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NASA NTRS2002

Vertical Mass, Momentum, Moisture, and Heat Fluxes in Hurricanes above 10 km during CAMEX-3 and CAMEX-4

The third and fourth NASA Convection and Moisture Experiments (CAMEX-3 and CAMEX-4) during the Atlantic hurricane seasons of 1998 and 2001, respectively, have yielded comprehensive multi-aircraft datasets using, both remote and in-situ instrumentation. Among these are high-frequency in-situ measurements of vertical wind, horizontal wind, temperature, and water vapor, made from NASA's DC-8 aircraft in the upper portions of the hurricane (typically above 10 km). Wind and temperature measurements were made at 20 hz by the NASA/Ames Meteorological Measurement System, while water vapor was measured at 1 hz by the NASA/JPL Laser Hygrometer. Fluxes of heat, momentum, and moisture at these levels are important, since modeling studies have shown that ice processes, which are dominant at temperatures below -40C (where the DC-8 flies) are important for hurricane intensification. Also, there are indications from satellite studies that latent heat release at DC-8 levels is significant, perhaps a third of those in the mid-troposphere. Preliminary results show that typical updrafts in the eyewall region are comparable to or higher than previous observations of tropical convection, with several instances of updraft magnitudes of 15 meters per second (the maximum observed was 21 meters per second). They also show significant supersaturations (10-20% or more) in the updrafts, which would enhance the latent heat release at the upper levels of the hurricane. This paper will examine the magnitude and distribution of small and mesoscale vertical fluxes of mass, momentum, moisture, and heat. The goal is to examine the role of these fluxes in the overall budgets of the respective quantities in the upper portions of the hurricane.

Pfister, Leonhard↗

NASA NTRS2011

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

James, Robert S.↗

NASA NTRS2001

Numerical Simulations of Precipitation Processes, Microphysics, and Microwave Radiative Properties of flood Producing Storms in Mediterranean & Adriatic Basins

A comprehensive understanding of the meteorological and microphysical nature of Mediterranean storms requires a combination of in situ data analysis, radar data analysis, and satellite data analysis, effectively integrated with numerical modeling studies at various scales. An important aspect of understanding microphysical controls of severe storms, is first understanding the meteorological controls under which a storm has evolved, and then using that information to help characterize the dominant microphysical processes. For hazardous Mediterranean storms, highlighted by the October 5-6, 1998 Friuli flood event in northern Italy, a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution. This involves intense convective development, Sratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that effect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. This talk overviews the microphysical elements of a severe Mediterranean storm in such a context, investigated with the aid of TRMM satellite and other remote sensing measurements, but guided by a nonhydrostatic mesoscale model simulation of the Friuli flood event. The data analysis for this paper was conducted by my research groups at the Global Hydrology and Climate Center in Huntsville, AL and Florida State University in Tallahassee, and in collaboration with Dr. Alberto Mugnai's research group at the Institute of Atmospheric Physics in Rome. The numerical modeling was conducted by Professor Oreg Tripoli and Ms. Giulia Panegrossi at the University of Wisconsin in Madison, using Professor Tripoli's nonhydrostatic modeling system (NMS). This is a scalable, fully nested mesoscale model capable of resolving nonhydrostatic circulations from regional scale down to cloud scale and below.

Smith, Eric A.↗

NASA NTRS2015

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗

DOE OSTI2025

Quantifying UAS Observation Error Variance Used in Data Assimilation Systems and Its Impact on Predictive Skill

Observation error determines the weights of the observations and background state used in data assimilation to generate analyses. Quantifying observation error is critical for the optimal assimilation of observational data sets. Uncrewed Aircraft System (UAS) observations have shown potential benefits in filling observational gaps in the lower atmosphere; however, characterization of their error characteristics has been limited. To optimize the use of UAS observations in numerical weather prediction, UAS observation error is estimated based on the 3‐cornered hat diagnostic approach which uses three independent estimates of the atmospheric state. This approach is applied to data from the 2018 Lower Atmospheric Profiling Studies at Elevation‐a Remotely‐piloted Aircraft Team Experiment field campaign using collocated UAS and rawinsonde observations along with output from a set of convection‐permitting model simulations. The estimated observation error values for UAS temperature, wind, and relative humidity measurements were found to be only weakly dependent on height AGL with mean values equal to 0.5°C, 0.8 m s −1 , and 3%, respectively. Only the newly estimated observation error for temperature differed from that previously used to assimilate commercial aircraft observations into global models (1.0°C). However, using this reduced temperature observation error produced more accurate mesoscale analyses and forecasts of both terrain‐driven flows and convection initiation generated by colliding outflow boundaries within the San Luis Valley of Colorado.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Flower‐Type Organized Trade‐Wind Cumulus: A Multi‐Day Lagrangian Large Eddy Simulation Intercomparison Study

Shallow cumulus cloud fields in subtropical marine trade wind environments, particularly over the tropical Atlantic Ocean, show distinct organizational patterns. Among these, Flower‐type clouds are characterized by expansive stratiform cloud patches surrounded by regions of scattered convection. The objectives of this study were (a) to construct a case study of a time period during the EUREC 4 A/ATOMIC field campaign when Flower‐type organization was observed, (b) to evaluate the fidelity of a multi‐model ensemble of large eddy simulations of that case, and (c) to analyze the interaction between cloud and precipitation processes and mesoscale organization in the simulations. The simulations follow a quasi‐Lagrangian trajectory, allowing mesoscale features to develop over time in a domain that follows the boundary‐layer airmass. The results show a broad agreement in simulated thermodynamic properties across different LES codes, with Flower‐type cloud patches appearing within hours of each other. The consensus among models is consistent with observations made during the EUREC 4 A/ATOMIC field campaign on the specific day of interest. The cloud structure reveals three distinct peaks in the joint probability densities of cloud base and cloud top height, with the dominant peak at any given time influenced by the stage of cloud organization. The simulated cloud system evolution reveals consistent occurrence of maxima in liquid water path and rain rate before Flower reaches its maximum length scale. Targeted sensitivity tests reveal a weak relationship between Cloud Droplet Number concentration and the extent/degree/type of organization.

EUREC4A↗

NASA NTRS1985

Severe wind flow of small spatial and temporal scales: The microburst and related phenomena

Low-altitude winds on the meso- and microscale are the primary focus of study for the Research Applications Program (RAP) of NCAR. Local weather features such as microbursts, microburst lines, gust fronts, and convergent wind boundaries have been observed and documented extensively. A microburst is a strong, small-scale convective storm outflow which diverges horizontally in all directions upon impact with the ground (Fujita, 1981). A microburst line is composed of two or more microbursts which occur either simultaneously or consecutively, and subsequently form a diverging line of outflow. The temporal and spatial scales of these phenomena are shown. Microbursts and microburst lines generally occur on both the meso- and microscale, while gust fronts and convergent wind boundaries overlap into the mesoscale. Microbursts, in particular, not only are small spatially but are also a short-lived phenomenon. Clearly, some of these features are on a much smaller spatial and temporal scale than can be resolved by a global wind measurement. During the past three years, three experiments were held in the Denver, CO, area to observe boundary-layer winds. Their main objectives were observation and documentation of those weather features discussed above. The Joint Airport Weather Studies (JAWS) Project, which ran in the summer of 1982, was set up to study microbursts. The Convective Initiation Project (1984) was designed to document clear-air convergent wind boundaries, including gust fronts, and their role in convective storm initiation. This project was immediately followed by the Classify, Locate, and Avoid Wind Shear experiment that expanded upon the work done in JAWS. Details on the scales of these weather features are presented. The wind sensors used to detect these phenomena are also discussed. Concluding comments address the usefulness of a global wind measurement system as it pertains to our local scale of interest.

Roberts, Rita D.↗

NASA NTRS2004

Assessing the Usefulness of AIRS Radiance Observations in a 4D-Var Assimilation Scheme Using the Penn State/NCAR Mesoscale Model Version 5 (MM5) and a Stand Alone Radiative Transfer Algorithm (SARTA)

Short-term precipitation forecast skill remains poor despite further advances in numerical modeling and data analysis. Utilizing indirect observations, such as the radiance observations obtained from the Atmospheric Infrared Sounder (AIRS), in a 4D-Var assimilation scheme may lead to a rapid improvement in the skill of 12-h QPF. In order to investigate the usefulness of AIRS observations, the adjoint code of a radiative transfer model (SARTA) is developed and linked to MM5 4D-Var system. A statistical comparison of the AIRS radiances with those calculated using the linked MMS-SARTA model is carried out to assess errors in the radiative transfer model, MM5 and AIRS data, and to develop a quality control scheme. Outliers and any bias that may exist in radiative transfer model, MM5 and AIRS data are identified. An adjoint sensitivity study, utilizing the SARTA adjoint model, is then done to identify the relative sensitivities of each spectral channel to such parameters as atmospheric temperature, pressure, and mixing ratio. Another sensitivity study is done using the MM5 alone to determine the sensitivity of the 12-h QPF to model parameters such as atmospheric temperature, pressure, and mixing ratio under various weather regimes (i.e. summertime convection, winter snowfall). Results from these two types of adjoint sensitivity studies are used to determine which AIRS channels contribute most to 12-h QPF under differing weather regimes. This information is useful when conducting 4D-Var experiments using a subset of the 2378 AIRS spectral channels. Finally, 4D-Var experiments are done to analyze the impact of the AIRS observations on the quality of the 12-h QPF results. This project falls under the data assimilation general session topic as specified by the conference organizers.

Carrier, M.↗

DOE OSTI2021

Enhance Low Level Temperature and Moisture Profiles Through Combining NUCAPS, ABI Observations, and RTMA Analysis

Thermodynamic information from low levels in the atmosphere is crucial for operational weather forecasts and meteorological researchers. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) sounding products have been proven beneficial to fill the data gap between synoptic radiosonde observations (RAOBs). However, compared with the upper troposphere, the accuracy of NUCAPS soundings in the low levels still needs improvement. In this study, a deep neural network (DNN) is applied to fuse multiple data sources to enhance the NUCAPS temperature and moisture profiles in the lower atmosphere. The network is developed by combining satellite observations, including NUCAPS sounding retrievals and high resolution geostationary satellite observations from the Advanced Baseline Imager, and surface analysis from the Real-Time Mesoscale Analysis (RTMA) as inputs, while collocated soundings from ECMWF re-analysis version 5 are used as the benchmark for the training. The performance of the model is evaluated by using the independent testing data set, data from a different year, as well as collocated RAOBs, showing improvement to the temperature and moisture profiles by reducing the root-mean-squared-error (RMSE) by more than 30% in the lower atmosphere (from 700 hPa to surface) in both clear sky and partially cloudy conditions. A convective event from June 18, 2017 is presented to illustrate the application of the enhanced low level soundings on high impact weather events. The enhanced soundings from fused data capture the large surface-based convective available potential energy structures in the preconvection environment, which is very useful for severe storm nowcasting and forecasting applications.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2014

Exploring the Utility of the Planned CYGNSS Mission for Investigating the Initiation and Development of the Madden-Julian Oscillation

CYGNSS is a planned constellation consisting of multiple micro-satellites that leverage the Global Positioning System (GPS) to provide rapidly updated, high resolution (approx. 15-50 km, approx. 4 h) surface wind speeds (via bi-static scatterometry) over the tropical oceans in any weather condition, including heavy rainfall. The approach of the work to be presented at this conference is to utilize a limited-domain, cloud-system resolving model (Weather Research and Forecasting or WRF) and its attendant data assimilation scheme (Three-Dimensional Variational Assimilation or 3DVAR) to investigate the utility of the CYGNSS mission for helping characterize key convectiveto- mesoscale processes - such as surface evaporation, moisture advection and convergence, and upscale development of precipitation systems - that help drive the initiation and development of the Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean. The proposed work will focus on three scientific objectives. Objective 1 is to produce a high-resolution surface wind dataset resolution (approx. 0.5 h, approx. 1-4 km) for multiple MJO onsets using WRF-assimilated winds and other data from the DYNAmics of the MJO (DYNAMO) field campaign, which took place during October 2011 - March 2012. Objective 2 is to study the variability of surface winds during MJO onsets at temporal and spatial scales of finer resolution than future CYGNSS data. The goal is to understand how sub-CYGNSS-resolution processes will shape the observations made by the satellite constellation. Objective 3 is to ingest simulated CYGNSS data into the WRF model in order to perform observing system simulation experiments (OSSEs). These will be used to test and quantify the potential beneficial effects provided by CYGNSS, particularly for characterizing the physical processes driving convective organization and upscale development during the initiation and development of the MJO. The proposed research is ideal for answering important questions about the CYGNSS mission, such as the representativeness of surface wind retrievals in the context of the complex airflow processes that occur during heavy precipitation, as well as the tradeoffs in retrieval accuracy that result from finer spatial resolution of the CYGNSS winds versus increased errors/noisiness in those data. Research plans and initial progress toward these objectives will be presented.

Lang, Timothy↗

NASA NTRS2002

The Structure of A Pacific Narrow Cold Frontal Rainband

A NOAA P-3 instrumented aircraft observed an intense, fast-moving narrow cold frontal Farmhand as it approached the Pacific Northwest coast on 19 February 2001 during the Pacific Coastal Jets Experiment. Pseudo-dual-Doppler analyses performed on the airborne Doppler radar data while the frontal system was well offshore indicated that a narrow ribbon of very high radar reflectively convective cores characterized the Farmhand at low levels with echo tops to approximately 4-5 km. The NCFR exhibited gaps in its narrow ribbon of high reflectively, probably as a result of hydrodynamic instability all no its advancing cold pool leading edge. In contrast to some earlier studies of cold frontal rainbands, density current theory described well the motion of the overall front. The character of the updraft structure associated with the heavy rainfall at its leading edge varied across the gap region. The vertical shear of the cross-frontal low-level ambient flow exerted a strong influence on the updraft character, consistent with theoretical arguments developed for squall lines describing the balance of vorticity at the leading edge. In short regions south of the gaps the vertical wind shear was strongest with the updrafts and rain shafts more intense, narrower, and more erect or even downshear tilted. North of the gaps the wind shear weakened with less intense Dihedrals which tilted upshear with a broader band of rainfall. Simulations using a nonhydrostatic mesoscale nested grid model are used to investigate the gap regions, particularly the balance of cold pool induced to pre-frontal ambient shears at the leading edge. Observations confirm the model results that the updraft character depends on the balance of vorticity at the leading edge. Downshear-tilted updrafts imply that convection south of the gap regions would weaken with time relative to the frontal segments north of the gaps since inflow air would be affected by passage through the heavy rain region before ascent, suggesting a mechanism for gap filling.

Jorgensen, David P.↗

NASA NTRS1996

Simulation of Tropical Biomass Burning

The research objectives that were achieved during the course of our studies include the following: (1) Over the last few years, a model has been developed in the Atmospheric Chemistry and Dynamics Branch at Ames Research Center in collaboration with the Physics Department at San Jose State University. It is referred to as the Global/Regional Atmospheric Chemistry Event Simulator (GRACES). Currently, the GRACES model system combines an atmospheric chemistry and transport model, and a regional mesoscale meteorological model. Therefore this system is suitable for simulating the conditions observed by the tropical observation missions, such as the Pacific Exploratory Mission in the 'Tropics (PEM-Tropics), Study of Ozone and Nitrogen oxides Experiment (SONEX), and other periods. Specifically, the research carried out included the evaluation of the behavior of several components of the MM5 (I.e., Meteorological Model 5, version 2) and the GRACES combined modeling system. We initiated research on (a) the ability of the MM5 model to assimilate downward vertical velocities at least as high as the analyses, (b) the ability of the Graces model to incorporate the vertical velocities from MM5, and (c) other factors related to transport patterns required to transport CO in the observed manner. We carried out improved calculations of the transport of tracers for both NASA airborne missions, SONEX and PEM-Tropics. We also made improved source strength estimates fopr isoprene dust, and similar emissions from the Earths surface. This required the use of newly available databases on the Earth's surface and vegetation. We completed atmospheric chemistry simulations of radicals and nitrogen oxide species. We have greatly improved the handling of cumulonimnbus convection by modifing an existing scheme.

Hamill, Patrick↗

NASA NTRS2013

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

microwave observations↗

NASA NTRS1996

The 29 July 1994 Merritt Island, Fl Microburst: A Case Study Intercomparing Kennedy Space Center Three-Dimensional Lightning Data (LDAR) and WSR-88D Radar Data

Many researchers have shown that the development and evolution of electrical discharges within convective clouds is fundamentally related to the growth and dynamics of precipitation particles aloft. In the presence of strong updrafts above the freezing level collisions among mixed-phase particles (i.e., hail. ice, supercooled water) promote the necessary charge separation needed to initiate intra-cloud lightning. A precipitation core that descends below the freezing level is often accompanied by a change in the electrical structure of the cloud. Consequently, more Cloud-to-Ground (CG) than Intra-Cloud (IC) lightning flashes appear. Descending precipitation cores can also play a significant role in the evolution of mesoscale features at the surface (e.g., microbursts, downbursts) because of latent heat and mass loading effects of water and ice. For this reason, some believe that lightning and microbursts are fundamentally linked by the presence of ice particles in thunderstorms. Several radar and lightning studies of microburst thunderstorms from COHMEX in 1986 showed that the peak IC lightning systematically occurred ten minutes before the onset of a microburst. In contrast, most CG lightning occurred at the time of the microburst. Many of the preceding studies have been done using high-resolution research radars and experimental lightning detection systems in focused field projects. In addition, these studies could only determine the vertical origin or occurrence of IC lightning, and not a true three-dimensional representation. Currently, the WSR-88D radar system and a real-time, state-of-the-art lightning system (LDAR) at the Kennedy Space Center (KSC) in Florida provide an opportunity to extend these kinds of studies in a more meaningful operational setting.

Hoffert, Steven G.↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2022

A New Organization Metric for Synoptic Scale Tropical Convective Aggregation

Organization metrics were originally developed to measure how densely convective clouds are arranged at mesoscales. In this work, we apply organization metrics to describe tropical synoptic scale convective activity. Such activity is identified by cloud-precipitation (hybrid) regimes defined at 1-degree and 1-hourly resolution. Existing metrics were found to perform inadequately for such convective regime aggregates because the large domain size and co-existence of sparse aggregate occurrences with noisy isolated convection often violate assumptions inherent in these metrics. In order to capture these characteristics, in this study the existing “convective organization potential” (COP) metric was modified so as to focus on local organization and provide increased weight to aggregate size. The resulting “area-based COP” (ABCOP) follows the principle that the more numerous the objects, the higher the chance of organization. It is thus optimized to capture large-scale convective events occurring during phenomena such as ENSO and MJO, while also performs as well as existing metrics for small domain sizes.

Synoptic scales↗