Improving the representation of supercooled liquid water in the HARMONIE-AROME weather forecast model

A realistic representation of mixed-phase clouds in weather and climate models is essential to accurately simulate the model&rsquo;s radiative balance and water cycle. In addition, it is important for providing downstream applications with physically realistic model data for computation of, for instance, atmospheric icing on societal infrastructure and aircraft. An important quantity for forecasts of atmospheric icing is to model accurately supercooled liquid water (SLW). In this study, we implement elements from the Thompson cloud microphysics scheme into the numerical weather prediction model HARMONIE-AROME, with the aim to improve its ability to predict SLW. We conduct an idealised process-level evaluation of microphysical processes, and analyse the water phase budget of clouds and precipitation to compare the modified and original schemes, and also identify the processes with the most impact to form SLW. Two idealised cases representing orographic lift and freezing drizzle, both known to generate significant amounts of SLW, are setup in a 1&thinsp;D column version of HARMONIE-AROME. The experiments show that the amount of SLW is largely sensitive to the ice initiation processes, snow and graupel collection of cloud water, and the rain size distribution. There is a doubling of the cloud water maximum mixing ratio, in addition to a prolonged existence of SLW, with the modified scheme compared with the original scheme. The spatial and temporal extent of cloud ice and snow are reduced, due to stricter conditions for ice nucleation. The findings are important as the HARMONIE-AROME models is used for operational forecasting in many countries in northern Europe having a colder climate, as well as for climate assessments over the Arctic region.</p

Effects of the ICE-T Microphysics Scheme in HARMONIE-AROME on Estimated Ice Loads on Transmission Lines

In-cloud icing can cause damage to infrastructure and is challenging to forecast due to lack of a good representation of supercooled liquid water (SLW) in numerical weather prediction (NWP) models. We validate the new microphysics scheme, ICE-T, implemented into the NWP model HARMONIE-AROME, in full 3D simulations running over a 3 month period from December 1st 2016 to February 28th 2017. Output from the model simulations are first compared with conventional observations to evaluate the overall quality, and then used as input to an ice accretion model (IAM) and compared against measured ice loads at the two test sites Hardingnuten and Ålvikfjellet. The results show a clear shift towards more cloud water and snow, and less graupel and cloud ice. This shift leads to less precipitation along the coast and more inland. The estimated ice loads based on the cloud water from the simulations are generally increased. We also focus on two different icing events during January 9–18 and February 1–14. During the first event, both the run in its original configuration and the run with ICE-T overestimated the ice loads, while the second event was underestimated. For Ålvikfjellet ICE-T gives the best estimates, while for Hardingnuten the ice loads are overestimated when the wind direction is from the southeast. This is due to local terrain shielding not captured by the model. During the Feb 1–14 event, the wind direction was generally easterly, which makes comparison between the simulations and the observations more reliable. In this case, ICE-T gives a better ice load estimate. Although there are major uncertainties, especially concerning the number concentration of cloud droplets, and local terrain effects, ICE-T appears to give a better estimate of the ice loads.publishedVersio

Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field CampaignpublishedVersio

The Polar Low in the Norwegian Sea March 16-17 2008

The polar low in the Norwegian Sea on March 16-17 2008 has been studied using both weather analysis and the numerical weather prediction (NWP) model weather research and forecasting (WRF). This particular polar low was poorly forecasted by several operational models, and has therefore been subject to this study. Weather analysis show that the low developed during a complex weather situation, in a confluence zone between polar and arctic air. It was one of three vortices found simultaneously in a wave-like cloud pattern along the confluence zone. There was a clear upper-level forcing by an advancing potential vorticity (PV) anomaly, along with strong convection during the cyclogenesis stage. The polar low developed in a region of the confluence zone with relatively high surface temperature and low static stability in the lower troposphere. It is suggested that this contributed to the rapid development of the vortex, and that the two other vortices might not have experienced this. Sensitivity studies with different initial times, high resolution runs and different parametrisation schemes representing microphysics, cumulus clouds and planetary boundary layer, were carried out. There were great deviations between all the simulations, particularly regarding time and location of development as well as trajectory and depth of the polar low, but all managed to produce at least one clear low. Most of the models produced several lows, which could be connected to the multiple vortices found in the confluence zone. The simulations initiated after cyclogenesis reproduced the depth of the polar low much better than the simulations initiated before cyclogenesis. It appears that the model have trouble simulating particularly the rapid development at the early stage. In contrast to previous studies, the high resolution runs did not improve the forecast much. The sensitivity study of the different parametrisation schemes of microphysics, cumulus clouds and planetary boundary layer, only showed improvements by changing the boundary layer scheme. It is concluded that the WRF simulations produced a much improved forecast compared to the operational HIRLAM simulations, and also the UM simulations carried out by McInnes et al. (2011). It is suggested that this may be due to better lateral boundary conditions due to the nesting option in WRF. Further investigations could reveal if the WRF model, in general, is be better suited for polar low forecasts than the operational HIRLAM

The ability of the ICE-T microphysics scheme in HARMONIE-AROME to predict aircraft icing

Abstract In-cloud icing is a major hazard for aviation traffic and forecasting of these events is an important task for weather agencies worldwide. A common tool utilized by aviation forecasters is an icing intensity index based on supercooled liquid water from numerical weather prediction models. We seek to validate the modified microphysics scheme, ICE-T, in the HARMONIE-AROME numerical weather prediction model with respect to aircraft icing. Icing intensities and supercooled liquid water derived from two 3-month winter season simulations with the original microphysics code, CTRL, and ICE-T are compared with pilot reports of icing and satellite retrieved values of liquid and ice water content from CloudSat–CALIPSO and liquid water path from AMSR-2. The results show increased supercooled liquid water and higher icing indices in ICE-T. Several different thresholds and sizes of neighborhood areas for icing forecasts were tested out, and ICE-T captures more of the reported icing events for all thresholds and nearly all neighborhood areas. With a higher frequency of forecasted icing, a higher false alarm ratio cannot be ruled out, but is not possible to quantify due to the lack of no-icing observations. The increased liquid water content in ICE-T shows a better match with the retrieved satellite observations, yet the values are still greatly underestimated at lower levels. Future studies should investigate this issue further, as liquid water content also has implications for downstream processes such as the cloud radiative effect, latent heat release, and precipitation

Snowfall model validation using surface observations and an optimal estimation snowfall retrieval

In the winter, orographic precipitation falls as snow in the mid to high latitudes where it causes avalanches, affects local infrastructure, or leads to flooding during the spring thaw. We present a technique to validate operational numerical weather prediction model simulations in complex terrain. The presented verification technique uses a combined retrieval approach to obtain surface snowfall accumulation and vertical profiles of snow water at the Haukeliseter test site, Norway. Both surface observations and vertical profiles of snow are used to validate model simulations from the Norwegian Meteorological Institute’s operational forecast system and two simulations with adjusted cloud microphysics. Retrieved surface snowfall is validated against measurements conducted with a double-fence automated reference gauge (DFAR). In comparison, the optimal estimation snowfall retrieval produces + 10.9% more surface snowfall than the DFAR. The predicted surface snowfall from the operational forecast model and two additional simulations with microphysical adjustments (CTRL and ICE-T) are overestimated at the surface with +41.0 %, +43.8 %, and +59.2 %, respectively. Simultaneously, the CTRL and ICE-T simulations underestimate the mean snow water path by -1071.4% and -523.7 %, respectively. The study shows that we would reach false conclusions only using surface accumulation or vertical snow water content profiles. These results highlight the need to combine ground-based in-situ and vertically-profiling remote sensing instruments to identify biases in numerical weather prediction

Utslipp, spredning og avsetning av SO2 fra Nikel og Zapoljarnij. En WRF-Chem modellstudie.

WRF-Chem-modellen har blitt brukt for å studere to episoder med forurensning fra smelteverkene i Nikel og Zapoljarnij, sommerepisoden 2007 og vinteren 2010/11. Meteorologiske inngangsdata fra WRF stemmer bra med analyse fra ECMWF. Modellen underestimerer SO2-konsentrasjoner i episoder, en mulig forklaring er at røykfanen blir midlet ut i modellen, samt at tidsutviklingen av utslippene ikke er korrekt representert. Budsjett over kilder og sluk viser at kjemisk tap er viktigst om sommeren, fulgt av våtavsetning, men våt- og tørravsetning er viktigst om vinteren. WRF-Chem er meget regnekrevende og oppsummert er WRF-Chem best egnet til å studere prosesser og enkeltepisoder

Effects of the ICE-T Microphysics Scheme in HARMONIE-AROME on Estimated Ice Loads on Transmission Lines

In-cloud icing can cause damage to infrastructure and is challenging to forecast due to lack of a good representation of supercooled liquid water (SLW) in numerical weather prediction (NWP) models. We validate the new microphysics scheme, ICE-T, implemented into the NWP model HARMONIE-AROME, in full 3D simulations running over a 3 month period from December 1st 2016 to February 28th 2017. Output from the model simulations are first compared with conventional observations to evaluate the overall quality, and then used as input to an ice accretion model (IAM) and compared against measured ice loads at the two test sites Hardingnuten and Ålvikfjellet. The results show a clear shift towards more cloud water and snow, and less graupel and cloud ice. This shift leads to less precipitation along the coast and more inland. The estimated ice loads based on the cloud water from the simulations are generally increased. We also focus on two different icing events during January 9–18 and February 1–14. During the first event, both the run in its original configuration and the run with ICE-T overestimated the ice loads, while the second event was underestimated. For Ålvikfjellet ICE-T gives the best estimates, while for Hardingnuten the ice loads are overestimated when the wind direction is from the southeast. This is due to local terrain shielding not captured by the model. During the Feb 1–14 event, the wind direction was generally easterly, which makes comparison between the simulations and the observations more reliable. In this case, ICE-T gives a better ice load estimate. Although there are major uncertainties, especially concerning the number concentration of cloud droplets, and local terrain effects, ICE-T appears to give a better estimate of the ice loads