![]() G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Rupa Kumar, K., Revadekar, J., Griffiths, G., Vincent, L., Stephenson, L. C., Caesar, J., Gleason, B., Klein Tank, A. Rclimdex con funcionalidades extras de control de calidad, Manual de Uso, version 1.12. WMO-CCl-ET-CRSCI Workshop on Applications of Climate Indices to the Agriculture, Water and Health Sectors, CIIFEN, Guayaquil, Ecuador. EXTRA-QC (sobre Rclimdex Conference PRESENTATION). Journal of Geophysical Research: Atmospheres, 108( D9), 4257. Adjustment of global gridded precipitation for systematic bias. International Journal of Climatology, 33( 1), 121– 131. Development of gridded surface meteorological data for ecological applications and modelling. Journal of Geophisycal Research: Atmospheres, 121( 8), 3807– 3823. New gridded daily climatology of Finland: Permutation-based uncertainty estimates and temporal trends in climate. Science of Water > Hydrological Processes.Moreover, scientists should adopt tailored strategies to improve the representativity and uncertainty of the estimates. Finally, we concluded that, despite better spatial and temporal resolutions, data access, and data processing capabilities, observational coverage remains a challenge. We identified gaps and challenges for near-future perspectives and provide guidelines for implementing improved approaches based on the performance of 48 products. It is, therefore, critical to provide general guidelines for the development of future and more robust gridded datasets based on the data characteristics, geographical factors, and advanced statistical techniques. Yet, despite multiple advances, most of the gridded datasets created and published since the mid-1990s to the present use a wide variety of techniques, methods, and outputs, which can completely change the final representativity of the data. Thus, the creation of a gridded dataset from observations requires the comprehensive and precise application of quality control, reconstruction, and gridding procedures. However, due to the complex characteristics of precipitation, it is difficult to obtain accurate estimations. These datasets describe the high spatial and temporal variability of precipitation as a continuous surface and for defined periods. Monthly and daily gridded precipitation datasets are one of the most demanded products in climatology and hydrology.
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