Thaw subsidence and frost heave caused by 2018-20 forest fires around Batagay: validation with multiple InSAR data and field observation

2021 ◽  
Author(s):  
Kazuki Yanagiya ◽  
Masato Furuya ◽  
Go Iwahana ◽  
Petr Danilov
Keyword(s):  
Forest Fires ◽  
Field Observation ◽  
Ground Deformation ◽  
Frost Heave ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Fire Scar ◽  
Before And After ◽  
Surface Vegetation

<p>The Arctic has experienced numerous fires in last year, and from June to August 2020, satellite data showed record carbon dioxide emissions from forest fires. Peatland in the Arctic contains large amounts of organic carbon, and their release into the atmosphere can create positive feedbacks for further increase of air temperature. In addition, forest fires burn the surface vegetation layer that has been acting as a heat insulator, which will accelerate the thawing of permafrost on scales of years to decades. Although the thaw depth can recover together with the recovery of surface vegetation, the massive segregated ice is not recoverable once it melted. Our study area is around the Batagay, Sakha Republic, Eastern Siberia. In June 2020, Verkhoyansk, located about 55 km west of Batagay, recorded the highest daily maximum temperature of 38.0 degrees Celcius. The Sentinel-2 optical satellite images showed a number of forest fires in 2019-20. We detected the surface deformation signals at each fire site with the remote-sensing method called InSAR (Interferometric Synthetic Aperture Radar). Also, we conducted a field observation in September 2019 for validations: 1) installed a soil thermometer and soil moisture meter; 2) established a reference point for leveling and first survey; 3) measured the thawing depth with a frost probe.</p><p> For seasonal ground deformations immediately after the fire, we mainly analyzed Sentinel-1 images. Sentinel-1 is the ESA's C-band SAR satellite, which has a short imaging interval of 12 days. As the short wavelength, vegetation changes lost coherence, and some pairs failed to detect ground deformation signals immediately after the fire. However, after the end of September, we detected displacements toward the satellite line-of-sight direction at all the fire sites. It indicates uplift signals due presumably to frost heave at the fire scar. For long-term deformations over one year, we used ALOS2 imaged derived by JAXA's L band SAR satellite. In the previous studies in Alaska, the ground deformation signal immediately after a fire could not be detected due to the coherence loss in the pairs derived from pre-fire and post-fire SAR images. Indeed, we could not detect deformation signals at the fire scars from the June pairs derived before and after the fire. However, the January pairs and March pairs, both of which were acquired before and after the fire, showed relatively high coherence even in the fire scar and indicated clear subsidence signals by as much as 15 cm. We interpret that, because the studied Verkhoyansk Basin is very dry and has little snow cover, the microwaves could penetrate the snow layer, which allowed us to detect deformation signals even in winter. Yanagiya and Furuya (2020) validated the consistency of the winter uplift signal for the 2014 fire site. We also analyzed the SM1 high spatial resolution mode (3 m) ALOS2 InSAR to investigate the specific ground deformation at each fire site.</p>

scholarly journals Projections of Twenty-First-Century Climate Extremes for Alaska via Dynamical Downscaling and Quantile Mapping

2017 ◽  
Vol 56 (9) ◽  
pp. 2393-2409 ◽  
Author(s):  
Rick Lader ◽  
John E. Walsh ◽  
Uma S. Bhatt ◽  
Peter A. Bieniek
Keyword(s):  
Climate Change ◽  
Dynamical Downscaling ◽  
Climate Extremes ◽  
First Century ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Quantile Mapping ◽  
Temperature And Precipitation ◽  
Twenty First Century

AbstractClimate change is expected to alter the frequencies and intensities of at least some types of extreme events. Although Alaska is already experiencing an amplified response to climate change, studies of extreme event occurrences have lagged those for other regions. Forced migration due to coastal erosion, failing infrastructure on thawing permafrost, more severe wildfire seasons, altered ocean chemistry, and an ever-shrinking season for snow and ice are among the most devastating effects, many of which are related to extreme climate events. This study uses regional dynamical downscaling with the Weather Research and Forecasting (WRF) Model to investigate projected twenty-first-century changes of daily maximum temperature, minimum temperature, and precipitation over Alaska. The forcing data used for the downscaling simulations include the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; 1981–2010), Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), historical (1976–2005), and GFDL CM3 representative concentration pathway 8.5 (RCP8.5; 2006–2100). Observed trends of temperature and sea ice coverage in the Arctic are large, and the present trajectory of global emissions makes a continuation of these trends plausible. The future scenario is bias adjusted using a quantile-mapping procedure. Results indicate an asymmetric warming of climate extremes; namely, cold extremes rise fastest, and the greatest changes occur in winter. Maximum 1- and 5-day precipitation amounts are projected to increase by 53% and 50%, which is larger than the corresponding increases for the contiguous United States. When compared with the historical period, the shifts in temperature and precipitation indicate unprecedented heat and rainfall across Alaska during this century.

scholarly journals Evaporative cooling over the Tibetan Plateau induced by vegetation growth

2015 ◽  
Vol 112 (30) ◽  
pp. 9299-9304 ◽  
Author(s):  
Miaogen Shen ◽  
Shilong Piao ◽  
Su-Jong Jeong ◽  
Liming Zhou ◽  
Zhenzhong Zeng ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Evaporative Cooling ◽  
Growing Season ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
The Tibetan Plateau ◽  
Vegetation Activity

In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

Relationship of the severity of Septoria tritici blotch of wheat to sowing time, rainfall at heading and average susceptibility of wheat cultivars in the area

1990 ◽  
Vol 41 (2) ◽  
pp. 307 ◽  
Author(s):  
GM Murray ◽  
RH Martin ◽  
BR Cullis
Keyword(s):  
New South ◽  
Septoria Tritici Blotch ◽  
Septoria Tritici ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Wheat Cultivars ◽  
South Wales ◽  
Before And After ◽  
Rainy Days

The severity of epidemics of Septoria tritici blotch (STB) in wheat, caused by Mycosphaerella graminicola, was recorded for a 38-year period at Temora in southern New South Wales. The disease was rated as severe in 11 years, moderate in 11 and nil to light in 15, while very wet conditions prevented sowing in one year. The correlation of disease severity (S, where 0 =nil, 7 =very severe) with environmental and management factors was examined: the correlation was positive with days from sowing to heading and with rainfall ( R-4W , R+4W, mm) and the number of rainy days in the 4-week periods before and after heading; negative with the time of sowing (DS, day of year) and with mean daily maximum temperature in the 4-week periods before and after heading. Days from sowing to heading were negatively correlated with sowing day, and rainy days and mean daily maximum temperature were correlated with total rainfall in the same time period. Addition of these terms did not significantly improve the prediction of severity. The cumulative sum of the recursive residuals from this regression showed a trend with time that was associated with the average susceptibility (SAV, where 1 =highly resistant, 7 =extremely susceptible) of wheat cultivars to STB grown in the district in the previous year. The second model showed that the reduction of the average susceptibility of cultivars grown in an area will reduce the severity of STB. It provided justification for minimum disease standards for cultivars to be grown where STB is potentially severe. Further, it explained the distribution of severity of STB in New South Wales.

scholarly journals Variability of Extreme Temperature in the Arctic - Observation and RCM

2010 ◽  
Vol 4 (1) ◽  
pp. 126-136 ◽  
Author(s):  
Heidrun Matthes ◽  
Annette Rinke ◽  
Klaus Dethloff
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Growing Degree Days ◽  
Degree Days ◽  
Warm Spell ◽  
Era40 Data

This paper discusses results of a simulation with the regional climate model HIRHAM for 1958-2001, driven by the ECMWF reanalysis (ERA40) data over the Arctic domain. The aim is to analyze the ability of the model to capture certain features of climate extremes derived from daily mean, maximum and minimum temperatures. For this purpose, a range of climate indices (frost days, cold and warm spell days, growing degree days and growing season length) was calculated from the model output as well as from ERA40 data and region-specific station data for Eastern and Western Russian Arctic for comparison. It is demonstrated that the model captures the main features in the spatial distribution and temporal development of most indices well. Though systematic deviations in the seasonal means occur in various indices (frost days, growing degree days), variability and trends are well reproduced. Seasonal mean patterns in frost days are reproduced best, though the model persistently calculates too many frost days. Seasonal means of cold and warm spell days are reproduced without systematic biases, though deviations occur in summer for cold spells and in spring and summer for warm spells due to an early spring warming in the regional climate model and a low variability of the daily maximum temperature over sea ice.

Factor Analytic Models of Bioclimate for Canadian Forest Regions

1974 ◽  
Vol 4 (4) ◽  
pp. 536-548 ◽  
Author(s):  
Wayne S. Miller ◽  
Allan N. Auclair
Keyword(s):  
Computer Experiments ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Mean Annual Precipitation ◽  
Daily Maximum ◽  
Mean Annual Temperature ◽  
Coastal Forests ◽  
Model Based ◽  
Forest Regions

Relational models of bioclimate were formulated for 90 Canadian forest sections defined by J. S. Rowe in 1972. Models were based on component solutions for correlations among climatic attributes believed to be important in tree growth and reproduction. In addition, computer experiments were attempted to find remedial solutions to problems of model resolution and R/Q-mode equivalence.An attribute model based on physiographic and climatic variables was characterized by mean annual temperature, mean annual precipitation, and July average daily maximum temperature. These factors accounted for 57, 18, and 12% of the total variation on components I, II, and III, respectively.A station model based on weighted factor scores of climatic attributes alone gave a consistent and realistic separation of major forest regions. The first component distinguished Boreal forest from Pacific Coastal, Acadian, and to a lesser degree Great Lake – St. Lawrence forest regions. The second component differentiated Columbian, Grassland, and Montane regions from the Boreal maritime and Pacific Coastal forests. In addition to this generalized model, analysis of a qualitative dataset derived to help overcome problems of nonlinearity in the original data was able to identify the mean summer position of the arctic polar front and a regional low pressure locus over central Alberta.Cluster analysis of forest stations was employed to illustrate the utility of factor models. Limitations and forest applications of our results are discussed.

scholarly journals Frequency of Ice Days at Selected Meteorological Stations in Svalbard

2013 ◽  
Vol 6 (1) ◽  
pp. 81-97 ◽  
Author(s):  
Ewa Łupikasza ◽  
Tadeusz Niedźwiedź
Keyword(s):  
Atmospheric Circulation ◽  
Correlation Coefficients ◽  
The Arctic ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Circulation Index ◽  
Atlantic Sector ◽  
Maximum Air Temperature

Abstract The paper aims to present research into both the long-term variability in the ice days in Svalbard representing the Atlantic sector of the Arctic, and their relations to atmospheric circulation. Ice days are defined as days with a daily maximum temperature below 0°C (Tmax<0°C). They are considered to be amongst the most important indices of current climate change. All the available data on daily maximum air temperature from three Norwegian stations (Svalbard Airport (Svalbard Lufthavn), Bjørnøya and Hopen) and from the Polish Polar Station in Hornsund (SW Spitsbergen) have been employed. The relevance of atmospheric circulation to the frequency of the occurrence of ice days was evaluated by calculating the Spearman correlation coefficients between the frequency of ice days and three regional circulation indices: zonal westerly circulation index (W), meridional southerly circulation index (S) and index of cyclonicity (C). At all the stations the number of ice days exhibited significant decreasing trends in the period of 1979-2012.

scholarly journals Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily J. Wilkins ◽  
Peter D. Howe ◽  
Jordan W. Smith
Keyword(s):  
National Park ◽  
National Park Service ◽  
Spatial Behavior ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Daily Weather ◽  
Visitor Behavior ◽  
Park Service ◽  
The Impact

AbstractDaily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

Flake Dispersal Experiments: Noncultural Transformation of the Archaeological Record

1983 ◽  
Vol 48 (3) ◽  
pp. 553-572 ◽  
Author(s):  
Peter M. Bowers ◽  
Robson Bonnichsen ◽  
David M. Hoch
Keyword(s):  
Human Activity ◽  
Time Lapse ◽  
Primary Factor ◽  
Frost Heave ◽  
The Arctic ◽  
Archaeological Sites ◽  
Archaeological Record ◽  
Alaska Range ◽  
Natural Processes ◽  
Present Test

Time lapse studies of frost action effects on arctic and subarctic surficial archaeological sites have been conducted from 1973 to the present. Test plots of experimentally produced flakes were constructed in 1973 in the Tangle Lakes Region of the Central Alaska Range and subsequently remapped and photographed in 1974, 1976, and 1980. Similar test plots were laid out in the arctic foothills province of the Brooks Range. Observations made during the study period include: (1) flake displacements of as much as 20 cm/yr; (2) average minimum movement is 4 cm/yr; and (3) upslope movements were observed, suggesting that slope is not the primary factor in flake displacements. Frost heave, needle ice and, possibly, wind appear to be the dominant forces responsible for dispersals. It is argued that these and other natural processes can restructure the archaeological record into patterns that easily can be mistaken for those produced by human activity.

scholarly journals Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada

2014 ◽  
Vol 53 (9) ◽  
pp. 2148-2162 ◽  
Author(s):  
Bárbara Tencer ◽  
Andrew Weaver ◽  
Francis Zwiers
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Negative Consequences ◽  
Temperature And Precipitation ◽  
Joint Occurrence

AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.

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