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https://doi.org/10.5194/essd-2026-183
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2026-183
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
23 Apr 2026
| 23 Apr 2026
Status: this preprint is currently under review for the journal ESSD.
Weather station data from the Mount Everest region, Nepal: 3,810-8,810 m above sea level
Abstract. The National Geographic Rolex Perpetual Planet Everest expeditions 2019–2022 installed a network of Automatic Weather Stations (AWSs) to improve understanding of the climate at high altitudes in the Nepal Himalaya. This knowledge is critical in the Mount Everest (Khumbu) region, due to its extreme altitude, popularity amongst trekkers and mountaineers, and its importance as a source of freshwater for downstream communities. Here we present quality controlled (QC) meteorological data from six AWSs from Phortse (3,810 m above sea level, m asl) to Bishop Rock (8,810 m asl) in the Everest region, including the seasonal climatology, and a comparison with ERA5 reanalysis data from the South Col AWS. The data is accessible from https://doi.org/10.5281/zenodo.18849098.
How to cite. Khadka, A., Perry, L. B., Matthews, T., Sherpa, T. G., Shrestha, C. B., Shrestha, D., Aryal, D., Tuladhar, S., Pradhananga, N., Kayastha, D., Raichle, B., Athans, P., Sherpa, D. Y., Garrett, K., Wheeler, G., Young, T., and Elmore, A.: Weather station data from the Mount Everest region, Nepal: 3,810-8,810 m above sea level, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2026-183, in review, 2026.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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- RC1: 'Comment on essd-2026-183', Anonymous Referee #1, 05 May 2026
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RC2: 'Comment on essd-2026-183', Anonymous Referee #2, 25 May 2026
The Authors present six new weather stations installed in the Khumbu region (Nepal) between 2019 and 2022, five of them installed between 5000m and 8810 m a.s.l. along the way to Mt Everest. Data are available on Zenodo, updated to May 2025 (last accessed 25/05/2026). After describing location, measured variables, and data treatment, the authors present the two lowest stations (Phortse 3840 m a.s.l.) and Base camp 5315 m a.s.l.) temperature and precipitation seasonality, as well as temperature seasonality at Camp II (6464 m a.s.l.). South col station (7945 m a.s.l.) hourly air temperature, relative humidity, and wind speed are then compared with the ERA5 free-atmosphere 350 hPa pressure level. Associated mean diurnal cycles are reported in the supplementary.Those data represent an impressive effort and are of high interest for both Everest expeditions and scientific knowledge of very high altitude meteorology. The paper is globally well written, and the figures are clearly presented. I think data from the two highest stations (Balcony, 8430 m a.s.l., and Bishop Rock, 8810 m a.s.l.) should be presented (even if spares) to better appreciate their potentialities, also because those stations represent a unique effort. The new network could also be better contextualized within the existing ones to further show its potential in combination with existing data.Please find below a list of comments, hoping it can help to improve the current manuscript.L28 Seasonal climatology is presented only for three of the six stationsL53 EvK2CNR network data is available at https://essd.copernicus.org/articles/17/4293/2025/ and should be cited hereL83 and Figure 1. The authors should choose between reporting all AWS installed in the Khumbu or only the ones presented in this paper. The current mixed solution creates confusion. In my opinion, it would be a nice added value for the new AWS to be contextualized within the existing networks (EvK2CNR and GLACIOCLIM as presented in L51 to L58). I would thus suggest reporting in Figure 1 all existing/published AWS (e.g., with different colors for each network), distinguishing between still active and dismissed stations.L95-96 It would be nice to see a comparison of wind measurement with traditional and pitot sensorsL118 considered reformulating “detail measurement details”L128 please explain the limitations that conduct to install temperature and humidity sensor at 1.5m in higher stations.L153. Please comment the installation of the optical disdrometer and the snow level sonic sensor (table 1), and how it may help to validate precipitation data in case of a lack or insufficient antifreeze agent.Table 1 why snow level and disdrometer has not been described in the text? ; L114 an estimation of the approximate weight has been given for the lower station. (Report m a.s.l. for elevation)L189-191 I am curious about wind speed measured with pitot sensor. Are the data available to cross-check the traditional wind sensor freezing event?L195-199: Please explain why you expect a SWin underestimation rather than SWout overestimation in the case of albedo > 0.95? (check typo L198 , “95 (Shea et al. 2015; […]”)L200 check typo “pluvio 2”)L200-203 Any check on missed snowfall due to potential issues with antifreeze agent? Do the authors consider potential cross-check with snow level and disdrometer data (especially for base camp station)?Figure 2 has not been recalled in the text. Consider moving the text (e.g. “a) temperature and relative humidity”) outside of the panels and enlarge line thickness for better visibility, especially for BR and BA stations (also consider avoiding the “intense” yellow for BA to improve readability)L109-216 and figure 3: Please add available data for SC, BA, and BR even if the data are very sparse. Also, consider adding and discussing radiative seasonality.L224 Please specify that -107 mm/km refers to the mean annual precipitation. In addition, considering that the wide majority of precipitation occurs during the monsoon, maybe the monsoon gradient is more significant?L228-234 Consider also using temperature from the other stations and plotting the seasonal mean value for each pair of stations so that non-linearity in temperature gradient can be appreciated. While it is easily understandable that precipitation measurement is limited to base camp, it is a pity to present a network ranging from 3800 to 8800 meters but reporting the temperature gradient only between 5300 and 3800.Table 2. Specify the definition used for winter, pre monsoon, monsoon and post-monsoon aggregationL239-247 and figure 4. It would be interesting to also report available data from BA and BR. It will help the reader to make its own opinion on how local station can be representative of larger-scale (0.25°*0.25°) era5 node and further support the affirmation L271-274.Figure 4. Specify if the daily max (blue dot) is from SC observation or ERA5.L256 Temperature gradient between SC, BA, and BR may help to downscale ERA5 temperature at actual SC elevation?L283 Specify that this is based on atmospheric pressure dataL289 consider to reformulate “[…] provided here provide […]“L300 check sentenceL307-311 I fully agree; Presenting the full networks in Figure 1 would be nice.L 340 check sentence “[…]the data in CSV format and can”Citation: https://doi.org/
10.5194/essd-2026-183-RC2
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AWS data from the Mount Everest region Arbindra Khadka et al. https://doi.org/10.5281/zenodo.18849099
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Latest update: 08 Jun 2026
Arbindra Khadka
CORRESPONDING AUTHOR
Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, Nepal
Université Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France
L. Baker Perry
Department of Geography (Climatology), University of Nevada, Reno, Nevada, USA
Research Institute for Environment, Energy, and Economics, Department of Sustainable Technology & the Built Environment, Appalachian State University, Boone, North Carolina
Tom Matthews
Department of Geography, King’s College London, London, UK
Tenzing Gyalzen Sherpa
Khumbu Climbing Centre, Phortse, Nepal
Chitra Bahadur Shrestha
Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, Nepal
Dibas Shrestha
Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, Nepal
Deepak Aryal
Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, Nepal
Subash Tuladhar
Department of Hydrology and Meteorology, Nepal
Niraj Pradhananga
Department of Hydrology and Meteorology, Nepal
Dinkar Kayastha
Department of Hydrology and Meteorology, Nepal
Brian Raichle
Research Institute for Environment, Energy, and Economics, Department of Sustainable Technology & the Built Environment, Appalachian State University, Boone, North Carolina
Peter Athans
The North Face, Alameda, California
Dawa Yangzum Sherpa
The North Face, Alameda, California
Keith Garrett
Mount Washington Observatory, North Conway, New Hampshire, USA
Garrett Wheeler
Campbell Scientific, Logan, Utah, USA
Tom Young
RM Young, Traverse City, Michigan, USA
Aurora Elmore
National Oceanic and Atmospheric Administration, Maryland, USA
Short summary
We installed six automatic weather stations from 3,810 m to 8,810 m on Mount Everest region to better understand weather conditions at high altitudes. These measurements reveal how temperature, humidity, and wind changes with height and season. Our results show differences between observations and widely used ERA5 datasets. This improved knowledge helps scientists better understand mountain weather and climate, climate change and supports water resource planning for communities downstream.
We installed six automatic weather stations from 3,810 m to 8,810 m on Mount Everest region to...
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Lines 92-93: Is it Universal Coordinated Time (UTC) or the university? That must be a typo. Check?
Lines 98-101: The figure 1 caption describes the locations of meteorological and glaciological observations since 2010, denoted by a plus (+). But no mention is made of the installed AWS in the Everest expeditions either, although it is in the legend with some symbol.
Line 106: Could not find the supplementary information for the photograph links, although it is mentioned.
Lines 127-128: Is there any reason why the AT and RH sensors are installed 1.5 m from the ground for higher AWSs, whereas 2 m for the lower AWSs?
Lines 156-158: Is there any standard time to capture the photo? Why is it set at 0937 NPT and 1437 NPT?
Table 1: What does the 'present weather sensor’ work for?
Section 2.1: AWS details and measured variables
Line 180: Supplementary Table S1 could not be found.
Line 201: Supplementary Figure S1 could not be found.
Line 206: What about data availability on surface elevation change or snow? Three sites have these sensors (ref. Table 1) As it would be very useful for the mountaineers and other communities.
Line 212: Average annual precipitation? If it is annual precipitation, 'of which year'?
Line 221: Is it ‘mean monthly’ or ‘monthly mean’?
Lines 226-228: Do the precipitation comparisons between the PH, BC and Pheriche, Pyramid cover the same time frame? If yes, it is not mentioned. Also, two values of precipitation amount from the Pyramid station – what do they mean? Are the values from the two stations at Pyramid?
Section 5: The SC-observed data is compared with ERA5; it is better to give a short overview of ERA5. Why is it not compared with any other stations?
Lines 254-255: As the comparison between ERA5 and observed has an approximation of R² > 0.6 (for all variables) for the period of monsoon and post-monsoon (June to Dec). Are the comparison limits for all seasons due to missing data?
Lines 257-258: Supplementary Figures S3 and S4 could not be found.
Lines 280-282: The wind and gust speed were highlighted for the mountaineers for the period; the comparison was missing for April and May (spring expedition).