34 research outputs found

    EVALUATION OF SOLAR RADIATION ESTIMATED FROM HIMAWARI-8 SATELLITE OVER VIETNAM REGION

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    The development of Solar energy system is growing rapidly in Vietnam in recent years by encouragement of the Government in renewable energy. Requirement for accurate knowledge of the solar radiation reaching the surface is increasingly important in the successful deployment of Solar photovoltaic plants. However, measurements of different components of solar resources including direct normal irradiance (DNI) and global horizontal irradiance (GHI) are limited to few stations over whole country. Satellite imagery provides an ability to monitor the surface radiation over large areas at high spatial and temporal resolution as alternatives at low cost. Observations from the new Japanese geostationary satellite Himawari-8 produce imagery covering Asia-Pacific region, permitting estimation of GHI and DNI over Vietnam at 10-minute temporal resolution. However, accurate comparisons with ground observations are essential to assess their uncertainty. In this study, we evaluated the Himawari-8 radiation product AMATERASS provided by JST/CREST TEEDDA using observations recorded at 5 stations in different regions of Vietnam. The result shows good agreement between satellite estimation and observed data with high correlation of range 0.92-0.94, but better in clear-sky episodes.Because of AMATERASS outperform, we used it for validating ERA-Interim reanalysis in the spatial scale. The comparison was made dividedly for 7 climate zones and 4 seasons. The conclusion is that ERA-Interim is also well associated with satellite-based estimates in seasonal trend for all season, but in average the reanalysis has negative bias towards satellite estimates. This underestimation is more pronounced in the months of JJA and SON periods and in the north part of Vietnam because of unpredicted cloud in the ERA reanalysis

    Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data

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    This study examines the progress made by two new reanalyses in the estimation of surface irradiance: ERAS, the new global reanalysis from the ECMWF, and COSMO-REA6, the regional reanalysis from the DWD for Europe. Daily global horizontal irradiance data were evaluated with 41 BSRN stations worldwide, 294 stations in Europe, and two satellite-derived products (NSRDB and SARAH). ERAS achieves a moderate positive bias worldwide and in Europe of + 4.05 W/m 2 and + 4.54 W/m 2 respectively, which entails a reduction in the average bias ranging from 50% to 75% compared to ERA-Interim and MERRA-2. This makes ERAS comparable with satellite-derived products in terms of the mean bias in most inland stations, but ERAS results degrade in coastal areas and mountains. The bias of ERAS varies with the cloudiness, overestimating under cloudy conditions and slightly underestimating under clear-skies, which suggests a poor prediction of cloud patterns and leads to larger absolute errors than that of satellite-based products. In Europe, the regional COSMO-REA6 underestimates in most stations (MBE = -5.29 W/m(2)) showing the largest deviations under clear-sky conditions, which is most likely caused by the aerosol climatology used. Above 45 degrees N the magnitude of the bias and absolute error of COSMO-REA6 are similar to ERAS while it outperforms ERA5 in the coastal areas due to its high-resolution grid (6.2 km). We conclude that ERAS and COSMO-REA6 have reduced the gap between reanalysis and satellite-based data, but further development is required in the prediction of clouds while the spatial grid of ERAS (31 km) remains inadequate for places with high variability of surface irradiance (coasts and mountains). Satellite-based data should be still used when available, but having in mind their limitations, ERAS is a valid alternative for situations in which satellite-based data are missing (polar regions and gaps in times series) while COSMO-REA6 complements ERA5 in Central and Northern Europe mitigating the limitations of ERA5 in coastal areas.Peer reviewe

    Global and direct solar radiation at surface over Iberian Peninsula: variability, trends and forecasting

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    Besides being the key to Earth's climate, global solar radiation at the surface ( ) is one of the most valuable renewable resources. This way, an adequate knowledge of the solar resource is critical as an assessment for a strategic planning of projects related to the production of solar energy. Therefore, the main goals of this thesis is to analyze past changes and variability of solar radiation fluxes in Portugal and Iberia Peninsula (IP) using observational available measurements, ERA−40 and NCEP/NCAR reanalysis datasets and, predict and characterize the solar radiation at the surface over Iberian Peninsula based on numerical weather prediction models. In a first part, this study is dedicated to the analysis of temporal and spatial variability of based on ground-based stations, as well as in ERA−40 and NCEP/NCAR reanalysis. Parametric and non-parametric tests are applied to detect trends in both reanalysis and ground-based observations. Cloud cover obtained from reanalysis is also used to examine the possible causes of the observed long-term changes in . In a second stage, is presented an assessment of the W model at high resolution ( 5 ) against observations and with another configuration. After a bias removal process, a and cloud cover climatology was obtained for IP (1950−2010 period). Finally, the performance of IFS/ECMWF is evaluated to predict Direct Normal Irradiance (DNI) over Évora city at very short (1 hour) and short term (1 to 3 days), for one year period. It is also described a new methodology to compute DNI attenuation using in situ observational data in order to estimate the transparency of the atmosphere in the absence of cloud cover datasets. To improve IFS/ECMWF outputs is also tested a bias correction methodology; Resumo: A Radiação Solar Global e Direta à Superfície na Península Ibérica: Variabilidade, Tendências e Previsão A radiação solar é um dos recursos energéticos renováveis mais valiosos. Na Península Ibérica (PI) estão em instalação muitos sistemas comerciais e de investigação para o aproveitamento da energia solar. Neste contexto, o conhecimento do fluxo de radiação solar que incide na superfície terrestre e da sua evolução torna-se de extrema importância. Pretende-se com este trabalho estudar a distribuição espacial, a variabilidade e as tendências da radiação solar de pequeno comprimento de onda ( ) à superfície, na PI e em Portugal, a partir de dados observacionais e das reanálises ERA−40/NCEP assim como, prever e caracterizar a radiação com base em modelos de previsão numérica do tempo. Na primeira parte deste estudo, efetua-se uma análise da variabilidade temporal e espacial da radiação recorrendo a estações terrestres, bem como a dados de reanálise ERA−40 e NCEP/NCAR. Para o efeito utilizam-se testes paramétricos e não paramétricos a fim de detetar tendências nas séries em estudo. A cobertura de nuvens obtida a partir das reanálises é também usada para avaliar as possíveis causas da variabilidade da radiação observada. Numa segunda etapa do estudo, obteve-se uma climatologia a 5 de resolução da radiação solar à superfície com base em simulações com o modelo regional − , para a PI, e para o período 1950−2010. Os resultados das simulações foram validados recorrendo a estações de observação e a uma outra simulação , com outra configuração, previamente validada. Na construção da climatologia e de nuvens foi aplicado um método de pós-processamento para remoção do viés. Finalmente, avalia-se o desempenho do modelo IFS, do ECMWF na previsão da radiação DNI a curto e médio prazo, sobre a região. Propõe-se uma nova metodologia para estimar a transparência da atmosfera e testa-se uma metodologia de correção de viés

    GlobSim (v1.0): Deriving meteorological time series for point locations from multiple global reanalyses

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    Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide glo

    The Global Energy Balance Archive (GEBA) version 2017: a database for worldwide measured surface energy fluxes

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    The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500 000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as "global dimming" and "brightening". GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch. Supplementary data are available at https://doi.org/10.1594/PANGAEA.873078.ISSN:1866-3516ISSN:1866-350

    Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS

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    New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight into the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008–2017 using the Kling–Gupta efficiency (KGE), a performance metric combining correlation, bias, and variability. As a reference, we used the high-resolution (4&thinsp;km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the ERA5-HRES fourth-generation reanalysis, reflecting the significant advances in earth system modeling during the last decade. The (re)analyses generally performed better in winter than in summer, while the opposite was the case for the satellite-based datasets. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements implemented in the IMERG satellite P retrieval algorithm. IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms, while the opposite was observed in regions of complex terrain. The ERA5-EDA ensemble average exhibited higher correlations than the ERA5-HRES deterministic run, highlighting the value of ensemble modeling. The WRF regional convection-permitting climate model showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings provide some guidance to choose the most suitable P dataset for a particular application.</p

    Polar clouds and radiation in satellite observations, reanalyses, and climate models

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    Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007-2010) to evaluate simulated clouds and radiation over both polar ice sheets and oceans in state-of-the-art atmospheric reanalyses (ERA-Interim and Modern Era Retrospective-Analysis for Research and Applications-2) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model ensemble. First, we show that, compared to Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled, CloudSat-CALIPSO better represents cloud liquid and ice water path over high latitudes, owing to its recent explicit determination of cloud phase that will be part of its new R05 release. The reanalyses and climate models disagree widely on the amount of cloud liquid and ice in the polar regions. Compared to the observations, we find significant but inconsistent biases in the model simulations of cloud liquid and ice water, as well as in the downwelling radiation components. The CMIP5 models display a wide range of cloud characteristics of the polar regions, especially with regard to cloud liquid water, limiting the representativeness of the multimodel mean. A few CMIP5 models (CNRM, GISS, GFDL, and IPSL_CM5b) clearly outperform the others, which enhances credibility in their projected future cloud and radiation changes over high latitudes. Given the rapid changes in polar regions and global feedbacks involved, future climate model developments should target improved representation of polar clouds. To that end, remote sensing observations are crucial, in spite of large remaining observational uncertainties, which is evidenced by the substantial differences between the two data sets
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