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NASA NTRS2020

Impact of Resolution and Parameterized Convection on the Diurnal Cycle of Precipitation in a Global Nonhydrostatic Model

A series of 40-day non-hydrostatic global simulations was run with the NASA Goddard Earth Observing System (GEOS) model with horizontal grid spacing ranging from 50 km to 3.5 km. Here we evaluate the diurnal cycle of precipitation and organized convection as a function of resolution. For validation we use the TRMM 3B42 and IMERG precipitation products and 4 km Merged Infrared brightness temperature, focusing on three regions: the contiguous United States (CONUS), the Maritime Continent, and Amazonia. We find that higher resolution has mixed impacts on diurnal phase. Regions dominated by non-local propagating convection show the greatest improvement, with better representation of organized convective systems. Precipitation in regions dominated by local thermodynamic forcing tends to peak too early at high resolution. Diurnal amplitudes in all regions develop unrealistic small-scale variability at high resolution, while amplitudes tend to be underestimated at low resolution. The GEOS model uses the Grell-Freitas scale-aware convection scheme, which smoothly reduces parameterized deep convection with increasing resolution. We find that some parameterized convection is beneficial for the diurnal amplitude and phase even with a 3.5 km model grid, but only when throttled with the scale-aware approach. An additional 3.5 km experiment employing the GFDL microphysics scheme and higher vertical resolution shows further improvement in propagating convection, but an earlier rainfall peak in locally forced regions.

Nathan P. Arnold↗
NASA NTRS2012

A CloudSat Perspective of the Atmospheric Water Cycle and Precipitation: Recent Progress and Grand Challenges

Summary Global - mean precipitation - is controlled by Earth's energy balance and is a quantifiable consequence of the water vapor feedback. Predictability rests on the degree to which the water vapor feedback is predictable. Regional scale - to a significant extent, changes are shaped by atmospheric circulation changes but we do not know the extent to which regional scale changes are predictable. The impacts of changes to atmospheric circulation on regional scale water cycle changes can be dramatic. Process - scale - significant biases to the CHARACTER of precipitation (frequency and intensity) is related to how the precipitation process is parameterized in models. Aerosol - We still do not know the extent to which the water cycle is influenced by aerosol but anecdotal evidence is building. The character of precipitation is affected by the way aerosol influence clouds and thus affects the forcing of the climate system through the albedo effect. Observations - we still have a way to go and need to approach the problem in a more integrated way (tie clouds, aerosol and precipitation together and then link to soil moisture, etc). Globally our capabilities seriously lag behind the science and model development.

terrestrial water cycles↗
NASA NTRS1991

Climate and the equilibrium state of land surface hydrology parameterizations

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Entekhabi, Dara↗
NASA NTRS2007

Clouds in GEOS-5

The GEOS-5 atmospheric model is being developed as a weather-and-climate capable model. It must perform well in assimilation mode as well as in weather and climate simulations and forecasts and in coupled chemistry-climate simulations. In developing GEOS-5, attention has focused on the representation of moist processes. The moist physics package uses a single phase prognostic condensate and a prognostic cloud fraction. Two separate cloud types are distinguished by their source: "anvil" cloud originates in detraining convection, and large-scale cloud originates in a PDF-based condensation calculation. Ice and liquid phases for each cloud type are considered. Once created, condensate and fraction from the anvil and statistical cloud types experience the same loss processes: evaporation of condensate and fraction, auto-conversion of liquid or mixed phase condensate, sedimentation of frozen condensate, and accretion of condensate by falling precipitation. The convective parameterization scheme is the Relaxed Arakawa-Schubert, or RAS, scheme. Satellite data are used to evaluate the performance of the moist physics packages and help in their tuning. In addition, analysis of and comparisons to cloud-resolving models such as the Goddard Cumulus Ensemble model are used to help improve the PDFs used in the moist physics. The presentation will show some of our evaluations including precipitation diagnostics.

Bacmeister, Julio↗
NASA NTRSDate not supplied

Representing the Sub-Grid Heterogeneity of Surface Precipitation in A General Circulation Model

Precipitation variability on spatial scales smaller than a typical general circulation model (GCM) grid box is often neglected, with the grid-mean precipitation rate being applied uniformly to underlying surface tiles. This reduces the extrema seen by the surface, with corresponding reductions in surface runoff and altered land-atmosphere fluxes. Here we present a novel approach to stochastically distribute precipitation across sub-grid surface tiles within a GCM. Based on 4 km Stage IV precipitation data, the scheme parameterizes the dry area fraction as a function of grid mean precipitation rate, and defines the relative distribution of intensities across non-dry surface tiles. To incorporate memory and mimic the persistence of precipitating storms, the relative intensity assigned to each sub-grid tile is determined by an autoregressive process. Using single column experiments, the scheme is shown to reproduce observed precipitation statistics at the scale of model surface tiles. We also document impacts on surface hydrology and energy partitioning, with notable increases in precipitation runoff, surface temperature variance, and the Bowen ratio.

GCM↗
NASA NTRS2002

Tropical Cumulus Convection and Upward Propagating Waves in Middle Atmospheric GCMs

It is recognized that the resolved tropical wave spectrum can vary considerably between general circulation models (GCMs) and that these differences can have an important impact on the simulated climate. A comprehensive comparison of the waves is presented for the December-January-February period using high-frequency (three-hourly) data archives from eight GCMs and one simple model participating in the GCM Reality Intercomparison Project for SPARC (GRIPS). Quantitative measures of the structure and causes of the wavenumber-frequency structure of resolved waves and their impacts on the climate are given. Space-time spectral analysis reveals that the wave spectrum throughout the middle atmosphere is linked to variability of convective precipitation, which is determined by the parameterized convection. The variability of the precipitation spectrum differs by more than an order of magnitude between the models, with additional changes in the spectral distribution (especially the frequency). These differences can be explained primarily by the choice of different, cumulus par amet erizations: quasi-equilibrium mass-flux schemes tend to produce small variability, while the moist-convective adjustment scheme is most active. Comparison with observational estimates of precipitation variability suggests that the model values are scattered around the truth. This result indicates that a significant portion of the forcing of the equatorial quasi-biennial oscillation (QBO) is provided by waves with scales that are not resolved in present-day GCMs, since only the moist convective adjustment scheme (which has the largest transient variability) can force a QBO in models that have no parameterization of non-stationary gravity waves. Parameterized cumulus convection also impacts the nonmigrating tides in the equatorial region. In most of the models, momentum transport by diurnal nonmigrating tides in the mesosphere is larger than that by Kelvin waves, being more significant than has been thought. It is shown that the equatorial semi-annual oscillation in the models examined is driven mainly by gravity waves with periods shorter than three days, with at least some contribution from parameterized gravity waves; the contribution from the ultra-fast zonal wavenumber-1 Kelvin waves is negligible.

Horinouchi, T.↗
NASA NTRS1994

Dynamic modeling of orographically induced precipitation

Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.

Barros, Ana Paula↗
NASA NTRS1985

Mesoscale research activities with the LAMPS model

Researchers achieved full implementation of the LAMPS mesoscale model on the Atmospheric Sciences Division computer and derived balanced and real wind initial states for three case studies: March 6, April 24, April 26, 1982. Numerical simulations were performed for three separate studies: (1) a satellite moisture data impact study using Vertical Atmospheric Sounder (VAS) precipitable water as a constraint on model initial state moisture analyses; (2) an evaluation of mesoscale model precipitation simulation accuracy with and without convective parameterization; and (3) the sensitivity of model precipitation to mesoscale detail of moisture and vertical motion in an initial state.

Kalb, M. W.↗
NASA NTRS2003

Variational Continuous Assimilation of TMI and SSM/I Rain Rates: Impact on GEOS-3 Hurricane Analyses and Forecasts

We describe a variational continuous assimilation (VCA) algorithm for assimilating tropical rainfall data using moisture and temperature tendency corrections as the control variable to offset model deficiencies. For rainfall assimilation, model errors are of special concern since model-predicted precipitation is based on parameterized moist physics, which can have substantial systematic errors. This study examines whether a VCA scheme using the forecast model as a weak constraint offers an effective pathway to precipitation assimilation. The particular scheme we exarnine employs a '1+1' dimension precipitation observation operator based on a 6-h integration of a column model of moist physics from the Goddard Earth Observing System (GEOS) global data assimilation system DAS). In earlier studies, we tested a simplified version of this scheme and obtained improved monthly-mean analyses and better short-range forecast skills. This paper describes the full implementation ofthe 1+1D VCA scheme using background and observation error statistics, and examines how it may improve GEOS analyses and forecasts of prominent tropical weather systems such as hurricanes. Parallel assimilation experiments with and without rainfall data for Hurricanes Bonnie and Floyd show that assimilating 6-h TMI and SSM/I surfice rain rates leads to more realistic storm features in the analysis, which, in turn, provide better initial conditions for 5-day storm track prediction and precipitation forecast. These results provide evidence that addressing model deficiencies in moisture tendency may be crucial to making effective use of precipitation information in data assimilation.

Hou, Arthur Y.↗
NASA NTRS1988

Theory on the uncertainty in cloud microphysical processes and climate

The interactive role of clouds and precipitation processes in a climate model is investigated. The basic model structure and parameterizations for condensation, evaporation, and precipitation are outlined. Results simulated from the cloud-climate model are discussed. The potential link between microphysical cloud processes and climate is theorized. The need to develop a climatology of the mean particle radius for clouds at the global scale, in order to understand the role of clouds in climate is stressed.

Liou, Kuo-Nan↗
NASA NTRS1994

A stochastic precipitation disaggregation scheme for GCM applications

In the surface hydrologic parameterization of general circulation models (GCMs), it is commonly assumed that the precipitation processes are homogeneous over a GCM grid square and that the precipitation intensity is uniformly distributed. Based on evidence that the spatial distribution of precipitation within a GCM grid square is crucial for the land surface hydrology parameterization, a few researchers have explored the impacts of assuming that the precipitation is exponentially distributed. This paper explores the suitability of the aforementioned assumptions. First, a statistical analysis is conducted of historical precipitation data for three GCM grids in different regions of the United States. The analysis suggests that neither the uniform nor the exponential distribution assumption may be suitable at the GCM grid scale and, that instead, the spatial variability in precipitation is characterized by statistical patterns that are inhomogeneous. These patterns vary from grid to grid and are induced by the interaction between atmospheric conditions and various land surface characteristics, such as topographical features, surface properties, etc. Within the same grid square, however, the statistical patterns are generally constant from year to year. Based on this analysis, a computationally viable (i.e., usable with GCMs) stochastic precipitation disaggregation scheme that utilizes these stable statistical patterns is proposed. The method was used to generate spatially distributed hourly rainfall for a summer season in the southwestern region of the continental United States. Analysis of the results shows that the methodology preserves the seasonal characteristics of spatial variability in precipitation that is observed in the long-term historical data.

Gao, Xiaogang↗
NASA NTRS1997

Evaluating and Understanding Parameterized Convective Processes and their Role in the Development of Mesoscale Precipitation Systems

Research efforts during the second year have centered on improving the manner in which convective stabilization is achieved in the Penn State/NCAR mesoscale model MM5. Ways of improving this stabilization have been investigated by (1) refining the partitioning between the Kain-Fritsch convective parameterization scheme and the grid scale by introducing a form of moist convective adjustment; (2) using radar data to define locations of subgrid-scale convection during a dynamic initialization period; and (3) parameterizing deep-convective feedbacks as subgrid-scale sources and sinks of mass. These investigations were conducted by simulating a long-lived convectively-generated mesoscale vortex that occurred during 14-18 Jul. 1982 and the 10-11 Jun. 1985 squall line that occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. The long-lived vortex tracked across the central Plains states and was responsible for multiple convective outbreaks during its lifetime.

Fritsch, J. Michael↗
NASA NTRS2019

Including a Cold Pool Representation in a Convection Parameterization and Simulating Its Impacts on the Spatial and Temporal Variability of the Precipitation in the NASA GEOS GCM

We developed and implemented a simple representation of a cold pool in the Grell-Freitas (GF) convection parameterization. The cold pool parameterization is based on the observation that convective-scale downdrafts produce a local ‘deficit’ of the moist static energy (MSE). This information is advected and becoming downwind available to trigger and intensify new convection. The cold pool is dissipated by a simple exponential decay using a lifetime of a few hours, or by interacting with the underneath surface by exchanging latent and sensible heat fluxes. Preliminary results show some improvement of the simulation of the diurnal cycle of the precipitation over the land, mainly during the nighttime.

Cold pools↗
NASA NTRS1996

Evaluating and Understanding Parameterized Convective Processes and Their Role in the Development of Mesoscale Precipitation Systems

Research efforts focused on numerical simulations of two convective systems with the Penn State/NCAR mesoscale model. The first of these systems was tropical cyclone Irma, which occurred in 1987 in Australia's Gulf of Carpentaria during the AMEX field program. Comparison simulations of this system were done with two different convective parameterization schemes (CPS's), the Kain-Fritsch (KF) and the Betts-Miller (BM) schemes. The second system was the June 10-11, 1985 squall line simulation, which occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. Simulations of this system using the KF scheme were examined in detail.

Fritsch, J. Michael↗
NASA NTRS1995

Evaluating and Understanding Parameterized Convective Processes and Their Role in the Development of Mesoscale Precipitation Systems

Research efforts during the first year focused on numerical simulations of two convective systems with the Penn State/NCAR mesoscale model. The first of these systems was tropical cyclone Irma, which occurred in 1987 in Australia's Gulf of Carpentaria during the AMEX field program. Comparison simulations of this system were done with two different convective parameterization schemes (CPS's), the Kain-Fritsch (1993 - KF) and the Betts-Miller (Betts 1986- BM) schemes. The second system was the June 10-11 1985 squall line simulation, which occurred over the Kansas-Oklahoma region during the PRE-STORM experiment. Simulations of this system using the KF scheme were examined in detail.

Fritsch, J. Michael↗
NASA NTRS1977

Atmospheric model development in support of SEASAT. Volume 3: Prediction models

As part of the SEASAT program of NASA, a set of four hemispheric, atmospheric models are developed. The four models use a polar stereographic grid in the horizontal and a sigma coordinate in the vertical. Conservation forms of the difference equations are integrated using either a fifteen or four minute time step on a 381 km or 127 km grid (at 60 deg N) for the 63 x 63 or 187 x 187 models respectively. A nonlinear pressure smoother is used along with momentum and temperature diffusion to help control computational noise. The horizontal boundary conditions are insulated slippery walls. Centered time differencing with time averaging of the pressure gradient force term in the momentum equations is used. Robert time filtering on of the temperature and moisture solutions is used for computational stability. The moisture and heat source/sink terms are modeled. Terms representing evaporation and large scale condensation, sensible heat exchange, parameterized cumulus convection and precipitation, and solar and terrestrial radiation are included. Initialization of the models is based on a pattern conservation technique to obtain objective analysis of the state parameter structure from the surface to 50 mb.

Wellck, R. E.↗
NASA NTRS1982

Cloud/climate sensitivity experiments

A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

Roads, J. O.↗