Evaluating the reconstruction method of satellite based monthly precipitation over Golestan province, Northern Iran

Abdollahipour, Arman; Ahmadi, Hassan; Aminnejad, Babak

doi:10.1007/s11600-021-00623-4

Artykuł - szczegóły

Tytuł artykułu

Evaluating the reconstruction method of satellite based monthly precipitation over Golestan province, Northern Iran

Autorzy

Abdollahipour Arman , Ahmadi Hassan , Aminnejad Babak

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-021-00623-4

Warianty tytułu

Języki publikacji

Abstrakty

Accurate gridded precipitation data with high spatial and temporal scales are required for diverse studies such as climatology, meteorology, and hydrology. Currently, one of the sources of global precipitation estimation is the satellite-based precipitation estimate products. Nonetheless, their spatial resolution is often too coarse for usage in local region and basin scales or for parameterizing of meteorological and hydrological models at regional scales. In the present paper, a reconstruction method of satellite-based monthly precipitation was developed to attain improved pixel-based precipitation data with high spatial resolution on Golestan province in Northern Iran. In this endeavor, we considered the spatially heterogeneous relationships between tropical rainfall measuring mission (TRMM) precipitation and environmental variables utilizing the moving-window regression methods, the geographically weighted regression (GWR) and the mixed geographically weighted regression (MGWR) models. By in situ observations from rain gauges in the study area, the calibration and validation were performed, and the following conclusions were derived: (1) the proposed procedure had the ability to enhance both the spatial resolution and accuracy of satellite-based precipitation estimates; (2) the monthly reconstructed precipitation using the GWR model (CC=0.69, bias=0.75) and using the MGWR model (CC=0.72, bias=0.64) outperformed the TRMM-3B43V7 data (CC=0.58, bias=0.84) against ground observations; (3) this research offered a potential solution for producing gridded precipitation estimates at high spatial resolution. remote sensing

Słowa kluczowe

remote sensing precipitation downscaling Golestan province

teledetekcja opad atmosferyczny skalowanie prowincja Golestan

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2021

Tom

Vol. 69, no. 6

Strony

2305--2323

Opis fizyczny

Bibliogr. 68 poz.

Twórcy

autor

Abdollahipour Arman

st.a_abdollahipour@riau.ac.ir

Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran

https://orcid.org/0000-0001-7926-1219

autor

Ahmadi Hassan

hgahmadi@riau.ac.ir

Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran

https://orcid.org/0000-0003-0314-1012

autor

Aminnejad Babak

aminnejad@riau.ac.ir

Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran

https://orcid.org/0000-0001-9411-9413

Bibliografia

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Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-80c4f512-35a9-4520-a793-8bfcaaa663e6