caa a22 4500 605474729 CHVBK 20210128100348.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s00382-014-2278-2 doi (NATIONALLICENCE)springer-10.1007/s00382-014-2278-2 Analysis of rainfall seasonality from observations and climate models [Elektronische Daten] [Salvatore Pascale, Valerio Lucarini, Xue Feng, Amilcare Porporato, Shabeh ul Hasson] Two new indicators of rainfall seasonality based on information entropy, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere-ocean general circulation models. The RE provides a measure of the number of wet months and, for precipitation regimes featuring a distinct wet and dry season, it isdirectly related to the duration of the wet season. The DSI combines the rainfall intensity with its degree of seasonality and it is an indicator of the extent of the global monsoon region. We show that the RE and the DSI are fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercomparison and ranking. Regions with different precipitation regimes are classified and characterized in terms of RE and DSI. Comparison of different land observational datasets reveals substantial difference in their local representation of seasonality. It is shown that two-dimensional maps of RE provide an easy way to compare rainfall seasonality from various datasets and to determine areas of interest. Models participating to the Coupled Model Intercomparison Project platform, Phase 5, consistently overestimate the RE over tropical Latin America and underestimate it in West Africa, western Mexico and East Asia. It is demonstrated that positive RE biases in a general circulation model are associated with excessively peaked monthly precipitation fractions, too large during the wet months and too small in the months preceding and following the wet season; negative biases are instead due, in most cases, to an excess of rainfall during the premonsoonal months. Springer-Verlag Berlin Heidelberg, 2014 Rainfall seasonality nationallicence Information entropy nationallicence Hydrological cycle nationallicence CMIP5 models nationallicence Pascale Salvatore Meteorologisches Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Grindelberg 5, 20144, Hamburg, Germany aut Lucarini Valerio Meteorologisches Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Grindelberg 5, 20144, Hamburg, Germany aut Feng Xue Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA aut Porporato Amilcare Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA aut Hasson Shabeh ul Meteorologisches Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Grindelberg 5, 20144, Hamburg, Germany aut Climate Dynamics Springer Berlin Heidelberg 44/11-12(2015-06-01), 3281-3301 0930-7575 44:11-12<3281 2015 44 382 https://doi.org/10.1007/s00382-014-2278-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00382-014-2278-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Pascale Salvatore Meteorologisches Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Grindelberg 5, 20144, Hamburg, Germany aut NATIONALLICENCE 700 1- Lucarini Valerio Meteorologisches Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Grindelberg 5, 20144, Hamburg, Germany aut NATIONALLICENCE 700 1- Feng Xue Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA aut NATIONALLICENCE 700 1- Porporato Amilcare Department of Civil and Environmental Engineering, Duke University, Durham, NC, USA aut NATIONALLICENCE 700 1- Hasson Shabeh ul Meteorologisches Institute, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Grindelberg 5, 20144, Hamburg, Germany aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 44/11-12(2015-06-01), 3281-3301 0930-7575 44:11-12<3281 2015 44 382