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A planetary boundary layer (PBL) height climatology from ECMWF reanalysis data is generated and analyzed. Different methods are first compared to derive PBL heights from atmospheric temperature, pressure, and relative humidity (RH), which mostly make use of profile gradients, for example, in RH, refractivity, and virtual or potential temperature. Three methods based on the vertical gradient of RH, virtual temperature, and potential temperature were selected for the climatology generation. The RH-based method appears to capture the inversion that caps the convective boundary layer very well as a result of its temperature and humidity dependence, while the temperature-based methods appear to capture the PBL better at high latitudes. A validation of the reanalysis fields with collocated radiosonde data shows generally good agreement in terms of mean PBL height and standard deviation for the RH-based method. The generated ECMWF-based PBL height climatology shows many of the expected climatological features, such as a fairly low PBL height near the west coast of continents where stratus clouds are found and PBL growth as the air is advected over warmer waters toward the tropics along the trade winds. Large seasonal and diurnal variations are primarily found over land. The PBL height can exceed 3 km, mostly over desert areas during the day, although large values can also be found in areas such as the ITCZ. The robustness of the statistics was analyzed by using information on the percentage of outliers. Here in particular, the sea-based PBL was found to be very stable.

The horizontal temperature gradients in the tropical free troposphere are generally assumed to be weak. We show with ERA5 data that substantial zonal virtual temperature (Tυ ) gradients persist climatologically in the tropical free troposphere and investigate their causes. The gradients change seasonally: Tυ at 500 hPa over the equatorial western Pacific Ocean (EWP) is usually much warmer (up to 3 K) than that over the equatorial central Pacific Ocean (ECP) during December–February (DJF), while the temperature differences between EWP and ECP are much smaller during June–August (JJA). During DJF, Tυ gradients over the Pacific prevail throughout the entire free troposphere, especially in the upper troposphere near 300 hPa. We find that the associated hydrostatic pressure gradients are mainly balanced by the nonlinear terms in the momentum equation, in particular via zonal wind advection. Strong zonal winds occur near the equator in boreal winter, transporting zonal momentum so as to balance the pressure gradient force. The zonal winds are due to large-scale equatorial waves, excited by a heating pattern that is relatively symmetric about the equator. In boreal summer, the large-scale equatorial waves are less active in the Pacific region due to a more asymmetric temperature pattern, so the zonal momentum advection and Tυ gradients are both much weaker. The results point to an important role of the nonlinear terms in the tropical balanced dynamics, stressing the need for an improved theoretical understanding and modeling framework of the tropical atmosphere that includes these nonlinear terms, or their net effect.

The virtual temperature used to model moisture-modified tropospheric dynamics is generalized to include a new thermospheric component. The resulting hybrid virtual potential temperature (HVPT) transitions seamlessly with height, from moist virtual potential temperature (MVPT) in the troposphere, to potential temperature in the stratosphere and mesosphere, to thermospheric virtual potential temperature thereafter. For numerical weather prediction (NWP) models looking to extend into the thermosphere, but still heavily invested in retaining MVPT-based dynamical cores for tropospheric prediction, upgrading to HVPT allows the core to capture critical new aspects of variable composition thermospheric dynamics, while leaving the original MVPT-based tropospheric equations and numerics essentially untouched. In this way, HVPT augmentation can both simplify and streamline extension into the thermosphere at little computational cost beyond the inevitable need for more vertical layers and somewhat smaller time steps. To demonstrate, we upgrade the MVPT-based dynamical core of the Navy global NWP model to HVPT, then test its performance in forecasting analytical globally balanced states containing hot or rapidly heated thermospheres and height-varying gas constants. These tests confirm that HVPT augmentation offers an efficient and effective means of extending MVPT-based NWP models into the thermosphere to accelerate development of future ground-to-space NWP models supporting space weather applications. The related issues of variable gravitational acceleration and shallow-atmosphere approximations are also briefly discussed.

Soil water and heat transfer is especially complicated during the freezing and thawing processes over the high‐altitude cold regions. In this study, four sensitivity tests of soil water and heat transfer parameterizations including replacing soil property data (SP1), soil resistance scheme modification (SP2), soil thermal conductivity scheme (SP3) and virtual temperature scheme (SP4), and four combination experiments (SP1+SP2+SP3/SP5, SP1+SP2+SP4/SP6, SP1+SP3+SP4/SP7, and SP1+SP2+SP3+SP4/SP8) were done using Community Land Model (CLM5.0) to examine its performances for soil water and heat transfer modeling on the Tibetan Plateau (TP) both in single‐point and regional simulations. The observed data from five eddy covariance sites, four soil moisture and temperature networks and 60 sites of soil temperature observations on the TP were used to evaluate the results. Single‐point simulations show that SP2 experiment reduced the wet biases of soil moisture in semiarid area, but enhanced the error of soil temperature. SP6 shows the best performances in simulating soil moisture, and SP3 in soil temperature. Regional simulations show that the SP7 experiment had the best performances for soil water and heat transfer simulation on the TP, and improved the simulation of soil freezing‐thawing processes. Compared to CLM5.0 default simulation, SP7 shows the best performances. For soil moisture, it reduced average Bias by 23%, Root Mean Square Error (RMSE) by 18%, and increased the Correlation Coefficient (Corr) by2%. For soil temperature, it reduced the Bias by 9%, 10%, 23%, and 13% at four soil depths on the TP, respectively. Plain Language Summary Soil water and heat transfer is a critical feature of the land surface process. Variations in soil water and heat transfer are important for water and energy partition between atmosphere and land surface. In this study, single‐point simulations were evaluated against the observed soil moisture and temperature and surface heat flux in different climate zones over the Tibetan Plateau (TP). Single‐point results using Community Land Model (CLM5.0) show that the simulated soil temperature generally coincided with observations, and large biases for soil moisture still remain in cold region. By replacing the soil property data in CLM5.0 default, simulations of soil moisture and temperature were improved during thawing period. To reduce the biases, modification of soil parameterization in CLM5.0 are proposed, (a) setup soil resistance to 0 in soil evaporation, (b) replacing freezing temperature by virtual temperature to determine occurring of phase change, (c) Using Balland and Arp schemes in soil thermal conductivity. We use different combinations of the above modifications to do the sensitivity experiments. The observed data from five eddy covariance sites, four soil moisture and temperature networks and 60 sites of soil temperature observations on the TP were used to evaluate the results. Regional simulations show that after modifying soil property data, the combination using Balland and Arp scheme and the virtual temperature scheme had the best performances for soil water and heat transfer simulation on the TP, reduced the wet biases from the beginning of melting stage. Key Points Simulation biases are evident in soil water and heat transfer After modifying the dry surface layer, it improves soil moisture simulation in semiarid area Use of Balland and Arp scheme and virtual temperature scheme improves the simulations of soil water and heat transfer

Mesoscale numerical weather prediction models using fine-grid [ O (1) km] meshes for weather forecasting, environmental assessment, and other applications capture aspects of larger-than-grid-mesh size, convectively induced secondary circulations (CISCs) such as cells and rolls that occur in the convective planetary boundary layer (PBL). However, 1-km grid spacing is too large for the simulation of the interaction of CISCs with smaller-scale turbulence. The existence of CISCs also violates the neglect of horizontal gradients of turbulent quantities in current PBL schemes. Both aspects—poorly resolved CISCs and a violation of the assumptions behind PBL schemes—are examples of what occurs in Wyngaard’s “terra incognita,” where horizontal grid spacing is comparable to the scale of the simulated motions. Thus, model CISCs (M-CISCs) cannot be simulated reliably. This paper describes how the superadiabatic layer in the lower convective PBL together with increased horizontal resolution allow the critical Rayleigh number to be exceeded and thus allow generation of M-CISCs like those in nature; and how the M-CISCs eventually neutralize the virtual temperature stratification, lowering the Rayleigh number and stopping their growth. Two options for removing M-CISCs while retaining their fluxes are 1) introducing nonlocal closure schemes for more effective removal of heat from the surface and 2) restricting the effective Rayleigh number to remain subcritical. It is demonstrated that CISCs are correctly handled by large-eddy simulation (LES) and thus may provide a way to improve representation of them or their effects. For some applications, it may suffice to allow M-CISCs to develop, but account for their shortcomings during interpretation.

The case of the heavy precipitation event on 14 and 15 October 2018 which has led to severe flash flooding in the Aude watershed in south-western France is studied from a meteorological point of view using deterministic and probabilistic numerical weather prediction systems, as well as a unique combination of observations from both standard and personal weather stations. This case features typical characteristics of Mediterranean heavy precipitation events such as its classic synoptic situation and its quasi-stationary convective precipitation that regenerates continuously, as well as some peculiarities such as the presence of a former hurricane and a pre-existing cold air mass close to the ground. Mediterranean Sea surface temperature and soil moisture anomalies are briefly reviewed, as they are known to play a role in this type of hydrometeorological events. A study of rainfall forecasts shows that the event had limited predictability, in particular given the small size of the watersheds involved. It is shown that the stationarity of precipitation, whose estimation benefits from data from personal stations, is linked to the presence near the ground of a trough and a strong potential virtual temperature gradient, the stationarity of both of which is highlighted by a combination of observations from standard and personal stations. The forecast that comes closest to the rainfall observations contains the warmest, wettest, and fastest low-level jet and also simulates near the ground a trough and a marked boundary between cold air in the west and warm air in the east, both of which are stationary.

Accurate and continuous estimates of the thermodynamic structure of the lower atmosphere are highly beneficial to meteorological process understanding and its applications, such as weather forecasting. In this study, the Tropospheric Remotely Observed Profiling via Optimal Estimation (TROPoe) physical retrieval is used to retrieve temperature and humidity profiles from various combinations of input data collected by passive and active remote sensing instruments, in situ surface platforms, and numerical weather prediction models. Among the employed instruments are microwave radiometers (MWRs), infrared spectrometers (IRSs), radio acoustic sounding systems (RASSs), ceilometers, and surface sensors. TROPoe uses brightness temperatures and/or radiances from MWRs and IRSs, as well as other observational inputs (virtual temperature from the RASS, cloud-base height from the ceilometer, pressure, temperature, and humidity from the surface sensors) in a physical iterative retrieval approach. This starts from a climatologically reasonable profile of temperature and water vapor, with the radiative transfer model iteratively adjusting the assumed temperature and humidity profiles until the derived brightness temperatures and radiances match those observed by the MWR and/or IRS instruments within a specified uncertainty, as well as within the uncertainties of the other observations, if used as input. In this study, due to the uniqueness of the dataset that includes all the abovementioned sensors, TROPoe is tested with different observational input combinations, some of which also include information higher than 4 km above ground level (a.g.l.) from the operational Rapid Refresh numerical weather prediction model. These temperature and humidity retrievals are assessed against independent collocated radiosonde profiles under non-cloudy conditions to assess the sensitivity of the TROPoe retrievals to different input combinations.

Topology optimization is a mathematical method used to determine the optimal design of a structure to achieve desirable functional performance. Traditional single-material topology optimization can be extended to include multiple materials, offering greater design freedom, and the potential for superior layouts. Additive manufacturing technologies have become powerful tools to build up such multi-material solutions. However, inherent limitations in these processes must be considered in the optimal design. One significant challenge in additive manufacturing is the trapping of either unmelted or non-solidified powder, or in some cases, support structures in enclosed voids. This study investigates a gradient-based 3D bi-material topology optimization method that considers not only the volume fraction of each material and total mass constraints but also an additional virtual temperature constraint to avoid enclosed voids. To this end, the virtual temperature method is extended to identify and mitigate enclosed voids in bi-material structures. An efficient and straightforward technique is proposed for interpolating the elemental virtual heat conduction matrix and the elemental thermal load. Additionally, a discrete material optimization approach is employed to interpolate the elemental stiffness matrix. The problem formulation and sensitivities are thoroughly discussed. The method of moving asymptotes is used to update the design variables, which are the element densities of each material. 3D numerical results are presented to demonstrate the capability and feasibility of the proposed implementation, thereby providing superior performing designs with minimal impact on the structural performance.

This study uses the WRF ARW to investigate how different atmospheric temperature environments impact the size and structure development of a simulated tropical cyclone (TC). In each simulation, the entire vertical virtual temperature profile is either warmed or cooled in 1°C increments from an initial specified state while the initial relative humidity profile and sea surface temperature are held constant. This alters the initial amount of convective available potential energy (CAPE), specific humidity, and air–sea temperature difference such that, when the simulated atmosphere is cooled (warmed), the initial specific humidity and CAPE decrease (increase), but the surface energy fluxes from the ocean increase (decrease). It is found that the TCs that form in an initially cooler environment develop larger wind and precipitation fields with more active outer-core rainband formation. Consistent with previous studies, outer-core rainband formation is associated with high surface energy fluxes, which leads to increases in the outer-core wind field. A larger convective field develops despite initializing in a low CAPE environment, and the dynamics are linked to a wider field of surface radial inflow. As the TC matures and radial inflow expands, large imports of relative angular momentum in the boundary layer continue to drive expansion of the TC’s overall size.

High-impact events such as heat waves and droughts are often associated with persistent positive geopotential height anomalies (PAs). Understanding how PA activity will change in a future warmer climate is therefore fundamental to projecting associated changes in weather and climate extremes. This is a complex problem because the dynamics of PAs and their associated blocking activity are still poorly understood. Furthermore, climate change influences on PA activity may be geographically dependent and encompass competing influences. To expose the salient impacts of climate change, we use an oceanic channel configuration of the Weather Research and Forecasting Model in a bivariate experiment focused on changes in environmental temperature, moisture, and baroclinicity. The 500-hPa wind speed and flow variability are found to increase with increasing temperature and baroclinicity, driven by increases in latent heat release and a stronger virtual temperature gradient. Changes to 500-hPa sinuosity are negligible. PAs are objectively identified at the 500-hPa level using an anomaly threshold method. When using a fixed threshold, PA trends indicate increased activity and strength with warming but decreased activity and strength with Arctic amplification. Use of a climate-relative threshold hides these trends and highlights the importance of accurate characterization of the mean flow. Changes in PA activity mirror corresponding changes in 500-hPa flow variability and are found to be attributable to changes in three distinct dynamical mechanisms: baroclinic wave activity, virtual temperature effects, and latent heat release.