REDCAPP (v1.0): parameterizing valley inversions in air temperature data downscaled from reanalyses

Abstract

Abstract. In mountain areas, the use of coarse-grid reanalysis data for driving fine-scale models requires downscaling of near-surface (e.g., 2 m high) air temperature. Existing approaches describe lapse rates well but differ in how they include surface effects, i.e., the difference between the simulated 2 m and upper-air temperatures. We show that different treatment of surface effects result in some methods making better predictions in valleys while others are better in summit areas. We propose the downscaling method RED-CAPP (REanalysis Downscaling Cold Air Pooling Parameterization) with a spatially variable magnitude of surface effects. Results are evaluated with observations (395 stations) from two mountain regions and compared with three reference methods. Our findings suggest that the difference between near-surface air temperature and pressure-level temperature ( T ) is a good proxy of surface effects. It can be used with a spatially variable land-surface correction factor (LSCF) for improving downscaling results, especially in valleys with strong surface effects and cold air pooling during winter. While LSCF can be parameterized from a fine-scale digital elevation model (DEM), the transfer of model parameters between mountain ranges needs further investigation.

Permafrost zonation index map and statistics over the Qinghai–Tibet Plateau based on field evidence

“…To assess the performance of the PZI model, we conducted a 10‐fold cross‐validation. This is a commonly used method to compare and select a model for a given predictive modeling problem and it generally has a lower bias than other methods such as a simple split of training and test data (e.g …”

“…It is well known that the total permafrost simulation chain may be significantly affected by the choice of input data sets . ERA‐Interim, produced by the European Center for Medium‐range Weather Forecast (ECMWF), was chosen for this study as it was found to describe the complex environments over the QTP better than other re‐analyses, and its downscaled results have achieved promising results (e.g …”

“…A 3 arc second (∼ 90 m) DEM was created by spatially averaging the Global Digital Elevation Model version 2 (GDEM2), which has an original resolution of 1 arc second . This was done to reduce the level of noise in the original data set . Subsequently, topographic indices including slope and aspect were calculated for all sites in the inventory using RSAGA .…”

Using Persistent Scatterer Interferometry to Map and Quantify Permafrost Thaw Subsidence: A Case Study of Eboling Mountain on the Qinghai‐Tibet Plateau

“…ERA‐Interim reanalysis data, produced by the European Center for Medium‐Range Weather Forecasts, have been well proven to resolve near‐surface air temperature for various mountain regions (Bao & Zhang, ; Fiddes et al, ). Cao, Gruber, and Zhang () proposed an advanced downscaling approach by incorporating the parameters related to cold air pooling (or winter inverse). The downscaled 2‐m air temperature had been validated against the in situ measurements with a high‐degree match over the Qilian Mountains during 2012–2016 (Cao, Gruber, & Zhang, ).…”

“…Cao, Gruber, and Zhang () proposed an advanced downscaling approach by incorporating the parameters related to cold air pooling (or winter inverse). The downscaled 2‐m air temperature had been validated against the in situ measurements with a high‐degree match over the Qilian Mountains during 2012–2016 (Cao, Gruber, & Zhang, ). Figure shows the downscaled 2‐m air temperature in our study area during 2006–2011.…”