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The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000–19,000 y ago (27–19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30–13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe.

This study suggests potential benefits in forecast performance by assimilating clear-sky satellite radiances from geostationary based SEVIRI instrument into the limited area model of HARMONIE-AROME in the far North of Europe. The current geographical limitations of assimilating geostationary have been breached and a series of data assimilation experiments were conducted over a winter period to assess the impact of including SEVIRI water vapor channels at large satellite zenith angles. The results suggest improved background departures and improved analyses for humidity and temperature fields and subsequent enhancements in forecast skill in surface meteorological parameters like pressure, temperature, humidity and clouds. The findings highlight opportunities for using geostationary satellite data beyond current limitations and identify areas for further improvements.

Numerical weather prediction models contain parameters that are inherently uncertain and cannot be determined exactly. It is thus desirable to have reliable objective approaches for estimation of optimal values and uncertainties of these parameters. Traditionally, the parameter tuning has been done manually, which can lead to the tuning process being a maze of subjective choices. In this paper we present how to optimize 20 key physical parameters in the atmospheric model Open Integrated Forecasting System (OpenIFS) that have a strong impact on forecast quality. The results show that simultaneous optimization of O (20) parameters is possible with O (100) algorithm steps using an ensemble of O (20) members; the results also show that the optimized parameters lead to substantial enhancement of predictive skill. The enhanced predictive skill can be attributed to reduced biases in low-level winds and upper-tropospheric humidity in the optimized model. We find that the optimization process is dependent on the starting values of the parameters that are optimized (starting from better-suited values results in a better model). The results show also that the applicability of the tuned parameter values across different model resolutions is somewhat limited because of resolution-dependent model biases, and we also found that the parameter covariances provided by the tuning algorithm seem to be uninformative.

Purpose Juvenile polyposis syndrome (JPS) is a rare, autosomal-dominantly inherited cancer predisposition caused in approximately 50% of cases by pathogenic germline variants in SMAD4 and BMPR1A . We aimed to gather detailed clinical and molecular genetic information on JPS disease expression to provide a basis for management guidelines and establish open access variant databases. Methods We performed a retrospective, questionnaire-based European multicenter survey on and established a cohort of SMAD4/BMPR1A pathogenic variant carriers from the medical literature. Results We analyzed questionnaire-based data on 221 JPS patients (126 kindreds) from ten European centers and retrieved literature-based information on 473 patients. Compared with BMPR1A carriers, SMAD4 carriers displayed anemia twice as often (58% vs. 26%), and exclusively showed overlap symptoms with hemorrhagic telangiectasia (32%) and an increased prevalence (39% vs. 13%) of gastric juvenile polyps. Cancer, reported in 15% of JPS patients (median age 41 years), mainly occurred in the colorectum (overall: 62%, SMAD4 : 58%, BMPR1A : 88%) and the stomach (overall: 21%; SMAD4 : 27%, BMPR1A : 0%). Conclusion This comprehensive retrospective study on genotype–phenotype correlations in 694 JPS patients corroborates previous observations on JPS in general and SMAD4 carriers in particular, facilitates recommendations for clinical management, and provides the basis for open access variant SMAD4 and BMPR1A databases.

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 ∼550-800 hPa. Large vertical gradients occur in the profile of the mean temperature difference between ERA5 and observations at ∼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 ∼650-800 hPa while ERA-Interim is closer to observations there. Below the ∼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.

Lauri Aaltonen and colleagues show that a region on 8q24 associated with colorectal cancer risk functions as an enhancer and that the risk allele at this locus binds with higher affinity to the Wnt-regulated transcription factor TCF4 (also called TCF7L2), conferring enhanced responsiveness to Wnt signaling. Homozygosity for the G allele of rs6983267 at 8q24 increases colorectal cancer (CRC) risk ∼1.5 fold. We report here that the risk allele G shows copy number increase during CRC development. Our computer algorithm, Enhancer Element Locator (EEL), identified an enhancer element that contains rs6983267. The element drove expression of a reporter gene in a pattern that is consistent with regulation by the key CRC pathway Wnt. rs6983267 affects a binding site for the Wnt-regulated transcription factor TCF4, with the risk allele G showing stronger binding in vitro and in vivo . Genome-wide ChIP assay revealed the element as the strongest TCF4 binding site within 1 Mb of MYC . An unambiguous correlation between rs6983267 genotype and MYC expression was not detected, and additional work is required to scrutinize all possible targets of the enhancer. Our work provides evidence that the common CRC predisposition associated with 8q24 arises from enhanced responsiveness to Wnt signaling.

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined.

Hurricane Ophelia was a category 3 hurricane which underwent extratropical transition and made landfall in Europe as an exceptionally strong post-tropical cyclone in October 2017. In Ireland, Ophelia was the worst storm in 50 years and resulted in significant damage and even loss of life. In this study, the different physical processes affecting Ophelia's transformation from a hurricane to a mid-latitude cyclone are studied. For this purpose, we have developed software that uses OpenIFS model output and a system consisting of a generalized omega equation and vorticity equation. By using these two equations, the atmospheric vertical motion and vorticity tendency are separated into the contributions from different physical processes: vorticity advection, thermal advection, friction, diabatic heating, and the imbalance between the temperature and vorticity tendencies. Vorticity advection, which is often considered an important forcing for the development of mid-latitude cyclones, is shown to play a small role in the re-intensification of the low-level cyclone. Instead, our results show that the adiabatic upper-level forcing was strongly amplified by moist processes, and thus, the diabatic heating was the dominant forcing in both the tropical and extratropical phases of Ophelia. Furthermore, we calculated in more detail the diabatic heating contributions from different model parameterizations. We find that the temperature tendency due to the convection scheme was the dominant forcing for the vorticity tendency during the hurricane phase, but as Ophelia transformed into a mid-latitude cyclone, the microphysics temperature tendency, presumably dominated by large-scale condensation, gradually increased becoming the dominant forcing once the transition was complete. Temperature tendencies caused by other diabatic processes, such as radiation, surface processes, vertical diffusion, and gravity wave drag, were found to be negligible in the development of the storm.

Relative humidity (RH) has been observed to be anticorrelated with continental new particle formation. Several reasons have been proposed for this rather surprising finding, but no firm conclusions have been drawn so far. Here we study several of the proposed reasons: Enhanced coagulational scavenging of sub‐3 nm clusters at high RH, diminished solar radiation at high RH leading to diminished gas phase oxidation chemistry, and increased condensation sink (CS) of condensable gases due to hygroscopic growth of the preexisting particles. Our theoretical calculations indicate that the increase of coagulational scavenging plays a relatively small role in the inhibition of nucleation at high RH. On the other hand, field data show that the maximum observed gas phase sulphuric acid concentrations are limited to RHs below 60%. The field data also indicate that this is likely due to low OH concentrations at high RH. This finding is also supported by aerosol dynamics model simulations. The model was used to find out whether this is mainly due to decreased source (solar radiation) or increased sink (CS) terms at the elevated RH. The simulation results show that the decreased source term at high RH limits H2SO4 levels in the air, and therefore high new particle formation rates (above ∼1 cm−3 s−1) rarely occur above 80% RH.

Mobile, vehicle-installed road weather sensors are becoming ubiquitous. While mobile sensors are often capable of making observations on a high frequency, their reliability and accuracy may vary. Large-scale road weather observation and forecasting are still mostly based on stationary road weather stations (RWS). Though expensive, sparsely located and making observations on a relatively low frequency, RWS' reliability and accuracy are well-known and accommodated for in the road weather forecasting models. Statistical analysis revealed that road weather conditions indeed have a great effect on how the observations of mobile and stationary road weather temperature sensors differ from each other. Consequently, we calibrated the observations of mobile sensors with a linear mixed model. The mixed model was fitted fusing ca. 20 000 pairs of mobile and RWS observations of the same location at the same time, following a rendezvous model of sensor calibration. The calibration nearly halved the MSE between the observations of the mobile and the RWS sensor types. Computationally very light, the calibration can be embedded directly in the sensors.