Characteristics and Establishment of Objective Identification Criteria and Predictors for Foehn Winds in Urumqi, China

Abstract

The special terrain of Urumqi (in the valley area) often triggers strong foehn winds, causing huge losses to local people’s lives and social economies. By using the surface observation data of the hourly temperature, pressure, humidity, and wind from the downwind Urumqi Meteorological Station and the upwind Dabancheng Meteorological Station in the Middle Tianshan Canyon and the NCEP/NCAR reanalysis data during 2008–2022, this paper establishes the dataset of foehn processes at Urumqi Station in the past 15 years and analyzes the variation rules of the associated meteorological variables during the foehn processes. In addition, based on the physical mechanism of the occurrence of foehn, a three-element identification criterion (i.e., 94° ≤ 2 min average wind direction ≤ 168°, 2 min average wind speed ≥ 2.0 m/s, and Δθ between Urumqi station and Dabancheng station ≥ 0.29 K) for foehn in Urumqi is established by comparing and analyzing the variations of wind direction (WD), wind speed (WS), and the potential temperature difference (Δθ) between the two weather stations during the periods of foehn and non-foehn winds from 2013 to 2022. In addition, the performance of the three-element identification criterion is verified, and the results suggest that this criterion has an accuracy of 82.96% and a hit rate of 89.50% for the 2008–2012 foehn events in Urumqi. Moreover, the hit rate of this criterion for foehn wind of gale or above level (i.e., a 2 min wind ≥ 10.8 m/s on average) is 100%. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between downwind stations and upwind stations, the foehn forecast can be more accurate than that provided by a single predictor. With ΔP ≤ −12 hPa and Δθ ≥ 5 K, the chances for foehn to occur are over 90%. This finding would have some reference and application values for the foehn forecasting.

Characteristics of Foehn Wind in Urumqi, China, and Their Relationship with EI Niño and Extreme Heat Events in the Last 15 Years

“…(1) Meteorological station observation data. This study selected meteorological variables such as hourly 2 min average, 10 min average, instantaneous, and maximum wind speeds and directions; atmospheric and sea level pressure; temperature; and relative humidity from Urumqi Station from 2008 to 2022.The beginning and end periods of Foehn wind, the duration of FW weather, and the distribution of various meteorological elements over time in Urumqi over the past 15 years were analyzed based on the southeast winds in Urumqi, the conditions in the upper level during the Foehn period, the surface pressure situation of "high in the south and low in the north", and the sudden rise/drop in temperature/humidity [14]. The selection criteria for strong FW are as follows: an instantaneous wind speed ≥ 17 m/s or a 2 min average wind speed ≥ 10.8 m/s.…”

“…FW usually occurs on the lee slope of mountain ranges, which experiences a localized form of air movement caused by a mountainous region [1]. FW occurs in many mountainous areas around the world, such as the Alps in Europe, the Rockies in America, and the Taihang Mountains in China [2][3][4][5][6][7][8][9][10][11][12][13][14]. It often poses a threat to local people's safety, the infrastructure, transportation, agricultural production, etc.…”

“…When Urumqi is located at the bottom of a high-pressure system, southeast winds blow, and the airflow is forced by the terrain to sink rapidly after crossing the mountains, causing adiabatic heating of the air and a decrease in humidity. This is the unique FW weather in the Urumqi region [13,14,[18][19][20]. FW in Urumqi has had a significant impact on local socio-economic development, and thus a thorough investigation and exploration of the activity patterns of FW is urgent.…”

Influence of color steel buildings on urban land surface temperature: a case study in Urumqi, Xinjiang, China

“…The temperature difference between day and night is significant (Xing et al, 2022). The topography of the urban area slopes from southeast to northwest, with an average elevation of 800 m and a drop of 300-400 m (Ayitikan et al, 2023). In order to study the impact of CSB on urban LST, we chose areas with high CSB coverage, including Midong District, Toutunhe District, New Downtown District, Shayibak District, Tianshan District and Shuimogou District.…”