The Peñalara Mountain Meteorological Network (1999–2014): Description, Preliminary Results and Lessons Learned
Abstract
:1. Introduction
2. Method
2.1. Measuring Objective
2.2. Measuring Strategy
2.2.1. Measuring Technique
2.2.2. Density of Stations
2.2.3. Sitting Criteria
2.2.4. Remoteness
2.2.5. Extreme Environmental Conditions
2.2.6. Microclimate
2.2.7. Safety and Environment
2.3. Quality Assurance and Quality Control
2.3.1. Preventive Maintenance
2.3.2. Corrective Maintenance
2.3.3. Data Validation
2.3.4. Storage and Reporting
3. Results and Discussion
3.1. Description of the Network
3.2. Temperature Observations
- effect of down-up short wave radiation reflected from ground due to snow cover. Radiation shields are designed for an up-down direction of direct radiation
- effect of raised ground level due to snow height in winter
- effect of evaporation of water drops condensed over the temperature sensor
3.3. Wind Observations
3.4. Precipitation Observations
4. Conclusions
- RMPNP evolved considerably from 1999, when the first station was installed, to 2014. The overall performance of the network has been improved in the last decade thanks to an optimization of the power consumption, application of a sustainable quality assurance program and the use of a reliable telecommunication system for operational alarms.
- Apart from the frequent sensor replacements, the logging system and changes made in data processing methods during this long operation period, the observations of air temperature at RMPNP have shown to be complete and homogeneous, hence they are valid for future climate analysis.
- Factors affecting data completion and reliability are common to other automatic networks, but here some negative factors gain prominence with increasing height like: icing, low solar power, difficulties for maintenance and breakage.
- A two phase validation based first on automatic checks when data is received for fast detection of errors and a second delayed phase which can be iteratively performed when new information is available, has shown to be efficient.
- Five automatic weather stations ranging from 1104 m.a.s.l. to 2079 m.a.s.l. of altitude but in a small territory of 40 km have been enough to show the complexity of the weather phenomena in the area, which should be further investigated.
- Temperature records in the area show a typical alpine behavior: decreasing temperatures with height with some inversion episodes during the first morning hours and a marked decreasing diurnal temperature amplitude. Monthly means have been calculated for every site, but a deeper analysis should be done in the future. For statistically representative trend analyses, longer records will be necessary so this should be done in the future if homogeneity of the series is kept.
- Regarding wind speed and direction, wind roses for the whole period have been calculated for the less locally influenced site. The prevailing wind direction is SW for all seasons. This is coherent with the prevailing synoptic wind directions, but also an orographic influence is expected since valley axis also runs in this direction. This issue should be investigated in the future.
- The horizontal axes four blade helical propeller wind anemometer and wind vane have shown to be more robust and less rime influenced than other non-heated mechanical alternatives. Power failure, sensor breakage and icing are the main sources of wind data loss. Icing is only responsible of 11% of the data loss at one of the higher sites.
- As expected, non-heated tipping bucket rain gauges have shown to perform fairly well only during spring, summer and fall if ambient temperature is above 5 °C, but they require a lot of effort for data validation.
- Manual observations of precipitation performed at one site in parallel with an automatic weather station have resulted in being crucial for assessing precipitation in the area. It has also helped to develop algorithms for data validation.
- Snow height measurement has shown to be a good estimator of snow precipitation when rain gauges are not operative, but further analysis will be necessary to convert height variations into equivalent precipitated water.
- From this experience and the available literature, we conclude that a basic but reliable automatic weather station at a very remote location only powered by the sun should consist of:
- -
- Precipitation: gravimetric measurement method for precipitation with very wide inlets (no funnels), with wind shields, using antifreeze during the winter and installed in a very solid mast above expected snow pack.
- -
- Temperature/Humidity: Low power aspirated radiation shields with smart management of the aspirated process in order to minimize power consumption. Redundant measurements of temperature at different angles should help to diminish and investigate the effect of rime and prevent data loss.
- -
- Wind: ultrasonic rugged sensors with a smart management of heating for lower consumption, if possible; not necessarily installed at the standard 10 m height since this jeopardizes the structural integrity and makes sensor substitution and maintenance much more complex. Sensor height will change with snow pack and should be taken into account.
- -
- Solar radiation: Sensors with a smart heating, low power algorithm should be found or developed. Investigation into minimum heating activation and detection of total or partial sensor malfunction due to ice and snow should be done in the future, perhaps by using cameras.
- -
- Ground temperature: Reliable soil temperature sensors at different depths are easy to perform and can be valid for data validation and gap filling.
- -
- Snow height: Ultrasonic sensors, which are crucial for correcting and validating many of the variables measured at this sites.
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
AEMET | Agencia Estatal de MEteorología (Spanish Meteorological Agency) |
ASCII | American Standard Code for Information Interchange |
GPRS | General Packet Radio Service |
GSM | Global System for Mobile communications |
QAQC | Quality Assurance and control |
RMPNP | Red Meteorológica del Parque Natural de Peñalara |
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Year | Collection | Volume | Storage | Station | ||||
---|---|---|---|---|---|---|---|---|
Method | Data (bytes) | 001 | 002 | 003 | 004 | 005 | ||
Ontalva | C. Mediana | Zabala | Cotos | Alameda | ||||
1999 | Local | 202039 | ASCII | 34 | 42 | |||
2000 | Local | 722874 | ASCII | 98 | 100 | |||
2001 | Local | 1015623 | ASCII | 96 | 94 | |||
2002 | Local | 1698549 | ASCII | 83 | 73 | |||
2003 | Local | 2198111 | ASCII | 63 | 61 | |||
2004 | Local | 2850198 | ASCII | 84 | 89 | |||
2005 | Local | 3613656 | S.Sheet | 91 | 85 | 96 | ||
2006 | GSM | 4219771 | S.Sheet | 55 | 58 | 51 | ||
2007 | GSM | 5375096 | S.Sheet | 66 | 80 | 56 | ||
2008 | GPRS | 7510050 | SQL | 84 | 92 | 90 | 96 | |
2009 | GPRS | 9911400 | SQL | 88 | 87 | 88 | 98 | 21 |
2010 | GPRS | 12634429 | SQL | 81 | 100 | 75 | 95 | 99 |
2011 | GPRS | 15261155 | SQL | 95 | 80 | 83 | 98 | 88 |
2012 | GPRS | 18022734 | SQL | 97 | 93 | 84 | 99 | 100 |
2013 | GPRS | 20629862 | SQL | 100 | 80 | 79 | 100 | 82 |
2014 | GPRS | 21966337 | SQL | 99 | 77 | 75 | 99 | 55 |
Average | 92 | 80 | 79 | 89 | 75 |
Code | Name | Comments on Measurements Uncertainties |
---|---|---|
001 | Ontalva | This station is located in the lower land of the valley. Land use is natural grass immersed into a pine forest in a sheltered clear. Wind observation is not very representative of the boundary layer wind due to obstacles, much higher than tower. The not heated rain gauge might under sample in winter due to snow blocking. Minimum temperatures are lower than expected due to this location is immersed in Valle de la Umbría, a north oriented valley within Lozoya Valley. Cold air drainage from higher elevations is also expected |
002 | Cabeza Mediana | Mountain site. Land use is natural pasture with some small trees. Nice location in the top of a flat and round ended hill in the middle of Valle del Lozoya. Promising representation of wind measurements. Not heated rain gauge is surely under sampling real precipitation in winter |
003 | Refugio Zabala | Very high mountain environmental conditions. Land use is mainly bare rock with snow cover during many months. Sensors are located in the top of small construction for security and impact reasons, so some impact is expected in wind and precipitation measurements. Good representation of temperature at 4 m but rime might be influencing temperature measurements in winter. Not heated rain gauge, so precipitation measurements are surely under sampled in winter |
004 | Cotos | High mountain site. Land use is natural pasture with tall pine trees at 100 m. Good representation but the site is located not in a very flat area. Local effects of catabatic cold air drainage from higher terrain is expected due to the slope. Not heated rain gauge, so precipitation measurements are surely under sampled |
005 | Alameda | Good representation of all measurements. Land use is natural grass. Even though rain gauge is not heated, under sampling might be less important due to less snow precipitation at this altitude, but needs to be taken into account in winter |
Code | Name | Coordinates (City, Province) | UTM (m) Altitude (m.a.s.l.) | Starting Year | Variable Code | Magnitude (Units) | Sensor (2014) |
---|---|---|---|---|---|---|---|
001 | Ontalva | 2008 | TA01 | Air temperature at 2 m (°C) | Vaisala HMP45 | ||
40°5220 N | X: 424736 | 2008 | HR01 | Relative humidity at 2 m (%) | Vaisala HMP45 | ||
3°531 W | Y: 4524980 | 2008 | LL01 | Liquid precipitation at 3 m (mm) | NovaLynx 260-2500 | ||
(Rascafría, Madrid) | Z: 1190 | 2008 | VV01 | Wind velocity at 6 m (m/s) | NRG #40 | ||
2008 | DV01 | Wind direction at 6 m (°) | NRG | ||||
002 | 1999 | TA01 | Air temperature at 2 m (°C) | Vaisala HMP45 | |||
40°5013 N | X: 423450 | 1999 | HR01 | Relative humidity at 2 m (%) | Vaisala HMP45 | ||
Cabeza | 3°5415 W | Y: 4521790 | 1999 | LL01 | Liquid precipitation at 3 m (mm) | NovaLynx 260-2500 | |
Mediana | (Rascafría, Madrid) | Z: 1691 | 1999 | VV01 | Wind velocity at 6 m (m/s) | Young Wind Monitor | |
1999 | DV01 | Wind direction at 6 m (°) | Young Wind Monitor | ||||
2008 | PA01 | Atmospheric pressure at 1.75 m (hPa) | NovaLynx | ||||
003 | 1999 | TA01 | Air temperature at 2 m (°C) | Vaisala HMP45 | |||
1999 | HR01 | Relative humidity at 2 m (%) | Vaisala HMP45 | ||||
Refugio | 40°5020 N | X: 419300 | 1999 | LL01 | Liquid precipitation at 4 m (mm) | Young wind monitor | |
Zabala | 3°571 W | Y: 4521330 | 2008 | LL02 | Liquid precipitation at 4 m (mm) | Lambrecht | |
(Rascafría, Madrid) | Z: 2079 | 1999 | VV01 | Wind velocity at 6 m (m/s) | Young Wind Monitor | ||
1999 | DV01 | Wind direction at 6 m (°) | Young Wind Monitor | ||||
2008 | PA01 | Atmospheric pressure at 1.75 m (hPa) | NovaLynx | ||||
004 | Cotos | 2008 | TA02 | Air temperature at 2 m (°C) | E+E Elektronic | ||
2005 | TA01 | Air temperature at 10 m (°C) | E+E Elektronic | ||||
40°4931 N | X: 418955 | 2008 | HR02 | Relative humidity at 2 m (%) | E+E Elektronic | ||
3°40 W | Y: 4519800 | 2005 | LL01 | Liquid precipitation at 1.5 m (mm) | NovaLynx | ||
(Rascafría, Madrid) | Z: 1857 | 2005 | VV01 | Wind velocity at 10 m (°) | NGR #40 | ||
2005 | DV01 | Wind direction at 10 m (°) | NGR | ||||
2008 | HN01 | Snow height (m) | Judd Comunicatio | ||||
005 | Alameda | 40°5453 N | X: 428934 | 2009 | TA01 | Air temperature at 4 m (°C) | E+E Elektronic |
3°5039 W | Y: 4529640 | 2009 | HR01 | Relative humidity at 4 m (%) | E+E Elektronic | ||
(Alameda, Madrid) | Z: 1102 | 2009 | LL01 | Liquid precipitation at 4 m (mm) | NovaLynx |
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Durán, L.; Rodríguez-Muñoz, I.; Sánchez, E. The Peñalara Mountain Meteorological Network (1999–2014): Description, Preliminary Results and Lessons Learned. Atmosphere 2017, 8, 203. https://doi.org/10.3390/atmos8100203
Durán L, Rodríguez-Muñoz I, Sánchez E. The Peñalara Mountain Meteorological Network (1999–2014): Description, Preliminary Results and Lessons Learned. Atmosphere. 2017; 8(10):203. https://doi.org/10.3390/atmos8100203
Chicago/Turabian StyleDurán, Luis, Irene Rodríguez-Muñoz, and Enrique Sánchez. 2017. "The Peñalara Mountain Meteorological Network (1999–2014): Description, Preliminary Results and Lessons Learned" Atmosphere 8, no. 10: 203. https://doi.org/10.3390/atmos8100203