scholarly journals Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

2017 ◽  
Vol 56 (10) ◽  
pp. 2821-2844 ◽  
Author(s):  
Eun-Gyeong Yang ◽  
Hyun Mee Kim
Keyword(s):  
Relative Humidity ◽  
East Asia ◽  
Geopotential Height ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Lower Troposphere ◽  
Near Surface ◽  
Skill Scores ◽  
Regional Reanalysis

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

scholarly journals Dominant Anomaly Patterns in the Near-Surface Baroclinicity and Accompanying Anomalies in the Atmosphere and Oceans. Part II: North Pacific Basin

2010 ◽  
Vol 23 (24) ◽  
pp. 6445-6467 ◽  
Author(s):  
Mototaka Nakamura ◽  
Shozo Yamane
Keyword(s):  
Heat Flux ◽  
North Pacific ◽  
Spatial Scales ◽  
Baroclinic Instability ◽  
Lower Troposphere ◽  
Pacific Basin ◽  
Mean Flow ◽  
Near Surface ◽  
Eddy Heat Flux ◽  
North Pacific Basin

Abstract Variability in the monthly-mean flow and storm track in the North Pacific basin is examined with a focus on the near-surface baroclinicity. Dominant patterns of anomalous near-surface baroclinicity found from empirical orthogonal function (EOF) analyses generally show mixed patterns of shift and changes in the strength of near-surface baroclinicity. Composited anomalies in the monthly-mean wind at various pressure levels based on the signals in the EOFs show accompanying anomalies in the mean flow up to 50 hPa in the winter and up to 100 hPa in other seasons. Anomalous eddy fields accompanying the anomalous near-surface baroclinicity patterns exhibit, broadly speaking, structures anticipated from simple linear theories of baroclinic instability, and suggest a tendency for anomalous wave fluxes to accelerate–decelerate the surface westerly accordingly. However, the relationship between anomalous eddy fields and anomalous near-surface baroclinicity in the midwinter is not consistent with the simple linear baroclinic instability theories. Composited anomalous sea surface temperature (SST) accompanying anomalous near-surface baroclinicity often exhibits moderate values and large spatial scales in the basin, rather than large values concentrated near the oceanic fronts. In the midsummer and in some cases in cold months, however, large SST anomalies are found around the Kuroshio–Oyashio Extensions. Accompanying anomalies in the net surface heat flux, SST in the preceding and following months, and meridional eddy heat flux in the lower troposphere suggest active roles played by the ocean in generating the concomitant anomalous large-scale atmospheric state in some of these cases.

scholarly journals High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

2015 ◽  
Vol 8 (8) ◽  
pp. 2645-2653 ◽  
Author(s):  
C. G. Nunalee ◽  
Á. Horváth ◽  
S. Basu
Keyword(s):  
High Resolution ◽  
Vortex Shedding ◽  
Weather Prediction ◽  
Surface Wind ◽  
Wrf Model ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
Nwp Model ◽  
Height Data

Abstract. Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP) modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL), is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF) model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30), the Shuttle Radar Topography Mission (SRTM), and the Global Multi-resolution Terrain Elevation Data set (GMTED2010) terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.

scholarly journals Wintertime Subkilometer Numerical Forecasts of Near-Surface Variables in the Canadian Rocky Mountains

2015 ◽  
Vol 143 (2) ◽  
pp. 666-686 ◽  
Author(s):  
Vincent Vionnet ◽  
Stéphane Bélair ◽  
Claude Girard ◽  
André Plante
Keyword(s):  
Relative Humidity ◽  
High Altitude ◽  
Rocky Mountains ◽  
Weather Prediction ◽  
Slope Angle ◽  
Forecast Accuracy ◽  
Surface Radiation ◽  
Canadian Rocky Mountains ◽  
Grid Spacing ◽  
Near Surface

Abstract Numerical weather prediction (NWP) systems operational at many national centers are nowadays used at the kilometer scale. The next generation of NWP models will provide forecasts at the subkilometer scale. Large impacts are expected in mountainous terrain characterized by highly variable orography. This study investigates the ability of the Canadian NWP system to provide an accurate forecast of near-surface variables at the subkilometer scale in the Canadian Rocky Mountains in wintertime when the region is fully covered by snow. Observations collected at valley and high-altitude stations are used to evaluate forecast accuracy at three different grid spacing (2.5, 1, and 0.25 km) over a period of 15 days. Decreasing grid spacing was found to improve temperature forecasts at high-altitude stations because of better orography representation. In contrast, no improvement is obtained at valley stations due to an inability of the model to fully capture at all resolutions the intensity of valley cold pools forming during nighttime. Errors in relative humidity reveal that the model tends to overestimate relative humidity at all resolutions, without improvement with decreasing grid spacing. Wind speed forecasts show large improvements with decreasing grid spacing for high-altitude stations exposed to or sheltered from wind. However, no systematic improvement with decreasing grid spacing is found for all stations, which is similar to previous studies. In addition, the model’s sensitivity at subkilometer grid spacing is investigated by evaluating the effects of (i) accounting for additional drag generated by subgrid orographic features, (ii) considering slope angle and aspect on surface radiation, and (iii) using high-resolution initialization for the surface fields.

scholarly journals EnKF Assimilation of High-Resolution, Mobile Doppler Radar Data of the 4 May 2007 Greensburg, Kansas, Supercell into a Numerical Cloud Model

2013 ◽  
Vol 141 (2) ◽  
pp. 625-648 ◽  
Author(s):  
Robin L. Tanamachi ◽  
Louis J. Wicker ◽  
David C. Dowell ◽  
Howard B. Bluestein ◽  
Daniel T. Dawson ◽  
...  
Keyword(s):  
Wind Profile ◽  
Doppler Radar ◽  
Cloud Model ◽  
Weather Prediction ◽  
Surface Wind ◽  
Radar Data ◽  
Data Availability ◽  
Cold Pool ◽  
Near Surface ◽  
Doppler Radar Data

Abstract Mobile Doppler radar data, along with observations from a nearby Weather Surveillance Radar-1988 Doppler (WSR-88D), are assimilated with an ensemble Kalman filter (EnKF) technique into a nonhydrostatic, compressible numerical weather prediction model to analyze the evolution of the 4 May 2007 Greensburg, Kansas, tornadic supercell. The storm is simulated via assimilation of reflectivity and velocity data in an initially horizontally homogeneous environment whose parameters are believed to be a close approximation to those of the Greensburg supercell inflow sector. Experiments are conducted to test analysis sensitivity to mobile radar data availability and to the mean environmental near-surface wind profile, which was changing rapidly during the simulation period. In all experiments, a supercell with similar location and evolution to the observed storm is analyzed, but the simulated storm’s characteristics differ markedly. The assimilation of mobile Doppler radar data has a much greater impact on the resulting analyses, particularly at low altitudes (≤2 km), than modifications to the near-surface environmental wind profile. Differences in the analyzed updrafts, vortices, cold pool structure, rear-flank gust front structure, and observation-space diagnostics are documented. An analyzed vortex corresponding to the enhanced Fujita scale 5 (EF-5) Greensburg tornado is stronger and deeper in experiments in which mobile (higher resolution) Doppler radar data are included in the assimilation. This difference is linked to stronger analyzed horizontal convergence, which in turn is associated with increased stretching of vertical vorticity. Changing the near-surface wind profile appears to impact primarily the updraft strength, availability of streamwise vorticity for tilting into the vertical, and low-level vortex strength and longevity.

scholarly journals Forecasting global atmospheric CO<sub>2</sub>

2014 ◽  
Vol 14 (9) ◽  
pp. 13909-13962 ◽  
Author(s):  
A. Agustí-Panareda ◽  
S. Massart ◽  
F. Chevallier ◽  
S. Boussetta ◽  
G. Balsamo ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Real Time ◽  
Diurnal Cycle ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Physical Models ◽  
Atmospheric Co2 ◽  
Co2 Fluxes ◽  
Near Surface ◽  
Forecasting System

Abstract. A new global atmospheric carbon dioxide (CO2) real-time forecast is now available as part of the pre-operational Monitoring of Atmospheric Composition and Climate – Interim Implementation (MACC-II) service using the infrastructure of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). One of the strengths of the CO2 forecasting system is that the land surface, including vegetation CO2 fluxes, is modelled online within the IFS. Other CO2 fluxes are prescribed from inventories and from off-line statistical and physical models. The CO2 forecast also benefits from the transport modelling from a state-of-the-art numerical weather prediction (NWP) system initialized daily with a wealth of meteorological observations. This paper describes the capability of the forecast in modelling the variability of CO2 on different temporal and spatial scales compared to observations. The modulation of the amplitude of the CO2 diurnal cycle by near-surface winds and boundary layer height is generally well represented in the forecast. The CO2 forecast also has high skill in simulating day-to-day synoptic variability. In the atmospheric boundary layer, this skill is significantly enhanced by modelling the day-to-day variability of the CO2 fluxes from vegetation compared to using equivalent monthly mean fluxes with a diurnal cycle. However, biases in the modelled CO2 fluxes also lead to accumulating errors in the CO2 forecast. These biases vary with season with an underestimation of the amplitude of the seasonal cycle both for the CO2 fluxes compared to total optimized fluxes and the atmospheric CO2 compared to observations. The largest biases in the atmospheric CO2 forecast are found in spring, corresponding to the onset of the growing season in the Northern Hemisphere. In the future, the forecast will be re-initialized regularly with atmospheric CO2 analyses based on the assimilation of CO2 satellite retrievals, as they become available in near-real time. In this way, the accumulation of errors in the atmospheric CO2 forecast will be reduced. Improvements in the CO2 forecast are also expected with the continuous developments in the operational IFS.

scholarly journals An experimental 2DVAR retrieval using AMSR2

2019 ◽  
Author(s):  
David Ian Duncan ◽  
Patrick Eriksson ◽  
Simon Pfreundschuh
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Spatial Scales ◽  
Surface Wind ◽  
Optimal Estimation ◽  
Surface Wind Speed ◽  
Model Errors ◽  
Near Surface ◽  
Noise Characteristics ◽  
Microwave Imager

Abstract. A two-dimensional variational retrieval (2DVAR) is presented for a passive microwave imager. The overlapping antenna patterns of all frequencies from the Advanced Microwave Scanning Radiometer-2 (AMSR2) are explicitly simulated to attempt retrieval of near surface wind speed and surface skin temperature at finer spatial scales than individual antenna beams. This is achieved, with the effective spatial resolution of retrieved parameters shown by analysis of 2DVAR averaging kernels. Sea surface temperature retrievals achieve about 30 km resolution, with wind speed retrievals at about 10 km resolution. It is argued that multi-dimensional optimal estimation permits greater use of total information content from microwave sensors than other methods, with no compromises on target resolution needed; instead, various targets are retrieved at the highest possible spatial resolution, driven by the channels' sensitivities. All AMSR2 channels can be simulated within near their published noise characteristics for observed clear-sky scenes, though calibration and emissivity model errors are key challenges. This experimental retrieval shows the feasibility of 2DVAR for cloud-free retrievals, and opens the possibility of standalone 3DVAR retrievals of water vapour and hydrometeor fields from microwave imagers in the future. The results have implications for future satellite missions and sensor design, as spatial oversampling can somewhat mitigate the need for larger antennas in the push for higher spatial resolution.

Assessing reasons for skilful predictions of winter windstorms over the Atlantic/European region

2020 ◽  
Author(s):  
Lisa Degenhardt ◽  
Gregor Leckebusch ◽  
Adam Scaife
Keyword(s):  
Large Scale ◽  
Surface Wind ◽  
Forecast Model ◽  
Surface Wind Speed ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Seasonal Forecasts ◽  
Financial Industry ◽  
Near Surface ◽  
Skill Scores

&lt;p&gt;Severe Atlantic winter storms are affecting densely populated regions of Europe (e.g. UK, France, Germany, etc.). Consequently, different parts of the society, financial industry (e.g., insurance) and last but not least the general public are interested in skilful forecasts for the upcoming storm season (usually December to March). To allow for a best possible use of steadily improved seasonal forecasts, the understanding which factors contribute to realise forecast skill is essential and will allow for an assessment whether to expect a forecast to be skilful or not.&lt;/p&gt;&lt;p&gt;This study analyses the predictability of the seasonal forecast model of the UK MetOffice, the GloSea5. Windstorm events are identified and tracked following Leckebusch et al. (2008) via the exceedance of the 98&lt;sup&gt;th&lt;/sup&gt; percentile of the near surface wind speed.&lt;/p&gt;&lt;p&gt;Seasonal predictability of windstorm frequency in comparison to observations (based e.g., on ERA5 reanalysis) are calculated and different statistical methods (skill scores) are compared.&lt;/p&gt;&lt;p&gt;Large scale patterns (e.g., NAO, AO, EAWR, etc.) and dynamical factors (e.g., Eady Growth Rate) are analysed and their predictability is assessed in comparison to storm frequency forecast skill. This will lead to an idea how the forecast skill of windstorms is depending on the forecast skill of forcing factors conditional to the phase of large-scale variability modes. Thus, we deduce information, which factors are most important to generate seasonal forecast skill for severe extra-tropical windstorms.&lt;/p&gt;&lt;p&gt;The results can be used to get a better understanding of the resulting skill for the upcoming windstorm season.&lt;/p&gt;

scholarly journals A Reliability Assessment of the NCEP/FNL Reanalysis Data in Depicting Key Meteorological Factors on Clean Days and Polluted Days in Beijing

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 481
Author(s):  
Chao Liu ◽  
Jianping Guo ◽  
Bihui Zhang ◽  
Hengde Zhang ◽  
Panbo Guan ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Meteorological Factors ◽  
Surface Wind ◽  
Lower Boundary ◽  
Temperature Inversion ◽  
Surface Wind Speed ◽  
Reanalysis Data ◽  
Near Surface ◽  
The Difference

In this study, based on the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data, the reliability and performances of their application on clean days and polluted days (based on the PM2.5 mass concentrations) in Beijing were assessed. Conventional meteorological factors and diagnostic physical quantities from the NCEP/FNL data were compared with the L-band radar observations in Beijing in the autumns and winters of 2017–2019. The results indicate that the prediction reliability of the temperature was the best compared with those of the relative humidity and wind speed. It is worth noting that the relative humidity was lower and the near-surface wind speed was higher on polluted days from the NCEP/FNL data than from the observations. As far as diagnostic physical quantity is concerned, it was revealed that the temperature inversion intensity depicted by the NCEP/FNL data was significantly lower than that from the observations, especially on polluted days. For example, the difference in the temperature inversion intensity between the NCEP/FNL data and the observation ranged from −0.56 to −0.77 °C on polluted days. In addition, the difference in the wind shears between the NCEP/FNL reanalysis data and the observations increased to 0.40 m/s in the lower boundary layer on polluted days compared with that on clean days. Therefore, it is suggested that the underestimation of the relative humidity and temperature inversion intensity, and the overestimation of the near-surface wind speed should be seriously considered in simulating the air quality in the model, particularly on polluted days, which should be focused on more in future model developments.

scholarly journals Downscaling surface wind predictions from numerical weather prediction models in complex terrain with WindNinja

2016 ◽  
Author(s):  
N. S. Wagenbrenner ◽  
J. M. Forthofer ◽  
B. K. Lamb ◽  
K. S. Shannon ◽  
B. W. Butler
Keyword(s):  
Numerical Weather Prediction ◽  
Complex Terrain ◽  
Prediction Models ◽  
Wildland Fire ◽  
Weather Prediction ◽  
Surface Wind ◽  
Atmospheric Stability ◽  
Wind Model ◽  
Near Surface ◽  
Numerical Weather

Abstract. Wind predictions in complex terrain are important for a number of applications. Dynamic downscaling of numerical weather prediction (NWP) model winds with a high resolution wind model is one way to obtain a wind forecast that accounts for local terrain effects, such as wind speed-up over ridges, flow channeling in valleys, flow separation around terrain obstacles, and flows induced by local surface heating and cooling. In this paper we investigate the ability of a mass-consistent wind model for downscaling near-surface wind predictions from four NWP models in complex terrain. Model predictions are compared with surface observations from a tall, isolated mountain. Downscaling improved near-surface wind forecasts under high-wind (near-neutral atmospheric stability) conditions. Results were mixed during upslope and downslope (non-neutral atmospheric stability) flow periods, although wind direction predictions generally improved with downscaling. This work constitutes evaluation of a diagnostic wind model at unprecedented high spatial resolution in terrain with topographical ruggedness approaching that of typical landscapes in the western US susceptible to wildland fire.

scholarly journals Evaluation of Arctic cloud products from the EUMETSAT Climate Monitoring Satellite Application Facility based on CALIPSO-CALIOP observations

2009 ◽  
Vol 9 (4) ◽  
pp. 16755-16810 ◽  
Author(s):  
K.-G. Karlsson ◽  
A. Dybbroe
Keyword(s):  
Weather Prediction ◽  
Lower Troposphere ◽  
Arctic Region ◽  
Numerical Weather Prediction Model ◽  
The Arctic ◽  
Cloud Type ◽  
Near Surface ◽  
Noaa Avhrr ◽  
Climate Monitoring ◽  
June July

Abstract. The performance of the three cloud products cloud fractional cover, cloud type and cloud top height, derived from NOAA AVHRR data and produced by the EUMETSAT Climate Monitoring Satellite Application Facility, has been evaluated in detail over the Arctic region for four months in 2007 using CALIPSO-CALIOP observations. The evaluation was based on 142 selected NOAA/Metop overpasses allowing almost 400 000 individual matchups between AVHRR pixels and CALIOP measurements distributed approximately equally over the studied months (June, July, August and December 2007). Results suggest that estimations of cloud amounts are very accurate during the polar summer season while a substantial loss of detected clouds occurs in the polar winter. Evaluation results for cloud type and cloud top products point at specific problems related to the existence of near isothermal conditions in the lower troposphere in the polar summer and the use of reference vertical temperature profiles from Numerical Weather Prediction model analyses. The latter are currently not detailed enough in describing true conditions relevant on the pixel scale. This concerns especially the description of near-surface temperature inversions which are often too weak leading to large errors in interpreted cloud top heights.

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