TY - JOUR
T1 - Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates
AU - Marra, Francesco
AU - Morin, Efrat
N1 - Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - 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.
AB - 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.
KW - Autocorrelation
KW - Convective rainfall
KW - Semiarid, arid climate
KW - X-Band weather radar
UR - http://www.scopus.com/inward/record.url?scp=85033502501&partnerID=8YFLogxK
U2 - 10.1016/j.atmosres.2017.09.020
DO - 10.1016/j.atmosres.2017.09.020
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AN - SCOPUS:85033502501
SN - 0169-8095
VL - 200
SP - 126
EP - 138
JO - Atmospheric Research
JF - Atmospheric Research
ER -