European Centre For Medium-Range Weather Forecasts Integrated Forecasting System Research Articles

A new implementation of FLEXPART with Enviro-HIRLAM meteorological input, and a case study during a heavy air pollution event

ABSTRACT We integrated Enviro-HIRLAM (Environment-High Resolution Limited Area Model) meteorological output into FLEXPART (FLEXible PARTicle dispersion model). A FLEXPART simulation requires meteorological input from a numerical weather prediction (NWP) model. The publicly available version of FLEXPART can utilize either ECMWF (European Centre for Medium-range Weather Forecasts) Integrated Forecast System (IFS) forecast or reanalysis NWP data, or NCEP (U.S. National Center for Environmental Prediction) Global Forecast System (GFS) forecast or reanalysis NWP data. The primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological fields. We compared backward trajectories generated with FLEXPART using Enviro-HIRLAM (both with and without aerosol effects) to trajectories generated using NCEP GFS and ECMWF IFS meteorological inputs, for a case study of a heavy haze event which occurred in Beijing, China in November 2018. We found that results from FLEXPART were considerably different when using different meteorological inputs. When aerosol effects were included in the NWP, there was a small but noticeable difference in calculated trajectories. Moreover, when looking at potential emission sensitivity instead of simply expressing trajectories as lines, additional information, which may have been missed when looking only at trajectories as lines, can be inferred.

Deep learning‐based postprocessing for hourly temperature forecasting

AbstractIn this article, a prediction model based on spatiotemporal stacked ResNet (Res‐STS) for hourly temperature prediction is designed. On the timescale, the Res‐STS removes the gate structure of the long short‐term memory (LSTM) model, and the data of multiple consecutive time nodes are stacked together to preserve all temporal characteristics of the data. A point‐to‐point data mapping relationship is developed on the spatial scale to maximize the impact of large‐scale environmental background field characteristics on a single grid point. Based on the historical gridded data from the China Meteorological Administration land data assimilation system (CLDAS) and the optimal factor dataset of the European Centre for Medium‐Range Weather Forecasts Integrated Forecasting System (ECMWF‐IFS) from 2017 to 2020, hourly temperature prediction models based on convolutional long short‐term memory (ConvLSTM) and Res‐STS model are developed, respectively. Furthermore, the prediction results of the two models in 2021 are compared with the ECMWF‐IFS. The results show that the root mean square error (RMSE) of the prediction results by ConvLSTM and Res‐STS models are both smaller than that of ECMWF‐IFS. Specially, the Res‐STS model performs best: it reduces the RMSE by 20.8% (24.5%) compared with the ConvLSTM (ECMWF‐IFS). Specifically, the RMSE peaks in the afternoon when the daily maximum temperature occurs, while it is relatively smaller at night. Res‐STS demonstrates a significant improvement in forecast performance compared with ECMWF‐IFS, while ConvLSTM's correction during the period of maximum temperature occurrence has been enhanced. Moreover, the forecast performance of the Res‐STS model is least affected by terrain compared with those of the ConvLSTM and ECMWF‐IFS. For the regions with terrain height greater than 1 km, the model Res‐STS evidently improves the RMSE.

Evaluation of Western North Pacific Typhoon Track Forecasts in Global and Regional Models during the 2021 Typhoon Season

The track forecasts of tropical cyclones (TC) in the western North Pacific (WNP) basin during 2021 typhoon season with five global models and four regional models are evaluated here. The results show that the average direct position errors (DPEs) of the global and regional models are approximately 80, 150, 200, 300, and 400 km at 24 h, 48 h, 72 h, 96 h, and 120 h lead-times, respectively. The European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) achieved the best track forecast performance at each lead among the five global models. Among the four regional models, The China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) attained the smallest DPEs within a 72 h lead, while The Hurricane Weather Research and Forecasting (HWRF) achieved the best track forecast performance at 96 h and 120 h leads. Most of the models produced an obvious westward systematic bias on track forecast from a 24 h to a 120 h lead. Further correlation and cluster analyses indicate that initial TC intensity and size and environmental steering flow can be regarded as good predictors for TC DPEs. TCs with a stronger initial intensity, a bigger initial size, and a larger environmental steering flow in general attain a smaller DPE, and the improvements may go up to 36% at short lead-time.

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.

Validation of Precipitation Type Forecasts Based on ECMWF’s Ensemble Model for Hungary

Forecasts of precipitation type are of high priority, as they have a large influence on human safety, the economy and the environment. In recent decades, methods of statistical post-processing of numerical weather prediction (NWP) outputs were only applied beside the experience of the operational forecasters. In the last few years, numerical models developed significantly; thus, precipitation type has become a variable directly calculated in some models. In the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system (IFS) model, a new method has been used since 2015 to predict the type of precipitation. In this study, we examine the forecast of the ECMWF IFS ensemble model concerning precipitation type through ensemble verification and a case study on a freezing-rain situation for the territory of Hungary. We put emphasis on the investigation of the usability of ensemble forecasts. We introduce the developed forms of visualization supporting the interpretation of ensemble precipitation-type forecasts.

Propagation paths and source distributions of resolved gravity waves in ECMWF-IFS analysis fields around the southern polar night jet

Abstract. In the southern winter polar stratosphere, the distribution of gravity wave momentum flux in many state-of-the-art climate simulations is inconsistent with long-time satellite and superpressure balloon observations around 60∘ S. Recent studies hint that a lateral shift between prominent gravity wave sources in the tropospheric mid-latitudes and the location where gravity wave activity is present in the stratosphere causes at least part of the discrepancy. This lateral shift cannot be represented by the column-based gravity wave drag parameterisations used in most general circulation models. However, recent high-resolution analysis and re-analysis products of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) show good agreement with the observations and allow for a detailed investigation of resolved gravity waves, their sources, and propagation paths. In this paper, we identify resolved gravity waves in the ECMWF-IFS analyses for a case of high gravity wave activity in the lower stratosphere using small-volume sinusoidal fits to characterise these gravity waves. The 3D wave vector together with perturbation amplitudes, wave frequency, and a fully described background atmosphere are then used to initialise the Gravity Wave Regional or Global Ray Tracer (GROGRAT) gravity wave ray tracer and follow the gravity waves backwards from the stratosphere. Finally, we check for the indication of source processes on the path of each ray and, thus, quantitatively attribute gravity waves to sources that are represented within the model. We find that stratospheric gravity waves are indeed subject to far (>1000 km) lateral displacement from their sources, which already take place at low altitudes (<20 km). Various source processes can be linked to waves within stratospheric gravity wave (GW) patterns, such as the orography equatorward of 50∘ S and non-orographic sources above the Southern Ocean. These findings may explain why superpressure balloons observe enhanced gravity wave momentum fluxes in the lower stratosphere over the Southern Ocean despite an apparent lack of sources at this latitude. Our results also support the need to improve gravity wave parameterisations to account for meridional propagation.

Evaluating the added value of multi-input atmospheric transport ensemble modeling for applications of the Comprehensive Nuclear Test-Ban Treaty organization (CTBTO)

The Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO) runs to date operationally an atmospheric transport modeling chain in backward mode based on operational deterministic European Centre for Medium-Range Weather Forecasts-Integrated Forecasting System (ECMWF-IFS) and on National Centers for Environmental Prediction-Global Forecast System (NCEP-GFS) input data. Meanwhile, ensemble dispersion modeling is becoming more and more widespread due to the ever increasing computational power and storage capacities. The potential benefit of this approach for current and possible future CTBTO applications was investigated using data from the ECMWF-Ensemble Prediction System (EPS). Five different test cases - among which are the ETEX-I experiment and the Fukushima accident - were run in backward or forward mode and - in the light of a future operational application - special emphasis was put on the performance of an arbitrarily selected 10- versus the full 51-member ensemble. For those test cases run in backward mode and based on a puff release it became evident that Possible Source Regions (PSRs) can be meaningfully reduced in size compared to results based solely on the deterministic run by applying minimum and probability of exceedance ensemble metrics. It was further demonstrated that a given puff release of 4E10 Bq of Se-75 can be reproduced within the meteorological uncertainty range [1.9E9 Bq,1.7E13 Bq] including a probability for not exceeding an assumed upper limit source term using simple scaling of a measurement with the corresponding ensemble metrics of backward fields. For the test cases run in forward mode it was found that the control run as well as 10- and 51-member medians all exhibit similar performance in time series evaluation. Maximum rank difference adds up to less than 10% with reference to possible rank values [0,4]. The maximum difference in the Brier score for both ensembles is less than 3%. The main added value of the ensemble lies in producing meteorologically induced concentration uncertainties and thus explaining observed measurements at specific sites. Depending on the specific test case and on the ensemble size between 27 and 74% of samples all lie within concentration ranges derived from the different meteorological fields used. In the future uncertainty information per sample could be used in a full source term inversion to account for the meteorological uncertainty in a proper way. It can be concluded that a 10-member meteorological ensemble is good enough to already benefit from useful ensemble properties. Meteorological uncertainty to a large degree is covered by the 10-member subset because forecast uncertainty is largely suppressed due to concatenating analyses and short term forecasts, as required in the operational CTBTO procedure, on which this study focuses. Besides, members from different analyses times are on average unrelated. It was recommended to Working Group B of CTBTO to implement the ensemble system software in the near future.

Forecast Errors and Uncertainties in Atmospheric Rivers

AbstractA key aim of observational campaigns is to sample atmosphere–ocean phenomena to improve understanding of these phenomena, and in turn, numerical weather prediction. In early 2018 and 2019, the Atmospheric River Reconnaissance (AR Recon) campaign released dropsondes and radiosondes into atmospheric rivers (ARs) over the northeast Pacific Ocean to collect unique observations of temperature, winds, and moisture in ARs. These narrow regions of water vapor transport in the atmosphere—like rivers in the sky—can be associated with extreme precipitation and flooding events in the midlatitudes. This study uses the dropsonde observations collected during the AR Recon campaign and the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) to evaluate forecasts of ARs. Results show that ECMWF IFS forecasts 1) were colder than observations by up to 0.6 K throughout the troposphere; 2) have a dry bias in the lower troposphere, which along with weaker winds below 950 hPa, resulted in weaker horizontal water vapor fluxes in the 950–1000-hPa layer; and 3) exhibit an underdispersiveness in the water vapor flux that largely arises from model representativeness errors associated with dropsondes. Four U.S. West Coast radiosonde sites confirm the IFS cold bias throughout winter. These issues are likely to affect the model’s hydrological cycle and hence precipitation forecasts.

A Sensitivity Analysis with COSMO-LM at 1 km Resolution over South Italy

The results of a sensitivity analysis based on COSMO-LM (COnsortium for Small-Scale MOdeling—Lokal Model) simulations driven by ECMWF-IFS (European Centre for Medium-Range Weather Forecasts—Integrated Forecasting System). global data over a domain located in southern Italy are presented. Simulations have been performed at very high resolution (about 1 km). The main aim of this study is to individuate the most sensitive physical and numerical parameters of the model configuration, comparing a set of 18 simulations in terms of temperature and precipitation against ground observations. The parameters that result in having more influence for a proper representation of temperature and precipitation fields are the heat resistance length of laminar layer (which accounts for the high complexity of the interaction of the atmosphere with the underlying surface) and the minimal diffusion coefficient for heat. Temperature values are strongly influenced also by the vertical variation of critical relative humidity. An optimized tuning of these parameters allows COSMO-LM to improve the representation of simulated main features of this area, with significant bias reductions.

The Time-Scale-Dependent Response of the Wintertime North Atlantic to Increased Ocean Model Resolution in a Coupled Forecast Model

AbstractThis study uses initialized forecasts and climate integrations to evaluate the wintertime North Atlantic response to an increase of ocean model resolution from ~100 km [low-resolution ocean (LRO)] to ~25 km [high-resolution ocean (HRO)] in the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS). Importantly, the simulated impacts are time-scale dependent such that impacts in subseasonal and seasonal forecasts cannot be extrapolated to climate time scales. In general, mean biases are reduced in HRO relative to LRO configurations and the impact is increased at longer lead times. At subseasonal to seasonal lead times, surface heating anomalies over the Gulf Stream are associated with local increases to the poleward heat flux associated with transient atmospheric eddies. In contrast, surface heating anomalies in climate experiments are balanced by changes to the time-mean surface winds that resemble the steady response under linear dynamics. Some aspects of air–sea interaction exhibit a clear improvement with increased resolution at all lead times. However, it is difficult to identify the impact of increased ocean eddy activity in the variability of the overlying atmosphere. In particular, atmospheric blocking and the intensity of the storm track respond more strongly to mean biases and thus have a larger response at longer lead times. Finally, increased ocean resolution drives improvements to subseasonal predictability over Europe. This increase in skill seems to be a result of improvements to the Madden–Julian oscillation and its associated teleconnections rather than changes to air–sea interaction in the North Atlantic region.

Operational Implementation of the AROME Model in the Tropics: Multiscale Validation of Rainfall Forecasts

AbstractMétéo-France runs operationally, for the needs of several overseas regions in the tropical belt, five numerical weather prediction configurations, based on the convection-permitting model AROME and called the AROME-OM system. These configurations use the high-resolution model [Integrated Forecasting System (IFS)] from the European Centre for Medium-Range Weather Forecasts (ECMWF) for both initialization and lateral forcing. In this study, the performance of the AROME-OM system for rainfall forecasting is compared to the one of ECMWF IFS. The validation uses spatialized rainfall estimates over a 24-h time period at two time scales (daily and annual), from both satellite and ground-based instruments. It has been performed over a 10-month period and across five tropical domains. The intercomparison demonstrates consistent signals across domains and scales. The added value of the AROME-OM system compared to ECMWF IFS is shown for rain/no-rain discrimination and for rain accumulations larger than 10 mm day−1. The AROME-OM system also shows a better ability to forecast realistic rain patterns over these tropical regions. The main weakness found is for an intermediate range of rain accumulations, from 1 to 10 mm day−1, for which the ECMWF IFS forecasts slightly outperform the AROME-OM system forecasts.

An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF

Abstract. An aerosol climatology to represent aerosols in the radiation schemes of global atmospheric models was recently developed. We derived the climatology from a reanalysis of atmospheric composition produced by the Copernicus Atmosphere Monitoring Service (CAMS). As an example of an application in a global atmospheric model, we discuss the technical aspects of the implementation in the European Centre for Medium Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) and the impact of the new climatology on the medium-range weather forecasts and 1-year simulations. The new aerosol climatology was derived by combining a set of model simulations with constrained meteorological conditions and an atmospheric composition reanalysis for the period 2003–2013 produced by the IFS. The aerosol fields of the reanalysis are constrained by assimilating the aerosol optical thickness (AOT) retrievals product by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. In a further step, we used modelled aerosol fields to correct the aerosol speciation and the vertical profiles of the aerosol reanalysis fields. The new climatology provides the monthly-mean mass mixing ratio of five aerosol species constrained by assimilated MODIS AOT. Using the new climatology in the ECMWF-IFS leads to changes in the direct aerosol radiative effect compared to the climatology previously implemented, which have a small but non-impact on the forecast skill of large-scale weather patterns in the medium-range. However, details of the regional distribution of aerosol radiative forcing can have a large local impact. This is the case for the area of the Arabian Peninsula and the northern Indian Ocean. Here changes in the radiative forcing of the mineral dust significantly improve the summer monsoon circulation.

Convectively Coupled Equatorial Wave Simulations Using the ECMWF IFS and the NOAA GFS Cumulus Convection Schemes in the NOAA GFS Model

Abstract There is a longstanding challenge in numerical weather and climate prediction to accurately model tropical wave variability, including convectively coupled equatorial waves (CCEWs) and the Madden–Julian oscillation. For subseasonal prediction, the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) has been shown to be superior to the NOAA Global Forecast System (GFS) in simulating tropical variability, suggesting that the ECMWF model is better at simulating the interaction between cumulus convection and the large-scale tropical circulation. In this study, we experiment with the cumulus convection scheme of the ECMWF IFS in a research version of the GFS to understand which aspects of the IFS cumulus convection scheme outperform those of the GFS convection scheme in the tropics. We show that the IFS cumulus convection scheme produces significantly different tropical moisture and temperature tendency profiles from those simulated by the GFS convection scheme when it is coupled with other physics schemes in the GFS physics package. We show that a consistent treatment of the interaction between parameterized convective plumes in the GFS planetary boundary layer (PBL) and the IFS convection scheme is required for the GFS to replicate the tropical temperature and moisture profiles simulated by the IFS model. The GFS model with the IFS convection scheme, and the consistent treatment between the convection and PBL schemes, produces much more organized convection in the tropics, and generates tropical waves that propagate more coherently than the GFS in its default configuration due to better simulated interaction between low-level convergence and precipitation.

A Forecast Evaluation of Planetary Boundary Layer Height Over the Ocean

AbstractThe planetary boundary layer (PBL) is the layer closest to the Earth's surface in which heat, moisture, and momentum fluxes occur between the surface and free atmosphere. As these fluxes affect the atmospheric flow, it is important for weather forecast systems to accurately characterize them to provide skillful forecasts. A key PBL property is its height, and this study assesses the PBL height forecast skill over the oceans in the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). Using the ECMWF IFS and 1,959 dropsonde profiles from multiple flight missions, the average observed PBL height was 744.2 m and the short‐range (3–15 hr) forecast root‐mean‐square error was 242.5 m; the data assimilation step reduced the analysis root‐mean‐square error to 180.4 m. These data were also analyzed based on their location, the observed 925‐hPa wind speed, and the PBL stability, and results showed that the IFS had larger errors in the midlatitudes, under weaker winds on forecast days 1–4, and in unstable PBL conditions. The medium‐range forecasts are also underdispersive, which is considered to be largely due to representativeness errors, whereby the forecast model attempts to represent the grid box average rather than subgrid atmospheric variability. These results highlight an area of forecast uncertainty in current forecasting systems.

Evaluation of ECMWF-IFS (version 41R1) operational model forecasts of aerosol transport by using ceilometer network measurements

Abstract. In this paper, we present a comparison of model simulations of aerosol profiles with measurements of the ceilometer network operated by the German Weather Service (DWD) over 1 year from September 2015 to August 2016. The aerosol forecasts are produced by the Copernicus Atmosphere Monitoring Service (CAMS) using the aerosol module developed within the Global and regional Earth-system Monitoring using Satellite and in-situ data (GEMS) and Monitoring Atmospheric Composition and Climate (MACC) projects and coupled into the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS). As the model output provides mass mixing ratios of different types of aerosol, whereas the ceilometers do not, it is necessary to determine a common physical quantity for the comparison. We have chosen the attenuated backscatter β∗ for this purpose. The β∗ profiles are calculated from the mass mixing ratios of the model output assuming the inherent aerosol microphysical properties. Comparison of the attenuated backscatter averaged between an altitude of 0.2 km (typical overlap range of ceilometers) and 1 km in general shows similar annual average values. However, the standard deviation of the difference between model and observation is larger than the average in 8 out of 12 sites. To investigate possible reasons for the differences, we have examined the role of the hygroscopic growth of particles and the particle shape. Our results show that using a more recent particle growth model would result in a ∼22 % reduction of particle backscatter for sea salt aerosols, corresponding to a 10 % reduction of the total backscatter signal on average. Accounting for nonspherical dust particles in the model would reduce attenuated backscatter of dust particles by ∼30 %. As the concentration of dust aerosol is in general very low in Germany, a significant effect on the total backscatter signal is restricted to dust episodes. In summary, consideration of both effects tends to improve the agreement between model and observations but without leading to a perfect consistency. In addition, a strong Saharan dust event was investigated to study the agreement of the spatiotemporal distribution of particles. It was found that the arrival time of the dust layer and its vertical extent very well agree between model and ceilometer measurements for several stations. This underlines the potential of a network of ceilometers to validate the dispersion of aerosol layers.

Climate model configurations of the ECMWF Integrated Forecasting System (ECMWF-IFS cycle 43r1) for HighResMIP

Abstract. This paper presents atmosphere-only and coupled climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal ensemble experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6). These experiments are used to evaluate the sensitivity of major biases in the atmosphere, ocean, and cryosphere to changes in atmosphere and ocean resolution. All configurations successfully reproduce the observed long-term trends in global mean surface temperature. Furthermore, following an adjustment to account for drift in the subsurface ocean, coupled configurations of ECMWF-IFS realistically reproduce observation-based estimates of ocean heat content change since 1950. Climatological surface biases in ECMWF-IFS are relatively insensitive to an increase in atmospheric resolution from ∼ 50 to ∼ 25 km. However, increasing the horizontal resolution of the atmosphere while maintaining the same vertical resolution enhances the magnitude of a cold bias in the lower stratosphere. In coupled configurations, there is a strong sensitivity to an increase in ocean model resolution from 1 to 0.25°. However, this sensitivity to ocean resolution takes many years to fully manifest and is less apparent in the first year of integration. This result has implications for the ECMWF coupled model development strategy that typically relies on the analysis of biases in short ( < 1 year) ensemble (re)forecast data sets. The impacts of increased ocean resolution are particularly evident in the North Atlantic and Arctic, where they are associated with an improved Atlantic meridional overturning circulation, increased meridional ocean heat transport, and more realistic sea-ice cover. In the tropical Pacific, increased ocean resolution is associated with improvements to the magnitude and asymmetry of El Niño–Southern Oscillation (ENSO) variability and better representation of non-linear sea surface temperature (SST)–radiation feedbacks during warm events. However, increased ocean model resolution also increases the magnitude of a warm bias in the Southern Ocean. Finally, there is tentative evidence that both ocean coupling and increased atmospheric resolution can improve teleconnections between tropical Pacific rainfall and geopotential height anomalies in the North Atlantic.

AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction Model

Abstract Since October 2013 a convective-scale weather prediction model has been used operationally to provide short-term forecasts covering large parts of the Nordic region. The model is now operated by a bilateral cooperative effort [Meteorological Cooperation on Operational Numerical Weather Prediction (MetCoOp)] between the Norwegian Meteorological Institute and the Swedish Meteorological and Hydrological Institute. The core of the model is based on the convection-permitting Applications of Research to Operations at Mesoscale (AROME) model developed by Météo-France. In this paper the specific modifications and updates that have been made to suit advanced high-resolution weather forecasts over the Nordic regions are described. This includes modifications in the surface drag description, microphysics, snow assimilation, as well as an update of the ecosystem and surface parameter description. Novel observation types are introduced in the operational runs, including ground-based Global Navigation Satellite System (GNSS) observations and radar reflectivity data from the Norwegian and Swedish radar networks. After almost two years’ worth of experience with the AROME-MetCoOp model, the model’s sensitivities to the use of specific parameterization settings are characterized and the forecast skills demonstrating the benefit as compared with the global European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (ECMWF-IFS) are evaluated. Furthermore, case studies are provided to demonstrate the ability of the model to capture extreme precipitation and wind events.

SARAL/AltiKa Wind and Wave Products: Monitoring, Validation and Assimilation

SARAL/AltiKa surface wind speed (WS) and significant wave height (SWH) measurements are monitored and validated against operational European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric and wave model results in addition to available in-situ observations to access their suitability for various applications, especially SWH data assimilation. The quality of SWH is very high while that of WS is very good except for an underestimation of high wind speeds. The impact of assimilating SWH in the ECMWF Integrated Forecast System was assessed using several numerical experiments. The results show positive impact. Operational assimilation of SWH at ECMWF model is part of the forthcoming model change.

Characterizing the radiative impacts of precipitating snow in the ECMWF Integrated Forecast System global model

AbstractGlobal weather and climate models often exclude the effects of precipitating hydrometeors and convective core mass on radiative fluxes. In particular, many models split the ice phase into separate “cloud ice” and “snow” categories representing the smaller and larger ice particles, respectively; a separation that is generally not well defined in observations. A version of the European Centre for Medium‐Range Weather Forecasts (ECMWF) global numerical weather prediction model which includes the radiative effects of cloud liquid, cloud ice, and precipitating snow is used to investigate the impact of including and excluding the radiative effects of the precipitating snow category. The results show that exclusion of precipitating snow in the radiation calculations leads to differences in the shortwave and longwave radiative fluxes of 5–15 W m−2 in strongly precipitating and convective areas. These differences are of the same order of magnitude as the systematic errors in the model compared to satellite observations. Corresponding biases in the radiative heating profiles are on the order of 0.15 K d−1. The results imply that precipitating snow should be included in the radiative calculations in all weather and climate models in the context of improving model fidelity and reducing compensating errors.

A New Formulation of the Spectral Energy Budget of the Atmosphere, with Application to Two High-Resolution General Circulation Models

Abstract A new formulation of the spectral energy budget of kinetic and available potential energies of the atmosphere is derived, with spherical harmonics as base functions. Compared to previous formulations, there are three main improvements: (i) the topography is taken into account, (ii) the exact three-dimensional advection terms are considered, and (iii) the vertical flux is separated from the energy transfer between different spherical harmonics. Using this formulation, results from two different high-resolution GCMs are analyzed: the Atmospheric GCM for the Earth Simulator (AFES) T639L24 and the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) T1279L91. The spectral fluxes show that the AFES, which reproduces quite realistic horizontal spectra with a k−5/3 inertial range at the mesoscales, simulates a strong downscale energy cascade. In contrast, neither the k−5/3 vertically integrated spectra nor the downscale energy cascade are produced by the ECMWF IFS.