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Tropical glaciers serve as crucial sources of fresh water, particularly in arid tropical regions, where glacial runoff supports human consumption and economic activities such as agriculture, livestock farming, and tourism. Glaciers, due to their rapid response to melting conditions, are widely regarded as key indicators of climate change (
In South America, the extent of glaciers covers several countries from Bolivia to Venezuela, with Peru having a large number of glaciers in its 18 glacial mountain ranges located mainly between the center and south regions. According to recent measurements, the total glacial extent was approximately 1050.32 km2 as of 2020, representing a 6.5% reduction since 2017 (
Glacier retreat has been demonstrated to affect not only the dynamics of water supply and demand but also socioeconomic, environmental, and cultural systems, as discussed by several research workers (
To address this issue, in this report, we present a database of four stations located in three Peruvian mountain ranges: Huaytapallana, located in the Cordillera of the same name Huaytapallana; Coropuna, in the Cordillera Ampato; Quelccaya and Quisoquipina, both situated in the same Cordillera called Vilcanota. These four stations have been recording hourly meteorological data for approximately 9–14 years, including variables such as air temperature, wind speed and direction, precipitation, humidity, and radiation, as detailed in the data description section. The data information presented has been processed and allowed to calculate daily, monthly, and annual averages/accumulation. This dataset has not yet been widely disseminated within the scientific community or the general public, and we hope it serves as a valuable resource for future research on tropical glaciers.
As stated, this dataset is being shared in order to deal with the scarcity of data in the tropics and high-elevation locations such as these four glaciers. The value of these data of more than 10 years lies in the great utility they have for the validation of satellite products and climate models, support for bias corrections, hydrological studies, glaciological studies, and specific topics such as energy balance and mass balance in tropical glaciers as there are stations in ablation and accumulation zones of the glacier.
In 2011, the National Service of Meteorology and Hydrology of Peru (SENAMHI), through the Adaptation to the Impact of Rapid Glacier Retreat in the Tropical Andes Project (PRAA), financed by the World Bank’s Global Environment Facility Fund, installed two weather stations to monitor meteorological variables related to glacier mass loss and to study climate variations in the region. The first one is in the Junin region on the front moraine of the Lazontay glacier in the Cordillera Huaytapallana at 4,700 masl, and the second one is in the Cusco region, on the Cordillera Vilcanota in the tongue of the Quisoquipina glacier at 5,180 masl, specifically in the ablation zone.
In 2014, SENAMHI, in cooperation with the Appalachia State University, installed a third station in the Cusco region, in the Cordillera Vilcanota at 5,560 masl, in the accumulation zone of the Quelccaya Ice Field; so, in this case, the purpose of this station is to monitor meteorological variables involved in accumulation processes. Since 2016, this station has also been part of the Global Cryosphere Watch network. A year later, in 2015, a fourth station was installed in the Cordillera Ampato in the Arequipa region at an altitude of 5,800 masl on the ablation zone of the Coropuna glacier plate tongue, which is the highest glacier volcano in the world.
Location map of the automatic weather stations on glaciers:
The four stations record data on the variables recommended for CryoNet stations, specifically those related to surface meteorology (
Regarding the variables for glacier monitoring purposes, air temperature serves as an indicator of melting conditions if values are greater than or equal to 0 (≥0°C) and could also be used to compute the sensible heat flux, and air humidity was used to compute the latent heat flux. Wind speed is usually used to compute the sensible and latent heat flux; meanwhile, wind direction demonstrates the occurrence of katabatic winds. The albedo of a surface also determines the amount of heat reflected by that surface. It is an essential parameter for understanding the thermal balance of a surface exposed to solar radiation in the field of thermal comfort, climatology, and spacecraft.
Station location details and model brand sensors per variable of each station.
Station | Quisoquipina | Quelccaya | Huaytapallana | Coropuna |
---|---|---|---|---|
Region | Cusco | Cusco | Junin | Arequipa |
Cordillera | Vilcanota | Vilcanota | Huaytapallana | Ampato |
Longitude | 70°53′8″W | 70°48′59″W | 75°3′42″W | 72°35′59″W |
Latitude | 13°47′34″S | 13°55′11″S | 11°55′38″S | 15°32′10″S |
Altitude | 5,180 m | 5,650 m | 4,700 m | 5,800 m |
Glacier zone | Ablation zone | Accumulation zone | Outside of the glacier | Ablation zone |
Variables | Sensor per variable | |||
---|---|---|---|---|
Wind speed and direction | Young 05103-45 | Young RM-Young 5 | Young 05103-45 | Young 05103-45 |
Temperature and relative humidity | Vaisala HMP45C | Vaisala | Vaisala HMP45C | Rotronic HygroClip 2 |
Atmospheric pressure | Vaisala PTB110 | - | - | Vaisala PTB110 |
Radiation | KIPP & ZONEN: CNR1 (until 2016) CNR4 (since 2017) | - | - | KIPP & ZONEN: CNR1 (until 2018) CNR4 (since 2019) |
Precipitation | - | OTT Pluvio2 | Texas Electronics TE552 | - |
Ice surface temperature | - | - | - | Apogee Instruments SI-111 |
The raw dataset was collected as an Excel file and subsequently cleaned using Python libraries. First, values such as −999.9, NA, or non-numeric entries were deleted. Then, a second filter was applied to eliminate values outside the plausible limits, as outlined in
Air temperature: −40°C ≤ T ≤ 60°C.
Relative humidity: 0.0 ≤ RH ≤ 100%.
Precipitation: 0 ≤ PP ≤ 401 mm/h.
Wind speed: 0 ≤ WS ≤ 75 m/s.
Wind direction: 0° ≤ WD ≤ 360°.
Atmospheric pressure: 300 hPa ≤
Incoming short-wave radiation: −1 ≤ SRin ≤1,400 W/m2.
Albedo: 0 ≤ Alb ≤1.
We also evaluated the time consistency and internal consistency of the parameters. Following a diurnal and seasonal boxplot analysis, an outlier detection process was applied to evaluate the “outer fences,” defined by
This dataset is a compilation of hourly measurements from the four weather stations presented as a daily mean or cumulative sum (in the case of the precipitation variable) in
Time series of daily weather data measured at the four stations from 2011 to 2024. The variables are shown from top to bottom as follows: incoming long-wave radiation (W/m2), outgoing long-wave radiation (W/m2), incoming short-wave radiation (W/m2), outgoing short-wave radiation (W/m2), relative humidity (%), wind speed (m/s), accumulated precipitation (mm), and air temperature (°C).
The Quisoquipina station has the largest amount of data among the four stations; it has recorded hourly data from 28 September 2011 until 12 July 2024 (with missing values between 2017 and 2019) for the following variables: air temperature, relative humidity, and wind speed and direction. Radiation variables were recorded as incoming and outgoing short-wave radiation, with averages of 463.64 W/m2 and 256.59 W/m2, respectively. Since 2018, there was a generalized increase in these variables, probably due to the radiation sensor change. Furthermore, long-wave radiation values were also recorded, with average incoming and outgoing components of 269.29 W/m2 and 308.69 W/m2, respectively. From these variables, we calculated the short-wave net radiation, long-wave net radiation, and total net radiation. Finally, albedo values were analyzed, with 0.59 as the total average.
The Quelccaya station, located at the second highest elevation, recorded hourly data for seven variables from 15 October 2014 until 11 October 2023 (with most missing values between 2015 and 2016). These variables include air temperature, relative humidity, and wind speed and direction data (average wind speed of 3.67 m/s, with southeastern winds being the most frequent), and the maximum wind speed is also recorded. Finally, in contrast to the previous stations, this one records hourly precipitation values, with a maximum cumulative daily sum of 34.49 mm.
The Huaytapallana station recorded hourly data of five variables from 26 August 2013 until 2 July 2024 (most missing values in 2015). These variables include air temperature, relative humidity, and wind speed and direction, with an average speed of 1.85 m/s and mostly northerly winds. In addition, precipitation values reach 32.98 mm of the cumulative daily sum.
The Coropuna station recorded hourly data from 10 September 2014 until 9 July 2024, with missing values in 2018 and 2020. This station is the second in terms of the number of recorded values but with the most amount of variables, which include atmospheric pressure measured in hPa unit, air temperature (hourly maximum and minimum), relative humidity, and wind speed and direction; the wind speed values from this station are the highest (3.81 m/s as average) among all other stations, which corresponds to its location at the highest elevation. Meanwhile, the most frequent wind direction is from the south. This station also recorded solar radiation data, such as outgoing and incoming short-wave radiation; the calculated average values of these variables are 330.72 W/m2 and 525.01 W/m2, respectively; incoming and outgoing long-wave radiation had averages values of 238.15 W/m2 and 291.93 W/m2, respectively. Based on these, short-wave and long-wave net radiation and total net radiation were calculated. Other variables such as ice surface temperature were also recorded exclusively at this station.
SENAMHI is currently planning to operate the stations as part of a cryosphere observation network, which will be proposed for inclusion in the Cryonet network operated by the WMO. In addition, efforts are underway to standardize data acquisition procedures as the current framework are different for each station.
The daily, monthly and annual cleaned datasets are available at:
WS: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft. LC: Data curation, Formal Analysis, Visualization, Writing – original draft. MV: Data curation, Writing – original draft.
The author(s) declare that no financial support was received for the research and/or publication of this article.
The authors would like to acknowledge the institutions whose collaboration allowed us to establish the station network on Peruvian glaciers, the PRAA for funding the Huaytapallana and Quisoquipina stations, Appalachia State University, in particular Baker Perry who shared and gave us permission to publish the data (2014–2022) from Quelccaya, and the collaboration of AEDES in the installation, operation, and maintenance of the Coropuna station.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declare that no Generative AI was used in the creation of this manuscript.
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