Browsing by Subject "ERA-INTERIM"

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  • Vuollekoski, H.; Vogt, M.; Sinclair, V. A.; Duplissy, J.; Jarvinen, H.; Kyro, E. -M.; Makkonen, R.; Petaja, T.; Prisle, N. L.; Räisänen, P.; Sipila, M.; Ylhaisi, J.; Kulmala, M. (2015)
  • Urraca, Ruben; Gracia-Amillo, Ana M.; Huld, Thomas; Martinez-de-Pison, Francisco Javier; Trentmann, Jörg; Lindfors, Anders V.; Riihelä, Aku; Sanz-Garcia, Andres (2017)
    Several quality control (QC) procedures are available to detect errors in ground records of solar radiation, mainly range tests, model comparison and graphical analysis, but most of them are ineffective in detecting common problems that generate errors within the physical and statistical acceptance ranges. Herein, we present a novel QC method to detect small deviations from the real irradiance profile. The proposed method compares ground records with estimates from three independent radiation products, mainly satellite-based datasets, and flags periods of consecutive days where the daily deviation of the three products differs from the historical values for that time of the year and region. The confidence intervals of historical values are obtained using robust statistics and errors are subsequently detected with a window function that goes along the whole time series. The method is supplemented with a graphical analysis tool to ease the detection of false alarms. The proposed QC was validated in a dataset of 313 ground stations. Faulty records were detected in 31 stations, even though the dataset had passed the Baseline Surface Radiation Network (BSRN) range tests. The graphical analysis tool facilitated the identification of the most likely causes of these errors, which were classified into operational errors (snow over the sensor, soiling, shading, time shifts, large errors) and equipment errors (miscalibration and sensor replacements), and it also eased the detection of false alarms (16 stations). These results prove that our QC method can overcome the limitations of existing QC tests by detecting common errors that create small deviations in the records and by providing a graphical analysis tool that facilitates and accelerates the inspection of flagged values.
  • Virman, Meri; Bister, Marja; Räisänen, Jouni; Sinclair, Victoria; Järvinen, Heikki (2021)
    After the release of the ERA-Interim reanalysis, many changes have been made to the Integrated Forecasting System model and data-assimilation system, resulting in an improved reanalysis, ERA5. One of the changes in the model allows the model version in ERA5 to represent the moisture sensitivity of deep convection more realistically than the model version in ERA-Interim. A previous modeling study showed that this change alone improved the representation of the tropical atmosphere, e.g. tropical variability and precipitation distribution. Here we compare the vertical structures of average temperature and moisture over tropical oceans in ERA5, ERA-Interim and radiosonde observations to see whether ERA5 is also closer to observations for those regions and variables. Our results reveal that at many levels, temperature and relative humidity in ERA5 and ERA-Interim differ from observations, however ERA-Interim is generally closer to observations than ERA5 in the low-to-midtroposphere. Most notably, in many stations, ERA5 is on average colder than observations at similar to 550-800 hPa. Large vertical gradients occur in the profile of the mean temperature difference between ERA5 and observations at similar to 700-900 hPa, but are absent in ERA-Interim. Relative humidity differences are not as robust as temperature differences, however in many stations ERA5 is on average moister than observations at similar to 650-800 hPa while ERA-Interim is closer to observations there. Below the similar to 950 hPa-level ERA5 and ERA-Interim are generally colder and moister than observations. Our results indicate that ERA5 deviates more than ERA-Interim from tropical radiosonde observations in the low-to-midtroposphere. It seems plausible that this deviation is, at least partly, due to the newer formulation of organised deep entrainment in ERA5 and the associated mechanism for the moisture sensitivity. However, more extensive model evaluation is needed to understand the reasons for the differences between the reanalyses and radiosonde observations.
  • Urraca, Ruben; Huld, Thomas; Javier Martinez-de-Pison, Francisco; Sanz-Garcia, Andres (2018)
    The major sources of uncertainty in short-term assessment of global horizontal radiation (G) are the pyranometer type and their operation conditions for measurements, whereas the modeling approach and the geographic location are critical for estimations. The influence of all these factors in the uncertainty of the data has rarely been compared. Conversely, solar radiation data users are increasingly demanding more accurate uncertainty estimations. Here we compare the annual bias and uncertainty of all the mentioned factors using 732 weather stations located in Spain, two satellite-based products and three reanalyses. The largest uncertainties were associated to operational errors such as shading (bias = - 8.0%) or soiling (bias = - 9.4%), which occurred frequently in low-quality monitoring networks but are rarely detected because they pass conventional QC tests. Uncertainty in estimations greatly changed from reanalysis to satellite-based products, ranging from the gross accuracy of ERA-Interim (+ 6.1(-6.7)(+)(1)(8.)(8)%) to the high quality and spatial homogeneity of SARAH-1 (+ 1.4(-5.3)(+)(5.6)%). Finally, photodiodes from the Spanish agricultural network SIAR showed an uncertainty of (+6.)(9)(-5.4)%, which is far greater than that of secondary standards (+/- 1.5%) and similar to SARAH-1. This is probably caused by the presence of undetectable operational errors and the use of uncorrected photodiodes. Photodiode measurements from low-quality monitoring networks such as SIAR should be used with caution, because the chances of adding extra uncertainties due to poor maintenance or inadequate calibration considerably increase.