7 research outputs found
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The atmospheric aerosol over Siberia, as seen from the 300 m ZOTTO tower
This report describes a unique setup for aerosol measurements at the new long-term Tall Tower monitoring facility near Zotino, Siberia (ZOTTO). Through two inlets at 50 and 300 m aerosol particle number size distributions are measured since September 2006 in the size range 15β835 nanometer dry diameter. Until the end of May 2007 total number (N300) concentrations at 300 m height ranged between 400 cm-3 (5%) and 4000 cm-3 (95%) with a median of 1200 cm-3, which is rather high for a nearly uninhabited boreal forest region during the low productivity period of the year.
Fitting 1-h average distributions with a maximum of four lognormal functions yielded frequent ultrafine modes below 20 nm at 50 m height than at 300 m, whereas the latter height more frequently showed an aged nucleation mode near 30 nm. The positions of Aitken (β80 nm) and accumulation modes (β210 nm) were very similar at both inlet heights, the very sharp latter one being the most frequent of all modes. The encouraging first results let us expect exciting newfindings during the summer period with frequent forest fires and secondary particle sources from vegetation emissions
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The influence of land-use activities and regional drought on historical fire regimes of Buryatia, Siberia
Every year, millions of hectares burn across Siberia, driven by a combination of warming temperatures, regional drought and human-caused ignitions. Dendrochronology provides a long-term context to evaluate recent trends in fire activity and interpret the relative influence of humans and climate drivers on fire regimes. We developed a 400 year record of fire-scarred trees from 17 sites in pine-dominated forests located southeast of Lake Baikal. Site-level mean fire return intervals (MFIs) ranged from 4 to 27 years for all fires and 8 to 35 years for widespread fires within sites. Sites with the lowest MFI values were located within 1 km of agricultural fields in grassland valleys, suggesting that agricultural burning influenced MFIs at nearby sites. Fire frequency varied over the record, with significantly high values around 1790, from 1865 to 1880, 1948 to 1955 and 1995 to 2005. The increased fire activity corresponded with migration waves to the region and major socio-economic change connected with the establishment and breakdown of the Soviet Union. At broader scales, superposed epoch analysis showed that synchronous fire years were associated with regional drought and precipitation deficits. Wet conditions for 2–3 years prior to the event year were also significant, suggesting that increased moisture promoted growth of understory fine fuels to support more extensive fires across the study area. Although fire frequencies increased during the 20th century, fire–climate relationships weakened, suggesting increased human-caused ignitions may override regional climate drivers. Our dataset presents a continuous record of frequent surface fires over the past 400 years, providing a valuable opportunity to compare dendrochronology-based reconstructions with satellite and documentary records.
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Seasonal, synoptic, and diurnal-scale variability of biogeochemical trace gases and O2 from a 300-m tall tower in central Siberia
We present first results from 19 months of semicontinuous concentration measurements of biogeochemical trace gases (CO2, CO, and CH4) and O2, measured at the Zotino Tall Tower Observatory (ZOTTO) in the boreal forest of central Siberia. We estimated CO2 and O2 seasonal cycle amplitudes of 26.6 ppm and 134 per meg, respectively. An observed west-east gradient of about -7 ppm (in July 2006) between Shetland Islands, Scotland, and ZOTTO reflects summertime continental uptake of CO2 and is consistent with regional modeling studies. We found the oceanic component of the O2 seasonal amplitude (Atmospheric Potential Oxygen, or APO) to be 51 per meg, significantly smaller than the 95 per meg observed at Shetlands, illustrating a strong attenuation of the oceanic O2 signal in the continental interior. Comparison with the Tracer Model 3 (TM3) atmospheric transport model showed good agreement with the observed phasing and seasonal amplitude in CO2; however, the model exhibited greater O2 (43 per meg, 32%) and smaller APO (9 per meg, 18%) amplitudes. This seeming inconsistency in model comparisons between O2 and APO appears to be the result of phasing differences in land and ocean signals observed at ZOTTO, where ocean signals have a significant lag. In the first 2 months of measurements on the fully constructed tower (November and December 2006), we observed several events with clear vertical concentration gradients in all measured species except CO. During βcold eventsβ (below -30Β°C) in November 2006, we observed large vertical gradients in CO2 (up to 22 ppm), suggesting a strong local source. The same pattern was observed in CH4 concentrations for the same events. Diurnal vertical CO2 gradients in April to May 2007 gave estimates for average nighttime respiration fluxes of 0.04 Β± 0.02 mol C m-2 d-1, consistent with earlier eddy covariance measurements in 1999β2000 in the vicinity of the tower
ΠΡΠΈΡΠΎΠ΄Π° ΠΊΡΡΠΏΠ½ΡΡ ΠΏΠΎΠΆΠ°ΡΠΎΠ² Π² ΠΏΠΎΠ΄Π·ΠΎΠ½Π°Ρ ΡΠ°ΠΉΠ³ΠΈ Π¦Π΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡΠΈ
The work deals with the nature of large wildfires, conditions of their occurrence and distribution in the
taiga of Central Siberia. The large fires in this region occur during periods of prolonged and intense
drought, with precipitation deficit more than 60 % of the norm. Vegetation and climate conditions of
large fires are identified and map of their distribution is compiled using satellite information. Fire
seasons scenarios are examined, and an iterative model for short-term forecasting of extreme fire
situations is proposed. Methodology for short-term forecasting of large wildfires risk is offered based
on satellite data simultaneously on the whole territory of Central SiberiaΠ ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ Π²ΠΎΠΏΡΠΎΡΡ ΠΏΡΠΈΡΠΎΠ΄Ρ ΠΏΠΎΠΆΠ°ΡΠΎΠ², ΡΡΠ»ΠΎΠ²ΠΈΡ ΠΈΡ
Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ ΠΈ
ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Π² ΠΏΠΎΠ΄Π·ΠΎΠ½Π°Ρ
ΡΠ°ΠΉΠ³ΠΈ Π¦Π΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡΠΈ. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΊΡΡΠΏΠ½ΡΠ΅ ΠΏΠΎΠΆΠ°ΡΡ Π²
ΡΡΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π²ΠΎΠ·Π½ΠΈΠΊΠ°ΡΡ Π² ΠΏΠ΅ΡΠΈΠΎΠ΄Ρ Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΡΡ
Π·Π°ΡΡΡ
Ρ Π½Π΅Π΄ΠΎΠ±ΠΎΡΠΎΠΌ ΠΎΡΠ°Π΄ΠΊΠΎΠ² Π±ΠΎΠ»Π΅Π΅
60 % ΠΎΡ Π½ΠΎΡΠΌΡ. ΠΡΡΠ²Π»Π΅Π½Ρ ΡΠ°ΡΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΊΡΡΠΏΠ½ΡΡ
ΠΏΠΎΠΆΠ°ΡΠΎΠ² ΠΈ ΡΠΎΡΡΠ°Π²Π»Π΅Π½Π° ΠΊΠ°ΡΡΠ° ΠΈΡ
ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠΎ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΠΏΠΎ ΠΊΠΎΡΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ.
Π Π°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΡΡΠ΅Π½Π°ΡΠΈΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠΎΠΆΠ°ΡΠΎΠΎΠΏΠ°ΡΠ½ΡΡ
ΡΠ΅Π·ΠΎΠ½ΠΎΠ², ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ ΠΈΡΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ
ΠΊΡΠ°ΡΠΊΠΎΡΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΡΡΡΠ΅ΠΌΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠΎΠΆΠ°ΡΠΎΠΎΠΏΠ°ΡΠ½ΠΎΠΉ ΠΎΠ±ΡΡΠ°Π½ΠΎΠ²ΠΊΠΈ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ°
ΠΊΡΠ°ΡΠΊΠΎΡΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·Π° ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ Π»Π°Π½Π΄ΡΠ°ΡΡΠ½ΡΡ
ΠΏΠΎΠΆΠ°ΡΠΎΠ² ΠΏΠΎ ΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΡΠΌ
Π΄Π°Π½Π½ΡΠΌ ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ Π½Π° Π²ΡΠ΅ΠΉ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ Π¦Π΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡ
ΠΡΠΈΡΠΎΠ΄Π° ΠΊΡΡΠΏΠ½ΡΡ ΠΏΠΎΠΆΠ°ΡΠΎΠ² Π² ΠΏΠΎΠ΄Π·ΠΎΠ½Π°Ρ ΡΠ°ΠΉΠ³ΠΈ Π¦Π΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡΠΈ
The work deals with the nature of large wildfires, conditions of their occurrence and distribution in the
taiga of Central Siberia. The large fires in this region occur during periods of prolonged and intense
drought, with precipitation deficit more than 60 % of the norm. Vegetation and climate conditions of
large fires are identified and map of their distribution is compiled using satellite information. Fire
seasons scenarios are examined, and an iterative model for short-term forecasting of extreme fire
situations is proposed. Methodology for short-term forecasting of large wildfires risk is offered based
on satellite data simultaneously on the whole territory of Central SiberiaΠ ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ Π²ΠΎΠΏΡΠΎΡΡ ΠΏΡΠΈΡΠΎΠ΄Ρ ΠΏΠΎΠΆΠ°ΡΠΎΠ², ΡΡΠ»ΠΎΠ²ΠΈΡ ΠΈΡ
Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ ΠΈ
ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Π² ΠΏΠΎΠ΄Π·ΠΎΠ½Π°Ρ
ΡΠ°ΠΉΠ³ΠΈ Π¦Π΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡΠΈ. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΊΡΡΠΏΠ½ΡΠ΅ ΠΏΠΎΠΆΠ°ΡΡ Π²
ΡΡΠΎΠΌ ΡΠ΅Π³ΠΈΠΎΠ½Π΅ Π²ΠΎΠ·Π½ΠΈΠΊΠ°ΡΡ Π² ΠΏΠ΅ΡΠΈΠΎΠ΄Ρ Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈ ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΡΡ
Π·Π°ΡΡΡ
Ρ Π½Π΅Π΄ΠΎΠ±ΠΎΡΠΎΠΌ ΠΎΡΠ°Π΄ΠΊΠΎΠ² Π±ΠΎΠ»Π΅Π΅
60 % ΠΎΡ Π½ΠΎΡΠΌΡ. ΠΡΡΠ²Π»Π΅Π½Ρ ΡΠ°ΡΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΠΈ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΊΡΡΠΏΠ½ΡΡ
ΠΏΠΎΠΆΠ°ΡΠΎΠ² ΠΈ ΡΠΎΡΡΠ°Π²Π»Π΅Π½Π° ΠΊΠ°ΡΡΠ° ΠΈΡ
ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠΎ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΠΏΠΎ ΠΊΠΎΡΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ.
Π Π°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΡΡΠ΅Π½Π°ΡΠΈΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠΎΠΆΠ°ΡΠΎΠΎΠΏΠ°ΡΠ½ΡΡ
ΡΠ΅Π·ΠΎΠ½ΠΎΠ², ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ ΠΈΡΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½Π°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ
ΠΊΡΠ°ΡΠΊΠΎΡΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΊΡΡΡΠ΅ΠΌΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠΎΠΆΠ°ΡΠΎΠΎΠΏΠ°ΡΠ½ΠΎΠΉ ΠΎΠ±ΡΡΠ°Π½ΠΎΠ²ΠΊΠΈ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ°
ΠΊΡΠ°ΡΠΊΠΎΡΡΠΎΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΠ·Π° ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ Π²ΠΎΠ·Π½ΠΈΠΊΠ½ΠΎΠ²Π΅Π½ΠΈΡ Π»Π°Π½Π΄ΡΠ°ΡΡΠ½ΡΡ
ΠΏΠΎΠΆΠ°ΡΠΎΠ² ΠΏΠΎ ΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΡΠΌ
Π΄Π°Π½Π½ΡΠΌ ΠΎΠ΄Π½ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎ Π½Π° Π²ΡΠ΅ΠΉ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ Π¦Π΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π‘ΠΈΠ±ΠΈΡ