Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++

A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called ANAKLIM++ (Adjustment of Assimilation Software for the Reanalysis of Climate Data) which was originally designed for the efficient assimilation of two-dimensional data sets using a variational approach. A nowcasting for SIS was already presented and validated in earlier publications as seamless solar radiation forecast (SESORA). For our blending, two NWP models, namely the ICON (Icosahedral Non-hydrostatic model) from the German weather Service (DWD) and the IFS (Integrated Forecasting System) from the European Centre for Medium-Range Weather Forecasts (ECMWF), were used. The weights for the input data for ANAKLIM++ vary for every single forecast time and pixel, depending on the error growth of the nowcasting. The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or NWP models, respectively.

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Implementation of Bessel's method for solar eclipses prediction in the WRF-ARW model

Atmospheric Chemistry and Physics ◽

10.5194/acp-16-5949-2016 ◽

2016 ◽

Vol 16 (9) ◽

pp. 5949-5967 ◽

Cited By ~ 2

Author(s):

Alex Montornès ◽

Bernat Codina ◽

John W. Zack ◽

Yolanda Sola

Keyword(s):

Solar Radiation ◽

Solar Eclipse ◽

Weather Prediction ◽

Grid Point ◽

Absolute Error ◽

Resource Assessment ◽

Surface Radiation ◽

Computational Time ◽

Arw Model ◽

Solar Eclipses

Abstract. Solar eclipses are predictable astronomical events that abruptly reduce the incoming solar radiation into the Earth's atmosphere, which frequently results in non-negligible changes in meteorological fields. The meteorological impacts of these events have been analyzed in many studies since the late 1960s. The recent growth in the solar energy industry has greatly increased the interest in providing more detail in the modeling of solar radiation variations in numerical weather prediction (NWP) models for the use in solar resource assessment and forecasting applications. The significant impact of the recent partial and total solar eclipses that occurred in the USA (23 October 2014) and Europe (20 March 2015) on solar power generation have provided additional motivation and interest for including these astronomical events in the current solar parameterizations.Although some studies added solar eclipse episodes within NWP codes in the 1990s and 2000s, they used eclipse parameterizations designed for a particular case study. In contrast to these earlier implementations, this paper documents a new package for the Weather Research and Forecasting–Advanced Research WRF (WRF-ARW) model that can simulate any partial, total or hybrid solar eclipse for the period 1950 to 2050 and is also extensible to a longer period. The algorithm analytically computes the trajectory of the Moon's shadow and the degree of obscuration of the solar disk at each grid point of the domain based on Bessel's method and the Five Millennium Catalog of Solar Eclipses provided by NASA, with a negligible computational time. Then, the incoming radiation is modified accordingly at each grid point of the domain.This contribution is divided in three parts. First, the implementation of Bessel's method is validated for solar eclipses in the period 1950–2050, by comparing the shadow trajectory with values provided by NASA. Latitude and longitude are determined with a bias lower than 5  ×  10−3 degrees (i.e., ∼  550 m at the Equator) and are slightly overestimated and underestimated, respectively. The second part includes a validation of the simulated global horizontal irradiance (GHI) for four total solar eclipses with measurements from the Baseline Surface Radiation Network (BSRN). The results show an improvement in mean absolute error (MAE) from 77 to 90 % under cloudless skies. Lower agreement between modeled and measured GHI is observed under cloudy conditions because the effect of clouds is not included in the simulations for a better analysis of the eclipse outcomes. Finally, an introductory discussion of eclipse-induced perturbations in the surface meteorological fields (e.g., temperature, wind speed) is provided by comparing the WRF–eclipse outcomes with control simulations.

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How long do satellites need to overlap? Evaluation of climate data stability from overlapping satellite records

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-15069-2017 ◽

2017 ◽

Vol 17 (24) ◽

pp. 15069-15093 ◽

Cited By ~ 6

Author(s):

Elizabeth C. Weatherhead ◽

Jerald Harder ◽

Eduardo A. Araujo-Pradere ◽

Greg Bodeker ◽

Jason M. English ◽

...

Keyword(s):

Solar Radiation ◽

Spectral Irradiance ◽

Data Sets ◽

Climate Data ◽

Data Set ◽

Long Term Stability ◽

Earth Observations ◽

Earth’S Climate ◽

The Stability

Abstract. Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr−1 uncertainty (0.00008 W m−2 nm−1 yr−1), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.

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Yearly changes in surface solar radiation in New Caledonia

Advances in Science and Research ◽

10.5194/asr-12-1-2015 ◽

2015 ◽

Vol 12 (1) ◽

pp. 1-4 ◽

Cited By ~ 3

Author(s):

P. Blanc ◽

C. Coulaud ◽

L. Wald

Keyword(s):

Solar Radiation ◽

New Caledonia ◽

Solar Irradiation ◽

Data Sets ◽

Climate Data ◽

Surface Solar Radiation ◽

Data Set ◽

The Mean ◽

Energy Plants

Abstract. New Caledonia experiences a decrease in surface solar irradiation since 2004. It is of order of 4% of the mean yearly irradiation over the 10 years period: 2004–2013, and amounts to −9 W m−2. The preeminent roles of the changes in cloud cover and to a lesser extent, those in aerosol optical depth on the decrease in yearly irradiation are evidenced. The study highlights the role of data sets offering a worldwide coverage in understanding changes in solar radiation and planning large solar energy plants such as the ICOADS (International Comprehensive Ocean-Atmosphere Data Set) of the NOAA and MACC (Monitoring Atmosphere Composition and Climate) data sets combined with the McClear model.

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Regional Short-term Micro-climate Air Temperature Prediction with CBPNN

E3S Web of Conferences ◽

10.1051/e3sconf/20185303009 ◽

2018 ◽

Vol 53 ◽

pp. 03009 ◽

Cited By ~ 1

Author(s):

Lvwen Huang ◽

Lianliang Chen ◽

Qin Wang ◽

Siwen Yan ◽

Xunbing Gao ◽

...

Keyword(s):

Air Temperature ◽

Stepwise Regression ◽

Back Propagation ◽

Absolute Error ◽

Back Propagation Neural Network ◽

Data Sets ◽

Climate Data ◽

Short Term ◽

Temperature Prediction ◽

Air Temperature Prediction

This paper proposes a novel short-term air temperature prediction with three-layer Back Propagation Neural Network (BPNN) for the regional application of next 1-12 hours. With the continuous collection of eight real-time micro-climate parameters in the experimentation and demonstration stations in our university, the Multiple Stepwise Regression (MSR) is employed to screen the original historical data to find the parameter factors with greater contribution rate. On the basis of the Root Mean Square Error (RMSE) value evaluating the optimal fitting degree of the stepwise regression, the Levenberg-Marquardt (LM) and the Resilient Propagation (R-Prop) training algorithm are employed to construct a Combined BPNN (CBPNN) with two MSR inputs. Compared with the known micro-climate data sets, the Mean Absolute Error (MAE) is to evaluate the applicability of CBPNN prediction model. The experimentation shows that the MAE is within 4°C in the next 12 hours. This proposal will be deployed in stations in our university for extreme weather warnings, and could be applied to some regional short-term parameter prediction for the future agricultural production service.

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Analysis of the ozone profile specifications in the WRF-ARW model and their impact on the simulation of direct solar radiation

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-2693-2015 ◽

2015 ◽

Vol 15 (5) ◽

pp. 2693-2707 ◽

Cited By ~ 7

Author(s):

A. Montornès ◽

B. Codina ◽

J. W. Zack

Keyword(s):

Solar Radiation ◽

Weather Prediction ◽

Reanalysis Data ◽

Direct Solar Radiation ◽

Spatial And Temporal Variability ◽

Data Sets ◽

Data Set ◽

Ozone Profile ◽

Arw Model ◽

The Impact

Abstract. Although ozone is an atmospheric gas with high spatial and temporal variability, mesoscale numerical weather prediction (NWP) models simplify the specification of ozone concentrations used in their shortwave schemes by using a few ozone profiles. In this paper, a two-part study is presented: (i) an evaluation of the quality of the ozone profiles provided for use with the shortwave schemes in the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model and (ii) an assessment of the impact of deficiencies in those profiles on the performance of model simulations of direct solar radiation. The first part compares simplified data sets used to specify the total ozone column in six schemes (i.e., Goddard, New Goddard, RRTMG, CAM, GFDL and Fu–Liou–Gu) with the Multi-Sensor Reanalysis data set during the period 1979–2008 examining the latitudinal, longitudinal and seasonal limitations in the ozone profile specifications of each parameterization. The results indicate that the maximum deviations are over the poles and show prominent longitudinal patterns in the departures due to the lack of representation of the patterns associated with the Brewer–Dobson circulation and the quasi-stationary features forced by the land–sea distribution, respectively. In the second part, the bias in the simulated direct solar radiation due to these deviations from the simplified spatial and temporal representation of the ozone distribution is analyzed for the New Goddard and CAM schemes using the Beer–Lambert–Bouguer law and for the GFDL using empirical equations. For radiative applications those simplifications introduce spatial and temporal biases with near-zero departures over the tropics throughout the year and increasing poleward with a maximum in the high middle latitudes during the winter of each hemisphere.

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Projecting Northern Hemisphere Flow Regime Transition Using Integrated Enstrophy

Atmosphere ◽

10.3390/atmos11090915 ◽

2020 ◽

Vol 11 (9) ◽

pp. 915

Author(s):

Emily Klaus ◽

Patrick Market ◽

Anthony Lupo ◽

Michael Bodner ◽

Joshua Kastman

Keyword(s):

Flow Regime ◽

Northern Hemisphere ◽

Weather Prediction ◽

Probability Of Detection ◽

Data Sets ◽

Regime Transition ◽

Flow Regime Transition ◽

Forecasting System ◽

Environmental Prediction ◽

Regime Transitions

Integrated enstrophy (IE) is the square of vorticity integrated over an entire hemisphere at a particular level in the atmosphere. Previous work has shown this quantity is correlated to the positive Lyapunov Exponent for hemispheric flow, and as such is a measure of flow stability or predictability. In this study, IE is calculated at 500 hPa over an area that encompasses 0° to 70° in the Northern Hemisphere. The data sets used were the 500 hPa initial and forecast fields for the Global Ensemble Forecasting System (GEFS) (on a 1 × 1 latitude-longitude grid) provided by the National Oceanic and Atmospheric Administration (NOAA) Weather Prediction Center (WPC) and the National Centers for Environmental Prediction/NOAA reanalyses (on a 2.5 × 2.5 latitude-longitude grid) archived in Boulder, CO. The GEFS forecast fields were provided every 24 h out to 240 h. By examining these forecasts over a year, it was found here that significant changes in the calculated IE values, as quantitatively determined, are a good predictor of flow regime transition, and 34 cases were found. We also found that the model IE forecasts identified these regime transitions reliably out to about seven days, however, the probability of detection and the skill decreased after this time. Additionally, a threshold for changes in IE was found for the cases studied here.

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MorphoCluster: Efficient Annotation of Plankton Images by Clustering

Sensors ◽

10.3390/s20113060 ◽

2020 ◽

Vol 20 (11) ◽

pp. 3060

Author(s):

Simon-Martin Schröder ◽

Rainer Kiko ◽

Reinhard Koch

Keyword(s):

Image Annotation ◽

Novelty Detection ◽

Image Data ◽

Software Tool ◽

Data Driven ◽

Data Sets ◽

Fine Grained ◽

Novel Approach ◽

Human Ability ◽

Similar Images

In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate annotation of large image data sets. While already having surpassed the annotation rate of human experts, volume and complexity of marine data will continue to increase in the coming years. Still, this data requires interpretation. MorphoCluster augments the human ability to discover patterns and perform object classification in large amounts of data by embedding unsupervised clustering in an interactive process. By aggregating similar images into clusters, our novel approach to image annotation increases consistency, multiplies the throughput of an annotator, and allows experts to adapt the granularity of their sorting scheme to the structure in the data. By sorting a set of 1.2 M objects into 280 data-driven classes in 71 h (16 k objects per hour), with 90% of these classes having a precision of 0.889 or higher. This shows that MorphoCluster is at the same time fast, accurate, and consistent; provides a fine-grained and data-driven classification; and enables novelty detection.

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Impact of diffuse solar radiation on HAM simulation accuracy

MATEC Web of Conferences ◽

10.1051/matecconf/201928202093 ◽

2019 ◽

Vol 282 ◽

pp. 02093

Author(s):

Peter Juras

Keyword(s):

Solar Radiation ◽

Simulation Models ◽

Urban Heat Islands ◽

Data Sets ◽

Good Precision ◽

Climate Data ◽

Simulation Accuracy ◽

Heat Islands ◽

Diffuse Solar Radiation ◽

Diffuse Part

Advance in the numerical simulation models brings higher need for more accuracy outdoor boundary conditions - climate data sets. With influence of the urban heat islands, measured climate on the meadows, far from pawed surfaces creates uncertainty in the simulation. Another problem is the modelling of solar radiation impact on the surface temperatures. Solar radiation heats up the surface of the structure and increase the speed of vapor transport. To obtain correct results, global and diffuse solar radiation is needed in the HAM software. In this paper, influence of the diffuse part of solar radiation is analyzed. As it would be shown, correct modeling of the solar radiation, both global and diffuse is very important to reach good precision. This analysis is done in software WUFI Pro and compared with the experimental measurement of the wooden wall fragments.

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Coupling meteorological forecasts with hydrologic and hydraulic models: The Itaipu Dam ensemble inflow forecasting system

10.5194/egusphere-egu21-6228 ◽

2021 ◽

Author(s):

José Quevedo ◽

Daniel Firmo Kazay ◽

Mariana Maria Werlang ◽

Giovanni Gomes ◽

Roberto Takahashi ◽

...

Keyword(s):

Weather Prediction ◽

Precipitation Forecast ◽

Distributed Model ◽

Hydrological Models ◽

Forecast Horizon ◽

Generation Scheduling ◽

Lumped Models ◽

Forecasting System ◽

Itaipu Dam ◽

The Difference

This work presents the development of the inflow ensemble forecasting system for Itaipu Dam. The system is based on combination of twelve Quantitative Precipitation Forecast (QPF) with three hydrological models and one hydrodynamic one-dimensional model. The QPF are provided by different meteorological institutions based in the results of the global Numerical Weather Prediction (NWP) models GFS and ECMWF, as well as of the regional NWP models WRF and COSMO executed by the Brazilian and Paraguay meteorological services (SIMEPAR, INMET and DINAC). The semi-distributed model MGB &#8211; Large Basin Model, the lumped models SMAP and HEC-HMS are considered as the hydrological models. Furthermore, the computed flows are propagated in a HEC-RAS scheme designed with extensive field data from bathymetry of Parana River and tributaries. The daily results are presented as fifteen inflow scenarios that are considered for the definition of a unique flow forecast. Finally, that forecast is used for the electric generation scheduling of the power plant. Each of these fifteen methods performance was evaluated as well as the suitability of the system for it purposes. For a short-term forecast horizon (less than 4 days), the performances of the hydrological models forced by the different rain forecast are quite similar. However, it is remarkable the difference between the results of the three hydrological models for the same horizon. On the other hand, for medium-term horizon (more than 4 days) both hydrological and meteorological models have diverse behavior and contribute for a wide representation of the possible scenarios. Overall, it has been showed that the simulations are complementary and provides to the forecaster a general overview of the hydrologic situation. Nevertheless, at this moment, further analysis of accuracy and reliability of the prediction have not been realized, so the forecaster needs to appeal to its own expertise to assure the consistence of the scenarios for decision-making.

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Global and Regional Satellite-based Surface Solar Radiation data sets provided by the CM SAF

10.5194/egusphere-egu21-8167 ◽

2021 ◽

Author(s):

Jörg Trentmann ◽

Uwe Pfeifroth ◽

Jaqueline Drücke ◽

Roswitha Cremer

Keyword(s):

Solar Radiation ◽

Global Climate ◽

Surface Radiation ◽

Data Sets ◽

Climate Data ◽

Surface Solar Radiation ◽

Climate Monitoring ◽

Data Record ◽

Irradiance Data ◽

Climate Data Record

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth&#8217;s energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models.The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF are freely available via www.cmsaf.eu.Here we present the regional and global climate data records of surface solar radiation from the CM SAF. The regional SARAH-2.1 climate data record (Surface Solar Radiation Dataset &#8211; Heliosat, doi: 10.5676/EUM_SAF_CM/SARAH/V002_01) is based on observations from the series of Meteosat satellites. SARAH-2.1 provides high resolution data (temporal and spatial) of the surface solar radiation (global and direct) and the sunshine duration from 1983 to 2017 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The global climate data record CLARA (CM SAF Clouds, Albedo and Radiation dataset from AVHRR data, doi: 10.5676/EUM_SAF_CM/CLARA_AVHRR/V002_01) is based on observations from the series of AVHRR instruments onboard polar-orbiting satellites. CLARA provides daily- and monthly-averaged global data of the solar irradiance (SIS) from January 1982 to June 2019 with a spatial resolution of 0.25&#176;. In addition to the solar surface radiation, also the longwave surface radiation as well as surface albedo and numerous cloud properties are provided in CLARA. The high accuracy and stability of these data record allows the assessment of the spatial and temporal variability and trends as well as a number of other applications that require high-resolution surface irradiance data.Both Thematic Climate Data Records (TCDR) are accompanied and temporally-extended by consistent data records, so-called Interim Climate Data Records (ICDR), which are provided with a latency of 5 days to support applications that require more recent surface irradiance data, e.g., operational climate monitoring.In late 2021 / early 2022 new versions of both data records, SARAH and CLARA, will be provided by the CM SAF. The quality of these data records will be improved, e.g, by a better treatment of snow-covered surfaces, and temporally extended to cover the WMO climate reference period 1991 to 2020. Here, first results of the updated data records and their improvements will be presented.

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