Impacts of Shallow Convection Processes on a Simulated Boreal Summer Climatology in a Global Atmospheric Model

2018 ◽  
Vol 54 (S1) ◽  
pp. 361-370 ◽  
Author(s):  
Song-You Hong ◽  
Jihyeon Jang
Keyword(s):  
Atmospheric Model ◽  
Boreal Summer ◽  
Shallow Convection ◽  
Global Atmospheric Model

scholarly journals Characteristics of convective snow bands along the Swedish east coast

2017 ◽  
Vol 8 (1) ◽  
pp. 163-175 ◽  
Author(s):  
Julia Jeworrek ◽  
Lichuan Wu ◽  
Christian Dieterich ◽  
Anna Rutgersson
Keyword(s):  
Regional Climate Model ◽  
East Coast ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
Atmospheric Model ◽  
Ocean Model ◽  
Sea Surface ◽  
Precipitation Rate ◽  
Shallow Convection

Abstract. Convective snow bands develop in response to a cold air outbreak from the continent or the frozen sea over the open water surface of lakes or seas. The comparatively warm water body triggers shallow convection due to increased heat and moisture fluxes. Strong winds can align with this convection into wind-parallel cloud bands, which appear stationary as the wind direction remains consistent for the time period of the snow band event, delivering enduring snow precipitation at the approaching coast. The statistical analysis of a dataset from an 11-year high-resolution atmospheric regional climate model (RCA4) indicated 4 to 7 days a year of moderate to highly favourable conditions for the development of convective snow bands in the Baltic Sea region. The heaviest and most frequent lake effect snow was affecting the regions of Gävle and Västervik (along the Swedish east coast) as well as Gdansk (along the Polish coast). However, the hourly precipitation rate is often higher in Gävle than in the Västervik region. Two case studies comparing five different RCA4 model setups have shown that the Rossby Centre atmospheric regional climate model RCA4 provides a superior representation of the sea surface with more accurate sea surface temperature (SST) values when coupled to the ice–ocean model NEMO as opposed to the forcing by the ERA-40 reanalysis data. The refinement of the resolution of the atmospheric model component leads, especially in the horizontal direction, to significant improvement in the representation of the mesoscale circulation process as well as the local precipitation rate and area by the model.

scholarly journals An efficient training scheme for supermodels

2017 ◽  
Vol 8 (2) ◽  
pp. 429-438 ◽  
Author(s):  
Francine J. Schevenhoven ◽  
Frank M. Selten
Keyword(s):  
Climate Models ◽  
State Of The Art ◽  
Atmospheric Model ◽  
High Dimensional ◽  
Model Errors ◽  
Global Atmospheric Model ◽  
Training Scheme ◽  
Skill Scores ◽  
Weather And Climate ◽  
The Individual

Abstract. Weather and climate models have improved steadily over time as witnessed by objective skill scores, although significant model errors remain. Given these imperfect models, predictions might be improved by combining them dynamically into a so-called supermodel. In this paper a new training scheme to construct such a supermodel is explored using a technique called cross pollination in time (CPT). In the CPT approach the models exchange states during the prediction. The number of possible predictions grows quickly with time, and a strategy to retain only a small number of predictions, called pruning, needs to be developed. The method is explored using low-order dynamical systems and applied to a global atmospheric model. The results indicate that the CPT training is efficient and leads to a supermodel with improved forecast quality as compared to the individual models. Due to its computational efficiency, the technique is suited for application to state-of-the art high-dimensional weather and climate models.

scholarly journals The Brazilian Global Atmospheric Model (BAM): Performance for Tropical Rainfall Forecasting and Sensitivity to Convective Scheme and Horizontal Resolution

2016 ◽  
Vol 31 (5) ◽  
pp. 1547-1572 ◽  
Author(s):  
Silvio N. Figueroa ◽  
José P. Bonatti ◽  
Paulo Y. Kubota ◽  
Georg A. Grell ◽  
Hugh Morrison ◽  
...  
Keyword(s):  
South America ◽  
Weather Prediction ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Southeastern Brazil ◽  
Rainfall Forecasting ◽  
Dynamical Core ◽  
Tropical Rainfall ◽  
Global Atmospheric Model ◽  
Convective Scheme

Abstract This article describes the main features of the Brazilian Global Atmospheric Model (BAM), analyses of its performance for tropical rainfall forecasting, and its sensitivity to convective scheme and horizontal resolution. BAM is the new global atmospheric model of the Center for Weather Forecasting and Climate Research [Centro de Previsão de Tempo e Estudos Climáticos (CPTEC)], which includes a new dynamical core and state-of-the-art parameterization schemes. BAM’s dynamical core incorporates a monotonic two-time-level semi-Lagrangian scheme, which is carried out completely on the model grid for the tridimensional transport of moisture, microphysical prognostic variables, and tracers. The performance of the quantitative precipitation forecasts (QPFs) from two convective schemes, the Grell–Dévényi (GD) scheme and its modified version (GDM), and two different horizontal resolutions are evaluated against the daily TRMM Multisatellite Precipitation Analysis over different tropical regions. Three main results are 1) the QPF skill was improved substantially with GDM in comparison to GD; 2) the increase in the horizontal resolution without any ad hoc tuning improves the variance of precipitation over continents with complex orography, such as Africa and South America, whereas over oceans there are no significant differences; and 3) the systematic errors (dry or wet biases) remain virtually unchanged for 5-day forecasts. Despite improvements in the tropical precipitation forecasts, especially over southeastern Brazil, dry biases over the Amazon and La Plata remain in BAM. Improving the precipitation forecasts over these regions remains a challenge for the future development of the model to be used not only for numerical weather prediction over South America but also for global climate simulations.

scholarly journals Global atmospheric model for mercury including oxidation by bromine atoms

2010 ◽  
Vol 10 (24) ◽  
pp. 12037-12057 ◽  
Author(s):  
C. D. Holmes ◽  
D. J. Jacob ◽  
E. S. Corbitt ◽  
J. Mao ◽  
X. Yang ◽  
...  
Keyword(s):  
Gas Phase ◽  
Atmospheric Model ◽  
Atmospheric Mercury ◽  
The Arctic ◽  
Deposition Flux ◽  
Mercury Deposition ◽  
Photochemical Reduction ◽  
Global Atmospheric Model ◽  
Summer Maximum ◽  
Southeast Us

Abstract. Global models of atmospheric mercury generally assume that gas-phase OH and ozone are the main oxidants converting Hg0 to HgII and thus driving mercury deposition to ecosystems. However, thermodynamic considerations argue against the importance of these reactions. We demonstrate here the viability of atomic bromine (Br) as an alternative Hg0 oxidant. We conduct a global 3-D simulation with the GEOS-Chem model assuming gas-phase Br to be the sole Hg0 oxidant (Hg + Br model) and compare to the previous version of the model with OH and ozone as the sole oxidants (Hg + OH/O3 model). We specify global 3-D Br concentration fields based on our best understanding of tropospheric and stratospheric Br chemistry. In both the Hg + Br and Hg + OH/O3 models, we add an aqueous photochemical reduction of HgII in cloud to impose a tropospheric lifetime for mercury of 6.5 months against deposition, as needed to reconcile observed total gaseous mercury (TGM) concentrations with current estimates of anthropogenic emissions. This added reduction would not be necessary in the Hg + Br model if we adjusted the Br oxidation kinetics downward within their range of uncertainty. We find that the Hg + Br and Hg + OH/O3 models are equally capable of reproducing the spatial distribution of TGM and its seasonal cycle at northern mid-latitudes. The Hg + Br model shows a steeper decline of TGM concentrations from the tropics to southern mid-latitudes. Only the Hg + Br model can reproduce the springtime depletion and summer rebound of TGM observed at polar sites; the snowpack component of GEOS-Chem suggests that 40% of HgII deposited to snow in the Arctic is transferred to the ocean and land reservoirs, amounting to a net deposition flux to the Arctic of 60 Mg a−1. Summertime events of depleted Hg0 at Antarctic sites due to subsidence are much better simulated by the Hg + Br model. Model comparisons to observed wet deposition fluxes of mercury in the US and Europe show general consistency. However the Hg + Br model does not capture the summer maximum over the southeast US because of low subtropical Br concentrations while the Hg + OH/O3 model does. Vertical profiles measured from aircraft show a decline of Hg0 above the tropopause that can be captured by both the Hg + Br and Hg + OH/O3 models, except in Arctic spring where the observed decline is much steeper than simulated by either model; we speculate that oxidation by Cl species might be responsible. The Hg + Br and Hg + OH/O3 models yield similar global budgets for the cycling of mercury between the atmosphere and surface reservoirs, but the Hg + Br model results in a much larger fraction of mercury deposited to the Southern Hemisphere oceans.

The Impacts of Horizontal Resolution on the Seasonally Dependent Biases of the Northeastern Pacific ITCZ in Coupled Climate Models

2020 ◽  
Vol 33 (3) ◽  
pp. 941-957 ◽  
Author(s):  
Fengfei Song ◽  
Guang J. Zhang
Keyword(s):  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Cmip5 Models ◽  
Boreal Summer ◽  
Easterly Wind ◽  
Boreal Spring ◽  
Southeastern Pacific ◽  
Double Itcz ◽  
Northeastern Pacific ◽  
Wind Bias

ABSTRACTThe double-ITCZ bias has puzzled the climate modeling community for more than two decades. Here we show that, over the northeastern Pacific Ocean, precipitation and sea surface temperature (SST) biases are seasonally dependent in the NCAR CESM1 and 37 CMIP5 models, with positive biases during boreal summer–autumn and negative biases during boreal winter–spring, although the easterly wind bias persists year round. This seasonally dependent bias is found to be caused by the model’s failure to reproduce the climatological seasonal wind reversal of the North American monsoon. During winter–spring, the observed easterly wind dominates, so the simulated stronger wind speed enhances surface evaporation and lowers SST. It is opposite when the observed wind turns to westerly during summer–autumn. An easterly wind bias, mainly evident in the lower troposphere, also occurs in the atmospheric model when the observed SST is prescribed, suggesting that it is of atmospheric origin. When the atmospheric model resolution is doubled in the CESM1, both SST and precipitation are improved in association with the reduced easterly wind bias. During boreal spring, when the double-ITCZ bias is most significant, the northern and southern ITCZ can be improved by 29.0% and 18.8%, respectively, by increasing the horizontal resolution in the CESM1. When dividing the 37 CMIP5 models into two groups on the basis of their horizontal resolutions, it is found that both the seasonally dependent biases over the northeastern Pacific and year-round biases over the southeastern Pacific are reduced substantially in the higher-resolution models, with improvement of ~30% in both regions during boreal spring. Close relationships between wind and precipitation biases over the northeastern and southeastern Pacific are also found among CMIP5 models.

scholarly journals Relative Roles of Background Moisture and Vertical Shear in Regulating Interannual Variability of Boreal Summer Intraseasonal Oscillations

2016 ◽  
Vol 29 (19) ◽  
pp. 7009-7025 ◽  
Author(s):  
Li Deng ◽  
Tim Li
Keyword(s):  
Interannual Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Tropical Indian Ocean ◽  
Atmospheric Model ◽  
Vertical Shear ◽  
Boreal Summer ◽  
Moisture Condition ◽  
Intensity Index ◽  
Intraseasonal Oscillations

Abstract The interannual variability of the boreal summer intraseasonal oscillation (BSISO) is investigated using observed outgoing longwave radiation (OLR) and ERA-Interim data for the period of 1980–2012. It is found that the interannual variability of BSISO intensity is much stronger in the tropical western Pacific (TWP) than the tropical Indian Ocean (TIO). A BSISO intensity index is defined based on a multivariate EOF analysis in TWP. It is found that strong BSISO years are associated with El Niño–like sea surface temperature anomalies in the tropical Pacific, anomalous easterly shear, and enhanced background moisture condition in the region. Using a 2.5-layer atmospheric model with a specified idealized background mean state, the authors further examine the relative roles of background moisture and vertical shear fields in modulating the BSISO intensity. Sensitivity numerical experiments indicate that the background moisture change is most important in regulating the BSISO intensity, whereas the background vertical shear change also plays a role.

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