Nearby Meteorological Station Research Articles

Method for prediction of landslide movements based on random forests

Prediction of landslide movements with practical application for landslide risk mitigation is a challenge for scientists. This study presents a methodology for prediction of landslide movements using random forests, a machine learning algorithm based on regression trees. The prediction method was established based on a time series consisting of 2 years of data on landslide movement, groundwater level, and precipitation gathered from the Kostanjek landslide monitoring system and nearby meteorological stations in Zagreb (Croatia). Because of complex relations between precipitations and groundwater levels, the process of landslide movement prediction is divided into two separate models: (1) model for prediction of groundwater levels from precipitation data and (2) model for prediction of landslide movements from groundwater level data. In a groundwater level prediction model, 75 parameters were used as predictors, calculated from precipitation and evapotranspiration data. In the landslide movement prediction model, 10 parameters calculated from groundwater level data were used as predictors. Model validation was performed through the prediction of groundwater levels and prediction of landslide movements for the periods from 10 to 90 days. The validation results show the capability of the model to predict the evolution of daily displacements, from predicted variations of groundwater levels, for the period up to 30 days. Practical contributions of the developed method include the possibility of automated predictions, updated and improved on a daily basis, which would be an important source of information for decisions related to crisis management in the case of risky landslide movements.

Modelling population exposure to arsenic release during the chemical accident occurred at Manfredonia (Italy) in 1976

Introduction On September 26th 1976, in Manfredonia, Italy, a mixture containing arsenic compounds was released into the atmosphere due to an accident in a fertilizer production plant. 40 years later, the municipality promoted an epidemiological programme to investigate possible long-term health effects in the population. Aim of this work is to estimate population exposure to arsenic, taking into account uncertainties on the accident dynamics by using a dispersion model with different setup initial conditions. Methods Contaminant dispersion was estimated with the CALPUFF model initialized with a meteorological model. Meteorological data were not available at the plant location but only at two Air Force weather stations, a few kilometers away. Evaluation of the meteorological model was performed with data available on the same day and with data available in later years in similar synoptic conditions. Different hypothesis on puff vertical release, puff status and composition were assumed from direct testimonies, documental and literature information. We used measured arsenic deposition in soils around the town to test the model inputs. Results Meteorological model during the accident evidences complex mountain/sea breeze circulations under high-pressure synoptic conditions. It matches the nearby meteorological station records. Results indicate that the model is capable to reproduce the mean flow and dispersion with some uncertainties due to the hypothesis on the release characterization. Conclusions For the first time an up-to-date dispersion model was used and integrated with environmental data, testimonies and proxies to assess the population exposure during the Manfredonia accident. Uncertainties of results should be taken into account in the epidemiological study. The case study confirms the need to collect data on concentration and dispersion of released chemicals during the early phase of an accident, considering the difficulties in collecting them in a late phase.

A 2000-year temperature reconstruction in the Animaqin Mountains of the Tibet Plateau, China

A 2665-year ring-width chronology was developed based on Qilian juniper from the upper treeline of the Animaqin Mountains on the eastern Tibetan Plateau. Correlation analysis results showed that the chronology was significantly negatively correlated with April–June maximum temperature at nearby meteorological stations, indicating that maximum temperature is the factor that limits tree growth in this area. Accordingly, we reconstructed the average April–June maximum temperature variations since 261 BC. Our regression model explained 37.9% of the total variance for the whole calibration period of 1960–2012. Our reconstruction revealed that the maximum temperature started to increase from approximately 1750 without a rapid warming trend, and the warmest period was from AD 890 to 947, as opposed to the recent period, whereas the period from AD 351–483 was the coldest. Significant periods in the wavelet power spectrum were approximately 2–8 years, 20–30 years, 30–60 years, and 60–130 years, as well as some long-term periods (more than 200 years). Comparisons with other temperature series from neighboring regions and the Northern Hemisphere as a whole support the validity of our reconstruction and suggest that it provides a representation of the temperature change for the Animaqin area, although asymmetric variation patterns in minimum and maximum temperatures were found.

Trends and variability in the global dataset of glacier mass balance

Glacier mass balance (i.e., accumulation and ablation) is the most direct connection between climate and glaciers. We perform a comprehensive evaluation of the available global network of mass-balance measurements. Each mass-balance time series is decomposed into a trend and the variability about that trend. Observed variability ranges by an order of magnitude, depending on climate setting (i.e., maritime vs continental). For the great majority of glaciers, variability is well characterized by normally distributed, random fluctuations that are uncorrelated between seasons, or in subsequent years. The magnitude of variability for both summer and winter is well correlated with mean wintertime balance, which reflects the climatic setting. Collectively, summertime variability exceeds wintertime variability, except for maritime glaciers. Trends in annual mass balance are generally negative, driven primarily by summertime changes. Approximately 25 % of annual-mean records show statistically significant negative trends when judged in isolation. In aggregate, the global trend is negative and significant. We further evaluate the magnitude of trends relative to the variability. We find that, on average, trends are approximately −0.2 standard deviations per decade, although there is a broad spread among individual glaciers. Finally, for two long records we also compare mass-balance trends and variability with nearby meteorological stations. We find significant differences among stations meaning caution is warranted in interpreting any point measurement (such as mass balance) as representative of region-wide behavior. By placing observed trends in the context of natural variability, the results are useful for interpreting past glacial history, and for placing constraints on future predictability.

Ground thermal regime on the Kaffiøyra Plain (NW Spitsbergen) in the period from 1 September 2012 to 31 August 2014

The article presents the results of ground temperature measurements taken at 1 cm to 100 cm below ground level on the Kaffioyra Plain (NW Spitsbergen) from 1 September 2012 to 31 August 2014. Observations of thermal conditions were carried out at three sites located in characteristic Polar ecotopes: on a beach, in tundra and on a moraine. The results of ground temperature measurements for the Kaffioyra Plain were compared to the observations of weather conditions at the nearby meteorological station in Ny-Alesund. The variability of ground temperature was analysed in annual, seasonal and diurnal courses. These reflected the prevailing meteorological conditions at the time. Substantial differences in the ground thermal conditions were found between the ecotopes, which was due to the morphological diversity of the ground, its moisture content, vegetation and snow cover, as well as the depth of the permafrost.

A simple wind–tree interaction model predicting the probability of wind damage at stand level

Forest wind damage occurs under the passage of strong intermittent wind gusts at tree level. In order to predict the probability of tree damage of a forest, a simple statistical wind speed model was developed and coupled to a tree swaying model. The wind model is based on a stochastic approach and on some universal characters of normalized wind statistics at canopy top. This model aims at generating high frequency (10Hz) time series of the three wind velocity components at canopy top knowing only the wind intensity from a nearby meteorological station and the height and cumulative plant area index of the forest. Compared to field measurements and large-eddy simulations over different canopy structures and densities, the wind model was able to reproduce accurately the main features of canopy-top wind dynamics, in particular the signature of the mixing-layer type coherent eddy structures developing at canopy top. Coupled with a tree swaying model, the model has allowed to predict the probability of wind damage of forest following the windstorm intensity and duration, and following the main tree characteristics resulting from silvicultural scenarios. By responding to some weaknesses of existing mechanistic wind risk models, this simple wind–tree interaction model may represent the first step toward a new generation of mechanistic wind risk models based on a probabilistic approach.

Ground thermal regime on the Kaffiøyra Plain (NW Spitsbergen) in the period from 1 September 2012 to 31 August 2014

Abstract The article presents the results of ground temperature measurements taken at 1 cm to 100 cm below ground level on the Kaffiøyra Plain (NW Spitsbergen) from 1 September 2012 to 31 August 2014. Observations of thermal conditions were carried out at three sites located in characteristic polar ecotopes: on a beach, in tundra and on a moraine. The results of ground temperature measurements for the Kaffiøyra Plain were compared to the observations of weather conditions at the nearby meteorological station in Ny-Ålesund. The variability of ground temperature was analysed in annual, seasonal and diurnal courses. These reflected the prevailing meteorological conditions at the time. Substantial differences in ground thermal conditions were found between the ecotopes, which was due to the morphological diversity of the ground, its moisture content, vegetation and snow cover, as well as the depth of the permafrost.

Thinning of the Monte Perdido Glacier in the Spanish Pyrenees since 1981

Abstract. This paper analyzes the evolution of the Monte Perdido Glacier, the third largest glacier in the Pyrenees, from 1981 to the present. We assessed the evolution of the glacier's surface area by analysis of aerial photographs from 1981, 1999, and 2006, and changes in ice volume by geodetic methods with digital elevation models (DEMs) generated from topographic maps (1981 and 1999), airborne lidar (2010) and terrestrial laser scanning (TLS, 2011, 2012, 2013, and 2014) data. We interpreted the changes in the glacier based on climate data from nearby meteorological stations. The results indicate that the degradation of this glacier accelerated after 1999. The rate of ice surface loss was almost three times greater during 1999–2006 than during earlier periods. Moreover, the rate of glacier thinning was 1.85 times faster during 1999–2010 (rate of surface elevation change = −8.98 ± 1.80 m, glacier-wide mass balance = −0.73 ± 0.14 m w.e. yr−1) than during 1981–1999 (rate of surface elevation change = −8.35 ± 2.12 m, glacier-wide mass balance = −0.42 ± 0.10 m w.e. yr−1). From 2011 to 2014, ice thinning continued at a slower rate (rate of surface elevation change = −1.93 ± 0.4 m yr−1, glacier-wide mass balance = −0.58 ± 0.36 m w.e. yr−1). This deceleration in ice thinning compared to the previous 17 years can be attributed, at least in part, to two consecutive anomalously wet winters and cool summers (2012–2013 and 2013–2014), counteracted to some degree by the intense thinning that occurred during the dry and warm 2011–2012 period. However, local climatic changes observed during the study period do not seem sufficient to explain the acceleration of ice thinning of this glacier, because precipitation and air temperature did not exhibit statistically significant trends during the study period. Rather, the accelerated degradation of this glacier in recent years can be explained by a strong disequilibrium between the glacier and the current climate, and likely by other factors affecting the energy balance (e.g., increased albedo in spring) and feedback mechanisms (e.g., heat emitted from recently exposed bedrock and debris covered areas).

Twentieth-century warming preserved in a Geladaindong mountain ice core, central Tibetan Plateau

AbstractHigh-resolution δ18O records from a Geladaindong mountain ice core spanning the period 1477-1982 were used to investigate past temperature variations in the Yangtze River source region of the central Tibetan Plateau (TP). Annual ice-core δ18O records were positively correlated with temperature data from nearby meteorological stations, suggesting that the δ18O record represented the air temperature in the region. A generally increasing temperature trend over the past 500 years was identified, with amplified warming during the 20th century. A colder stage, spanning before the 1850s, was found to represent the Little Ice Age with colder periods occurring during the 1470s–1500s, 1580s–1660s, 1700s–20s and 1770s–1840s. Compared with other temperature records from the TP and the Northern Hemisphere, the Geladaindong ice-core record suggested that the regional climate of the central TP experienced a stronger warming trend during the 20th century than other regions. In addition, a positive relationship between the Geladaindong δ18O values and the North Atlantic Oscillation index, combined with a wavelet analysis of δ18O records, indicated that there was a potential atmospheric teleconnection between the North Atlantic and the central TP.

Mass-balance reconstruction for Glacier No. 354, Tien Shan, from 2003 to 2014

AbstractThis study presents a reconstruction of the seasonal mass balance of Glacier No. 354, located in the Akshiirak range, Kyrgyzstan, from 2003 to 2014. We use a distributed accumulation and temperature-index melt model driven by daily air temperature and precipitation from a nearby meteorological station. The model is calibrated with in situ measurements of the annual mass balance collected from 2011 to 2014. The snow-cover depletion pattern observed using satellite imagery provides additional information on the dynamics of mass change throughout the melting season. Two digital elevation models derived from high-resolution satellite stereo images acquired in 2003 and 2012 are used to calculate glacier volume change for the corresponding period. The geodetic mass change thus derived is used to validate the modelled cumulative glacier-wide balance. For the period 2003–12 we find a cumulative mass balance of –0.40±10mw.e.a-1. This result agrees well with the geodetic balance of –0.48±0.07mw.e.a-1over the same period.

Interviews of Mongolian herders and high resolution precipitation data reveal an increase in short heavy rains and thunderstorm activity in semi-arid Mongolia

Increases in extreme record-breaking daily precipitation events have accompanied warming temperatures causing increased flooding in many areas of the World, but are not well documented for arid and semi-arid regions. In semi-arid Mongolia where warming has been over 2o C from 1940 to 2008, nomadic herders described their concerns over an increase in the number of hot days and a shift from multi-day gentle rains to heavy rains lasting less than one hour that damage their pastures, animals, gers and people, suggesting a transition from stratiform rains to convective storms. The brief intense rains are not seen in daily precipitation data typically reported by meteorological stations, and here the correlation between fine-scale rainfall readings and thunderstorm activity were used to hind cast brief heavy rains. From 2008 to 2012, an automated weather station in Dalbay Valley at Lake Hovsgol, Mongolia, recording at 5-min intervals, detected at least 40 heavy sub-daily summer rains each lasting less than 40 min. Heavy rains in Dalbay were correlated with thunderstorm activity and were 2.5 times more likely to occur when thunderstorms were reported within the previous 24 h at the Hatgal meteorological station (80 km to the southwest of Dalbay) than when no thunderstorms were reported. Daily thunderstorm frequency, recorded at nearby meteorological stations from 1960 to 2012, has increased and thus supports herders’ perceptions that the frequency of the short heavy rains have increased.

Global solar radiation estimation using artificial neural network by the addition of nearby meteorological stations' solar radiation data and exergy of solar radiation: a case study

The artificial neural networks (ANNs) can be used to accurately predict the global solar radiation (GSR). There are many geographical, meteorological and terrestrial parameters affecting GSR. In this study, the most relevant of six input parameters are selected to predict the GSR of Goksun Station in Turkey using Waikato environment for knowledge analysis (Weka) Software. The effect of using nearby meteorological stations' GSR data as input on GSR prediction is investigated. Different ANN models are developed to demonstrate the difference between the exclusion and inclusion of these parameters on the model. The results show that the exclusion of less influential parameters and the inclusion of three nearby stations' GSR data has improved performance criteria. Petela, Spanner and Jeter's approaches are used for exergy analysis of measured and estimated GSR values. The mean exergy-to-energy ratio for both Petela and Spanner's approaches is 0.934, while Jeter's approach showed 0.950.

How to report biogas production when monitoring small-scale digesters in field

The aim of this research was to evaluate the error originated when biogas production from field monitoring digesters, influenced by the diurnal temperature cycle, was normalized to standard conditions for pressure and temperature (273.15 K and 100 kPa) from local conditions. The biogas production data is often reported without indicating if done under local conditions, whether these conditions have been standardized and, if they have actually been standardized, the standard temperature and pressure is not indicated. In this research ambient and biogas temperature, as well as biogas production were monitored with a 30 min frequency during three consecutive days, in three different tubular digesters. Normalization was realized using the high frequency data collected as reference values, and also using daily biogas production with mean daily biogas, ambient and nearby meteorological station temperatures. The outcome of this research shows that normalization of biogas production can be obtained using daily biogas production and the daily mean ambient temperature with an overestimation by no more than 1.5%, in comparison to the normalization achieved by using high frequency data from biogas temperature and production. Using mean daily ambient temperature or mean daily biogas temperature results in the same overestimation, while using mean daily ambient temperature from a nearby airport weather station pushes the overestimation up to 2.7%. So, if ambient temperature and altitude is identified, biogas production reported in local conditions can be normalized.

Validation of quantitative IR thermography for estimating the U-value by a hot box apparatus

Energy saving plays a key role in the reduction of energy consumption and carbon emission, and therefore it is essential for reaching the goal of the 20-20-2020 policy.In particular, buildings are responsible of about 30% of the total amount of Europe energy consumption; the increase of their energy efficiency with the reduction of the thermal transmittance of the envelope is a point of strength with the actions and strategies of the policy makers.Currently, the study of energy performance of buildings is based on international standards, in particular the Italian one allows to calculate the U-value according the ISO 6946 or by in-situ measurements, using a heat flow meter (HFM), following recommendations provided in ISO 9869.In the last few years, a new technique, based on Infrared Thermography (IRT) (also referred to as Infrared Thermovision Technique - ITT), has been proposed for in situ determination of the thermal transmittance of opaque building elements. Some case studies have been reported.This method has already been applied on existing buildings, providing reliable results, but also revealing some weaknesses.In order to overcome such weak points and to assess a systematic procedure for the application of IRT, a validation of the method has been performed in a monitored environment.Infrared camera, the heat flow meter sensors and a nearby meteorological station have been used for thermal transmittance measurement. Comparison between the U-values measured in a hot box with IRT as well as values calculated following international standards and HFM results has been effected. Results give a good description of the advantages, as well as of the open problems, of IR Thermography for estimating the U-value.Further studies will help to refine the technique, and to identify the best operative conditions.

Abiotic predictors and annual seasonal dynamics of Ixodes ricinus, the major disease vector of Central Europe.

BackgroundAbiotic conditions provide cues that drive tick questing activity. Defining these cues is critical in predicting biting risk, and in forecasting climate change impacts on tick populations. This is particularly important for Ixodes ricinus nymphs, the vector of numerous pathogens affecting humans.MethodsA 6-year study of the questing activity of I. ricinus was conducted in Central Bohemia, Czech Republic, from 2001 to 2006. Tick numbers were determined by weekly flagging the vegetation in a defined 600 m2 field site. After capture, ticks were released back to where they were found. Concurrent temperature data and relative humidity were collected in the microhabitat and at a nearby meteorological station. Data were analysed by regression methods.ResultsDuring 208 monitoring visits, a total of 21,623 ticks were recorded. Larvae, nymphs, and adults showed typical bimodal questing activity curves with major spring peaks and minor late summer or autumn peaks (mid-summer for males). Questing activity of nymphs and adults began with ~12 h of daylight and ceased at ~9 h daylight, at limiting temperatures close to freezing (in early spring and late autumn); questing occurred during ~70 % calendar year without cessation in summer. The co-occurrence of larvae and nymphs varied annually, ranging from 31 to 80 % of monitoring visits, and depended on the questing activity of larvae. Near-ground temperature, day length, and relative air humidity were all significant predictors of nymphal activity. For 70 % of records, near-ground temperatures measured in the microhabitat were 4–5 °C lower than those recorded by the nearby meteorological observatory, although they were strongly dependent. Inter-annual differences in seasonal numbers of nymphs reflected extreme weather events.ConclusionsWeather predictions (particularly for temperature) combined with daylight length, are good predictors of the initiation and cessation of I. ricinus nymph questing activity, and hence of the risk period to humans, in Central Europe. Co-occurrence data for larvae and nymphs support the notion of intrastadial rather than interstadial co-feeding pathogen transmission. Annual questing tick numbers recover quickly from the impact of extreme weather events.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-015-1092-y) contains supplementary material, which is available to authorized users.

Effect of regulated deficit irrigation on tree growth of pear cv. Triunfo de Viena

The deficit irrigation controlled (RDI) as reducing water in phases of the crops where it is less sensitive to water stress, three different drip irrigation treatments were applied in pear tree crop of Triunfo de Viena variety. Control, irrigated throughout the year at 100% of estimated crop evapotranspiration (ETc); 67%ETc and 55%ETc treatments were irrigated at 67 and 55% of the (ETc), respectively during the period of rapid fruit growth (from December 28, 2011 until February 29, 2012) and at 100% (ETc) during the rest of the season. Reference evapotranspiration (ETo) was determined by the Penman-Monteith, with hourly weather data collected in a nearby meteorological station. During the test total precipitation was 53.8 mm and the water application in the control treatments was 683.0 mm. The results indicate that none of the treatments differed significantly (P≤0.05) from control in terms of yield and quality, resulting in water savings of 33 to 45% in 67%ETc and 55%ETc respectively compared to the control. The vegetative growth of shoots had a behavior defined by a sigmoid curve fitted to a four parameter logistic equation, and it was significantly reduced in the 67%ETc and 55%ETc, respect to control, at the end of the restriction.

Impact of estimated solar radiation on gross primary productivity simulation in subtropical plantation in southeast China

Sunshine duration is widely used to estimate solar radiation, but this estimated inherently contains some uncertainties, limiting its applications. This study investigated the impacts of the estimated solar radiation on simulated gross primary productivity (GPP), which were obtained using ecosystem models – light use efficiency model (LUE) and process-based model – Boreal Ecosystem Productivity Simulator (BEPS) at an evergreen coniferous forest ecosystem in southeast China. The models for solar radiation and diffuse radiation estimation were calibrated through observation data from nearby meteorological stations. The results showed that the established model could be successfully used to estimate solar radiation with high coefficient of determination (0.92) and low root mean square error (2.18MJm−2day−1), but the solar radiation was overestimated when the clearness index was less than 0.15 and underestimated when it was within the range of 0.2–0.35 or greater than 0.6. The estimated solar radiation has significant influence on the diffuse radiation estimation and GPP simulation comparing with using observations. The two ecosystem models reacted differently to the errors of estimated solar radiation. For the LUE model, the estimated solar radiation led to the underestimated GPP in growing season (May–October), and overestimated GPP during non-growing season (November–April) with the bias ranged from −11% to 10% depending on the month of a year. For the BEPS model, estimated solar radiation resulted in overestimated GPP in most months with the bias ranged from −6% to 20%. The difference between the simulated GPP based on these two sources of solar radiation could be counteracted to some extent at the annual scale, especially for LUE model.

Groundwater balance estimation in karst by using simple conceptual rainfall–runoff model

The objective of this work is the study of Opacac karst spring which geographically lies in Dalmatia (Croatia). Numerous studies have been carried out in karst aiming the investigation of groundwater regime. The karst spring hydrograph can reflect the groundwater regime and consequently the analysis is based on them. A simple conceptual rainfall–runoff model is used for the estimation of groundwater balance components including the influences of time-invariant catchment boundaries (Jukic and Denic-Jukic 2009). The proposed parameter estimation procedure merges the soil-moisture balance and the groundwater balance approaches to obtain the complete groundwater budget. The effective rainfall is calculated by using mathematical model based on soil-moisture balance equations, i.e. Palmer’s fluid mass balance method. The parameters of model of effective rainfall are determined by using simple conceptual rainfall–runoff model consisting of two linear reservoirs representing the fast and slow flow component of the recession. The weight coefficient between the fast and slow component is determined by using base flow index analysis of hydrograph. Recession coefficient of the slow flow component and the weight coefficient are determined from hydrograph analysis. Available data from nearby meteorological station includes daily average discharge, the amount of precipitation, the average temperature and the humidity from 1995 to 2010. The average catchment area is also estimated with the average yearly runoff deficit using Turc’s method and compared with the values obtained from the application of the rainfall–runoff model. Nash–Sutcliffe model efficiency, root mean square error and Pearson’s correlation coefficient for simulated hydrograph are applied to assess the predictive power of model. Calculated groundwater balance shows that the Opacac spring aquifer contains a significant storage capacity. The application of series of linear reservoirs is a classical and common technique, but the proposed simple approach enables the estimation of the components of groundwater balance in karst areas.

A 500 year atmospheric dust deposition retrieved from a Mt. Geladaindong ice core in the central Tibetan Plateau

A 147-m ice core was retrieved from Guoqu Glacier (33.58°N, 91.18°E, 5750ma.s.l.) during the Sino–US cooperation expedition on Mt. Geladaindong in the central Tibetan Plateau (TP). In this study, we investigated the high-resolution of atmospheric dust records by using the insoluble particles and crustal ions (Ca2+ and Mg2+) from the upper 109.93m segments, covering the period of 1477 to 1982AD. There existed positive correlations among the ice core dust records themselves and with the dust days from the nearby meteorological stations during the recent decades, indicating that the insoluble particles and crustal ions in the ice core can be used to reconstruct the past atmospheric dust variability. During the past 500years, the insoluble particles and crustal ions showed high concentrations in the 18th to 19th centuries and low concentrations in the 20th century, corresponding to low and high precipitation in the potential dust source regions. The ice core dust records were positively correlated with the zonal wind and the winter North Atlantic Oscillation (NAO) index, suggesting that NAO may be teleconnected to dust entrainment over the inland TP. This long-term ice core provided an approach to understand the atmospheric dust variability in the central TP during the last 500years.

Long-term wind resource assessment for small and medium-scale turbines using operational forecast data and measure–correlate–predict

Output from a state-of-the-art, 4 km resolution, operational forecast model (UK4) was investigated as a source of long-term historical reference data for wind resource assessment. The data were used to implement measure–correlate–predict (MCP) approaches at 37 sites throughout the United Kingdom (UK). The monthly and hourly linear correlation between the UK4-predicted and observed wind speeds indicates that UK4 is capable of representing the wind climate better than the nearby meteorological stations considered. Linear MCP algorithms were implemented at the same sites using reference data from UK4 and nearby meteorological stations to predict the long-term (10-year) wind resource. To obtain robust error statistics, MCP algorithms were applied using onsite measurement periods of 1–12 months initiated at 120 different starting months throughout an 11 year data record. Using linear regression MCP over 12 months, the average percentage errors in the long-term predicted mean wind speed and power density were 3.0% and 7.6% respectively, using UK4, and 2.8% and 7.9% respectively, using nearby meteorological stations. The results indicate that UK4 is highly competitive with nearby meteorological observations as an MCP reference data source. UK4 was also shown to systematically improve MCP predictions at coastal sites due to better representation of local diurnal effects.