Everette Joseph

Service-Oriented Environments for Dynamically Interacting with Mesoscale Weather

Within a decade after John von Neumann and colleagues conducted the first experimental weather forecast on the ENIAC computer in the late 1940s, numerical models of the atmosphere become the foundation of modern-day weather forecasting and one of the driving application areas in computer science. This article describes research that is enabling a major shift toward dynamically adaptive responses to rapidly changing environmental conditions.

CASA and LEAD: adaptive cyberinfrastructure for real-time multiscale weather forecasting

Two closely linked projects aim to dramatically improve storm forecasting speed and accuracy. CASA is creating a distributed, collaborative, adaptive sensor network of low-power, high-resolution radars that respond to user needs. LEAD offers dynamic workflow orchestration and data management in a Web services framework designed to support on-demand, real-time, dynamically adaptive systems

Regional Climate–Weather Research and Forecasting Model

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approac...

A trajectory-based estimate of the tropospheric ozone column using the residual method

We estimate the tropospheric column ozone using a forward trajectory model to increase the horizontal resolution of the Aura Microwave Limb Sounder (MLS) derived stratospheric column ozone. Subtracting the MLS stratospheric column from Ozone Monitoring Instrument total column measurements gives the trajectory enhanced tropospheric ozone residual (TTOR). Because of different tropopause definitions, we validate the basic residual technique by computing the 200-hPa-to-surface column and comparing it to the same product from ozonesondes and Tropospheric Emission Spectrometer measurements. Comparisons show good agreement in the tropics and reasonable agreement at middle latitudes, but there is a persistent low bias in the TTOR that may be due to a slight high bias in MLS stratospheric column. With the improved stratospheric column resolution, we note a strong correlation of extratropical tropospheric ozone column anomalies with probable troposphere-stratosphere exchange events or folds. The folds can be identified by their colocation with strong horizontal tropopause gradients. TTOR anomalies due to folds may be mistaken for pollution events since folds often occur in the Atlantic and Pacific pollution corridors. We also compare the 200-hPa-to-surface column with Global Modeling Initiative chemical model estimates of the same quantity. While the tropical comparisons are good, we note that chemical model variations in 200-hPa-to-surface column at middle latitudes are much smaller than seen in the TTOR.

Intercontinental Chemical Transport Experiment Ozonesonde Network Study (IONS) 2004: 1. Summertime upper troposphere/lower stratosphere ozone over northeastern North America

Coordinated ozonesonde launches from the Intercontinental Transport Experiment (INTEX) Ozonesonde Network Study (IONS) (http://croc.gsfc.nasa.gov/intex/ions.html) in July-August 2004 provided nearly 300 O3 profiles from eleven North American sites and the R/V Ronald H. Brown in the Gulf of Maine. With the IONS period dominated by low-pressure conditions over northeastern North America (NENA), the free troposphere in that region was frequently enriched by stratospheric O3. Stratospheric O3 contributions to the NENA tropospheric O3 budget are computed through analyses of O3 laminae (Pierce and Grant, 1998; Teitelbaum et al., 1996), tracers (potential vorticity, water vapor), and trajectories. The lasting influence of stratospheric incursions into the troposphere is demonstrated, and the computed stratospheric contribution to tropospheric column O3 over the R/V Ronald H. Brown and six sites in Michigan, Virginia, Maryland, Rhode Island, and Nova Scotia, 23% ± 3%, is similar to summertime budgets derived from European O3 profiles (Collette and Ancellet, 2005). Analysis of potential vorticity, Wallops ozonesondes (37.9°N, 75.5°W), and Measurements of Ozone by Airbus In-service Aircraft (MOZAIC) O3 profiles for NENA airports in June-July-August 1996–2004 shows that the stratospheric fraction in 2004 may be typical. Boundary layer O3 at Wallops and northeast U.S. sites during IONS also resembled O3 climatology (June-July-August 1996–2003). However, statistical classification of Wallops O3 profiles shows the frequency of profiles with background, nonpolluted boundary layer O3 was greater than normal during IONS.

Surface Boundary Conditions for Mesoscale Regional Climate Models

Abstract This paper utilizes the best available quality data from multiple sources to develop consistent surface boundary conditions (SBCs) for mesoscale regional climate model (RCM) applications. The primary SBCs include 1) fields of soil characteristic (bedrock depth, and sand and clay fraction profiles), which for the first time have been consistently introduced to define 3D soil properties; 2) fields of vegetation characteristic fields (land-cover category, and static fractional vegetation cover and varying leaf-plus-stem-area indices) to represent spatial and temporal variations of vegetation with improved data coherence and physical realism; and 3) daily sea surface temperature variations based on the most appropriate data currently available or other value-added alternatives. For each field, multiple data sources are compared to quantify uncertainties for selecting the best one or merged to create a consistent and complete spatial and temporal coverage. The SBCs so developed can be readily incorpor...

Multiyear Observations of the Tropical Atlantic Atmosphere: Multidisciplinary Applications of the NOAA Aerosols and Ocean Science Expeditions

This paper gives an overview of a unique set of ship-based atmospheric data acquired over the tropical Atlantic Ocean during boreal spring and summer as part of ongoing National Oceanic and Atmospheric Administration (NOAA) Aerosols and Ocean Science Expedition (AEROSE) field campaigns. Following the original 2004 campaign onboard the Ronald H. Brown, AEROSE has operated on a yearly basis since 2006 in collaboration with the NOAA Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Northeast Extension (PNE). In this work, attention is given to atmospheric soundings of ozone, temperature, water vapor, pressure, and wind obtained from ozonesondes and radiosondes launched to coincide with low earth orbit environmental satellite overpasses [MetOp and the National Aeronautics and Space Administration (NASA) A-Train]. Data from the PNE/ AEROSE campaigns are unique in their range of marine meteorological phenomena germane to the satellite missions in question, including dust and smoke outflows ...

Measuring Trans‐Atlantic aerosol transport from Africa

An estimated three billion metric tons of mineral aerosols are injected into the troposphere annually from the Saharan desert [Prospero et al., 1996]. Additionally, smoke from biomass burning sites in the savanna grasslands in sub-Saharan Africa contribute significant quantities of smaller-sized aerosols [e.g., Hobbs, 2000]. These windswept aerosols from the African continent are responsible for a variety of climate, health, and environmental impacts on both global and regional scales that span the Western Hemisphere. Unfortunately in situ measurements of aerosol evolution and transport across the Atlantic are difficult to obtain, and satellite remote sensing of aerosols can be challenging.

Comparison of MODIS cloud microphysical properties with in-situ measurements over the Southeast Pacific

Utilizing the unique characteristics of the cloud over the Southeast Pacific (SEP) off the coast of Chile during the VOCALS field campaign, we compared satellite remote sensing of cloud microphysical properties against insitu data from multi-aircraft observations, and studied the extent to which these retrieved properties are sufficiently constrained and consistent to reliably quantify the influence of aerosol loading on cloud droplet sizes. After constraining the spatial-temporal coincidence between satellite retrievals and in-situ measurements, we selected 17 non-drizzle comparison pairs. For these cases the mean aircraft profiling times were within one hour of Terra overpasses at both projected and un-projected (actual) aircraft positions for two different averaging domains of 5 km and 25 km. Retrieved quantities that were averaged over a larger domain of 25 km compared better statistically with in-situ observations than averages over a smaller domain of 5 km. Comparison at projected aircraft positions was slightly better than un-projected aircraft positions for some parameters. Overall, both MODISretrieved effective radius and LWP were larger but highly correlated with the in-situ measured effective radius and LWP, e.g., for averaging domains of 5 km, the biases are up to 1.75 μm and 0.02 mm whilst the correlation coefficients are about 0.87 and 0.85, respectively. The observed effective radius difference between the two decreased with increasing cloud drop number concentration (CDNC), and increased with increasing cloud geometrical thickness. Compared to the absolute effective radius difference, the correlations between the relative effective radius difference and CDNC or cloud geometric thickness are weaker. For averaging domains of 5 km and 25 km, the correlation coefficients between MODIS-retrieved and in-situ measured CDNC are 0.91 and 0.93 with fitting slopes of 1.23 and 1.27, respectively. If the cloud adiabaticity is taken into account, better agreements are achieved for both averaging domains (the fitting slopes are 1.04 and 1.07, respectively). Our comparison and sensitivity analysis of simulated retrievals demonstrate that both cloud geometrical thickness and cloud adiabaticity are important factors in satellite retrievals of effective radius and cloud drop number concentration. The large variabilities in cloud geometrical thickness and adiabaticity, the dependencies of cloud microphysical properties on both quantities (as demonstrated in our sensitivity study of simulated retrievals), and the inability to accurately account for either of them in retrievals lead to some uncertainties and biases in satellite retrieved cloud effective radius, cloud liquid water path, and cloud drop number concentration. However, strong correlations between satellite retrievals and in-situ measurements suggest that satellite retrievals of cloud effective radius, cloud liquid water path, and cloud drop number concentration can be used to investigate aerosol indirect effects qualitatively.

Water Vapor Measurements by Howard University Raman Lidar during the WAVES 2006 Campaign

Abstract Water vapor mixing ratio retrieval using the Howard University Raman lidar is presented with emphasis on three aspects: (i) comparison of the lidar with collocated radiosondes and Raman lidar, (ii) investigation of the relationship between atmospheric state variables and the relative performance of the lidar and sonde (in particular, their poor agreement), and (iii) comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 campaign. Ensemble averaging of water vapor mixing ratio data from 10 nighttime comparisons with Vaisala RS92 radiosondes shows, on average, an agreement within ±10%, up to ∼8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20% over the first 7 km (10% below 4 km). A grid analysis, defined in the temperature–relative humidity space, was developed to characterize the lidar–radiosonde agreement and quantitatively localizes regions of strong and...