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Jong-Jin Baik, Mark DeMaria, and Sethu Raman

Abstract

Numerical simulations of tropical cyclones in an axisymmetric model with the Betts convective adjustment scheme and the 1974 Kuo cumulus parameterization are compared. It is shown that the storm with the Betts scheme has a slightly more intense mature stage than the storm with the Kuo scheme. For both schemes, the parameterized heating is dominant initially, while the grid-scale heating is dominant at the mature stage. The storms begin to intensify rapidly when the grid-scale heating extends through a deep layer. The Betts scheme is more effective at removing water vapor and delays the onset of grid-scale heating. This results in later development of the storm with the Betts scheme. The storm evolution with both the Betts and Kuo schemes is sensitive to the treatment of the evaporation of liquid water in the grid-scale condensation scheme. This suggests that a prognostic equation for liquid water should be used when simulating tropical cyclones with a model resolution fine enough for grid-scale heating to be important.

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Jong-Jin Baik, Mark DeMaria, and Sethu Raman

Abstract

A new convective parameterization scheme proposed by Betts is tested in a tropical cyclone model. The convective adjustment scheme adjusts the local temperature and moisture structures towards the observed quasi-equilibrium thermodynamic state and includes nonprecipitating shallow convection as well as deep convection. The numerical model used for this study is an axisymmetric, primitive equation, hydrostatic, finite difference model with 15 vertical levels and a horizontal resolution of 20 km. The spectral radiation boundary condition, which uses a different gravity wave speed for each vertical mode, is implemented in the model.

It is shown that the convective scheme is capable of simulating the developing, rapidly intensifying, and mature stages of a tropical cyclone from a weak vortex. At the mature stage, the minimum surface pressure and maximum low level tangential wind speed are around 923 mb and 58 m s−1. During the early developing stage, the latent heat release is from the convective parameterization, but at the mature stage the latent heat release is mainly due to the grid-scale phase change.

For comparison, an experiment is conducted with the parameterized convection excluded, leaving only the grid-scale condensation and evaporation. The results show that the development of a tropical cyclone can be modeled with crude grid-scale condensation and evaporation processes for the 20 km horizontal resolution, similar to other studies. However, the storm with the explicit convective latent heat release is considerably less intense than that with the parameterized convective latent heat release.

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Devdutta S. Niyogi, Sethu Raman, and Kiran Alapaty

Abstract

Stomatal resistance (R s) forms a pivotal component of the surface energy budget and of the terrestrial biosphere–atmosphere interactions. Using a statistical–graphical technique, the R s-related interactions between different atmospheric and physiological variables are resolved explicitly from observations made during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). A similar analysis was undertaken for the R s parameterization schemes, as used in the present models. Three physiological schemes (the Ball–Woodrow–Berry, Kim and Verma, and Jacobs) and one operational Jarvis-type scheme were evaluated in terms of their ability to replicate the terrestrial biosphere–atmosphere interactions.

It was found that all of the R s parameterization schemes have similar qualitative behavior for routine meteorological applications (without carbon assimilation). Compared to the observations, there was no significant difference found in employing either the relative humidity or the vapor pressure deficit as the humidity descriptor in the analysis. Overall, the relative humidity–based interactions were more linear than the vapor pressure deficit and hence could be considered more convenient in the scaling exercises. It was found that with high photosynthesis rates, all of the schemes had similar behavior. It was found with low assimilation rates, however, that the discrepancies and nonlinearity in the interactions, as well as the uncertainties, were exaggerated.

Introduction of CO2 into the analysis created a different dimension to the problem. It was found that for CO2-based studies, the outcome had high uncertainty, as the interactions were nonlinear and the schemes could not converge onto a single interpretive scenario. This study highlights the secondary or indirect effects, and the interactions are crucial prior to evaluation of the climate and terrestrial biosphere–related changes even in the boundary layer perspective. Overall, it was found that direct and indirect effects could lead the system convergence toward different scenarios and have to be explicitly considered for atmospheric applications at all scales.

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Aaron P. Sims, Kiran Alapaty, and Sethu Raman

Abstract

Two mesoscale circulations, the Sandhills circulation and the sea breeze, influence the initiation of deep convection over the Sandhills and the coast in the Carolinas during the summer months. The interaction of these two circulations causes additional convection in this coastal region. Accurate representation of mesoscale convection is difficult as numerical models have problems with the prediction of the timing, amount, and location of precipitation. To address this issue, the authors have incorporated modifications to the Kain–Fritsch (KF) convective parameterization scheme and evaluated these mesoscale interactions using a high-resolution numerical model. The modifications include changes to the subgrid-scale cloud formulation, the convective turnover time scale, and the formulation of the updraft entrainment rates. The use of a grid-scaling adjustment parameter modulates the impact of the KF scheme as a function of the horizontal grid spacing used in a simulation. Results indicate that the impact of this modified cumulus parameterization scheme is more effective on domains with coarser grid sizes. Other results include a decrease in surface and near-surface temperatures in areas of deep convection (due to the inclusion of the effects of subgrid-scale clouds on the radiation), improvement in the timing of convection, and an increase in the strength of deep convection.

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Christopher Holder, Ryan Boyles, Ameenulla Syed, Dev Niyogi, and Sethu Raman

Abstract

The National Weather Service's Cooperative Observer Program (COOP) is a valuable climate data resource that provides manually observed information on temperature and precipitation across the nation. These data are part of the climate dataset and continue to be used in evaluating weather and climate models. Increasingly, weather and climate information is also available from automated weather stations. A comparison between these two observing methods is performed in North Carolina, where 13 of these stations are collocated. Results indicate that, without correcting the data for differing observation times, daily temperature observations are generally in good agreement (0.96 Pearson product–moment correlation for minimum temperature, 0.89 for maximum temperature). Daily rainfall values recorded by the two different systems correlate poorly (0.44), but the correlations are improved (to 0.91) when corrections are made for the differences in observation times between the COOP and automated stations. Daily rainfall correlations especially improve with rainfall amounts less than 50 mm day−1. Temperature and rainfall have high correlation (nearly 1.00 for maximum and minimum temperatures, 0.97 for rainfall) when monthly averages are used. Differences of the data between the two platforms consistently indicate that COOP instruments may be recording warmer maximum temperatures, cooler minimum temperatures, and larger amounts of rainfall, especially with higher rainfall rates. Root-mean-square errors are reduced by up to 71% with the day-shift and hourly corrections.

This study shows that COOP and automated data [such as from the North Carolina Environment and Climate Observing Network (NCECONet)] can, with simple corrections, be used in conjunction for various climate analysis applications such as climate change and site-to-site comparisons. This allows a higher spatial density of data and a larger density of environmental parameters, thus potentially improving the accuracy of the data that are relayed to the public and used in climate studies.

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Jainn-Jong Shi, Simon Wei-Jen Chang, and Sethu Raman

Abstract

The structure and dynamics of the outflow layer of tropical cyclones are studied using a three-dimensional numerical model. Weak and strong tropical cyclones are produced by the numerical model when starting from idealized initial vortices embedded in mean hurricane soundings. The quasi-steady state outflow layers of both the weak and strong tropical cyclones have similar characteristics 1) the circulations are mainly anticyclonic (except for a small region of cyclonic flow near the center) and highly asymmetric about the center, 2) the outflow layer is dominated by a narrow but elongated outflow jet, which contributes up to 50% of the angular momentum transport and 3) the air particles in the outflow jet mostly originate from the lower level, following “in-up-and-out” trajectories.

We found that there are secondary circulations around the outflow jet, very much like those associated with midlatitude westerly jet streaks. In the jet entrance region, the secondary circulation is thermally direct. That is, the ascending motion is located on the anticyclonic shear side of the jet, and the descending motion on the cyclonic shear side. There is a radially outward (perpendicular to the jet) flow above the jet and inflow below it. In the jet exit region, the secondary circulation is weaker and reversed in its direction (thermally indirect). The secondary circulations leave pronounced signatures on the relative humidity, potential vorticity, and tropopause height fields. The secondary circulation is more intense in the stronger tropical cyclone (with a stronger outflow jet) than in the weaker tropical cyclone.

The sensitivities to upper-tropospheric forcing of the outflow are tested in numerical experiments with prescribed forcings. It is found that the simulated tropical cyclone intensifies when its upper levels within a radius of approximately 500 km are accelerated and forced to be more divergent. Convection plays a key role in transforming the upper level divergence into low level convergence. In another experiment, additional regions of convection are initiated in the ascending branches of the circum-jet secondary circulations away from the inner region when the outflow jet between the radii of 500 and 1000 km is accelerated. These regions of convection become competitive with the inner core convection and eventually weaken the tropical cyclone. In both experiments, cumulus convection is the major link between the upper-level forcing and tropical cyclone's response.

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Dewey E. Harms, Sethu Raman, and Rangarao V. Madala

Four-dimensional data-assimilation methods, along with the most commonly used objective analysis and initialization techniques, are examined from a historical perspective. Operational techniques, including intermittent data assimilation and Newtonian nudging, and next-generation methods (Kalman–Bucy filtering and the adjoint method) are briefly described. Several methods are compared, with primary emphasis being placed on recent papers dealing with the operational assimilation techniques. Ongoing and future research is outlined, and some important implications of this research are discussed.

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Christopher Holder, Ryan Boyles, Peter Robinson, Sethu Raman, and Greg Fishel

Normal temperatures, which are calculated by the National Climatic Data Center for locations across the country, are quality-controlled, smoothed 30-yr-average temperatures. They are used in many facets of media, industry, and meteorology, and a given day's normal maximum and minimum temperatures are often used synonymously with what the observed temperature extremes “should be.” However, allowing some leeway to account for natural daily and seasonal variations can more accurately reflect the ranges of temperature that we can expect on a particular day—a “normal range.” Providing such a range, especially to the public, presents a more accurate perspective on what the temperature “usually” is on any particular day of the year. One way of doing this is presented in this study for several locations across North Carolina. The results yield expected higher variances in the cooler months and seem to well represent the varied weather that locations in North Carolina tend to experience. Day-to-day variations in the normal range are larger than expected, but are retained rather than smoothed. The method is simple and applicable to any location with a complete 30-yr record and with a temperature variance time series that follows a bell curve. The normal-range product has many potential applications.

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Dev Niyogi, Kiran Alapaty, Sethu Raman, and Fei Chen

Abstract

Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.

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Joseph J. Cione, Sethu Raman, and Leonard J. Pietrafesa

Abstract

Midlatitude cyclones develop off the Carolinas during winters and move north producing gale-force winds, ice, and heavy snow. It is believed that boundary-layer and air-sea interaction processes are very important during the development stages of these East Coast storms. The marine boundary layer (MBL) off the mid- Atlantic coastline is highly baroclinic due to the proximity of the Gulf Stream just offshore.

Typical horizontal distances between the Wilmington coastline and the western edge of the Gulf Stream vary between 90 and 250 km annually, and this distance can deviate by over 30 km within a single week. While similar weekly Gulf Stream position standard deviations also exist at Cape Hatteras, the average annual distance to the Gulf Stream frontal zone is much smaller off Cape Hatteras, normally ranging between 30 and 100 km.

This research investigates the low-level baroclinic conditions present prior to observed storm events. The examination of nine years of data on the Gulf Stream position and East Coast winter storms seems to indicate that the degree of low-level baroclinicity and modification existing prior to a cyclonic event may significantly affect the rate of cyclonic deepening off the mid-Atlantic coastline. Statistical analyses linking the observed surface-pressure decrease with both the Gulf Stream frontal location and the prestorm coastal baroclinic conditions are presented. These results quantitatively indicate that Gulf Stream-induced wintertime baroclinicity may significantly affect the regional intensification of East Coast winter cyclones.

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