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Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.

The Tibetan Plateau (TP) contains the largest amount of snow outside the polar regions and is the source of many major rivers in Asia. An accurate long-range (i.e. seasonal) meteorological forecast is of great importance for this region. The fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5) provides global long-range meteorological forecasts including over the TP. However, SEAS5 uses land initial conditions produced by assimilating Interactive Multisensor Snow and Ice Mapping System (IMS) snow data only below 1500 m altitude, which may affect the forecast skill of SEAS5 over mountainous regions like the TP. To investigate the impacts of snow assimilation on the forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer 2018. Significant changes occur in the springtime. Without snow assimilation, the reforecasts overestimate snow cover and snow depth while underestimating daily temperature over the TP. Compared to satellite-based estimates, precipitation reforecasts perform better in the west TP (WTP) than in the east TP (ETP). With snow assimilation, the reforecasts of snow cover, snow depth and temperature are consistently improved in the TP in the spring. However, the positive bias between the precipitation reforecasts and satellite observations worsens in the ETP. Compared to the experiment with no snow assimilation, the snow assimilation experiment significantly increases temperature and precipitation for the ETP and around the longitude 95∘ E. The higher temperature after snow assimilation, in particular the cold bias reduction after initialization, can be attributed to the effects of a more realistic, decreased snowpack, providing favourable conditions for generating more precipitation. Overall, snow assimilation can improve seasonal forecasts through the interaction between land and atmosphere.

Abstract: The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. The work was performed in the framework of the GEWEX/LS4P Phase I (LS4P-I) experiment, which focused on whether the TP LST/SUBT provides an additional source for subseasonal-to-seasonal (S2S) predictability. The summer 2003, when there were severe drought/flood over the southern/northern part of the Yangtze River basin, respectively, has been selected as the focus case. With the newly developed LST/SUBT initialization method, the observed surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature. Consideration of the TP LST/SUBT effect has produced about 25–50% of observed precipitation anomalies in most hotspot regions. The multiple models have shown more consistency in the hotspot regions along the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train. The mechanisms for the LST/SUBT effect on the 2003 drought over the southern part of the Yangtze River Basin are discussed. For comparison, the global SST effect has also been tested and 6 regions with significant SST effects were identified in the 2003 case, explaining about 25–50% of precipitation anomalies over most of these regions. This study suggests that the TP LST/SUBT effect is a first-order source of S2S precipitation predictability, and hence it is comparable to that of the SST effect. With the completion of the LS4P-I, the LS4P-II has been launched and the LS4P-II protocol is briefly presented.

Due to the lack of tools that can be easily used by practitioners, there is a need to develop acceptable embedded ways to assess children's fine motor skill development within early childhood education and care settings. This study examined the validity and reliability of a brief and ecologically valid fine motor assessment tool for preschool-aged children; the fine motor growth assessment (i.e., FINGA). Children's fine motor performance on FINGA was compared with widely-used and validated performance-based (Peabody Developmental Motor Scales 2nd edition) and informant-based (Ages and Stages Questionnaire 3rd edition) fine motor assessments. Ninety-one children [mean age (y) ± SD = 4.50y ± 0.68] were assessed within seven early childhood education and care services in New South Wales, Australia. Exploratory factor analyses (EFA) and linear regression analyses showed that FINGA had good internal consistency (EFA of 73%) and age sensitivity (B[subscript std] = 0.69, p < 0.001), and bivariate correlation analyses demonstrated good concurrent validity (rs from 0.69 to 0.84, ps < 0.001) against the two comparison assessments. Because of its brevity and ecological validity, the FINGA tool should be further examined as a routine fine motor skills assessment administered within the context of universal early childhood education and care service provision.

There is need and opportunity for assessments that support quick and playful--yet also accurate, rigorous and developmentally sensitive--appraisals of early numeracy. Ideally, these should be accessible to those who have opportunity to support children's learning development and ultimately shift children's trajectories. The iPad-based "Early Years Toolbox (EYT) Early Numeracy" assessment was developed and evaluated to determine its validity and reliability, and appropriateness of use by researchers and preschool educators. Results from two studies with 246 children aged 3-5 years indicated the following: construct validity and internal consistency, concurrent validity with established measures, developmental sensitivity, test--retest reliability and highly comparable results whether used by a researcher or an educator. This yields a brief and playful assessment of early numeracy and a potential approach to develop broad-use early years assessments.

Background: Over the past few decades early self-regulation has been identified as foundational to positive learning and wellbeing trajectories. As a consequence, a wide range of approaches have been developed to capture children's developmental progress in self-regulation. Little is known, however, about whether and which of these are reliable indicators of future ability and risk for young children. Objective: This study examined measures from prominent approaches to self-regulation assessment (i.e., task-based, observation, adult-report) to determine: their structure; how these predict future academic school readiness in 3-5-year-old children, individually and if combined; and whether thresholds could be ascertained to reliably discriminate those children at risk of poor academic outcomes. Methods: Longitudinal analyses were conducted on start-of-year self-regulation data from 217 children in the final year of pre-school, using three prominent approaches to self-regulation assessment, and their end-of-year school readiness data. Data were subjected to path analysis, structural equation modelling and receiver operating characteristic curve analyses. Results: Start-of-year cognitive self-regulation indices--but not behavioral or emotional self-regulation indices--from each approach reliably predicted school readiness 7 months later, just prior to commencing school. Only when combined into a composite score was a threshold with sufficient sensitivity and specificity for predicting school readiness risk established; yet this provided better prediction of true-negative than true-positive cases. Conclusions: Taken together, these results suggest the importance of cognitive self-regulation in particular for school readiness, as measured here, although self-regulation is just one of the contributing factors to school readiness risk.

Introduction: Vasa previa (VP), defined as unprotected fetal vessels traversing the membranes over the cervix, is associated with a high perinatal mortality when undiagnosed prenatally. Conversely, prenatal diagnosis with ultrasound and cesarean delivery before the membranes rupture is associated with excellent outcomes. However, controversy exists regarding screening for VP. In the UK, routine screening for VP is not recommended. The objective of this study was to report the incidence of VP and our experience in the detection of VP with a universal screening protocol at the time of the second-trimester fetal anomaly scan with third-trimester confirmation in an unselected population of pregnancies., Material and Methods: We performed a single-center historical cohort study of all pregnant women who underwent routine second-trimester anomaly screening scans at West Middlesex University Hospital, London, UK, between 2012 and 2016. Over 5 years, every patient undergoing routine anomaly screening was evaluated for VP using a systematic protocol during their 20-week anomaly scan. Suspected cases of VP were rescanned in the third trimester by specialist sonographers with an interest in VP. The primary outcomes were the incidence and detection of VP., Results: During the study period, 24 690 anatomy scans were performed. A total of 64 patients were identified as having potential VP at the second-trimester anomaly screening scan, of which 19 were confirmed by the specialist sonographer in the third trimester and at delivery. The screen positive rate was 0.26% (95% confidence interval [CI] 0.20%-0.32%). VP at birth was found in 19/24690 births (1:1299 [95% CI: 1:832-1:2030] births). Universal screening for VP using our protocol had a sensitivity of 100% and a specificity of 99.78% (95% CI: 99.72%-99.84%). The false-positive rate of the second-trimester screen was 0.18% (95% CI: 0.13-0.24). There were no false positives or false negatives at delivery. Of the 19 patients with confirmed VP, 17 had scheduled cesarean deliveries, and two required emergency deliveries due to antepartum hemorrhage. One baby died, giving a perinatal mortality of 5%., Conclusions: VP complicates approximately 1:1300 pregnancies. Routine screening for VP yielded a 100% detection rate. We suggest the inclusion of structured VP assessment in standard fetal anomaly screening programs., (© 2024 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).)