Preprints
https://doi.org/10.5194/hess-2021-34
https://doi.org/10.5194/hess-2021-34

  15 Feb 2021

15 Feb 2021

Review status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

Evaluation of INCA precipitation analysis using a very dense rain gauge network in southeast Austria

Esmail Ghaemi1,2,3, Ulrich Foelsche1,2,3, Alexander Kann4, and Jürgen Fuchsberger3 Esmail Ghaemi et al.
  • 1Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics (IGAM/IP), NAWI Graz, University of Graz, Austria
  • 2FWF-DK Climate Change, University of Graz, Austria
  • 3Wegener Center for Climate and Global Change (WEGC), University of Graz, Austria
  • 4Department of Forecasting Models, Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria

Abstract. An accurate estimate of precipitation is essential to improve the reliability of hydrological models and helps for decision-making in agriculture and economy. Merged radar–rain-gauge products provide precipitation estimates at high spatial and temporal resolution. In this study, we assess the ability of the INCA (Integrated Nowcasting through Comprehensive Analysis) precipitation analysis product provided by ZAMG (the Austrian Central Institute for Meteorology and Geodynamics) in detecting and estimating precipitation for 12 years in southeast Austria. The blended radar–rain-gauge INCA precipitation analyses are evaluated using WegenerNet – a very dense rain gauge network with about 1 station per 2 km2 – as true precipitation. We analyze annual, seasonal, and extreme precipitation of the 1 km × 1 km INCA product and its development from 2007 to 2018. Based on the results, the performance of INCA can be divided into three different periods. From 2007 to 2011, the annual area-mean precipitation in INCA was slightly higher than WegenerNet, except in 2009. However, INCA underestimates precipitation in grid cells farther away from the two ZAMG meteorological stations in the study area (which are used as input for INCA), especially from May to September (wet season). From 2012 to 2014, INCA's overestimation of the annual-mean precipitation amount is even higher, with an average of 25 %, but INCA performs better close to the two ZAMG stations. From 2015 onwards, the overestimation is still dominant in most cells but less pronounced than during the second period, with an average of 12.5 %. Regarding precipitation detection, INCA performs better during the wet seasons. Generally, false events in INCA happen less frequently in the cells closer to the ZAMG stations than in other cells. The number of true events, however, is comparably low closer to the ZAMG stations. The difference between INCA and WegenerNet estimates is more noticeable for extremes. We separate individual events using a 1-hour minimum inter-event time (MIT) and demonstrate that INCA underestimates the events' peak intensity until 2012 and overestimates this value after mid-2012 in most cases. The overestimation of the peak-intensity is more pronounced during July. In general, the precipitation rate and the number of grid cells with precipitation are higher in INCA. Furthermore, 40 % of the individual events start earlier, and 50 % end later in INCA. Considering four extreme convective short-duration events, there is a time shift in peak intensity detection. The relative differences in the peak intensity in these events can change from approximately −40 % to 40 %. The results of this study can be used for further improvements of INCA products as well as for future hydrological studies in this area.

Esmail Ghaemi et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-34', Anonymous Referee #1, 27 Mar 2021
  • RC2: 'Comment on hess-2021-34', Anonymous Referee #2, 28 Mar 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-34', Anonymous Referee #1, 27 Mar 2021
  • RC2: 'Comment on hess-2021-34', Anonymous Referee #2, 28 Mar 2021

Esmail Ghaemi et al.

Esmail Ghaemi et al.

Viewed

Total article views: 621 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
490 122 9 621 3 3
  • HTML: 490
  • PDF: 122
  • XML: 9
  • Total: 621
  • BibTeX: 3
  • EndNote: 3
Views and downloads (calculated since 15 Feb 2021)
Cumulative views and downloads (calculated since 15 Feb 2021)

Viewed (geographical distribution)

Total article views: 494 (including HTML, PDF, and XML) Thereof 494 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 25 Jul 2021
Download
Short summary
We assess an operational merged gauge-radar precipitation product over a period of 12 years, using gridded precipitation fields from a dense gauge network (WegenerNet) in southeast Austria. We analyze annual data, seasonal data, and extremes using different metrics. We identify individual events using a simple threshold based on the interval between two consecutive events and evaluate the events’ characteristics in both datasets.