Operational Global Model Research Articles

Validation of OceanSat-3 sea surface winds for their utilization in the NCMRWF NWP assimilation systems

The Indian Space Research Organization (ISRO) launched OceanSat-3, the third-generation satellite in the OceanSat series, carrying a Ku-band scatterometer in November 2022. The novelty of the OceanSat-3 scatterometer (OSCAT-3) is its high-resolution sea surface wind products generated at 12.5 km in addition to 25 km. This study aims to check the quality of OSCAT-3 winds for their possible assimilation in the National Centre for Medium Range Weather Forecasting (NCMRWF) operational Numerical Weather Prediction (NWP) models. The newly available high-resolution OSCAT-3 wind products are validated against in-situ buoy winds and NCMRWF NWP model equivalents for six months from July to December 2023. The validation results of OSCAT-3 winds are also compared with those of the Advanced Scatterometer (ASCAT) onboard the Meteorological Operational Satellite-C (MetOp-C) using the same method. Validation of OSCAT-3 winds against buoy winds shows that the Root Mean Square Errors (RMSEs) in wind speed (direction) is less than 2 m/s (15°) over the Tropics (20° N − 20° S) and slightly higher than 2 m/s (20°) over the Northern Hemisphere (20° N − 90° N), which is closer to the satellite’s mission specifications of 1.8 m/s and 20°. The RMSE in the wind speed/direction in both the scatterometer winds are less than 2 m/s (20°) over the three different geographical regions: the Tropics, Northern Hemisphere, and Southern Hemisphere, but with lower errors for ASCAT winds. The better agreement of ASCAT winds with the NWP equivalents can be attributed partially to the routine assimilation of ASCAT winds in the NCMRWF operational NWP models and also due to the frequency of operation, C-band compared to the OSCAT-3 operated in the Ku band. Since there are three distinct datasets, scatterometer winds, buoy winds, and the NWP equivalents, triple collocation is also carried out in this study. Triple collocation also shows that the errors in OSCAT-3 winds are within the mission goal. The findings from this study indicate that the OSCAT-3 vector winds are of similar quality as its predecessors (OSCAT-2 and SCATSAT-1) and can be assimilated operationally in the NCMRWF NWP models as well as in other global operational NWP models.

The Met Office Forecast Ocean Assimilation Model (FOAM) using a 1/12‐degree grid for global forecasts

AbstractThe Met Office Forecast Ocean Assimilation Model (FOAM) ocean–sea‐ice analysis and forecasting operational system has been using an ORCA tripolar grid with 1/4° horizontal grid spacing since December 2008. Surface boundary forcing is provided by numerical weather prediction fields from the operational global atmosphere Met Office Unified Model. We present results from a 2‐year simulation using a 1/12° global ocean–sea‐ice model configuration while keeping a 1/4° data assimilation (DA) set‐up. We also describe recent operational data assimilation enhancements that are included in our 1/4° control and 1/12° simulations: a new bias‐correction term for sea‐level anomaly assimilation and a revised pressure correction algorithm. The primary effect of the first is to decrease the mean and variability of sea‐level anomaly increments at high latitudes, whereas the second significantly reduces the vertical velocity standard deviation in the tropical Pacific. The level of improvement achieved with the higher resolution configuration is moderate but consistently satisfactory when measured using neighbourhood verification metrics that provide fairer quantitative comparisons between gridded model fields at different spatial resolutions than traditional root‐mean‐square metrics. A comparison of the eddy kinetic energy from each configuration and an observation‐based product highlights the regions where further system developments are most needed.

Ocean waves in the southwestern Atlantic Ocean: An evaluation of global wave models

AbstractIn situ wave observations are essential for implementing coastal management strategies, designing coastal and offshore structures and understanding many processes related to sedimentology and marine biology. Despite their importance, these observations are rather scarce in the coastal areas of southeastern South America. Moreover, the existing observations are discontinuous, with several gaps and no simultaneity. Today, global wave models have improved their performance by providing reliable wave parameters with high resolution and coverage even at near‐shore areas. In this work, wave parameters from five global models were compared with significant wave heights (HS), peak periods (T) and propagation direction at nine sites located at the Southwestern South Atlantic Ocean. The global products used were WAVERYS (Global Reanalysis Wav 001 032), IOWAGA (WAVEWATCH III Hindcast – WW3 – Global grid – CFSR), ERA5 (ECMWF reanalysis), NOAA WW3 – 30‐year Hindcast Phase 2 and NCEP/EMC Operational global wave model GFS – Wave. Mean arithmetic error (Bias), root mean square deviation, scatter index and the Pearson linear correlation coefficient (r) were assessed at each location where wave observations were available. The best agreements for HS were obtained at the deepest sites located farther from the coast. Lower statistical metrics were achieved at coastal sites where the bathymetry is roughly represented by the global models. The calculated correlation coefficients were found to be lower for T than for HS. Overall, T was slightly underestimated by global models. Wave propagation directions were excellently represented by global models at offshore sites. The WAVERYS model is the global product that best represents the wave parameters in the study area, probably due to its higher spatial resolution (0.2°) and more realistic atmospheric forcing (ERA5). In addition, it satisfactorily represents the temporal variability of HS in open water as well as swell characteristics at the outer the Río de la Plata.

Intercomparison of tropospheric and stratospheric mesoscale kinetic energy resolved by the high‐resolution global reanalysis datasets

AbstractWith the development of advanced data assimilation and computing techniques, many modern global reanalysis datasets aim to resolve the atmospheric mesoscale spectrum. However, large uncertainties remain with respect to the representation of mesoscale motions in these reanalysis datasets, for which a clear understanding is lacking. The aforementioned challenges have served as a strong motivation to reveal and quantify their mesoscale differences. This study presents the first comprehensive global intercomparison of the tropospheric and stratospheric mesoscale kinetic energy and its spectra over two selected periods of summer and winter events among six leading high‐resolution atmospheric reanalysis products: European Centre for Medium‐Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), China Meteorological Administration Reanalysis, Modern‐Era Retrospective Analysis for Research and Applications version 2, National Centers for Environmental Prediction's Climate Forecast System version 2 (CFSv2), Japanese 55‐year Reanalysis, and ECMWF Reanalysis‐Interim. A state‐of‐the‐art global operational model is adopted as a supplementary reference. Although all reanalysis datasets can reproduce broad distribution characteristics that are grossly consistent with the 9 km model, there are substantial discrepancies among them in magnitudes. The ability to capture mesoscale signals is closely linked to their resolutions, but it is also impacted by other factors, including, but not limited to, the selected types of energy, seasons, altitudes, latitudes, model diffusions, parametrization schemes, moist condition, assimilation methods, and observation inputs. Moreover, all datasets illustrate conclusive behaviors for the prevalence of the rotational component in the troposphere, whereas only very few products fail to exhibit the dominance of the divergent component in the stratosphere. Overall, stratospheric ERA5 and CFSv2 outperform the other reanalysis datasets, and only these two can reproduce the feature of the canonical kinetic energy spectrum with a distinct shift from a steeper slope (approximately −3) at lower wave numbers to a shallower slope (approximately −5/3) at higher wave numbers. In addition, the relative disparities among datasets increase dramatically with height, and they are more pronounced in the divergent component. It is also found that the correlations among these datasets are much weaker in the Tropics.

Atmospheric kinetic energy spectra from global and regional NCMRWF unified modelling system

AbstractCharacteristics of the atmospheric kinetic energy (KE) spectrum follow a distinct power‐law dependence in the synoptic (k−3) and mesoscales (k−5/3), where k is the horizontal wave‐number. The representation of this canonical spectral behaviour provides a testimony of the acceptability of the design, configuration and performance of a numerical weather prediction (NWP) model. Therefore, the characteristics of the KE spectrum are studied using an operational version of the high‐resolution National Centre for Medium Range Weather Forecasting (NCMRWF) Unified Model (NCUM) system considering both global (∼12 km mesh) and regional (∼4 km mesh) configurations during the northern hemispheric summer period (June–August 2020). The synoptic‐scale spectral characteristics of the NCUM global (NCUM‐G) model match well with the observed spectrum in the tropics, midlatitudes and polar regions. However, the regional NCUM model (NCUM‐R) outperforms the NCUM‐G in representing the canonical slope at mesoscales. As the NCMRWF is accelerating towards a high‐resolution 6 km global (NCUM‐G6) operational model, the spectral characteristics from NCUM‐G6 are also studied during the monsoon period. Though the representation of the mesoscale spectrum is better in NCUM‐G6 relative to NCUM‐G, the regional model surpasses both the global models while demonstrating the mesoscale characteristics close to the observed spectral slopes. Further, the mesoscale spectrum deviates gradually from the Lindborg (1999) analytical fit in the mesoscales around 20Δx (where Δx ∼ 4 km), which specifies an effective resolution of the regional model. Hence, the regional model needs refinements optimally to further reduce the energy dissipation at high wave‐numbers to improve the mesoscale features at the limits of its grid resolution.

A Study on the Influence of Air Pollution on Temperature Forecast Skill Based on Operational Weather Forecast in BTH Region

Surface air temperature is a comprehensive function of aerosols in the atmosphere and various weather factors. However, there is no real-time aerosol concentration feedback in most operational numerical weather prediction (NWP) models. This raises a scientific question of how abnormal changes in air pollutants in a short period of time will affect the temperature prediction skill of NWP models. Thus, the study was carried out to investigate the possible influence of air pollution on the temperature forecast skill based on the operational NWP model over the Beijing–Tianjin–Hebei (BTH) region during January–February 2020. The results show that the average concentrations of PM2.5, SO2, NO2 and CO over the BTH region in February were smaller than those in January by 38.5%, 35.1%, 48.0% and 33.1%, respectively. Simultaneously, the forecast skills for surface temperature in February from both regional (RMAPS, Rapid-refresh Multi-scale Analysis and Prediction System) and global (ECMWF, European Centre for Medium-Range Weather Forecasts) operational NWP models improved markedly compared with that in January. In both models, the underestimation of maximum temperature and the overestimation of minimum temperature in most cities over the BTH region in February were significantly reduced. With the 24 h (24 h) forecast lead time, the RMSE (root mean square error) of BTH daily mean, maximum and minimum temperature prediction in February based on RMAPS were 17.3%, 9.8% and 21.6% lower than that in January, respectively. These are generally consistent with the other statistical indices such as deviation and regression coefficient. As the forecast lead time extended to 48 h and 72 h forecast, the phenomena still existed and were also evident in the ECMWF model. The improvement of temperature forecast skill of NWP models may be attributed to the unexpected dramatical reduction of air pollutants. Less aerosols during the daytime allow more solar radiation reaching the surface and cause a warming in the near-surface temperature, while less aerosols during the nighttime favor the outgoing long-wave radiation and then lead to a cooling near the ground.

Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact

Abstract. In operational flood forecast systems, the effect of sea ice is typically neglected or parameterized solely in terms of ice concentration. In this study, an efficient way of adding ice effects to the global total water level prediction systems, via the ice–ocean stress, is described and evaluated. The approach features a novel, consistent representation of the tidal relative ice–ocean velocities, based on a transfer function derived from ice and ocean tidal ellipses given by an external ice–ocean model. The approach and its impact are demonstrated over four ice seasons in the Northern Hemisphere, using in situ observations and model predictions. We show that adding ice effects helps the model reproduce most of the observed seasonal modulations in tides (up to 40 % in amplitude and 50∘ in phase for M2) in the Arctic and Hudson Bay. The dominant driving mechanism for the seasonal modulations is shown to be the under-ice friction, acting in areas of shallow water (less than 100 m) and its accompanied large shifts in the amphidromes (up to 125 km). Important contributions from baroclinicity and tide–surge interaction due to ice–ocean stress are also found in the Arctic. Both mechanisms generally reinforce the seasonal modulations induced by the under-ice friction. In forecast systems that neglect or rely on simple ice concentration parameterizations, storm surges tend to be overestimated. With the inclusion of ice–ocean stress, surfaces stresses are significantly reduced (up to 100 % in landfast ice areas). Over the four ice seasons covered by this study, corrections up to 1.0 m to the overestimation of surges are achieved. Remaining limitations regarding the overestimated amphidrome shifts and insufficient ice break-up during large storms are discussed. Finally, the anticipated trend of increasing risk of coastal flooding in the Arctic, associated with decreasing ice and its profound impact on tides and storm surges, is briefly discussed.

Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model

An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlight the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).

DHI-GHM: Real-time and forecasted hydrology for the entire planet

An operational global hydrological model (DHI-GHM) has been developed that provides historical, real-time, 10-day and seasonal forecast simulations at the global scale. DHI-GHM is comprised of a distributed gridded rainfall-runoff model with a spatial resolution of 0.1° and an agile kinematic routing model that moves water between model grid cells and sub-catchments and in the river system. Model output includes gridded hydrological variables, such as soil moisture content and different runoff components, and discharge at more than 1 million river points globally. DHI-GHM uses a novel parameterization scheme, where global data products of land surface physical characteristics are used to establish relations with model parameters, and thus DHI-GHM does not rely on local discharge data for model calibration. Multiple forcing datasets were tested, and the combination of ERA5 precipitation and Priestley-Taylor potential evaporation yielded the overall best results with a median KGE of 0.51 and average water balance error of 0.78% based on data from 1667 discharge stations worldwide. The model results and the operational system are particularly relevant for organizations with national, regional, or global scope who need information on large areas at once and for data scarce areas or projects without resources for local scale models.

Operation optimization of a refrigeration ventilation system for the deep metal mine

With the increment of the depth of metal mines, the energy conservation of refrigeration ventilation for deep metal mines has attracted more attention. This study uses the heat current method and artificial neural network to model the refrigeration ventilation system of deep metal mines, and establishes the systematic flow constraints using the driving-drag balance relationship. A global operational optimization model is built using a Lagrange multiplier method to minimize the pumping power consumption. An iterative algorithm combined with the stope model is proposed by coupling the water outlet temperature of the evaporator and condenser. Subsequently, the optimal frequency of the variable frequency pumps is obtained. The operation of the optimal data on the experimental platform showed that the pumping power consumption of the cooling tower loop decreased the most by 72.84%, and the total energy consumption of system decreased by 25.79%. Additionally, the influences of the inlet air temperature of the air cooler, fan frequency, and inlet air temperature of the cooling tower on the system power consumption are analyzed and provides guidance on energy saving and consumption reduction for refrigeration ventilation systems in deep metal mines.

Global Distributions of Tropospheric and Stratospheric Gravity Wave Momentum Fluxes Resolved by the 9-km ECMWF Experiments

Abstract Based on 20-day control forecasts by the 9-km Integrated Forecasting System (IFS) at the European Centre for Medium-Range Weather Forecasts (ECMWF) for selected periods of summer and winter events, this study investigates global distributions of gravity wave momentum fluxes resolved by the highest-resolution-ever global operational numerical weather prediction model. Two supplementary datasets, including 18-km ECMWF IFS experiments and the 30-km ERA5, are included for comparison. In the stratosphere, there is a clear dominance of westward momentum fluxes over the winter extratropics with strong baroclinic instability, while eastward momentum fluxes are found in the summer tropics. However, meridional momentum fluxes, locally as important as the above zonal counterpart, show different behaviors of global distribution characteristics, with northward and southward momentum fluxes alternating with each other especially at lower altitudes. Both events illustrate conclusive evidence that stronger stratospheric fluxes are found in the ECMWF forecast with finer resolution, and that ERA5 datasets have the weakest signals in general, regardless of whether regridding is applied. In the troposphere, probability distributions of vertical motion perturbations are highly asymmetric with more strong positive signals especially over latitudes covering heavy rainfall, likely caused by convective forcing. With the aid of precipitation accumulation, a simple filtering method is proposed in an attempt to eliminate those tropospheric asymmetries by convective forcing, before calculating tropospheric wave-induced fluxes. Furthermore, this research demonstrates promising findings that the proposed filtering method could help in reducing the potential uncertainties with respect to estimating tropospheric wave-induced fluxes. Finally, absolute momentum flux distributions with proposed approaches are presented, for further assessment in the future.

Changes in Arctic Halocline Waters Along the East Siberian Slope and in the Makarov Basin From 2007 to 2020

AbstractThe evolution of halocline waters in the Makarov Basin and along the East Siberian continental slope is examined by combining drifting platform observations, shipborne hydrographic data, and simulations from a global operational physical model from 2007 to 2020. From 2012 onwards, relatively shallow and cold Atlantic‐derived lower halocline waters, previously restricted to the Lomonosov Ridge area, progressed eastward along the East Siberian continental slope. Their eastward extent abruptly shifted from 155°E to 170°E in early 2012, stabilized at 170°E until the end of 2015, then gradually advanced to reach the western Chukchi Sea in 2017. Such eastward progression led to a strengthening of the associated boundary current and to the shedding of mesoscale eddies of cold Atlantic‐derived waters into the lower halocline of the Makarov Basin in September 2015 and near the East Siberian continental slope in November 2017. Additionally, active mixing between upwelled Atlantic Water and shelf water formed dense warm water supplying the Makarov Basin lower halocline. The increasing contribution from Atlantic‐derived waters into the lower halocline along the East Siberian continental slope and in the Makarov Basin led to a weakening of the halocline, which is characteristic of a new Arctic Ocean regime that started in the early 2000s in the Eurasian Basin. Our results suggest that this new Arctic regime may now extend toward the Amerasian Basin.

Skill of Medium-Range Forecast Models Using the Same Initial Conditions

Abstract In the Different Models, Same Initial Conditions (DIMOSIC) project, forecasts from different global medium-range forecast models have been created based on the same initial conditions. The dataset consists of 10-day deterministic forecasts from seven models and includes 122 forecast dates spanning one calendar year. All forecasts are initialized from the same ECMWF operational analyses to minimize the differences due to initialization. The models are run at or near their respective operational resolutions to explore similarities and differences between operational global forecast models. The main aims of this study are 1) to evaluate the forecast skill and how it depends on model formulation, 2) to assess systematic differences and errors at short lead times, 3) to compare multimodel ensemble spread to model uncertainty schemes, and 4) to identify models that generate similar solutions. Our results show that all models in this study are capable of producing high-quality forecasts given a high-quality analysis. But at the same time, we find a large variety in model biases, both in terms of temperature errors and precipitation. We are able to identify models whose forecasts are more similar to each other than they are to those of other systems, due to the use of similar model physics packages. However, in terms of multimodel ensemble spread, our results also demonstrate that forecast sensitivities to different model formulations still are substantial. We therefore believe that the diversity in model design that stems from parallel development efforts at global modeling centers around the world remains valuable for future progress in the numerical weather prediction community.

Adding baroclinicity to a global operational model for forecasting total water level: Approach and impact

Operational flood forecast systems are typically based on barotropic models in order to limit computational cost. In this study, a computationally efficient way of adding spatial and temporal variations of water density (henceforth “adding baroclinicity”) to a global barotropic forecast system is described and evaluated. The approach is illustrated using a global high-resolution (1/12°) model with an optimized vertical grid of nine ocean levels. Temperature (T) and salinity (S) for each layer are weakly nudged to forecast fields provided by a coarser resolution (1/4°), data-assimilative ocean model. This adds realistic baroclinic variability with periods exceeding about 15 d to the 1/12° model while allowing the higher frequency variability to evolve freely. The computational cost of running the new model is only 10% higher than the cost of running the two-dimensional barotropic version of the model that forms the basis of the present total water level (TWL) forecast system. The value of adding baroclinicity is demonstrated across the sea level frequency spectrum using hourly observations of TWL made between October 20, 2019 and February 28, 2021 by a global distribution of 211 tide gauges. Large improvements in the tidal residuals (TWL-tide) are shown for periods exceeding 15 d. This is consistent with the known importance of baroclinic processes to sea level variability in this frequency range. For periods between 10 h and 15 d, baroclinicity also improves the predictions of extreme residuals by up to 15 cm, with the largest improvements occurring on narrow shelves. In terms of extremes, adding baroclinicity improves predictions of the three largest positive tidal residuals for 2020 at 89% of the tide gauges with the largest improvements reaching 42 cm. Similar results were found for the three largest negative residuals for each tide gauge record. The importance of modeling baroclinically-modified coastal trapped waves is illustrated for the west coast of North and South America.

A global 30-m ET model (HSEB) using harmonized Landsat and Sentinel-2, MODIS and VIIRS: Comparison to ECOSTRESS ET and LST

Advances in earth observation science in recent years have contributed to improving the quantification of evapotranspiration (ET) at field, regional and global scales. Many studies have stressed the need for a high temporal and spatial resolution ET product that minimizes the bias between modeled and actual water use for proper water accounting. We present a hybrid single-source energy balance (HSEB) model that calculates evapotranspiration at the field-scale based on the synergistic use of Sentinel-2, Landsat, Visible Infrared Imaging Radiometer Suite (VIIRS) and (Moderate Resolution Imaging Spectroradiometer) MODIS land surface temperature products. The model operates in Google Earth Engine as a time series using global atmospheric variables and 100-m Copernicus Land cover data. Evaluation of HSEB for calculating evaporation over 29 flux tower sites within an extensive range of climatic conditions and biomes over the US, Europe and Australia for 2018–2020 shows that the model significantly improves the temporal and spatial components of ET mapping. Overall, HSEB performed well in all considered biome types and climatic conditions (r = 0.81, 0.74, and 0.8, a Nash-Sutcliff efficiency of 0.6, 0.74, 0.8, and a bias of 4%, 1%, and − 0.9% at the daily, weekly, and monthly scales, respectively). Root Mean Square Error averaged at 1.31 mm/day. Comparison of instantaneous latent heat fluxes of the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) against tower data shows that HSEB produces acceptable results, although ECOSTRESS had a slightly lower bias (3.8% for HSEB vs. -0.8% for ECOSTRESS). HSEB performed better over croplands. We also discuss comparisons of sharpened LST from VIIRS VNP02, VNP21, MODIS, Landsat, Sentinel-3, and LST from ECOSTRESS versus ground LST measurements, and briefly discuss the sensitivity of HSEB to the thermal data used. Both ECOSTRESS and Landsat showed better performance at different LST ranges and time of day when compared to LST observation collected over a small potato field in Lebanon. The analysis of impact of LST product used in HSEB on ET results at US-ARM site showed that HSEB with MODIS LST outperforms HSEB ET from VNP02 (an overestimate) and VNP21 (an underestimate). We conclude that HSEB can be used as an operational global model for monitoring evaporative stress and evaporation at the small-agriculture field level with higher temporal and spatial resolution utilizing the wide suite of available satellite data.

Influence of the Madden–Julian Oscillation on the Arctic Oscillation Prediction in S2S Operational Models

The connections between the Madden–Julian Oscillation (MJO) and the Arctic Oscillation (AO) are examined in both observations and model forecasts. In the observations, the time-lag composites are carried out for AO indices and anomalies of 1,000-hPa geopotential height after an active or inactive initial MJO. The results show that when the AO is in its positive (negative) phase at the initial time, the AO activity is generally enhanced (weakened) after an active MJO. Reforecast data of the 11 operational global circulation models from the Sub-seasonal to Seasonal (S2S) Prediction Project are further used to examine the relationship between MJO activity and AO prediction. When the AO is in its positive phase on the initial day of the S2S prediction, an initial active MJO can generally improve the AO prediction skill in most of the models. This is consistent with results found in the observations that a leading MJO can enhance the AO activity. However, when the AO is in its negative phase, the relationship between the MJO and AO prediction is not consistent among the 11 models. Only a few S2S models provide results that agree with the observations. Furthermore, the S2S prediction skill of the AO is examined in different MJO phases. There is a significantly positive relationship between the MJO-related AO activity and the AO prediction skill. When the AO activity is strong (weak) in an MJO phase, including the inactive MJO, the models tend to have a high (low) AO prediction skill. For example, no matter what phase the initial AO is in, the AO prediction skill is generally high in MJO phase 7, in which the AO activity is generally strong. Thus, the MJO is an important predictability source for the AO forecast in the S2S models.

Improving Numerical Weather Prediction–Based Near-Cloud Aviation Turbulence Forecasts by Diagnosing Convective Gravity Wave Breaking

AbstractBased on a convective gravity wave drag parameterization scheme in a numerical weather prediction (NWP) model, previously proposed near-cloud turbulence (NCT) diagnostics for better detecting turbulence near convection are tested and evaluated by using global in situ flight data and outputs from the operational global NWP model of the Korea Meteorological Administration for one year (from December 2016 to November 2017). For comparison, 11 widely used clear air turbulence (CAT) diagnostics currently used in operational NWP-based aviation turbulence forecasting systems are separately computed. For selected cases, NCT diagnostics predict more accurately localized turbulence events over convective regions with better intensity, which is clearly distinguished from the turbulence areas diagnosed by conventional CAT diagnostics that they mostly failed to forecast with broad areas and low magnitudes. Although overall performance of NCT diagnostics for one whole year is lower than conventional CAT diagnostics due to the fact that NCT diagnostics exclusively focus on the isolated NCT events, adding the NCT diagnostics to CAT diagnostics improves the performance of aviation turbulence forecasting. Especially in the summertime, performance in terms of an area under the curve (AUC) based on probability of detection statistics is the best (AUC = 0.837 with a 4% increase, compared to conventional CAT forecasts) when the mean of all CAT and NCT diagnostics is used, while performance in terms of root-mean-square error is the best when the maximum among combined CAT and single NCT diagnostic is used. This implies that including NCT diagnostics to currently used NWP-based aviation turbulence forecasting systems should be beneficial for safety of air travel.

Spatial and temporal variations in near‐surface energy fluxes in an Alpine valley under synoptically undisturbed and clear‐sky conditions

AbstractDiurnal cycles of turbulent sensible and latent heat fluxes are typically closely related to the diurnal cycles of solar irradiation under synoptically undisturbed and clear‐sky conditions. In mountainous terrain, large variations can occur in the topographic and surface properties, which modify the local radiation budget and thus turbulent energy fluxes and the surface energy balance. Another characteristic of mountainous terrain is local, thermally driven circulation systems, such as the slope‐ and valley‐wind system, which can equally affect turbulent exchange. Observations of near‐surface radiative and turbulent fluxes are presented from six eddy‐covariance stations in an approximately east–west‐oriented major Alpine valley for undisturbed and clear‐sky conditions. Median diurnal cycles over the whole year are compared at the six sites and related to local terrain characteristics and the thermally driven wind systems. At a scale that is smaller than grid cells in current operational global forecast models, heat, moisture, and momentum fluxes show a large spatial variability in the magnitudes and their diurnal cycles. Lowest heat fluxes are observed on the north‐facing sidewall, where solar irradiation and thus available energy are reduced compared with the valley floor and south‐facing sidewall. Differences in the land surface characteristics further affect the partitioning of the available energy into sensible and latent heat fluxes. The median sensible heat flux reaches its daily peak already before solar noon at several sites, which appears to be related to the transition from down‐valley to up‐valley winds. In contrast to flat and homogeneous terrain, horizontal heat fluxes and lateral momentum fluxes can reach magnitudes that are similar to the magnitudes of vertical heat fluxes and longitudinal momentum fluxes, respectively.

On the Generation of Daily Gridded Ocean Surface Vector Wind Products From Scatsat-1

An optimal interpolation (OI)-based technique is utilized to generate global daily gridded wind products from Scatsat-1 data. The first guess (i.e., background) for the OI is used from the analyses of National Centre for Medium Range Weather Forecasting (NCMRWF) global operational model. The generated gridded products are subsequently validated using observations from global moored buoys and surface winds analyses from European Centre for Medium-Range Weather Forecasts (ECMWF), and that shows a root mean square error of ~1.3 m/s in wind speed and ~19° in wind direction. Along with the gridded winds, several wind-dependent products (e.g., wind stress, wind divergence, wind stress curl, sensible and latent heat flux, etc.) are also generated. The gridded products from Scatsat-1 are available freely from Meteorological and Oceanographic Satellite Data Archival Center ( <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">http://www.mosdac.gov.in</uri> ) since October 03, 2016.

Anatomy of Subinertial Waves Along the Patagonian Shelf Break in a 1/12° Global Operational Model

AbstractThe Patagonian slope hosts a variety of waves. We used a state‐of‐the‐art ocean reanalysis to examine waves at the shelf break and in the core of the Malvinas Current (MC) at periods larger than 10 days. Statistics over 25 years indicated three types of signals: in phase signals at specific locations of the shelf break to the south of 47°S; fast propagating signals all along the shelf break (phase speed from 140 to 300 cm/s) at periods between 5 and 110 days; and slower signals in the core of the MC (phase speeds from 10 to 30 cm/s) at 20‐day, 60‐day, and 100‐day periods. The large zonal wind stress variations south of 47°S forced in‐phase along‐slope velocity variations and triggered fast propagating waves at distinct sites corresponding to abrupt changes in the shelf‐break orientation. The shelf‐break waves modulated the intensity of the inshore jet, which varied from 0 to 30 cm/s at 100 m depth, and had spatial and temporal structures and scales consistent with those of observed upwelling events. Slow propagating waves in the core of the MC had along‐slope wavelengths between 450 and 1,200 km and were not forced by the local winds. They were tracked back to the Drake Passage and the Malvinas Escarpment.