Amazon Region

The fire season in the southern Amazon runs from June to November, with peak burning activity in September along the eastern and southern Amazon forest frontiers, a swath sometimes referred to as the "arc of deforestation". Year-to-year variability in fires is strongly linked to climate anomalies, and both the El Niño Southern Oscillation in the Pacific Ocean and Atlantic Multi-decadal Oscillation influence drought conditions and the risk of fires across the southern Amazon.

Recent Posts (View All)

2020 Fire Season Forecast:

To follow the evolution of the current fire season for the 10 forecast regions (6 states in the Brazilian Amazon, 3 regions in Bolivia, and Peru), click the radio dials showing the predicted fire season severity for 2020 or scroll down for more information. Figures are updated daily, based on active fire detections from the MODIS sensors on NASA's Terra and Aqua satellites.

Sea surface temperatures (SSTs) in the tropical Pacific Ocean and North Atlantic Ocean during early 2020 were significantly higher than the mean values during the 2001-2015 period of satellite fire observations. By combining the SSTs in both oceans, we projected a high fire risk for Acre, El Beni, Mato Grosso, Pando, Para, Rondonia, and Santa Cruz, and an above-average risk for Amazonas, Maranhao, and Peru during the 2020 dry season. For more information on the 2020 Amazon fire forecast, please see the fire forecast page (available in English, Spanish, and Portuguese).

---

Estimated fire emissions are based on the historic relationship between active fire detections and GFED fire emissions for each region (see GFED Data for more information). Estimated fire emissions for 2016+ are preliminary, and should be interpreted with caution. The historic relationship between fire detections and emissions does not account for potential differences in fire types and climate conditions in the current year, variability that is considered using additional data on burned area and climate in GFED.

2015 Fire Season

Indonesian fire season progression

Last and final update: November 16, 2015.

Heavy rains have been reported in Kalimantan starting October 26 and since then the fire season has been coming to an end. There are still fires burning but nothing compared to those that burned earlier in the season.

This figure shows how the current fire season progressed in relation to previous ones (2003-2014). On October 21 this year passed 2006, which was the highest fire year in the MODIS satellite era, 2000 onwards. The main fire season is August through October when the southern part of Indonesia experiences its dry season. However, in some years including 2014 the fire season in the northern part of Sumatra is prominent as well, burning in February and March.

Emissions estimates

We expect that the GFED estimate for the 2015 fires will be about 1.75 billion metric ton of CO2 equivalents, with substantial uncertainty.

Above the greenhouse gas emissions from Indonesian fires are plotted according to GFED for 1997-2014 with estimates for 2015 based on active fires. These are converted to emissions based on a relation between the two, established using data from previous years, see the figure and text below for more information. The numbers on the right indicate fossil fuel CO2 emissions for various countries for 2013 derived from the EDGAR database.

In general, fire CO2 emissions are compensated for by regrowing vegetation after a fire and should not be compared to fossil fuel emissions, but that is not the case when forests are burned to make way for other land uses or when peat is burned. That is exactly what happens with the vast majority of the fires in Indonesia and these fires are thus a net source of CO2 as well as other greenhouse gases.

Conversion of active fires to emissions

This graph shows how we derive the 2015 estimates. The grey dots indicate the total annual active fire observations in Indonesia on the horizontal axis and the corresponding GFED estimates are on the vertical axis with the years 2006 and 2014 labeled. Each grey dot represents one year between 2003 and 2014. The relation is not perfect and adds some uncertainty to those that are in these estimates already. The non-linearity is probably related to smoke obscuration of active fires in high fire years.

Note: we have adjusted the trendline describing the relation between active fire detections and emissions on October 20 to better represent the high fire years, especially 2006. This led to a small increase in emissions compared to the relation used before October 20.

Daily emissions

Using the conversion from active fires to emissions we can calculate daily emissions which is shown above. This has generated a lot of media interest after WRI showed that on many days the rate exeeds that of fossil fuel emissions in the US (roughly 15 million ton CO2 per day). Keep in mind though that these fires do not burn continuously at this rate: on a global annual scale they are far less important for climate change than other sources of greenhouse gases.

A few things to consider:

• These estimates contain a substantial amount of uncertainty related to the complex fire situation in Indonesia. We would very much welcome opportunities to lower uncertainties which is poorly supported by the regular national agencies.
• Top-down studies using atmospheric observation provide some confidence in the emission estimates provide here, see for example Aouizerats et al. (2014) and Van der Werf et al. (2009)
• GFED starts in 1997, there is information on earlier years thanks to work of, amongst others, Wooster et al. (2012) and Field et al. (2009). That work supports the tight link between (El Nino related) drought and fires. However, El Nino is not the root cause: the work of Field shows that without humans these extreme fire seasons would not exist.
• In addition to greenhouse gas emissions from fires, drainage of peatlands also leads to CO2 emissions from decomposition. The emissions are not as visible as those from fires but may be of similar magnitude according to the work of Hooijer et al. (2010), although not as variable from year to year.

For more information please contact Guido van der Werf