The role of topography on the local circulation and formation of fog at Perth Airport

Bush M., Boutle I., Edwards J., Finnenkoetter A., Franklin C., Hanley K., Jayakumar A., Lewis H., Lock A., Mittermaier M., Mohandas S., North R., Porson A., Roux B., Webster S., et. al.

Abstract. In this paper we define RAL2 – the second Regional Atmosphere and Land (RAL) science configuration for regional modelling. RAL2 uses the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL2 defines the science configuration of the dynamics and physics schemes of the atmosphere and land and builds on the baseline of RAL1. There are two RAL2 sub-releases, one for mid-latitudes (RAL2-M) and one for tropical regions (RAL2-T). We document the differences between them and where appropriate discuss how RAL2 relates to RAL1 and the corresponding configuration of the global forecasting model. Our results show an increase in medium and low cloud amounts in the mid-latitudes leading to improved cloud forecasts. The increase in cloud amount leads to a reduced diurnal cycle of screen temperature. There is also a reduction in the frequency of heavier precipitation rates. RAL2 is expected to be the last RAL science configuration with two sub-releases as research effort is focused on producing a single defined configuration of the model that performs effectively in all regions of the world.

Field P.R., Hill A., Shipway B., Furtado K., Wilkinson J., Miltenberger A., Gordon H., Grosvenor D.P., Stevens R., Van Weverberg K.

Roux B., Potts R., Siems S., Manton M.

• A comprehensive climatology of fog events at Perth Airport was developed. • On average Perth Airport gets fog events per year, mainly in the cool season. • Fog often forms when the moist environmental westerlies and surface flow decouples. A comprehensive climatology of fog events at Perth Airport was developed with the aim of improving the forecasting of fog through an enhanced understanding of its nature. From 2002 to 2019 (inclusive) the airport experienced 8.9 ± 3.0 fog events per year with 96% of all events occurring in the cool season (from April to October inclusive). The fog events were ordered into different fog types, following a hierarchical classification method. Radiation fog were found to be the most prevalent in this region. A k-means clustering method was applied to 2300 UTC (0700 LST) observations at Perth Airport to divide the dataset into 5 different weather regimes. The majority of fog events occurred in a post-frontal/trough system with a high-pressure system to the west, bringing in moisture from the Indian Ocean. Perth Airport is located on a coastal plain with an escarpment 10 km to the east of the airport, roughly parallel to the coast and rising to about 300 m. In the 2002–2019 cool season period, 41% of fog events had northerly to easterly 10 m winds at 2300 UTC (0700 LST) while the 925 hPa winds were southerly to westerly. This compares with 15% of days with north to east winds at 10 m across all cool season days in the same period. These results support the current theory that fog often forms when nocturnal cooling on the coastal plain leads to increased stability in the near surface layer and a decoupling between the moist environmental westerlies and the surface flow at Perth airport. This allows the development of local circulations forced by the local topography.

Su C., Eizenberg N., Jakob D., Fox-Hughes P., Steinle P., White C.J., Franklin C.

Abstract. Regional reanalyses provide a dynamically consistent recreation of past weather observations at scales useful for local-scale environmental applications. The development of convection-permitting models (CPMs) in numerical weather prediction has facilitated the creation of kilometre-scale (1–4 km) regional reanalysis and climate projections. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) also aims to realize the benefits of these high-resolution models over Australian sub-regions for applications such as fire danger research by nesting them in BARRA's 12 km regional reanalysis (BARRA-R). Four midlatitude sub-regions are centred on Perth in Western Australia, Adelaide in South Australia, Sydney in New South Wales (NSW), and Tasmania. The resulting 29-year 1.5 km downscaled reanalyses (BARRA-C) are assessed for their added skill over BARRA-R and global reanalyses for near-surface parameters (temperature, wind, and precipitation) at observation locations and against independent 5 km gridded analyses. BARRA-C demonstrates better agreement with point observations for temperature and wind, particularly in topographically complex regions and coastal regions. BARRA-C also improves upon BARRA-R in terms of the intensity and timing of precipitation during the thunderstorm seasons in NSW and spatial patterns of sub-daily rain fields during storm events. BARRA-C reflects known issues of CPMs: overestimation of heavy rain rates and rain cells, as well as underestimation of light rain occurrence. As a hindcast-only system, BARRA-C largely inherits the domain-averaged bias pattern from BARRA-R but does produce different climatological extremes for temperature and precipitation. An added-value analysis of temperature and precipitation extremes shows that BARRA-C provides additional skill over BARRA-R when compared to gridded observations. The spatial patterns of BARRA-C warm temperature extremes and wet precipitation extremes are more highly correlated with observations. BARRA-C adds value in the representation of the spatial pattern of cold extremes over coastal regions but remains biased in terms of magnitude.

Cuxart J., Telisman Prtenjak M., Matjacic B.

Under high-pressure systems, the nocturnal atmospheric boundary layer in the Pannonian Basin is influenced by gravity flows generated at the mountain ranges and along the valleys, determining the variability of wind and temperature at a local scale and the presence of fog. The mechanisms at the mountain foothills are explored at Zagreb Airport using data from a sodar and high-resolution WRF-ARW numerical simulations, allowing identification of how the downslope flows from the nearby Medvednica mountain range condition the temperature inversion and the visibility at night and early morning. These flows may progress tens of kilometres away from the mountain ranges, merging with valley flows and converging in the central areas of the basin. The ECMWF model outputs allow us to explore the mesoscale structures generated in form of low-level jets, how they interact when they meet, and what is the effect of the synoptic pressure field over eastern Europe, to illustrate the formation of a basin-wide cold air pool and the generation of fog in winter.

Van Weverberg K., Morcrette C.J., Boutle I., Furtado K., Field P.R.

AbstractCloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional midlatitude forecasts, the Met Office uses a diagnostic cloud fraction scheme that relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. For model grid boxes located in this entrainment zone, collocated moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given gridbox mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the southern Great Plains in the United States, it is shown that the new scheme improves the relation between cloud fraction, relative humidity, and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in Part II.

Van Weverberg K., Morcrette C.J., Boutle I.

AbstractA wide range of approaches exists to account for subgrid cloud variability in regional simulations of the atmosphere. This paper addresses the following questions: 1) Is there still benefit in representing subgrid variability of cloud in convection-permitting simulations? 2) What is the sensitivity to the cloud fraction parameterization complexity? 3) Are current cloud fraction parameterizations scale-aware across convection-permitting resolutions? These questions are addressed for regional simulations of a 6-week observation campaign in the U.S. southern Great Plains. Particular attention is given to a new diagnostic cloud fraction scheme with a bimodal subgrid saturation-departure PDF, described in Part I. The model evaluation is performed using ground-based remote sensing synergies, satellite-based retrievals, and surface observations. It is shown that not using a cloud fraction parameterization results in underestimated cloud frequency and water content, even for stratocumulus. The use of a cloud fraction parameterization does not guarantee improved cloud property simulations, however. Diagnostic and prognostic cloud schemes with a symmetric subgrid saturation-departure PDF underestimate cloud fraction and cloud optical thickness, and hence overestimate surface shortwave radiation. These schemes require empirical bias-correction techniques to improve the cloud cover. The new cloud fraction parameterization, introduced in Part I, improves cloud cover, liquid water content, cloud-base height, optical thickness, and surface radiation compared to schemes reliant on a symmetric PDF. Furthermore, cloud parameterizations using turbulence-based, rather than prescribed constant subgrid variances, are shown to be more scale-aware across convection-permitting resolutions.

Fernando H.J., Gultepe I., Dorman C., Pardyjak E., Wang Q., Hoch S.W., Richter D., Creegan E., Gaberšek S., Bullock T., Hocut C., Chang R., Alappattu D., Dimitrova R., Flagg D., et. al.

AbstractC-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

Hertwig D., Grimmond S., Hendry M.A., Saunders B., Wang Z., Jeoffrion M., Vidale P.L., McGuire P.C., Bohnenstengel S.I., Ward H.C., Kotthaus S.

Two urban schemes within the Joint UK Land Environment Simulator (JULES) are evaluated offline against multi-year flux observations in the densely built-up city centre of London and in suburban Swindon (UK): (i) the 1-tile slab model, used in climate simulations; (ii) the 2-tile canopy model MORUSES (Met Office–Reading Urban Surface Exchange Scheme), used for numerical weather prediction over the UK. Offline, both models perform better at the suburban site, where differences between the urban schemes are less pronounced due to larger vegetation fractions. At both sites, the outgoing short- and longwave radiation is more accurately represented than the turbulent heat fluxes. The seasonal variations of model skill are large in London, where the sensible heat flux in autumn and winter is strongly under-predicted if the large city centre magnitudes of anthropogenic heat emissions are not represented. The delayed timing of the sensible heat flux in the 1-tile model in London results in large negative bias in the morning. The partitioning of the urban surface into canyon and roof in MORUSES improves this as the roof tile is modelled with a very low thermal inertia, but phase and amplitude of the grid box-averaged flux critically depend on accurate knowledge of the plan-area fractions of streets and buildings. Not representing non-urban land cover (e.g. vegetation, inland water) in London results in severely under-predicted latent heat fluxes. Control runs demonstrate that the skill of both models can be greatly improved by providing accurate land cover and morphology information and using representative anthropogenic heat emissions, which is essential if the model output is intended to inform integrated urban services.

Bush M., Allen T., Bain C., Boutle I., Edwards J., Finnenkoetter A., Franklin C., Hanley K., Lean H., Lock A., Manners J., Mittermaier M., Morcrette C., North R., Petch J., et. al.

Abstract. In this paper we define the first Regional Atmosphere and Land (RAL) science configuration for kilometre-scale modelling using the Unified Model (UM) as the basis for the atmosphere and the Joint UK Land Environment Simulator (JULES) for the land. RAL1 defines the science configuration of the dynamics and physics schemes of the atmosphere and land. This configuration will provide a model baseline for any future weather or climate model developments to be described against, and it is the intention that from this point forward significant changes to the system will be documented in the literature. This reproduces the process used for global configurations of the UM, which was first documented as a science configuration in 2011. While it is our goal to have a single defined configuration of the model that performs effectively in all regions, this has not yet been possible. Currently we define two sub-releases, one for mid-latitudes (RAL1-M) and one for tropical regions (RAL1-T). The differences between RAL1-M and RAL1-T are documented, and where appropriate we define how the model configuration relates to the corresponding configuration of the global forecasting model.

Su C., Eizenberg N., Steinle P., Jakob D., Fox-Hughes P., White C.J., Rennie S., Franklin C., Dharssi I., Zhu H.

Abstract. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12 km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2 m temperature, 10 m wind speed, and surface pressure observations. It also shows reduced biases in daily 2 m temperature maximum and minimum at 5 km resolution and a higher frequency of very heavy precipitation days at 5 and 25 km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10 m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (<2 km) models.

Hang C., Nadeau D.F., Gultepe I., Hoch S.W., Román-Cascón C., Pryor K., Fernando H.J., Creegan E.D., Leo L.S., Silver Z., Pardyjak E.R.

We present a valley fog case study in which radiation fog is modulated by topographic effects using data obtained from a field campaign conducted in Heber Valley, Utah from January 7–February 1, 2015, as part of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. We use data collected on January 9, 2015 to gain insight into relationships between typical shallow radiation fog, turbulence, and gravity waves associated with the surrounding topography. A ≈ 10–30 m fog layer formed by radiative cooling was observed from 0720 to 0900 MST under cold air temperatures (≈−9 °C), near-saturated (relative humidity with respect to water ≈95 %), and calm wind (mostly <0.5 m s−1) conditions. Drainage flows were observed occasionally prior to fog formation, which modulated heat exchanges between air masses through the action of internal gravity waves and cold-air pool sloshing. The fog appeared to be triggered by cold-air advection from the south (≈200°) at 0700 MST. Quasi-periodic oscillations were observed before and during the fog event with a time period of about 15 min. These oscillations were detected in surface pressure, temperature, sensible heat flux, incoming longwave radiation, and turbulent kinetic energy measurements. We hypothesize that the quasi-periodic oscillations were caused by atmospheric gravity waves with a time period of about 10–20 min based on wavelet analysis. During the fog event, internal gravity waves led to about 1 °C fluctuations in air temperatures. After 0835 MST when net radiation became positive, fog started to dissipate due to the surface heating and heat absorption by the fog particles. Overall, this case study provides a concrete example of how fog evolution is modulated by very weak thermal circulations in mountainous terrain and illustrates the need for high density vertical and horizontal measurements to ensure that the highly spatially varying physics in complex terrain are sufficient for hypothesis testing.

BESSHO K., DATE K., HAYASHI M., IKEDA A., IMAI T., INOUE H., KUMAGAI Y., MIYAKAWA T., MURATA H., OHNO T., OKUYAMA A., OYAMA R., SASAKI Y., SHIMAZU Y., SHIMOJI K., et. al.

Himawari-8/9 –a new generation of Japanese geostationary meteorological satellites–carry state-of-the-art optical sensors with significantly higher radiometric, spectral, and spatial resolution than those previously available in the geostationary orbit. They have 16 observation bands, and their spatial resolution is 0.5 or 1 km for visible and near-infrared bands and 2 km for infrared bands. These advantages, when combined with shortened revisit times (around 10 min for Full Disk and 2.5 min for sectored regions), provide new levels of capacity for the identification and tracking of rapidly changing weather phenomena and for the derivation of quantitative products. For example, fundamental cloud product is retrieved from observation data of Himawari-8 operationally. Based on the fundamental cloud product, Clear Sky Radiance and Atmospheric Motion Vector are processed for numerical weather prediction, and volcanic ash product and Aeolian dust product are created for disaster watching and environmental monitoring. Imageries from the satellites are distributed and disseminated to users via multiple paths, including Internet cloud services and communication satellite services.

Bari D., Bergot T., El Khlifi M.

Lock A.P., Eyre J.E., Boutle I.A.

Abstract A pragmatic approach for representing partially resolved turbulence in numerical weather prediction models is introduced and tested. The method blends a conventional boundary layer parameterization, suitable for large grid lengths, with a subgrid turbulence scheme suitable for large-eddy simulation. The key parameter for blending the schemes is the ratio of grid length to boundary layer depth. The new parameterization is combined with a scale-aware microphysical parameterization and tested on a case study forecast of stratocumulus evolution. Simulations at a range of model grid lengths between 1 km and 100 m are compared to aircraft observations. The improved microphysical representation removes the correlation between precipitation rate and model grid length, while the new turbulence parameterization improves the transition from unresolved to resolved turbulence as grid length is reduced.

Tian M., Wen Y., Meng L., Zhang Y., Liu S., Guo Y.