Abstract
Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial–temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances ~ 1.5–2.8 km and rarely exceeding 5 km, and time-correlation distances ~ 1.8–6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.
| Original language | English |
|---|---|
| Pages (from-to) | 126-138 |
| Number of pages | 13 |
| Journal | Atmospheric Research |
| Volume | 200 |
| DOIs | |
| State | Published - 1 Feb 2018 |
Bibliographical note
Publisher Copyright:© 2017 Elsevier B.V.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Autocorrelation
- Convective rainfall
- Semiarid, arid climate
- X-Band weather radar
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