Comparison of radiation parametrizations  within the HARMONIE–AROME NWP model

Rontu, Laura; Lindfors, Anders V.

doi:10.5194/asr-15-81-2018

Cited by 5 publications

(6 citation statements)

References 19 publications

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“…Observed climatologies can be obtained from surface-based instrumentation (Ohmura et al, 1998) and from satellite (Posselt et al, 2012;López and Batlles, 2014;Müller et al, 2015). Climatologies can also be derived from Numerical Weather Prediction (NWP) forecasts and reanalyses, which are attractive from a cost perspective but may display larger uncertainties than observations (Jia et al, 2013;Boilley and Wald, 2015;Frank et al, 2018;Urraca et al, 2018). Climatologies require that the correct amount and type of cloud is predicted on average, whereas a forecast additionally requires that the cloud is forecast at the right time.…”

Section: Introductionmentioning

confidence: 99%

Evaluating solar radiation forecast uncertainty

2019

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Abstract. The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar energy and UV radiation forecasts. Here we investigate how operational forecasts of low and mid-level clouds affect the accuracy of solar radiation forecasts. A total of 4 years of cloud and solar radiation observations from one site in Helsinki, Finland, are analysed. Cloud observations are obtained from a ceilometer and therefore we first develop algorithms to reliably detect cloud base, precipitation, and fog. These new algorithms are widely applicable for both operational use and research, such as in-cloud icing detection for the wind energy industry and for aviation. The cloud and radiation observations are compared to forecasts from the Integrated Forecast System (IFS) run operationally and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop methods to evaluate the skill of the cloud and radiation forecasts. These methods can potentially be extended to hundreds of sites globally. Over Helsinki, the measured global horizontal irradiance (GHI) is strongly influenced by its northerly location and the annual variation in cloudiness. Solar radiation forecast error is therefore larger in summer than in winter, but the relative error in the solar radiation forecast is more or less constant throughout the year. The mean overall bias in the GHI forecast is positive (8 W m−2). The observed and forecast distributions in cloud cover, at the spatial scales we are considering, are strongly skewed towards clear-sky and overcast situations. Cloud cover forecasts show more skill in winter when the cloud cover is predominantly overcast; in summer there are more clear-sky and broken cloud situations. A negative bias was found in forecast GHI for correctly forecast clear-sky cases and a positive bias in correctly forecast overcast cases. Temporal averaging improved the cloud cover forecast and hence decreased the solar radiation forecast error. The positive bias seen in overcast situations occurs when the model cloud has low values of liquid water path (LWP). We attribute this bias to the model having LWP values that are too low or the model optical properties for clouds with low LWP being incorrect.

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Section: Introductionmentioning

confidence: 99%

Evaluating solar radiation forecast uncertainty

2019

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“…Compared to them, the solar radiation data has a higher spatial and temporal resolution. A previous study, for example, compared the performance of different radiation schemes in the HARMONIE-AROME NWP model with solar radiation measurements during spring in Finland (Rontu and Lindfors, 2018). They found good agreement between the model and measurements in clear-sky cases, while under cloudy skies, the modeled surface solar radiation tended to be too high.…”

mentioning

confidence: 99%

10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

Vos¹,

Leijnse²,

Uijlenhoet³

2018

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“…observed cloud cover greater than 0.9 shows a positive solar radiation forecast ME (27 W m −2 ) and observed cloud cover less than 0.1 shows negative ME (−16 W m −2 ). This negative bias during clear-sky situations over Helsinki was also observed by Rontu and Lindfors (2018) and is most likely due to the aerosol climatology implemented in the model having too much aerosol. Another possible source of negative bias during clear-sky situations would be too much water vapour in the atmosphere.…”

Section: How Do Errors In Cloud Cover Impact the Solar Radiation Foresupporting

confidence: 52%

“…Eddy-Covariance technique, used in paper III to investigate the effect of LLJs on the fluxes of latent and sensible heat and the net ecosystem CO 2 exchange, requires a sonic anemometer in addition to an open path gas-analyser (Mauder et al, 2013). Pyranometers were used in paper IV to observe the GHI, and 1-minute averaged, quality-controlled GHI values (Long and Shi, 2008;Rontu and Lindfors, 2018) over four years were used.…”

Section: Other Observationsmentioning

confidence: 99%

“…Automated quality control has been applied by the Finnish Meteorological Institute (FMI) together with a visual check to ensure the data quality. The automated quality control is based on the Baseline Surface Radiation Network (BSRN) quality control procedure (Long and Shi, 2008) with small modifications to be more suitable for Finnish conditions (Rontu and Lindfors, 2018). GHI measurements are stored as 1 min averages in the FMI database.…”

Section: Ceilometer and Solar Radiation Observationsmentioning

confidence: 99%

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Meteorological conditions affecting renewable energy

Tuononen

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Synoptic situation and different meteorological phenomena can highly affect renewable energy production. Investigating different phenomena will give new information on the occurrence and characteristics of specific phenomena and their impacts on renewable energy applications. Different observational data sets and numerical models can be widely used in different phases of renewable energy projects; from planning of the project to help with the operation and the maintenance of the existing wind or solar field.In this thesis a meteorological phenomena, a low-level jet, is investigated. Thesis comprises analysis of the climatological occurrence of low-level jets, their characteristics and forcing mechanisms, as well as numerical model capability to capture the phenomena. In addition, solar radiation forecasts obtained from the operational numerical weather prediction model are evaluated and the role of cloud cover forecast skill in solar radiation forecast error is investigated. Long data sets of observational data: mainly Doppler wind lidar, ceilometer, and solar radiation observations, are used, in addition to reanalysis and operational numerical weather prediction model data.A low-level jet is a wind phenomenon that can affect wind energy production. Nighttime low-level jets are a commonly known boundary-layer phenomenon occurring during stably stratified conditions over flat terrain. In this thesis, new information on the occurrence, characteristics, and forcing mechanisms of a low-level jet was gained in different conditions: in Northern Hemisphere mid-latitude and polar regions based on reanalysis data and at two different sites in Finland and Germany based on long-term Doppler lidar observations. The low-level jet identification algorithms developed in these studies can be used to repeat the studies by using different models covering different areas or at any site operating a Doppler lidar. The low-level jet identification algorithm for Doppler lidar data can also be applied to operationally detect low-level jets, which is useful information for example from wind energy point-of-view.Solar radiation and cloud cover forecasts were evaluated at one site in Finland based on long time-series of solar radiation and ceilometer observations. The role of cloud cover forecast in solar radiation forecast error is investigated. The solar radiation and cloud cover forecasts were obtained from operational numerical weather prediction model that can be used to predict the expected power production at solar field day-ahead. It was found that there is a positive bias in the forecast incoming solar radiation even if the cloud cover forecast is correct. The study can guide model improvements as the bias is likely due to underestimation in the forecast cloud liquid water content or incorrect representation of cloud optical properties. The methods created in this study can be applied to hundreds of sites globally. In addition, the algorithms developed in this study can be further used in different applications in the field of ren...

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Comparison of radiation parametrizations within the HARMONIE–AROME NWP model

Cited by 5 publications

References 19 publications

Evaluating solar radiation forecast uncertainty

Evaluating solar radiation forecast uncertainty

10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

Meteorological conditions affecting renewable energy

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