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Jared W. Marquis
,
Alec S. Bogdanoff
,
James R. Campbell
,
James A. Cummings
,
Douglas L. Westphal
,
Nathaniel J. Smith
, and
Jianglong Zhang

Abstract

Passive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level for cloud optical depths between 0.0 and 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud-top height and COD (assuming they are consistent across each platform) integrated within each corresponding modeled cold bias matrix. NLSST relative OTC cold biases, for any single observation, range from 0.33° to 0.55°C for the three sensors, with an absolute (bulk mean) bias between 0.09° and 0.14°C. Triple-window retrievals are more resilient, ranging from 0.08° to 0.14°C relative and from 0.02° to 0.04°C absolute. Cold biases are constant across the Pacific and Indian Oceans. Absolute bias is lower over the Atlantic but relative bias is higher, indicating that this issue persists globally.

Full access
James R. Campbell
,
Erica K. Dolinar
,
Simone Lolli
,
Gilberto J. Fochesatto
,
Yu Gu
,
Jasper R. Lewis
,
Jared W. Marquis
,
Theodore M. McHardy
,
David R. Ryglicki
, and
Ellsworth J. Welton

Abstract

Cirrus cloud daytime top-of-the-atmosphere radiative forcing (TOA CRF) is estimated for a 2-yr NASA Micro-Pulse Lidar Network (532 nm; MPLNET) dataset collected at Fairbanks, Alaska. Two-year-averaged daytime TOA CRF is estimated to be between −1.08 and 0.78 W·m−2 (from −0.49 to 1.10 W·m−2 in 2017, and from −1.67 to 0.47 W·m−2 in 2018). This subarctic study completes a now trilogy of MPLNET ground-based cloud forcing investigations, following midlatitude and tropical studies by Campbell et al. at Greenbelt, Maryland, and Lolli et al. at Singapore. Campbell et al. hypothesize a global meridional daytime TOA CRF gradient that begins as positive at the equator (2.20–2.59 W·m−2 over land and from −0.46 to 0.42 W·m−2 over ocean at Singapore), becomes neutral in the midlatitudes (0.03–0.27 W·m−2 over land in Maryland), and turns negative moving poleward. This study does not completely confirm Campbell et al., as values are not found as exclusively negative. Evidence in historical reanalysis data suggests that daytime cirrus forcing in and around the subarctic likely once was exclusively negative. Increasing tropopause heights, inducing higher and colder cirrus, have likely increased regional forcing over the last 40 years. We hypothesize that subarctic interannual cloud variability is likely a considerable influence on global cirrus cloud forcing sensitivity, given the irregularity of polar versus midlatitude synoptic weather intrusions. This study and hypothesis lay the basis for an extrapolation of these MPLNET experiments to satellite-based lidar cirrus cloud datasets.

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Jared W. Marquis
,
Erica K. Dolinar
,
Anne Garnier
,
James R. Campbell
,
Benjamin C. Ruston
,
Ping Yang
, and
Jianglong Zhang

Abstract

The assimilation of hyperspectral infrared sounders (HIS) observations aboard Earth-observing satellites has become vital to numerical weather prediction, yet this assimilation is predicated on the assumption of clear-sky observations. Using collocated assimilated observations from the Atmospheric Infrared Sounder (AIRS) and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), it is found that nearly 7.7% of HIS observations assimilated by the Naval Research Laboratory Variational Data Assimilation System–Accelerated Representer (NAVDAS-AR) are contaminated by cirrus clouds. These contaminating clouds primarily exhibit visible cloud optical depths at 532 nm (COD532nm) below 0.10 and cloud-top temperatures between 240 and 185 K as expected for cirrus clouds. These contamination statistics are consistent with simulations from the Radiative Transfer for TOVS (RTTOV) model showing a cirrus cloud with a COD532nm of 0.10 imparts brightness temperature differences below typical innovation thresholds used by NAVDAS-AR. Using a one-dimensional variational (1DVar) assimilation system coupled with RTTOV for forward and gradient radiative transfer, the analysis temperature and moisture impact of assimilating cirrus-contaminated HIS observations is estimated. Large differences of 2.5 K in temperature and 11 K in dewpoint are possible for a cloud with COD532nm of 0.10 and cloud-top temperature of 210 K. When normalized by the contamination statistics, global differences of nearly 0.11 K in temperature and 0.34 K in dewpoint are possible, with temperature and dewpoint tropospheric root-mean-squared errors (RMSDs) as large as 0.06 and 0.11 K, respectively. While in isolation these global estimates are not particularly concerning, differences are likely much larger in regions with high cirrus frequency.

Open access
David A. Peterson
,
Michael D. Fromm
,
Jeremy E. Solbrig
,
Edward J. Hyer
,
Melinda L. Surratt
, and
James R. Campbell

Abstract

Intense wildfires occasionally generate fire-triggered storms, known as pyrocumulonimbus (pyroCb), that can inject smoke particles and trace gases into the upper troposphere and lower stratosphere (UTLS). This study develops the first pyroCb detection algorithm using three infrared (IR) channels from the imager on board GOES-West (GOES-15). The algorithm first identifies deep convection near active fires via the longwave IR brightness temperature, distinguishing between midtropospheric and UTLS injections. During daytime, unique pyroCb microphysical properties are characterized by a medium-wave brightness temperature that is significantly larger than that in the longwave, allowing for separation of pyroCb from other deep convection. A cloud-opacity test reduces potential false detections. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in successful detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of pyroconvective activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation is that pyroCb anvils can be small relative to GOES-West pixel size, especially in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. A total of 26 pyroCb events are inventoried, including 31 individual pulses, all of which can inject smoke into the UTLS. Six of the inventoried intense pyroCb were not previously documented. Near-real-time application of this algorithm can be extended to other regions and to next-generation geostationary sensors, which offer significant advantages for pyroCb and fire detection.

Full access
Matthew D. Shupe
,
Von P. Walden
,
Edwin Eloranta
,
Taneil Uttal
,
James R. Campbell
,
Sandra M. Starkweather
, and
Masataka Shiobara

Abstract

Cloud observations over the past decade from six Arctic atmospheric observatories are investigated to derive estimates of cloud occurrence fraction, vertical distribution, persistence in time, diurnal cycle, and boundary statistics. Each observatory has some combination of cloud lidar, radar, ceilometer, and/or interferometer for identifying and characterizing clouds. By optimally combining measurements from these instruments, it is found that annual cloud occurrence fractions are 58%–83% at the Arctic observatories. There is a clear annual cycle wherein clouds are least frequent in the winter and most frequent in the late summer and autumn. Only in Eureka, Nunavut, Canada, is the annual cycle shifted such that the annual minimum is in the spring with the maximum in the winter. Intersite monthly variability is typically within 10%–15% of the all-site average. Interannual variability at specific sites is less than 13% for any given month and, typically, is less than 3% for annual total cloud fractions. Low-level clouds are most persistent at the observatories. The median cloud persistence for all observatories is 3–5 h; however, 5% of cloud systems at far western Arctic sites are observed to occur for longer than 100 consecutive hours. Weak diurnal variability in cloudiness is observed at some sites, with a daily minimum in cloud occurrence near solar noon for those seasons for which the sun is above the horizon for at least part of the day.

Full access
David A. Peterson
,
Edward J. Hyer
,
James R. Campbell
,
Michael D. Fromm
,
Johnathan W. Hair
,
Carolyn F. Butler
, and
Marta A. Fenn

Abstract

The 2013 Rim Fire, which burned over 104,000 ha, was one of the most severe fire events in California’s history, in terms of its rapid growth, intensity, overall size, and persistent smoke plume. At least two large pyrocumulonimbus (pyroCb) events were observed, allowing smoke particles to extend through the upper troposphere over a large portion of the Pacific Northwest. However, the most extreme fire spread was observed on days without pyroCb activity or significant regional convection. A diverse archive of ground, airborne, and satellite data collected during the Rim Fire provides a unique opportunity to examine the conditions required for both extreme spread events and pyroCb development. Results highlight the importance of upper-level and nocturnal meteorology, as well as the limitations of traditional fire weather indices. The Rim Fire dataset also allows for a detailed examination of conflicting hypotheses surrounding the primary source of moisture during pyroCb development. All pyroCbs were associated with conditions very similar to those that produce dry thunderstorms. The current suite of automated forecasting applications predict only general trends in fire behavior, and specifically do not predict 1) extreme fire spread events and 2) injection of smoke to high altitudes. While these two exceptions are related, analysis of the Rim Fire shows that they are not predicted by the same set of conditions and variables. The combination of numerical weather prediction data and satellite observations exhibits great potential for improving automated regional-scale forecasts of fire behavior and smoke emissions.

Full access
Dan Welsh
,
Bart Geerts
,
Xiaoqin Jing
,
Philip T. Bergmaier
,
Justin R. Minder
,
W. James Steenburgh
, and
Leah S. Campbell

Abstract

The distribution of radar-estimated precipitation from lake-effect snowbands over and downwind of Lake Ontario shows more snowfall in downwind areas than over the lake itself. Here, two nonexclusive processes contributing to this are examined: the collapse of convection that lofts hydrometeors over the lake and allows them to settle downwind; and stratiform ascent over land, due to the development of a stable boundary layer, frictional convergence, and terrain, leading to widespread precipitation there. The main data sources for this study are vertical profiles of radar reflectivity and hydrometeor vertical velocity in a well-defined, deep long-lake-axis-parallel band, observed on 11 December 2013 during the Ontario Winter Lake-effect Systems (OWLeS) project. The profiles are derived from an airborne W-band Doppler radar, as well as an array of four K-band radars, an X-band profiling radar, a scanning X-band radar, and a scanning S-band radar.

The presence of convection offshore is evident from deep, strong (up to 10 m s−1) updrafts producing bounded weak-echo regions and locally heavily rimed snow particles. The decrease of the standard deviation, skewness, and peak values of Doppler vertical velocity during the downwind shore crossing is consistent with the convection collapse hypothesis. Consistent with the stratiform ascent hypothesis are (i) an increase in mean vertical velocity over land; and (ii) an increasing abundance of large snowflakes at low levels and over land, due to depositional growth and aggregation, evident from flight-level and surface particle size distribution data, and from differences in reflectivity values from S-, X-, K-, and W-band radars at nearly the same time and location.

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James R. Campbell
,
Dennis L. Hlavka
,
Ellsworth J. Welton
,
Connor J. Flynn
,
David D. Turner
,
James D. Spinhirne
,
V. Stanley Scott III
, and
I. H. Hwang

Abstract

Atmospheric radiative forcing, surface radiation budget, and top-of-the-atmosphere radiance interpretation involve knowledge of the vertical height structure of overlying cloud and aerosol layers. During the last decade, the U.S. Department of Energy, through the Atmospheric Radiation Measurement (ARM) program, has constructed four long-term atmospheric observing sites in strategic climate regimes (north-central Oklahoma; Barrow, Alaska; and Nauru and Manus Islands in the tropical western Pacific). Micropulse lidar (MPL) systems provide continuous, autonomous observation of nearly all significant atmospheric clouds and aerosols at each of the central ARM facilities. These systems are compact, and transmitted pulses are eye safe. Eye safety is achieved by expanding relatively low-powered outgoing pulse energy through a shared, coaxial transmit/receive telescope. ARM MPL system specifications and specific unit optical designs are discussed. Data normalization and calibration techniques are presented. These techniques, in tandem, represent an operational value-added processing package used to produce normalized data products for ARM cloud and aerosol research.

Full access
Jared W. Marquis
,
Mayra I. Oyola
,
James R. Campbell
,
Benjamin C. Ruston
,
Carmen Córdoba-Jabonero
,
Emilio Cuevas
,
Jasper R. Lewis
,
Travis D. Toth
, and
Jianglong Zhang

Abstract

Numerical weather prediction systems depend on Hyperspectral Infrared Sounder (HIS) data, yet the impacts of dust-contaminated HIS radiances on weather forecasts has not been quantified. To determine the impact of dust aerosol on HIS radiance assimilation, we use a modified radiance assimilation system employing a one-dimensional variational assimilation system (1DVAR) developed under the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Numerical Weather Prediction–Satellite Application Facility (NWP-SAF) project, which uses the Radiative Transfer for TOVS (RTTOV). Dust aerosol impacts on analyzed temperature and moisture fields are quantified using synthetic HIS observations from rawinsonde, Micropulse Lidar Network (MPLNET), and Aerosol Robotic Network (AERONET). Specifically, a unit dust aerosol optical depth (AOD) contamination at 550 nm can introduce larger than 2.4 and 8.6 K peak biases in analyzed temperature and dewpoint, respectively, over our test domain. We hypothesize that aerosol observations, or even possibly forecasts from aerosol predication models, may be used operationally to mitigate dust induced temperature and moisture analysis biases through forward radiative transfer modeling.

Open access
Simone Lolli
,
James R. Campbell
,
Jasper R. Lewis
,
Yu Gu
,
Jared W. Marquis
,
Boon Ning Chew
,
Soo-Chin Liew
,
Santo V. Salinas
, and
Ellsworth J. Welton

Abstract

Daytime top-of-the-atmosphere (TOA) cirrus cloud radiative forcing (CRF) is estimated for cirrus clouds observed in ground-based lidar observations at Singapore in 2010 and 2011. Estimates are derived both over land and water to simulate conditions over the broader Maritime Continent archipelago of Southeast Asia. Based on bookend constraints of the lidar extinction-to-backscatter ratio (20 and 30 sr), used to solve extinction and initialize corresponding radiative transfer model simulations, relative daytime TOA CRF is estimated at 2.858–3.370 W m−2 in 2010 (both 20 and 30 sr, respectively) and 3.078–3.329 W m−2 in 2011 and over water between −0.094 and 0.541 W m−2 in 2010 and −0.598 and 0.433 W m−2 in 2011 (both 30 and 20 sr, respectively). After normalizing these estimates for an approximately 80% local satellite-estimated cirrus cloud occurrence rate, they reduce in absolute daytime terms to 2.198–2.592 W m−2 in 2010 and 2.368–2.561 W m−2 in 2011 over land and −0.072–0.416 W m−2 in 2010 and −0.460–0.333 W m−2 in 2011 over water. These annual estimates are mostly consistent despite a tendency toward lower relative cloud-top heights in 2011. Uncertainties are described. Estimates support the open hypothesis of a meridional hemispheric gradient in cirrus cloud daytime TOA CRF globally, varying from positive near the equator to presumably negative approaching the non-ice-covered poles. They help expand upon the paradigm, however, by conceptualizing differences zonally between overland and overwater forcing that differ significantly. More global oceans are likely subject to negative daytime TOA CRF than previously implied.

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