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Douglas C. Morton
,
Ruth S. DeFries
,
Yosio E. Shimabukuro
,
Liana O. Anderson
,
Fernando Del Bon Espírito-Santo
,
Matthew Hansen
, and
Mark Carroll

Abstract

The Brazilian government annually assesses the extent of deforestation in the Legal Amazon for a variety of scientific and policy applications. Currently, the assessment requires the processing and storing of large volumes of Landsat satellite data. The potential for efficient, accurate, and less data-intensive assessment of annual deforestation using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) at 250-m resolution is evaluated. Landsat-derived deforestation estimates are compared to MODIS-derived estimates for six Landsat scenes with five change-detection algorithms and a variety of input data—Surface Reflectance (MOD09), Vegetation Indices (MOD13), fraction images derived from a linear mixing model, Vegetation Cover Conversion (MOD44A), and percent tree cover from the Vegetation Continuous Fields (MOD44B) product. Several algorithms generated consistently low commission errors (positive predictive value near 90%) and identified more than 80% of deforestation polygons larger than 3 ha. All methods accurately identified polygons larger than 20 ha. However, no method consistently detected a high percent of Landsat-derived deforestation area across all six scenes. Field validation in central Mato Grosso confirmed that all MODIS-derived deforestation clusters larger than three 250-m pixels were true deforestation. Application of this field-validated method to the state of Mato Grosso for 2001–04 highlighted a change in deforestation dynamics; the number of large clusters (>10 MODIS pixels) that were detected doubled, from 750 between August 2001 and August 2002 to over 1500 between August 2003 and August 2004. These analyses demonstrate that MODIS data are appropriate for rapid identification of the location of deforestation areas and trends in deforestation dynamics with greatly reduced storage and processing requirements compared to Landsat-derived assessments. However, the MODIS-based analyses evaluated in this study are not a replacement for high-resolution analyses that estimate the total area of deforestation and identify small clearings.

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Jason A. Otkin
,
Martha C. Anderson
,
Christopher Hain
,
Iliana E. Mladenova
,
Jeffrey B. Basara
, and
Mark Svoboda

Abstract

Reliable indicators of rapid drought onset can help to improve the effectiveness of drought early warning systems. In this study, the evaporative stress index (ESI), which uses remotely sensed thermal infrared imagery to estimate evapotranspiration (ET), is compared to drought classifications in the U.S. Drought Monitor (USDM) and standard precipitation-based drought indicators for several cases of rapid drought development that have occurred across the United States in recent years. Analysis of meteorological time series from the North American Regional Reanalysis indicates that these events are typically characterized by warm air temperature and low cloud cover anomalies, often with high winds and dewpoint depressions that serve to hasten evaporative depletion of soil moisture reserves. Standardized change anomalies depicting the rate at which various multiweek ESI composites changed over different time intervals are computed to more easily identify areas experiencing rapid changes in ET. Overall, the results demonstrate that ESI change anomalies can provide early warning of incipient drought impacts on agricultural systems, as indicated in crop condition reports collected by the National Agricultural Statistics Service. In each case examined, large negative change anomalies indicative of rapidly drying conditions were either coincident with the introduction of drought in the USDM or lead the USDM drought depiction by several weeks, depending on which ESI composite and time-differencing interval was used. Incorporation of the ESI as a data layer used in the construction of the USDM may improve timely depictions of moisture conditions and vegetation stress associated with flash drought events.

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Rebecca E. Morss
,
Julie L. Demuth
,
Heather Lazrus
,
Leysia Palen
,
C. Michael Barton
,
Christopher A. Davis
,
Chris Snyder
,
Olga V. Wilhelmi
,
Kenneth M. Anderson
,
David A. Ahijevych
,
Jennings Anderson
,
Melissa Bica
,
Kathryn R. Fossell
,
Jennifer Henderson
,
Marina Kogan
,
Kevin Stowe
, and
Joshua Watts

Abstract

During the last few decades, scientific capabilities for understanding and predicting weather and climate risks have advanced rapidly. At the same time, technological advances, such as the Internet, mobile devices, and social media, are transforming how people exchange and interact with information. In this modern information environment, risk communication, interpretation, and decision-making are rapidly evolving processes that intersect across space, time, and society. Instead of a linear or iterative process in which individual members of the public assess and respond to distinct pieces of weather forecast or warning information, this article conceives of weather prediction, communication, and decision-making as an interconnected dynamic system. In this expanded framework, information and uncertainty evolve in conjunction with people’s risk perceptions, vulnerabilities, and decisions as a hazardous weather threat approaches; these processes are intertwined with evolving social interactions in the physical and digital worlds. Along with the framework, the article presents two interdisciplinary research approaches for advancing the understanding of this complex system and the processes within it: analysis of social media streams and computational natural–human system modeling. Examples from ongoing research are used to demonstrate these approaches and illustrate the types of new insights they can reveal. This expanded perspective together with research approaches, such as those introduced, can help researchers and practitioners understand and improve the creation and communication of information in atmospheric science and other fields.

Open access
J. Shukla
,
J. Anderson
,
D. Baumhefner
,
C. Brankovic
,
Y. Chang
,
E. Kalnay
,
L. Marx
,
T. Palmer
,
D. Paolino
,
J. Ploshay
,
S. Schubert
,
D. Straus
,
M. Suarez
, and
J. Tribbia

Dynamical Seasonal Prediction (DSP) is an informally coordinated multi-institution research project to investigate the predictability of seasonal mean atmospheric circulation and rainfall. The basic idea is to test the feasibility of extending the technology of routine numerical weather prediction beyond the inherent limit of deterministic predictability of weather to produce numerical climate predictions using state-of-the-art global atmospheric models. Atmospheric general circulation models (AGCMs) either forced by predicted sea surface temperature (SST) or as part of a coupled forecast system have shown in the past that certain regions of the extratropics, in particular, the Pacific–North America (PNA) region during Northern Hemisphere winter, can be predicted with significant skill especially during years of large tropical SST anomalies. However, there is still a great deal of uncertainty about how much the details of various AGCMs impact conclusions about extratropical seasonal prediction and predictability.

DSP is designed to compare seasonal simulation and prediction results from five state-of-the-art U.S. modeling groups (NCAR, COLA, GSFC, GFDL, NCEP) in order to assess which aspects of the results are robust and which are model dependent. The initial emphasis is on the predictability of seasonal anomalies over the PNA region. This paper also includes results from the ECMWF model, and historical forecast skill over both the PNA region and the European region is presented for all six models.

It is found that with specified SST boundary conditions, all models show that the winter season mean circulation anomalies over the Pacific–North American region are highly predictable during years of large tropical sea surface temperature anomalies. The influence of large anomalous boundary conditions is so strong and so reproducible that the seasonal mean forecasts can be given with a high degree of confidence. However, the degree of reproducibility is highly variable from one model to the other, and quantities such as the PNA region signal to noise ratio are found to vary significantly between the different AGCMs. It would not be possible to make reliable estimates of predictability of the seasonal mean atmosphere circulation unless causes for such large differences among models are understood.

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Wayman E. Baker
,
George D. Emmitt
,
Franklin Robertson
,
Robert M. Atlas
,
John E. Molinari
,
David A. Bowdle
,
Jan Paegle
,
R. Michael Hardesty
,
Robert T. Menzies
,
T. N. Krishnamurti
,
Robert A. Brown
,
Madison J. Post
,
John R. Anderson
,
Andrew C. Lorenc
, and
James McElroy

The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.

This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.

Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.

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A. B. White
,
M. L. Anderson
,
M. D. Dettinger
,
F. M. Ralph
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A. Hinojosa
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D. R. Cayan
,
R. K. Hartman
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D. W. Reynolds
,
L. E. Johnson
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T. L. Schneider
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R. Cifelli
,
Z. Toth
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S. I. Gutman
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C. W. King
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F. Gehrke
,
P. E. Johnston
,
C. Walls
,
D. Mann
,
D. J. Gottas
, and
T. Coleman

Abstract

During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for the water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. To improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, are required. Here, the authors describe how California is addressing their most important and costliest environmental issue—water management—in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.

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J. Boutin
,
Y. Chao
,
W. E. Asher
,
T. Delcroix
,
R. Drucker
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K. Drushka
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N. Kolodziejczyk
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T. Lee
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N. Reul
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G. Reverdin
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J. Schanze
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A. Soloviev
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L. Yu
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J. Anderson
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L. Brucker
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E. Dinnat
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A. Santos-Garcia
,
W. L. Jones
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C. Maes
,
T. Meissner
,
W. Tang
,
N. Vinogradova
, and
B. Ward

Abstract

Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km2. In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.

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L. L. Pan
,
E. L. Atlas
,
R. J. Salawitch
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S. B. Honomichl
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J. F. Bresch
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W. J. Randel
,
E. C. Apel
,
R. S. Hornbrook
,
A. J. Weinheimer
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D. C. Anderson
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S. J. Andrews
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S. Baidar
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S. P. Beaton
,
T. L. Campos
,
L. J. Carpenter
,
D. Chen
,
B. Dix
,
V. Donets
,
S. R. Hall
,
T. F. Hanisco
,
C. R. Homeyer
,
L. G. Huey
,
J. B. Jensen
,
L. Kaser
,
D. E. Kinnison
,
T. K. Koenig
,
J.-F. Lamarque
,
C. Liu
,
J. Luo
,
Z. J. Luo
,
D. D. Montzka
,
J. M. Nicely
,
R. B. Pierce
,
D. D. Riemer
,
T. Robinson
,
P. Romashkin
,
A. Saiz-Lopez
,
S. Schauffler
,
O. Shieh
,
M. H. Stell
,
K. Ullmann
,
G. Vaughan
,
R. Volkamer
, and
G. Wolfe

Abstract

The Convective Transport of Active Species in the Tropics (CONTRAST) experiment was conducted from Guam (13.5°N, 144.8°E) during January–February 2014. Using the NSF/NCAR Gulfstream V research aircraft, the experiment investigated the photochemical environment over the tropical western Pacific (TWP) warm pool, a region of massive deep convection and the major pathway for air to enter the stratosphere during Northern Hemisphere (NH) winter. The new observations provide a wealth of information for quantifying the influence of convection on the vertical distributions of active species. The airborne in situ measurements up to 15-km altitude fill a significant gap by characterizing the abundance and altitude variation of a wide suite of trace gases. These measurements, together with observations of dynamical and microphysical parameters, provide significant new data for constraining and evaluating global chemistry–climate models. Measurements include precursor and product gas species of reactive halogen compounds that impact ozone in the upper troposphere/lower stratosphere. High-accuracy, in situ measurements of ozone obtained during CONTRAST quantify ozone concentration profiles in the upper troposphere, where previous observations from balloonborne ozonesondes were often near or below the limit of detection. CONTRAST was one of the three coordinated experiments to observe the TWP during January–February 2014. Together, CONTRAST, Airborne Tropical Tropopause Experiment (ATTREX), and Coordinated Airborne Studies in the Tropics (CAST), using complementary capabilities of the three aircraft platforms as well as ground-based instrumentation, provide a comprehensive quantification of the regional distribution and vertical structure of natural and pollutant trace gases in the TWP during NH winter, from the oceanic boundary to the lower stratosphere.

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Robert M. Rauber
,
Bjorn Stevens
,
Harry T. Ochs III
,
Charles Knight
,
B. A. Albrecht
,
A. M. Blyth
,
C. W. Fairall
,
J. B. Jensen
,
S. G. Lasher-Trapp
,
O. L. Mayol-Bracero
,
G. Vali
,
J. R. Anderson
,
B. A. Baker
,
A. R. Bandy
,
E. Burnet
,
J.-L. Brenguier
,
W. A. Brewer
,
P. R. A. Brown
,
R Chuang
,
W. R. Cotton
,
L. Di Girolamo
,
B. Geerts
,
H. Gerber
,
S. Göke
,
L. Gomes
,
B. G. Heikes
,
J. G. Hudson
,
P. Kollias
,
R. R Lawson
,
S. K. Krueger
,
D. H. Lenschow
,
L. Nuijens
,
D. W. O'Sullivan
,
R. A. Rilling
,
D. C. Rogers
,
A. P. Siebesma
,
E. Snodgrass
,
J. L. Stith
,
D. C. Thornton
,
S. Tucker
,
C. H. Twohy
, and
P. Zuidema

Shallow, maritime cumuli are ubiquitous over much of the tropical oceans, and characterizing their properties is important to understanding weather and climate. The Rain in Cumulus over the Ocean (RICO) field campaign, which took place during November 2004–January 2005 in the trades over the western Atlantic, emphasized measurements of processes related to the formation of rain in shallow cumuli, and how rain subsequently modifies the structure and ensemble statistics of trade wind clouds. Eight weeks of nearly continuous S-band polarimetric radar sampling, 57 flights from three heavily instrumented research aircraft, and a suite of ground- and ship-based instrumentation provided data on trade wind clouds with unprecedented resolution. Observational strategies employed during RICO capitalized on the advances in remote sensing and other instrumentation to provide insight into processes that span a range of scales and that lie at the heart of questions relating to the cause and effects of rain from shallow maritime cumuli.

Full access
Robert M. Rauber
,
Harry T. Ochs III
,
L. Di Girolamo
,
S. Göke
,
E. Snodgrass
,
Bjorn Stevens
,
Charles Knight
,
J. B. Jensen
,
D. H. Lenschow
,
R. A. Rilling
,
D. C. Rogers
,
J. L. Stith
,
B. A. Albrecht
,
P. Zuidema
,
A. M. Blyth
,
C. W. Fairall
,
W. A. Brewer
,
S. Tucker
,
S. G. Lasher-Trapp
,
O. L. Mayol-Bracero
,
G. Vali
,
B. Geerts
,
J. R. Anderson
,
B. A. Baker
,
R. P. Lawson
,
A. R. Bandy
,
D. C. Thornton
,
E. Burnet
,
J-L. Brenguier
,
L. Gomes
,
P. R. A. Brown
,
P. Chuang
,
W. R. Cotton
,
H. Gerber
,
B. G. Heikes
,
J. G. Hudson
,
P. Kollias
,
S. K. Krueger
,
L. Nuijens
,
D. W. O'Sullivan
,
A. P. Siebesma
, and
C. H. Twohy
Full access