Preprints
https://doi.org/10.5194/nhess-2021-262
https://doi.org/10.5194/nhess-2021-262

  15 Sep 2021

15 Sep 2021

Review status: this preprint is currently under review for the journal NHESS.

Forecasting the regional fire radiative power for regularly ignited vegetation fires

Tero M. Partanen and Mikhail Sofiev Tero M. Partanen and Mikhail Sofiev
  • Finnish Meteorological Institute, Erik Palménin aukio 1, 00560 Helsinki, Finland

Abstract. This paper presents a phenomenological framework for forecasting the area-integrated fire radiative power from wildfires. In the method, a region of interest is covered with a regular grid, which cells are uniquely and independently parameterized with regard to the fire intensity according to (i) the fire incidence history, (ii) the retrospective meteorological information, and (iii) remotely-sensed high temporal resolution fire radiative power taken together with (iv) consistent cloud mask data. The parameterization is realized by fitting the predetermined functions for diurnal and annual profiles of fire radiative power to the remote-sensing observations. After the parametrization, the input for the fire radiative power forecast is the meteorological data alone, i.e., the weather forecast. The method is tested retrospectively for south-central African savannah areas with grid cell size of 1.5° × 1.5°. The input data included ECMWF ERA5 meteorological reanalysis and SEVIRI/MSG Fire Radiative Power and Cloud Mask. It has been found that in the areas with large numbers of wildfires regularly ignited on a daily basis during dry seasons from year to year, the temporal fire radiative power evolution is quite predictable, whereas the areas with irregular fire behaviour predictability was low. The predictive power of the method is demonstrated by comparing the predicted fire radiative power patterns and fire radiative energy values against the corresponding remote-sensing observations. The current method showed good skills for the considered African regions and was useful in understanding the challenges in predicting the wildfires in a more general case.

Tero M. Partanen and Mikhail Sofiev

Status: open (until 29 Oct 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-262', Anonymous Referee #1, 06 Oct 2021 reply
  • RC2: 'Comment on nhess-2021-262', Anonymous Referee #2, 11 Oct 2021 reply

Tero M. Partanen and Mikhail Sofiev

Tero M. Partanen and Mikhail Sofiev

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Short summary
The presented method aims to forecast regional wildfire emitted radiative power in a time dependent manner several days in advance. The temporal fire radiative power can be converted to an emission production rate, which can be implemented in air quality forecasting simulations. It is shown that in areas with a high incidence of wildfires, the fire radiative power is quite predictable, otherwise it is not.
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