Development of Temperature Patterns during Clear Nights

Gustavsson, Torbjörn; Karlsson, Maria; Bogren, Jörgen; Lindqvist, Sven

doi:10.1175/1520-0450(1998)037<0559:dotpdc>2.0.co;2

Cited by 101 publications

(129 citation statements)

References 21 publications

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“…The formation of cold pools depends on the terrain and land use and the problem has been approached using a number of different forecasting strategies (e.g. Gustavsson et al, 1998;Blennow and Persson, 1998;Eriksson and Norrman, 2001;Jarvis and Stuart, 2001;Chung et al, 2006;Lundquist et al, 2008). Commonly cited causes are (1) topographic sheltering, reducing turbulent mixing-down of warmer air to the surface and (2) drainage flows which katabatically feed cold air from elevated surface locations to lower lying areas.…”

Section: Discussionmentioning

confidence: 99%

“…Temperature varies with height due to the background airmass lapse rate and, in addition, temperatures may be further depressed in valleys due to the formation of cold air pools (see e.g. Thompson, 1986;Neff and King, 1989;Gustavsson et al, 1998;Mahrt et al, 2001;Clements et al, 2003;Vosper and Brown, 2008). These factors depend on the prevailing weather conditions and have implications for road safety since they govern the risk of frost and fog formation in cold hollows.…”

Section: Introductionmentioning

confidence: 99%

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A simple height-based correction for temperature downscaling in complex terrain

et al. 2010

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ABSTRACT:A new downscaling method has been developed to improve forecasts of near-surface temperature. This involves applying a correction to forecast temperatures to account for the difference in height between the terrain in the forecast model and the real terrain, using an estimate of the lapse rate of temperature. The strongest variations in lapse rate are found to occur overnight, being a function of cloud cover and geostrophic wind speed. These variables similarly influence the night time lapse rate in the UK Met Office Unified Model forecast at 4 km resolution. Therefore, a simple algorithm has been employed to estimate the lapse rate at a given location, based on forecast model temperature and elevation fields. The algorithm has a positive impact on performance in stable conditions, compared to assuming an adiabatic lapse rate at all times.  Crown

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A simple height-based correction for temperature downscaling in complex terrain

et al. 2010

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“…However, Cerdanya's main characteristics are sharp temperature inversion events (Pepin and Kidd, 2006) in winter, when high pressures and stability are settled over southwest Europe and cold air pools (CAPs) are likely to be formed. Several studies, for instance Gustavsson et al (1998), Iijima and Shinoda (2000), Clements et al (2003), mentioned this valley phenomenon, which also forms in other countries and continents. Although temperature inversions occur in Val d'Aran these are not as frequent and strong as in Cerdanya under the same synoptic situation.…”

Section: Locationmentioning

confidence: 94%

Determining temperature lapse rates over mountain slopes using vertically weighted regression: a case study from the Pyrenees

Pagès

Miró

2009

Meteorological Applications

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This study took place in the Pyrenees Range, in the northeastern Iberian Peninsula. The Pyrenees extend longitudinally, separating the Iberian Peninsula from the rest of Europe, and high peaks around 3000 m arise from deep valleys. As a mountain range it creates a barrier to advection, in this case from the north and south, and typical meteorological phenomena of mountainous areas occur within it (inversions, Foehn effect, extreme wind-chill, snow storms). Thus, two specific valleys in Catalonia were considered, Val d'Aran and Cerdanya. In both valleys automatic weather stations (AWSs) are available at similar heights. Although these valleys are only 100 km apart, they have different climates. However, the main reason for developing the study was that Numerical Weather Prediction (NWP) has problems when forecasting temperatures in complex terrain areas, mainly in the valley floor in winter season.Firstly, different equations based on a multilinear regression were obtained for each weather station. Multilinear regression was considered in this case as the most suitable downscaling method and data used were provided by the AWSs and MM5 (PSU/NCAR mesoscale model) numerical weather prediction model outputs.These equations were obtained to set up a Geographically Weighted Regression (GWR) method, although this one was modified and changed to a Vertically Weighted Regression (VWR) in order to create vertical temperature profiles.

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“…The locations have to be examined more carefully so that they can be located at similar places to obtain a more reliable comparison between them. Studies have been conducted during clear, calm nights on road stretches where temperatures were measured and compared (for example, Gustavsson et al, 1998;Karlsson, 2000) in order to examine the temperature differences between forests and adjacent open areas.…”

Section: Discussionmentioning

confidence: 99%

Geographical distribution of road slipperiness in Sweden, on national, regional and county scales

Andersson

Gustavsson

Bogren

et al. 2007

Meteorological Applications

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ABSTRACT:The influence of latitude on the distribution of slipperiness of roads in Sweden was studied at three scales: national, regional and county. Data from 654 Road Weather Information System (RWIS) stations were compiled over five winter seasons, from 1998/1999 to 2002/2003. The aim of the study was to establish a basis on which to model how future climate changes might affect frequency of slipperiness and costs for maintenance in winter. Four types of slipperiness were studied (slippery conditions due to moderate (HR1) or severe (HR2) hoarfrost, moist/wet surface that freezes (HT), and rain or sleet falling on a cold road (HN)), all adding up to form the winter index (WI).In Sweden, the distribution of slipperiness varies depending on the scale (national, regional or county). On the national and regional scales the mean temperatures give a general picture of the total slipperiness -i.e. dependence on latitude; different factors were tested and latitude proved to be the most correlated. Slipperiness caused by HR1 and HR2 hoarfrost tends to increase towards the north, while road icing (HT) decreases. On the county scale, neither latitude nor any other tested geographical variable, could explain much of the variance. Local climate and the directions of movement of individual weather systems may be more important. The regional scale is considered to be most suitable for future modelling of the influence of the effect of a changed climate on the slipperiness of the roads.

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Development of Temperature Patterns during Clear Nights

Cited by 101 publications

References 21 publications

A simple height-based correction for temperature downscaling in complex terrain

A simple height-based correction for temperature downscaling in complex terrain

Determining temperature lapse rates over mountain slopes using vertically weighted regression: a case study from the Pyrenees

Geographical distribution of road slipperiness in Sweden, on national, regional and county scales

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