Search

Changes in aerosol optical depth, both positive and negative, are observed across the globe during the 21rst Century. However, attribution of these changes to specific sources is largely uncertain ...

We investigate the air quality impact of record‐breaking wildfires in Southern California during 5–18 December 2017 using the Weather Research and Forecasting model with Chemistry in combination with satellite and surface observations. This wildfire event was driven by dry and strong offshore Santa Ana winds, which played a critical role in fire formation and air pollutant transport. By utilizing fire emissions derived from the high‐resolution (375 × 375 m²) Visible Infrared Imaging Radiometer Suite active fire detections, the simulated magnitude and temporal evolution of fine particulate matter (PM_(2.5)) concentrations agree reasonably well with surface observations (normalized mean bias = 4.0%). Meanwhile, the model could generally capture the spatial pattern of aerosol optical depth from satellite observations. Sensitivity tests reveal that using a high spatial resolution for fire emissions and a reasonable treatment of plume rise (a fair split between emissions injected at surface and those lifted to upper levels) is important for achieving decent PM_(2.5) simulation results. Biases in PM_(2.5) simulation are relatively large (about 50%) during the period with the strongest Santa Ana wind, due to a possible underestimation of burning area and uncertainty in wind field variation. The 2017 December fire event increases the 14‐day averaged PM_(2.5) concentrations by up to 231.2 μg/m³ over the downwind regions, which substantially exceeds the U.S. air quality standards, potentially leading to adverse health impacts. The human exposure to fire‐induced PM_(2.5) accounts for 14–42% of the annual total PM_(2.5) exposure in areas impacted by the fire plumes.

Atmospheric aerosols are an important element of Earth’s climate system, and have significant impacts on the environment and on human health. Global aerosol modeling has been increasingly used for operational forecasting and as support to decision making. For example, aerosol analyses and forecasts are routinely used to provide air quality information and alerts in both civilian and military applications. The growing demand for operational aerosol forecasting calls for additional observational data that can be assimilated into models to improve model accuracy and predictive skill. These factors have motivated the development, testing, and release of a new near real-time (NRT) level 2 (L2) aerosol product from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA’s Terra platform. The NRT product capitalizes on the unique attributes of the MISR aerosol retrieval approach and product contents, such as reliable aerosol optical depth as well as aerosol microphysical information. Several modifications are described that allow for rapid product generation within a three-hour window following acquisition of the satellite observations. Implications for the product quality and consistency are discussed as compared to the current operational L2 MISR aerosol product. Several ways of implementing additional use-specific retrieval screenings are also highlighted.

Operational retrievals of aerosol optical depth (AOD) from Multi-angle Imaging SpectroRadiometer (MISR) data have been shown to have a high bias in pristine oceanic areas. One line of evidence involves comparison with Maritime Aerosol Network (MAN) observations, including the areas of low aerosol loading close to Antarctica. In this paper, a principal reason for the AOD overestimation is identified, which is stray light measured by the MISR cameras in dark regions of high-contrast scenes. A small fraction of the light from surrounding bright areas, such as clouds or sea ice, is redistributed to dark areas, artificially increasing their brightness. Internal reflections and light scattering from optical elements in MISR’s pushbroom cameras contribute to this veiling light effect. A simple correction model is developed that relies on the average scene brightness and an empirically determined set of veiling light coefficients for each MISR camera and wavelength. Several independent methods are employed to determine these coefficients. Three sets of coefficients are further implemented and tested in prototype MISR 4.4-km AOD retrievals. The results show dramatic improvements in retrieved AODs compared against MAN observations and the currently operational V22 MISR retrievals. For the best performing set of coefficients, the bias is reduced by 51%, from 0.039 to 0.019, the RMSE is lowered by 19%, from 0.062 to 0.050, and 84% of retrievals fall within the uncertainty envelope compared with 66% of retrievals in V22. The best performing set will be implemented operationally in the next V23 MISR AOD product release.

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, “best estimate” AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

The Multi-angle Imaging SpectroRadiometer (MISR) instrument has been operational on the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Terra satellite since early 2000, creating an extensive data set of global Earth observations. Here we introduce the latest version of the MISR aerosol products. The Level 2 (swath) product, which is reported on a 4.4 km spatial grid, is designated Version 23 (V23) and contains retrieved aerosol optical depth (AOD) and aerosol particle property information derived from MISR's multi-angle observations over both land and water. The changes from the previous version of the algorithm (V22) have significant impacts on the data product and its interpretation. The V23 data set is created from two separate retrieval algorithms that are applied over dark water and land surfaces, respectively. Besides increasing the horizontal resolution to 4.4 km compared with the coarser 17.6 m resolution in V22, and streamlining the format and content, the V23 product has added geolocation information, pixel-level uncertainty estimates, and improved cloud screening. MISR data can be obtained from the NASA Langley Research Center Atmospheric Science Data Center at https://eosweb.larc.nasa.gov/project/misr/misr_table. The version number for the V23 Level 2 aerosol product is F13_0023. The Level 3 (gridded) aerosol product is still reported at 0.5° x 0.5° spatial resolution with results aggregated from the higher-resolution Level 2 data. The format and content at Level 3 have also been updated to reflect the changes made at Level 2. The Level 3 product associated with the V23 Level 2 product version is designated F15_0032. Both the Level 2 and Level 3 products are now provided in NetCDF format.

Recent years have seen the increasing inclusion of per-retrieval prognostic (predictive) uncertainty estimates within satellite aerosol optical depth (AOD) data sets, providing users with quantitative tools to assist in the optimal use of these data. Prognostic estimates contrast with diagnostic (i.e. relative to some external truth) ones, which are typically obtained using sensitivity and/or validation analyses. Up to now, however, the quality of these uncertainty estimates has not been routinely assessed. This study presents a review of existing prognostic and diagnostic approaches for quantifying uncertainty in satellite AOD retrievals, and it presents a general framework to evaluate them based on the expected statistical properties of ensembles of estimated uncertainties and actual retrieval errors. It is hoped that this framework will be adopted as a complement to existing AOD validation exercises; it is not restricted to AOD and can in principle be applied to other quantities for which a reference validation data set is available. This framework is then applied to assess the uncertainties provided by several satellite data sets (seven over land, five over water), which draw on methods from the empirical to sensitivity analyses to formal error propagation, at 12 Aerosol Robotic Network (AERONET) sites. The AERONET sites are divided into those for which it is expected that the techniques will perform well and those for which some complexity about the site may provide a more severe test. Overall, all techniques show some skill in that larger estimated uncertainties are generally associated with larger observed errors, although they are sometimes poorly calibrated (i.e. too small or too large in magnitude). No technique uniformly performs best. For powerful formal uncertainty propagation approaches such as optimal estimation, the results illustrate some of the difficulties in appropriate population of the covariance matrices required by the technique. When the data sets are confronted by a situation strongly counter to the retrieval forward model (e.g. potentially mixed land–water surfaces or aerosol optical properties outside the family of assumptions), some algorithms fail to provide a retrieval, while others do but with a quantitatively unreliable uncertainty estimate. The discussion suggests paths forward for the refinement of these techniques.

The current operational eddy-diffusivity countergradient (EDCG) planetary boundary layer (PBL) scheme in the NCEP Global Forecast System (GFS) tends to underestimate the PBL growth in the convective boundary layer (CBL). To improve CBL growth, an eddy-diffusivity mass-flux (EDMF) PBL scheme is developed, where the nonlocal transport by large turbulent eddies is represented by a mass-flux (MF) scheme and the local transport by small eddies is represented by an eddy-diffusivity (ED) scheme. For the vertical momentum mixing, the MF scheme is modified to include the effect of the updraft-induced pressure gradient force. While the EDMF scheme displays better CBL growth than the EDCG scheme, it tends to overproduce the amount of low clouds and degrades wind vector forecasts over the tropical ocean where strongly unstable PBLs are rarely found. In order not to degrade the forecast skill in the tropics, a hybrid scheme is developed, where the EDMF scheme is applied only for the strongly unstable PBL, while the EDCG scheme is used for the weakly unstable PBL. Along with the hybrid EDMF scheme, the heating by turbulent kinetic energy (TKE) dissipation is parameterized to reduce an energy imbalance in the GFS. To enhance a too weak vertical turbulent mixing for weakly and moderately stable conditions, the current local scheme in the stable boundary layer (SBL) is modified to use an eddy-diffusivity profile method. The hybrid EDMF PBL scheme with TKE dissipative heating and modified SBL mixing led to significant improvements in some key medium-range weather forecast metrics and was operationally implemented into the NCEP GFS in January 2015.

Despite many years of observations by multiple sensors, there is still substantial ambiguity regarding aerosol optical depths (AOD) over remote oceans, in particular, over the pristine Southern Ocean. Passive satellite retrievals (e.g., Multiangle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS)) and global aerosol transport models show a distinct AOD maximum around the 60°S latitude band. Sun photometer measurements performed by the Maritime Aerosol Network (MAN), on the other hand, indicate no increased AODs over the Southern Ocean. In this study elevated Southern Ocean AODs are examined from the modeling perspective. The primary aerosol component over the Southern Ocean is sea spray aerosol (SSA). Multiple simulations of SSA concentrations and optical depths are carried out using a single modeling framework, the Navy Aerosol Analysis and Prediction System (NAAPS) model. Several SSA emission functions are examined, including recently proposed formulations with sea surface temperature corrections. The differences between NAAPS simulations are primarily due to different SSA emission formulations. The results are compared against satellite-derived AODs from the MISR and MODIS instruments. MISR and MODIS AOD retrievals are further filtered to eliminate retrievals potentially affected by cloud contamination and cloud adjacency effects. The results indicate a very large impact of SSA emission parameterization on the simulated AODs. For some scenarios, the Southern Ocean AOD maximum almost completely disappears. Further MISR and MODIS AOD quality screening substantially improves model/satellite agreement. Based on these comparisons, an optimal SSA emission function for global aerosol transport models is recommended.

Visible to the naked eye, the gas giants Jupiter and Saturn have been known to astronomers since antiquity. In the modern times much was learned about them, and yet so much remains to be learned. They are made almost entirely of hydrogen and helium, they have no hard surface to land to; their low temperature atmospheres are characterized by strong winds, at least in the observed upper atmosphere. What we know about them comes from remote sensing—yet their clouds impede deeper observation through remote sensing. We also have, in a singular case, data transmitted by a robotic probe that descended through the Jovian atmosphere. We need more of these probes, to confirm the models we formed about these planets, and to discover new phenomena below their clouds. This chapter examines mission concept alternatives in which robotic craft operate in the atmospheres of gas giants, for long duration, and using energy derived from local sources. In a preferred scenario these Wind Robots (WBs), with high mobility and autonomy compared to passive balloons, would operate in the Jovian atmosphere above and below the region of clouds, between 0.3 and 10 bar, for a year-long duration mission, in strong (potentially turbulent) winds. In an example, notional mission, a WB would operate in the eyewall of the Great Red Spot, using the high wind and updrafts of the anticyclone, as well as horizontal gusts. Both naturally buoyant and winged solutions, as well as hybrids of the two, are determined possible. A Network of WBs could measure wind speeds, temperatures, and atmospheric composition simultaneously, at multiple locations.

In this study a new approach to the vertical transport of the turbulent kinetic energy (TKE) is proposed. The principal idea behind the new parameterization is that organized updrafts or convective plumes play an important role in transferring TKE vertically within convectively driven boundary layers. The parameterization is derived by applying an updraft environment decomposition to the vertical velocity triple correlation term in the TKE prognostic equation. The additional mass flux (MF) term that results from this decomposition closely resembles the features of the TKE transport diagnosed from the large-eddy simulation (LES) and accounts for 97% of the LES-diagnosed transport when the updraft fraction is set to 0.13. Another advantage of the MF term is that it is a function of the updraft vertical velocity and can be readily calculated using already existing parameterization. The new MF approach, combined with several eddy diffusivity (ED) formulations, is implemented into a simplified 1D TKE prognostic model. The 1D model results, compared against LES simulations of dry convective boundary layers, show substantial improvement in representing the vertical structure of TKE. The new combined ED–MF parameterization, as well as the MF term alone, surpasses in accuracy the ED parameterizations. The proposed TKE transport parameterization shows large potential of improving TKE simulations in mesoscale and global circulation models.

This study presents a new approach to the eddy diffusivity/mass flux (EDMF) framework for the modeling of convective boundary layers. At the root of EDMF lies a decomposition of turbulent transport mechanisms into strong ascending updrafts and smaller-scale turbulent motions. The turbulent fluxes can be therefore described using two conventional approaches: mass flux (MF) for the organized thermals and eddy diffusivity (ED) for the remaining turbulent field. Since the intensities of both MF and ED transports depend on the kinetic energy of the turbulent motions, it seems reasonable to formulate an EDMF framework based on turbulent kinetic energy (TKE). Such an approach allows for more physical and less arbitrary formulations of parameters in the model. In this study the EDMF–TKE coupling is achieved through the use of (i) a new parameterization for the lateral entrainment coefficient ɛ and (ii) the MF contribution to the buoyancy source of TKE. Some other important features of the EDMF parameterization presented here include a revised mixing length formulation and Monin–Obukhov stability scaling for the surface layer. The scheme is implemented in a one-dimensional (1D) model. Several cases of dry convective boundary layers (CBL) with different surface sensible heat fluxes in the free-convection limit are investigated. Results are compared to large-eddy simulation (LES). Good agreement between LES and the 1D model is achieved with respect to mean profiles, boundary layer evolution, and updraft characteristics. Some disagreements between the models are found to most likely relate to deficiencies in the TKE simulation in the 1D model. Comparison with other previously established ɛ parameterizations shows that the new TKE-based formulation leads to equally accurate, and in many respects better, simulation of the CBL. The encouraging results obtained with the proposed EDMF framework indicate that full integration of EDMF with higher-order closures is possible and can further improve boundary layer simulations.

In this study the importance of sea salt aerosol (SSA) size representation in a global transport model is investigated. For this purpose the Navy Aerosol Analysis and Prediction System (NAAPS) model is employed in a number of SSA simulations. A new dry deposition velocity parameterization is implemented into NAAPS in order to more physically represent deposition processes in the model. SSA size distribution is divided into size bins using two different partition procedures: the previously used iso-log method and the iso-gradient method, which relies on size-dependence of deposition processes. The global SSA simulations are analyzed in terms of the total sea salt mass and the average SSA optical thickness. The results indicate that there is a large dependence of the total mass and average aerosol optical depth on the number of size bins used to represent the aerosol size distribution. The total SSA mass is underestimated by 20% if 2 instead of 15 (reference) size intervals are used. The average aerosol opt...

This study contains a comparative analysis of aerosol optical thickness (AOT) between numerical calculations obtained from the Navy Aerosol Analysis and Prediction System (NAAPS) model and direct observations from the AERONET robotic network and the Saharan Aerosol over WArsaw (SAWA) field campaign. AOT was calculated for 500 nm wavelength. The comparison shows underestimation of the total aerosol optical thickness simulated by NAAPS. The correlation coefficients between model and observation oscillates between 0.57 and 0.72. Results of seven-year (1998–2004) NAAPS simulation of aerosol components (sea salt, mineral dust, sulphate, and smoke) show large temporal and spatial variability of the aerosol optical thickness over Europe. The least polluted region is the Iberian Peninsula, while the highest aerosol burdens occurred in Central Europe, mostly due to anthropogenic sulphate particles. Finally, the analysis of mineral dust transport shows frequent episodes of Saharan dust inflow over Central Europe. There are about 20 days a year (4 days in May) when instantaneous AOT associated with mineral dust aerosol increases over 0.1.

In this paper two stable and explicit numerical methods to integrate the one-dimensional (1D) advection-diffusion equation are presented. These schemes are stable by design and follow the main general concept behind the semi-Lagrangian method by constructing a virtual grid where the explicit method becomes stable. It is shown that the new schemes compare well with analytic solutions and are often more accurate than implicit schemes. In particular, the diffusion-only case is explored in some detail. The error produced by the stable and explicit method is a function of the ratio between the standard deviation @s"0 of the initial Gaussian state and the characteristic virtual grid distance @DS. Larger values of this ratio lead to very accurate results when compared to implicit methods, while lower values lead to less accuracy. It is shown that the @s"0/@DS ratio is also significant in the advection-diffusion problem: it determines the maximum error generated by new methods, obtained with a certain combination of the advection and diffusion values. In addition, the error becomes smaller when the problem becomes more advective or more diffusive.

Aerosol radiative forcing in the Persian Gulf region is derived from data collected during the United Arab Emirates (UAE) Unified Aerosol Experiment (UAE2). This campaign took place in August and September of 2004. The land–sea-breeze circulation modulates the diurnal variability of the aerosol properties and aerosol radiative forcing at the surface. Larger aerosol radiative forcing is observed during the land breeze in comparison to the sea breeze. The aerosol optical properties change as the onshore wind brings slightly cleaner air. The mean diurnal value of the surface aerosol forcing during the UAE2 campaign is about −20 W m−2, which corresponds to large aerosol optical thickness (0.45 at 500 nm). The aerosol forcing efficiency [i.e., broadband shortwave forcing per unit optical depth at 550 nm, W m−2 (τ500)−1] is −53 W m−2 (τ500)−1 and the average single scattering albedo is 0.93 at 550 nm.

Long-term surface observations indicate that soil dust represents over 30% of the annual fine (particle diameter less than 2.5 μm) particulate mass in many areas of the western US; in spring and summer, it represents an even larger fraction. There are numerous dust-producing playas in the western US, but surface dust aerosol concentrations in this region are also influenced by dust of Asian origin. This study examines the seasonality of surface soil dust concentrations at 15 western US sites using observations from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network from 2001 to 2004. Average soil concentrations in particulate matter less than 10 μm in diameter (PM 10 ) were lowest in winter and peaked during the summer months at these sites; however, episodic higher-concentration events (>10 μg m −3 ) occurred in the spring, the time of maximum Asian dust transport to the western US. Simulated surface dust concentrations from the Navy Aerosol Analysis and Prediction System (NAAPS) suggested that long-range transport from Asia dominates surface dust concentrations in the western US in the spring, and that, although some long-range transport does occur throughout the year (1–2 μg m −3 ), locally generated dust plays a larger role in the region in summer and fall. However, NAAPS simulated some anomalously high concentrations (>50 μg m −3 ) of local dust in the fall and winter months over portions of the western US. Differences between modeled and observed dust concentrations were attributed to overestimation of total observed soil dust concentrations by the assumptions used to convert IMPROVE measurements into PM 10 soil concentrations, lack of inhibition of model dust production in snow-covered regions, and lack of seasonal agricultural sources in the model.

The aim of this study is to investigate the sensitivity of radiative-forcing computations to various contrail crystal shape models. Contrail optical properties in the shortwave and longwave ranges are derived using a ray-tracing geometric method and the discrete dipole approximation method, respectively. Both methods present good correspondence of the single-scattering albedo and the asymmetry parameter in a transition range (3–8 μm). There are substantial differences in single-scattering properties among 10 crystal models investigated here (e.g., hexagonal columns and plates with different aspect ratios, and spherical particles). The single-scattering albedo and the asymmetry parameter both vary by up to 0.1 among various crystal shapes. The computed single-scattering properties are incorporated in the moderate-resolution atmospheric radiance and transmittance model (MODTRAN) radiative transfer code to simulate solar and infrared fluxes at the top of the atmosphere. Particle shapes have a strong impact on the contrail radiative forcing in both the shortwave and longwave ranges. The differences in the net radiative forcing among optical models reach 50% with respect to the mean model value. The hexagonal-column and hexagonal-plate particles show the smallest net radiative forcing, and the largest forcing is obtained for the spheres. The balance between the shortwave forcing and longwave forcing is highly sensitive with respect to the assumed crystal shape and may even change the sign of the net forcing. The optical depth at which the mean diurnal radiative forcing changes sign from positive to negative varies from 4.5 to 10 for a surface albedo of 0.2 and from 2 to 6.5 for a surface albedo of 0.05. Contrails are probably never that optically thick (except for some aged contrail cirrus), however, and so will not have a cooling effect on climate.

[1] A new approach to sea salt parameterization is proposed which incorporates wind-wave characteristics into the sea salt emission function and can be employed globally and under swell-influenced conditions. The new source function was applied into Navy Aerosol Analysis and Prediction System model together with predictions from the global wave model Wave Watch III. The squared surface wind velocity U10 and the wave's orbital velocity Vorb=πHs/TP are shown to be the key parameters in the proposed parameterization. Results of the model simulations are validated against multi-campaign shipboard measurements of the sea salt aerosol. The validations indicate a good correlation between Vorb and the measured surface concentrations. The model simulations with the new parameterization exhibit an improved agreement with the observations when compared to a wind-speed-only approach. The proposed emission parameterization has the potential to improve the simulations of sea salt emission in aerosol transport models.

[1] Open-ocean measurements of sea-salt concentrations from five different campaigns are used to validate the sea-salt parameterization in numerical models. The data set is unique in that it is from open-ocean shipboard measurements which alleviates typical problems associated with onshore wave breaking on land stations (surf zone). The validity of the sea-salt parameterizations is tested by employing a global forecasting model and transport model with detailed representation of dry and wet deposition, advection and diffusion, and other physical processes. It is shown that the inclusion of these processes leads to good agreement with shipboard measurements. The correlation coefficient of measured and modeled sea-salt mass concentrations for all data points was 0.76 and varied from 0.55 to 0.84 for different experiments. Average sea-salt mass concentration was 4.6μg/m3 from measurements and 7.3 μg/m3 from the model, for all considered experiments. It was found that model-measurements discrepancies were affected by wet deposition uncertainties but also suggested was the influence of source uncertainties in the strong wind-speed regime, lack of a wind-speed threshold for emission onset, and lack of size differentiation in applied deposition velocity. No apparent relationship between the water temperature and the measured sea-salt concentration was found in the analyzed data set.

[1] The spectral aerosol absorption properties in the Arabian Gulf region were observed during the United Arab Emirates Unified Aerosol Experiment (UAE2). Measurements were taken at a coastal region of the Arabian Gulf located 60 km northeast of Abu Dhabi, the capital of the United Arab Emirates, allowing characterization of pollution and dust absorption properties in a highly heterogeneous environment. A large observed change of the diurnal signal during the period under study (27 August through 30 September 2004) was due to (1) strong sea and land breeze and (2) changes in prevailing synoptic-scale flow. During the night, stagnating air resulted in gradual accumulation of pollution with maximum absorption in the early morning hours. The rising sun increased both the depth of the boundary layer and the temperature of the interior desert, resulting in strong and sudden sea breeze onset which ventilated the polluted air accumulated during the night. Our observations show that the onshore winds brought cleaner air resulting in decreasing values of the absorption coefficient and increasing values of the single-scattering albedo (SSA). The mean value of the absorption coefficient at 550 nm measured during the sea breeze was 10.2 ± 0.9 Mm−1, while during the land breeze it was 13.8 ± 1.2 Mm−1. Synoptic-scale transport also strongly influenced particle fine/coarse partition with “northern” flow bringing pollution particles and “southern” flow bringing more dust.

Our long-term goal is to implement an operational high-resolution atmospheric data assimilation and prediction system and to use it for daily weather forecasting. To date we have worked on several operational and scientific aspects of the problem using the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS(registered)1): (a) setting up stable large scale data transfer capabilities to facilitate COAMPS runs 2-4 times per day in an operational manner for different geographical regions and using different nested grid configurations; (b) perform research on the MPI scalability of COAMPS on selected computer architectures and to optimize the code to take advantage of the vector capabilities of the Cray X1 and the massively parallel features of our Linux cluster; (c) identify and understand the uncertainties in high-resolution NWP forecast and their impact on severe weather, such as extreme rainfall, and to develop model metrics appropriate to mesoscale weather phenomena; and (d) improve our knowledge of observational error characteristics for spatially correlated data and develop the numerical schemes capable of assimilating these types of observations.