Search Results

You are looking at 1 - 10 of 25 items for

  • Author or Editor: Andrea Molod x
  • Refine by Access: All Content x
Clear All Modify Search
Andrea Molod

Abstract

Atmospheric general circulation model (AGCM) cloud parameterizations generally include an assumption about the subgrid-scale probability distribution function (PDF) of total water and its vertical profile. In the present study, the Atmospheric Infrared Sounder (AIRS) monthly-mean cloud amount and relative humidity fields are used to compute a proxy for the second moment of an AGCM total water PDF called the “RH01 diagnostic,” which is the AIRS mean relative humidity for cloud fractions of 0.1 or less. The dependence of the second moment on horizontal grid resolution is analyzed using results from a high-resolution global model simulation.

The AIRS-derived RH01 diagnostic is generally larger near the surface than aloft, indicating a narrower PDF near the surface, and varies with the type of underlying surface. High-resolution model results show that the vertical structure of profiles of the AGCM PDF second moment is unchanged as the grid resolution changes from 200 to 100 to 50 km, and that the second-moment profiles shift toward higher values with decreasing grid spacing.

Several Goddard Earth Observing System, version 5 (GEOS-5), AGCM simulations were performed with several choices for the profile of the PDF second moment. The resulting cloud and relative humidity fields were shown to be quite sensitive to the prescribed profile, and the use of a profile based on the AIRS-derived proxy results in improvements relative to observational estimates. The AIRS-guided total water PDF profiles, including their dependence on underlying surface type and on horizontal resolution, have been implemented in the version of the GEOS-5 AGCM used for publicly released simulations.

Full access
Andrea Molod
and
Haydee Salmun
Full access
Arthur Y. Hou
and
Andrea Molod

Abstract

The hypothesis that the cross-equatorial Hadley circulation can modulate the poleward heat transport in the winter extratropics is investigated using the Goddard Earth Observing System (GEOS-1) GCM for 10 northern winter initial conditions. Three-month forecasts are compared with parallel runs from the same initial conditions but with a slightly perturbed radiative forcing in the Tropics. Analysis of the zonal-mean climates shows that, on timescales longer than a month, a persistent intensification in the winter Hadley circulation is positively correlated with increased dynamic cooling in the winter midlatitudes and warming at the high latitudes through-out the troposphere, signaling an increased beat transport toward the winter pole.

While the heating anomaly can undergo significant transient fluctuations in the winter extratropics, the variance of the time-averaged dynamic heating anomaly is dominated by contributions from low zonal wavenumbers (particularly wavenumbers 1 and 2), with minor contributions from wavenumbers 4 and higher, suggesting that the low-frequency planetary-scale waves are the primary vehicle for the increased poleward heat transport, with the synoptic-scale waves assuming a secondary role along the storm tracks.

These results support the earlier idealized GCM study by Hou showing that a stronger winter Hadley circulation induced by a latitudinal shift in tropical convection can lead to enhanced upper-level tropical easterlies and a slightly stronger subtropical winter jet attended by increased poleward heat transport in the winter extratropics. Specific examples were also found in which the zonally averaged response is dominated by regional changes (notably over the North Pacific), indicating these relations may hold locally, as suggested by Bjerknes.

The implication of this work is that the low-frequency variability in the Hadley circulation associated with persistent tropical rainfall anomalies may play an important role in global climate by modulating the subtropical wind shear and the energy available for baroclinic wave growth outside the Tropics.

Full access
Haydee Salmun
,
Holly Josephs
, and
Andrea Molod

Abstract

The planetary boundary layer (PBL) is central to the exchange of heat and moisture between Earth’s surface and the atmosphere, to the turbulent transport of aerosol and chemical pollutants affecting air quality, and to near- and long-term climate prediction. Consequently, the PBL has become a major focus of atmospheric and climate science, particularly after its designation as a “targeted observable” by the 2018 National Academies of Science, Engineering, and Medicine Earth Science Decadal Survey. Information about the height of the PBL that is global in scope allows for wide geographical analysis of connections to seasonality, to latitude, proximity to oceans, and synoptic variability. Information about the PBL height at hourly resolution allows for the analysis of diurnal cycles and PBL height growth rates, both of which are critical to the study of near-surface transport processes. This manuscript describes the release of a new global dataset of PBL height estimates retrieved from radar wind profilers (RWPs), called Global Radar Wind Profiler Planetary Boundary Layer Height (GRWP-PBLH). Hourly PBL height estimates are retrieved using an existing algorithm applied to archived signal-to-noise ratio data from a series of networks located around the globe, specifically in Australia, Europe, and Japan. Information about the source data, details of data processing, and production of PBL height estimates are discussed here along with a description of supplementary data and the available software. The GRWP-PBLH dataset is now accessible to the community for ongoing and future research.

Open access
Andrea Molod
,
Haydee Salmun
, and
Darryn W. Waugh

Abstract

Heterogeneities in the land surface on scales smaller than the typical general circulation model (GCM) grid size can have a profound influence on the grid-scale mean climate. There exists observational and modeling evidence that the direct effects of surface heterogeneities may be felt by the atmosphere well into the planetary boundary layer. The impact of including an “extended mosaic” (EM) scheme, which accounts for the vertical influence of land surface heterogeneities in a GCM, is evaluated here by comparing side-by-side GCM simulations with EM and with the more standard mosaic formulation (M).

Differences between the EM and M simulations are observed in the boundary layer structure, in fields that link the boundary layer and the general circulation, and in fields that represent the general circulation itself. Large EM − M differences are found over the eastern United States, eastern Asia, and southern Africa in the summertime, and are associated with a boundary layer eddy diffusion feedback mechanism. The feedback mechanism operates as a positive or negative feedback depending on the local Bowen ratio. Significant EM − M differences are also found in the region of the Australian monsoon and in the strength of the stationary Pacific–North America pattern in the northern Pacific.

Full access
Andrea Molod
,
Haydee Salmun
, and
Darryn W. Waugh

Abstract

Heterogeneities in the land surface exist on a wide range of spatial scales and make the coupling between the land surface and the overlying boundary layer complex. This study investigates the vertical extent to which the surface heterogeneities affect the boundary layer turbulence. A technique called “extended mosaic” is presented. It models the coupling between the heterogeneous land surface and the atmosphere by allowing the impact of the subgrid-scale variability to extend throughout the vertical extent of the planetary boundary layer. Simulations with extended mosaic show that there is a GCM level at which the distinct character of the turbulence over different land scene types is homogenized, which the authors call the model blending height. The behavior of the model blending height is an indicator of the mechanism by which the surface heterogeneities extend their direct influence upward into the boundary layer and exert their influence on the climate system. Results are presented that show the behavior of the model blending height and the relationships to atmospheric and surface conditions. The model blending height is generally one-third to one-half of the planetary boundary layer height, although the exact ratio varies with local conditions and the distribution of the underlying vegetation. The model blending height also increases with canopy temperature and sensible heat flux and is influenced by the amount of variability in the surface vegetation and the presence of deciduous trees.

Full access
Kay Suselj
,
Joao Teixeira
,
Marcin J. Kurowski
, and
Andrea Molod

Abstract

A systematic underestimation of subtropical planetary boundary layer (PBL) stratocumulus clouds by the GEOS model has been significantly improved by a new eddy-diffusivity/mass-flux (EDMF) parameterization. The EDMF parameterization represents the subgrid-scale transport in the dry and moist parts of the PBL in a unified manner and it combines an adjusted eddy-diffusivity PBL scheme from GEOS with a stochastic multiplume mass-flux model. The new EDMF version of the GEOS model is first compared against the CONTROL version in a single-column model (SCM) framework for two benchmark cases representing subtropical stratocumulus and shallow cumulus clouds, and validated against large-eddy simulations. Global simulations are performed and compared against observations and reanalysis data. The results show that the EDMF version of the GEOS model produces more realistic subtropical PBL clouds. The EDMF improvements first detected in the SCM framework translate into similar improvements of the global GEOS model.

Full access
Andrea Molod
,
H. M. Helfand
, and
Lawrence L. Takacs

Abstract

The Goddard Earth Observing System (GEOS) General Circulation Model (GCM) is part of the GEOS Data Assimilation System (DAS), which is being developed at the Goddard Data Assimilation Office for the production of climate datasets. This study examines Version 1 of the GEOS CYCM by evaluating the quality of the fields that relate most closely to the GCM physical parameterizations and examines the impact of the GCM climate errors on the climate of the DAS assimilated fields.

The climate characteristics are evaluated using independent satellite and ground-based data for comparison. The GEOS-1 GCM shows reasonably good agreement with available observations in terms of general global distribution and seasonal cycles. The major biases or systematic errors are a tendency toward a dry tropical atmosphere and an inadequate cloud radiative impact in the extratropics. Other systematic errors are a generally wet subtropical atmosphere, slightly excess precipitation over the continents, and excess cloud radiative effects over the Tropics. There is also an underestimation of surface sensible and latent heat fluxes over the area of maximum flux.

The DAS climate characteristics, in general, show better agreement with available observations than the GCM. Four distinct ways that the GCM impacts the DAS have been identified, ranging from a DAS climate with little or no impact from the GCM bias to a DAS climate with a greater bias than the GCM due to a spurious feedback between the GCM and the input data.

Full access
Derek J. Posselt
,
Bruce Fryxell
,
Andrea Molod
, and
Brian Williams

Abstract

Parameterization of processes that occur on length scales too small to resolve on a computational grid is a major source of uncertainty in global climate models. This study investigates the relative importance of a number of parameters used in the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model, focusing on cloud, convection, and boundary layer parameterizations. Latin hypercube sampling is used to generate a few hundred sets of 19 candidate physics parameters, which are subsequently used to generate ensembles of single-column model realizations of cloud content, precipitation, and radiative fluxes for four different field campaigns. A Gaussian process model is then used to create a computationally inexpensive emulator for the simulation code that can be used to determine a measure of relative parameter sensitivity by sampling the response surface for a very large number of input parameter sets. Parameter sensitivities are computed for different geographic locations and seasons to determine whether the intrinsic sensitivity of the model parameterizations changes with season and location. The results indicate the same subset of parameters collectively control the model output across all experiments, independent of changes in the environment. These are the threshold relative humidity for cloud formation, the ice fall speeds, convective and large-scale autoconversion, deep convection relaxation time scale, maximum convective updraft diameter, and minimum ice effective radius. However, there are differences in the degree of parameter sensitivity between continental and tropical convective cases, as well as systematic changes in the degree of parameter influence and parameter–parameter interaction.

Full access
Randal D. Koster
,
Anthony M. DeAngelis
,
Siegfried D. Schubert
, and
Andrea M. Molod

Abstract

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state.

Full access