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By contrast, the number of convective regions primarily impacts the zonal variance of humidity-related quantities in the aquaplanet simulations, as the distribution of convective regions affects the size of the subsidence regions and thereby the moistening influence of convective regions. The aquaplanet simulations confirm many other qualitative results from RCE simulations, such as a reduction of equatorial tropospheric humidity when the area covered by convection diminishes.This paper describes the GISS-E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS-E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden-Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7-3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks.Cloud and precipitation systems are simulated with a multi-scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar-defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to produce simulated precipitation features (PFs) from the output of the embedded two-dimensional (2D) cloud-resolving models (CRMs) within an MMF. Despite the limitations of 2D CRMs, the simulated population distribution, horizontal and vertical structure of PFs, and the geographical location and local rainfall contribution of mesoscale convective systems (MCSs) are in good agreement with the TRMM observations. However, some model discrepancies are found and can be identified and quantified within the PF distributions. selleck chemicals llc Using model biases in relative population and rainfall contributions, PFs can be characterized into four size categories small, medium to large, very large, and extremely large. Four different major mechanisms might account for the model biases in each different category (1) the two-dimensionality of the CRMs, (2) a positive convection-wind-evaporation feedback loop, (3) an artificial dynamic constraint in a bounded CRM domain with cyclic boundaries, and (4) the limited CRM domain size. The second and fourth mechanisms tend to contribute to the excessive tropical precipitation biases commonly found in most MMFs, whereas the other mechanisms reduce rainfall contributions from small and very large PFs. MMF sensitivity experiments with various CRM domain sizes and grid spacings showed that larger domains (higher resolutions) tend to shift PF populations toward larger (smaller) sizes.Spinning up a highly complex, coupled Earth system model (ESM) is a time consuming and computationally demanding exercise. For models with interactive ice sheet components, this becomes a major challenge, as ice sheets are sensitive to bidirectional feedback processes and equilibrate over glacial timescales of up to many millennia. This work describes and demonstrates a computationally tractable, iterative procedure for spinning up a contemporary, highly complex ESM that includes an interactive ice sheet component. The procedure alternates between a computationally expensive coupled configuration and a computationally cheaper configuration where the atmospheric component is replaced by a data model. By periodically regenerating atmospheric forcing consistent with the coupled system, the data atmosphere remains adequately constrained to ensure that the broader model state evolves realistically. The applicability of the method is demonstrated by spinning up the preindustrial climate in the Community Earth System Model Version 2 (CESM2), coupled to the Community Ice Sheet Model Version 2 (CISM2) over Greenland. The equilibrium climate state is similar to the control climate from a coupled simulation with a prescribed Greenland ice sheet, indicating that the iterative procedure is consistent with a traditional spin-up approach without interactive ice sheets. These results suggest that the iterative method presented here provides a faster and computationally cheaper method for spinning up a highly complex ESM, with or without interactive ice sheet components. link2 The method described here has been used to develop the climate/ice sheet initial conditions for transient, ice sheet-enabled simulations with CESM2-CISM2 in the Coupled Model Intercomparison Project Phase 6 (CMIP6).Gravity waves (GWs) generated by tropical convection are important for the simulation of large-scale atmospheric circulations, for example, the quasi-biennial oscillation (QBO), and small-scale phenomena like clear-air turbulence. link3 However, the simulation of these waves still poses a challenge due to the inaccurate representation of convection, and the high computational costs of global, cloud-resolving models. Methods combining models with observations are needed to gain the necessary knowledge on GW generation, propagation, and dissipation so that we may encode this knowledge into fast parameterized physics for global weather and climate simulation or turbulence forecasting. We present a new method suitable for rapid simulation of realistic convective GWs. Here, we associate the profile of latent heating with two parameters precipitation rate and cloud top height. Full-physics cloud-resolving WRF simulations are used to develop a lookup table for converting instantaneous radar precipitation rates and echo top measurements into a high-resolution, time-dependent latent heating field. The heating field from these simulations is then used to force an idealized dry version of the WRF model. We validate the method by comparing simulated precipitation rates and cloud tops with scanning radar observations and by comparing the GW field in the idealized simulations to satellite measurements. Our results suggest that including variable cloud top height in the derivation of the latent heating profiles leads to better representation of the GWs compared to using only the precipitation rate. The improvement is especially noticeable with respect to wave amplitudes. This improved representation also affects the forcing of GWs on large-scale circulation.In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physicd to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.According to the data derived from several national and international registries, including SANI (Severe Asthma Network Italy), and considering the strong impact that frequent or regular use of oral corticosteroid has on quality of life (QoL) of severe asthmatics, as well as on the costs for managing corticosteroid-related diseases, oral corticosteroid sparing up to withdrawal should be considered a primary outcome in the management of severe asthma. New biologics have clearly demonstrated that this effect is possible, with concomitant reduction in the rate of exacerbations and in symptom control. Then, there is no reason for using so frequently oral corticosteroid before having explored all alternatives currently available for a large part of severe asthmatics.Data from electronic health records (EHR) are prone to errors, which are often correlated across multiple variables. The error structure is further complicated when analysis variables are derived as functions of two or more error-prone variables. Such errors can substantially impact estimates, yet we are unaware of methods that simultaneously account for errors in covariates and time-to-event outcomes. Using EHR data from 4217 patients, the hazard ratio for an AIDS-defining event associated with a 100 cell/mm3 increase in CD4 count at ART initiation was 0.74 (95%CI 0.68-0.80) using unvalidated data and 0.60 (95%CI 0.53-0.68) using fully validated data. Our goal is to obtain unbiased and efficient estimates after validating a random subset of records. We propose fitting discrete failure time models to the validated subsample and then multiply imputing values for unvalidated records. We demonstrate how this approach simultaneously addresses dependent errors in predictors, time-to-event outcomes, and inclusion criteria. Using the fully validated dataset as a gold standard, we compare the mean squared error of our estimates with those from the unvalidated dataset and the corresponding subsample-only dataset for various subsample sizes. By incorporating reasonably sized validated subsamples and appropriate imputation models, our approach had improved estimation over both the naive analysis and the analysis using only the validation subsample.The anatomy of the wrist and hand is complex and contains numerous small structures. Magnetic resonance imaging (MRI) is often an ideal imaging modality in the assessment of various traumatic and pathologic conditions of this region, and it is frequently performed after initial radiographs. In this manuscript we describe the normal anatomy, imaging techniques, and MRI findings of various traumatic and pathologic conditions of the wrist and hand including occult fractures, osteonecrosis, ligamentous and tendon injuries, and entrapment neuropathies.Elbow pain can cause disability, especially in athletes, and is a common clinical complaint for both the general practitioner and the orthopaedic surgeon. Magnetic resonance imaging (MRI) is an excellent tool for the evaluation of joint pathology due to its high sensitivity as a result of high contrast resolution for soft tissues. This article aims to describe the normal imaging anatomy and biomechanics of the elbow, the most commonly used MRI protocols and techniques, and common MRI findings related to tendinopathy, ligamentous and osteochondral injuries, and instability of the elbow.
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