High-resolution Forecast Model Research Articles

A high-resolution prediction system for birch pollen in Sapporo

This study aims to develop a high-resolution forecast model for airborne birch pollen concentration in Sapporo. Using results that shows that the bulk of pollen grains was deposited near the source plant, we created a high-resolution birch tree density map from a field survey along public roads and footpaths and Street View on Google Maps. The map was linearly extrapolated to cover an area 10 km from the city centre, including forests in the south and southwest. A new atmospheric dispersion deposition model for birch pollen was developed to represent wind advection, turbulent mixing, and convection in the atmospheric boundary layer, and gravitational settling and scavenging with precipitation. Pollen emission was also modelled as a function of the birch tree density and surface air temperatures. The onset of the pollen season was based on the pollen observations by a sampler at Hokkaido Institute of Public Health in Sapporo, and the end of pollen season was assumed to be 40 days after its onset. Comparison with observations suggested that the hindcast simulation with the model reproduced the daily variations in the dry deposition well in most years from 2001 to 2011. The geographical distribution of birch pollen deposition was highly correlated with the birch tree density map, even on windy days.

Validation and correction of sea surface salinity retrieval from SMAP

In this study, sea surface salinity (SSS) Level 3 (L3) daily product derived from soil moisture active passive (SMAP) during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity (SMOS) and in-situ measurements. Generally, the root mean square error (RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature (SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.

Development of a new operational system for monitoring and forecasting coastal and open-ocean states around Japan

We developed a new system to monitor and forecast coastal and open-ocean states around Japan for operational use by the Japan Meteorological Agency. The system consists of an eddy-resolving analysis model based on four-dimensional variational assimilation and a high (2-km) resolution forecast model covering Japanese coastal areas that incorporates an initialization scheme with temporal and spatial filtering. Assimilation and forecast experiments were performed for 2008 to 2017, and the results were validated against various observation datasets. The assimilation results captured well the observed variability in sea surface temperature, coastal sea level, volume transport, and sea ice. Furthermore, the volume budget for the Japan Sea was significantly improved by the use of the 2-km resolution forecast model compared with the 10-km resolution analysis model. The forecast results indicate that this system has a predictive limit longer than 1 month in many areas, including in the Kuroshio current area south of Japan and the southern Japan Sea. In the forecast results of case studies, the 2017 Kuroshio large meander was well predicted, and warm water intrusions accompanying Kuroshio path variations south of Japan were also successfully reproduced. Sea ice forecasts for the Sea of Okhotsk largely captured the evolution of sea ice in late winter, but sea ice in early winter included relatively large errors. This system has high potential to meet operational requirements for monitoring and forecasting ocean phenomena at both meso- and coastal scales.

Gravity-Wave Drag in the Stable Boundary Layer Over Moderate Terrain

Two previous studies of vertical stress profiles due to gravity waves in the stable boundary layer have given differing results. The current study uses a high-resolution numerical forecast model to determine the effect of moderate topography on the vertical stress profile due to gravity waves in the stable boundary layer. The results show that while a quadratic stress profile is expected when topography is low compared to the stable boundary-layer height, when topography height is moderate the pressure term in the valleys becomes dominant. This results in a linear effective stress profile below the hill tops with possibly some remnant stress transmitted up into the troposphere.

LANFEX: A Field and Modeling Study to Improve Our Understanding and Forecasting of Radiation Fog

AbstractFog is a high-impact weather phenomenon affecting human activity, including aviation, transport, and health. Its prediction is a longstanding issue for weather forecast models. The success of a forecast depends on complex interactions among various meteorological and topographical parameters; even very small changes in some of these can determine the difference between thick fog and good visibility. This makes prediction of fog one of the most challenging goals for numerical weather prediction. The Local and Nonlocal Fog Experiment (LANFEX) is an attempt to improve our understanding of radiation fog formation through a combined field and numerical study. The 18-month field trial was deployed in the United Kingdom with an extensive range of equipment, including some novel measurements (e.g., dew measurement and thermal imaging). In a hilly area we instrumented flux towers in four adjacent valleys to observe the evolution of similar, but crucially different, meteorological conditions at the different sites. We correlated these with the formation and evolution of fog. The results indicate new quantitative insight into the subtle turbulent conditions required for the formation of radiation fog within a stable boundary layer. Modeling studies have also been conducted, concentrating on high-resolution forecast models and research models from 1.5-km to 100-m resolution. Early results show that models with a resolution of around 100 m are capable of reproducing the local-scale variability that can lead to the onset and development of radiation fog, and also have identified deficiencies in aerosol activation, turbulence, and cloud micro- and macrophysics, in model parameterizations.

The importance of forecasting regional wind power ramping: A case study for the UK

In recent years there has been a significant change in the distribution of wind farms in Great Britain, with a trend towards very large offshore farms clustered together in zones. However, there are concerns these clusters could produce large ramping events on time scales of less than 6 h as local meteorological phenomena simultaneously impact the production of several farms. This paper presents generation data from the wind farms in the Thames Estuary (the largest cluster in the world) for 2014 and quantifies the high frequency power ramps. Based on a case study of a ramping event which occurred on 3rd November 2014, we show that due to the large capacity of the cluster, a localised ramp can have a significant impact on the cost of balancing the power system on a national level if it is not captured by the forecast of the system operator. The planned construction of larger offshore wind zones will exacerbate this problem. Consequently, there is a need for accurate regional wind power forecasts to minimise the costs of managing the system. This study shows that state-of-the-art high resolution forecast models have capacity to provide valuable information to mitigate this impact.

Evaluation of High-Frequency Channels for Deep-Space Data Transmission Using Radiometeorological Model Forecast

The aim of this paper is to investigate the usability of high-frequency channels for deep-space (DS) transmissions exploiting radiometeorological forecast modeling. A previously developed model chain for DS link-budget optimization, based on numerical weather forecasts (WFs), is adopted. The latter, already tested at Ka-band, exploits the combination of a high-resolution mesoscale forecast model and a radiative transfer model to predict the atmospheric scenario and optimize received data volume (DV) during DS transmissions. To shift available Ka-band results to other frequencies, we apply frequency-scaling laws to extrapolate forecast path attenuation, link parameters, and maximum allowed bit-rate for data transmission. Exploiting the available WF-based methodology, we compute DV return for DS missions operating at $X$ -, $K$ -, Ka-, $Q$ -, and $W$ -bands in order to make a comparative study of the behavior of DS transmission-channels at these frequencies. Results show that, in terms of received DV, an innovative WF-based approach is more convenient than traditional methodologies and exhibits a trend similar to the benchmark (ideal case). Increasing link frequency, received DV increases up to $Q$ -band. From $Q$ - to $W$ -band, despite received DV does not increase significantly, lost data remain under reasonable values, thus making the $W$ -band suitable if coupled with a WF-based technique.

Mountain Waves in High Resolution Forecast Models: Automated Diagnostics of Wave Severity and Impact on Surface Winds

An automated method producing a diagnostic of the severity of lee waves and their impacts on surface winds as represented in output from a high resolution linear numerical model (3D velocities over mountains (3DVOM)) covering several areas of the U.K. is discussed. Lee waves involving turbulent rotor activity or downslope windstorms represent a hazard to aviation and ground transport, and summary information of this kind is highly valuable as an efficient ‘heads-up’ for forecasters, for automated products or to feed into impact models. Automated diagnosis of lee wave surface effects presents a particular challenge due to the complexity of turbulent zones in the lee of irregular terrain. The method proposed quantifies modelled wind perturbations relative to those that would occur in the absence of lee waves for a given background wind, and diagnoses using it are found to be quite consistent between cases and for different ranges of U.K. hills. A recent upgrade of the operational U.K. limited area model, the U.K. Variable Resolution Model (UKV) used for general forecasting at the Met Office means that it now resolves lee waves, and its performance is here demonstrated using comparisons with aircraft- and surface-based observations and the linear model. In the future, automated diagnostics may be adapted to use its output to routinely produce contiguous mesoscale maps of lee wave activity and surface impacts over the whole U.K.

Exploiting Existing Ground-Based Remote Sensing Networks to Improve High-Resolution Weather Forecasts

Abstract A new generation of high-resolution (1 km) forecast models promises to revolutionize the prediction of hazardous weather such as windstorms, flash floods, and poor air quality. To realize this promise, a dense observing network, focusing on the lower few kilometers of the atmosphere, is required to verify these new forecast models with the ultimate goal of assimilating the data. At present there are insufficient systematic observations of the vertical profiles of water vapor, temperature, wind, and aerosols; a major constraint is the absence of funding to install new networks. A recent research program financed by the European Union, tasked with addressing this lack of observations, demonstrated that the assimilation of observations from an existing wind profiler network reduces forecast errors, provided that the individual instruments are strategically located and properly maintained. Additionally, it identified three further existing European networks of instruments that are currently underexploited, but with minimal expense they could deliver quality-controlled data to national weather services in near–real time, so the data could be assimilated into forecast models. Specifically, 1) several hundred automatic lidars and ceilometers can provide backscatter profiles associated with aerosol and cloud properties and structures with 30-m vertical resolution every minute; 2) more than 20 Doppler lidars, a fairly new technology, can measure vertical and horizontal winds in the lower atmosphere with a vertical resolution of 30 m every 5 min; and 3) about 30 microwave profilers can estimate profiles of temperature and humidity in the lower few kilometers every 10 min. Examples of potential benefits from these instruments are presented.

Net sea–air CO<sub>2</sub> flux uncertainties in the Bay of Biscay based on the choice of wind speed products and gas transfer parameterizations

Abstract. The estimation of sea–air CO2 fluxes is largely dependent on wind speed through the gas transfer velocity parameterization. In this paper, we quantify uncertainties in the estimation of the CO2 uptake in the Bay of Biscay resulting from the use of different sources of wind speed such as three different global reanalysis meteorological models (NCEP/NCAR 1, NCEP/DOE 2 and ERA-Interim), one high-resolution regional forecast model (HIRLAM-AEMet), winds derived under the Cross-Calibrated Multi-Platform (CCMP) project, and QuikSCAT winds in combination with some of the most widely used gas transfer velocity parameterizations. Results show that net CO2 flux estimations during an entire seasonal cycle (September 2002–September 2003) may vary by a factor of ~ 3 depending on the selected wind speed product and the gas exchange parameterization, with the highest impact due to the last one. The comparison of satellite- and model-derived winds with observations at buoys advises against the systematic overestimation of NCEP-2 and the underestimation of NCEP-1. In the coastal region, the presence of land and the time resolution are the main constraints of QuikSCAT, which turns CCMP and ERA-Interim in the preferred options.

A high-resolution pre-operational forecast model of circulation on the Texas-Louisiana continental shelf and slope

A new pre-operational model of circulation over the Texas-Louisiana continental shelf and slope, based on the Regional Ocean Modelling System (ROMS) is presented. The model is designed with a number of practical applications in mind: to predict oil spill trajectories, investigate the mechanisms controlling seasonal hypoxia, and to understand the origins of harmful algal blooms on the Texas-Louisiana continental shelf and slope. This model consists of two parts: the hindcast and pre-operational components. The hindcast model is forced with the observed freshwater fluxes from the nine major Texas and Louisiana rivers, surface winds, and heat and salt fluxes from North American Regional Reanalysis (NARR) dataset. The hindcast simulations are carried out over an eight-year period (February 2003–June 2011). The pre-operational model, which provides nowcast and a five-day forecast, starts from July 2011 with a different surface momentum and heat flux forcing from the Global Forecast System (GFS). Both hindcast and forecast models are nested to the Gulf of Mexico HYCOM (Hybrid Coordinate Ocean Model) which provides an estimate of the circulation in the deep Gulf. Model performance is quantified based on the model skills calculated using measurements from the Texas Automated Buoy System (TABS), coastal water level stations and satellite altimetry data. The model is able to reproduce not only the seasonal pattern of sea surface height (SSH), temperature, and velocity fields, but also the strong sea-breezedriven near-inertial surface currents, which have been found dominant in this region during the summer months.

Extracting Unique Information from High-Resolution Forecast Models: Monitoring Selected Fields and Phenomena Every Time Step

Abstract A new strategy for generating and presenting model diagnostic fields from convection-allowing forecast models is introduced. The fields are produced by computing temporal-maximum values for selected diagnostics at each horizontal grid point between scheduled output times. The two-dimensional arrays containing these maximum values are saved at the scheduled output times. The additional fields have minimal impacts on the size of the output files and the computation of most diagnostic quantities can be done very efficiently during integration of the Weather Research and Forecasting Model. Results show that these unique output fields facilitate the examination of features associated with convective storms, which can change dramatically within typical output intervals of 1–3 h.

Combination of Mesoscale and Synoptic Mechanisms for Triggering an Isolated Thunderstorm: Observational Case Study of CSIP IOP 1

Abstract An isolated thunderstorm formed in the southern United Kingdom on 15 June 2005 and moved through the area where a large number of observational instruments were deployed as part of the Convective Storm Initiation Project. Earlier, a convergence line had formed downstream of Devon in the southwest of the United Kingdom in a southwesterly airflow, along which a series of light showers had formed. The depth of these showers was limited by a capping inversion, or lid, at around 2.5 km. The deep thunderstorm convection developed from one of these showers when the convection broke through the lid and ascended up to the next inversion, associated with a tropopause fold at around 6 km. A series of clear-air reflectivity RHIs are used to map the height of the capping inversion and its lifting resulting from the ascent along the convergence line. The origins of the lid are tracked back to some descent from the midtroposphere along dry adiabats. The strength of the lid was weaker along a northwest-to-southeast-oriented region located behind an overrunning upper cold front. The transition from shallow to deep convection occurred where this region with a weaker lid intersected the region with a raised lid, oriented southwest to northeast, downstream of Devon. A very high resolution forecast model that is being developed by the Met Office predicted the isolated thunderstorm successfully. This success depended on the accurate representation of the following two scales: the synoptic-scale and the surface-forced mesoscale convergence line. The interaction between these scales localized the convection sufficiently in space and time for the initiation and subsequent development to be highly predictable despite the relatively poor representation in the model of processes at the cloud scale.

High-Resolution Forecast Models of Water Vapor Over Mountains: Comparison With MERIS and Meteosat Data

Propagation delay due to variable tropospheric water vapor (WV) is one of the most intractable problems for radar interferometry, particularly over mountains. The WV field can be simulated by an atmospheric model, and the difference between the two fields is used to correct the radar interferogram. Here, we report our use of the U.K. Met Office Unified Model in a nested mode to produce high-resolution forecast fields for the 3-km-high Mount Etna volcano. The simulated precipitable-water field is validated against that retrieved from the Medium-Resolution Imaging Spectrometer (MERIS) radiometer on the Envisat satellite, which has a resolution of 300 m. Two case studies, one from winter (November 24, 2004) and one from summer (June 25, 2005), show that the mismatch between the model and the MERIS fields ( rms = 1.1 and 1.6 mm, respectively) is small. One of the main potential sources of error in the models is the timing of the WV field simulation. We show that long-wavelength upper tropospheric troughs of low WV could be identified in both the model output and Meteosat WV imagery for the November 24, 2004 case and used to choose the best time of model output.

Does the Influence of Oblate-Like Distortions in Larger Raindrops Make a Difference in Collection and Evaporation Parameterizations?

Abstract This note documents the results of more exact parameterizations for continuous-collection growth and evaporation against simpler traditional ones. Although the main focus is on improving research models, the research results also apply to high-resolution forecast models because the use of lookup tables can make the proposed evaporation, terminal velocity, and collection parameterizations as fast as or faster than proposed ones. It is shown that the older method of ignoring oblate-like distortions of shapes in raindrops, truncated at a maximum diameter of 8 mm, gives a solution like that including oblate-like distortions but only because of two large errors that nearly cancel. The biggest differences from the solutions using oblate-like distortions in shape arise from parameterizations that incorporate more exact approximations (e.g., sweep-out diameter) that are not combined with appropriately more exact approximations for other variables dependent on diameter (e.g., terminal velocity).

A high resolution forecast model of storm surge inundation

In order to forecast storm surge inundation, a two-dimensional model is established. In the model, an alternating computation sequence method is used to solve the governing equations, and the dry and wet method is introduced to treat the moving boundary. This model is easy to use. It has a friendly input interface and Arcview GIS is used as the output interface. The model is applied to the Shantou area to simulate the storm surge elevations and inundations caused by Typhoons 6903 ane 0104 using the same relevant parameters. The calculated results agree well with the observations.

Combining weather prediction and remote sensing data for the calculation of evapotranspiration rates: application to Denmark

Evapotranspiration rates in Denmark were estimated using Advanced Very High Resolution Radiometer (AVHRR) satellite data and weather conditions predicted by a high-resolution weather forecast model (HIRLAM). The predictions were used both for atmospheric correction of satellite data and for remote sensing based calculation of net radiation, sensible heat fluxes and evapotranspiration rates. Climate predictions at 12 GMT were used as proxies for the atmospheric conditions at the time of the afternoon satellite passage (12.30–14.30 GMT). The air temperature at the time of the satellite passage was retrieved with a rms error of 1.9°C, and the rms error of the retrieved air humidity was 204 Pa. The evapotranspiration results were significantly influenced by the spatial distribution of weather conditions. Due to the encirclement of Denmark by sea shorelines, sea breezes extending more than 30 km inland were responsible for the intrusion of cooler air temperatures which increased the sensible heat fluxes and suppressed the evapotranspiration rates. The predictions were linearly related to eddy-covariance flux measurements representing agricultural land, beech forest and conifer forest, but the relationships were also characterized by a large degree of scattering. The results are discussed in relation to inaccuracies and future perspectives.

Numerical Extended-Range Prediction: Forecast Skill Using a Low-Resolution Climate Model

Abstract A pilot study that evaluates the potential forecast skill of winter 10–30-day time-mean flow from a low-resolution (R15) climate simulation model is presented. The hypothesis tested is that low-resolution climate model forecasts might be as skillful as high-resolution numerical weather prediction model forecasts at extended-range timescales, if the low-frequency evolution is primarily a large-scale process and if the systematic error of the climate model is less detrimental than high-resolution forecast model error. Eight forecast cases, each containing four ensemble members, are examined and compared to high-resolution forecasts discussed by Miyakoda et al. The systematic error of the climate model is examined and then used to reduce the forecast error in an a posteriors fashion. The operational utility of these climate model forecasts is also assessed. The low-resolution climate model is quite successful in duplicating the skill of the high-resolution forecast model. If the forecast systematic ...