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NASA NTRS2003

Analysis of Atmospheric Mesoscale Models for Entry, Descent and Landing

Each Mars Exploration Rover (MER) is sensitive to the martian winds encountered near the surface during the Entry, Descent and Landing (EDL) process. These winds are strongly influenced by local (mesoscale) conditions. In the absence of suitable wind observations, wind fields predicted by martian mesoscale atmospheric models have been analyzed to guide landing site selection. Two different models were used, the MRAMS model and the Mars MM5 model. In order to encompass both models and render their results useful to the EDL engineering team, a series of statistical techniques were applied to the model results. These analyses cover the high priority landing sites during the expected landing times (1200 to 1500 local time). The number of sites studied is limited by the computational and analysis cost of the mesoscale models.

D M Kass↗

NASA NTRS2004

High-Resolution Mesoscale Simulations of the 6-7 May 2000 Missouri Flash Flood: Impact of Model Initialization and Land Surface Treatment

High-resolution mesoscale model simulations of the 6-7 May 2000 Missouri flash flood event were performed to test the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation. In this flash flood event, a mesoscale convective system (MCS) produced over 340 mm of rain in roughly 9 hours in some locations. Two different types of model initialization were employed: 1) NCEP global reanalysis with 2.5-degree grid spacing and 12-hour temporal resolution, and 2) Eta reanalysis with 40- km grid spacing and $hour temporal resolution. In addition, two different land surface treatments were considered. A simple land scheme. (SLAB) keeps soil moisture fixed at initial values throughout the simulation, while a more sophisticated land model (PLACE) allows for r interactive feedback. Simulations with high-resolution Eta model initialization show considerable improvement in the intensity of precipitation due to the presence in the initialization of a residual mesoscale convective vortex (hlCV) from a previous MCS. Simulations with the PLACE land model show improved location of heavy precipitation. Since soil moisture can vary over time in the PLACE model, surface energy fluxes exhibit strong spatial gradients. These surface energy flux gradients help produce a strong low-level jet (LLJ) in the correct location. The LLJ then interacts with the cold outflow boundary of the MCS to produce new convective cells. The simulation with both high-resolution model initialization and time-varying soil moisture test reproduces the intensity and location of observed rainfall.

Baker, R. David↗

NASA NTRS1996

(abstract) Detection of Mesoscale Oceanic Phenomena in the Southern California Bight via ERS-1 SAR

ERS-1 SAR images are examined with the intent of identifying mesoscale oceanic phenomena in the Southern California Bight (SCB). The SCB is a region of dynamic physical and biological processes, and as such has long been studied. The ERS-1 SAR images are augmented with other remote sensing data, including SIR-C SAR, AVHRR, ERS-1 ATSR, and Space Shuttle hand-held photography. Analysis of these images has revealed a more dynamic mesoscale field than was previously suspected. Eddies with scales on the order of 20-30 km in diameter have been the most common mesoscale features evident, but the presence of oceanic fronts and internal waves, as well as atmospheric internal waves, have been documented as well. The multisensor data record will provide insight as to the underlying ocean and meterological conditions that lead to the prevalence especially of the eddies in this region.

Southern California Bight SCB remote sensing data ↗

NASA NTRS2010

Mixed Layer Sub-Mesoscale Parameterization - Part 1: Derivation and Assessment

Several studies have shown that sub-mesoscales (SM 1km horizontal scale) play an important role in mixed layer dynamics. In particular, high resolution simulations have shown that in the case of strong down-front wind, the re-stratification induced by the SM is of the same order of the de-stratification induced by small scale turbulence, as well as of that induced by the Ekman velocity. These studies have further concluded that it has become necessary to include SM in ocean global circulation models (OGCMs), especially those used in climate studies. The goal of our work is to derive and assess an analytic parameterization of the vertical tracer flux under baroclinic instabilities and wind of arbitrary directions and strength. To achieve this goal, we have divided the problem into two parts: first, in this work we derive and assess a parameterization of the SM vertical flux of an arbitrary tracer for ocean codes that resolve mesoscales, M, but not sub-mesoscales, SM. In Part 2, presented elsewhere, we have used the results of this work to derive a parameterization of SM fluxes for ocean codes that do not resolve either M or SM. To carry out the first part of our work, we solve the SM dynamic equations including the non-linear terms for which we employ a closure developed and assessed in previous work. We present a detailed analysis for down-front and up-front winds with the following results: (a) down-front wind (blowing in the direction of the surface geostrophic velocity) is the most favorable condition for generating vigorous SM eddies; the de-stratifying effect of the mean flow and re-stratifying effect of SM almost cancel each other out,

Canuto, V. M.↗

NASA NTRS2011

Comparison of Four Mixed Layer Mesoscale Parameterizations and the Equation for an Arbitrary Tracer

In this paper we discuss two issues, the inter-comparison of four mixed layer mesoscale parameterizations and the search for the eddy induced velocity for an arbitrary tracer. It must be stressed that our analysis is limited to mixed layer mesoscales since we do not treat sub-mesoscales and small turbulent mixing. As for the first item, since three of the four parameterizations are expressed in terms of a stream function and a residual flux of the RMT formalism (residual mean theory), while the fourth is expressed in terms of vertical and horizontal fluxes, we needed a formalism to connect the two formulations. The standard RMT representation developed for the deep ocean cannot be extended to the mixed layer since its stream function does not vanish at the ocean's surface. We develop a new RMT representation that satisfies the surface boundary condition. As for the general form of the eddy induced velocity for an arbitrary tracer, thus far, it has been assumed that there is only the one that originates from the curl of the stream function. This is because it was assumed that the tracer residual flux is purely diffusive. On the other hand, we show that in the case of an arbitrary tracer, the residual flux has also a skew component that gives rise to an additional bolus velocity. Therefore, instead of only one bolus velocity, there are now two, one coming from the curl of the stream function and other from the skew part of the residual flux. In the buoyancy case, only one bolus velocity contributes to the mean buoyancy equation since the residual flux is indeed only diffusive.

Canuto, V. M.↗

NASA NTRS2012

Mesoscale Simulation Data for Initializing Fast-Time Wake Transport and Decay Models

The fast-time wake transport and decay models require vertical profiles of crosswinds, potential temperature and the eddy dissipation rate as initial conditions. These inputs are normally obtained from various field sensors. In case of data-denied scenarios or operational use, these initial conditions can be provided by mesoscale model simulations. In this study, the vertical profiles of potential temperature from a mesoscale model were used as initial conditions for the fast-time wake models. The mesoscale model simulations were compared against available observations and the wake model predictions were compared with the Lidar measurements from three wake vortex field experiments.

Ahmad, Nashat N.↗

NASA NTRS2014

Range-Specific High-Resolution Mesoscale Model Setup: Data Assimilation

Mesoscale weather conditions can have an adverse effect on space launch, landing, and ground processing 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. Some of these other boundaries include the Indian River breeze front, Banana River breeze front, outflows from previous convection, horizontal convective rolls, convergence lines from other inland bodies of water such as Lake Okeechobee, the trailing convergence line from convergence of sea breeze fronts due to the shape of Cape Canaveral, frictional convergence lines from the islands in the Bahamas, convergence lines from soil moisture differences, convergence lines from cloud shading, and others. All these subtle weak boundary interactions often make forecasting of operationally important weather very difficult at KSC/CCAFS during the convective season (May-Oct). These convective processes often build quickly, last a short time (60 minutes or less), and occur over small distances, all of which also poses a significant challenge to the local forecasters who are responsible for issuing weather advisories, watches, and warnings. Surface winds during the transition seasons of 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 aid in their decision making. Both the ER and WFF would benefit greatly from high-resolution mesoscale model output 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 model at a high resolution is needed to provide improved capability. This task is a multi-year effort in which the Applied Meteorology Unit (AMU) will tune the Weather Research and Forecasting (WRF) model individually for each range. The goal of the first year, the results of which are in this report, was to tune the WRF model based on the best model resolution and run time while using reasonable computing capabilities. To accomplish this, the ER and WFF supported the tasking of the AMU to perform a number of sensitivity tests in order to determine the best model configuration for operational use at each of the ranges to best predict winds, precipitation, and temperature (Watson 2013). This task is a continuation of that work and will provide a recommended local data assimilation (DA) and numerical forecast model design optimized for the ER and WFF to support space launch activities. The model will be optimized for local weather challenges at both ranges.

Global and national scale models↗

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.↗

NASA NTRS2017

Contribution of Sub-Mesoscales to the Vertical Velocity: The Omega-Equation

The oceans ability to regulate carbon dioxide depends on biogeochemical processes that are influenced strongly by eddies. Eddy-resolving simulations have shown that sub-mesoscales (SM) (110 km) generate the highest magnitude vertical velocity and that mesoscales (M) also enhance their contribution to the vertical velocity but to a lesser extent. In this study, we consider the question: can analogous results be obtained using the less numerically demanding -equation? Previously, this question has not been answered because of two reasons: 1) the canonical Hoskins form of the - equation does not include the buoyancy vertical fluxes caused by M and SM; and 2) Giordani et al. (2016) showed how to include an arbitrary vertical buoyancy flux, but no parameterizations were available for the M and SM vertical fluxes. How- ever, the latter are now available together with their assessments, so we consider SM because they make the largest contribution to the vertical velocity. The resulting vertical velocity depends on the extent of the SM regime, the horizontal buoyancy gradient (representing baroclinic instabilities), and the SM eddy kinetic energy. The vertical velocity depends in a linear manner on the wind stress and it may exhibit seasonal variations. The wind stress has two effects on the -equation: indirectly via its contribution to the sub-mesoscale buoyancy flux and directly through the wind stress itself. The results of our sensitivity analysis highlight the range of SM-induced vertical velocities obtained using different input data.

oceans↗

NASA NTRS2023

Distributions of Mesoscale Periodic Structures in the Elemental and Ionic Composition of the Solar Wind

Multiple statistical and event studies based on in situ observations have shown that the solar wind contains mesoscale (∼ 100 – 10,000 Mm) periodic structures in the proton number density. Remote observations of such structures and event studies of concurrent variations in composition have demonstrated that they can form in the solar atmosphere and be preserved while advecting outwards through the heliosphere. Viall, Kepko, and Spence (J. Geophys. Res. (Space Phys.) 113, A07101, 2008; J. Geophys. Res. (Space Phys.) 114, A01201, 2009) and Kepko, Viall, and Wolfinger (J. Geophys. Res. (Space Phys.) 125(8), e28037, 2020) have reported that periodic proton density structures preferentially occur at specific radial length scales and have published their distributions from Wind measurements near L1. Here, we conduct a statistical study of 14 years (1998 – 2011) of 12-minute composition data measured by the Solar Wind Ion Composition Spectrometer instrument aboard the Advanced Composition Explorer spacecraft. We found that the elemental and ionic composition also contain statistically significant mesoscale periodic structures and, for the first time, present occurrence distributions for elemental abundance ratios with low, intermediate, and high first ionization potentials as well as for key solar wind charge states. These distributions set important constraints on solar wind formation in general and the formation of periodic mesoscale solar wind structures specifically, as the elemental and ionic composition are known to be determined at the Sun and to not evolve during advection.

Solar wind↗

NASA NTRS2021

Do Sub-Mesoscales Inhibit Destruction of PV?

We present the first explicit form of the three components, advective, diabatic and frictional of the PV J fluxes contributed by sub-mesoscales SM. Of particular interest is the surface value of the vertical frictional PV flux which when positive, can induce destruction of PV by down-front winds. The 2005 numerical simulations of Thomas confirmed that this is indeed the case. However, since the 12 km numerical resolution could not account for sub-mesoscales SM (0.1-10) km, the effect of SM on the PV destruction process could not be quantified. The goal of this work is to provide an answer to that question asked in the title. The two SM parameterizations entering the problem, the vertical buoyancy flux and the momentum flux (Reynolds stresses), bring about a new feature, the dependence on the SM kinetic energy (represented by the dimensionless Rossby number Ro), that causes unexpected results. While in the absence of SM, there were no restrictions on where PV destruction could occur, in the presence of SM, the condition of a positive surface vertical frictional flux is restricted to SM regimes with very low Ro<1 and very high Ro>10. Since the SM kinetic energy is location dependent, so is PV destruction. The effect of SM seems to make PV destruction a much rarer occurrence than previously thought.

potential vorticity↗

NASA NTRS1976

Mesoscale temperature and moisture fields from satellite infrared soundings

The combined use of radiosonde and satellite infrared soundings can provide mesoscale temperature and moisture fields at the time of satellite coverage. Radiance data from the vertical temperature profile radiometer on NOAA polar-orbiting satellites can be used along with a radiosonde sounding as an initial guess in an iterative retrieval algorithm. The mesoscale temperature and moisture fields at local 9 - 10 a.m., which are produced by retrieving temperature profiles at each scan spot for the BTPR (every 70 km), can be used for analysis or as a forecasting tool for subsequent weather events during the day. The advantage of better horizontal resolution of satellite soundings can be coupled with the radiosonde temperature and moisture profile both as a best initial guess profile and as a means of eliminating problems due to the limited vertical resolution of satellite soundings.

Hillger, D. W.↗

NASA NTRS1976

Investigation of mesoscale cloud features viewed by LANDSAT

The author has identified the following significant results. Some 50 LANDSAT images displaying mesoscale cloud features were analyzed. This analysis was based on the Rayleigh-Kuettner model describing the formation of that type of mesoscale cloud feature. This model lends itself to computation of the average wind speed in northerly flow from the dimensions of the cloud band configurations measured from a LANDSAT image. In nearly every case, necessary conditions of a curved wind profile and orientation of the cloud streets within 20 degrees of the direction of the mean wind in the convective layer were met. Verification of the results by direct observation was hampered, however, by the incompatibility of the resolution of conventional rawinsonde observations with the scale of the banded cloud patterns measured from LANDSAT data. Comparison seems to be somewhat better in northerly flows than in southerly flows, with the largest discrepancies in wind speed being within 8m/sec, or a factor of two.

Sherr, P. E.↗

NASA NTRS1977

An investigation of the temporal character of mesoscale perturbations in the troposphere and stratosphere

The effectiveness of mesoscale models in explaining perturbations observed in vertical detailed wind profile measurements in the troposphere and lower stratosphere is assessed. The structure and persistence of the data were analyzed and interpreted in terms of several physical models with the goal of establishing explanations for the observed persistent features of the mesoscale flow patterns. The experimental data used in the investigation were obtained by a unique detailed wind profile measurement system. This system is capable of providing resolution of 50 to 100 m wavelengths for the altitude region from approximately 200 m to 18 km. The system consists of a high-resolution tracking radar and special super-pressure balloon configuration known as a Jimsphere.

Vaughan, W. W.↗

NASA NTRS1977

Mesoscale cloud phenomena observed by LANDSAT

Examples of certain mesoscale cloud features - jet cirrus, eddies/vortices, cloud banding, and wave clouds - were collected from LANDSAT imagery and placed into Mason's four groups of causes of cloud formation based on the mechanism of vertical motion which produces condensation. These groups are as follows: (1) layer clouds formed by widespread regular ascent; (2) layer clouds caused by irregular stirring motions; (3) convective clouds; and (4) clouds formed by orographic disturbances. These mechanisms explain general cloud formation. Once formed, other forces may play a role in the deformation of a cloud or cloud mass into unusual and unique meso- and microscale patterns. Each example presented is followed by a brief discussion describing the synoptic situation, and some inference into the formation and occurrence of the more salient features. No major attempt was made to discuss in detail the meteorological and topographic interplay producing these mesoscale features.

Ormsby, J. P.↗

NASA NTRS1977

Comparisons among second-order, fourth-order, and pseudospectral advection techniques in a mesoscale numerical model

The reported investigation is concerned with mesoscale squall-line simulation utilizing numerical techniques. Particular attention is given to fourth-order results and their implications for the dynamical evolution of mesoscale squall-line systems which contain severe local storms. An adiabatic inviscid set of prognostic equations is utilized in a z coordinate system for the fundamental experiment. The fourth-order advection is employed for all time-dependent equations. The Euler-backward time marching scheme is utilized with a 60 second time step. The horizontal mesh length is 42 km. Horizontal diffusion is accomplished by utilizing a smoother-desmoother. Lateral boundary conditions are designed to reduce the development of strong gradients in dependent variables near the boundaries by bringing interior values from the grid to the boundaries.

Kaplan, M.↗

NASA NTRS1979

Covariance analyses of satellite-derived mesoscale wind fields

Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.

Maddox, R. A.↗

NASA NTRS1979

Shallow convection on day 261 of GATE - Mesoscale arcs

Cloudy convection in the moist layer of a cloud cluster growing in the GATE ship array is examined. Analyses suggest that the moist layer was dominated by features of horizontal dimension roughly 40 km and lifetime roughly 2 h, with arc patterns triggered by dense downdraft air accompanying rainfall, and composed of many small cumulus clouds. Aircraft recorded data on thermodynamic quantities and winds, indicating that the arcs persisted as mesoscale circulations driven by the release of latent heat in the clouds, rather than being driven by the original density current at the surface. It is also suggested that the mesoscale cloud patterns of the moist layer play a primary role in heat transfer upward within this layer, and contribute to the forcing of showering midtropospheric clouds.

Warner, C.↗