Impact of different surface temperature perturbation schemes on the simulation of nocturnal temperature inversions in ensemble modeling

A nocturnal surface-based temperature inversion refers to a phenomenon where air temperature increases with height. Such inversions are of interest because they play a significant role in enhancing the risk of frost events during the autumn–spring period and in the accumulation of air pollutants near the surface, with potential adverse impacts on human health. 

The key conditions for nocturnal inversion formation are: the absence of cloud cover, which enhances radiative cooling, and weak winds or calm conditions, which minimize vertical air mixing and thus intensify near-surface cooling. Based on these criteria, we analyzed meteorological observation data for the period 2011–2025 and selected nights when the average cloud cover over Poland did not exceed 0.5 oktas and wind speed remained below 3 m/s. An additional requirement was sunset before 18 UTC (the forecast initialization time) to exclude the influence of incoming solar radiation. For the selected cases, we chose stations where cloud cover remained at 0 oktas and wind speed did not exceed 3 m/s throughout the modeling period. 

For the modeling, we used the COSMO-2k8 ensemble prediction system with perturbations applied to the surface level soil temperature (T_SO) along with a separate deterministic run.  

At the first stage, the 20 ensemble members were split into two groups: group 1 with perturbations in initial conditions only and group 2 with perturbations in both initial and boundary conditions. 

In the near-surface layer, most cases show significant deviations between the modeled and observed temperature profiles, both positive and negative. For almost all simulated events, a characteristic feature is the rapid decrease in the amplitude of surface temperature among ensemble members. As a result, the amplitude of air temperature at 2 m and higher levels also decreases. 

At the second stage, a new approach to introducing perturbations into the T_SO was implemented. A new 40-member ensemble with different methods of initialization of perturbations was generated to hold the spread level during the model forecast. The members were divided into four groups of 10: 

• group 1: perturbations applied only to the initial conditions, with temperature deviations of ±0.5 and ±1.0 K and noise amplitude of 1–2 K during the first two time steps. 

• group 2: perturbations applied to both the initial and boundary conditions, with gradual accumulation of shift and amplitudes from 0.05 to 1.0 K; due to the simulation time step, the maximum amplitude over 12 h reaches ±0.3 K. 

• group 3: perturbations up to ±1.0 K, accumulated during the first ~100 minutes (240 steps). 

• group 4: perturbations up to ±1.0 K, accumulated rapidly during the first ~17 minutes (40 steps). 

The new perturbation scheme demonstrated not only the preservation of spread among individual ensemble members, but also its propagation up to a height of about 900 hPa.