Evaluation of the TRMM Product for Spatio-temporal Characteristics of Precipitation over Nepal (1998-2018)

Hamal, Kalpana; Khadka, Nitesh; Rai, Samresh; Joshi, Bharat Badayar; Dotel, Jagdish; Khadka, Lilaram; Bag, Niraj; Ghimire, Shravan Kumar; Shrestha, Dibas

doi:10.3126/jist.v25i2.33733

Cited by 6 publications

(6 citation statements)

References 40 publications

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“…Several studies have recently examined the temperature and precipitation trend over the Himalayas and surrounding high altitude regions (Yue et al, 2019;Hamal et al, 2020a;Shrestha et al, 2021). Moreover, these studies indicate that the annual temperatures have generally increased in the region (Shrestha & Devkota, 2010;Shrestha & Aryal, 2011;Dibike et al, 2012;Kattel et al, 2013;Thakuri et al, 2019), and experiencing higher increase rates of temperature than the global average (Li et al, 2011;Poudel et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Does the High Elevation Climate along Mt. Everest can be Represented by Lower Elevation Stations?

Dawadi¹,

Sharma²,

Hamal³

et al. 2021

J. Inst. Sci. Tech.

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Climate change studies of the high mountain areas of the central Himalayan region are mostly represented by the meteorological stations of the lower elevation. Therefore, to validate the climatic linkages, daily observational climate data from five automated weather stations (AWS) at elevations ranging from 2660 m to 5600 m on the southern slope of Mt. Everest were examined. Despite variations in the means and distribution of daily, 5-day, 10-day, and monthly temperature and precipitation between stations located at a higher elevation and their corresponding lower elevation, temperature records in the different elevations are highly correlated. In contrast, the precipitation data shows a comparatively weaker correlation. The slopes of the regression model (0.82–1.13) with (R2>0.74) for higher altitude (5050 m and 5600 m) throughout the year, 0.83–1.12 (R2>0.68) except late monsoon season for the station at 4260 m and 5050 m asl indicated the similar variability of the temperature between those stations. Similarly, Namche (3570 m) temperature changes by 0.81–1.32°C per degree change in corresponding lower elevation Lukla station (2660 m), except for monsoon season. However, inconsistent variation was observed between the station with a large altitudinal difference (2940 m) at Lukla and Kala Patthar (5600 m). In general, climate records from corresponding lower elevation can be used to quantitatively assess climatic information of the high elevation areas on the southern slope of Mt. Everest. However, corrections are necessary when absolute values of climatic factors are considered, especially in snow cover and snow-free areas. This study will be beneficial for understanding the high-altitude climate change and impact studies.

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Section: Introductionmentioning

confidence: 99%

Does the High Elevation Climate along Mt. Everest can be Represented by Lower Elevation Stations?

Dawadi¹,

Sharma²,

Hamal³

et al. 2021

J. Inst. Sci. Tech.

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“…Consistent with the global pattern, South Asia has experienced several climatic extremes, and such extremes are anticipated to be more frequent in the future (Klein Tank et al, 2006). Nepal is a South Asian mountainous country experiencing a high rate of temperature increase, changing precipitation patterns, with frequent and severe occurrences of climate-induced disasters, such as landslides, glacial lake outburst floods, flash floods, drought (Khadka et al, 2018;Sharma et al, 2020a, Hamal et al, 2020a. Thus, understanding the present and future spatial and temporal variations of precipitation and temperature is important for monitoring climate-induced disasters (Bhattarai, 2015; Maharjan & Regmi, 2015).…”

Section: Introductionmentioning

confidence: 94%

Statistical Downscaling and Projection of Future Temperature and Precipitation Change in Gandaki Basin

Shrestha

Sharma

Bhandari

et al. 2021

J. Inst. Sci. Tech.

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Understanding the present and future spatial and temporal variations of precipitation and temperature is important for monitoring climate-induced disasters. Satellite and global reanalysis data can provide evenly distributed climate data; however, they are still too coarse to resolve fundamental processes over complex terrains. The study applies global climate model CGCM4/CANESM2, to project future maximum temperature, minimum temperature, and precipitation across the cross-section of the Gandaki River basin, Nepal. Large scale atmospheric variables of the National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis (NCEP/NCAR) datasets are downscaled using Statistical Downscaling Model (SDSM) under different emission scenarios. For the variability and changes in maximum temperature (Tmax), minimum temperature (Tmin), and precipitation for future periods (2020s, 2050s, and 2080s), three different scenarios RCP2.6, RC4.5, and RCP8.5 of CGCM4 model were performed. The study revealed that both the temperature and precipitation would increase for three RCPs (representative concentration pathways) in the future. The highest increase in precipitation was found in the arid region compared to humid and sub-humid regions by the end of 2100. Similarly, the increase in mean monthly Tmin and Tmax was more pronounced in Jomsom station than Baglung and Dumkauli stations. Overall, a decrease in summer temperature and increase in winter temperature was expected for future periods across all regions. Further, spatial consistency was observed for Tmax and Tmin, whereas spatial consistency was not found for precipitation.

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“…In contrast, the pre-monsoon and monsoon seasons are wet and humid (Shrestha, 2000;Sharma et al, 2021a). Low-land and Mid-Mountains receive large amounts of precipitation during the summer monsoon from July to September as part of the South Asian monsoon, which is the country's primary source of annual precipitation (Hamal et al, 2020a;Hamal et al, 2020b;Hamal et al, 2020c;Sharma et al, 2020b;Shrestha and Deshar, 2014;Shrestha et al, 2021). Meanwhile, the northern part of the high Himalayas, including trans-Himalayan regions, is relatively dry as mountains block the precipitation and are known as rain shadow areas (Dawadi et al, 2020;Pokharel et al, 2019;Talchabhadel and Karki, 2019;Talchabhadel et al, 2018).…”

Section: Study Areamentioning

confidence: 99%

“…The Himalayas are water towers and the primary source of many rivers supporting millions of people downstream (Hannah et al, 2005;Sharma et al, 2005;Immerzeel et al, 2020). Precipitation in Nepal is predominantly governed by the summer monsoon system and is highly variable due to complex topography (Krakauer et al, 2013;Hamal et al, 2020a;Hamal et al, 2021). Rain Gauge-based stations provide relatively accurate and actual precipitation measurements at discrete locations on the ground surface (Sun et al, 2018;Hamal et al, 2020c;Sharma et al, 2020c;Sharma et al, 2021b).…”

Section: Introductionmentioning

confidence: 99%

Spatial Pattern of Precipitation in GPM-Era Satellite Products against Rain Gauge Measurements over Nepal

et al. 2021

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Precipitation in a mountainous region is highly variable due to the complex terrain. Satellite-based precipitation estimates are potential alternatives to gauge measurements in these regions, as these typical measurements are not available or are scarce in high elevation areas. However, the accuracy of these gridded precipitation datasets need to be addressed before further usage. In this study, an evaluation of the spatial precipitation pattern in satellite-based precipitation products is provided, including satellite-only (Integrated Multi satellite Retrievals for GPM IMERG-UCORR and Global Satellite Mapping of Precipitation (GSMaP-MVK) and gauge calibrated (IMERG-CORR and GSMaP-Gauge) products, with a spatial resolution of 0.1°, which is compared to 387-gauge measurements in Nepal from April 2014 to December 2016. The major results are as follows: (1) The gauge calibrated version 5 IMERG-CORR and version 6 GSMaP-Gauge are relatively better than the satellite-only datasets, although they all underestimate the observed precipitation. (2) The daily gauge calibrated GSMaP-Gauge performs fairly well in low and mid-elevation areas, whereas the monthly gauge calibrated IMERG-C performs better in high-elevation areas. (3) For the daily time scale, IMERG-CORR shows a better ability to detect the true precipitation (higher Probability of Detection (POD)) and (lowest False Alarm Ratio (FAR)) events among all datasets. However, all four satellite-based precipitation datasets accurately detect (Critical Success Index (CSI) >40%) precipitation and no-precipitation events. The results of this work provide the systematic quantification of IMERG and GSMaP of satellite precipitation products over Nepal using station observations and delivers a helpful statistical basis for the selection of these datasets for future scientific research.

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Evaluation of the TRMM Product for Spatio-temporal Characteristics of Precipitation over Nepal (1998-2018)

Cited by 6 publications

References 40 publications

Does the High Elevation Climate along Mt. Everest can be Represented by Lower Elevation Stations?

Does the High Elevation Climate along Mt. Everest can be Represented by Lower Elevation Stations?

Statistical Downscaling and Projection of Future Temperature and Precipitation Change in Gandaki Basin

Spatial Pattern of Precipitation in GPM-Era Satellite Products against Rain Gauge Measurements over Nepal

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