Histone deacetylases (HDACs) tighten chromatin structure and repress gene expression through the removal of acetyl groups from histone tails. The class I HDACs, HDAC1 and HDAC2, are expressed ubiquitously, but their potential roles in tissue-specific gene expression and organogenesis have not been defined. To explore the functions of HDAC1 and HDAC2 in vivo, we generated mice with conditional null alleles of both genes. Whereas global deletion of HDAC1 results in death by embryonic day 9.5, mice lacking HDAC2 survive until the perinatal period, when they succumb to a spectrum of cardiac defects, including obliteration of the lumen of the right ventricle, excessive hyperplasia and apoptosis of cardiomyocytes, and bradycardia. Cardiac-specific deletion of either HDAC1 or HDAC2 does not evoke a phenotype, whereas cardiac-specific deletion of both genes results in neonatal lethality, accompanied by cardiac arrhythmias, dilated cardiomyopathy, and up-regulation of genes encoding skeletal muscle-specific contractile proteins and calcium channels. Our results reveal cell-autonomous and non-cell-autonomous functions for HDAC1 and HDAC2 in the control of myocardial growth, morphogenesis, and contractility, which reflect partially redundant roles of these enzymes in tissue-specific transcriptional repression.[Keywords: Heart development; histone deacetylase; transcription] Supplemental material is available at http://www.genesdev.org.

Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.

A high-resolution (3-km horizontal grid spacing) near-cloud-resolving numerical simulation of the formation of Hurricane Diana (1984) is used to examine the contribution of deep convective processes to tropical cyclone formation. This study is focused on the 3-km horizontal grid spacing simulation because this simulation was previously found to furnish an accurate forecast of the later stages of the observed storm life cycle. The numerical simulation reveals the presence of vortical hot towers, or cores of deep cumulonimbus convection possessing strong vertical vorticity, that arise from buoyancy-induced stretching of local absolute vertical vorticity in a vorticity-rich prehurricane environment. At near-cloud-resolving scales, these vortical hot towers are the preferred mode of convection. They are demonstrated to be the most important influence to the formation of the tropical storm via a two-stage evolutionary process: (i) preconditioning of the local environment via diabatic production of multiple small-scale lowertropospheric cyclonic potential vorticity (PV) anomalies, and (ii) multiple mergers and axisymmetrization of these low-level PV anomalies. The local warm-core formation and tangential momentum spinup are shown to be dominated by the organizational process of the diabatically generated PV anomalies; the former process being accomplished by the strong vertical vorticity in the hot tower cores, which effectively traps the latent heat from moist convection. In addition to the organizational process of the PV anomalies, the cyclogenesis is enhanced by the aggregate diabatic heating associated with the vortical hot towers, which produces a net influx of lowlevel mean angular momentum throughout the genesis. Simpler models are examined to elucidate the underlying dynamics of tropical cyclogenesis in this case study. Using the Sawyer-Eliassen balanced vortex model to diagnose the macroscale evolution, the cyclogenesis of Diana is demonstrated to proceed in approximate gradient and hydrostatic balance at many instances, where local radial and vertical accelerations are small. Using a shallow water primitive equation model, a characteristic ''moist'' (diabatic) vortex merger in the cloud-resolving numerical simulation is captured in a large part by the barotropic model. Since a moist merger results in a stronger vortex and occurs twice as fast as a dry merger, it is inferred (consistent with related work) that a net low-level convergence can accelerate and intensify the merger process in the real atmosphere. Although the findings reported herein are based on a sole case study and thus cannot yet be generalized, it is believed the results are sufficiently interesting to warrant further idealized simulations of this nature.

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A recently developed method of defining rain areas for the purpose of verifying precipitation produced by numerical weather prediction models is described. Precipitation objects are defined in both forecasts and observations based on a convolution (smoothing) and thresholding procedure. In an application of the new verification approach, the forecasts produced by the Weather Research and Forecasting (WRF) model are evaluated on a 22-km grid covering the continental United States during July-August 2001. Observed rainfall is derived from the stage-IV product from NCEP on a 4-km grid (averaged to a 22-km grid). It is found that the WRF produces too many large rain areas, and the spatial and temporal distribution of the rain areas reveals regional underestimates of the diurnal cycle in rain-area occurrence frequency. Objects in the two datasets are then matched according to the separation distance of their centroids. Overall, WRF rain errors exhibit no large biases in location, but do suffer from a positive size bias that maximizes during the later afternoon. This coincides with an excessive narrowing of the rainfall intensity range, consistent with the dominance of parameterized convection. Finally, matching ability has a strong dependence on object size and is interpreted as the influence of relatively predictable synoptic-scale systems on the larger areas.