simulation of ship-track versus satellite-sensor differences in oceanic precipitation using an island-based radar

simulation of ship-track versus satellite-sensor differences in oceanic precipitation using an island-based radar

;Jörg Burdanowitz;Christian Klepp;Stephan Bakan;Stefan A. Buehler
Journal of pharmacological sciences 2017 Vol. 9 pp. 593-
137
burdanowitz2017remotesimulation

Abstract

The point-to-area problem strongly complicates the validation of satellite-based precipitation estimates, using surface-based point measurements. We simulate the limited spatial representation of light-to-moderate oceanic precipitation rates along ship tracks with respect to areal passive microwave satellite estimates using data from a subtropical island-based radar. The radar data serves to estimate the discrepancy between point-like and areal precipitation measurements. From the spatial discrepancy, two statistical adjustments are derived so that along-track precipitation ship data better represent areal precipitation estimates from satellite sensors. The first statistical adjustment uses the average duration of a precipitation event as seen along a ship track, and the second adjustment uses the median-normalized along-track precipitation rate. Both statistical adjustments combined reduce the root mean squared error by 0.24 mm h − 1 (55%) compared to the unadjusted average track of 60 radar pixels in length corresponding to a typical ship speed of 24–34 km h − 1 depending on track orientation. Beyond along-track averaging, the statistical adjustments represent an important step towards a more accurate validation of precipitation derived from passive microwave satellite sensors using point-like along-track surface precipitation reference data.

Citation

ID: 152196
Ref Key: burdanowitz2017remotesimulation
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
152196
Unique Identifier:
10.3390/rs9060593
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet