Description: The last extended time period when climate may have been warmer than today was during the Last Interglacial (LIG; ca. 129 to 120 thousand years ago). However, a global view of LIG precipitation is lacking. Here, seven new LIG climate models are compared to the first global database of proxies for LIG precipitation. In this way, models are assessed in their ability to capture important hydroclimatic processes during a different climate. The models can reproduce the proxy-based positive precipitation anomalies from the preindustrial period over much of the boreal continents. Over the Southern Hemisphere, proxy-model agreement is partial. In models, LIG boreal monsoons have 42% wider area than in the preindustrial and produce 55% more precipitation and 50% more extreme precipitation. Austral monsoons are weaker. The mechanisms behind these changes are consistent with stronger summer radiative forcing over boreal high latitudes and with the associated higher temperatures during the LIG.

Description: Numerical modeling enables a comprehensive understanding not only of the Earth's system today, but also of the past. To date, a significant amount of time and effort has been devoted to paleoclimate modeling and analysis, which involves the latest and most advanced Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4). The definition of seasonality, which is influenced by slow variations in the Earth's orbital parameters, plays a key role in determining the calculated seasonal cycle of the climate. In contrast to the classical calendar used today, where the lengths of the months and seasons are fixed, the angular calendar calculates the lengths of the months and seasons according to a fixed number of degrees along the Earth's orbit. When comparing simulation results for different time intervals, it is essential to account for the angular calendar to ensure that the data for comparison are from the same position along the Earth's orbit. Most models use the classical calendar, which can lead to strong distortions of the monthly and seasonal values, especially for the climate of the past. Here, by analyzing daily outputs from multiple PMIP4 model simulations, we examine calendar effects on surface air temperature and precipitation under mid-Holocene, Last Interglacial, and pre-industrial climate conditions. We came to the following conclusions. (a) The largest cooling bias occurs in boreal autumn when the classical calendar is applied for the mid-Holocene and Last Interglacial, due to the fact that the vernal equinox is fixed on 21 March. (b) The sign of the temperature anomalies between the Last Interglacial and pre-industrial in boreal autumn can be reversed after the switch from the classical to angular calendar, particularly over the Northern Hemisphere continents. (c) Precipitation over West Africa is overestimated in boreal summer and underestimated in boreal autumn when the classical seasonal cycle is applied. (d) Finally, month-length adjusted values for surface air temperature and precipitation are very similar to the day-length adjusted values, and therefore correcting the calendar based on the monthly model results can largely reduce the artificial bias. In addition, we examine the calendar effects in three transient simulations for 6–0 ka by AWI-ESM, MPI-ESM, and IPSL-CM. We find significant discrepancies between adjusted and unadjusted temperature values over continents for both hemispheres in boreal autumn, while for other seasons the deviations are relatively small. A drying bias can be found in the summer monsoon precipitation in Africa (in the classical calendar), whereby the magnitude of bias becomes smaller over time. Overall, our study underlines the importance of the application of calendar transformation in the analysis of climate simulations. Neglecting the calendar effects could lead to a profound artificial distortion of the calculated seasonal cycle of surface air temperature and precipitation.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Stammer, D., Bracco, A., AchutaRao, K., Beal, L., Bindoff, N. L., Braconnot, P., Cai, W., Chen, D., Collins, M., Danabasoglu, G., Dewitte, B., Farneti, R., Fox-Kemper, B., Fyfe, J., Griffies, S. M., Jayne, S. R., Lazar, A., Lengaigne, M., Lin, X., Marsland, S., Minobe, S., Monteiro, P. M. S., Robinson, W., Roxy, M. K., Rykaczewski, R. R., Speich, S., Smith, I. J., Solomon, A., Storto, A., Takahashi, K., Toniazzo, T., & Vialard, J. Ocean climate observing requirements in support of climate research and climate information. Frontiers in Marine Science, 6, (2019): 444, doi:10.3389/fmars.2019.00444.

Description: Natural variability and change of the Earth’s climate have significant global societal impacts. With its large heat and carbon capacity and relatively slow dynamics, the ocean plays an integral role in climate, and provides an important source of predictability at seasonal and longer timescales. In addition, the ocean provides the slowly evolving lower boundary to the atmosphere, driving, and modifying atmospheric weather. Understanding and monitoring ocean climate variability and change, to constrain and initialize models as well as identify model biases for improved climate hindcasting and prediction, requires a scale-sensitive, and long-term observing system. A climate observing system has requirements that significantly differ from, and sometimes are orthogonal to, those of other applications. In general terms, they can be summarized by the simultaneous need for both large spatial and long temporal coverage, and by the accuracy and stability required for detecting the local climate signals. This paper reviews the requirements of a climate observing system in terms of space and time scales, and revisits the question of which parameters such a system should encompass to meet future strategic goals of the World Climate Research Program (WCRP), with emphasis on ocean and sea-ice covered areas. It considers global as well as regional aspects that should be accounted for in designing observing systems in individual basins. Furthermore, the paper discusses which data-driven products are required to meet WCRP research and modeling needs, and ways to obtain them through data synthesis and assimilation approaches. Finally, it addresses the need for scientific capacity building and international collaboration in support of the collection of high-quality measurements over the large spatial scales and long time-scales required for climate research, bridging the scientific rational to the required resources for implementation.

Description: This work was partly supported by the DFG funded excellence center CliSAP of the Universituat Hamburg (DS). AB was supported by the National Science Foundation through award NSF-1658174 and by the NOAA through award NA16OAR4310173. SM was supported by the Earth Systems and Climate Change Hub of the Australian Government’s National Environmental Science Program.