Abstract
AbstractThe Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer Program (ISOBAR) is a research project investigating stable atmospheric boundary layer (SBL) processes, whose representation still poses significant challenges in state-of-the-art numerical weather prediction (NWP) models. In ISOBAR ground-based flux and profile observations are combined with boundary layer remote sensing methods and the extensive usage of different unmanned aircraft systems (UAS). During February 2017 and 2018 we carried out two major field campaigns over the sea ice of the northern Baltic Sea, close to the Finnish island of Hailuoto at 65°N. In total 14 intensive observational periods (IOPs) resulted in extensive SBL datasets with unprecedented spatiotemporal resolution, which will form the basis for various numerical modeling experiments. First results from the campaigns indicate numerous very stable boundary layer (VSBL) cases, characterized by strong stratification, weak winds, and clear skies, and give detailed insight in the temporal evolution and vertical structure of the entire SBL. The SBL is subject to rapid changes in its vertical structure, responding to a variety of different processes. In particular, we study cases involving a shear instability associated with a low-level jet, a rapid strong cooling event observed a few meters above ground, and a strong wave-breaking event that triggers intensive near-surface turbulence. Furthermore, we use observations from one IOP to validate three different atmospheric models. The unique finescale observations resulting from the ISOBAR observational approach will aid future research activities, focusing on a better understanding of the SBL and its implementation in numerical models.
Highlights
The Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer Program (ISOBAR) is a research project investigating stable atmospheric boundary layer (SBL) processes, whose representation still poses significant challenges in state-of-the-art numerical weather prediction (NWP) models
Climate and numerical weather prediction (NWP) models suffer from insufficient atmospheric boundary layer (ABL) parameterizations and have a strong need for an improved representation of the SBL, in particular in very stable boundary layer (VSBL) conditions
The common positive temperature biases are typically related to excessively large downward sensible heat flux (Cuxart et al 2005; Tjernström et al 2005), whereas large negative biases may be generated via thermal decoupling between the atmosphere and the snow/ice surface (Mahrt 2003; Uppala et al 2005)
Summary
The Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer Program (ISOBAR) is a research project investigating stable atmospheric boundary layer (SBL) processes, whose representation still poses significant challenges in state-of-the-art numerical weather prediction (NWP) models. Climate and numerical weather prediction (NWP) models suffer from insufficient atmospheric boundary layer (ABL) parameterizations and have a strong need for an improved representation of the SBL, in particular in very stable boundary layer (VSBL) conditions. This is demonstrated by large errors under VSBL conditions, where 2-m air temperature errors (∆T2m) on the order of 10 K are common even in short-term (24-h) NWP products (Atlaskin and Vihma 2012). Empirical studies evaluating MOST commonly indicate an inability to differentiate between near-neutral and very stable regimes (Foken 2006; Sorbjan and Grachev 2010; Sorbjan 2010; Grachev et al 2013), which is largely related to the very weak turbulent heat fluxes present in both situations
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