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C. O. Collins III
,
B. Blomquist
,
O. Persson
,
B. Lund
,
W. E. Rogers
,
J. Thomson
,
D. Wang
,
M. Smith
,
M. Doble
,
P. Wadhams
,
A. Kohout
,
C. Fairall
, and
H. C. Graber

Abstract

“Sea State and Boundary Layer Physics of the Emerging Arctic Ocean” is an ongoing Departmental Research Initiative sponsored by the Office of Naval Research (http://www.apl.washington.edu/project/project.php?id=arctic_sea_state). The field component took place in the fall of 2015 within the Beaufort and Chukchi Seas and involved the deployment of a number of wave instruments, including a downward-looking Riegl laser rangefinder mounted on the foremast of the R/V Sikuliaq. Although time series measurements on a stationary vessel are thought to be accurate, an underway vessel introduces a Doppler shift to the observed wave spectrum. This Doppler shift is a function of the wavenumber vector and the velocity vector of the vessel. Of all the possible relative angles between wave direction and vessel heading, there are two main scenarios: 1) vessel steaming into waves and 2) vessel steaming with waves. Previous studies have considered only a subset of cases, and all were in scenario 1. This was likely to avoid ambiguities, which arise when the vessel is steaming with waves. This study addresses the ambiguities and analyzes arbitrary cases. In addition, a practical method is provided that is useful in situations when the vessel is changing speed or heading. These methods improved the laser rangefinder estimates of spectral shapes and peak parameters when compared to nearby buoys and a spectral wave model.

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William S. Olson
,
Christian D. Kummerow
,
Song Yang
,
Grant W. Petty
,
Wei-Kuo Tao
,
Thomas L. Bell
,
Scott A. Braun
,
Yansen Wang
,
Stephen E. Lang
,
Daniel E. Johnson
, and
Christine Chiu

Abstract

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5°-resolution range from approximately 50% at 1 mm h−1 to 20% at 14 mm h−1. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%–80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5° resolution is relatively small (less than 6% at 5 mm day−1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%–35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%–15% at 5 mm day−1, with proportionate reductions in latent heating sampling errors.

Full access
Mary E. Whelan
,
Leander D. L. Anderegg
,
Grayson Badgley
,
J. Elliott Campbell
,
Roisin Commane
,
Christian Frankenberg
,
Timothy W. Hilton
,
Le Kuai
,
Nicholas Parazoo
,
Yoichi Shiga
,
Yuting Wang
, and
John Worden

Abstract

Where does the carbon released by burning fossil fuels go? Currently, ocean and land systems remove about half of the CO2 emitted by human activities; the remainder stays in the atmosphere. These removal processes are sensitive to feedbacks in the energy, carbon, and water cycles that will change in the future. Observing how much carbon is taken up on land through photosynthesis is complicated because carbon is simultaneously respired by plants, animals, and microbes. Global observations from satellites and air samples suggest that natural ecosystems take up about as much CO2 as they emit. To match the data, our land models generate imaginary Earths where carbon uptake and respiration are roughly balanced, but the absolute quantities of carbon being exchanged vary widely. Getting the magnitude of the flux is essential to make sure our models are capturing the right pattern for the right reasons. Combining two cutting-edge tools, carbonyl sulfide (OCS) and solar-induced fluorescence (SIF), will help develop an independent answer of how much carbon is being taken up by global ecosystems. Photosynthesis requires CO2, light, and water. OCS provides a spatially and temporally integrated picture of the “front door” of photosynthesis, proportional to CO2 uptake and water loss through plant stomata. SIF provides a high-resolution snapshot of the “side door,” scaling with the light captured by leaves. These two independent pieces of information help us understand plant water and carbon exchange. A coordinated effort to generate SIF and OCS data through satellite, airborne, and ground observations will improve our process-based models to predict how these cycles will change in the future.

Free access
Eun-Pa Lim
,
Harry H. Hendon
,
Amy H. Butler
,
David W. J. Thompson
,
Zachary D. Lawrence
,
Adam A. Scaife
,
Theodore G. Shepherd
,
Inna Polichtchouk
,
Hisashi Nakamura
,
Chiaki Kobayashi
,
Ruth Comer
,
Lawrence Coy
,
Andrew Dowdy
,
Rene D. Garreaud
,
Paul A. Newman
, and
Guomin Wang

Abstract

This study offers an overview of the low-frequency (i.e., monthly to seasonal) evolution, dynamics, predictability, and surface impacts of a rare Southern Hemisphere (SH) stratospheric warming that occurred in austral spring 2019. Between late August and mid-September 2019, the stratospheric circumpolar westerly jet weakened rapidly, and Antarctic stratospheric temperatures rose dramatically. The deceleration of the vortex at 10 hPa was as drastic as that of the first-ever-observed major sudden stratospheric warming in the SH during 2002, while the mean Antarctic warming over the course of spring 2019 broke the previous record of 2002 by ∼50% in the midstratosphere. This event was preceded by a poleward shift of the SH polar night jet in the uppermost stratosphere in early winter, which was then followed by record-strong planetary wave-1 activity propagating upward from the troposphere in August that acted to dramatically weaken the polar vortex throughout the depth of the stratosphere. The weakened vortex winds and elevated temperatures moved downward to the surface from mid-October to December, promoting a record strong swing of the southern annular mode (SAM) to its negative phase. This record-negative SAM appeared to be a primary driver of the extreme hot and dry conditions over subtropical eastern Australia that accompanied the severe wildfires that occurred in late spring 2019. State-of-the-art dynamical seasonal forecast systems skillfully predicted the significant vortex weakening of spring 2019 and subsequent development of negative SAM from as early as late July.

Full access
Eun-Pa Lim
,
Harry H. Hendon
,
Amy H. Butler
,
David W. J. Thompson
,
Zachary D. Lawrence
,
Adam A. Scaife
,
Theodore G. Shepherd
,
Inna Polichtchouk
,
Hisashi Nakamura
,
Chiaki Kobayashi
,
Ruth Comer
,
Lawrence Coy
,
Andrew Dowdy
,
Rene D. Garreaud
,
Paul A. Newman
, and
Guomin Wang
Open access
H. J. S. Fernando
,
E. R. Pardyjak
,
S. Di Sabatino
,
F. K. Chow
,
S. F. J. De Wekker
,
S. W. Hoch
,
J. Hacker
,
J. C. Pace
,
T. Pratt
,
Z. Pu
,
W. J. Steenburgh
,
C. D. Whiteman
,
Y. Wang
,
D. Zajic
,
B. Balsley
,
R. Dimitrova
,
G. D. Emmitt
,
C. W. Higgins
,
J. C. R. Hunt
,
J. C. Knievel
,
D. Lawrence
,
Y. Liu
,
D. F. Nadeau
,
E. Kit
,
B. W. Blomquist
,
P. Conry
,
R. S. Coppersmith
,
E. Creegan
,
M. Felton
,
A. Grachev
,
N. Gunawardena
,
C. Hang
,
C. M. Hocut
,
G. Huynh
,
M. E. Jeglum
,
D. Jensen
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V. Kulandaivelu
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M. Lehner
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L. S. Leo
,
D. Liberzon
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J. D. Massey
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K. McEnerney
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S. Pal
,
T. Price
,
M. Sghiatti
,
Z. Silver
,
M. Thompson
,
H. Zhang
, and
T. Zsedrovits

Abstract

Emerging application areas such as air pollution in megacities, wind energy, urban security, and operation of unmanned aerial vehicles have intensified scientific and societal interest in mountain meteorology. To address scientific needs and help improve the prediction of mountain weather, the U.S. Department of Defense has funded a research effort—the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) Program—that draws the expertise of a multidisciplinary, multi-institutional, and multinational group of researchers. The program has four principal thrusts, encompassing modeling, experimental, technology, and parameterization components, directed at diagnosing model deficiencies and critical knowledge gaps, conducting experimental studies, and developing tools for model improvements. The access to the Granite Mountain Atmospheric Sciences Testbed of the U.S. Army Dugway Proving Ground, as well as to a suite of conventional and novel high-end airborne and surface measurement platforms, has provided an unprecedented opportunity to investigate phenomena of time scales from a few seconds to a few days, covering spatial extents of tens of kilometers down to millimeters. This article provides an overview of the MATERHORN and a glimpse at its initial findings. Orographic forcing creates a multitude of time-dependent submesoscale phenomena that contribute to the variability of mountain weather at mesoscale. The nexus of predictions by mesoscale model ensembles and observations are described, identifying opportunities for further improvements in mountain weather forecasting.

Full access
Mary E. Whelan
,
Leander D. L. Anderegg
,
Grayson Badgley
,
J. Elliott Campbell
,
Roisin Commane
,
Christian Frankenberg
,
Timothy W. Hilton
,
Le Kuai
,
Nicholas Parazoo
,
Yoichi Shiga
,
Yuting Wang
, and
John Worden
Full access
Z. Q. Li
,
H. Xu
,
K. T. Li
,
D. H. Li
,
Y. S. Xie
,
L. Li
,
Y. Zhang
,
X. F. Gu
,
W. Zhao
,
Q. J. Tian
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R. R. Deng
,
X. L. Su
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B. Huang
,
Y. L. Qiao
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W. Y. Cui
,
Y. Hu
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C. L. Gong
,
Y. Q. Wang
,
X. F. Wang
,
J. P. Wang
,
W. B. Du
,
Z. Q. Pan
,
Z. Z. Li
, and
D. Bu

Abstract

An overview of Sun–Sky Radiometer Observation Network (SONET) measurements in China is presented. Based on observations at 16 distributed SONET sites in China, atmospheric aerosol parameters are acquired via standardization processes of operational measurement, maintenance, calibration, inversion, and quality control implemented since 2010. A climatology study is performed focusing on total columnar atmospheric aerosol characteristics, including optical (aerosol optical depth, ÅngstrÖm exponent, fine-mode fraction, single-scattering albedo), physical (volume particle size distribution), chemical composition (black carbon; brown carbon; fine-mode scattering component, coarse-mode component; and aerosol water), and radiative properties (aerosol radiative forcing and efficiency). Data analyses show that aerosol optical depth is low in the west but high in the east of China. Aerosol composition also shows significant spatial and temporal variations, leading to noticeable diversities in optical and physical property patterns. In west and north China, aerosols are generally affected by dust particles, while monsoon climate and human activities impose remarkable influences on aerosols in east and south China. Aerosols in China exhibit strong light-scattering capability and result in significant radiative cooling effects.

Full access
H. J. S. Fernando
,
I. Gultepe
,
C. Dorman
,
E. Pardyjak
,
Q. Wang
,
S. W Hoch
,
D. Richter
,
E. Creegan
,
S. Gaberšek
,
T. Bullock
,
C. Hocut
,
R. Chang
,
D. Alappattu
,
R. Dimitrova
,
D. Flagg
,
A. Grachev
,
R. Krishnamurthy
,
D. K. Singh
,
I. Lozovatsky
,
B. Nagare
,
A. Sharma
,
S. Wagh
,
C. Wainwright
,
M. Wroblewski
,
R. Yamaguchi
,
S. Bardoel
,
R. S. Coppersmith
,
N. Chisholm
,
E. Gonzalez
,
N. Gunawardena
,
O. Hyde
,
T. Morrison
,
A. Olson
,
A. Perelet
,
W. Perrie
,
S. Wang
, and
B. Wauer
Full access
H. J. S. Fernando
,
I. Gultepe
,
C. Dorman
,
E. Pardyjak
,
Q. Wang
,
S. W Hoch
,
D. Richter
,
E. Creegan
,
S. Gaberšek
,
T. Bullock
,
C. Hocut
,
R. Chang
,
D. Alappattu
,
R. Dimitrova
,
D. Flagg
,
A. Grachev
,
R. Krishnamurthy
,
D. K. Singh
,
I. Lozovatsky
,
B. Nagare
,
A. Sharma
,
S. Wagh
,
C. Wainwright
,
M. Wroblewski
,
R. Yamaguchi
,
S. Bardoel
,
R. S. Coppersmith
,
N. Chisholm
,
E. Gonzalez
,
N. Gunawardena
,
O. Hyde
,
T. Morrison
,
A. Olson
,
A. Perelet
,
W. Perrie
,
S. Wang
, and
B. Wauer

Abstract

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

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