Search

The New York State Mesonet (NYSM) has provided continuous in situ and remote sensing observations near the surface and within the lower troposphere since 2017. The dense observing network can capture the evolution of mesoscale motions with high temporal and spatial resolution. The objective of this study was to investigate whether the assimilation of NYSM observations into numerical weather prediction models could be beneficial for improving model analysis and short-term weather prediction. The study was conducted using a convective event that occurred in New York on 21 June 2021. A line of severe thunderstorms developed, decayed, and then reintensified as it propagated eastward across the state. Several data assimilation (DA) experiments were conducted to investigate the impact of NYSM data using the operational DA system Gridpoint Statistical Interpolation with rapid update cycles. The assimilated datasets included National Centers for Environmental Prediction Automated Data Processing global upper-air and surface observations, NYSM surface observations, Doppler lidar wind retrievals, and microwave radiometer (MWR) thermodynamic retrievals at NYSM profiler sites. In comparison with the control experiment that assimilated only conventional data, the timing and location of the convection reintensification was significantly improved by assimilating NYSM data, especially the Doppler lidar wind data. Our analysis indicated that the improvement could be attributed to improved simulation of the Mohawk–Hudson Convergence. We also found that the MWR DA resulted in degraded forecasts, likely due to large errors in the MWR temperature retrievals. Overall, this case study suggested the positive impact of assimilating NYSM surface and profiler data on forecasting summertime severe weather.

The New York State Mesonet (NYSM) is a network of 126 standard environmental monitoring stations deployed statewide with an average spacing of 27 km. The primary goal of the NYSM is to provide high-quality weather data at high spatial and temporal scales to improve atmospheric monitoring and prediction, especially for extreme weather events. As compared with other statewide networks, the NYSM faced considerable deployment obstacles with New York’s complex terrain, forests, and very rural and urban areas; its wide range of weather extremes; and its harsh winter conditions. To overcome these challenges, the NYSM adopted a number of innovations unique among statewide monitoring systems, including 1) strict adherence to international siting standards and metadata documentation; 2) a hardened system design to facilitate continued operations during extreme, high-impact weather; 3) a station design optimized to monitor winter weather conditions; and 4) a camera installed at every site to aid situational awareness. The network was completed in spring of 2018 and provides data and products to a variety of sectors including weather monitoring and forecasting, emergency management, agriculture, transportation, utilities, and education. This paper focuses on the standard network of the NYSM and reviews the network siting, site configuration, sensors, site communications and power, network operations and maintenance, data quality control, and dissemination. A few example analyses are shown that highlight the benefits of the NYSM.

Aqueous chemical processing within cloud and fog water is thought to be a key process in the production and transformation of secondary organic aerosol mass, found abundantly and ubiquitously throughout the troposphere. Yet, significant uncertainty remains regarding the organic chemical reactions taking place within clouds and the conditions under which those reactions occur, owing to the wide variety of organic compounds and their evolution under highly variable conditions when cycled through clouds. Continuous observations from a fixed remote site like Whiteface Mountain (WFM) in New York State and other mountaintop sites have been used to unravel complex multiphase interactions in the past, particularly the conversion of gas-phase emissions of SO2 to sulfuric acid within cloud droplets in the presence of sunlight. These scientific insights led to successful control strategies that reduced aerosol sulfate and cloud water acidity substantially over the following decades. This paper provides an overview of observations obtained during a pilot study that took place at WFM in August 2017 aimed at obtaining a better understanding of Chemical Processing of Organic Compounds within Clouds (CPOC). During the CPOC pilot study, aerosol cloud activation efficiency, particle size distribution, and chemical composition measurements were obtained below-cloud for comparison to routine observations at WFM, including cloud water composition and reactive trace gases. Additional instruments deployed for the CPOC pilot study included a Doppler lidar, sun photometer, and radiosondes to assist in evaluating the meteorological context for the below-cloud and summit observations.

This paper uses the “Super Outbreak” of 2011 as a case study to examine the potential gaps between the dissemination of severe weather warnings and the public’s behavioral response to this information. This study focuses on a single tornado track that passed through Tuscaloosa, Alabama. The tornado caused massive damage and destruction and led to a total of 62 fatalities. The threat of severe storms was known days in advance, and forecasts were disseminated to the public. Questions were raised about the forecasts, warning lead times, and the perception of the warnings among residents. This paper examines the potential gaps that exist between the dissemination of tornadic warning information and citizen response. The analysis of data collected through a mixed-method approach suggests that, regardless of weather forecast accuracy, a significant chasm exists between the dissemination of warnings and the personalizing of risks, which results in limited use of protective measures in the face of severe weather threats.

Vertical profiles of atmospheric temperature, moisture, wind, and aerosols are essential information for weather monitoring and prediction. Their availability, however, is limited in space and time due to the significant resources required to observe them. To fill this gap, the New York State Mesonet (NYSM) Profiler Network has been deployed as a national testbed to facilitate the research, development and evaluation of ground-based profiling technologies and applications. The testbed comprises 17 profiler stations across the state, forming a long-term regional observational network. Each Profiler station is comprised of a ground-based Doppler lidar, a microwave radiometer (MWR) and an environmental Sky Imaging Radiometer (eSIR). Thermodynamic profiles (temperature and humidity) from the MWR; wind and aerosol profiles from the Doppler lidar; and solar radiance and optical depth parameters from the eSIR are collected, processed, disseminated, and archived every 10 minutes. This paper introduces the NYSM Profiler Network and reviews the network design and siting, instrumentation, network operations and maintenance, data and products, and some example applications highlighting the benefits of the network. Some sample applications include improved situational awareness and monitoring of the sea/land breeze, long-range wildfire smoke transport, air quality (PM2.5 and AOD) and boundary layer height. Ground-based profiling systems promise a path forward for filling a critical gap in the nation’s observing system with the potential to improve analysis and prediction for many weather-sensitive sectors, such as aviation, ground transportation, health, and wind energy.

Twenty-six balloon-borne ozonesondes were launched near the north shore of central Long Island in the summers of 2018 and 2019 as part of the Long Island Sound Tropospheric Ozone Study (LISTOS). Wh...

The microphysical features of the typhoon (TY) and non-typhoon (NTY) rainfall in summer seasons are analyzed using long-term (2004 to 2016) data from the impact disdrometer installed in north Taiwan. The RSD stratified based on rainfall rate showed distinct RSD characteristics between TY and NTY rainfall. More (less) number of small (big) size raindrops are noticed in TY rainfall than NTY rainfall. RSD features in terms of gamma parameters are studied for these two weather regimes. The mass-weighted mean diameter (Dm) values are higher in NTY than TY rainfall, and an inverse behavior is observed for the normalized intercept parameter (Nw). Even after separating the rainfall regimes into convective and stratiform type, a large Dm is found in NTY compared to TY precipitation. Distinct variations in Z–R, Dm–R, Nw–R, KE–R, and KE–Dm relations are noticed between TY and NTY rainfall. Possible mechanisms responsible for the RSD variations between TY and NTY are discussed using reanalysis, remote-sensing, and ground-based radar datasets.

This paper continues an overview of the validation of operational profile retrievals from the Suomi National Polar-Orbiting Partnership (SNPP), with focus here given to the infrared (IR) ozone profile environmental data record (EDR) product. The SNPP IR ozone profile EDR is retrieved using the cross-track IR sounder (CrIS), a Fourier transform spectrometer that measures high-resolution IR earth radiance spectra containing atmospheric state information, namely, vertical profiles of temperature, moisture, and trace gas constituents. The SNPP CrIS serves as the U.S. low earth orbit (LEO) satellite IR sounding system and will be featured on future Joint Polar Satellite System (JPSS) LEO satellites. The operational sounding algorithm is the National Oceanic and Atmospheric Administration-Unique Combined Atmospheric Processing System (NUCAPS), a legacy sounder science team algorithm that retrieves atmospheric profile EDR products, including ozone and carbon trace gases, with optimal vertical resolution under nonprecipitating (clear to partly cloudy) conditions. The NUCAPS ozone profile product is assessed in this paper using extensive global $in\;situ$ truth data sets, namely, ozonesonde observations launched from ground-based networks and from ocean-based intensive field campaigns, along with numerical weather prediction model output. Based upon rigorous statistical analyses using these data sets, the NUCAPS ozone profile EDRs are determined to meet the JPSS Level 1 global performance requirements.

During the NASA DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) campaign conducted in July 2011 across metropolitan Washington, DC, 25 daytime ozonesondes were launched from the Howard University Beltsville Campus (HUBC), representing the highest temporal density of measurements ever taken over the region. Time-height depiction of ozone concentration reveals considerable variability near the surface and in the mid/upper troposphere. Meteorological influences are assessed using the synoptic and mesoscale information, which revealed that periodic stratospheric intrusion of ozone-rich air was the main mechanism for elevated levels in the upper troposphere. It is also shown that high concentrations of ozone prevalent in the free troposphere were due to a combination of advection and aged air masses, which accounted for over 40% of the total budget. Poor air quality episodes with high surface concentration were due local emissions of precursors and associated synoptic-scale conditions. Breaks in the elevated ozone concentrations in the boundary layer and free troposphere occurred from frontal passages and accompanying storms. In the most unusual case (26 July, 2011), the combined effect of storms followed by two frontal passages and high pressure positioned west of the region led to decrease column ozone as much as 70%. The unusually deep extent of the reduction appears to be related to the temporary cutoff of air advected from fire locations and polluted regions, which dominated the upper troposphere throughout the period.

The U.S. Mid-Atlantic region experiences a wide variability of aerosol loading and frequent episodes of elevated anthropogenic aerosol loading associated with urban pollution conditions during summer months. In this study, multi-year ground-based observations (2006 to 2010) of aerosol and cloud properties from passive, active and in situ measurements at an atmospheric measurement field station in the Baltimore–Washington corridor operated by Howard University were analyzed to examine aerosol indirect effect on single-layer warm clouds including cloud optical depth (COD), liquid water path (LWP), cloud droplet effective radius (Re) and cloud droplet number concentration (Nd) in this region. A greater occurrence of polluted episodes and cloud cases with smaller Re (

This paper examines the performance of satellite sounder atmospheric vertical moisture profiles under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs), tropical Hadley cells, and Pacific Ocean atmospheric rivers (ARs). Operational satellite sounder moisture profile retrievals from the Suomi National Polar-Orbiting Partnership (SNPP) NOAA Unique Combined Atmospheric Processing System (NUCAPS) are empirically assessed using collocated dedicated radiosonde observations (raobs) obtained from ocean-based intensive field campaigns. The raobs from these campaigns provide uniquely independent correlative truth data not assimilated into numerical weather prediction (NWP) models for satellite sounder validation over oceans. Although ocean cases are often considered “easy” by the satellite remote sensing community, these hydrometeorological phenomena present challenges to passive sounders, including vertical gradient discontinuities (e.g., strong inversions), as well as persistent uniform clouds, aerosols, and precipitation. It is found that the operational satellite sounder 100-layer moisture profile NUCAPS product performs close to global uncertainty requirements in the SAL/Hadley cell environment, with biases relative to raob within 10% up to 350 hPa. In the more difficult AR environment, bias relative to raob is found to be within 20% up to 400 hPa. In both environments, the sounder moisture retrievals are comparable to NWP model outputs, and cross-sectional analyses show the capability of the satellite sounder for detecting and resolving these tropospheric moisture features, thereby demonstrating a near-real-time forecast utility over these otherwise raob-sparse regions.

The remote sensing of PM2.5 (particulate matter concentration with aerodynamic diameter d ≤ 2.5 μm) mass concentration is mostly based on the measurements of AOD (aerosol optical depth) that is a common product of satellite and ground instruments which measure spectral radiance. The relationship between surface PM2.5 and column integrated AOD is found associated with vertical and size distribution of aerosols. In this study, a non-linear regression model combining AOD and near surface backscatter for estimation of PM2.5 is developed and tested based on 6 years ground measurements from HUBC (Howard University Beltsville Campus) facility. Overall, the non-linear model explains ~ 60% of the variability in hourly PM2.5. The RMSE (root-mean-square error) is ~ 5.83 μg/m 3 with a corresponding average PM2.5 of 15.43 μg/m 3 . That is a big improvement to the linear model using AOD alone (~ 40% of the variability, RMSE is ~ 7.14 μg/m 3 ). The ceilometer measured near surface backscatter is found to improve the estimation of PM2.5-AOD relationship the most compared to other factors, such as aerosol size indicator, surface temperature, relative humidity, wind speed and pressure especially when AOD is large (AOD ≥ 0.3). As aerosol size indicator, two Angstrom exponents are calculated by AOD at three wavelengths of 415, 500, 860 nm and are found also important to the PM2.5-AOD relationship. In addition to the HUBC site, the model is tested based on the 4 years (2012 to 2015) measurements from ARM SGP site and the nearest EPA site. The results also show the significant role of the ceilometer measured near surface backscatter on improving estimation of PM2.5. This study illustrated the potential of ceilometer on investigation of air pollution. With broad ceilometer network, ground-level particle concentrations can be better determined.

Changes to urban areas over time and their relationship to precipitation and climate is a topic of growing interest. Cities have existed and expanded for centuries, but datasets which show levels and changes in urbanization prior to recent years are often spatially or temporally limited. It is known urban areas are generally warmer than rural areas, therefore relative values of temperatures can be used to discern land type. In this study, a new method utilizing the statistical k-means clustering technique is proposed to identify urbanization by using temperature data recorded at meteorological weather stations. The new technique was developed and applied to a network of meteorological stations in the greater Washington, DC region for 5-year intervals from 1980 to 2010, where it was able to identify urban, suburban, and rural land types for both large and small cities. The technique was also able to capture general temporal transitions from rural to suburban environments at the edges of urban areas.

A new automatic mixing layer height detection method for lidar observations of aerosol backscatter profiles is presented and evaluated for robustness. The new detection method incorporates the strengths of Steyn et al.’s error function–ideal profile (ERF) method and Davis et al.’s wavelet covariance transform (WCT) method. These two methods are critical components of the new method, and their robustness is also evaluated and then contrasted to the new method. The new method is applied to aerosol backscatter observations in two ways: 1) by looking for the most realistic mixing height throughout the entire profile and 2) by searching for mixing height below significant elevated obscurations (e.g., clouds or aerosol layers). The first approach is referred to as the hybrid method and the second as the hybrid-lowest method. Coincident radiosounding observations of mixing heights are used to independently reference the lidar-based estimates.There were 4030 cases examined over a 5-yr period for mixing heights. The efficacy of the lidar-based methods was determined based on diurnal, seasonal, stability, and sky obscuration conditions. Of these conditions, the hybrid method performed best for unstable and cloudy situations. It determined mixing heights reliably (less than ±0.30-km bias) for close to 70% of those cases. The hybrid-lowest method performed best in stable and clear-sky conditions; it determined mixing heights reliably for over 70% of those cases. The WCT method performed the best overall.

Monitoring PM2.5 (particulate matter with aerodynamic diameter d ≤ 2.5 µm) mass concentration has become of more importance recently because of the negative impacts of fine particles on human health. However, monitoring PM2.5 during cloudy and nighttime periods is difficult since nearly all the passive instruments used for aerosol remote sensing are not able to measure aerosol optical depth (AOD) under either cloudy or nighttime conditions. In this study, an empirical model based on the regression between PM2.5 and the near-surface backscatter measured by ceilometers was developed and tested using 6 years of data (2006 to 2011) from the Howard University Beltsville Campus (HUBC) site. The empirical model can explain ∼ 56, ∼ 34 and ∼ 42 % of the variability in the hourly average PM2.5 during daytime clear, daytime cloudy and nighttime periods, respectively. Meteorological conditions and seasons were found to influence the relationship between PM2.5 mass concentration and the surface backscatter. Overall the model can explain ∼ 48 % of the variability in the hourly average PM2.5 at the HUBC site when considering the seasonal variation. The model also was tested using 4 years of data (2012 to 2015) from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, which was geographically and climatologically different from the HUBC site. The results show that the empirical model can explain ∼ 66 and ∼ 82 % of the variability in the daily average PM2.5 at the ARM SGP site and HUBC site, respectively. The findings of this study illustrate the strong need for ceilometer data in air quality monitoring under cloudy and nighttime conditions. Since ceilometers are used broadly over the world, they may provide an important supplemental source of information of aerosols to determine surface PM2.5 concentrations.

During summer 2011, particle growth events were investigated in Beltsville, Maryland, USA where anthropogenic and biogenic hydrocarbon emissions heavily influenced the lower atmosphere. Aerosol sampling was made from a 5-m tower during July 2011. Ultrafine particle growth events occurred on 4 of the 25 days sampled. Regional particle growth events occurred after the passage of synoptic cold fronts. During regional particle growth events temperature and relative humidity were 2° Celsius lower and 3 % less than on non-event days and the local wind direction came from the northeast. With average growth rates of 3.5 nm hr−1, regional particle growth events happened around 15:00 Universal Time Coordinated, shortly after increased mixing within the atmospheric boundary layer. Regional particle growth events were associated with cooler, drier, mostly sunny days that had low sulfur dioxide mixing ratio (~0.6 parts per billion by volume). Regional particle growth events occurred when the atmospheric boundary layer was dominated by free convection and had lower sensible heat fluxes compared to short-lived events or non-particle growth event days.

We validate the Ozone Monitoring Instrument (OMI) Ozone Profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the dataset into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004–2008) and post-RA (2009–2014). The retrieval shows good agreement with ozonesondes in the tropics and midlatitudes and for pressure ∼ 50 hPa after applying OMI averaging kernels to ozonesonde data. The MBs of the stratospheric ozone column (SOC, the ozone column from the tropopause pressure to the ozonesonde burst pressure) are within 2 % with SDs of ∼ 50 hPa. The SOC MBs increase up to 3 % with SDs as great as 6 % and the TOC SDs increase up to 30 %. The comparison generally degrades at larger solar zenith angles (SZA) due to weaker signals and additional sources of error, leading to worse performance at high latitudes and during the midlatitude winter. Agreement also degrades with increasing cloudiness for pressure > ∼ 100 hPa and varies with cross-track position, especially with large MBs and SDs at extreme off-nadir positions. In the tropics and midlatitudes, the post-RA comparison is considerably worse with larger SDs reaching 2 % in the stratosphere and 8 % in the troposphere and up to 6 % in TOC. There are systematic differences that vary with latitude compared to the pre-RA comparison. The retrieval comparison demonstrates good long-term stability during the pre-RA period but exhibits a statistically significant trend of 0.14–0.7 % year−1 for pressure

Various studies indicate that high-resolution oxygen A-band spectrum has the capability to retrieve the vertical profiles of aerosol and cloud properties. To improve the understanding of oxygen A-band inversions and utility, we developed a high-resolution oxygen A-band spectrometer (HABS), and deployed it at Howard University Beltsville site during the NASA Discover Air-Quality Field Campaign in July, 2011. By using a single telescope, the HABS instrument measures the direct solar and the zenith diffuse radiation subsequently. HABS exhibits excellent performance: stable spectral response ratio, high signal-to-noise ratio (SNR), high-spectrum resolution (0.016 nm), and high out-of-band rejection (10−5). For the spectral retrievals of HABS measurements, a simulator is developed by combining a discrete ordinates radiative transfer code (DISORT) with the High Resolution Transmission (HITRAN) database HITRAN2008. The simulator uses a double-k approach to reduce the computational cost. The HABS-measured spectra are consistent with the related simulated spectra. For direct-beam spectra, the discrepancies between measurements and simulations, indicated by confidence intervals (95%) of relative difference, are (−0.06, 0.05) and (−0.08, 0.09) for solar zenith angles of 27 and 72°, respectively. For zenith diffuse spectra, the related discrepancies between measurements and simulations are (−0.06, 0.05) and (−0.08, 0.07) for solar zenith angles of 27 and 72°, respectively. The main discrepancies between measurements and simulations occur at or near the strong oxygen absorption line centers. They are mainly due to two kinds of causes: (1) measurement errors associated with the noise/spikes of HABS-measured spectra, as a result of combined effects of weak signal, low SNR, and errors in wavelength registration; (2) modeling errors in the simulation, including the error of model parameters setting (e.g., oxygen absorption line parameters, vertical profiles of temperature and pressure) and the lack of treatment of the rotational Raman scattering. The high-resolution oxygen A-band measurements from HABS can constrain the active radar retrievals for more accurate cloud optical properties (e.g., cloud optical depth, effective radius), particularly for multi-layer clouds and for mixed-phase clouds.

Multi-platform and multi-sensor observations are used to study the impacts of mineral dust on ice clouds of tropical deep convection systems based on one massive Sahara dust event. The comparisons of cloud properties between dust-laden and dust-free conditions support the hypothesis that the presence of large concentrations of mineral dust produces more ice particles at warmer temperature through heterogeneous nucleation processes. Water vapor competition limits ice particles' growth and results in relatively small sizes of ice particles and a narrow distribution of effective particle diameter in non-precipitating ice clouds, particularly at upper layer with temperatures colder than − 40 to − 50 °C. On the other hand, precipitating ice clouds with sufficient water vapor supply have greater ice water paths under dust-laden conditions than under dust-free conditions. The results also suggest that mineral dusts may invigorate the convection and enhance water vapor supply in deep convective precipitating clouds, lifting ice particles to higher altitudes. Additional study illustrates that the observed microphysical changes of ice clouds in the deep convection systems are not simply due to the differences of large-scale dynamics and thermodynamics.

We outline a methodology using broadband and spectral irradiances to quantify aerosol direct effects on the surface diffuse shortwave (SW) irradiance. Best Estimate Flux data span a 13 year timeframe at the Department of Energy Atmospheric Radiation Measurement Program’s Southern Great Plains (SGP) site. Screened clear-sky irradiances and aerosol optical depth (AOD), for solar zenith angles ≤ 65°, are used to estimate clear-sky diffuse irradiances. We validate against detected clear-sky observations from SGP’s Basic Radiation System (BRS). BRS diffuse irradiances were in accordance with estimates, producing a root-mean-square error and mean bias errors of 4.0 W/m2 and -1.4 W/m2, respectively. Absolute differences show 99% of estimates within ±10 W/m2 (10%) of the mean BRS observations. Clear-sky diffuse estimates are used to derive quantitative estimates of aerosol radiative effects, represented as the aerosol diffuse irradiance (ADI). ADI is the contribution of diffuse SW to global SW, attributable to scattering of atmospheric transmission by natural plus anthropogenic aerosols. Estimated slope for the ADI as a function of AOD indicates an increase of ~22 W/m2 in diffuse SW for every 0.1 increase in AOD. Such significant increases in the diffuse fraction could possibly increase photosynthesis. Annual mean ADI is 28.2 W/m2, and heavymore » aerosol loading at SGP provides up to a maximum increase of 120 W/m2 in diffuse SW over background conditions. With regard to seasonal variation, the mean diffuse forcings are 17.2, 33.3, 39.0, and 23.6 W/m2 for winter, spring, summer, and fall, respectively.« less

Continuous lidar observations of the planetary boundary layer (PBL) depth have been made at the Micropulse Lidar Network (MPLNET) site in Greenbelt, MD since April 2001. However, because of issues with the operational PBL depth algorithm, the data is not reliable for determining seasonal and diurnal trends. Therefore, an improved PBL depth algorithm has been developed which uses a combination of the wavelet technique and image processing. The new algorithm is less susceptible to contamination by clouds and residual layers, and in general, produces lower PBL depths. A 2010 comparison shows the operational algorithm overestimates the daily mean PBL depth when compared to the improved algorithm (1.85 and 1.07 km, respectively). The improved MPLNET PBL depths are validated using radiosonde comparisons which suggests the algorithm performs well to determine the depth of a fully developed PBL. A comparison with the Goddard Earth Observing System-version 5 (GEOS-5) model suggests that the model may underestimate the maximum daytime PBL depth by 410 m during the spring and summer. The best agreement between MPLNET and GEOS-5 occurred during the fall and they diered the most in the winter.

An ocean-based prelaunch evaluation of the Geostationary Operational Environmental Satellite (GOES)-R series Advanced Baseline Imager (ABI) legacy atmospheric profile (LAP) products is conducted using proxy data based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation satellite. SEVIRI-based LAP temperature and moisture profile retrievals are validated against in situ correlative data obtained over the open ocean from multiple years of the National Oceanic and Atmospheric Administration (NOAA) Aerosols and Ocean Science Expeditions (AEROSE). The NOAA AEROSE data include dedicated radiosonde observations (RAOBs) launched from the NOAA ship Ronald H. Brown over the tropical Atlantic: a region optimally situated within the full-disk scanning range of SEVIRI and one of great meteorological importance as the main development area of Atlantic hurricanes. The most recent versions of the GOES-R Algorithm Working Group team algorithms (e.g., cloud mask, aerosol detection products, and LAP) implemented within the algorithms integration team framework (the NOAA operational system that will host these operational product algorithms) are used in the analyses. Forecasts from the National Centers for Environmental Prediction Global Forecasting System (NCEP GFS) are used for the LAP regression and direct comparisons. The GOES-R LAP retrievals are found to agree reasonably with the AEROSE RAOB observations, and overall retrievals improve both temperature and moisture against computer model NCEP GFS outputs. The validation results are then interpreted within the context of a difficult meteorological regime (e.g., Saharan air layers and dust) coupled with the difficulty of using a narrowband imager for the purpose of atmospheric sounding.

After sunset, a stable boundary layer (SBL) develops close to the ground, while the upper region of the daytime mixed layer becomes the residual layer (RL). Mixing between the SBL and RL is often quite limited and the RL is thought to be a reservoir for daytime mixed-layer pollutants under such conditions. However, ozone (O3) profiles observed in Maryland, U.S. suggest that the RL is not always a reservoir of O3 in that region. Nocturnal low-level jets (LLJs) and/or other mechanisms are speculated to enhance vertical mixing between the SBL and RL, which influences the vertical O3redistribution. Nocturnal surface O3 maxima, an RL with reduced O3 levels, and a concurrent strong LLJ were observed in Maryland on the night of August 9–10, 2010. Surface O3 measurements in the region and three-dimensional air quality simulations suggest that horizontal advection cannot explain the nocturnal O3 maxima and concurrent decrease of O3 levels within the RL. A sensitivity study with a single column (1D) chemistry model was performed to investigate the role of LLJs in generating turbulent mixing within the nighttime boundary layer and to identify related impacts on O3 concentrations at night and on the following day. The strong shear associated with the LLJ enhanced turbulent mixing and weakened the decoupling of the RL and SBL substantially. Ozone was actively mixed down from the RL to the surface, causing secondary nocturnal surface O3 maxima. Near the surface, O3 was efficiently removed by chemical reactions and dry deposition, which resulted in lower O3 peak values on the next day.

[1] This paper continues an investigation into the zenith angular effect of cloud-contamination within “clear-sky” infrared (IR) radiance observations commonly used in the retrieval of environmental data records (EDRs), which include “cloud-cleared radiances” (as is typical from hyper/ultra spectral IR sounders), as well as “cloud-masked” data (as is typical from imagers). The simple probability of clear line of sight (PCLoS) models and sensitivity studies of Part 1 (Nalli et al., 2012a) are corroborated with experimental analyses of environmental satellite data products as functions of sensor zenith angle, including sounder cloud-cleared radiances (CCRs) and retrieved effective cloud fraction, as well as narrowband imager cloud masking. Analyses of hyperspectral microwindow calc − obs are performed using MetOp-A Infrared Atmospheric Sounding Interferometer (IASI) CCR observations matched to dedicated radiosonde observations (RAOBs) during intensive validation field campaigns. The IASI calc − obs are found to exhibit a systematic positive bias with a strong concave-up variation with satellite zenith angle (i.e., an increasing positive bias symmetric over the scanning range) on the order of 1–3 K in magnitude, a signal associated with both residual clouds and dust aerosols. This is corroborated by analysis of the IASI retrieved effective cloud fraction product compared to the expected angular variations predicted by the PCLoS models, which show that the observed concave-up calc − obs variation may be the result of contamination by mid-to-upper tropospheric clouds. Finally, a corollary global analysis of the MetOp-A Advanced Very High Resolution Radiometer (AVHRR) cloud-mask shows concave-up variation that may be underestimating the angular variation for global ensembles containing clouds with vertical development (i.e., aspect ratios >0.5). The results presented in this work thus support the sensitivity studies of Part 1, indicating that contamination by residual clouds and/or aerosols within clear-sky observations can have a measurable concave-up impact on the angular agreement of observations with calculations.

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 in-situ 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 MODIS-retrieved 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.

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 approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

This paper discusses experiences and lessons learned from developing an interdisciplinary graduate program (IDP) during the last 10 y: The Howard University Graduate Program in Atmospheric Sciences...

Although much research has focused on daytime ozone (O 3 ) distribution in the atmospheric boundary layer, there remain many unresolved processes related to O 3 transport in the residual layer. To address such unresolved questions, a field study was conducted in Beltsville, MD during the summer of 2010 to study the spatial and temporal distribution of O 3 and other pollutants using ground-based gas analyzers and ozonesondes. During elevated pollution events in the daytime, the convective boundary layer, which reached a maximum depth of about 2 km, had nearly uniform O 3 levels of almost 100 parts per billion (ppbv). Due to intermittent and intense vertical turbulent motion, the residual layer became “leaky” and permitted vertical transport to enhance ground-level O 3 mixing ratios by as much as 10–30 ppbv in a span of 0.5–3 h. Model simulations, using the Weather Research and Forecasting model with Chemistry (WRF/Chem), were carried out to investigate the impact of different treatments of vertical mixing on the simulation of O 3 in the nocturnal boundary layer and residual layer. WRF/Chem model simulations provided realistic O 3 vertical distribution during the daytime. During the nighttime, in the residual layer, model outputs resulted in higher O 3 levels compared with the in-situ observations. Model sensitivity analyses showed that increasing the turbulent length scales and improved stability functions yielded improvements in the vertical transport of O 3 within the residual layer. One key conclusion of this study is that models such as WRF/Chem require improved numerical algorithms to properly account for the nocturnal vertical transport of O 3 in the residual region of the atmospheric boundary layer.

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 from Africa, the Saharan air layer (SAL), and the distribution of tropical water vapor and tropical Atlantic ozone. The multiyear PNE/AEROSE sounding data are valuable as correlative data for prelaunch phase validation of the planned Joint Polar Satellite System (JPSS) and NOAA Geosynchronous Operational Environmental Satellite R series (GOES-R) systems, as well as numerous other science applications. A brief summary of these data, along with an overview of some important science highlights, including meteorological phenomena of general interest, is presented.

The number and quality of atmospheric observations used by meteorologists and operational forecasters are increasing year after year, and yet, consistent improvements in forecast skill remains a challenge. While contributing factors involving these challenges have been identified, including the difficulty in accurately establishing initial conditions, improving the observations at regional and local scales is necessary for accurate depiction of the atmospheric boundary layer (below 2km), particularly the wind profile, in high resolution numerical models. Above the uncertainty of weather forecasts, the goal is also to improve the detection of severe and extreme weather events (severe thunderstorms, tornadoes and other mesoscale phenomena) that can adversely affect life, property and commerce, primarily in densely populated urban centers. This paper will describe the New York State Mesonet that is being deployed in the state of New York, USA. It is composed of 126 stations including 17 profiler sites. These sites will acquire continuous upper air observations through the combination of WINDCUBE Lidars and microwave radiometers. These stations will provide temperature, relative humidity & “3D” wind profile measurements through and above the planetary boundary layer (PBL) and will retrieve derived atmospheric quantities such as the PBL height, cloud base, momentum fluxes, and aerosol & cloud optical properties. The different modes and configurations that will be used for the Lidars are discussed. The performances in terms of data availability and wind accuracy and precision are evaluated. Several profiles with specific wind and aerosol features are presented to illustrate the benefits of the use of Coherent Doppler Lidars to monitor accurately the PBL.

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 weak correlations as a function of altitude, temperature, or relative humidity. Three main regions of weak correlation emerge: (i) regions of low relative humidity and low temperature, (ii) regions of moderate relative humidity at low temperatures, and (iii) regions of low relative humidity at moderate temperatures. Comparison of Atmospheric Infrared Sounder and Tropospheric Emission Sounder satellite retrievals of moisture with those of Howard University Raman lidar showed a general agreement in the trend, but the satellites miss details in atmospheric structure because of their low resolution. A relative difference of about ±20% is usually found between lidar and satellite measurements for the coincidences available.

Ozone profiles are often used to investigate day-to-day and year-to-year variability in origins of free tropospheric ozone. With this in mind, more than 50 ozonesonde launches were conducted in Beltsville, MD, during the summers of 2004 through 2007. Budgets of free tropospheric ozone were calculated for each ozone profile in the four summers using a laminar identification (LID) method and unusual episodes were analyzed with respect to meteorological variables. The laminar method showed that stratosphere-to-troposphere transport (ST) accounted for greater than 50% of the free tropospheric ozone column on 17% of days sampled, a more pronounced influence than regional convective and lightning (RCL) sources. The ST origins were confirmed with trajectories, and tracers (water vapor and potential vorticity). The amount of free tropospheric ozone from ST and RCL sources varied from year-to-year (up to 13%) and can be explained by differences in mean meteorological patterns. On average, almost 30% of the free tropospheric column was attributed to ST influence, about twice as much as RCL, although the LID method may not capture weeks-old lightning influences as in a chemical model. The prevalence of ST ozone in summertime Beltsville soundings was similar to six sounding sites in the IONS-04 campaign [Thompson, A.M., et al., 2007b. Intercontinental Transport Experiment Ozonesonde Network Study (IONS, 2004): 1. Summertime upper tropospheric/lower stratosphere ozone over northeastern North America. J. Geophys. Res. 112, D12S12; Thompson, A.M., et al., 2007c. Intercontinental Transport Experiment Ozonesonde Network Study (IONS, 2004): 2. Tropospheric ozone budgets and variability over northeastern North America. J. Geophys. Res. 112, D12S13.] and to statistics from a 30 year climatology of European soundings [Collette, A., Ancellet, G., 2005. Impact of vertical transport processes on the tropospheric ozone layering above Europe. Part II: Climatological analysis of the past 30 years. Atmos. Environ. 39, 5423–5435]. The Beltsville record also demonstrated the value of soundings for air quality forecasting in an urban area. The 22 nighttime soundings collected over Beltsville in 2004–2007 can be divided into distinct polluted and unpolluted subsets, the former 20 ppbv higher in residual layer ozone (1 km) than the latter. These distinctions propagated to daytime differences of 10 ppbv at the surface in the Washington, DC, area, with the high-ozone residual layers leading to non-attainment of the National Ambient Air Quality Standard for ozone. More frequent ozone observations aloft appear essential for better understanding ozone variability and for enabling air quality modelers to achieve more accurate ozone forecasts.

This study reports the findings of TRMM (Tropical Rainfall Measuring Mission) satellite data analyses undertaken to investigate differences in intensity and depth of precipitating systems in the transition region from continental to maritime environments in West Africa during the rainy season of June to September in 1998–2004. The results of this study are interpreted in the context of regional thermodynamic variables such as equivalent potential temperature and equivalent convective available potential energy to discern the processes governing storm development. Over continental West Africa, convective-type precipitating storms exhibit a substantially larger vertical extent compared to the ones over the eastern Atlantic Ocean. In contrast, the stratiform precipitating systems show similar vertical reflectivity patterns, depth and intensity over both land and adjacent ocean in West Africa. The differences in the attributes of storms, as they move from the continent to the ocean, can be partly explained in terms of the surface-atmosphere interactions that provide the necessary transports of energy and water vapor from the surface to the cloud layer.

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

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 became 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.

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 incorporated into any RCM suitable for U.S. climate and hydrology modeling studies, while the data processing and validation procedures can be more generally applied to construct SBCs for any specific domain over the globe.

A three-day workshop took place at Howard University in Washington D.C. 27 July through 29 July 2000 to examine scientific and social issues associated with climate research in West Africa. Atmospheric scientists from West Africa and United States presented research and sought solutions to various problems that exist with respect to the state of science in West Africa. Presentations covered global climate model (GCM) and regional climate model simulations for West Africa, easterly wave representation in GCMs and the NCEP reanalysis, land-surface processes and atmospheric chemistry. A number of obstacles currently inhibit West African-U.S. collaboration including a lack of resources, communications, technology, and language. In order to overcome these obstacles, sustained efforts by numerous individuals in United States and West Africa are necessary. An institute in West Africa should be identified that can serve as a center for education, research, and a base for international field studies in th...

Long-term ground-based observations (2006 to 2010) of aerosol and cloud properties derived from passive radiometric sensors deployed at an atmospheric measurement field station in the Baltimore–Washington corridor operated by Howard University were used to examine aerosol indirect effect on cloud optical depth (COD), liquid water path (LWP), cloud droplets effective radius (Re) and cloud droplets number concentration (Nd). A higher frequency of clouds with large COD (> 20) and small Re (< 7 m) was found during summer of 2006 and 2007 along with higher frequency of abundant aerosol loading. The five-year data are screened for summer months only and are separated into clean and polluted cases based on aerosol particulate matter with aerodynamic diameter ≤ 2.5 m (PM2.5) value. Evidence of aerosol indirect effect is found where for polluted cases the mean and median values of COD and Nd distributions were elevated while the mean and median values of Re were decreased. Further reinforcing this conclusion is the result that the mean and median values of LWP distributions did not show prominent difference between clean and polluted cases, this implies that differences between the two cases of influential factors on cloud properties were relatively controlled. Moreover aerosol indirect effects were found insignificant when LWP was small but significant when LWP was large through the analysis of sensitivity of Nd to LWP under different aerosol loading and the measurements of aerosol size distribution.