Effect of Sea Surface Temperature Errors on Snowfall in WRF: A Case Study of a Heavy Snowfall Event in Korea in December 2012 (original) (raw)
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Ground and Satellite Based Evaluation of WRF Snowfall Prediction
SOLA, 2022
This study performed 4-day numerical integration in 1-hour intervals using the Weather Research and Forecasting (WRF) model for four major cases of heavy snowfall that occurred from 2020 to 2021. The model-predicted snow depth data were compared with the ground-observed snow depth and the satellite-observed snow cover data and then were statistically verified. The scalar verification results for ground data from the four cases showed a root-mean-square error of 2.55−16.67 cm and a correlation coefficient of 0.48−0.80, whereas the verification results with satellite data showed the correlation coefficients of 0.38−0.60. For categorical verification, using a threshold value of a snow depth exceeding 5 cm, the proportion correct was 90% or higher for ground observations of each case. In addition, in the satellite categorical verification, when the threshold value of the Snow Cover Fraction (SCF) exceeds 0.5, the proportion correct was 50% or more. These results are meaningful because the model snow depth verification methods were devised strategically for the first time using both the snow depth data of the mesoscale ground observation networks and ultra-high-resolution Sentinel-2 satellite data currently available in Korea. The findings of this study will contribute to the development of a high-resolution numerical prediction model and its verification methodology for snowfalls in the Korean Peninsula, eventually leading to increased prediction accuracy and reduced snow damage.
Journal of Climate
This research investigates the impact of local sea surface temperature (SST) on the 2-month (January and February) accumulated snowfall over the Yeongdong (YD) region. The YD region is strongly affected by synoptic-scale factors such as the East Asian winter monsoon (EAWM). The relationships of snowfall over the YD region to the EAWM and local SST are examined based on observational analyses and sensitivity experiments using a regional climate model. In the sensitivity experiments, local SST is replaced with the 33-yr mean winter SST (1982–2014). The observational analysis shows that both the synoptic environment and local SST are important factors for the occurrence of anomalous heavy snowfall over the YD region. The favorable synoptic environments can be characterized by eastward expansion of the Siberian high over Manchuria and corresponding enhancement of easterly anomalies over the YD region. These conditions are more frequently observed during the weak EAWM years than during t...
Simulation of Snowstorm over the Yellow Sea Using a Mesoscale Coupled Model
This study aims to examine the favorable conditions for an ocean effect snowstorm across the Yellow Sea over the southwestern coast of Korea on 21 December 2005, using a coupled model with a Coupled Ocean/Atmosphere Mesoscale Prediction System as the atmospheric component and the Regional Ocean Modeling System as the oceanic component. Simulation of heavy snowfall event, which was 44.3 cm of snow accumulated in 24-hour, was performed to investigate the mesoscale structure, dynamics and development mechanisms in the snowstorm. As a result from 48-hour integration, the results of simulation showed that barotropic instability and turbulent heat fluxes played important roles in the formation of snowstorm. The enhanced surface diabatic heating was dominant in the latent heat flux, and eventually induced convective instability. An additional factor was the favorable condition of synoptic environment, accessing the cold air transport by the approach of the upper-level cold vortex over the warm ocean. Besides these factors, conditional symmetric instability (CSI) is a mechanism which can result in a heavy snowfall with sufficient moisture and upward vertical motion. A slantwise con-vection from the release of CSI could support a complex snowfall event with heavier than expected amounts. The result comparison between a coupled model and an uncoupled model supports that air-sea coupling has an impact of decreasing of about 10% in a snowfall amount on the snowstorm.
Sea-Effect Precipitation over the Shandong Peninsula, Northern China
Journal of Applied Meteorology and Climatology
Sea-effect precipitation (SEP) over the Shandong Peninsula is a unique climatological phenomenon in mainland China, and it exerts a considerable impact on the southern shore of the Bohai Sea. From observed data from 123 stations for the period 1962–2012, the characteristics of cold-season (November–February) SEP in this area were analyzed. Results showed that SEP occurred throughout the late autumn and winter. In all, 1173 SEP days were identified during the 51 years, of which snow days accounted for 73.7% and rain and snow–rain days accounted for 16.1% and 10.1%, respectively. December had the largest number of SEP snow days, followed by January and November. November was the most productive month in terms of SEP rain and snow–rain days. Intense SEP snowfall mainly affected the inland hill area of the peninsula, whereas light SEP snowfall reached farther inland. SEP rainfall shared a similar pattern with snowfall. The SEP frequency showed a significant interannual variability and a...
Variations in Snow on Sea Ice: A Mechanism for Producing Climate Variations
Journal of Geophysical Research, 1993
Studies of the impact of increases in greenhouse gases on the climate system indicate that in addition to increases in temperature there will be changes in the precipitation rate, possibly both in the mean and in the extremes. While the magnitude,• of the changes in the precipitation rate are not well known, it is important to access the impact of the possible changes in precipitation rate and to identify the mechanisms by which these changes affect cli•nate. In this study the impact of various precipitation rates, and thus snowfall rates, on sea ice thickness, its subsequent effect on climate, and how this effect occurs is examined. The results show that the general effect of a thin layer of snow on the sea ice surface is to thin the sea ice. When the snow is thick enough in the poleward most zone to survive the summer season, the sea ice thickens. In addition, snow cools the climate system, and this cooling increases as the snow thickens. The cooling is caused by two factors. The first is the increase in the surface albedo for an increasingly snow-covered surface, which causes a decrease in the absorbed solar radiation by the entire system. The second is the decrease in the turbulent energy transfer from the ocean to the atmosphere, which is the result of the increased insulation of the surface from the relatively warm ocean as the snow thickens and sea ice becomes more extensive through the year. Thus as the snow thickens, the climate cools.
Journal of Geophysical Research, 2011
1] The effects of deviations in the sea surface temperature (SST) on the atmospheric variables over the Yellow Sea were investigated by numerical simulations based on realistic deviations in the magnitude and gradient of the SST. The SST magnitude was found to control primarily the surface air temperature, the atmospheric stability, and vertical moisture fluxes, whereas the SST gradient mainly affected the surface wind fields. Although the SST magnitude can also affect wind fields, its effect on the winds was small compared with the influence of the SST gradient. Both the SST gradient and magnitude clearly affected the evaporation rates. The magnitudes of the evaporation rates were found to be directly controlled by the SST magnitude, whereas the horizontal distributions of the evaporation rates were controlled by the SST gradient. The spatial patterns of the precipitable water amounts at the surface were similar to those of the vertical winds but slightly different from those of the evaporation rates. The use of an accurate SST in a meteorological model could be therefore of primary importance particularly for more accurate weather forecasting. Additionally, the effect of deviations in the SST on the atmospheric variables was damping with height, but that on the vertical winds was oscillatory and amplifying to the top of troposphere with height. This study has demonstrated that the construction of realistic SST field without smoothing the SST gradient can produce more accurate and realistic meteorological fields over the Yellow Sea in a mesoscale meteorological model. Citation: Park, R. S., Y.-K. Cho, B.-J. Choi, and C. H. Song (2011), Implications of sea surface temperature deviations in the prediction of wind and precipitable water over the Yellow Sea,
Atmosphere
This study aimed to determine the atmospheric conditions in which sea-effect snow (SES) and non-SES events occurred in a meso-scale structure. All snow events between 2009 and 2018 were found by examining the aviation reports at two international airports in Istanbul, Turkey. Then, threshold values and threshold intervals were presented for SES and non-SES events on the basis of many meteorological parameters (e.g., air temperature, dew point, relative humidity, heat fluxes, sea surface temperature (SST)). In addition, an algorithm was created for operational prediction of SES events at both airports. The most important parameter that distinguished SES events from NON-SES events was the temperature difference between sea surface (SS) and upper-atmosphere air parcel. Accordingly, sensible and latent heat fluxes had similarly higher values in SES events on average. Although the wind directions were mostly northerly in both event types, low wind shear in the layer between the SS and su...
The Cryosphere
The accuracy of the initial state is very important for the quality of a forecast, and data assimilation is crucial for obtaining the best-possible initial state. For many years, sea-ice concentration was the only parameter used for assimilation into numerical sea-ice models. Sea-ice concentration can easily be observed by satellites, and satellite observations provide a full Arctic coverage. During the last decade, an increasing number of sea-ice related variables have become available, which include sea-ice thickness and snow depth, which are both important parameters in the numerical sea-ice models. In the present study, a coupled ocean-sea-ice model is used to assess the assimilation impact of sea-ice thickness and snow depth on the model. The model system with the assimilation of these parameters is verified by comparison with a system assimilating only ice concentration and a system having no assimilation. The observations assimilated are sea ice concentration from the Ocean and Sea Ice Satellite Application Facility, thin sea ice from the European Space Agency's (ESA) Soil Moisture and Ocean Salinity mission, thick sea ice from ESA's CryoSat-2 satellite, and a new snowdepth product derived from the National Space Agency's Advanced Microwave Scanning Radiometer (AMSR-E/AMSR-2) satellites. The model results are verified by comparing assimilated observations and independent observations of ice concentration from AMSR-E/AMSR-2, and ice thickness and snow depth from the IceBridge campaign. It is found that the assimilation of ice thickness strongly improves ice concentration, ice thickness and snow depth, while the snow observations have a smaller but still positive short-term effect on snow depth and sea-ice concentration. In our study, the seasonal forecast showed that assimilating snow depth led to a less accurate long-term estimation of sea-ice extent compared to the other assimilation systems. The other three gave similar results. The improvements due to assimilation were found to last for at least 3-4 months, but possibly even longer.
2018
A sea-effect snowfall accumulated a national record-breaking snowdrift of 73 cm in Merikarvia, on the west coast of Finland, in less than one day on 8 January 2016. A good understanding of such heavy sea-effect snowfalls in the present climate is essential if we want to assess the probability of their occurrence and intensity in the future. Since very few in situ observations were made of the Merikarvia snowfall event in the sea area where the convection cells developed, we investigated the case with an ERA5 reanalysis, the Global Navigation Satellite System (GNSS), and the numerical weather prediction model HARMONIE, using weather radar information as a reference. We aimed to study the feasibility of the reanalysis and GNSS methods for investigating the basic characteristics of the snowband. In addition, we examined whether the assimilation of observed radar reflectivities could improve the HARMONIE simulations. In addition to snowfall patterns, the vertical structure of the atmosp...
Model experiments on snow and ice thermodynamics in the Arctic Ocean with CHINARE 2003 data
Journal of Geophysical Research, 2008
1] Snow and ice thermodynamics over the Arctic Ocean were simulated applying a one-dimensional model. A number of numerical experiments in synoptic (10 days in early autumn) and seasonal (May-September) scales were carried out to investigate the impact of external forcing, snow physics, and the model resolution: the number of layers in both snow and ice ranged from 3 to 40. The model forcing was based on in situ observations carried out in 2003 during the Chinese National Arctic Research Expedition (CHINARE) as well as on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR). The model results were compared against the results of the ECMWF and NCEP/NCAR sea ice schemes. The ECMWF operational precipitation forecasts yielded realistic seasonal snowfall, while the precipitation in NCEP/NCAR reanalysis was unrealistically large. A good result on snow thickness evolution also strongly depended on the accuracy of modeled snowmelt. A time-dependent surface albedo parameterization was critical for the seasonal evolution of snow and ice thickness. Application of 15-20 model levels in snow and ice is recommended as it (1) ensured good reproduction of the vertical snow/ice temperature profile also when solar radiation was large, (2) decreased the sensitivity of snow and ice mass balance to changes in surface albedo, (3) enabled the calculation of subsurface melting of snow and ice, and (4) reasonably reproduced the superimposed ice formation and onset of ice melt. In autumn, however, the accuracy of atmospheric forcing was more important than the model resolution.