scholarly journals Development of a meteorological forecast for snow accumulation on transmission lines

1993 ◽  
Vol 18 ◽  
pp. 107-112
Author(s):  
Tatsuhito Ito ◽  
Masaru Yamaoka ◽  
Hisayuki Ohura ◽  
Takashi Taniguchi ◽  
Gorow Wakahama
Keyword(s):  
Air Temperature ◽  
Transmission Lines ◽  
Wind Direction ◽  
Mesoscale Model ◽  
Meteorological Data ◽  
Snow Accumulation ◽  
Surface Winds ◽  
Temperature And Precipitation ◽  
Wet Snow

In Hokkaido we have often experienced hazardous accidents, such as tower collapses and conductor breakage, caused by wet-snow accretion on transmission lines, and over many years have developed countermeasures for wet-snow accretion. Recently we have been developing a system to forecast areas where snow accretion may occur. We used the southern part of Hokkaido, divided into 5 km × 5 km meshes, as a forecast area; our predictions were hourly, 3–24 hours in advance. A method of predicting meteorological data which forms an important part of the system predicts three elements which influence wet-snow accretion: air temperature, precipitation, and wind direction and speed. We used an interpolation for predicting temperature and precipitation and a one-level, mesoscale model for diagnosing surface winds for wind direction and speed. By applying the method to many examples of wet-snow accretion, we checked the prediction of weather elements.

scholarly journals Development of a meteorological forecast for snow accumulation on transmission lines

1993 ◽  
Vol 18 ◽  
pp. 107-112
Author(s):  
Tatsuhito Ito ◽  
Masaru Yamaoka ◽  
Hisayuki Ohura ◽  
Takashi Taniguchi ◽  
Gorow Wakahama
Keyword(s):  
Air Temperature ◽  
Transmission Lines ◽  
Wind Direction ◽  
Mesoscale Model ◽  
Meteorological Data ◽  
Snow Accumulation ◽  
Surface Winds ◽  
Temperature And Precipitation ◽  
Wet Snow

In Hokkaido we have often experienced hazardous accidents, such as tower collapses and conductor breakage, caused by wet-snow accretion on transmission lines, and over many years have developed countermeasures for wet-snow accretion. Recently we have been developing a system to forecast areas where snow accretion may occur. We used the southern part of Hokkaido, divided into 5 km × 5 km meshes, as a forecast area; our predictions were hourly, 3–24 hours in advance. A method of predicting meteorological data which forms an important part of the system predicts three elements which influence wet-snow accretion: air temperature, precipitation, and wind direction and speed. We used an interpolation for predicting temperature and precipitation and a one-level, mesoscale model for diagnosing surface winds for wind direction and speed. By applying the method to many examples of wet-snow accretion, we checked the prediction of weather elements.

scholarly journals Climatic and atmospheric circulation pattern variability from ice-core isotope/geochemistry records (Altai, Tien Shan and Tibet)

2006 ◽  
Vol 43 ◽  
pp. 49-60 ◽  
Author(s):  
Vladimir B. Aizen ◽  
Elena M. Aizen ◽  
Daniel R. Joswiak ◽  
Koji Fujita ◽  
Nozomu Takeuchi ◽  
...  
Keyword(s):  
Air Temperature ◽  
Isotope Geochemistry ◽  
Eastern Mediterranean ◽  
Meteorological Data ◽  
Ice Core ◽  
Ice Cores ◽  
Snow Accumulation ◽  
Tien Shan ◽  
Synoptic Climatology ◽  
The Tibetan Plateau

AbstractSeveral firn/ice cores were recovered from the Siberian Altai (Belukha plateau), central Tien Shan (Inilchek glacier) and the Tibetan Plateau (Zuoqiupu glacier, Bomi) from 1998 to 2003. The comparison analyses of stable-isotope/geochemistry records obtained from these firn/ice cores identified the physical links controlling the climate-related signals at the seasonal-scale variability. The core data related to physical stratigraphy, meteorology and synoptic atmospheric dynamics were the basis for calibration, validation and clustering of the relationships between the firn-/ice-core isotope/ geochemistry and snow accumulation, air temperature and precipitation origin. The mean annual accumulation (in water equivalent) was 106 gcm−2 a−1 at Inilchek glacier, 69 gcm−2 a−1 at Belukha and 196 g cm−2 a−1 at Zuoqiupu. The slopes in regression lines between the δ18O ice-core records and air temperature were found to be positive for the Tien Shan and Altai glaciers and negative for southeastern Tibet, where heavy amounts of isotopically depleted precipitation occur during summer monsoons. The technique of coupling synoptic climatology and meteorological data with δ18O and d-excess in firn-core records was developed to determine climate-related signals and to identify the origin of moisture. In Altai, two-thirds of accumulation from 1984 to 2001 was formed from oceanic precipitation, and the rest of the precipitation was recycled over Aral–Caspian sources. In the Tien Shan, 87% of snow accumulation forms by precipitation originating from the Aral–Caspian closed basin, the eastern Mediterranean and Black Seas, and 13% from the North Atlantic.

Simple estimations of new and bulk snow density in the Italian Alps: Lessons from a decade of distributed observations

2020 ◽  
Author(s):  
Nicolas Guyennon ◽  
Franco Salerno ◽  
Mauro Valt ◽  
Anna Bruna Petrangeli ◽  
Rosa Maria Salvatori ◽  
...  
Keyword(s):  
Bulk Density ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Snow Accumulation ◽  
Easy Access ◽  
Monitoring Site ◽  
Italian Alps ◽  
Snow Density ◽  
Late Season

<p>The Snow Water Equivalent (SWE), combining the information of snow depth and snow density is a necessary variable for snow-hydrological studies and applications, as well as, for ecological function or avalanche forecasting. Direct automatics measurements of SWE requires an easy access to the monitoring site while manual measurements are costly and challenging. On the other hands, physically based models for snow density estimates require local meteorological data limiting their application in complex topography such as mountains areas. For this reason, different empirical regressions methods for the characterization of SWE and associated variability have been proposed for regional studies. In this study, we report our experience based on simple regression models able to characterize the new snow density and the snow bulk density at the scale of the entire Italian Alps, taking advantage of a decade of distributed observations. 12112 snowfall observations (2005-2015) gathered at 122 stations, ranging from 650 m to 2858 m a.s.l., have been analyzed to characterize the new snow density. 6078 snowpack depth and bulk density measurements (2009-2018) from 150 sites, ranging from 640 m to 3400 m a.s.l., have been collected to investigate the snow bulk density.</p><p>The mean air temperature of the 24 hours preceding the snowfall event, as a proxy of the transformation of freshly-fallen snow, has been found to be the best predictor of the new snow density, within 30% of uncertainty over the whole Italian Alps. While monthly regression allows considering part of the snow state variability through seasonality, the analysis of the associated residues suggests that, in the lack of local wind field information, the adoption of a local approach is not able to substantially increase the predictive capabilities of the model. The snow bulk density variability mainly responds to seasonality and can be estimated adopting the day of the year, as a proxy of the combined effect of compaction through seasonal snow accumulation and partial melting during the late season. Such approach enables a continuous (along the season) description of the SWE variation within 15% of uncertainty, similar to the within-site variability, presenting even better performances during the late season through the introduction of non-linearity. Differently from new snow density, regionalization performed considering separately those regions close to the sea improves the overall performances.</p><p>Although more performing models have already been proposed, the variables necessary to feed the proposed regressions (i.e. mean air temperature for new snow density and the day of the year for the bulk snow density) are easy to be acquired, making the proposed models valuable tools either in case of low instrumented watersheds or for past reconstruction. Finally, the low number of parameters to be calibrated makes the proposed regressions easy to be tested in other regions.  </p>

scholarly journals Temperature and precipitation signal in two Alpine ice cores over the period 1961–2001

2012 ◽  
Vol 8 (6) ◽  
pp. 5867-5891 ◽  
Author(s):  
I. Mariani ◽  
A. Eichler ◽  
S. Brönnimann ◽  
R. Auchmann ◽  
T. M. Jenk ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Ice Core ◽  
Ice Cores ◽  
Snow Accumulation ◽  
Spatial Correlations ◽  
Annual Basis ◽  
Temperature And Precipitation ◽  
Time Period ◽  
Regional Temperature ◽  
Relationship Of

Abstract. Water stable isotope ratios and net snow accumulation in ice cores are usually interpreted as temperature and precipitation proxies. However, only in a few cases a direct calibration with instrumental data has been attempted. In this study we took advantage of the dense network of observations in the European Alpine region to rigorously test the relationship of the proxy data from two highly-resolved ice cores with local temperature and precipitation, respectively, on an annual basis. We focused on the time period 1961–2001 with the highest amount and quality of meteorological data and the minimal uncertainty in ice core dating (±1 yr). The two ice cores come from Fiescherhorn glacier (Northern Alps, 3900 m a.s.l.) and Grenzgletscher (Southern Alps, 4200 m a.s.l.). Due to the orographic barrier, the two flanks of the Alpine chain are affected by distinct patterns of precipitation. Therefore, the different location of the two ice cores offers the unique opportunity to test whether the precipitation proxy reflects this very local condition. We obtained a significant spatial correlation between annual δ18O and regional temperature at Fiescherhorn. Due to the pronounced intraseasonal to interannual variability of precipitation at Grenzgletscher, significant results were only found when weighting the temperature with precipitation. For this site, disentangling the temperature from the precipitation signal was thus not possible. Significant spatial correlations between net accumulation and precipitation were found for both sites but required the record from the Fiescherhorn glacier to be shifted by −1 yr (within the dating uncertainty). The study underlines that even for well-resolved ice core records, interpretation of proxies on an annual or even sub-annual basis remains critical. This is due to both, dating issues and the fact that the signal preservation intrinsically depends on precipitation.

scholarly journals Temperature and precipitation signal in two Alpine ice cores over the period 1961–2001

2014 ◽  
Vol 10 (3) ◽  
pp. 1093-1108 ◽  
Author(s):  
I. Mariani ◽  
A. Eichler ◽  
T. M. Jenk ◽  
S. Brönnimann ◽  
R. Auchmann ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Ice Core ◽  
Ice Cores ◽  
Snow Accumulation ◽  
Global Network ◽  
Proxy Data ◽  
Altitude Effect ◽  
Temperature And Precipitation ◽  
Precipitation Regimes ◽  
Combining Data

Abstract. Water stable isotope ratios and net snow accumulation in ice cores are commonly interpreted as temperature or precipitation proxies. However, only in a few cases has a direct calibration with instrumental data been attempted. In this study we took advantage of the dense network of observations in the European Alpine region to rigorously test the relationship of the annual and seasonal resolved proxy data from two highly resolved ice cores with local temperature and precipitation. We focused on the time period 1961–2001 with the highest amount and quality of meteorological data and the minimal uncertainty in ice core dating (±1 year). The two ice cores were retrieved from the Fiescherhorn glacier (northern Alps, 3900 m a.s.l.), and Grenzgletscher (southern Alps, 4200 m a.s.l.). A parallel core from the Fiescherhorn glacier allowed assessing the reproducibility of the ice core proxy data. Due to the orographic barrier, the two flanks of the Alpine chain are affected by distinct patterns of precipitation. The different location of the two glaciers therefore offers a unique opportunity to test whether such a specific setting is reflected in the proxy data. On a seasonal scale a high fraction of δ18O variability was explained by the seasonal cycle of temperature (~60% for the ice cores, ~70% for the nearby stations of the Global Network of Isotopes in Precipitation – GNIP). When the seasonality is removed, the correlations decrease for all sites, indicating that factors other than temperature such as changing moisture sources and/or precipitation regimes affect the isotopic signal on this timescale. Post-depositional phenomena may additionally modify the ice core data. On an annual scale, the δ18O/temperature relationship was significant at the Fiescherhorn, whereas for Grenzgletscher this was the case only when weighting the temperature with precipitation. In both cases the fraction of interannual temperature variability explained was ~20%, comparable to the values obtained from the GNIP stations data. Consistently with previous studies, we found an altitude effect for the δ18O of −0.17‰/100 m for an extended elevation range combining data of the two ice core sites and four GNIP stations. Significant correlations between net accumulation and precipitation were observed for Grenzgletscher during the entire period of investigation, whereas for Fiescherhorn this was the case only for the less recent period (1961–1977). Local phenomena, probably related to wind, seem to partly disturb the Fiescherhorn accumulation record. Spatial correlation analysis shows the two glaciers to be influenced by different precipitation regimes, with the Grenzgletscher reflecting the characteristic precipitation regime south of the Alps and the Fiescherhorn accumulation showing a pattern more closely linked to northern Alpine stations.

scholarly journals The influence of local climate change on the productivity of spring cereals in the Kirov region

2021 ◽  
Vol 22 (2) ◽  
pp. 244-253
Author(s):  
I. V. Lyskova ◽  
O. E. Sukhoveeva ◽  
T. V. Lyskova
Keyword(s):  
Air Temperature ◽  
Spring Wheat ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Eastern Region ◽  
Positive Trend ◽  
Local Climate ◽  
Temperature And Precipitation ◽  
Spring Cereals

On the basis of long-term meteorological data and research results in a long-term stationary experiment of 1971-2020 a retrospective analysis of changes in air temperature and precipitation in the eastern region of the central climatic zone of the Kirov region was carried out and the influence of these characteristics on the dynamics of the yield of spring cereals was estimated. It has been established that the average annual air temperature during the research period was 2.4±1.0 °C. At the same time, its stable positive trend was observed at the rate of 0.39 °С /10 years. Two decades from 2001 to 2020 were recorded as the warmest for 50 years, when the temperature was 0.7...2.6 °C above climate normal. Selyaninov hydrothermal coefficient (0.7...2.1) testifies to the contrasting conditions of humidification of the vegetation periods during the research years – from drought to excessively humidified. In a long-term experiment, the yield of spring cereals increased in the row wheat – barley – oats: 2.17±0.86, 3.04±0.61, 3.39±0.65 t/ha, respectively. Strong correlations were marked between the average yield (spring wheat) and weather conditions in June: reverse with air temperature (rр = -0.735) and direct with the amount of precipitation (rр = 0.686). It has been established that the use of phosphorus fertilizers (and their aftereffect) in combination with nitrogen-potassium fertilizers weakened the influence of weather conditions on the productivity of spring wheat: the determination coefficients (R2), which reflect the portion of variability due to weather conditions, were 0.59-0.73 for the variant without fertilizers and decreased to 0.50-0.56 when applying NP3K.

scholarly journals Geoinformation modeling of the spatial distribution of the favourability level of climatic resources over the Sevastopol region for grape growing

2020 ◽  
pp. 51-56
Author(s):  
E. V. Vyshkvarkova ◽  
E. A. Rybalko ◽  
N. V. Baranova
Keyword(s):  
Spatial Distribution ◽  
Air Temperature ◽  
Heat Supply ◽  
Main Part ◽  
Meteorological Data ◽  
Climatic Conditions ◽  
Slope Aspect ◽  
Temperature And Precipitation ◽  
Rational Distribution ◽  
Geoinformation Modeling

Viticulture is one of the promising agricultural sectors in the Sevastopol region. In connection with this the goal of the work is a comprehensive analysis of the climatic conditions of the region for the rational distribution of vineyards. Meteorological data (air temperature and precipitation) for the period 1985-2018 and terrain parameters (slope, aspect, altitude) for the Sevastopol region were used. To assess the optimal climatic conditions, the analysis of frost risk, heat supply and water supply (average of absolute minimums of air temperature, growing degree days, Selianinov’s Hydrothermal Coeffi cient, Huglin and Winkler indices) was carried out. The spatial distribution of the listed agroclimatic parameters was modeled using author formulas. Using GIS technologies, maps of the spatial distribution of heat supply and agroclimatic parmeters for the region were obtained. The main part of the territory of the Sevastopol region is located in a zone with a sum of active temperatures of 3500-3900°С. The amount of precipitation during the growing season and the values of the hydrothermal coeffi cient indicate insuffi cient moisture in the region. Most of the region’s territory (72 %) has an average of absolute minimums of air temperature above –14 °C. According to the values of the Huglin index, the main part of the region is in the warm zone (2400-2700 °C), and by the values of the Winkler index – in Region 3 (1667-1944 °C). The heliothermal conditions of the Sevastopol region territory are suffi cient for growing grapes of diff erent groups of varieties and ripening dates. Agroclimatic parameters are characterized by positive trends, which in the future can lead to changes in heat supply and the displacement of terroirs. The territory of the Sevastopol region has favourable agroclimatic conditions, which makes it possible to grow grape varieties from very early to late ripening and placing them on fl at and sloping lands.

scholarly journals Change in snow depletion pattern in a river basin of Arunachal Pradesh under projected climatic scenarios

2017 ◽  
Vol 19 (2) ◽  
pp. 199-210
Keyword(s):  
Snow Cover ◽  
Meteorological Data ◽  
Snow Accumulation ◽  
High Mountain ◽  
Present Climate ◽  
Arunachal Pradesh ◽  
Temperature And Precipitation ◽  
Depletion Curve ◽  
Climatic Scenarios ◽  
The Impact

<p>Snow depletion curves (SDCs) are important in hydrological studies for predicting snowmelt generated runoff in high mountain catchments. The present study deals with the derivation of the average snow depletion pattern in the Mago basin of Arunachal Pradesh, which falls in the eastern Himalayan region and the generation of climate affected SDCs in future years (2020, 2030, 2040, and 2050) under different projected climatic scenarios. The MODIS daily snow cover product at 500m resolution from both the Aqua and Terra satellites was used to obtain daily snow cover maps. MOD10A1 and MYD10A1 images were compared to select cloud free or minimum cloud image to obtain the temporal distribution of snow cover area (SCA). Snow accumulation and depletion patterns were obtained by analysing SCA at different days. For most of the years, two peaks were observed in the SCA analysis. The conventional depletion curve (CDC) representing present climate was derived by determining and interpolating the SCA from cloud-free (cloud&lt;5%) images for the selected hydrological year 2007. The investigation shows that the SCA was highest in February and lowest in May. Ten years meteorological data were used to normalize the temperature and precipitation data of the selected hydrological year (2007) to eliminate the impact of their yearly fluctuations on the snow cover depletion. The temperature and precipitation changes under four different projected climatic scenarios (A1B, A2, B1, and IPCC Commitment) were analysed for future years. Changes in the cumulative snowmelt depth with respect to the present climate for different future years were studied by a degree-day approach and were found to be highest under A1B, followed by A2, B1, and IPCC Commitment scenarios. It was observed that the A1B climatic scenario affected the depletion pattern most, making the depletion of snow to start and complete faster than under different scenarios. Advancing of depletion curve for different future years was found to be highest under A1B and lowest under IPCC Commitment scenarios with A2 and B1 in-between them.</p>

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