Weather Forecasts Model Output Research Articles

Improving Accuracy of Daily Weather Forecast Model at Soekarno-Hatta Airport Using BILSTM with SMOTE and ADASYN

Bidirectional LSTM (BiLSTM) is an extension of LSTM which can improve model efficiency and accuracy in classification scenarios based on time series data or longer time series data repeatedly. This research uses the BiLSTM algorithm to build a daily weather forecast model at Soekarno-Hatta Airport. The model built will assist forecasters in making weather forecasts on a local scale. This research is expected to be implemented and able to increase the verification value of Soekarno-Hatta Airport weather forecasts to support flight safety in Indonesia. The dataset used is hourly surface air weather parameter data (synoptic data) of Soekarno-Hatta Meteorological Station for the period January 2018 - December 2022. There is an imbalance in the data set, so the SMOTE and ADASYN techniques are used to handle the problem. The output of this research is weather conditions categorised into sunny, sunny cloudy, cloudy, light rain, moderate rain, heavy rain, and thunder rain. The results obtained will go through model verification and evaluation by finding the accuracy value by comparing the weather forecast model output with actual weather data using a multi-category contingency table. The BiLSTM - ADASYN model obtained the highest average accuracy value compared to other models, which was 83.2%.

Response of a high-resolution ocean circulation model to winds from different sources in simulating summer monsoon freshening in the North Bay of Bengal: A case study

A very high-resolution model for the Bay of Bengal is configured to simulate submesoscale flow features, which are otherwise absent in coarse resolution models. In this manuscript, we present the response of this model to simulate summer monsoon freshening in the northern Bay of Bengal when forced with two different winds, one based on weather forecast model output from National Centre for medium range weather forecast (NCMRWF) and the other based on satellite-derived SCATSAT ocean surface winds for 2017 as a case study. Our results reveal that the spatio-temporal evolution of lateral freshwater dispersal in the northern Bay of Bengal is sensitive to wind vorticity and eddy formation/evolution. A reasonably realistic decrease of 2–3 psu in the sea surface salinity at the mooring location of 18oN, 90oE towards the end of September 2017 is simulated in the model when forced with the SCATSAT winds, whereas significantly weaker freshening occurs at the mooring location when the model is forced with the NCMRWF winds. A filament of strong positive vorticity connecting two cyclonic eddies in the north central Bay in the NCMRWF wind forced simulations prevents the direct southward advection of freshwater, resulting in higher salinity at the mooring location. A similar mechanism that would prevent southward advection of fresh water is absent in the SCATSAT forced model run. Westward moving Rossby waves in the SCATSAT forced model run are found to play an important role in the evolution of freshening events at various locations in the northern Bay of Bengal. Lagrangian Coherent Structures (LCS) derived from the model currents suggest that the background conditions were favourable to advect freshwater from Ganges-Brahmaputra towards the mooring location in the northern Bay of Bengal in the SCATSAT forced simulations.

Statistical downscaling of MM5 model output to better assess avalanche threats

AbstractIn this study, we use MM5 weather-forecast model output and observed surface weather data from 11 stations in the western Himalaya to develop a statistical downscaling model (SDM) to better predict precipitation, 10 m wind speed and 2 m temperature. The analysis covers three consecutive winters: 2004/05, 2005/06 and 2006/07. The performance of the SDM was assessed using an independent dataset from the 2007/08 winter season. This assessment shows that the SDM technique substantially improves the forecast over specific station locations, which is important for avalanche-threat assessment.

Verified combination of numerical weather- and avalanche-prediction models at Kootenay Pass, British Columbia, Canada

AbstractThe combination of numerical weather prediction (NWP) and snow avalanche forecasting has been performed using the output of two weather models run at the University of British Columbia, Canada, and a local numerical avalanche-forecasting model developed for Kootenay Pass (McClung and Tweedy, 1994). The main motivations for this work are. (1) to extend the lead time of avalanche forecasts by using NWP forecasts of meteorological variables as input to statistical avalanche-threat models (instead of the traditional method of using current/past observed meteorological variables as input); and (2) to create another tool to help avalanche forecasters in their daily decision-making by making true forecasts instead of “nowcasts”. Therefore, verified weather-forecast model output was used as input for the local avalanche-forecasting model at Kootenay Pass. The resulting 24 hour avalanche forecast was compared to observed avalanche occurrences and to the 12 hour avalanche forecast with current weather observations. As a result, the avalanche-model output for the test runs with numerically predicted weather data is comparable in accuracy to the runs with observed weather data. The results also suggest that avalanches may be predicted statistically for 24 hours into the future when high-resolution NWP is used as input, weather- and avalanche-forecast errors taken into account during operational use.

High-resolution forest fire weather index computations using satellite remote sensing

Wildfires are important in regions dominated by forest, such as found in large parts of Canada. The principal objective of this study was to provide homogeneously distributed indices for the Canadian Fire Weather Index (FWI) System. The FWI was calculated using four sets of input variables: meteorological station measurements (OBS); weather forecast model output (SIM); meteorological station measurements and remote sensing estimations combined (SAT1); and weather forecast model output and remote sensing estimations combined (SAT2). Remote sensing parameterization of air temperature and relative humidity was performed. The air temperature and relative humidity reproduced showed good agreement with ground-based measurements (R2 = 0.77 and SE = 1.48°C; R2 = 0.73 and SE = 5%, respectively). For the FWI regionalized using this requirement, category SAT1 showed the best fit. Category SAT2 produced more precise results (0.09 to 2.19% of the normalized root mean square error) versus SIM.

Surface salinity budget in oceanic simulation using data from TOGA COARE

A three‐dimensional regional model is used to investigate the role of different terms of the salinity budget in the western Pacific during TOGA COARE. The model is a version of the ocean general circulation model (OGCM) developed at the Laboratoire d'Océanographie Dynamique et de Climatologie (LODYC) in Paris and includes open lateral boundaries and a 1.5‐level‐order turbulence closure scheme. The surface atmospheric forcing used, including water flux, comes from a combination of European Center for Medium‐Range Weather Forecasts model output and estimates from bulk parameterization. The data set collected during the Intensive Observation Period enables the initialization, taking into account the lateral boundary conditions, and validating the model outputs. Different atmospheric weather conditions were experienced during the simulation of the variability of the mixed layer. During 25 days, air‐sea fluxes were downward, that is precipitation exceeds evaporation, and increasing with time. In periods of weak winds (December 2–12), strong solar radiation, and shoaling of the oceanic mixed layer, the entrainment is negative and salt is removed from the oceanic mixed layer. Mixed layer currents are low and slightly divergent from the equator toward the south with a mean eastward component. Due to the zonal advection, there is a freshening tendency in the north of the domain. In periods of strong winds (December 21–27) and reduced solar radiation, the oceanic mixed layer is deepening and entrainment is positive and contributes to the salinity increase. The salinity storage term is quite inhomogeneous during the two periods as a consequence of the patchy pattern of advection. Moreover, most of its temporal and spatial variability is strongly correlated with the temporal and spatial variability of the advection term. Currents are largely converging toward the equator and create a band of saltier water in the surface layer.

Surface heat budget in an oceanic simulation using data from Tropical Ocean‐Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment

A three‐dimensional regional ocean model is used to investigate the response of the upper ocean to different atmospheric weather events encountered during the Tropical Ocean‐Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment (COARE). The basic model is a version of the ocean general circulation model developed at the Laboratoire d'Océanographie Dynamique et de Climatologie in Paris and includes open lateral boundaries and a 1.5 level order turbulence closure scheme. The horizontal grid spacing is 0.1° in longitude and 0.08° in latitude. There are 29 vertical levels, with a resolution of 5 m near the top. The surface atmospheric forcing used comes from a combination of European Centre for Medium‐Range Weather Forecasts model output and estimates from bulk parameterization. The data set collected during the Intensive Observation Period enables a detailed initialization of the model. The analyses of the model output show that most features are in good agreement with the observations. During westerly wind bursts the mixed layer heat budget is negative (−83 W m−2) over a larger part of the COARE domain mainly because of the strong latent heat flux and weak solar radiation. Strong inhomogeneities due to local importance of horizontal advection contrast with relative homogeneous net heat flux. In this period all terms of the heat balance are active in the oceanic mixing layer. During the calm period the budget is weakly positive (15 W m−2) but still remains patchy because of the contribution of horizontal advection.

Monthly Evapotranspiration from Satellite and Conventional Meteorological Observations

Monthly mean satellite measurements of surface heating rate, surface temperature, and normalized difference vegetation index were collected for seven locations in Kansas. These were combined with monthly average surface observations and used in a surface energy balance model to estimate monthly mean evapotranspiration at each site. The modeled evapotranspiration and surface energy fluxes are reasonable. The nature of the surface energy balance model is such that it can be solved with satellite measurements and numerical weather forecast model output alone. This suggests that large-scale evapotranspiration climatologies can be made without in situ observations.