scholarly journals Observations and modelling of algal growth on a snowpack in northwest Greenland

2017 ◽  
Author(s):  
Yukihiko Onuma ◽  
Nozomu Takeuchi ◽  
Sota Tanaka ◽  
Naoko Nagatsuka ◽  
Masashi Niwano ◽  
...  
Keyword(s):  
Algal Blooms ◽  
Meteorological Data ◽  
Algal Growth ◽  
Data Sets ◽  
Snow Surface ◽  
Snow Algae ◽  
Alpine Regions ◽  
Air Temperatures ◽  
Algal Abundance ◽  
Study Sites

Abstract. Snow algal bloom is a common phenomenon on melting snowpacks in polar and alpine regions and can substantially increase melting rates of the snow due to the effect of albedo reduction on the snow surface. In order to reproduce algal growth on the snow surface using a numerical model, temporal changes in snow algal abundance were investigated on the Qaanaaq Glacier in northwest Greenland from June to August 2014. Snow algae first appeared at the study sites in late June, which was approximately 94 hours after air temperatures exceeded the melting point. Algal abundance increased exponentially after the appearance, but the increasing rate became slow after late July, and finally reached 3.5 × 107 cells m-2 in early August. We applied a logistic model to the algal growth curve and found that the algae could be reproduced with an initial cell concentration of 6.9 × 102 cells m-2, a growth rate of 0.42 d-1, and a carrying capacity of 3.5 × 107 cells m-2 on this glacier. This model has the potential to simulate algal blooms from meteorological data sets and to evaluate their impact on the melting of seasonal snowpacks and glaciers.

scholarly journals Observations and modelling of algal growth on a snowpack in north-western Greenland

2018 ◽  
Vol 12 (6) ◽  
pp. 2147-2158 ◽  
Author(s):  
Yukihiko Onuma ◽  
Nozomu Takeuchi ◽  
Sota Tanaka ◽  
Naoko Nagatsuka ◽  
Masashi Niwano ◽  
...  
Keyword(s):  
Algal Blooms ◽  
Meteorological Data ◽  
Algal Growth ◽  
Snow Surface ◽  
Snow Algae ◽  
Alpine Regions ◽  
Air Temperatures ◽  
Algal Abundance ◽  
Study Sites ◽  
North Western

Abstract. Snow algal bloom is a common phenomenon on melting snowpacks in polar and alpine regions and can substantially increase snow melt rates due to the effect of albedo reduction on the snow surface. In order to reproduce algal growth on the snow surface using a numerical model, temporal changes in snow algal abundance were investigated on the Qaanaaq Glacier in north-western Greenland from June to August 2014. Snow algae first appeared at the study sites in late June, which was approximately 94 h after air temperatures exceeded the melting point. Algal abundance increased exponentially after this appearance, but the increasing rate became slow after late July, and finally reached 3.5 × 107 cells m−2 in early August. We applied a logistic model to the algal growth curve and found that the algae could be reproduced with an initial cell concentration of 6.9 × 102 cells m−2, a growth rate of 0.42 d−1, and a carrying capacity of 3.5 × 107 cells m−2 on this glacier. This model has the potential to simulate algal blooms from meteorological data sets and to evaluate their impact on the melting of seasonal snowpacks and glaciers.

Season and ambient air temperature influence the distribution of mites (Proctophyllodes stylifer) across the wings of blue tits (Parus caeruleus)

2000 ◽  
Vol 78 (8) ◽  
pp. 1397-1407 ◽  
Author(s):  
P R Wiles ◽  
J Cameron ◽  
J M Behnke ◽  
I R Hartley ◽  
F S Gilbert ◽  
...  
Keyword(s):  
Air Temperature ◽  
Meteorological Data ◽  
Ambient Air ◽  
Parus Caeruleus ◽  
Wing Feather ◽  
Ambient Air Temperature ◽  
Air Temperatures ◽  
West Midlands ◽  
Study Sites ◽  
Blue Tits

Changes in the distribution of the wing-feather mite Proctophyllodes stylifer (Buckholz 1869) on the flight feathers of blue tits (Parus caeruleus) were studied throughout the seasons and in relation to ambient air temperature at three combinations of study sites (Lancashire, West Midlands, and South Midlands). We tested the hypotheses that the distribution of mites is influenced in part by season and ambient air temperature. In the winter months mites clustered predominantly on the tertiary feathers, whereas in late spring, summer, and autumn, mite-infestation scores were higher on the proximal primary and secondary feathers. Three approaches were employed to determine whether this seasonal redistribution of mites arose as a response to changes in microclimate, probably ambient air temperature, rather than to season per se. Firstly, meteorological data for the Lancashire study sites, and our own monitoring of the precise air temperature at the time of handling and inspection at the West Midlands study sites, enabled us to establish a link between distribution pattern and ambient temperature. Secondly, limited observations on the distribution of mites on birds recaptured when ambient air temperatures differed by 5°C or more between first and second nettings, one temperature being below 10°C and the other above, supported the idea that the change in distribution was associated with air temperature. Finally, the results of a small experiment in which heavily infested birds caught on a day when air temperatures ranged from 9 to 11°C were taken indoors and temporarily subjected to a higher ambient air temperature (20 min) prior to re-inspection and release also confirmed that mite movement was associated with the temperature of their environment. We conclude that the seasonal changes in distribution were driven by microclimatic changes, in part by temperature.

scholarly journals Bioavailability of Mineral-Bound Iron to a Snow Algal-Bacterial Coculture and Implications for Albedo-Altering Snow Algal Blooms

2018 ◽  
Vol 84 (7) ◽  
Author(s):  
Z. R. Harrold ◽  
E. M. Hausrath ◽  
A. H. Garcia ◽  
A. E. Murray ◽  
O. Tschauner ◽  
...  
Keyword(s):  
Growth Rate ◽  
Algal Blooms ◽  
Mineral Dust ◽  
Algal Growth ◽  
16S Rrna Genes ◽  
Rrna Genes ◽  
Control Analysis ◽  
Content Type ◽  
Snow Albedo ◽  
Snow Algae

ABSTRACTSnow algae can form large-scale blooms across the snowpack surface and near-surface environments. These pigmented blooms can decrease snow albedo and increase local melt rates, and they may impact the global heat budget and water cycle. Yet, the underlying causes for the geospatial occurrence of these blooms remain unconstrained. One possible factor contributing to snow algal blooms is the presence of mineral dust as a micronutrient source. We investigated the bioavailability of iron (Fe)-bearing minerals, including forsterite (Fo90, Mg1.8Fe0.2SiO4), goethite, smectite, and pyrite as Fe sources for aChloromonas brevispina-bacterial coculture through laboratory-based experimentation. Fo90was capable of stimulating snow algal growth and increased the algal growth rate in otherwise Fe-depleted cocultures. Fo90-bearing systems also exhibited a decrease in the ratio of bacteria to algae compared to those of Fe-depleted conditions, suggesting a shift in microbial community structure. TheC. brevispinacoculture also increased the rate of Fo90dissolution relative to that of an abiotic control. Analysis of 16S rRNA genes in the coculture identifiedGammaproteobacteria,Betaproteobacteria, andSphingobacteria, all of which are commonly found in snow and ice environments. Archaea were not detected.CollimonasandPseudomonas, which are known to enhance mineral weathering rates, comprised two of the top eight (>1%) operational taxonomic units (OTUs). These data provide unequivocal evidence that mineral dust can support elevated snow algal growth under otherwise Fe-depleted growth conditions and that snow algal microbial communities can enhance mineral dissolution under these conditions.IMPORTANCEFe, a key micronutrient for photosynthetic growth, is necessary to support the formation of high-density snow algal blooms. The laboratory experiments described herein allow for a systematic investigation of the interactions of snow algae, bacteria, and minerals and their ability to mobilize and uptake mineral-bound Fe. Results provide unequivocal and comprehensive evidence that mineral-bound Fe in Fe-bearing Fo90was bioavailable toChloromonas brevispinasnow algae within an algal-bacterial coculture. This evidence includes (i) an observed increase in snow algal density and growth rate, (ii) decreased ratios of bacteria to algae in Fo90-containing cultures relative to those of cultures grown under similarly Fe-depleted conditions with no mineral-bound Fe present, and (iii) increased Fo90dissolution rates in the presence of algal-bacterial cocultures relative to those of abiotic mineral controls. These results have important implications for the role of mineral dust in supplying micronutrients to the snow microbiome, which may help support dense snow algal blooms capable of lowering snow albedo and increasing snow melt rates on regional, and possibly global, scales.

Relationship between flowering phenology of perennial herbs and meteorological data in deciduous forests of Sweden

1996 ◽  
Vol 74 (4) ◽  
pp. 528-537 ◽  
Author(s):  
Martin Diekmann
Keyword(s):  
Deciduous Forest ◽  
Reference Model ◽  
Meteorological Data ◽  
Flowering Phenology ◽  
Data Sets ◽  
Base Temperature ◽  
Degree Days ◽  
Data Set ◽  
Air Temperatures ◽  
Full Flowering

The relationship between flowering phenology and meteorological measurements, in particular air temperature, was studied for 29 herbaceous species in four areas of deciduous forest near Uppsala, Sweden. Altogether 16 models were tested for their accuracy of predicting flowering. These were cumulative sum models based on the heat unit concept of an accumulation of (modified) temperatures above a threshold base temperature from a chosen starting date. Average temperature was tested as an alternative method. All models were first applied to a data set from the years 1990 to 1992 and then to an independent test data set from 1993. The accumulation of daily mean air temperatures (degree-days) above 5 °C from January 1 was chosen as the basic reference model. Despite its simplicity, it was a very accurate model in predicting flowering for these species. Only two models were superior to the reference model in both data sets: the summation of degree hours instead of degree-days from optimized starting dates for each species, and the addition of photoperiod (daylength) to daily mean temperature. In general, the models performed better for the late-flowering species than for the early-flowering species. The accuracy of the models was partly dependent on the actual course of temperature accumulation in a year. Keywords: degree-days, full flowering, photoperiod, solar radiation, temperature sum.

Selection of water source for water transfer based on algal growth potential to prevent algal blooms

2021 ◽  
Vol 103 ◽  
pp. 246-254
Author(s):  
Yongjun Song ◽  
Jing Qi ◽  
Le Deng ◽  
Yaohui Bai ◽  
Huijuan Liu ◽  
...  
Keyword(s):  
Algal Blooms ◽  
Algal Growth ◽  
Water Source ◽  
Water Transfer ◽  
Growth Potential ◽  
Algal Growth Potential ◽  
Selection Of

scholarly journals Model – TCCON comparisons of column-averaged methane with a focus on the stratosphere

2016 ◽  
Author(s):  
Andreas Ostler ◽  
Ralf Sussmann ◽  
Prabir K. Patra ◽  
Sander Houweling ◽  
Marko De Bruine ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Meteorological Data ◽  
Michelson Interferometer ◽  
Total Carbon ◽  
Data Sets ◽  
Transport Models ◽  
Improved Model ◽  
The Impact ◽  
Chemistry Experiment

Abstract. The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model-TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. In comparison to simulated model fields we find an improved model-TCCON XCH4 agreement for all models with MIPAS-based stratospheric CH4 fields. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 ppb to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 ppb to 4.3 ppb), and LMDz (Laboratoire de Météorologie Dynamique model with Zooming capability; from 6.8 ppb to 4.3 ppb), respectively. MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduce the average XCH4 bias for ACTM (3.3 ppb), but increase the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that the range of satellite-based stratospheric CH4 is insufficient to resolve a possible stratospheric contribution to differences in total column CH4 between TCCON and TM5 or LMDz. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. This implies that there is a need to better understand the impact of individual model transport components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) on modeled stratospheric CH4.

scholarly journals Multivariate Extreme Value Theory - A Tutorial with Applications to Hydrology and Meteorology

2014 ◽  
Vol 2 (1) ◽  
Author(s):  
Anne Dutfoy ◽  
Sylvie Parey ◽  
Nicolas Roche
Keyword(s):  
Extreme Value Theory ◽  
High Speed ◽  
Value Theory ◽  
Extreme Value ◽  
Asymptotic Independence ◽  
Data Sets ◽  
Overhead Lines ◽  
Multivariate Extreme Value Theory ◽  
Air Temperatures ◽  
Multivariate Extreme Value

AbstractIn this paper, we provide a tutorial on multivariate extreme value methods which allows to estimate the risk associated with rare events occurring jointly. We draw particular attention to issues related to extremal dependence and we insist on the asymptotic independence feature. We apply the multivariate extreme value theory on two data sets related to hydrology and meteorology: first, the joint flooding of two rivers, which puts at risk the facilities lying downstream the confluence; then the joint occurrence of high speed wind and low air temperatures, which might affect overhead lines.

Potential impact of natural hazards on water supply systems in Alpine regions

2008 ◽  
Vol 3 (3) ◽  
Author(s):  
M. Möderl ◽  
D. Vanham ◽  
S. De Toffo ◽  
W. Rauch
Keyword(s):  
Water Supply ◽  
Natural Hazards ◽  
Potential Effect ◽  
Water Supply Systems ◽  
Data Sets ◽  
Management Support ◽  
Prevention Measures ◽  
Support Tool ◽  
Alpine Regions ◽  
Definition Of

One of the most important aspects in water supply management is supply security. In this article a methodology is introduced to first identify vulnerable sites of a water supply system (WSS) and second to estimate the potential effect of alpine natural hazards on this system. The approach serves for the definition of zones with low, medium and high potential risk by combining vulnerability and hazard maps. This approach enables the possibility to accomplish prevention measures on risky sites considering the available budget. A management support tool (VulNetWS - Vulnerability of Water Supply Networks) is developed which quantifies vulnerability based on hydraulic and quality simulations assuming component failure of each single WSS component. Hazards of flooding, landslide, debris flow and avalanches are calculated and categorized in potential low, medium and high hazard zones. For this analysis different GIS data sets (e.g. Austrian hazard zone maps, HORA “Flood Risk Zoning”) are used. The methodology is presented by applying it upon an alpine region encompassing the municipality of Kitzbühel (Tyrol - Austria) and 4 neighbouring municipalities. The combination of vulnerability and hazard is summarized using a risk matrix that highlights a zone of 0.42 square kilometres within the study area as being potentially risky.

A review on acoustic methods of algal growth control by ultrasonication through existing and novel emerging technologies

2017 ◽  
Vol 33 (5) ◽  
Author(s):  
Aditi Mullick ◽  
Sudarsan Neogi
Keyword(s):  
Energy Consumption ◽  
Algal Blooms ◽  
Nutrient Loading ◽  
Algal Growth ◽  
High Energy ◽  
Operating Conditions ◽  
Process Efficiency ◽  
Industrial Water ◽  
Algal Toxins ◽  
Algae Growth

AbstractThe uncontrolled proliferation of algae and algal blooms due to excessive nutrient loading in natural and industrial water bodies is a major issue for water quality maintenance. It reduces usability of the water, imposes hazardous effects of algal toxins released from algal blooms, and creates nuisance in the operation of several industrial water units. Among several existing water treatment methods to diminish the post-algae growth effects, ultrasonication has emerged as an environmentally safe technology that does not involve any use of algaecide. The interaction of several parameters, including climatic and environmental conditions with algae growth rate, have been reviewed in this article. The effects of different acoustic operating conditions for inhibition of algae growth have also been discussed. Concern about high energy consumption led other technologies to be integrated with ultrasonication. It has enhanced the process efficiency and reduced the energy consumption as reported in some long-term field investigations and patent proposals. Several issues that require further research for making this technology widely applicable or to install an effective system design have been highlighted in this article.

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