A Nonhydrostatic Mesoscale Model Designed to Simulate Scale Interaction

Tripoli, Gregory J.

doi:10.1175/1520-0493(1992)120<1342:anmmdt>2.0.co;2

Cited by 164 publications

(82 citation statements)

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“…bin microphysics Khain and Sednev (1996) 33 bins each for liquid droplets, plates, columns, dendrites, snow, graupel, and frozen drops Chen et al (2003) Flatau et al (1989) Tripoli (1992) bin microphysics Hashino and Tripoli (2007) Meyers et al (1997) The dimensionality of the model is listed as two-dimensional (2D) or three-dimensional (3D Among SCMs, there are versions of two operational weather prediction models (ECMWF and NCEP) and five operational climate models (CCCMA, ECHAM, GFDL, GISS, and SCAM3). There are four SCMs which have primarily been used in research studies (ARC-SCM, MCRAS, SCRIPPS, and UWM).…”

Section: Overviewmentioning

confidence: 99%

Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. I: single‐layer cloud

Klein

McCoy

Morrison

et al. 2009

Quart J Royal Meteoro Soc

276

341

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ABSTRACT:Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) programme's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud-top temperature of −15 • C. The average liquid water path of around 160 g m −2 was about two-thirds of the adiabatic value and far greater than the average mass of ice which when integrated from the surface to cloud top was around 15 g m −2 .Simulations of 17 single-column models (SCMs) and 9 cloud-resolving models (CRMs) are compared. While the simulated ice water path is generally consistent with observed values, the median SCM and CRM liquid water path is a factor-of-three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path.Despite this underestimate, the simulated liquid and ice water paths of several models are consistent with observed values. Furthermore, models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter exists. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.

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Section: Overviewmentioning

confidence: 99%

Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. I: single‐layer cloud

Klein

McCoy

Morrison

et al. 2009

Quart J Royal Meteoro Soc

276

341

View full text Add to dashboard Cite

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“…By applying the RMS to numerous meteorological-microphysical situations simulated by the CRM for 60 numerical storms that occurred within the European/Mediterranean Basin region, and then marshalling into a specialized database some 2.5 million modeled DTH and microphysical profiles (from which optimal meteorological constraint parameters are then derived) with linked modeled TBs -it has become possible to use the database for Bayesian interpretation of analogous measured TBs and meteorological constraint parameters. The CRM itself is the regional/mesoscale Nonhydrostatic Modeling System (NMS) originally developed by Tripoli (1992) and recently upgraded by Tripoli and Smith (2013a, b). The heart of the model, insofar as its application with the CDRD algorithm, is its 2-water/4-ice microphysical parameterization scheme.…”

Section: Inclusion Of Optimal Meteorological Parameters As Solution Cmentioning

confidence: 99%

CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

Mugnai

Smith

Tripoli

et al. 2013

Nat. Hazards Earth Syst. Sci.

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Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided including a few examples of their performance. This aspect of the development of the two algorithms is placed in the context of what we refer to as the TRMM era, which is the era denoting the active and ongoing period of the Tropical Rainfall Measuring Mission (TRMM) that helped inspire their original development. In 2015, the ISAC-Rome precipitation algorithms will undergo a transformation beginning with the upcoming Global Precipitation Measurement (GPM) mission, particularly the GPM Core Satellite technologies. A few years afterward, the first pair of imaging and sounding Meteosat Third Generation (MTG) satellites will be launched, providing additional technological advances. Various of the opportunities presented by the GPM Core and MTG satellites for improving the current CDRD and PNPR precipitation retrieval algorithms, as well as extending their product capability, are discussed

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“…High resolution two-dimensional numerical simulations were completed utilizing the University of Wisconsin NonHydrostatic Modeling System (UW-NMS, Tripoli, 1992). While there are potential advantages to three-dimensional simulation (e.g.…”

Section: Model Descriptionmentioning

confidence: 99%

A numerical study of aerosol influence on mixed-phase stratiform clouds through modulation of the liquid phase

et al. 2013

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Numerical simulations were carried out in a high-resolution two-dimensional framework to increase our understanding of aerosol indirect effects in mixed-phase stratiform clouds. Aerosol characteristics explored include insoluble particle type, soluble mass fraction, influence of aerosol-induced freezing point depression and influence of aerosol number concentration. Simulations were analyzed with a focus on the processes related to liquid phase microphysics, and ice formation was limited to droplet freezing. Of the aerosol properties investigated, aerosol insoluble mass type and its associated freezing efficiency was found to be most relevant to cloud lifetime. Secondary effects from aerosol soluble mass fraction and number concentration also alter cloud characteristics and lifetime. These alterations occur via various mechanisms, including changes to the amount of nucleated ice, influence on liquid phase precipitation and ice riming rates, and changes to liquid droplet nucleation and growth rates. Alteration of the aerosol properties in simulations with identical initial and boundary conditions results in large variability in simulated cloud thickness and lifetime, ranging from rapid and complete glaciation of liquid to the production of long-lived, thick stratiform mixed-phase cloud

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A Nonhydrostatic Mesoscale Model Designed to Simulate Scale Interaction

Cited by 164 publications

References 0 publications

Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. I: single‐layer cloud

Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. I: single‐layer cloud

CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

A numerical study of aerosol influence on mixed-phase stratiform clouds through modulation of the liquid phase

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