scholarly journals Abrupt transitions in an atmospheric single-column model with weak temperature gradient approximation

2020 ◽  
Vol 1 (2) ◽  
pp. 389-404
Author(s):  
Benjamin A. Stephens ◽  
Charles S. Jackson
Keyword(s):  
Temperature Gradient ◽  
Large Scale ◽  
Global Climate ◽  
Deep Convection ◽  
Evaporative Cooling ◽  
Ice Age ◽  
Free Troposphere ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. We document a feature of the tropical atmosphere that could be relevant to episodes of abrupt transitions in global climate that regularly occurred during the last ice age. Using a single-column model (SCM) incorporating the weak temperature gradient (WTG) approximation, we find that abrupt transitions occur as the sea surface temperature is steadily increased. Because these transitions arise from the interplay between local deep convection and the large-scale adjustments that are required to maintain weak temperature and pressure gradients, they are only present with the WTG approximation relevant for the tropics but may be of interest as a trigger for abrupt transitions in global climate. These transitions are marked by an abrupt change in the partitioning of rainfall between convective and large-scale (microphysics) subroutines in addition to various other features of the column, including cloudiness, vertical velocity, temperature, and humidity. We conclude that the transitions are initiated by a failure of evaporative cooling in the lower free troposphere. This leads to lower-column heating and a burst of convection that heats the upper free troposphere, increasing the large-scale rainfall rate, which allows for sufficient evaporative cooling to restabilize the column.

scholarly journals Abrupt transitions in an atmospheric single-column model with weak temperature gradient approximation

2020 ◽  
Author(s):  
Benjamin A. Stephens ◽  
Charles S. Jackson
Keyword(s):  
Temperature Gradient ◽  
Large Scale ◽  
Global Climate ◽  
Evaporative Cooling ◽  
Ice Age ◽  
Free Troposphere ◽  
Column Model ◽  
Single Column ◽  
Single Column Model ◽  
Lower Column

Abstract. We document a feature of the tropical atmosphere that could be relevant to episodes of abrupt transitions in global climate that regularly occurred during the last ice age. Using a single-column model incorporating the weak temperature gradient (WTG) approximation, we find that abrupt transitions occur as the sea surface temperature is steadily increased. Because these transitions arise from the interplay of scales between local deep convection and the large-scale adjustments that are required to maintain weak temperature and pressure gradients, they are only present with the WTG approximation relevant for the tropics but may be of interest as a trigger for abrupt transitions in global climate. These transitions are marked by an abrupt change in the partitioning of rainfall between convective and large-scale (microphysics) subroutines, in addition to various other features of the column including cloudiness, vertical velocity, temperature, and humidity. We conclude that the transitions are initiated by a failure of evaporative cooling in the lower free troposphere. This leads to lower-column heating and a burst of convection that heats the upper free troposphere, increasing the large-scale rainfall rate and re-stabilizing the lower-column evaporative cooling.

scholarly journals Using a single column model (SGRIST1.0) for connecting model physics and dynamics in the Global-to-Regional Integrated forecast SysTem (GRIST-A20.8)

2020 ◽  
Author(s):  
Xiaohan Li ◽  
Yi Zhang ◽  
Xindong Peng ◽  
Jian Li
Keyword(s):  
Reference Model ◽  
Deep Convection ◽  
Operator Splitting ◽  
Shallow Convection ◽  
Forecast System ◽  
Time Step ◽  
Detailed Model ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. A single column model (SGRIST1.0) is developed as a tool for coupling a full-physics package (from Community Atmosphere Model, version 5 (CAM5)) to the Global-to-Regional Integrated forecast System (GRIST). In a two-step approach, the full-physics package is first isolated and coupled to SGRIST1.0 for reducing the uncertainties associated with model physics and assessing its behavior, then assimilated by the model dynamical framework. In the first step, SGRIST1.0 serves as a tool for evaluating the physical parameterization suite in the absence of 3D dynamics. Three single column model test cases, including the tropical deep convection, shallow convection, and stratocumulus, demonstrate that the parameterization suite mimics the behaviors in the observations and the reference model (SCAM) outputs. Cloud fraction, cloud liquid, and some other micro- and macro-physical variables are sensitive to the model time step, suggesting time-step dependency of the corresponding parameterization schemes. The second step couples the physics package to the 3D dynamical modeling system, and the verified parameterization suite works well in GRIST. Two physics-dynamics coupling strategies are examined and found to have a clear impact on the intensity of the simulated storm. The incremental operator splitting strategy (ptend_f1_f1), produces a weaker storm than the pure operator splitting strategy (ptend_f2_sudden). Comparing these two splitting approaches, the ptend_f2_sudden coupling strategy has higher large-step stability than the ptend_f1_f1 option, but the intensity of the simulated storm is substantially reduced by ptend_f2_sudden provided that the time step becomes quite large. Some detailed model configuration strategies are suggested when using the CAM5 parameterization suite in GRIST.

scholarly journals Modeling the Interaction between Quasigeostrophic Vertical Motion and Convection in a Single Column

2016 ◽  
Vol 73 (3) ◽  
pp. 1101-1117 ◽  
Author(s):  
Ji Nie ◽  
Adam H. Sobel
Keyword(s):  
Large Scale ◽  
Diabatic Heating ◽  
Vertical Motion ◽  
Large Set ◽  
Strongly Coupled ◽  
Column Model ◽  
Single Column ◽  
Single Column Model ◽  
Cloud Resolving Model ◽  
The Stability

Abstract A single-column modeling approach is proposed to study the interaction between convection and large-scale dynamics using the quasigeostrophic (QG) framework. This approach extends the notion of “parameterization of large-scale dynamics,” previously applied in the tropics via the weak temperature gradient approximation and other comparable methods, to the extratropics, where balanced adiabatic dynamics plays a larger role in inducing large-scale vertical motion. The diabatic heating in an air column is resolved numerically by a single-column model or a cloud-resolving model. The large-scale vertical velocity, which controls vertical advection of temperature and moisture, is computed through the QG omega equation including the dry adiabatic terms and the diabatic heating term. The component due to diabatic heating can be thought of as geostrophic adjustment to that heating and couples the convection to the large-scale vertical motion. The approach is demonstrated using two representations of convection: a single-column model and linear response functions derived by Z. Kuang from a large set of cloud-resolving simulations. The results are qualitatively similar in both cases. The behavior of convection that is strongly coupled to large-scale dynamics is significantly different from that in the uncoupled case. The positive feedback of the diabatic heating on the large-scale vertical motion reduces the stability of the system, extends the decay time scale after initial perturbations, and increases the amplitude of convective responses to transient large-scale perturbations or imposed forcings. The diabatic feedback of convection on vertical motion is strongest for horizontal wavelengths on the order of the Rossby deformation radius.

scholarly journals Introduction of prognostic rain in ECHAM5: design and single column model simulations

2008 ◽  
Vol 8 (11) ◽  
pp. 2949-2963 ◽  
Author(s):  
R. Posselt ◽  
U. Lohmann
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Cloud Microphysics ◽  
Rain Water ◽  
Time Step ◽  
Surface Precipitation ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-PROG). To this end, a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in the atmosphere to be available for the next time step. Rain formation in ECHAM5-PROG is, therefore, less dependent on the autoconversion rate than the standard ECHAM5 but shifts the emphasis towards the accretion rates in accordance with observations. ECHAM5-PROG is tested and evaluated with Single Column Model (SCM) simulations for two cases: the marine stratocumulus study EPIC (October 2001) and the continental mid-latitude ARM Cloud IOP (shallow frontal cloud case – March 2000). In case of heavy precipitation events, the prognostic equations for rain hardly affect the amount and timing of precipitation at the surface in different SCM simulations because heavy rain depends mainly on the large-scale forcing. In case of thin, drizzling clouds (i.e., stratocumulus), surface precipitation is sensitive to the number of sub-time steps used in the prognostic rain scheme. Cloud microphysical quantities, such as cloud liquid and rain water within the atmosphere, are sensitive to the number of sub-time steps in both considered cases. This results from the decreasing autoconversion rate and increasing accretion rate.

Evaluation of the NASA GISS Single-Column Model Simulated Clouds Using Combined Surface and Satellite Observations

2010 ◽  
Vol 23 (19) ◽  
pp. 5175-5192 ◽  
Author(s):  
Aaron D. Kennedy ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Patrick Minnis ◽  
Anthony D. Del Genio ◽  
...  
Keyword(s):  
Great Plains ◽  
Large Scale ◽  
Department Of Energy ◽  
Column Model ◽  
Low Clouds ◽  
Single Column ◽  
Single Column Model ◽  
Regional Reanalysis ◽  
Cloud Tops ◽  
High Clouds

Abstract Three years of surface and Geostationary Operational Environmental Satellite (GOES) data from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to evaluate the NASA GISS Single Column Model (SCM) simulated clouds from January 1999 to December 2001. The GOES-derived total cloud fractions for both 0.5° and 2.5° grid boxes are in excellent agreement with surface observations, suggesting that ARM point observations can represent large areal observations. Low (<2 km), middle (2–6 km), and high (>6 km) levels of cloud fractions, however, have negative biases as compared to the ARM results due to multilayer cloud scenes that can either mask lower cloud layers or cause misidentifications of cloud tops. Compared to the ARM observations, the SCM simulated most midlevel clouds, overestimated low clouds (4%), and underestimated total and high clouds by 7% and 15%, respectively. To examine the dependence of the modeled high and low clouds on the large-scale synoptic patterns, variables such as relative humidity (RH) and vertical pressure velocity (omega) from North American Regional Reanalysis (NARR) data are included. The successfully modeled and missed high clouds are primarily associated with a trough and ridge upstream of the ARM SGP, respectively. The PDFs of observed high and low occurrence as a function of RH reveal that high clouds have a Gaussian-like distribution with mode RH values of ∼40%–50%, whereas low clouds have a gammalike distribution with the highest cloud probability occurring at RH ∼75%–85%. The PDFs of modeled low clouds are similar to those observed; however, for high clouds the PDFs are shifted toward higher values of RH. This results in a negative bias for the modeled high clouds because many of the observed clouds occur at RH values below the SCM-specified stratiform parameterization threshold RH of 60%. Despite many similarities between PDFs derived from the NARR and ARM forcing datasets for RH and omega, differences do exist. This warrants further investigation of the forcing and reanalysis datasets.

scholarly journals Introduction of prognostic rain in ECHAM5: design and Single Column Model simulations

2007 ◽  
Vol 7 (5) ◽  
pp. 14675-14706 ◽  
Author(s):  
R. Posselt ◽  
U. Lohmann
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Cloud Microphysics ◽  
Rain Water ◽  
Time Step ◽  
Surface Precipitation ◽  
Column Model ◽  
Single Column ◽  
Single Column Model

Abstract. Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-RAIN). For this a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in the atmosphere to be available for the next time step. Rain formation in ECHAM5-RAIN is, therefore, less dependent on the autoconversion rate than the standard ECHAM5 but shifts the emphasis towards the accretion rates in accordance with observations. ECHAM5-RAIN is tested and evaluated with two cases: the continental mid-latitude ARM Cloud IOP (shallow frontal cloud case – March 2000) and EPIC (a marine stratocumulus study – October 2001). The prognostic equations for rain hardly affect the amount and timing of precipitation at the surface in different Single Column Model (SCM) simulations for heavy precipitating clouds because heavy rain depends mainly on the large-scale forcing. In case of thin, drizzling clouds (i.e., stratocumulus), an increase in surface precipitation is caused by more sub-time steps used in the prognostic rain scheme until convergence is reached. Cloud microphysical quantities, such as liquid and rain water, are more sensitive to the number of sub-time steps for light precipitation. This results from the decreasing autoconversion rate and increasing accretion rate.

scholarly journals Cloud Properties Simulated by a Single-Column Model. Part I: Comparison to Cloud Radar Observations of Cirrus Clouds

2005 ◽  
Vol 62 (5) ◽  
pp. 1428-1445 ◽  
Author(s):  
Yali Luo ◽  
Steven K. Krueger ◽  
Shrinivas Moorthi
Keyword(s):  
Large Scale ◽  
Cirrus Clouds ◽  
Radar Observations ◽  
Column Model ◽  
Cloud Radar ◽  
Single Column ◽  
Single Column Model ◽  
The Mean ◽  
Horizontal Inhomogeneity ◽  
Ice Water

Abstract This study describes and demonstrates a new method for identifying deficiencies in how cloud processes are represented in large-scale models. Kilometer-scale-resolving cloud radar observations and cloud-resolving model (CRM) simulations were used to evaluate the representation of cirrus clouds in the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model for a 29-day period during June and July 1997 at the Atmospheric Radiation Measurement Program site in Oklahoma. To produce kilometer-scale cirrus statistics from the SCM results, synthetic subgrid-scale (SGS) cloud fields were generated using the SCM’s cloud fraction and hydrometeor content profiles, and the SCM’s cloud overlap and horizontal inhomogeneity assumptions. Three sets of SCM synthetic SGS cloud fields were analyzed. Two NOSNOW sets were produced in which clouds did not include snow; one set used random overlap, the other, maximum/random. In the SNOW set, clouds included snow and random overlap was used. The three sets were sampled in the same way as the cloud-radar-detected cloud fields and the CRM-simulated cloud fields. The mean cirrus cloud occurrence frequency for the SCM NOSNOW cloud fields agrees with the observed value as well as the CRM’s does, while that for SCM SNOW cloud fields is only half that observed. In most aspects, the SCM’s cirrus properties differ significantly from the cloud radar’s and the CRM’s, which generally agree. In comparison, there are too many physically thin SCM NOSNOW cirrus layers (most occupy only a single model layer) and too many physically thick SCM SNOW cirrus layers (most are thicker than 4 km). For the optically thin subset of cirrus layers, 1) the mean, mode, and median ice water path, and layer-mean ice water content (IWC) values for the SCM are significantly larger than the observed and CRM values; 2) the SCM layer-mean IWCs decrease with cloud physical thickness, opposite to the observations and CRM results; and 3) the range of layer-mean effective radii in the SCM thin cirrus is too narrow.

Sign in / Sign up

Export Citation Format

Share Document