Forecasting the regional fire radiative power for regularly ignited vegetation fires
<p>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, whose cells are uniquely and independently parameterized with regard to the fire intensity according...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-04-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/22/1335/2022/nhess-22-1335-2022.pdf |
| _version_ | 1828846332152905728 |
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| author | T. M. Partanen M. Sofiev |
| author_facet | T. M. Partanen M. Sofiev |
| author_sort | T. M. Partanen |
| collection | DOAJ |
| description | <p>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, whose 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 the grid cell size of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1.5</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1.5</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="52pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="51ae01ea95da6e84c7e4ce1e24bb092f"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="nhess-22-1335-2022-ie00001.svg" width="52pt" height="11pt" src="nhess-22-1335-2022-ie00001.png"/></svg:svg></span></span>. The input data included ECMWF ERA5 meteorological reanalysis and SEVIRI/MSG (Spinning Enhanced Visible and Infra-Red Imager on board Meteosat Second Generation) fire radiative power and cloud mask data. It has been found that in the areas with a large number 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.</p> |
| first_indexed | 2024-12-12T21:46:43Z |
| format | Article |
| id | doaj.art-9d323f64960e4ef1bf7ad356d29c4231 |
| institution | Directory Open Access Journal |
| issn | 1561-8633 1684-9981 |
| language | English |
| last_indexed | 2024-12-12T21:46:43Z |
| publishDate | 2022-04-01 |
| publisher | Copernicus Publications |
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| series | Natural Hazards and Earth System Sciences |
| spelling | doaj.art-9d323f64960e4ef1bf7ad356d29c42312022-12-22T00:10:54ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812022-04-01221335134610.5194/nhess-22-1335-2022Forecasting the regional fire radiative power for regularly ignited vegetation firesT. M. PartanenM. Sofiev<p>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, whose 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 the grid cell size of <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1.5</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1.5</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="52pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="51ae01ea95da6e84c7e4ce1e24bb092f"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="nhess-22-1335-2022-ie00001.svg" width="52pt" height="11pt" src="nhess-22-1335-2022-ie00001.png"/></svg:svg></span></span>. The input data included ECMWF ERA5 meteorological reanalysis and SEVIRI/MSG (Spinning Enhanced Visible and Infra-Red Imager on board Meteosat Second Generation) fire radiative power and cloud mask data. It has been found that in the areas with a large number 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.</p>https://nhess.copernicus.org/articles/22/1335/2022/nhess-22-1335-2022.pdf |
| spellingShingle | T. M. Partanen M. Sofiev Forecasting the regional fire radiative power for regularly ignited vegetation fires Natural Hazards and Earth System Sciences |
| title | Forecasting the regional fire radiative power for regularly ignited vegetation fires |
| title_full | Forecasting the regional fire radiative power for regularly ignited vegetation fires |
| title_fullStr | Forecasting the regional fire radiative power for regularly ignited vegetation fires |
| title_full_unstemmed | Forecasting the regional fire radiative power for regularly ignited vegetation fires |
| title_short | Forecasting the regional fire radiative power for regularly ignited vegetation fires |
| title_sort | forecasting the regional fire radiative power for regularly ignited vegetation fires |
| url | https://nhess.copernicus.org/articles/22/1335/2022/nhess-22-1335-2022.pdf |
| work_keys_str_mv | AT tmpartanen forecastingtheregionalfireradiativepowerforregularlyignitedvegetationfires AT msofiev forecastingtheregionalfireradiativepowerforregularlyignitedvegetationfires |