were produced using the Himawari-8 satellite data. In this work the Geocat FLS products that meet Low Instrument Flight Rules (LIFR) conditions are shown, which is the probability of the cloud ceiling below 500 ft and/or a visibility less than 1 mile (1.6 km).

3. NWP MODEL SETUP

The Bureau of Meteorology uses the Australian Community Climate and Earth-System Simulator (ACCESS) for its operational numerical weather prediction (NWP) modelling. The system is based on the Unified Model (UM) from the UK Met Office, and a four-dimensional variational data assimilation scheme (Bureau of Meteorology, 2010; Puri et al., 2013). The NWP model is coupled to the Joint UK Land Environment Simulator (JULES) land surface model (Best et al., 2011; D. B. Clark et al., 2011). JULES uses nine tiles to represent the land-use/coverage within each grid box, defined by five vegetation surface types and four non-vegetation types. The total surface flux for a grid box is computed by taking a weighted average of the fluxes of the surface types present in the grid box. The APS1 ACCESS NWP modelling suite at the Bureau of Meteorology consists of a global model (ACCESS-G) with a horizontal resolution of approximately 25 km, a regional model covering Australia and the surrounding oceans (ACCESS-R) with a ~12 km resolution and higher resolution (~4 km) city scale models (ACCESS-C) covering the major populated regions. Numerical weather prediction (NWP) models are continually being improved and the Bureau of Meteorology updates the operational suite every few years to stay up to date with the latest science and computational improvements. The global and regional models were updated from APS1 to APS2 in 2016 and the city scale models are currently being updated to APS2, increasing the horizontal resolution from 4 km to 1.5 km. The models run four times daily, at 0000 UTC (1000 EST), 0600 UTC (1600 EST), 1200 UTC (22 EST) and 1800 UTC (0400 EST) but only the 0000 UTC runs are considered in this work. Even though forecasters might not look at the visibility field itself, it is an important variable to investigate due to its direct relationship to fog fraction (which is generally considered by forecasters). Fog fraction is given as the fraction of the grid box which has a visibility below 1 km. The visibility calculation in the UM is a diagnostic process and uses screen temperature, specific humidity, pressure, liquid water mixing ratio and the dry aerosol mass mixing ratio (P. A. Clark et al., 2008; Claxton, 2013). In the UK, the Met Office has constructed a "MURK" field which serves as a proxy field for the total aerosols that can be used as the dry aerosol mass mixing ratio in the visibility scheme. MURK has been tailored for the UK and is constrained by the assimilation of visibility (Claxton, 2013). The advantage of the MURK field is that it can have surface sources, be mixed by turbulence and advected by dynamics, and it can be removed by precipitation. However, in Australia, visibility is not assimilated and the MURK field is not based on any real data. So after some investigations in 2014 it was decided that MURK should be turned off in the APS1 model suite. This resulted in a notional "climatological" value being used to represent the dry aerosol mass mixing ratio instead. In the APS1 suite, MURK was only used for the visibility calculations but in the APS2 suite MURK also sets the cloud droplet number for the cloud microphysics and has been turned back on. It is possible to change the code so that MURK is not used for the visibility calculations


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even if it is turned on in the rest of the model. This option would potentially change the diagnosed visibility without influencing the rest of the model output and work is currently underway to test this in collaboration with the scientists in the Bureau’s ACCESS team and from the UK Met Office.

4. CASE STUDY: 2 JUNE 2016

The first case study is of a significant fog event (with low cloud and mist) at Melbourne airport on 2 June 2016. Fog formed at 2000 UTC (0600 LST) and cleared 2.5 hours later around 2230 UTC (0830 LST). Figure 2 shows the mean sea level pressure (MSLP) analysis over Australia at 1800 UTC which was about two hours before onset. Melbourne was between a high pressure system to the south and weak trough to the north. This resulted in relatively calm winds throughout the night and into the morning.

Figure 2: MSLP analysis over Australia for 2 June 2016 at 1800 UTC

The observed vertical profiles of temperature, dewpoint temperature and winds up to the 500 hPa pressure level for 1100 UTC (2100 LST) and 2300 UTC (0900 LST) at Melbourne airport are given in Figure 3. At both times the air was very moist from the surface up to a subsidence inversion around the 950 hPa pressure level. The winds were fairly light in the lower levels and backed from north-westerly/south-westerly at the surface to east/north-easterly in the upper levels. A time series of the observations from the Melbourne airport AWS is given in Figure 4. The solid red and blue lines represent temperature (T) and dewpoint temperature (Td), respectively, and the 10 m wind is plotted as wind barbs in green. The brown solid line represents horizontal visibility (in km, on the left axis), while the orange dashes are for the cloud heights (in meters above ground level on the right axis). The orange numbers are for the total cloud coverage in octas and the grey dashed line is the MSLP in hPa minus 1000 (on the left axis). The solid vertical yellow lines show the times of sunset (~1700 LST) and sunrise (~0730 LST) and the dashed brown vertical lines show the event start and end times (the first and last times where the visibility was recorded below 1 km).


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Figure 3: Observed vertical profiles of temperature, dewpoint temperature and winds for 11 UTC (top) and 23 UTC (bottom) at Melbourne airport

Visibilities below 1000m (fog) were observed at the airport between 2000 UTC and 2230 UTC, with low cloud from 1030 UTC. Between 2100 and 2200 UTC the visibility improved slightly and an additional level of low cloud was observed. The 10 m winds veered from light southerly in the afternoon to north easterly before it calmed for several hours before the fog onset time. During the fog event light south-westerly winds were observed. Figure 5 shows a time series of the variables simulated by ACCESS-C2 at Melbourne airport similar to the observed time series in Figure 4. The only differences are that the simulated cloud information and visibility were only available at hourly intervals and the cloud heights (dashed orange line) are for the lowest cloud base only. In general the model simulates the variables well. The simulated south-westerly winds persisted for a few hours too long around sunset and the light south-westerly winds at the time of the fog were not simulated, but overall both the wind strength and direction were simulated very well. The simulated cloud height was also very good as was the dewpoint depression around sunrise. The model predicted a reduction in visibility for this event but the predicted visibility was generally too high with a minimum value of 3 km at the airport.

Figure 4: Time series of observations from Melbourne airport AWS (YMML) for 2 June 2016

Figure 5: ACCESS-C2 time series at Melbourne Airport for 2 June 2016. The model base time is 0000 UTC, 2 June 2016.

Figure 6 shows the ACCESS-C2 wind fields over the Melbourne region for three different model levels at 1100 UTC (left) and 2100 UTC (right). The surface winds were generally calm over the Melbourne area with light winds being influenced by topography in the surrounding areas. The higher level winds show more uniform easterly to north-easterly winds over the region at 1100 UTC, which tended south-eastely by 2100 UTC. In the lower levels the winds were blocked by the Australian Alps, as is observed during Melbourne eddy conditions.


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Figure 6: ACCESS-C2 model level wind fields over Melbourne for 11 UTC (left) and 21 UTC (right) at 13 m (bottom), 293 m (middle) and 900 m (top) above ground level for 2 June 2016. The shades are model topography in meters and the location of Melbourne airport is denoted with a red cross

The north-south and east-west cross sections through Melbourne airport for the same hours are given in Figure 7. The height (shown in meters on the vertical axis) of the topography increases steadily from the coast towards the mountains to the north of Melbourne. In the east-west direction the topography at the latitude of the airport is relatively flat. The model simulates a change in the lower level wind direction from eastely over Port Phillip bay to westerly over the land at 1100 UTC while the upper level winds remain easterly. By 2100 UTC the surface winds over the airport and surrounding areas have calmed and fog has formed.

Figure 7: ACCESS-C2 north-south (top) and east-west (bottom) cross sections of wind (barbs), temperature (black contours) and vertical motion (orange contours up, green contours down) for 11 UTC (left) and 21 UTC (right). Melbourne airport is denoted with a red cross.

The time series of the vertical structure of relative humidity (shades), horizontal winds (barbs) and vertical winds (dashed lines) at the airport are given in Figure 8 for ACCESS-C1 (top) and ACCESS-C2 (bottom). The coinciding time series of the screen level temperature, dewpoint temperature, visibility and 10 m winds (with observations for comparison) are given in Figure 9. The observations in the ACCESS-C1 image are plotted at hourly intervals as opposed to the 10 minute intervals in the ACCESS-C2 image, accounting for the slight difference in appearance. Both models show similar patterns in their circulation and moisture fields but ACCESS-C1 did not simulate the light northerly winds around 1200-1600 UTC and instead shows calm surface conditions after 1000 UTC for the remainder of the period. This coincides with the model's simulation of a higher relative humidity close to the surface at the airport, with a prolonged


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period of very low cloud and fog (from about 1000 UTC on 2 June to 0200 UTC on 3 June). ACCESS-C2 simulates low cloud and low visibilities which have more realistic variations over that period, even though it does not lower the horizontal visibility at the airport below 3 km.

Figure 8: Time series of the ACCESS-1 (top) and ACCESS-C2 (bottom) vertical profile of relative humidity (shades), horizontal winds (barbs) and vertical winds in pa/s (red contours negative, blue contours positive) at Melbourne airport for 2 June 2016.

Figure 9: Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) temperature (red), dewpoint temperature (blue), visibility (orange) and winds (light green) against observations (dashed lines and dark green wind barbs) at Melbourne airport for 2 June 2016.

Figure 10 shows the Himawari-8 night microphysics image (left) and the Geocat FLS-LIFR image (right) over the Victorian region for 2100 UTC on 2 June. The night microphysics picture shows the fog in the light greyish shades with some overlying cloud (darker shades). The low cloud over Melbourne persisted for most of the night. There were high LIFR probabilities (30%) over Kilmore Gap at 2100 UTC which propagated south (over the airport) and to the east in the subsequent hours.


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Figure 10: Himawari-8 night microphysics image (left) and LIFR probability (right) for 21 UTC 0n 2 June 2016. The position of Melbourne airport is indicated with a cross.

The ACCESS-C1 and ACCESS-C2 fog fraction and visibility in Victoria at 2100 UTC are given in Figure 11. Both models simulate fog around Melbourne and the broad pattern is consistent with the LIFR probabilities. ACCESS-C1 has lower visibilities in a larger area around Melbourne and the fog fraction and visibilities below 1 km in ACCESS-C2 show a better correspondence to the highest LIFR probabilities. In contrast to the situation over Melbourne, ACCESS-C2 simulates much lower visibilities than ACCESS-C1 in northern Victoria.

Figure 11: ACCESS-C1 (left) and C2 (right) visibility (shades, km) and fog fraction (contours) for 2100 UTC on 2 June 2016. Observations of visibility (in km) are plotted in dark green

Figure 12 shows the dew point depression (DPD) and 10 m wind from the two models at the same hour (2100 UTC). Although some of the low visibilities in ACCESS-C2 in northern Victoria can be attributed to the increase in moisture (lower DPD) in the model, the DPD is not low enough to explain the extent of the low visibilities. Both models show a similar wind direction and strength, but the DPD has more variability in ACCESS-C2 and seems to be closer to the observations overall, especially to the north.

Figure 12: ACCESS-C1 (left) and C2 (right) dewpoint depression (shades) and 10 m winds (barbs) for 2100 UTC on 2 June 2016. Observations are plotted in dark green

To investigate the difference in the visibility between ACCESS-C1 and ACCESS-C2 further, Figure 13 shows the visibility and fog fraction in ACCESS-R1 and ACCESS-R2 for 2100 UTC. The lower visibility in northern Victoria observed in ACCESS-C2 is visible in ACCESS-R2 as well. One possible explanation is that the use of MURK without proper assimilation in the APS2 systems could lead to a build-up of aerosols under certain atmospheric conditions, leading to lower simulated visibilities.

Figure 13: ACCESS-R2 (left) and R1 (right) visibility (shades, km) and fog fraction (contours) for 21 UTC on 2 June 2016. Observations of visibility (in km) are plotted in green

The low visibilities of ACCESS-C2 in northern Victoria persisted in the morning hours, even though the DPD increased. Figure 14 shows the variables for 0100 UTC on 3 June 2015. This supports the idea that the low visibilities in northern Victoria in ACCESS-C2 might be because of a build-up in MURK. The impact of not using the MURK field in ACCESS-C2 visibility parameterisation is being tested currently and will be reported elsewhere.


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Figure 14: Visibility and fog fraction (top) and DPD and winds (bottom) for ACCESS-C1 (left) and ACCESS-C2 (right) for 0100 UTC on 3 June 2016. Observations are plotted in green.

5. CASE STUDY: 4 DECEMBER 2015

The second case study is for a less common summer fog event on 4 December 2015. Fog formed around 1830 UTC on (0530 LST) and lasted two hours. Figure 15 shows the MSLP analysis over Australia at 1800 UTC on 4 December 2015. There was a high pressure system to the east of the country with a cold front passing south, and troughs over western and central Australia.

Figure 15: MSLP analysis over Australia for 1800 UTC on 4 December 2015

Satellite products from both Himawari-8 and MTSAT-7 were available for this case. Figure 16 shows the Himawari-8 image, Geocat LIFR probabilities and the MTSAT-7 fog and low status image for 1800 UTC on 4 December 2015. The area of fog over Melbourne was relatively localised and consistent between the images. By 1900 UTC fog was established over the airport but neither of the satellite products identified this due to some overlying cloud as well as the deterioration of the Geocat products around sunrise as a result of switching between night- and day-time algorithms.

Figure 16: Satellite products for 1800 UTC. On the left is the Himawari-8 night microphysics image, the middle shows the Geocat LIFR probabilities and on the right is the MTSAT-7 picture of fog and low cloud.


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A time series of the observations from the Melbourne airport AWS (YMML) is given in Figure 17. The 10-m winds were south-easterly during the day, turning westerly around sunset. During the daytime, the air was dry and warm but cooled and moistened considerably during the night. Shortly before sunrise there was a sudden increase in dewpoint temperature and fog formed (~1830 UTC). The temperature and visibility increased with a southerly wind shift at approximately 2100 UTC in the morning.

Figure 17: Time series of observations from Melbourne airport AWS (YMML) for 0100 UTC 4 December to 0300 UTC 5 December 2015 (1200 LST 4 Dec to 1400 LST 5 Dec). Sunrise is at 1851 UTC (0551 LST).

Figure 18 gives the vertical profiles of temperature, dewpoint temperature and wind for Melbourne airport at 1100 UTC and 2300 UTC. There were westerly winds above the 700 hPa pressure level at both 1100 UTC and 2300 UTC. At 1100 UTC the surface winds were south-westerly but it backed with height through the lower levels such that the 950-900 hPa levels had easterly winds with north-westerly winds around 800 hPa. At 2300 UTC the winds maintain a westerly component throughout the atmosphere at Melbourne airport and had north-westerly to northerly winds between the 1000 hPa and 900 hPa pressure levels.


The ACCESS-C1 and ACCESS-C2 visibility and fog images at 1800 UTC together with coinciding maps of the DPD and winds are given in Figure 19. The ACCESS-C2 visibility is below 10 km for much of Victoria although the fog fraction greater than zero is limited to a few isolated spots. In contrast to this, the ACCESS-C1 visibility is much higher overall, with areas of low visibilities (below 10 km) confined around the bay and coastal areas with fog fractions to match. The DPD is comparable between the models, and fits with the pattern of ACCESS-C1 visibility. This anomalously low visibility in ACCESS-C2 is similar to the first case study and is believed to be due to the use of the aerosol variable. This is currently under investigation and it is anticipated that this will be rectified in the operational ACCESS-C2 as soon as the visibility trials are completed in August 2017. The apparent disconnect between visibility and fog fraction in ACCESS-C2 supports the deduction that the low visibilities in northern Victoria are related to a build-up of aerosol due to the inappropriate use of MURK. In the calculation of fog fraction the actual water content in a grid box is compared to the water content that would result in a visibility of 1 km or less. If the atmosphere is dry the real water content will be very small compared to that required to give a 1 km visibility, essentially neglecting the contribution of dry aerosol to the visibility.


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Figure 19: Visibility and fog fraction (top) and DPD and winds (bottom) for ACCESS-C1 (left) and ACCESS-C2 (right) for 1800 UTC on 4 December 2015. Observations are plotted in green.

Figure 20 shows the time series of the observations together with the ACCESS-C1 and ACCESS-C2 temperature, dewpoint temperature, visibility and winds at Melbourne airport. ACCESS-C2 captured the diurnal range of the temperature and dewpoint temperature at the airport better, but neither model simulated the jump in dewpoint temperature at the fog onset and the subsequent saturation of the air during the event. ACCESS-C2 overestimated the temperature and dewpoint temperature during the night as well as the dewpoint temperatures in the late afternoon but captured the diurnal range and morning temperatures well. In ACCESS-C1 the diurnal trends seem to be offset by a few hours and the model has a reduction in the dewpoint temperatures in the morning which was not observed. ACCESS-C1 had a reduced visibility but not below 10 km and ACCESS-C2 reduced the visibility down to 6 km approximately 2-3 hours before the event. Both models had some low cloud around sunrise (not shown) and simulated the 10-m winds well, although ACCESS-C2 captured the variability of the wind better.

Figure 20: Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) temperature (red), dewpoint temperature (blue), visibility (orange) and winds (light green) against observations (dashed lines and dark green wind barbs) at Melbourne airport for 4 December 2015 (sunrise is at 1851 UTC).

The vertical time series at the airport of the winds, relative humidity (RH) and vertical motion for the two models are given in Figure 21. Note that the vertical resolution is the same for the two models, but the pressure level fields were output on more levels operationally, giving the erroneous impression of a higher vertical resolution in ACCESS-C1. Both models simulated similar winds and relative humidity, with a relatively dry atmosphere (RH<70%) apart from some low level moisture in the early morning hours. The models captured the winds backing with height around 1100 UTC as well as the northerly winds below 900 hPa and westerlies above that at 2300 UTC that was observed in Figure 18.


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Figure 21:Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) vertical profile of relative humidity (shades), horizontal winds (barbs) and vertical winds in pa/s (red contours negative, blue contours positive) at Melbourne airport for 4 December 2015 (sunrise is at 1851 UTC).

6. CASE STUDY: 23 MAY 2015

The third case study is for 23 May 2015. Low cloud formed during the night which gradually lowered to the ground. Fog was only observed for a short period around 2300 UTC (0900 LST) but it is a fairly common scenario at Melbourne Airport. Although this is a short event, it is significant because the time of fog coincides with the morning peak activity at Melbourne airport. Figure 22 shows the MSLP analysis for 1800 UTC on 23 May 2015 (0400 LST, 24 May). There was a strong high pressure system situated over Melbourne with a trough over Western Australia which was associated with a cold front to the south of the country.

Figure 22: MSLP analysis over Australia for 1800 UTC on 23 May 2015

Figure 23 gives the time series of observations from the Melbourne Airport AWS (YMML) and the simulated variables from the ACCESS-C1 and ACCESS-C2 models at the airport. The observed 10m winds at the airport were southerly in the afternoon, backing to westerly shortly after sunset with northerlies through the rest of the night. Low cloud developed around 1230 UTC, about an hour after the winds turned northerly and gradually lowered into fog at 2230 UTC. Both the visibility and clouds cleared by 0000 UTC, 24 May (1000LST, 24 May). Both models simulated the southerly winds in the afternoon and the northerly winds later in the night but neither captured the westerly winds shortly after sunset. The models simulated some low cloud in the afternoon and early evening but the low clouds in the models mostly cleared before the observed cloud lowered into fog at the airport. Overall, ACCESS-C2 simulates the temperatures and dewpoint temperatures in better agreement with the observations than ACCESS-C1. ACCESS-C2 also succeeded in lowering the visibility to below 10 km during the night.


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Figure 23: Time series of observed (top), ACCESS-C1 (middle) and ACCESS-C2 (bottom) variables at Melbourne Airport on 23 May 2015.Sunrise is at 2119 UTC, 23 May (0719 LST, 24 May).

Figure 24 gives the observed vertical profiles at 1100 UTC and 2300 UTC of the temperature, dewpoint temperature and winds at Melbourne airport. At 1100 UTC there was a surface inversion with a moist layer up to the 925 hPa pressure level where there is a well-defined subsidence inversion with dry air above. The winds were variable and light up to the 500 hPa pressure level. At 2300 UTC fog was observed with the inversion and drying just above the 1000hPa level and the winds were north-westerly through most of the atmosphere.


The time series of the vertical profiles of the relative humidity and winds from the models at the airport are given in Figure 25. Even though ACCESS-C2 did not simulate the low cloud lowering to the ground, the model simulated a mass of air containing RHs of at least 80% lowering to the ground in the early morning hours. The light winds at 1100 UTC and more north-westerly winds at 2300 UTC were captured by the model. The relative humidity of ACCESS-C1 was above 90% between the 950 hPa and 900 hPa levels for a longer period around sunset but lower relative humidity close to the ground in the early morning hours when the fog formed. ACCESS-C2 simulated some westerly winds after sunset (similar to the 10-m wind observations) at the 800 hPa pressure level, but the surface level winds were simulated to be south-easterly.


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Figure 25: Time series of the ACCESS-C1 (top) and ACCESS-C2 (bottom) vertical profile of relative humidity (shades), horizontal winds (barbs) and vertical winds in pa/s (red contours negative, blue contours positive) at Melbourne airport for 23 May 2015

Figure 26 gives the satellite images for 1825 UTC and 2254 UTC. At 1825 UTC low cloud with a height of about 500m above ground level was reported at Melbourne airport. Much of the fog and low cloud signal (blue colours) could be atttributed to this. At 2254 UTC (when fog was reported at the airport) the satellite image shows overlying cloud, which obscured the fog. Looking at the visibility, fog fraction, DPD and 10-m winds form the ACCESS-C1 and ACCESS-C2 models (Figure 27), it is clear that this case has the same problem with low visibility in northern Victoria as the other two cases described in this report. The DPD from ACCESS-C2 seems to be closer to the observations than ACCESS-C1. The winds from the two models are comparable, with ACCESS-C2 providing more detail due to its higher spatial resolution.

Figure 26: Satellite images for 1825 (left) and 2254 (right) over Victoria on 23 May 2015

Figure 27: Visibility and fog fraction (top) and DPD and winds (bottom) for ACCESS-C1 (left) and ACCESS-C2 (right) for 2300 UTC on 23 May 2015 (0900 LST, 24 May). Observations are plotted in green.


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7. CONCLUSIONS

Three case studies were conducted for fog events at Melbourne Airport. For the first case study (2 June 2016) ACCESS-C2 simulated the mesoscale processes very well and gave a more realistic fog fraction around Melbourne, in spite of erroneous low visibilities in northern Victoria. For the second case study (4 December 2015), ACCESS-C2 again simulated the mesoscale dynamics well but failed to simulate the sudden increase in dewpoint temperature with the onset of fog in the morning. Although the model did not simulate fog, it did reduce the visibility to about 6 km at the airport. In the third case study (23 May 2015), the models did not forecast the low cloud lowering into fog at the airport but ACCESS-C2 did indicate a lowering to the ground of high relative humidity (>80%) air at the same time. In all the cases the ACCESS-C2 visibility over north and central Victoria was much lower than ACCESS-C1 but at the same time ACCESS-C1 had more visibilities in the 0-1 km range and a larger area of fog fraction around Melbourne. The anomalously low ACCESS-C2 visibilities in northern Victoria seem to occur after sunset, which could be attributed to the inappropriate use of MURK in ACCESS-C2 through an unrealistically large build-up of aerosol as the boundary layer becomes shallow and stable after sunset. Trials are being conducted with changes to the visibility parameterisation so that it is not dependent on MURK, with the aim to implement the changes operationally with the successful conclusion of the trial. Although state variables such as temperature, dewpoint temperature and wind from ACCESS-C2 are in general better than ACCESS-C1, the visibility and fog fractions are not necessarily improved over the whole domain. Both visibility and fog fraction should be used with caution because this report has demonstrated that there are not automatic or guaranteed improvements in the accuracy of predictions of all fields following a model upgrade. Trials are currently being conducted with changes to the visibility parameterisation so that it is not dependent on MURK, with the aim to implement the changes operationally with the successful conclusion of the trial.

8. ACKNOWLEDGMENTS

I thank Peter Newham for suggesting case study dates and discussions on fog forecasting in Melbourne, Chris Lucas for providing the Himawari-8 and Geocat images and Richard Dare for feedback on the report. The interest and ongoing discussions with Ian Boutle and Adrian Lock from the UK Met Office regarding the model visibility investigations are also very much appreciated.

9. REFERENCES

Barras, V.J.I. and Miao, Y. (2011). GENESIS: forming an ACCESS-SCM testbed from NWP analyses. CAWCR Research Letters, (6), 11–15.

Best, M.J., Pryor, M., Clark, D.B., Rooney, G.G., Essery, R.L.H., Ménard, C.B. and Harding, R. J. (2011). The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes. Geoscientific Model Development, 4(3), 677–699. https://doi.org/10.5194/gmd-4-701-2011

Boneh, T., Weymouth, G.T., Newham, P., Potts, R., Bally, J., Nicholson, A.E. and Korb, K.B. (2015). Fog Forecasting for Melbourne Airport Using a Bayesian Decision Network. Weather and Forecasting, 30(5), 1218–1233. https://doi.org/10.1175/waf-d-15-0005.1

Bureau of Meteorology. (2010). Operational implementation of the ACCESS Numerical

Weather Prediction systems. Operations Bulletin, (83), 1–35. Retrieved from http://web.bom.gov.au/nmoc/stan/opsbull/apob83.pdf

Calvert, C. and Pavolonis, M. (2010). GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document For Low Cloud and Fog (v1.0). Retrieved from http://www.goes-r.gov/products/ATBDs/option2/Aviation_Fog_v1.0_no_color.pdf]om.gov.au/nmoc/stan/opsbull/apob83.pdf

Clark, D.B., Mercado, L.M., Sitch, S., Jones, C.D., Gedney, N., Best, M.J. and Cox, P.M. (2011). The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics. Geoscientific Model Development, 4(3), 701–722. https://doi.org/10.5194/gmd-4-701-2011

Clark, P.A., Harcourt, S.A., Macpherson, B., Mathison, C.T., Cusack, S. and Naylor, M. (2008). Prediction of visibility and aerosol within the operational Met Office Unified Model. I: Model formulation and variational assimilation. Quarterly Journal of the Royal Meteorological Society, 134, 1801–1816.

Claxton, B.M. (2013). Parameters controlling the aerosol hydration scheme within the UKV visibility parametrization. Met Office, Cardington Technical Note No. 85, (85), 1–35.

Puri, K., Dietachmayer, G., Steinle, P., Dix, M., Rikus, L., Logan, L. and Engel, C. (2013). Implementation of the initial ACCESS numerical weather prediction system. Australian Meteorological and Oceanographic Journal, 63(2), 265–284. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84874408763&partnerID=tZOtx3y1

Spillane, K. Atmospheric characteristics on high oxidant days in Melbourne, Clean Air § (1978). Retrieved from https://publications.csiro.au/rpr/pub?list=BRO&pid=procite:fbcdd70c-0a60-4bc9-90c2-948591f0aecf

Weymouth, G.T. (2006). Fog and low cloud imagery from satellite. Asia–Pacific Satellite Applications Training Seminar. Melbourne.

Zeschke, B. (2015). The Night Microphysics RGB product, Australian Vlab Centre of Excellence National Himawari-8 Training Campaign resource. Melbourne. Retrieved from http://www.virtuallab.bom.gov.au/files/8314/4100/7579/NightMicrophysicsRGBTOTALoneslide_Compatibility_Mode.pdf

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