Zhuo Zheng, Lei Zheng, Kang Wang, Gary D. Clow, Xiao Cheng
{"title":"无人机斜向影像揭示了气象条件变化下东南极洲秦岭站积雪气动粗糙度的数量级变化","authors":"Zhuo Zheng, Lei Zheng, Kang Wang, Gary D. Clow, Xiao Cheng","doi":"10.1029/2025JF008781","DOIUrl":null,"url":null,"abstract":"<p>Snow aerodynamic roughness length (<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math>) plays a critical role in Antarctic surface energy and mass balance. Yet, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> is conventionally treated as a constant in turbulent flux calculations. Fine-scale spatiotemporal variations in <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mrow>\n <mspace></mspace>\n <mi>z</mi>\n </mrow>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\hspace*{.5em}\\mathscr{z}}_{0}$</annotation>\n </semantics></math> remain largely unmonitored. This study employed multi-temporal uncrewed aerial vehicle oblique photogrammetry to construct digital surface models and estimate <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> values for various underlying surfaces and weather conditions with the bulk-aerodynamic method at Qinling Station, East Antarctica. The results demonstrate similar spatial distribution patterns among five <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> estimation models, yet reveal an order-of-magnitude discrepancy in absolute values. The <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> values in snow sastrugi areas are approximately an order of magnitude lower than those in rock areas. Snow surface <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> shows high sensitivity to changes in meteorological conditions. Snowfall results in an increase of the regional mean <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> in the snow sastrugi area from 0.01 to 0.10 mm, while strong winds reduce it by approximately one order of magnitude. Furthermore, <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> tends to increase with the spatial sampling scales. Fine-scale estimation of <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> can be combined with wind-based <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>z</mi>\n <mn>0</mn>\n </msub>\n </mrow>\n <annotation> ${\\mathscr{z}}_{0}$</annotation>\n </semantics></math> observations to provide a basis for developing high-fidelity snow-atmosphere interaction models, which is particularly crucial for simulating complex polar climates and environments.</p>","PeriodicalId":15887,"journal":{"name":"Journal of Geophysical Research: Earth Surface","volume":"131 4","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"UAV Oblique Imagery Reveals Order-of-Magnitude Changes in Snow Aerodynamic Roughness Length Under Shifting Meteorological Regimes at Qinling Station, East Antarctica\",\"authors\":\"Zhuo Zheng, Lei Zheng, Kang Wang, Gary D. Clow, Xiao Cheng\",\"doi\":\"10.1029/2025JF008781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Snow aerodynamic roughness length (<span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math>) plays a critical role in Antarctic surface energy and mass balance. Yet, <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> is conventionally treated as a constant in turbulent flux calculations. Fine-scale spatiotemporal variations in <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mrow>\\n <mspace></mspace>\\n <mi>z</mi>\\n </mrow>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\hspace*{.5em}\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> remain largely unmonitored. This study employed multi-temporal uncrewed aerial vehicle oblique photogrammetry to construct digital surface models and estimate <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> values for various underlying surfaces and weather conditions with the bulk-aerodynamic method at Qinling Station, East Antarctica. The results demonstrate similar spatial distribution patterns among five <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> estimation models, yet reveal an order-of-magnitude discrepancy in absolute values. The <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> values in snow sastrugi areas are approximately an order of magnitude lower than those in rock areas. Snow surface <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> shows high sensitivity to changes in meteorological conditions. Snowfall results in an increase of the regional mean <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> in the snow sastrugi area from 0.01 to 0.10 mm, while strong winds reduce it by approximately one order of magnitude. Furthermore, <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> tends to increase with the spatial sampling scales. Fine-scale estimation of <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> can be combined with wind-based <span></span><math>\\n <semantics>\\n <mrow>\\n <msub>\\n <mi>z</mi>\\n <mn>0</mn>\\n </msub>\\n </mrow>\\n <annotation> ${\\\\mathscr{z}}_{0}$</annotation>\\n </semantics></math> observations to provide a basis for developing high-fidelity snow-atmosphere interaction models, which is particularly crucial for simulating complex polar climates and environments.</p>\",\"PeriodicalId\":15887,\"journal\":{\"name\":\"Journal of Geophysical Research: Earth Surface\",\"volume\":\"131 4\",\"pages\":\"\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2026-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geophysical Research: Earth Surface\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025JF008781\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research: Earth Surface","FirstCategoryId":"89","ListUrlMain":"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025JF008781","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
UAV Oblique Imagery Reveals Order-of-Magnitude Changes in Snow Aerodynamic Roughness Length Under Shifting Meteorological Regimes at Qinling Station, East Antarctica
Snow aerodynamic roughness length () plays a critical role in Antarctic surface energy and mass balance. Yet, is conventionally treated as a constant in turbulent flux calculations. Fine-scale spatiotemporal variations in remain largely unmonitored. This study employed multi-temporal uncrewed aerial vehicle oblique photogrammetry to construct digital surface models and estimate values for various underlying surfaces and weather conditions with the bulk-aerodynamic method at Qinling Station, East Antarctica. The results demonstrate similar spatial distribution patterns among five estimation models, yet reveal an order-of-magnitude discrepancy in absolute values. The values in snow sastrugi areas are approximately an order of magnitude lower than those in rock areas. Snow surface shows high sensitivity to changes in meteorological conditions. Snowfall results in an increase of the regional mean in the snow sastrugi area from 0.01 to 0.10 mm, while strong winds reduce it by approximately one order of magnitude. Furthermore, tends to increase with the spatial sampling scales. Fine-scale estimation of can be combined with wind-based observations to provide a basis for developing high-fidelity snow-atmosphere interaction models, which is particularly crucial for simulating complex polar climates and environments.