title: Nowcasting daily minimum air and grass temperature.
abstract: Site-specific and accurate prediction of daily minimum air and grass temperatures, made available online several hours before their occurrence, would be of significant benefit to several economic sectors and for planning human activities. Site-specific and reasonably accurate nowcasts of daily minimum temperature several hours before its occurrence, using measured sub-hourly temperatures hours earlier in the morning as model inputs, was investigated. Various temperature models were tested for their ability to accurately nowcast daily minimum temperatures 2 or 4 h before sunrise. Temperature datasets used for the model nowcasts included sub-hourly grass and grass-surface (infrared) temperatures from one location in South Africa and air temperature from four subtropical sites varying in altitude (USA and South Africa) and from one site in central sub-Saharan Africa. Nowcast models used employed either exponential or square root functions to describe the rate of nighttime temperature decrease but inverted so as to determine the minimum temperature. The models were also applied in near real-time using an open web-based system to display the nowcasts. Extrapolation algorithms for the site-specific nowcasts were also implemented in a datalogger in an innovative and mathematically consistent manner. Comparison of model 1 (exponential) nowcasts vs measured daily minima air temperatures yielded root mean square errors (RMSEs) <1 °C for the 2-h ahead nowcasts. Model 2 (also exponential), for which a constant model coefficient (b = 2.2) was used, was usually slightly less accurate but still with RMSEs <1 °C. Use of model 3 (square root) yielded increased RMSEs for the 2-h ahead comparisons between nowcasted and measured daily minima air temperature, increasing to 1.4 °C for some sites. For all sites for all models, the comparisons for the 4-h ahead air temperature nowcasts generally yielded increased RMSEs, <2.1 °C. Comparisons for all model nowcasts of the daily grass and grass-surface minima yielded increased RMSEs compared to those for air temperature at 2 m. The sufficiently small RMSEs using the 2-h ahead nowcasts of the air temperature minimum, for the exponential model, demonstrate that the methodology used may be applied operationally but with increased errors for grass minimum temperature and the 4-h nowcasts.
authors.affiliation: Agrometeorology Discipline, Soil-Plant-Atmosphere Continuum Research Unit, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa. savage@ukzn.ac.za.
authors.forename: M J
authors.initials: MJ
authors.lastname: Savage
mesh_terms: D005431:Florida; D008962:Models, Theoretical; D006109:Poaceae; D013019:South Africa; D013696:Temperature
keywords: Diurnal temperature modelling; Early warning of minimum temperature; Frost; Sub-hourly temperatures; Surface temperature