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Safiétou Sanfo
,
William M. Fonta
,
Ulrich J. Diasso
,
Michel P. Nikiéma
,
John P. A. Lamers
, and
Jerôme E. Tondoh

Abstract

This study investigated key environmental factors causing intervillage migration by farmers. Therefore, it used household data from surveys, semistructured interviews, life histories, and focus group discussions in southwestern Burkina Faso, West Africa. The results showed that 1) when referring to the experienced historical weather and climate, farmers were aware of the effects of ongoing climate and environmental change; 2) soil degradation, land tenure insecurity, and lack of rainfall were major drivers of environment-induced migration; and 3) soil fertility, productivity, rainfall, and humidity, as well as land tenure security, were major pull factors. Farmers indirectly identified population pressure as a major driver of intervillage migration since it contributes to land degradation and land tenure insecurity. It is argued that migration implicitly adds to the natural climate and environmental stresses. When aiming to elaborate suitable land-use planning, the findings call for additional research that is needed to understand better the complex interrelationships between environmental drivers and permanent, environment-driven intervillage migration.

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Robert S. Pickart
,
Alison M. Macdonald
,
G. W. K. Moore
,
Ian A. Renfrew
,
John E. Walsh
, and
William S. Kessler

Abstract

The seasonal change in the development of Aleutian low pressure systems from early fall to early winter is analyzed using a combination of meteorological reanalysis fields, satellite sea surface temperature (SST) data, and satellite wind data. The time period of the study is September–December 2002, although results are shown to be representative of the long-term climatology. Characteristics of the storms were documented as they progressed across the North Pacific, including their path, central pressure, deepening rate, and speed of translation. Clear patterns emerged. Storms tended to deepen in two distinct geographical locations—the Gulf of Alaska in early fall and the western North Pacific in late fall. In the Gulf of Alaska, a quasi-permanent “notch” in the SST distribution is argued to be of significance. The signature of the notch is imprinted in the atmosphere, resulting in a region of enhanced cyclonic potential vorticity in the lower troposphere that is conducive for storm development. Later in the season, as winter approaches and the Sea of Okhotsk becomes partially ice covered and cold, the air emanating from the Asian continent leads to enhanced baroclinicity in the region south of Kamchatka. This corresponds to enhanced storm cyclogenesis in that region. Consequently, there is a seasonal westward migration of the dominant lobe of the Aleutian low. The impact of the wind stress curl pattern resulting from these two regions of storm development on the oceanic circulation is investigated using historical hydrography. It is argued that the seasonal bimodal input of cyclonic vorticity from the wind may be partly responsible for the two distinct North Pacific subarctic gyres.

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Jesse E. Bell
,
Michael A. Palecki
,
C. Bruce Baker
,
William G. Collins
,
Jay H. Lawrimore
,
Ronald D. Leeper
,
Mark E. Hall
,
John Kochendorfer
,
Tilden P. Meyers
,
Tim Wilson
, and
Howard J. Diamond

Abstract

The U.S. Climate Reference Network (USCRN) is a network of climate-monitoring stations maintained and operated by the National Oceanic and Atmospheric Administration (NOAA) to provide climate-science-quality measurements of air temperature and precipitation. The stations in the network were designed to be extensible to other missions, and the National Integrated Drought Information System program determined that the USCRN could be augmented to provide observations that are more drought relevant. To increase the network’s capability of monitoring soil processes and drought, soil observations were added to USCRN instrumentation. In 2011, the USCRN team completed at each USCRN station in the conterminous United States the installation of triplicate-configuration soil moisture and soil temperature probes at five standards depths (5, 10, 20, 50, and 100 cm) as prescribed by the World Meteorological Organization; in addition, the project included the installation of a relative humidity sensor at each of the stations. Work is also under way to eventually install soil sensors at the expanding USCRN stations in Alaska. USCRN data are stewarded by the NOAA National Climatic Data Center, and instrument engineering and performance studies, installation, and maintenance are performed by the NOAA Atmospheric Turbulence and Diffusion Division. This article provides a technical description of the USCRN soil observations in the context of U.S. soil-climate–measurement efforts and discusses the advantage of the triple-redundancy approach applied by the USCRN.

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William B. Willis
,
William E. Eichinger
,
John H. Prueger
,
Cathleen J. Hapeman
,
Hong Li
,
Michael D. Buser
,
Jerry L. Hatfield
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John D. Wanjura
,
Gregory A. Holt
,
Alba Torrents
,
Sean J. Plenner
,
Warren Clarida
,
Stephen D. Browne
,
Peter M. Downey
, and
Qi Yao

Abstract

Pollutant emissions to the atmosphere commonly derive from nonpoint sources that are extended in space. Such sources may contain area, volume, line, or a combination of emission types. Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. Point measurement arrays often lack in spatial and temporal resolution and accuracy. In recent years, lidar has supplemented point measurements in agricultural research by sampling spatial ensembles nearly instantaneously. Here, a methodology using backscatter data from an elastic scanning lidar is presented to estimate emission rates from extended sources. To demonstrate the approach, a known amount of particulate matter was released upwind of a vegetative environmental buffer, a barrier designed to intercept emissions from animal production facilities. The emission rate was estimated downwind of the buffer, and the buffer capture efficiency (percentage of particles captured) was calculated. Efficiencies ranged from 21% to 74% and agree with the ranges previously published. A comprehensive uncertainty analysis of the lidar methodology was performed, revealing an uncertainty of 20% in the emission rate estimate; suggestions for significantly reducing this uncertainty in future studies are made. The methodology introduced here is demonstrated by estimating the efficiency of a vegetative buffer, but it can also be applied to any extended emission source for which point samples are inadequate, such as roads, animal feedlots, and cotton gin operations. It can also be applied to any pollutant for which a lidar system is configured, such as particulate matter, carbon dioxide, and ammonia.

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Harry L. Bryden
,
William E. Johns
,
Brian A. King
,
Gerard McCarthy
,
Elaine L. McDonagh
,
Ben I. Moat
, and
David A. Smeed

Abstract

Northward ocean heat transport at 26°N in the Atlantic Ocean has been measured since 2004. The ocean heat transport is large—approximately 1.25 PW, and on interannual time scales it exhibits surprisingly large temporal variability. There has been a long-term reduction in ocean heat transport of 0.17 PW from 1.32 PW before 2009 to 1.15 PW after 2009 (2009–16) on an annual average basis associated with a 2.5-Sv (1 Sv ≡ 106 m3 s−1) drop in the Atlantic meridional overturning circulation (AMOC). The reduction in the AMOC has cooled and freshened the upper ocean north of 26°N over an area following the offshore edge of the Gulf Stream/North Atlantic Current from the Bahamas to Iceland. Cooling peaks south of Iceland where surface temperatures are as much as 2°C cooler in 2016 than they were in 2008. Heat uptake by the atmosphere appears to have been affected particularly along the path of the North Atlantic Current. For the reduction in ocean heat transport, changes in ocean heat content account for about one-quarter of the long-term reduction in ocean heat transport while reduced heat uptake by the atmosphere appears to account for the remainder of the change in ocean heat transport.

Free access
Paul E. Ciesielski
,
Hungjui Yu
,
Richard H. Johnson
,
Kunio Yoneyama
,
Masaki Katsumata
,
Charles N. Long
,
Junhong Wang
,
Scot M. Loehrer
,
Kathryn Young
,
Steven F. Williams
,
William Brown
,
John Braun
, and
Teresa Van Hove

Abstract

The upper-air sounding network for Dynamics of the Madden–Julian Oscillation (DYNAMO) has provided an unprecedented set of observations for studying the MJO over the Indian Ocean, where coupling of this oscillation with deep convection first occurs. With 72 rawinsonde sites and dropsonde data from 13 aircraft missions, the sounding network covers the tropics from eastern Africa to the western Pacific. In total nearly 26 000 soundings were collected from this network during the experiment’s 6-month extended observing period (from October 2011 to March 2012). Slightly more than half of the soundings, collected from 33 sites, are at high vertical resolution. Rigorous post–field phase processing of the sonde data included several levels of quality checks and a variety of corrections that address a number of issues (e.g., daytime dry bias, baseline surface data errors, ship deck heating effects, and artificial dry spikes in slow-ascent soundings).

Because of the importance of an accurate description of the moisture field in meeting the scientific goals of the experiment, particular attention is given to humidity correction and its validation. The humidity corrections, though small relative to some previous field campaigns, produced high-fidelity moisture analyses in which sonde precipitable water compared well with independent estimates. An assessment of operational model moisture analyses using corrected sonde data shows an overall good agreement with the exception at upper levels, where model moisture and clouds are more abundant than the sonde data would indicate.

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Wendell A. Nuss
,
John ML Bane
,
William T. Thompson
,
Teddy Holt
,
Clive E. Dorman
,
F. Martin Ralph
,
Richard Rotunno
,
Joseph B. Klemp
,
William C. Skamarock
,
Roger M. Samelson
,
Audrey M. Rogerson
,
Chris Reason
, and
Peter Jackson

Coastally trapped wind reversals along the U.S. west coast, which are often accompanied by a northward surge of fog or stratus, are an important warm-season forecast problem due to their impact on coastal maritime activities and airport operations. Previous studies identified several possible dynamic mechanisms that could be responsible for producing these events, yet observational and modeling limitations at the time left these competing interpretations open for debate. In an effort to improve our physical understanding, and ultimately the prediction, of these events, the Office of Naval Research sponsored an Accelerated Research Initiative in Coastal Meteorology during the years 1993–98 to study these and other related coastal meteorological phenomena. This effort included two field programs to study coastally trapped disturbances as well as numerous modeling studies to explore key dynamic mechanisms. This paper describes the various efforts that occurred under this program to provide an advancement in our understanding of these disturbances. While not all issues have been solved, the synoptic and mesoscale aspects of these events are considerably better understood.

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Abhishek Savita
,
Catia M. Domingues
,
Tim Boyer
,
Viktor Gouretski
,
Masayoshi Ishii
,
Gregory C. Johnson
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John M. Lyman
,
Josh K. Willis
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Simon J. Marsland
,
William Hobbs
,
John A. Church
,
Didier P. Monselesan
,
Peter Dobrohotoff
,
Rebecca Cowley
, and
Susan E. Wijffels

Abstract

The Earth system is accumulating energy due to human-induced activities. More than 90% of this energy has been stored in the ocean as heat since 1970, with ∼60% of that in the upper 700 m. Differences in upper-ocean heat content anomaly (OHCA) estimates, however, exist. Here, we use a dataset protocol for 1970–2008—with six instrumental bias adjustments applied to expendable bathythermograph (XBT) data, and mapped by six research groups—to evaluate the spatiotemporal spread in upper OHCA estimates arising from two choices: 1) those arising from instrumental bias adjustments and 2) those arising from mathematical (i.e., mapping) techniques to interpolate and extrapolate data in space and time. We also examined the effect of a common ocean mask, which reveals that exclusion of shallow seas can reduce global OHCA estimates up to 13%. Spread due to mapping method is largest in the Indian Ocean and in the eddy-rich and frontal regions of all basins. Spread due to XBT bias adjustment is largest in the Pacific Ocean within 30°N–30°S. In both mapping and XBT cases, spread is higher for 1990–2004. Statistically different trends among mapping methods are found not only in the poorly observed Southern Ocean but also in the well-observed northwest Atlantic. Our results cannot determine the best mapping or bias adjustment schemes, but they identify where important sensitivities exist, and thus where further understanding will help to refine OHCA estimates. These results highlight the need for further coordinated OHCA studies to evaluate the performance of existing mapping methods along with comprehensive assessment of uncertainty estimates.

Open access
Paul A. Hirschberg
,
Elliot Abrams
,
Andrea Bleistein
,
William Bua
,
Luca Delle Monache
,
Thomas W. Dulong
,
John E. Gaynor
,
Bob Glahn
,
Thomas M. Hamill
,
James A. Hansen
,
Douglas C. Hilderbrand
,
Ross N. Hoffman
,
Betty Hearn Morrow
,
Brenda Philips
,
John Sokich
, and
Neil Stuart

The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (the Plan) is summarized. The Plan (available on the AMS website at www.ametsoc.org/boardpges/cwce/docs/BEC/ACUF/2011-02-20-ACUF-Final-Report.pdf) is based on and intended to provide a foundation for implementing recent recommendations regarding forecast uncertainty by the National Research Council (NRC), AMS, and World Meteorological Organization. It defines a vision, strategic goals, roles and respon- sibilities, and an implementation road map to guide the weather and climate enterprise (the Enterprise) toward routinely providing the nation with comprehensive, skillful, reliable, and useful information about the uncertainty of weather, water, and climate (hydrometeorological) forecasts. Examples are provided describing how hydrometeorological forecast uncertainty information can improve decisions and outcomes in various socioeconomic areas. The implementation road map defines objectives and tasks that the four sectors comprising the Enterprise (i.e., government, industry, academia, and nongovernmental organizations) should work on in partnership to meet four key, interrelated strategic goals: 1) understand social and physical science aspects of forecast uncertainty; 2) communicate forecast uncertainty information effectively and collaborate with users to assist them in their decision making; 3) generate forecast uncertainty data, products, services, and information; and 4) enable research, development, and operations with necessary information technology and other infrastructure. The Plan endorses the NRC recommendation that the National Oceanic and Atmospheric Administration and, in particular, the National Weather Service, should take the lead in motivating and organizing Enterprise resources and expertise in order to reach the Plan's vision and goals and shift the nation successfully toward a greater understanding and use of forecast uncertainty in decision making.

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Christopher J. Anderson
,
Raymond W. Arritt
,
Zaitao Pan
,
Eugene S. Takle
,
William J. Gutowski Jr.
,
Francis O. Otieno
,
Renato da Silva
,
Daniel Caya
,
Jens H. Christensen
,
Daniel Lüthi
,
Miguel A. Gaertner
,
Clemente Gallardo
,
Filippo Giorgi
,
René Laprise
,
Song-You Hong
,
Colin Jones
,
H-M. H. Juang
,
J. J. Katzfey
,
John L. McGregor
,
William M. Lapenta
,
Jay W. Larson
,
John A. Taylor
,
Glen E. Liston
,
Roger A. Pielke Sr.
, and
John O. Roads

Abstract

Thirteen regional climate model (RCM) simulations of June–July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 10° × 10° subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports.

All RCMs produced positive precipitation minus evapotranspiration (PE > 0), though most RCMs produced PE below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations.

Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C (convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals.

In station reports, accumulation from high (low) 3-h totals had a nocturnal (early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

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