Grey zone simulations of the morning convective boundary layer development

Numerical simulations of two cases of morning boundary layer development are conducted to investigate the impact of grid resolution on mean profiles and turbulent kinetic energy (TKE) partitioning from the large eddy simulation (LES) to the mesoscale limit. Idealized LES, using the 3-D Smagorinsky scheme, is shown to be capable of reproducing the boundary layer evolution when compared against measurements. However, increasing grid spacing results in the damping of resolved TKE and the production of superadiabatic temperature profiles in the boundary layer. Turbulence initiation is significantly delayed, exhibiting an abrupt onset at intermediate resolutions. Two approaches, the bounding of vertical diffusion coefficient and the blending of the 3-D Smagorinsky with a nonlocal 1D scheme, are used to model subgrid diffusion at grey zone resolutions. Simulations are compared against the coarse-grained fields from the validated LES results for each case. Both methods exhibit particular strengths and weaknesses, indicating the compromise that needs to be made currently in high-resolution numerical weather prediction. The blending scheme is able to reproduce the adiabatic profiles although turbulence is underestimated in favor of the parametrized heat flux, and the spin-up of TKE remains delayed. In contrast, the bounding approach gives an evolution of TKE that follows the coarse-grained LES very well, relying on the resolved motions for the nonlocal heat flux. However, bounding gives unrealistic static instability in the early morning temperature profiles (similar to the 3-D Smagorinsky scheme) because model dynamics are unable to resolve TKE when the boundary layer is too shallow compared to the grid spacing.This work has been funded by the Natural Environment Research Council (NERC) GREYBLS (Modelling Grey Zone Boundary Layers) project (grant NE/K011456/1). We acknowledge the use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the Met Office and the Natural Environment Research Council

Assessment of valley cold pools and clouds in a very high-resolution numerical weather prediction model

The formation of cold air pools in valleys under stable conditions represents an important challenge for numerical weather prediction (NWP). The challenge is increased when the valleys that dominate cold pool formation are on scales unresolved by NWP models, which can lead to substantial local errors in temperature forecasts. In this study a 2-month simulation is presented using a nested model con- figuration with a finest horizontal grid spacing of 100 m. The simulation is compared with observations from the recent COLd air Pooling Experiment (COLPEX) project and the model’s ability to represent cold pool formation, and the surface energy balance is assessed. The results reveal a bias in the model long-wave radiation that results from the assumptions made about the sub-grid variability in humidity in the cloud parametrization scheme. The cloud scheme assumes relative humidity thresholds below 100 % to diagnose partial cloudiness, an approach common to schemes used in many other models. The biases in radiation, and resulting biases in screen temperature and cold pool properties are shown to be sensitive to the choice of critical relative humidity, suggesting that this is a key area that should be improved for very high-resolution modeling

A method to represent subgrid-scale updraft velocity in kilometer-scale models: Implication for aerosol activation

©2014. American Geophysical Union. All Rights Reserved. Updraft velocities strongly control the activation of aerosol particles or that component that act as cloud condensation nuclei (CCN). For kilometer-scale models, vertical motions are partially resolved but the subgrid-scale (SGS) contribution needs to be parametrized or constrained to properly represent the activation of CCNs. This study presents a method to estimate the missing SGS (or unresolved) contribution to vertical velocity variability in models with horizontal grid sizes up to ∼2 km. A framework based on Large Eddy Simulations (LES) and high-resolution aircraft observations of stratocumulus and shallow cumulus clouds has been developed and applied to output from the United Kingdom Met Office Unified Model (UM) operating at kilometer-scale resolutions in numerical weather prediction configuration. For a stratocumulus deck simulation, we show that the UM 1 km model underestimates significantly the variability of updraft velocity with an averaged cloud base standard deviation between 0.04 and 0.05 m s-1 compared to LES and aircraft estimates of 0.38 and 0.54 m s-1, respectively. Once the SGS variability is considered, the UM corrected averages are between 0.34 and 0.44 m s-1. Off-line calculations of CCN-activated fraction using an activation scheme have been performed to illustrate the implication of including the SGS vertical velocity. It suggests increased CCN-activated fraction from 0.52 to 0.89 (respectively, 0.10 to 0.54) for a clean (respectively, polluted) aerosol environment for simulations with a 1 km horizontal grid size. Our results highlight the importance of representing the SGS vertical velocity in kilometer-scale simulations of aerosol-cloud interactions. Key PointsWe seek to improve the aerosol activation behavior in kilometer-scale modelsA method to constrain the subgrid-scale updraft velocity is presentedWe highlight the potential implication for aerosol-cloud interactions modeling.This work was funded by the Natural Environment Research Council (NERC) Aerosol-Cloud Interactions—a Directed Programme to Reduce Uncertainty in Forcing (ACID-PRUF) programme, grant code NE/I020121/1. The authors thank the scientists, ground crew and aircrew of the FAAM BAe-146 and C-130 aircraft, who were instrumental in the collection of the data analyzed from the VOCALS-REx campaign. The C-130 data were provided by NCAR/EOL, under sponsorship of the National Science Foundation. http://data.eol. ucar.edu/. The FAAM BAe-146 is jointly funded by the UK Met Office and the Natural Environment Research Council. VOCALS was supported by the UK Met Office and NERC, the latter through grant NE/F019874/1

The influence of the atmospheric boundary layer on nocturnal layers of noctuids and other moths migrating over southern Britain

Insects migrating at high altitude over southern Britain have been continuously monitored by automatically-operating, vertical-looking radars over a period of several years. During some occasions in the summer months, the migrants were observed to form well-defined layer concentrations, typically at heights of 200-400 m, in the stable night-time atmosphere. Under these conditions, insects are likely to have control over their vertical movements and are selecting flight heights which are favourable for long-range migration. We therefore investigated the factors influencing the formation of these insect layers by comparing radar measurements of the vertical distribution of insect density with meteorological profiles generated by the UK Met. Office’s Unified Model (UM). Radar-derived measurements of mass and displacement speed, along with data from Rothamsted Insect Survey light traps provided information on the identity of the migrants. We present here three case studies where noctuid and pyralid moths contributed substantially to the observed layers. The major meteorological factors influencing the layer concentrations appeared to be: (a) the altitude of the warmest air, (b) heights corresponding to temperature preferences or thresholds for sustained migration and (c), on nights when air temperatures are relatively high, wind-speed maxima associated with the nocturnal jet. Back-trajectories indicated that layer duration may have been determined by the distance to the coast. Overall, the unique combination of meteorological data from the UM and insect data from entomological radar described here show considerable promise for systematic studies of high-altitude insect layering

Single‐Column Model Simulations of Subtropical Marine Boundary‐Layer Cloud Transitions Under Weakening Inversions

Results are presented of the GASS/EUCLIPSE single‐column model intercomparison study on the subtropical marine low‐level cloud transition. A central goal is to establish the performance of state‐of‐the‐art boundary‐layer schemes for weather and climate models for this cloud regime, using large‐eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North‐Eastern Pacific, while one reflects conditions in the North‐Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low‐level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well‐known “too few too bright” problem. The boundary‐layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization

Impact Factor: outdated artefact or stepping-stone to journal certification?

A review of Garfield's journal impact factor and its specific implementation as the Thomson Reuters Impact Factor reveals several weaknesses in this commonly-used indicator of journal standing. Key limitations include the mismatch between citing and cited documents, the deceptive display of three decimals that belies the real precision, and the absence of confidence intervals. These are minor issues that are easily amended and should be corrected, but more substantive improvements are needed. There are indications that the scientific community seeks and needs better certification of journal procedures to improve the quality of published science. Comprehensive certification of editorial and review procedures could help ensure adequate procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table

Exploring the acceleration of the Met Office NERC Cloud model using FPGAs

The use of Field Programmable Gate Arrays (FPGAs) to accelerate computational kernels has the potential to be of great benefit to scientific codes and the HPC community in general. With the recent developments in FPGA programming technology, the ability to port kernels is becoming far more accessible. However, to gain reasonable performance from this technology it is not enough to simple transfer a code onto the FPGA, instead the algorithm must be rethought and recast in a data-flow style to suit the target architecture. In this paper we describe the porting, via HLS, of one of the most computationally intensive kernels of the Met Office NERC Cloud model (MONC), an atmospheric model used by climate and weather researchers, onto an FPGA. We describe in detail the steps taken to adapt the algorithm to make it suitable for the architecture and the impact this has on kernel performance. Using a PCIe mounted FPGA with on-board DRAM, we consider the integration on this kernel within a larger infrastructure and explore the performance characteristics of our approach in contrast to Intel CPUs that are popular in modern HPC machines, over problem sizes involving very large grids. The result of this work is an experience report detailing the challenges faced and lessons learnt in porting this complex computational kernel to FPGAs, as well as exploring the role that FPGAs can play and their fundamental limits in accelerating traditional HPC workloads.Comment: Preprint of article in proceedings, ISC High Performance 2019. Lecture Notes in Computer Science, vol 1188

Interactions between hydrological sensitivity, radiative cooling, stability, and low-level cloud amount feedback

This is the author accepted manuscript. The final version is available from American Meteorological Society via the DOI in this record.Low-level cloud feedbacks vary in magnitude but are positive in most climate models, due to reductions in low-level cloud fraction. This study explores the impact of surface evaporation on low-level cloud fraction feedback by performing climate change experiments with the aquaplanet configuration of the HadGEM2-A climate model, forcing surface evaporation to increase at different rates in two ways. Forcing the evaporation diagnosed in the surface scheme to increase at 7% K -1 with warming (more than doubling the hydrological sensitivity) results in an increase in global mean low-level cloud fraction and a negative global cloud feedback, reversing the signs of these responses compared to the standard experiments. The estimated inversion strength (EIS) increases more rapidly in these surface evaporation forced experiments, which is attributed to additional latent heat release and enhanced warming of the free troposphere. Stimulating a 7% K -1 increase in surface evaporation via enhanced atmospheric radiative cooling, however, results in a weaker EIS increase compared to the standard experiments and a slightly stronger low-level cloud reduction. The low-level cloud fraction response is predicted better by EIS than surface evaporation across all experiments. This suggests that surface-forced increases in evaporation increase low-level cloud fraction mainly by increasing EIS. Additionally, the results herein show that increases in surface evaporation can have a very substantial impact on the rate of increase in radiative cooling with warming, by modifying the temperature and humidity structure of the atmosphere. This has implications for understanding the factors controlling hydrological sensitivity.Mark Webb was supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme 726 (GA01101)

Improved representation of the diurnal variation of warm season precipitation by an atmospheric general circulation model at a 10 km horizontal resolution

This study investigates the diurnal variation of the warm season precipitation simulated by the Goddard Earth Observing System version 5 atmospheric general circulation model for 2??years (2005???2006) at a horizontal resolution of 10??km. The simulation was validated with the satellite-derived Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data and the Modern-Era Retrospective analysis for Research and Applications atmospheric reanalysis for atmospheric winds and moisture. The simulation is compared with the coarse-resolution run in 50??km to examine the impacts driven by resolution change. Overall, the 10??km model tends to reproduce the important features of the observed diurnal variation, such as the amplitude and phase at which precipitation peaks in the evening on land and in the morning over the ocean, despite an excessive amplitude bias over land. The model also reproduces the realistic propagation patterns of precipitation in the vicinity of ocean coasts and major mountains. The regional characteristics of the diurnal precipitation over two regions, the Bay of Bengal and the Great Plains in North America, are examined in detail, where the observed diurnal cycle exhibits a systematic transition in the peak phase due to the development and propagation of regional-scale convective systems. The model is able to reproduce this pattern as well as the diurnal variation of low-level wind and moisture convergence; however, it is less effective at representing the nocturnal peak of precipitation over the Great Plains. The model results suggest that increasing the horizontal resolution of the model to 10??km substantially improves the representation of the diurnal precipitation cycle. However, intrinsic model deficiencies in topographical precipitation and the accurate representation of mesoscale convective systems remain a challenge

TNFR1 inhibition with a nanobody protects against EAE development in mice

TNF has as detrimental role in multiple sclerosis (MS), however, anti-TNF medication is not working. Selective TNF/TNFR1 inhibition whilst sparing TNFR2 signaling reduces the pro-inflammatory effects of TNF but preserves the important neuroprotective signals via TNFR2. We previously reported the generation of a Nanobody-based selective inhibitor of human TNFR1, TROS that will be tested in experimental autoimmune encephalomyelitis (EAE). We specifically antagonized TNF/TNFR1 signaling using TROS in a murine model of MS, namely MOG(35-55)-induced EAE. Because TROS does not cross-react with mouse TNFR1, we generated mice expressing human TNFR1 in a mouse TNFR1-knockout background (hTNFR1 Tg), and we determined biodistribution of Tc-99m-TROS and effectiveness of TROS in EAE in those mice. Biodistribution analysis demonstrated that intraperitoneally injected TROS is retained more in organs of hTNFR1 Tg mice compared to wild type mice. TROS was also detected in the cerebrospinal fluid (CSF) of hTNFR1 Tg mice. Prophylactic TROS administration significantly delayed disease onset and ameliorated its symptoms. Moreover, treatment initiated early after disease onset prevented further disease development. TROS reduced spinal cord inflammation and neuroinflammation, and preserved myelin and neurons. Collectively, our data illustrate that TNFR1 is a promising therapeutic target in MS