Spatial Variation of Temperature and Precipitation in Bhutan and Links to Vegetation and Land Cover

Dorji, Ugyen; Olesen, Jørgen E.; Bøcher, Peder Klith; Seidenkrantz, Marit‐Solveig

doi:10.1659/mrd-journal-d-15-00020.1

Cited by 41 publications

(39 citation statements)

References 30 publications

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“…Mean summer temperature ranges from 12°C to 14°C while winter temperature ranges from −2°C to −6°C (Dorji et al 2016). Annual precipitation is in the order of 1801 mm to 2600 mm.…”

Section: Study Areamentioning

confidence: 99%

Lemthang Tsho glacial Lake outburst flood (GLOF) in Bhutan: cause and impact

Gurung

Khanal

Bajracharya

et al. 2017

Geoenviron Disasters

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Background: The Hindu Kush Himalayan (HKH) region being seismically active and sensitive to climate change is prone to glacial lake outburst flood (GLOF). The Lemthang Tsho GLOF breached in the evening of 28 July 2015 innorth-western Bhutan is reminds of the looming threat, and stresses the need to have good risk management plan. The need to understand the physical processes in generating GLOF to is therefore imperative in order to effectively manage the associated risk. The paper therefore assesses the cause and impact of the Lemthang Tsho GLOF event using field and remote sensing data. Results: The collapse of near vertical wall of supraglacial lake triggered by 2 days of incessant rainfall, opened up the englacial conduit resulting in emptying of interconnected supraglacial lakes into Lemthang Tsho. The5.1 magnitude earthquake epicentered 187 km to southeast in the Indian state of Assam in the morning (7:10 am Bhutan Standard Time) of the same day is unlikely to have played any role in triggering the event. The estimated volume of water unleased is 0.37 million m

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“…Mean summer temperature ranges from 12°C to 14°C while winter temperature ranges from −2°C to −6°C (Dorji et al 2016). Annual precipitation is in the order of 1801 mm to 2600 mm.…”

Section: Study Areamentioning

confidence: 99%

Lemthang Tsho glacial Lake outburst flood (GLOF) in Bhutan: cause and impact

Gurung

Khanal

Bajracharya

et al. 2017

Geoenviron Disasters

View full text Add to dashboard Cite

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“…Dorji et al . () used linear and polynomial regressions to describe the distribution of seasonal temperature and precipitation across Bhutan. The equations developed by Dorji et al .…”

Section: Introductionmentioning

confidence: 99%

“…Temperature 898 S. B. STEWART et al lapse rates show clear trends that are associated with the seasonal reversal of the north Indian monsoon (Kattel et al, 2013(Kattel et al, , 2015Dorji et al, 2016) and tend to be suppressed during the humid, cloudy and wet summer months. Increased levels of atmospheric moisture and the forced ascent of air against the Himalayas result in cloud formation, precipitation and an associated release of latent heat (Ohata et al, 1981;Whiteman, 2000;Barry, 2008;Krishnamurti et al, 2013), particularly at higher elevations (Kattel et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Until recently, the network of weather stations operating within Bhutan had not been used to develop spatially representative climate datasets for the region. Dorji et al (2016) used linear and polynomial regressions to describe the distribution of seasonal temperature and precipitation across Bhutan. The equations developed by Dorji et al (2016) are broadly representative of the region; however, they retain residual error when generating prediction surfaces and do not account for a spatially varying dependence upon elevation.…”

Section: Introductionmentioning

confidence: 99%

“…Dorji et al (2016) used linear and polynomial regressions to describe the distribution of seasonal temperature and precipitation across Bhutan. The equations developed by Dorji et al (2016) are broadly representative of the region; however, they retain residual error when generating prediction surfaces and do not account for a spatially varying dependence upon elevation. Furthermore, extrapolating precipitation into the northern regions of Bhutan using polynomial regression and excluding the effects of orography are likely to lead to oversimplified predictions of rainfall.…”

Section: Introductionmentioning

confidence: 99%

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The role of topography and the north Indian monsoon on mean monthly climate interpolation within the Himalayan Kingdom of Bhutan

Stewart

Choden

Fedrigo

et al. 2017

Intl Journal of Climatology

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Spatial climate datasets currently available for Bhutan are limited by weather station data availability, spatial resolution or interpolation methodology. This article presents new datasets for monthly maximum temperature, minimum temperature, precipitation and vapour pressure climate normals interpolated for the 1986–2015 reference period using trivariate smoothing splines. The inclusion of standardized day time Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) values as partial spline dependencies reduced cross validated root mean square error (RMSE) for maximum temperature by up to 16.0% and was most effective between March and September. Using both a topographic index of relative elevation and standardized night time MODIS LST values as partial spline dependencies reduced monthly mean minimum temperature RMSE by up to 23.4%. Neither variable was effective for minimum temperature interpolation between June and September. High humidity, extensive cloud cover and heavy precipitation occur during these months, which are likely to suppress the formation of temperature inversions that typically form under clear, calm conditions. These new temperature and precipitation surfaces show distinct differences from the WorldClim and CRU CL 2.0 datasets, which do not use weather stations within Bhutan for calibration. New precipitation surfaces better describe the heavy rainfall experienced in the southern foothills while retaining the effect of orography throughout the central valleys and ranges. The development of vapour pressure surfaces also allow for the calculation of ecologically important variables such as vapour pressure deficit, and may also be useful for solar radiation modelling in the region. The different datasets presented in this article will facilitate ecological and agricultural research in Bhutan and provide high quality surfaces needed for future climate change scenarios.

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Insights on the climate of Bhutan from a new daily 1 km gridded data set for temperature and precipitation

Lehner

Formayer

2023

Intl Journal of Climatology

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Gridded climatological data derived for Bhutan from internationally available data sets either come at a very low spatial resolution, or do not provide daily data, or contain few in situ measurements. We present a newly developed daily high‐resolution (1 km) gridded data set for Bhutan covering the years 1996–2019 for precipitation and maximum and minimum temperature (BhutanClim). As input, we used quality‐controlled and homogenized data from up to 67 weather stations from the National Center for Hydrology and Meteorology of Bhutan. The spatial interpolation of daily temperature consists of a non‐linear vertical profile combined with an inverse‐distance interpolation of the residuals. The interpolation uses a non‐Euclidian distance that takes elevation differences between grid cells and topographic obstacles into account. The daily coverage allows the calculation of climate indicators that need daily data such as frost days or precipitation days. The new climatology benefits from the use of local measurements and shows plausible small‐scale spatial patterns. It shows a distinct dry region in the valleys in central Bhutan bordering a dry climate classification according to Köppen–Geiger which is not visible in other data sets.

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Spatial Variation of Temperature and Precipitation in Bhutan and Links to Vegetation and Land Cover

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Cited by 41 publications

References 30 publications

Lemthang Tsho glacial Lake outburst flood (GLOF) in Bhutan: cause and impact

Lemthang Tsho glacial Lake outburst flood (GLOF) in Bhutan: cause and impact

The role of topography and the north Indian monsoon on mean monthly climate interpolation within the Himalayan Kingdom of Bhutan

Insights on the climate of Bhutan from a new daily 1 km gridded data set for temperature and precipitation

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