Estimation of Snow Distribution under Global Warming Using Data from Remote Weather Stations (AMeDAS)

Kominami, Yuji; Tanaka, Nobuyuki; Endo, Yasunori; Niwano, Shoji

doi:10.2480/agrmet.445

Cited by 20 publications

(13 citation statements)

References 5 publications

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“…Water vapor pressure is interpolated from the nearest meteorological observatory or weather station of the Japan Meteorological Agency. We assumed that the gauges catch 0.8 of the snowfall because of windinduced undercatchment of snow (Kominami et al, 2005), and all (1.0) of the rainfall. The coefficient C sf was obtained over each grid with the assumption that cumulative snowfall equals cumulative snowmelt during the snow cover season as follows: (3) where s i is the ratio of snowfall to total precipitation and i is time interval and i = 1 represents the first date of snow cover.…”

Section: Methodsmentioning

confidence: 99%

Spatial snowfall distribution in mountainous areas estimated with a snow model and satellite remote sensing

Asaoka

Kominami

2012

Hydrological Research Letters

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Abstract:We describe an approach for reconstructing snowfall that combines satellite observations of the snow disappearance date (SDD) with a snow model for two mountainous areas in Japan having distinct snow climatology. This approach allows assessment of the distribution of snow and topographical effects on snowfall within a catchment. We also evaluated how the reconstructed snowfall affects the catchment snow hydrology.Validation at observation sites demonstrated that a combination of the snow model and snowfall reconstructions successfully estimated the seasonal changes of snow water equivalent (SWE). In Japan, the dependence of snowfall on elevation is stronger in mountainous areas along the coast on the Sea of Japan side of Japan's central mountain spine (where snowfall triples with every 1000 m increase in elevation; C sf = 0.002 m −1 ) compared with inland locations of the same region (where snowfall doubles with every 1000 m increase; C sf = 0.001 m −1). Moreover, the reconstructed snowfall improved the estimation of maximum catchment SWE. Maximum total SWE, estimated with reconstructed snowfall, was 3.8 × 10 8 m 3 in Kurobe catchment (along the coast on the Sea of Japan side of Japan's central mountain spine), while that, estimated by convectional method with the spatially-constant C sf = 0.001 m −1 , was 2.0 × 10 8 m 3 . As a result, estimations of the snow disappearance date and of the catchment snowmelt were also improved. These results suggest that it is useful to estimate the spatial snow distribution, especially where steep topography causes large gradients of snowfall amount with respect to elevation.

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Section: Methodsmentioning

confidence: 99%

Spatial snowfall distribution in mountainous areas estimated with a snow model and satellite remote sensing

Asaoka

Kominami

2012

Hydrological Research Letters

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“…Snow depth in the Sierra Nevada varied between 15 cm and 1 m (Bales et al, 2011). In north-eastern Japan air temperature in winter is around 0 C (Kominami, Tanaka, Endo, & Niwano, 2005) and the Japanese Sea coastline receives heavy snowfall (Asaoka & Kominami, 2013) from the cold Siberian winds, which hit the Asahi Mountains and produce around 1,500 mm snowfall in winter (Dorman et al, 2004;Yamaguchi, Abe, Nakai, & Sato, 2011). Such high precipitation results in snow depths of more than three meters and snow coverage lasting until May.…”

Section: Introductionmentioning

confidence: 99%

Soil temperature and soil moisture dynamics in winter and spring under heavy snowfall conditions in North‐Eastern Japan

Brandt

Zhang

Caceres

et al. 2020

Hydrological Processes

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Warm winters and high precipitation in north‐eastern Japan generate snow covers of more than three meters depth and densities of up to 0.55 g cm−3. Under these conditions, rain/snow ratio and snowmelt have increased significantly in the last decade under increasing warm winters. This study aims at understanding the effect of rain‐on‐snow and snowmelt on soil moisture under thick snow covers in mid‐winter, taking into account that snowmelt in spring is an important source of water for forests and agriculture. The study combines three components of the Hydrosphere (precipitation, snow cover and soil moisture) in order to trace water mobility in winter, since soil temperatures remained positive in winter at nearly 0.3°C. The results showed that soil moisture increased after snowmelt and especially after rain‐on‐snow events in mid‐winter 2018/2019. Rain‐on‐snow events were firstly buffered by fresh snow, increasing the snow water equivalent (SWE), followed by water soil infiltration once the water storage capacity of the snowpack was reached. The largest increase of soil moisture was 2.35 vol%. Early snowmelt increased soil moisture with rates between 0.02 and 0.035 vol% hr−1 while, rain‐on‐snow events infiltrated snow and soil faster than snowmelt and resulted in rates of up to 1.06 vol% hr−1. These results showed the strong connection of rain, snow and soil in winter and introduce possible hydrological scenarios in the forest ecosystems of the heavy snowfall regions of north‐eastern Japan. Effects of rain‐on‐snow events and snowmelt on soil moisture were estimated for the period 2012–2018. Rain/snow ratio showed that only 30% of the total precipitation in the winter season 2011/2012 was rain events while it was 50% for the winter 2018/2019. Increasing climate warming and weakening of the Siberian winter monsoons will probably increase rain/snow ratio and the number of rain‐on‐snow events in the near future.

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“…MSW greatly influences the distribution and regeneration of F. crenata (Homma et al 1999;Shimano 2006). MSW and WR were calculated by aggregating daily changes in snowfall, rainfall, and meltwater (degree-day method) based on a daily climatic dataset supplied by the Automated Meteorological Data Acquisition System and the mesh climatic data (Japan Meteorological Agency 1996; Kominami et al 2005).…”

Section: Climatic Datamentioning

confidence: 99%

Projecting spatiotemporal changes in suitable climate conditions to regenerate trees using niche differences between adult and juvenile trees

et al. 2015

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Assessing suitable climate conditions to regenerate trees over a large area is of great importance to investigate potential impacts of climate change. In this study, we developed a size-based species distribution model (SBSDM) to assess spatiotemporal changes in the tree regeneration niche separately from the growth niche in adults. Siebold's beech (Fagus crenata) was selected as the target species. We projected (1) areas where adult and juvenile potential habitats (PHs) overlapped, (2)only-adult PHs, (3) only-juvenile PHs, and (4) non-habitats for 2080-2099 using the SBSDM, a distribution dataset from the Phytosociological Relevé Database of Japan, and a future climatic dataset from 24 general circulation models (GCMs). We also projected juvenile PHs for all decades between 2011 and 2099 using four representative GCMs to assess potential lost decades of the regeneration niche. The SBSDM provided sufficient projections of adult and juvenile tree distributions as well as their niche differences under the current climate. Overlapping areas and only-adult PHs were projected to decrease by the end of this century. An increase in only-juvenile PHs was projected to occur in snowy regions, with juvenile PHs starting to decrease in warm and less snowy regions. Furthermore, juvenile PHs are expected to decrease widely around 2060 as well as at the end of this century due to considerable rapid warming around those times. We conclude that regeneration of F. crenata will start to decline in 2060, but snowy conditions will postpone the timing of the regeneration loss, causing an increase in only-juvenile PHs.

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Estimation of Snow Distribution under Global Warming Using Data from Remote Weather Stations (AMeDAS)

Cited by 20 publications

References 5 publications

Spatial snowfall distribution in mountainous areas estimated with a snow model and satellite remote sensing

Spatial snowfall distribution in mountainous areas estimated with a snow model and satellite remote sensing

Soil temperature and soil moisture dynamics in winter and spring under heavy snowfall conditions in North‐Eastern Japan

Projecting spatiotemporal changes in suitable climate conditions to regenerate trees using niche differences between adult and juvenile trees

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