一个涵盖 Landsat 时代的美国西部雪再分析数据集，时间跨度为 1985 年至 2021 年的水年。

A western United States snow reanalysis dataset over the Landsat era from water years 1985 to 2021.

机构信息

Department of Civil and Environmental Engineering, University of California, Los Angeles, Los Angeles, CA, USA.

出版信息

Sci Data. 2022 Nov 7;9(1):677. doi: 10.1038/s41597-022-01768-7.

DOI:10.1038/s41597-022-01768-7

PMID:36344572

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9640559/

Abstract

Water stored in mountain snowpacks (i.e., snow water equivalent, SWE) represents an important but poorly characterized component of the terrestrial water cycle. The Western United States snow reanalysis (WUS-SR) dataset is novel in its combination of spatial resolution (~500 m), spatial extent (31°-49° N; 102°-125° W), and temporal continuity (daily over 1985-2021). WUS-SR is generated using a Bayesian framework with model-based snow estimates updated through the assimilation of cloud-free Landsat fractional snow-covered area observations. Over the WUS, the peak SWE verification with independent in situ measurements show correlation coefficient, mean difference (MD), and root mean squared difference (RMSD) of 0.77, -0.15 m, and 0.28 m, respectively. The effects of forest cover and Landsat image availability on peak SWE are assessed. WUS-SR peak SWE is well correlated (ranging from 0.75 to 0.91) against independent lidar-derived SWE taken near April 1, with MD <0.15 m and RMSD <0.38 m. The dataset is useful for characterizing WUS mountain snow storage, and ultimately for improving snow-derived water resources management.

摘要

储存在山地积雪中的水（即雪水当量，SWE）是陆地水循环中一个重要但特征描述较差的组成部分。西部美国雪再分析（WUS-SR）数据集在空间分辨率（约 500m）、空间范围（31°-49°N；102°-125°W）和时间连续性（1985-2021 年每天）方面具有新颖性。WUS-SR 是使用基于贝叶斯框架的方法生成的，通过同化无云 Landsat 积雪覆盖面积的观测值，对基于模型的雪量估计进行更新。在 WUS 地区，与独立的实地测量结果进行峰值 SWE 验证的相关系数、均值差（MD）和均方根差（RMSD）分别为 0.77、-0.15m 和 0.28m。评估了森林覆盖和 Landsat 图像可用性对峰值 SWE 的影响。WUS-SR 的峰值 SWE 与独立的激光雷达衍生的 SWE 高度相关（范围从 0.75 到 0.91），MD<0.15m，RMSD<0.38m。该数据集可用于描述 WUS 山区积雪储存，最终用于改善基于积雪的水资源管理。