UN Climate Disaster doubling revisited

By Pasi Autio 20th of October 2020

Couple of weeks ago a new United Nations report claimed doubling of natural disasters between periods 1980-1999 and 2000-2019:

Human cost of disasters

An overview of the last 20 years 2000 to 2019

GENEVA, 12 October 2020 – A UN report published to mark the International Day for Disaster Risk Reduction on October 13, confirms how extreme weather events have come to dominate the disaster landscape in the 21st century.

In the period 2000 to 2019, there were 7,348 major recorded disaster events claiming 1.23 million lives, affecting 4.2 billion people (many on more than one occasion) resulting in approximately US$2.97 trillion in global economic losses.

This is a sharp increase over the previous twenty years. Between 1980 and 1999, 4,212 disasters were linked to natural hazards worldwide claiming approximately 1.19 million lives and affecting 3.25 billion people resulting in approximately US$1.63 trillion in economic losses.

Much of the difference is explained by a rise in climate-related disasters including extreme weather events: from 3,656 climate-related events (1980-1999) to 6,681 climate-related disasters in the period 2000-2019. 

The last twenty years has seen the number of major floods more than double, from 1,389 to 3,254, while the incidence of storms grew from 1,457 to 2,034. Floods and storms were the most prevalent events.”

Doubling of natural disaster events – this is bad. The conclusion was based on EM-DAT International Disaster Database (1) consisting of 22000 mass disasters in the world between 1900 and 2020.

The claim is so bold that this requires more thorough analysis of the original data. Everyone can access the EM-DAT database by registering as EM-DAT user. Access is free for non-profit organizations, so let’s do it.

After approval as an EM-DAT database user, I was able to download the whole database of disasters between 1900 and 2020. By just selecting natural disasters I got the Excel file of 15564 individual disasters, each as a line in the Excel. Data contains up to 43 different columns of information for each disaster – for most disasters only less than half of the columns has any data.

Let’s start by plotting a diagram of number of disasters each year between 1900 and 2020.

Figure: All natural disasters worldwide in EM-DAT database

It’s easy to see where the UN claim comes from. Indeed the natural disasters have increased considerably during years 2000-2019 compared to years 1980-1999. But at the same time we see the first hint of what is wrong: There is a gradual increase of natural disasters from 1940s level to today’s level. If you see this kind of data the first question you have is the reporting: How does the improved reporting and data collection affect the dataset?

Let’s plot the number of countries reporting at least one natural disaster per year between 1900-2020:

Figure: Countries reporting at least one natural disaster each year

From the list of countries reporting at least one disaster we can see huge increase of reporting countries during the years. Also the shape of the data is very similar to the total number of natural disasters plotted earlier.

During 1901, for example, there was only two countries in the database (Japan and Uganda) whereas during 2000-2019 the number of countries reporting was about 120 each year. Even the new data has a lot less than countries than there is countries in the world, so it is likely that even the years 2000-2019 are underreporting the actual natural disasters quite heavily.

To analyze further the results in the UN paper the years 1980-2019 are of specific interest. You can see significant increase of reporting countries between 1980 and 2000. After that the number is quite steady. You might think this is due changes like Soviet Union breaking to many different countries, so let’s analyze Soviet Union in more depth:

Figure: Natural disasters in Soviet Union for each year between 1900-1991

We can see that the Soviet Union was not the most open reporter of natural disasters to the EM-DAT database and the increase of countries reporting natural disaster during 1990s is not the result of Soviet Union breakup. And what is the likelihood of country with the size of Soviet Union having only 1-2 natural disasters per year? You can easily conclude that this database contains only small portion of real natural disasters what happened in Soviet Union. Just the forest fires should have tens of reported incidents every year.

And by the way, it seems that the same “issue” of not reporting disasters seems to affect all former Eastern Bloc countries; almost all of them has a huge increase of natural disasters in the database after breakup of Soviet Bloc at 1991. Yugoslavia, for example, reported 0-2 natural disasters per year, but the just Serbia alone is reporting more than that. Clearly the entry criteria is not comparable between pre- and post-Yugoslavia era.

What about China? China was specifically mentioned in the UN report as a country with significant increase of natural disasters:

Figure: Natural disasters in China for each year between 1900-2020

You can see that for years before 1980 there is no meaningful data in the EM-DAT database. The reporting increases gradually after 1980 and reaching “steady state” around year 2000.

For 1980 the database contains just 5 disasters in China: Four floods and one tropical cyclone (there where several cyclones making onshore at China during 1980). The peak year 2013 contains total of 43 disasters: Droughts, Extreme temperatures, Storms, Floods, Earthquakes. The effect of better reporting year-by-year can be easily seen. Communist China was not the most open reporter of natural incidents either.

How about USA? Modern western civilization must have really good disaster reporting already in 1980s, right?

Figure: Natural disasters in USA for each year between 1900-2020

For 1980 the database contains just 8 natural disasters in USA: 4 floods, 3 storms, one volcanic activity (St. Helens) and one heat wave.

No tornadoes are present in the database for 1980, but a little study from Wikipedia tells us that year 1980 was below average tornado year with 28 tornado deaths and several bad outbreaks such as 1980 Kalamazoo tornado outbreak and 1980 Grand Island tornado outbreak. In total the season had 866 reported tornadoes. So, the EM-DAT database is just missing all these events.

Speaking of tornadoes, let’s see how much tornado data is available in the EM-DAT database:

Figure: Number of tornadoes in USA for each year between 1900-2020

It seems that while tornadoes have been the issue in the USA all the time, only after end of 1980s there has been some level of data collection of tornadoes to the EM-DAT database. And even now only small number of tornadoes end up into EM-DAT database. I took year 2000 as an example: Based on EM-DAT there was 30 deaths due to tornadoes. But according to the Tornado season 2000 wiki page it should be 41.

According to the Wikipedia, the tornado year 2012 was about twice as harsh as year 2000 in number of tornadoes and death count was 69 during 2012 season. But the EM-data says year 2000 had more tornadoes fulfilling the entry criteria.

Also no wildfires are present in 1980 data for USA. More in-depth study would reveal some more wildfires, but at least Panorama Fire (1980) is missing from the database. In this fire 28,800 acres burned, destroying 310 homes and 67 structures, killing four people, and injuring 77 in north San Bernardino. Clearly an incident, which should be in database according to the entry criteria.

In USA it seems that only from 1990s forward the database has some level of credibility. Earlier data is simply too lacking to draw any meaningful conclusions about the increase or decrease of natural disasters. But even for recent data, you should not make any conclusions about the number of natural disasters in USA.

The same issue of underreporting on early years seems to affect almost every country I look into. The country I live in, Finland, has only three natural disasters in total in the database; two storms (1990) and one flood (2005). Living in Finland I can assure all readers that we have floods every year (especially with rivers in north we have flooding after every winter) causing material damage almost every year. We also have storms affecting tens of thousands every year usually causing material damage in the forests and lot of damages to the electricity distribution.

What is exactly the entry criteria for EM-DAT database:

Entry criteria: The reason for recording the disaster event into EM-DAT. At least one of the following criteria must be fulfilled in order for an event to be entered into the database:

  • Deaths: 10 or more people deaths
  • Affected: 100 or more people affected/injured/homeless.
  • Declaration/international appeal: Declaration by the country of a state of emergency and/or an appeal for international assistance

As you can see the entry criteria quite relaxed: With this criteria almost every F3 or higher tornado, for example, should be in database assuming it happened on populated area.

Thus, we can conclude that the database really does not have any credibility even today, but even less during 1980s and 1990s. I don’t know how the data collection has been organized, but for scientific analysis of natural disaster trends the EM-DAT database has no scientific value. Therefore also the conclusions in the UN report have not merit. All claims that UN made about the increase of natural disasters should be retracted.

Total damages

UN also reported the sizable increase of damages. Pielke Jr has a lot more scientific merits to say anything about the normalized damages (2) during the years, but we can still make some interesting observations about the EM-DAT data for damages:

It seems that only small part of the entries has any damage data in the database. In 1994, for example, a tropical storm hit Osaka in Japan. According to the database 1000 died and 6.5 million was affected. The cost of this event is missing. This is just one of the thousands of missing damage entries. Only about 1/3 of all entries in the database has any kind of damage estimate. How do you draw any conclusions from that?

Affected people

UN claims that during 1980-1999 natural disasters affected 3.25 billion people whereas during 2000-2019 4.2 billion people was affected. But they omit to discuss the population increases. The world population was:

  • 1980: 4.46 billion
  • 2000: 6.14 billion
  • 2019: 7.71 billion

We can make the rough estimation that during 1980-1999 the average population was 5.4 billion and during 2000-2019 the average population was 6.9 billion. More population should mean more people affected (and dead) due to natural disasters. 3.25 x (6.9/5.4) = 4.15 billion – thus the increase of people affected can be explained entirely with the world population increase. Actually even more, since most of the population increases tend to happen on natural disaster-prone areas such as India, Bangladesh and Africa.

But regarding EM-DAT dataset itself, almost 30% of the whole dataset is missing the affected people data. Older the data is, more of it is missing.

Data collection methods

While trying to find some information about the EM-DAT history, I found something interesting (3). The document released 2004 provides interesting insights of EM-DATA data sources during the years and will explain quite well what we saw above: Why the increase of observations and reporting will explain the “increase” of natural disasters.

This diagram is from the document released by EM-DAT maintainers:

Figure: Reporting sources for EM-DAT database between 1974-2002

Natural disaster reports are provided by a number of sources and there seem to be significant evolution of EM-DAT reporting scheme during the years. Significant “increase” of natural disasters by around 1999 seems to be explained entirely by a new source of data “specialized agencies”. Specialized agencies refer to sources like e UN World Food Programme, the World Health Organization or the US National Oceanic and Atmospheric Administration. Thus, it seems that the data collection during the years has not been stable and based on scientifically stable sources.


  • EM-DAT database data is of poor quality in general
  • EM-DAT data collection methods have significantly evolved during the years rendering trend analysis totally invalid
  • UN report does not take in account the significant increase of world population, which by itself explains all increase of affected people
  • All conclusions made about the increase of natural disasters based on this database should be retracted


  1. EM-DAT, CRED / UCLouvain, Brussels, Belgium – www.emdat.be (D. Guha-Sapir)
  2. Pielke, R. (2020). Economic ‘normalisation’ of disaster losses 1998–2020: a literature review and assessmentEnvironmental Hazards, 1-19.
  3. D. Guha-Sapir D. Hargitt P. Hoyois, Thirty years of natural disasters 1974-2003: the numbers, centre for Research on the Epidemiology https://www.unisdr.org/files/1078_8761.pdf

Siberia on fire – every summer

Fire in the forest, burning trees and grass. Natural fires in Russia.

14th of July 2020 by Pasi Autio

Northern hemisphere summer – the season when forest fires in Siberia are on the loop. And usually every single new article about the Siberian forest fires somehow links them to climate change. Therefore it is good time to see how the forest fires has changed during the years. Is there really an increasing trend of Siberia forest fires as the news suggests and what is continuously predicted based on climate models?

With an area of 13.1 million square kilometres (5,100,000 sq mi), Siberia accounts for 77% of Russia’s land area. Majority of the Siberia is sparsely inhabited wilderness with little or no roads. Therefore, what sets on fire, usually burns until rain or other natural factor ends the fire. Southern Siberia also has extensive logging.

Getting reliable fire area data based on available literature seems to be problematic. According to the literature (1) USSR-era fire area data is unreliable and was consistently and severely underreporting fires on sparsely populated areas due to incomplete reporting structure that left most of the country unmonitored (6). The situation was improved only after western satellite data was taken in use by post-USSR Russia. But considering the size of Siberia and the fact that it is very sparsely populated, it is not wonder that no reliable data can be generated without the help of satellites. But even on satellite era some smaller fires goes undetected due to cloud cover or sensor detection limits (6).

After extensive literature study, I found no actual study providing satellite-based dataset for Siberian forest fires for post-USSR era either, which is strange considering how much coverage the Siberian forest fires have got lately. There seem to be an effort going on to create such a dataset for USSR-era years, however, by digitizing old satellite images taken since 1979, but let’s discuss that later a bit more.

Annual burned area in Siberia 1997-2016

Earlier essay I published (topic was Australian bushfires) made use of satellite data based on Giglio et al 2013. Giglio’s paper describes a fourth generation Global Fire Emissions Database (GFED4). This data set combines satellite records like the 500m MODIS burned area maps with active fire data from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) family of sensors. This is excellent source to create a dataset also for Siberian fires.

The data is available at globalfiredata.org. Site provides a great analysis tool and of course the data itself, if you want to analyze it further. Currently the dataset provides burned area data for the years 1997-2016. It’s possible to select a region or country and choose several options about the source data from emissions to burned area (among others). The Analysis tools section also gives ability to use custom area shape definition. And that’s what I use to create my Siberia forest fire area dataset.

Figure: Definition of Siberia in use with the presented dataset

The area shapefile used tries to mimic greatest extent of Siberia area definition as closely as possible.

Figure: Siberia annual burned area km2

Figure provides the total burned area in Siberia for each year between 1997 and 2016 in km2. We can see that for last 20 years the burned area trend for Siberia is slightly downwards. No evidence whatsoever can be seen for fires getting any worse. The average burned area annually during that period was ~ 91181 km2 – about the size of Maine.

Years 1998, 2003, 2008 and 2012 were the four most severe fire seasons during this period. In general the inter-annual variability is great (3) with up to 4x differences between years. Forest fires during 2003 were ~ 203288 km2.

USSR-era burned area data

While studying the available literature I found that Stocks and Cahoon had started (ca 2010) a project (3) to digitize old AVHRR satellite images from the period 1979-2000 to build a satellite-based fire-area product for Siberia. This seems to have taken a while since the results of this work has nowhere to be found. The former student of Cahoon, Soja A.J., seems to have continued with this work (4) with Cahoon and Stocks and has presented the results in several conferences during 2018 and 2019. I asked the author whether the data is available for public consumption, but the according to the answer the data is still under validation.

The data is based on different (less sophisticated) instruments, algorithms and methods than GFED4 dataset presented above. Therefore it makes no sense to compare these datasets directly. But for purposes of finding out whether the Siberia forest fires have been getting worse, comparing the trends is interesting. Also, the datasets contain four overlapping years (1997-2000) and using these as a reference we can conclude that burned area on years 1985 and 1987 exceed 1998 and are among the most severe seasons during the satellite era.

The data presented in the conference (4) shows no increasing trend for Siberia burned area either.

In summary when we combine the AVHRR and GFED4 datasets we have 37 years (1979-2016) of burned area data for Siberia. During that time no increasing trend for the forest fires and no detectable signal for “climate change” can be found.

2020 Season fires

As usual, the news outlets are providing worrying stories about the forest fires in Siberia for this season. Greenpeace Russia has provided this piece of information (7):

Greenpeace Russia’s forest programme, which analyses satellite data, said Saturday that a total of 9.26 million hectares—greater than the size of Portugal—have been impacted by wildfires since the beginning of 2020.”

Sounds bad. But how does this 9.26 million hectares (92600 km2) compare to earlier years? Once again, globalfiredata.org Analysis tool provides us this information. Cumulative burned area for Siberia from January to the end of June for selected years in the past:

  • 2003: 15.4 Mha (154205 km2)
  • 2008: 15.5 Mha (155114 km2)

If data provided by Greenpeace is correct (no source to verify it), the start of the 2020 fire season in Siberia has been one of the worst since 1997, but in no means the record.


  • Siberian forest fires are extensive every summer with up to ~4x variations between the years
  • Average burned area for the Siberia is ~ 91000 km2 / 9.1 Mha / 35200 sq miles – about the size of Portugal
  • Contrary to the climate model predictions, no increased burned area can be found during 1979-2016 for Siberia

Further reading

Russia’s Forests Dominating Forest Types and Their Canopy Density:



  1. Giglio, L., J. T. Randerson, and G. R. van der Werf (2013), Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4),J. Geophys. Res. Biogeosci.,118, 317–328, doi:10.1002/jgrg.20042.
  2. Giglio, L., Boschetti, L., Roy, D.P., Humber, M.L., Justice, C.O., 2018. The collection 6 MODIS burned area mapping algorithm and product. Remote Sens. Environ. 217,72–85. https://doi.org/10.1016/j.rse.2018.08.005.
  3. Stocks, Cahoon 2010; Reconstructing Post-1979 Forest Fire Activity and Area Burned in Russia: NOAA AVHRR Analysis https://www.researchgate.net/publication/253580597_Reconstructing_Post1979_Forest_Fire_Activity_and_Area_Burned_in_Russia_NOAA_AVHRR_Analysis_Invited
  4. Historic AVHRR-derived Burned Area product and validation for Siberia (1979 – 2000) https://ui.adsabs.harvard.edu/abs/2019AGUFMGC24C..07S/abstract
  5. Vegetation fires and global change; White paper directed to UN
  6. https://eecentre.org/Modules/EECResources/UploadFile/Attachment/Vegetation-Fires-Global-Change-UN-White-Paper-GFMC-2013.pdf#page=52
  7. Nearly 300 wildfires in Siberia amid record warm weather https://phys.org/news/2020-07-wildfires-siberia-weather.html

Siberia burned area dataset generated from globalfiredata.org:

Annual Burned Area: Area 1 (units: km^2)
area, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016
Area 1, 72515.49, 156759.94, 64566.03, 71509.61, 81478.54, 91947.5, 203288.34, 48805.25, 60614.74, 102303.24, 53793.62, 183118.31, 61870.23, 67793.46, 76604.99, 124019.83, 48602.92, 95504.16, 74647.34, 83883.75

Siberia shapefile used the generate the dataset above:

{"type":"Feature","properties":{"name":"Area 1"},"geometry":{"type":"MultiPolygon","coordinates":[[[[65.126953125,69.59589006237648],[69.697265625,73.50346063726599],[78.3984375,73.77577986189993],[100.986328125,77.29320180280092],[90.263671875,79.63987399850707],[90,80.7323485464832],[93.955078125,81.55707352166368],[138.25195312499997,76.9007089258869],[180,72.39825525029977],[180,61.683092710640715],[174.90234375,60.50052541051131],[156.181640625,49.38237278700955],[144.755859375,45.82879925192134],[142.91015625,45.583289756006316],[140.2734375,45.89000815866184],[134.736328125,40.97989806962013],[129.0234375,40.245991504199026],[128.14453125,41.83682786072714],[131.044921875,43.004647127794435],[130.95703125,44.96479793033101],[132.978515625,45.213003555993964],[134.6484375,48.45835188280866],[131.044921875,47.81315451752768],[130.4296875,48.922499263758255],[127.705078125,49.61070993807422],[125.94726562499999,52.96187505907603],[123.74999999999999,53.38332836757156],[121.201171875,53.4357192066942],[119.61914062499999,50.233151832472245],[117.7734375,49.61070993807422],[114.60937499999999,50.233151832472245],[112.5,49.32512199104001],[108.720703125,49.38237278700955],[105.46875,50.45750402042058],[102.83203125,50.28933925329178],[102.48046875,51.45400691005982],[98.525390625,51.998410382390325],[97.734375,51.01375465718821],[98.173828125,50.3454604086048],[97.03125,49.724479188712984],[94.833984375,49.95121990866204],[92.28515625,50.736455137010665],[87.71484375,49.03786794532644],[83.232421875,50.90303283111257],[80.33203125,50.792047064406866],[76.46484375,54.213861000644926],[74.1796875,53.54030739150022],[70.83984375,55.07836723201515],[68.818359375,55.429013452407396],[61.34765625,53.904338156274704],[60.55664062499999,51.998410382390325],[58.71093750000001,52.3755991766591],[59.4140625,56.07203547180089],[57.39257812499999,56.07203547180089],[57.48046875,56.84897198026975],[59.23828124999999,58.6769376725869],[58.447265625,59.57885104663186],[59.150390625,60.23981116999893],[59.765625,64.88626540914477],[65.91796875,67.47492238478702],[65.126953125,69.59589006237648]]],[[[-179.99,61.685412536149016],[-179.99,72.3971767678287],[-178.2421875,72.20867825343294],[-168.57421875,66.8265202749748],[-169.453125,64.1297836764257],[-179.99,61.685412536149016]]]]}}
You can upload this shapefile to globalfiredata.org analysis tool to replicate the results in this article.

Australian bushfire season 2019-2020 – Severity and reasons in context of available data

The Australian bushfire season of 2019-2020 is now the climate topic of the year – the severe bushfire season has caused more than 2000 houses to burn in the state of New South Wales (NSW) alone. At least 34 people have died and likely over 1 billion mammals, birds and reptiles has been lost (1).

According to wikipedia pages for the 2019-2020 bushfire season (2) 18.9 million hectares of land has been burned as of 14h of January. This sounds severe, but how large is the amount of burned land when comparing to the earlier seasons?

Annual burned area in Australia

There are sources to place this bushfire season in the context like the study by Giglio at al 2013 (3). The paper describes a fourth generation Global Fire Emissions Database (GFED4). This data set combines satellite records like the 500m MODIS burned area maps with active fire data from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and the Along-Track Scanning Radiometer (ATSR) family of sensors. The paper also provides burned area data for Australia and New Zealand (combined) for the years 1997-2011.

Luckily Louis Giglio and his team have continued to work and have created excellent source of all burned area and fire-based emissions datasets. MODIS Collection 6 (C6) MCD64A1 burned area dataset (4) provides satellite-based burned area data for all continents – and also for Australia.

The data and a great analysis tool are available at globalfiredata.org.The dataset provides burned area data for the years 1997-2016. It’s possible to select a continent or country and choose several options for the source data such as emission or burned area data.

Let’s start with burned area data for Australia:

Figure 1: Annual burned area in millions of hectares

Figure 1 shows the total burned area for each year between 1997 and 2016 in millions of hectares. Area burned every year was between 18.2 million hectares (2010) and 94.6 million hectares (2001). On average, the area burned during this time period was 52.9 million hectares. Since there is 769 million hectares of land in Australia, the area burned between 1997 and 2016 was 2.4 – 12.3 % of total land area – every year.

These figures seem very high, so let’s see were the bushfires typically happen. Giglio et al 2013 provides a view to that.

Figure 2: Mean annual area burned in Australia, Image source Giglio et al 2013 supplemental materials

Figure 2 provides Mean annual area burned in Australia, expressed as the fraction of each grid cell that burns each year, derived from the July 1996 – August 2012 monthly GFED4 burned area time series. As we can see the majority of fires are happening within the Australian northern and western territories. But overall, the fires can happen everywhere. There are fewer fires in some desert areas: like the Simpson desert. But if there is sufficient fuel load to burn, the fire seems to be likely at some point.

Thus the area burned so far during the bushfire season 2019-2020 can be placed into a context. The burned area as quoted by several sources (~ 18.9 million hectares) is ~36% of average area burned annually in Australia and exceeds the minimum burned area year in the satellite dataset (year 2010). Thus, it is likely that the quoted area is too low, since the fires in many remote areas are not reported. The real burned area during this season will eventually be available through satellite burned area datasets.

Most of the burned land areas are shrublands, woodlands and open forests. Forests fires happen mostly within eucalyptus forests (Australia’s northern and eastern shore).

The above data provides the details of area being burned in total whether it is forest, non-forest and whether the fire was planned (prescriptive burns) or non-planned. But how about the forests specifically?

Forest fires in Australia

There is another source, which provides a lot of details for forest fires specifically. Australia government’s department of Agriculture provides the “Australia’s State of the Forests Report” for every five year period. The latest one has been published in 2018 (5) and covers years 2011-2016.

This report provides details about forest fires in Australia starting with annual forest fires for seasons 2011-2012 to 2015-2016.

Figure: Annual planned and unplanned area of forest fires in Australia – millions of hectares

Unplanned forest fires burned between 8.9 million hectares (season 2013-2014) and 21.2 million hectares (2012-2013). In addition the area burned due the planned (prescriptive) burns was between 6.2 million hectares (season 2013-2014) and 8.2 million hectares (season 2011-2012).  Also we can see that this data correlates well with the satellite burned area dataset.

Earlier versions of these reports provides similar figures; for example the year 2008 version of this report says that the estimated area of forest burnt in the period from 2001 to 2006 was 24.7 million hectares; an estimated 20.0 million hectares was burnt in unplanned fires and 4.7 million hectares was burnt in planned fires. In average 15.7% of Australian forest land burned every year. According to the latest report, the total area of forest in Australia burnt one or more times during the period 2011–12 to 2015–16 was 55 million hectares (41% of Australia’s total forest area) (5). Some forests had at least one fire per year during five different years between 2011 and 2016. Thus, forest was in fire every year.

That is a lot of forest fires in one country. You would imagine that after these fires there are no forests left in Australia. But there is and according to the report, the area of forest has even increased slightly between 1990 and 2016. Most of the forested ecosystems in Australia are ecologically adapted to fire and even require it for regeneration.

For example – Eucalyptus trees do not just resist fire, they actively encourage it. Eucalyptus leaves don’t decompose and are highly flammable. Some species for these trees hold their seeds inside small capsules. Fire triggers massive drop of seeds to the ground cleaned by the forest fire (6). Due to the flammable materials generated by Eucalyptus trees, the forest fire in Eucalyptus forest is inevitable sooner or later. Sooner it happens, more controlled the fire is and less harm it will generate to the trees and animals. Avoiding fires too long is clearly not a good idea. Due to this there are a lot of planned (prescriptive burns) in Australia. Prescriptive burns are the only way of managing the volume of burnable biomass in Australian forests.

In summary, the Australian bushfire season 2019-2020 overall – despite of all the harm it has caused to lives – both for humans and animals – has not been exceptional on country level. It has not been one of the worst seasons in any metric e.g. not with the area of burned land or burned forests. But there is something special happening in New South Wales in particular.

Fires in New South Wales

Almost all the publicity regarding the 2019-2020 bushfire season in Australia has been related to the fires in New South Wales. And indeed, according to the MODIS fire count data from globalfiredata.org there is something extraordinary going in in Southeast Australia – especially in New South Wales, where the number of fires detected is about four times higher than previous records.

Figure: Eastern Australia fire counts (7)

Why the fires are so intense especially in New South Wales?

Positive Indian Ocean Dipole event

Incidentally there is an exceptional natural event going on. An exceptionally positive Indian Ocean Dipole (8) is currently ongoing (9) and has caused severe weather not only in Australia, but in Africa too (10). The event among the strongest in 60 years (12).

Why is this relevant to the extreme fires in South-East Australia? According to the study Cai et al 2009 (11) there is a systematic linkage between positive Indian Dipole events and severe fires in Southeast Australia. Almost half of most severe fires have occurred during pIOD.

Some of the studies have tried to link pIOD to the Climate Change, but so far the climate model’s ability to predict the pIOD has been less than optimal (13).

Lack of sufficient prescribed burning

According to studies, the hazardous level of fuel loads can be reached within 2 to 4 years from the low intensity prescribed burning in South East Australia (14). But the prescribed burning practices are not popular among locals. The smoke from the hazard reduction burns is a nuisance and health issue itself (15).

New South Wales has about 20 million hectares of forests and the current level of prescribed burning is ~ 200000 hectares annually. This level of prescribed burning will do little to reduce the risks of catastrophic bushfires.

But one thing is sure: the debate about the right level of prescribed burning will continue (16).


  • All-in-all the bushfire season in Australia is not abnormal for Australian scale
  • Consider Australia to be a continent of fire.
  • Most ecosystems in Australia are ecologically adapted to the fire and will even require it
  • The only effective way to manage the fire hazards in Australia is to manage the fuel loads
  • Natural Indian Ocean Dipole events (and ENSO events) has and will have the effect on droughts in Australia
  • Hazardous volume of fuel loads together with abnormally positive Indian Ocean dipole and the associated drought are the prime reasons for extreme bushfire season in Southeast Australia and especially in New South Wales during this season

Further reading

Australia’s state of forests report 1998 provides a lot of good background information about the forests and forest fires in Australia in the past.


  • Special credit to Joanne Nova for readability comments to the text and for background-checking all the references.


  1. https://www.theguardian.com/australia-news/2020/jan/07/record-breaking-49m-hectares-of-land-burned-in-nsw-this-bushfire-season
  2. https://en.wikipedia.org/wiki/2019%E2%80%9320_Australian_bushfire_season
  3. Giglio, L., J. T. Randerson, and G. R. van der Werf (2013), Analysis of daily, monthly, and annual burned area using thefourth-generation global fire emissions database (GFED4),J. Geophys. Res. Biogeosci.,118, 317–328, doi:10.1002/jgrg.20042.
  4. Giglio, L., Boschetti, L., Roy, D.P., Humber, M.L., Justice, C.O., 2018. The collection 6 MODIS burned area mapping algorithm and product. Remote Sens. Environ. 217,72–85. https://doi.org/10.1016/j.rse.2018.08.005.
  5. Australia’s State of the Forests Report 2018; https://www.agriculture.gov.au/abares/forestsaustralia/sofr
  6. https://wildfiretoday.com/2014/03/03/eucalyptus-and-fire/
  7. 2019-2020 Australian bushfire season; image credit globalfiredata.org; image and all other images used with https://creativecommons.org/licenses/by-nc-nd/4.0/
  8. http://www.bom.gov.au/climate/iod/
  9. https://www.abc.net.au/news/2019-05-16/positive-indian-ocean-dipole-bad-news-for-drought-crippled-areas/11120566
  10. https://www.bbc.com/news/science-environment-50602971
  11. Cai, W., Cowan, T., & Raupach, M. (2009). Positive Indian Ocean dipole events precondition southeast Australia bushfires. Geophysical Research Letters, 36, L19710. https://doi.org/10.1029/2009GL039902
  12. https://www.severe-weather.eu/news/unusually-strong-indian-ocean-dipole-australia-europe-fa/
  13. Cai, W., and T. Cowan, 2013: Why is the amplitude of the Indian Ocean dipole overly large in CMIP3 and CMIP5 climate models? Geophys. Res. Lett., 40, 1200–1205, https://doi.org/10.1002/grl.5020
  14. Morrison et al 1996, Conservation conflicts over burning bush in south-eastern Australiahttps://doi.org/10.1016/0006-3207(95)00098-4
  15. https://www.abc.net.au/news/2020-01-08/nsw-fires-rfs-commissioner-weights-in-on-hazard-reduction-debate/11850862
  16. https://www.abc.net.au/news/2019-12-20/hazard-reduction-burns-bushfires/11817336

Ilmastonmuutos haihduttaa Kaspianmeren – vai haihduttaako?

Ilta-Sanomat uutisoi 14.5.2019 (kaksi vuotta myöhässä) Kaspianmeren pinnan hälyyttävästä laskusta, syynä mikäs muukaan kuin ilmastonmuutos: “Ilmastonmuutos aiheuttaa Kaspianmeren altaassa hyvin nopeaa haihtumista, kertoo meribiologi Elnur Safarov. “

Uutinen perustuu AGU:ssa 21.6.2017 julkaistuun tiedeartikkeliin “Long‐term Caspian Sea level change” (1) ja tuolloin vuonna 2017 on asiasta uutisoinut jo mm. Tekniikan Maailma.

Artikkelissa on käsitelty Kaspian meren pinnan vaihtelua eri tekijöistä johtuen. Koska Kaspianmerellä ei ole lainkaan laskujokia, vaikuttaa pintaan käytännössä kaksi asiaa: Kaspianmereen laskevien jokien virtaama (josta Volga edustaa 80-90%:ia) sekä veden haihdunta. Haihduntaan liittyvät tiedot perustuvat artikkelissa täysin ilmastomalleihin, ei todellisiin mittauksiin haihdunnasta.

Ilta-Sanomien uutinen ei mainitse sanallakaan laskujokien virtaaman vaikutusta vaan antaa ymmärtää pinnan laskun johtuvan pelkästään haihdunnan kasvusta. Samasta tiedeartikkelista tehty Tekniikan maailman uutinen mainitsee myös muut esille tuodut tekijät: “Vedenpinnan laskusta noin puolet johtuu haihtumisesta, ja toinen puolikas sademäärien ja jokien virtaamien muutoksesta, tutkijat sanovat. Haihtuminen johtuu puolestaan lähes kokonaan lämpötilojen noususta.”

Eli toisin kuin Ilta-Sanomat antaa ymmärtää – jättämällä Kaspianmereen virtaavien jokien virtaamien muutokset mainitsematta – on artikkelin perusteella vain puolet veden pinnan laskusta haihdunnan aiheuttamaa.

Se minkä Ilta-Sanomat jättää myös mainitsematta on ajankohta, jolloin pinta on laskenut. IS:ää lukemalla voisi tehdä johtopäätöksen, että pinnan lasku olisi jo pitkäaikainen ongelma; mutta ei: Kaspianmeren pinta nousi jyrkästi (13cm/vuosi) vuosina 1976-1996 – siis aikana, jolloin “ilmastonmuutoksen” piti jo ilmastomallien ennusten mukaan vaikuttaa. Mutta toisaalta kun katsotaan taaksepäin historiaan, on pinta laskenut jyrkästi 1930-luvulta vuoteen 1976 – aikana, jolloin ilmastonmuutoksen ei teorioiden mukaan vielä pitänyt vaikuttaa.

Kuva Tekniikan maailman artikkelista Kaspianmeren pinnan vaihteluista

Mutta entä vuoden 1996 jälkeen? Tällöin täytyy palata paikallisiin lämpötiloihin: Artikkelin mukaan haihdunta olisi lisääntynyt lämpötilanmuutoksen vuoksi. Eli lämpötilojen olisi pitänyt nousta, jotta väite olisi järkevällä pohjalla. Lämpötilojen mittaaminen onkin helpompaa kuin haihdunnan, joten katsotaan mitä mittarit näyttävät.

Kaspianmeren ympäristöstä löytyy useita mittausasemia, joilta on saatavissa pitkäaikainen mittaussarja. Data on saatavilla NASAn sivustoilta (2).

Asemat ovat:

Mitä edellisistä asemadatoista voidaan havaita? Ne eivät korreloi aikaisemmin esitettyjen Kaspianmeren pintamuutosten kanssa lainkaan. Yhdelläkään noista asemista ei löydy vuoden 1996 jälkeen lämpenemistä, eikä etenkään sellaista lämpenemistä, joka selittäisi näin suuret haihdunnan muutokset. Mikä tämän sitten selittää, jos eivät lämpötilat? Pilvisyysmuutokset sekä jokien virtaamien muutokset.

Tästä aiheesta löytyykin erittäin hyvä paperi Arpe et al 2013 (3). Tässä on käsitelty kattavasti eri tekijöitä ja mallinnettu kunkin osuus.

Kuvassa OBS tarkoittaa havaittua pinnanvaihtelua. VOon on arvioitu pinnanvaihtelu laskemalla pelkästää Volgan virtaamasta. V+CS esittää arviota Volgan virtaaman sekä lasketun haihdunnan vaikutuksesta. +UR lisää laskentaan Ural-joen ja +SW muut pienemmät joet.

Eli tämänkin mukaan suurin yksittäinen tekijä on Volga-joen virtaama. Haihdunnan muutokset seuraavana. Ja kun tätä Arten paperia lukee, niin suurin tekijä haihdunnan muutokseen on lyhytaaltoisen auringon säteilyn vaikutus – eli käytännössä pilvisyys.

Jos mennään lisäksi tarkastelemaan virtaamia, niin näihin vaikuttaa merkittävästi myös maanviljelyn kehitys. Aral-järven kohtalon tiedämme – ja tämä kohtalo ei ole seurausta ilmastonmuutoksesta vaan Aral-järveen laskevien vesien käyttäminen (lähinnä puuvillan) kasteluun. Ihmisen vaikutusta tämäkin, mutta aivan eri ongelma kuin ilmastonmuutos.

Faktojentarkistuksen näkökulmasta opimme seuraavaa:

  • Ilta-sanomat
    • Uutisoi aiheen 2 vuotta myöhässä ja kertomatta erittäin olennaiset ja taustoittavat faktat Kaspianmeren historiallisesta pinnanvaihtelusta
    • Johtaa lukijaa pahasti harhaan jättämällä mainitsematta artikkelin kirjoittajan arvion, että vain puolet pinnanvaihtelusta johtuu haihdunnan muutoksista
  • Itse paperi
    • Ei perustele miksi pilvisyys Kaspian meren päällä olisi muuttunut nimenomaan ilmastonmuutoksen vuoksi
    • Koska näin ei tehdä, ei mitään linkkiä ilmastonmuutokseen synny
    • Muut paperit liittävät tämä muutokset ENSO-muutoksiin

(1) Long‐term Caspian Sea level change – Chen – 2017 – Geophysical Research Letters

(2) https://data.giss.nasa.gov/gistemp/stdata/

(3) Arpe et al 2013: “Prediction of the Caspian Sea level using ECMWF seasonal forecasts and reanalysis”

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