GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system

A geospatial data processing tool, GEO4PALM, has been developed to generate geospatial static input for the Parallelized Large-Eddy Simulation (PALM) model system. PALM is a community-driven large-eddy simulation model for atmospheric and environmental research. Throughout PALM\u27s 20-year development, research interests have been increasing in its application to realistic conditions, especially for urban areas. For such applications, geospatial static input is essential. Although abundant geospatial data are accessible worldwide, geospatial data availability and quality are highly variable and inconsistent. Currently, the geospatial static input generation tools in the PALM community heavily rely on users for data acquisition and pre-processing. New PALM users face large obstacles, including significant time commitments, to gain the knowledge needed to be able to pre-process geospatial data for PALM. Expertise beyond atmospheric and environmental research is frequently needed to understand the data sets required by PALM. Here, we present GEO4PALM, which is a free and open-source tool. GEO4PALM helps users generate PALM static input files with a simple, homogenised, and standardised process. GEO4PALM is compatible with geospatial data obtained from any source, provided that the data sets comply with standard geo-information formats. Users can either provide existing geospatial data sets or use the embedded data interfaces to download geo-information data from free online sources for any global geographic area of interest. All online data sets incorporated in GEO4PALM are globally available, with several data sets having the finest resolution of 1 m. In addition, GEO4PALM provides a graphical user interface (GUI) for PALM domain configuration and visualisation. Two application examples demonstrate successful PALM simulations driven by geospatial input generated by GEO4PALM using different geospatial data sources for Berlin, Germany, and Ōtautahi / Christchurch, New Zealand. GEO4PALM provides an easy and efficient way for PALM users to configure and conduct PALM simulations for applications and investigations such as urban heat island effects, air pollution dispersion, renewable energy resourcing, and weather-related hazard forecasting. The wide applicability of GEO4PALM makes PALM more accessible to a wider user base in the scientific community

Federated NLP in Few-shot Scenarios

Natural language processing (NLP) sees rich mobile applications. To support various language understanding tasks, a foundation NLP model is often fine-tuned in a federated, privacy-preserving setting (FL). This process currently relies on at least hundreds of thousands of labeled training samples from mobile clients; yet mobile users often lack willingness or knowledge to label their data. Such an inadequacy of data labels is known as a few-shot scenario; it becomes the key blocker for mobile NLP applications. For the first time, this work investigates federated NLP in the few-shot scenario (FedFSL). By retrofitting algorithmic advances of pseudo labeling and prompt learning, we first establish a training pipeline that delivers competitive accuracy when only 0.05% (fewer than 100) of the training data is labeled and the remaining is unlabeled. To instantiate the workflow, we further present a system FFNLP, addressing the high execution cost with novel designs. (1) Curriculum pacing, which injects pseudo labels to the training workflow at a rate commensurate to the learning progress; (2) Representational diversity, a mechanism for selecting the most learnable data, only for which pseudo labels will be generated; (3) Co-planning of a model's training depth and layer capacity. Together, these designs reduce the training delay, client energy, and network traffic by up to 46.0$\times$, 41.2$\times$ and 3000.0$\times$, respectively. Through algorithm/system co-design, FFNLP demonstrates that FL can apply to challenging settings where most training samples are unlabeled

AdS/BCFT and Island for curvature-squared gravity

In this paper, we investigate AdS/BCFT for curvature-squared gravity. To warm up, we start with Gauss-Bonnet gravity. We derive the one point function of stress tensor and show that the central charge related to the norm of displacement operator is positive for the couplings obeying causality constraints. Furthermore, by imposing the null energy condition on the end-of-the-world brane, we prove the holographic g-theorem for Gauss-Bonnet gravity. This corrects a wrong point of view in the literature, which claims that the holographic g-theorem is violated for Gauss-Bonnet gravity. As a by-product, we obtain the boundary entropy and A-type boundary central charges in general dimensions. We also study AdS/BCFT for general curvature-squared gravity. We find that it is too restrictive for the shape of the brane and the dual BCFT is trivial if one imposes Neumann boundary conditions for all of the gravitational modes. Instead, we propose to impose Dirichlet boundary condition for the massive graviton, while imposing Neumann boundary condition for the massless graviton. In this way, we obtain non-trivial shape dependence of stress tensor and well-defined central charges. In particular, the holographic g-theorem is satisfied by general curvature-squared gravity. Finally, we discuss the island and show that the Page curve can be recovered for Gauss-Bonnet gravity. Interestingly, there are zeroth-order phase transitions for the Page curve within one range of couplings obeying causality constraints. Generalizing the discussions to holographic entanglement entropy and holographic complexity in AdS/CFT, we get new constraints for the Gauss-Bonnet coupling, which is stronger than the causality constraint.Comment: 49 pages, 29 figures, revision accepted for publication in JHEP, main improvements: prove that our g-function can recover the universal term of boundary entropy in general dimensions; add a toy model to explain the novel zeroth-order phase transition of the Page curve analyticall

Investigating multiscale meteorological controls and impact of soil moisture heterogeneity on radiation fog in complex terrain using semi-idealised simulations

Coupled surface–atmosphere high-resolution mesoscale simulations were carried out to understand meteorological processes involved in the radiation fog life cycle in a city surrounded by complex terrain. The controls of mesoscale meteorology and microscale soil moisture heterogeneity on fog were investigated using case studies for the city of ¯Otautahi / Christchurch, New Zealand. Numerical model simulations from the synop- tic to microscale were carried out using the Weather Research and Forecasting (WRF) model and the Parallelised Large-Eddy Simulation Model (PALM). Heterogeneous soil moisture, land use, and topography were included. The spatial heterogeneity of soil moisture was derived using Landsat 8 satellite imagery and ground-based me- teorological observations. Nine semi-idealised simulations were carried out under identical meteorological conditions. One contained homogeneous soil moisture of about 0.31 m$^3$ m$^{−3}$, with two other simulations of halved and doubled soil moisture to demonstrate the range of soil moisture impact. Another contained heterogeneous soil moisture derived from Landsat 8 imagery. For the other five simulations, the soil moisture heterogeneity magnitudes were amplified following the observed spatial distribution to aid our understanding of the impact of soil moisture heterogeneity. Analysis using pseudo-process diagrams and accumulated latent heat flux shows significant spatial heterogeneity of processes involved in the simulated fog. Our results showed that soil mois- ture heterogeneity did not significantly change the general spatial structure of near-surface fog occurrence, even when the heterogeneity signal was amplified and/or when the soil moisture was halved and doubled. However, compared to homogeneous soil moisture, spatial heterogeneity in soil moisture can lead to changes in fog duration. These changes can be more than 50 min, although they are not directly correlated with spatial variations in soil moisture. The simulations showed that the mesoscale (10 to 200 km) meteorology controls the location of fog occurrence, while soil moisture heterogeneity alters fog duration at the microscale on the order of 100 m to 1 km. Our results highlight the importance of including soil moisture heterogeneity for accurate spatiotemporal fog forecasting

Towards Practical Few-shot Federated NLP

Transformer-based pre-trained models have emerged as the predominant solution for natural language processing (NLP). Fine-tuning such pre-trained models for downstream tasks often requires a considerable amount of labeled private data. In practice, private data is often distributed across heterogeneous mobile devices and may be prohibited from being uploaded. Moreover, well-curated labeled data is often scarce, presenting an additional challenge. To address these challenges, we first introduce a data generator for federated few-shot learning tasks, which encompasses the quantity and skewness of scarce labeled data in a realistic setting. Subsequently, we propose AUG-FedPrompt, a prompt-based federated learning system that exploits abundant unlabeled data for data augmentation. Our experiments indicate that AUG-FedPrompt can perform on par with full-set fine-tuning with a limited amount of labeled data. However, such competitive performance comes at a significant system cost.Comment: EuroSys23 worksho

Structure and seasonal changes in atmospheric boundary layer on coast of the east Antarctic continent

The temperature, humidity, and vertical distribution of ozone in the Antarctic atmospheric boundary layer(ABL) and their seasonal changes are analyzed, by using the high-resolution profile data obtained during the International Polar Year 2008 to 2009 at Zhongshan Station, to further the understanding of the structure and processes of the ABL. The results show that the frequency of the convective boundary layer in the warm season accounts for 84% of its annual occurrence frequency. The frequency of the stable boundary layer in the cold season accounts for 71% of its annual occurrence frequency. A neutral boundary layer appears rarely. The average altitude of the convective boundary layer determined by the parcel method is 600 m; this is 200 to 300 m higher than that over inland Antarctica. The average altitude of the top of the boundary layer determined by the potential temperature gradient and humidity gradient is 1 200 m in the warm season and 1 500 m in the cold season. The vertical structures of ozone and specific humidity in the ABL exhibit obvious seasonal changes. The specific humidity is very high with greater vertical gradient in the warm season and very low with a lesser gradient in the cold season under 2 000 m. The atmospheric ozone in the ABL is consumed by photochemical processes in the warm season, which results in a slight difference in altitude. The sub-highest ozone center is located in the boundary layer, indicating that the ozone transferred from the stratosphere to the troposphere reaches the low boundary layer during October and November in Antarctica

Wrf4palm v1.0: A mesoscale dynamical driver for the microscale PALM model system 6.0

A set of Python-based tools, WRF4PALM, has been developed for offline nesting of the PALM model system 6.0 into the Weather Research and Forecasting (WRF) modelling system. Time-dependent boundary conditions of the atmosphere are critical for accurate representation of microscale meteorological dynamics in high-resolution real-data simulations. WRF4PALM generates initial and boundary conditions from WRF outputs to provide time-varying meteorological forcing for PALM. The WRF model has been used across the atmospheric science community for a broad range of multidisciplinary applications. The PALM model system 6.0 is a turbulence-resolving large-eddy simulation model with an additional Reynolds-averaged Navier–Stokes (RANS) mode for atmospheric and oceanic boundary layer studies at microscale (Maronga et al., 2020). Currently PALM has the capability to ingest output from the regional scale Consortium for Small-scale Modelling (COSMO) atmospheric prediction model. However, COSMO is not an open source model and requires a licence agreement for operational use or academic research (http://www.cosmo-model.org/, last access: 23 April 2021). This paper describes and validates the new free and open-source WRF4PALM tools (available at https://github.com/dongqi-DQ/WRF4PALM, last access: 23 April 2021). Two case studies using WRF4PALM are presented for Christchurch, New Zealand, which demonstrate successful PALM simulations driven by meteorological forcing from WRF outputs. The WRF4PALM tools presented here can potentially be used for micro- and mesoscale studies worldwide, for example in boundary layer studies, air pollution dispersion modelling, wildfire emissions and spread, urban weather forecasting, and agricultural meteorology

Validation of total ozone data between satellite and ground-based measurements at Zhongshan and Syowa stations in Antarctica

We present validation between total ozone from satellite and ground-based observations of the Dobson and Brewer spectrometers and ozone radiosonde at Zhongshan and Syowa Antarctic research stations, for September 2004 to March 2009. Results show that mean bias error between Zhongshan (Syowa) and Ozone Monitor Instrument Total Ozone Mapping Spectrometer (OMI-TOMS) data are −0.06%±3.32% (−0.44%±2.41%); between it and OMI Multi Axis Differential Optical Absorption Spectroscopy (OMI-DOAS) data, the error is −0.34%±4.99% (−0.22%±4.85%). Mean absolute bias error values of OMI-TOMS data are less than those of OMI-DOAS. This means that total ozone of OMI-TOMS is closer to ground-based observation than that of OMI-DOAS. Comparison between direct observational total ozone of ground-based and integrated ozone from the ozone profile measured by ozone radiosonde shows that ozone amount calculated with the Solar Backscatter Ultraviolet (SBUV) method above balloon burst height is similar to corresponding Microwave Limb Sounder (MLS) data. Therefore, MLS data can be substituted with SBUV data to estimate ozone amount above that level. Mean bias error of the MLS ozone column is 2% compared with the ozonesonde column, with standard deviation within 9.5%. Comparison of different layers from ozone profiler and MLS data indicates that at the 215 hPa layer, the MLS ozone value is high, with relative deviation more than 20%. At the 100 hPa and 68 hPa layers, the MLS ozone value is also high. This deviation is mainly in spring, during Antarctic ozone hole appearance. In this period, at the height of severe ozone loss, relative deviation of MLS ozone values is especially large

Structure and seasonal changes in atmospheric boundary layer on coast of the east Antarctic continent

The temperature, humidity, and vertical distribution of ozone in the Antarctic atmospheric boundary layer(ABL) and their seasonal changes are analyzed, by using the high-resolution profile data obtained during the International Polar Year 2008 to 2009 at Zhongshan Station, to further the understanding of the structure and processes of the ABL. The results show that the frequency of the convective boundary layer in the warm season accounts for 84% of its annual occurrence frequency. The frequency of the stable boundary layer in the cold season accounts for 71% of its annual occurrence frequency. A neutral boundary layer appears rarely. The average altitude of the convective boundary layer determined by the parcel method is 600 m; this is 200 to 300 m higher than that over inland Antarctica. The average altitude of the top of the boundary layer determined by the potential temperature gradient and humidity gradient is 1 200 m in the warm season and 1 500 m in the cold season. The vertical structures of ozone and specific humidity in the ABL exhibit obvious seasonal changes. The specific humidity is very high with greater vertical gradient in the warm season and very low with a lesser gradient in the cold season under 2 000 m. The atmospheric ozone in the ABL is consumed by photochemical processes in the warm season, which results in a slight difference in altitude. The sub-highest ozone center is located in the boundary layer, indicating that the ozone transferred from the stratosphere to the troposphere reaches the low boundary layer during October and November in Antarctica