David P. Duda

Contrail coverage derived from 2001 AVHRR data over the continental United States of America and surrounding areas

Linear contrail coverage, optical depth, and longwave radiative forcing are derived from NOAA-15 and NOAA-16 Advanced Very High Resolution Radiometer data taken during daytime over the continental United States of America (USA), southern Canada, northern Mexico, and the adjacent oceans. Analyses were performed for all available overpasses during 2001, but for NOAA-15 were primarily limited to the eastern half and the northwestern corner of the domain. Contrail coverage averaged 1.17 % and 0.65 % from the early morning NOAA-15 and midafternoon NOAA-16, respectively, for the areas and month common to both satellites. The NOAA-16 contrail coverage and radiative properties for the limited NOAA-15 domain are, on average, nearly identical to those for the entire domain. The estimated combined maximum coverage for the entire domain was ∼1.05 % during February, while the minimum of 0.57 % occurred during August. Mean optical depths varied by ∼ 20 % with winter minima and summer maxima. The annual mean optical depth of 0.27 translated to a normalized contrail longwave radiative forcing of 15.5 Wm -2 . The overall daytime longwave radiative forcing for the domain is 0.11 Wm -2 . The normalized radiative forcing peaked during summer while the overall forcing was at a maximum during winter because of the greater contrail coverage. A detailed error analysis showed that the linear contrail coverage was overestimated by ∼40 % for both satellites the true coverage is closer to 0.70 and 0.40 % for NOAA-15 and 16, respectively. Errors in the mean NOAA-15 optical depths and radiative forcing were negligible while their NOAA-16 counterparts were overestimated by approximately 13 %. Contrail coverage was dramatically lower than expected from previous studies, but is most likely due to the significant decrease in upper tropospheric humidity observed in numerical weather analysis data. Contrail optical depths are much greater than both theoretical estimates for this part of North America and empirical retrievals over Europe. The cause of the morning-afternoon difference in contrail coverage is not yet known. Further modelling studies and additional satellite analyses are needed to understand this diurnal cycle and to explain the differences between the present and previous results.

A case study of the development of contrail clusters over the Great Lakes

Abstract Widespread persistent contrails over the western Great Lakes during 9 October 2000 were examined using commercial flight data, coincident meteorological data, and satellite remote sensing data from several platforms. The data were analyzed to determine the atmospheric conditions under which the contrails formed and to measure several physical properties of the contrails, including areal coverage, spreading rates, fall speeds, and optical properties. Most of the contrails were located between 10.6 and 11.8 km in atmospheric conditions consistent with a modified form of the Appleman contrail formation theory. However, the Rapid Update Cycle-2 analyses have a dry bias in the upper-tropospheric relative humidity with respect to ice (RHI), as indicated by persistent contrail generation during the outbreak where RHI ≥ 85%. The model analyses show that synoptic-scale vertical velocities affect the formation of persistent contrails. Areal coverage by linear contrails peaked at 30 000 km2, but the maximum...

Estimates of cloud radiative forcing in contrail clusters using GOES imagery

Using data from the Geostationary Operational Environmental Satellite (GOES), the evolution of solar and longwave radiative forcing in contrail clusters is presented in several case studies. The first study examines contrails developing over the midwestern United States in a region of upper tropospheric moisture enhanced by the remnants of Hurricane Nora on September 26, 1997. Two other cases involve contrail clusters that formed over the Chesapeake Bay and the Atlantic Ocean on February 11 and March 5, 1999, respectively. The last study includes contrails forming over the tropical Pacific near Hawaii. Observations of tropical contrails near Hawaii show that the contrail optical properties are similar to those measured from satellite in the midlatitudes, with visible optical depths between 0.3 and 0.5 and particle sizes between 30 and 60 μm as the contrails mature into diffuse cloudiness. Radiative transfer model simulations of the tropical contrail case suggest that ice crystal shape may have an important effect on radiative forcing in contrails. The magnitudes of the observed solar and longwave radiative forcings were 5.6 and 3.2 W m−2 less than those from the corresponding model simulations, and these differences are attributed to the subpixel scale low clouds and uncertainties in the anisotropic reflectance and limb-darkening models used to estimate the observed forcing. Since the broadband radiative forcing in contrails often changes rapidly, contrail forcing estimates based only on the polar orbiting advanced very high resolution radiometer (AVHRR) data could be inaccurate due to the lack of sufficient temporal sampling.

Impact of aviation on climate: FAA’s Aviation Climate Change Research Initiative (ACCRI) Phase II

AbstractUnder the Federal Aviation Administration’s (FAA) Aviation Climate Change Research Initiative (ACCRI), non-CO2 climatic impacts of commercial aviation are assessed for current (2006) and for future (2050) baseline and mitigation scenarios. The effects of the non-CO2 aircraft emissions are examined using a number of advanced climate and atmospheric chemistry transport models. Radiative forcing (RF) estimates for individual forcing effects are provided as a range for comparison against those published in the literature. Preliminary results for selected RF components for 2050 scenarios indicate that a 2% increase in fuel efficiency and a decrease in NOx emissions due to advanced aircraft technologies and operational procedures, as well as the introduction of renewable alternative fuels, will significantly decrease future aviation climate impacts. In particular, the use of renewable fuels will further decrease RF associated with sulfate aerosol and black carbon. While this focused ACCRI program effort...

Estimated contrail frequency and coverage over the contiguous United States from numerical weather prediction analyses and flight track data

Estimates of contrail frequency and coverage over the contiguous United States (CONUS) are developed using hourly meteorological analyses from the Rapid Update Cycle (RUC) numerical weather prediction model and commercial air traffic data for 2 months during 2001. The potential contrail frequency over the CONUS is computed directly from RUC analyses using several modified forms of the classical Appleman criteria for persistent contrail formation. Various schemes for diagnosing contrails from the RUC analyses were tested by first tuning each model to mean satellite estimates of contrail coverage for the domain and then comparing the resulting distributions to those from the satellite retrievals. The most accurate method for forming persistent contrails for both months uses a fourth root relationship between flight lengths and contrail coverage, accounts for contrail overlap and for the dry bias in the humidity profiles, and assumes that contrails can be detected in all cloudiness conditions. The differences between the simulated and satellite-derived contrail amounts are due to errors in the satellite observations, possible diurnally dependent saturation effects, and uncertainties in the numerical weather analysis humidity fields and other input variables. The algorithms developed here are suitable for eventual application to real-time predictions of potential contrail outbreaks. When refined, the methodology could be useful for both contrail mitigation and for contrail-climate effects assessment.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence Using High-Resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Abstract Straightforward application of the Schmidt–Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper-tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy: the percent correct (PC) and the Hanssen–Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitab...

Basic Diagnosis and Prediction of Persistent Contrail Occurrence Using High-Resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Abstract A probabilistic forecast to accurately predict contrail formation over the conterminous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and the Rapid Update Cycle (RUC) combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The most common predictors selected for the SURFACE models tend to be related to temperature, relative humidity, and wind direction when the models are generated using RUC or ARPS analyses. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The most common predictors for the OUTBREAK models tend to be wind direction, atmospheric lapse rate, temperature, relative humidity, ...

Observations of Aircraft Dissipation Trails from GOES

Abstract Two cases of aircraft dissipation trails (distrails) with associated fall streak clouds were analyzed with multispectral geostationary satellite data. One dissipation trail was observed in a single cloud layer on 23 July 2000 over southeastern Virginia and the Chesapeake Bay. Another set of trails developed at the top of multilayer cloudiness off the coasts of Georgia and South Carolina on 6 January 2000. The distrails on both days formed in optically thin, midlevel stratified clouds with cloud-top heights between 7.6 and 9.1 km. The distrail features remained intact and easily visible from satellite images over a period of 1–2 h despite winds near 50 kt at cloud level. The width of the distrails became as large as 20 km within a period of 90 min or less. Differences between the optical properties of the fall streak particles inside the distrails and those of the clouds surrounding the trails allowed for the easy identification of the fall streak clouds in either the 3.9-μm brightness temperature...

Estimating Contrail Climate Effects from Satellite Data

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Development of multi-sensor global cloud and radiance composites for earth radiation budget monitoring from DSCOVR

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). Radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers have to be co-located with EPIC pixels to provide scene identification in order to select anisotropic directional models needed to calculate shortwave and longwave fluxes. A new algorithm is proposed for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. An aggregated rating is employed to incorporate several factors and to select the best observation at the time nearest to the EPIC measurement. Spatial accuracy is improved using inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into EPIC-view domain by convolving composite pixels with the EPIC point spread function defined with a half-pixel accuracy. PSF-weighted average radiances and cloud properties are computed separately for each cloud phase. The algorithm has demonstrated contiguous global coverage for any requested time of day with a temporal lag of under 2 hours in over 95% of the globe.