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E. J. Smith, E. E. Adderley, and D. T. Walsh

Abstract

A cloud-seeding experiment was conducted in the Snowy Mountains of Australia from 1955–1959 inclusive. The objective was to determine if silver-iodide smoke released from an aircraft into clouds could increase the precipitation over a selected area. The method involved a comparison of the precipitation in a target area and that in a control area during randomized periods of seeding and no seeding. Over the five years, the ratio of the precipitation in the target to that in the control area was higher in seeded than in unseeded periods. Three statistical tests are presented which show that the seeded periods are different from the unseeded periods at significance levels of 0.03, 0.09 and 0.03 (one sided). This supports a positive seeding effect. Other analyses both detract from and support this contention. The net result is that the experiment in inconclusive. Further, improved experiments are proposed.

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D. W. T. Griffith, N. B. Jones, B. McNamara, C. Paton Walsh, W. Bell, and C. Bernardo

Abstract

A formal intercomparison of atmospheric total column measurements of N2O, N2, CH4, O3, HCl, HNO3, and HF by two ground-based solar Fourier transform infrared (FTIR) spectrometers conducted as part of the Network for the Detection of Stratospheric Change (NDSC) instrument certification procedure at Lauder, New Zealand, is presented. The two instruments were nominally very similar, collocated, and collected data at the same times. Collected spectra were analyzed independently by the individual operators in a blind-phase intercomparison, then reanalyzed by a single operator using identical analysis methods to eliminate any potential bias from the spectral analysis. From the consistent reanalysis, gases with predominantly tropospheric distributions and pressure-broadened spectral lines, such as N2O and CH4, showed differences between retrieved columns of typically less than 1%. For predominantly stratospheric gases, such as HCl and O3, differences were less than 3%. In most cases, the differences were greater than the scatter in the individual measurements and were significant at the 95% confidence level. The worst case observed was for HF, which showed a 7% systematic bias between instruments. The differences are consistent in magnitude with those expected for known types of imperfection in spectrometer alignment and operation, but attempts to quantify these effects through instrument line shape analysis, phase error, zero offsets, and channel spectra did not remove the apparent differences.

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E. J. Walsh, C. W. Wright, D. Vandemark, W. B. Krabill, A. W. Garcia, S. H. Houston, S. T. Murillo, M. D. Powell, P. G. Black, and F. D. Marks Jr.

Abstract

The NASA Scanning Radar Altimeter (SRA) flew aboard one of the NOAA WP-3D hurricane research aircraft to document the sea surface directional wave spectrum in the region between Charleston, South Carolina, and Cape Hatteras, North Carolina, as Hurricane Bonnie was making landfall near Wilmington, North Carolina, on 26 August 1998. Two days earlier, the SRA had documented the hurricane wave field spatial variation in open water when Bonnie was 400 km east of Abaco Island, Bahamas. Bonnie was similar in size during the two flights. The maximum wind speed was lower during the landfall flight (39 m s−1) than it had been during the first flight (46 m s−1). Also, Bonnie was moving faster prior to landfall (9.5 m s−1) than when it was encountered in the open ocean (5 m s−1). The open ocean wave height spatial variation indicated that Hurricane Bonnie would have produced waves of 10 m height on the shore northeast of Wilmington had it not been for the continental shelf. The gradual shoaling distributed the wave energy dissipation process across the shelf so that the wavelength and wave height were reduced gradually as the shore was approached. The wave height 5 km from shore was about 4 m.

Despite the dramatic differences in wave height caused by shoaling and the differences in the wind field and forward speed of the hurricane, there was a remarkable agreement in the wave propagation directions for the various wave components on the two days. This suggests that, in spite of its complexity, the directional wave field in the vicinity of a hurricane may be well behaved and lend itself to be modeled by a few parameters, such as the maximum wind speed, the radii of the maximum and gale force winds, and the recent movement of the storm.

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James L. Partain Jr., Sharon Alden, Heidi Strader, Uma S. Bhatt, Peter A. Bieniek, Brian R. Brettschneider, John E. Walsh, Rick T. Lader, Peter Q. Olsson, T. Scott Rupp, Richard L. Thoman Jr., Alison D. York, and Robert H. Ziel
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A. D. McGuire, J. E. Walsh, J. S. Kimball, J. S. Clein, S. E. Euskirchen, S. Drobot, U. C. Herzfeld, J. Maslanik, R. B. Lammers, M. A. Rawlins, C. J. Vorosmarty, T. S. Rupp, W. Wu, and M. Calef

Abstract

The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncertainties of simulated hydrologic and ecosystem dynamics of the western Arctic in the context of 1) uncertainties in the data available to drive the models and 2) different approaches to simulating regional hydrology and ecosystem dynamics. Analyses of datasets on climate available for driving hydrologic and ecosystem models within the western Arctic during the late twentieth century indicate that there are substantial differences among the mean states of datasets for temperature, precipitation, vapor pressure, and radiation variables. Among the studies that examined temporal trends among the alternative climate datasets, there is not much consensus on trends among the datasets. In contrast, monthly and interannual variations of some variables showed some correlation across the datasets. The application of hydrology models driven by alternative climate drivers revealed that the simulation of regional hydrology was sensitive to precipitation and water vapor differences among the driving datasets and that accurate simulation of regional water balance is limited by biases in the forcing data. Satellite-based analyses for the region indicate that vegetation productivity of the region increased during the last two decades of the twentieth century because of earlier spring thaw, and the temporal variability of vegetation productivity simulated by different models from 1980 to 2000 was generally consistent with estimates based on the satellite record for applications driven with alternative climate datasets. However, the magnitude of the fluxes differed by as much as a factor of 2.5 among applications driven with different climate data, and spatial patterns of temporal trends in carbon dynamics were quite different among simulations. Finally, the study identified that the simulation of fire by ecosystem models is particularly sensitive to alternative climate datasets, with little or no fire simulated for some datasets. The results of WALE identify the importance of conducting retrospective analyses prior to coupling hydrology and ecosystem models with climate system models. For applications of hydrology and ecosystem models driven by projections of future climate, the authors recommend a coupling strategy in which future changes from climate model simulations are superimposed on the present mean climate of the most reliable datasets of historical climate.

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D. H. Bromwich, A. B. Wilson, L. Bai, Z. Liu, M. Barlage, C.-F. Shih, S. Maldonado, K. M. Hines, S.-H. Wang, J. Woollen, B. Kuo, H.-C. Lin, T.-K. Wee, M. C. Serreze, and J. E. Walsh

Abstract

The Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000–12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century–complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks.

Open access
P. Zion Klos, John T. Abatzoglou, Alycia Bean, Jarod Blades, Melissa A. Clark, Megan Dodd, Troy E. Hall, Amanda Haruch, Philip E. Higuera, Joseph D. Holbrook, Vincent S. Jansen, Kerry Kemp, Amber Lankford, Timothy E. Link, Troy Magney, Arjan J. H. Meddens, Liza Mitchell, Brandon Moore, Penelope Morgan, Beth A. Newingham, Ryan J. Niemeyer, Ben Soderquist, Alexis A. Suazo, Kerri T. Vierling, Von Walden, and Chelsea Walsh

Abstract

Climate change is well documented at the global scale, but local and regional changes are not as well understood. Finer, local- to regional-scale information is needed for creating specific, place-based planning and adaption efforts. Here the development of an indicator-focused climate change assessment in Idaho is described. This interdisciplinary framework couples end users’ data needs with observed, biophysical changes at local to regional scales. An online statewide survey of natural resource professionals was conducted to assess the perceived impacts from climate change and determine the biophysical data needed to measure those impacts. Changes to water resources and wildfire risk were the highest areas of concern among resource professionals. Guided by the survey results, 15 biophysical indicator datasets were summarized that included direct climate metrics (e.g., air temperature) and indicators only partially influenced by climate (e.g., wildfire). Quantitative changes in indicators were determined using time series analysis from 1975 to 2010. Indicators displayed trends of varying likelihood over the analysis period, including increasing growing-season length, increasing annual temperature, increasing forest area burned, changing mountain bluebird and lilac phenology, increasing precipitation intensity, earlier center of timing of streamflow, and decreased 1 April snowpack; changes in volumetric streamflow, salmon migration dates, and stream temperature displayed the least likelihood. A final conceptual framework derived from the social and biophysical data provides an interdisciplinary case example useful for consideration by others when choosing indicators at local to regional scales for climate change assessments.

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Russell S. Vose, Scott Applequist, Mark A. Bourassa, Sara C. Pryor, Rebecca J. Barthelmie, Brian Blanton, Peter D. Bromirski, Harold E. Brooks, Arthur T. DeGaetano, Randall M. Dole, David R. Easterling, Robert E. Jensen, Thomas R. Karl, Richard W. Katz, Katherine Klink, Michael C. Kruk, Kenneth E. Kunkel, Michael C. MacCracken, Thomas C. Peterson, Karsten Shein, Bridget R. Thomas, John E. Walsh, Xiaolan L. Wang, Michael F. Wehner, Donald J. Wuebbles, and Robert S. Young

This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves are judged to be of intermediate quality. In terms of physical causes leading to multidecadal changes, the level of understanding for both extratropical storms and extreme winds is considered to be relatively low, while that for extreme waves is judged to be intermediate. Since the ability to measure these changes with some confidence is relatively recent, understanding is expected to improve in the future for a variety of reasons, including increased periods of record and the development of “climate reanalysis” projects.

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P. W. Thorne, R. J. Allan, L. Ashcroft, P. Brohan, R. J. H Dunn, M. J. Menne, P. R. Pearce, J. Picas, K. M. Willett, M. Benoy, S. Bronnimann, P. O. Canziani, J. Coll, R. Crouthamel, G. P. Compo, D. Cuppett, M. Curley, C. Duffy, I. Gillespie, J. Guijarro, S. Jourdain, E. C. Kent, H. Kubota, T. P. Legg, Q. Li, J. Matsumoto, C. Murphy, N. A. Rayner, J. J. Rennie, E. Rustemeier, L. C. Slivinski, V. Slonosky, A. Squintu, B. Tinz, M. A. Valente, S. Walsh, X. L. Wang, N. Westcott, K. Wood, S. D. Woodruff, and S. J. Worley

Abstract

Observations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional, and national holdings for different variables and time scales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across essential climate variables (ECVs) and across time scales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multitiered user support. The present paper provides a high-level overview, based upon broad community input, of the steps that are required to bring about this integration. The significant challenge is to find a sustained means to realize this vision. This requires a long-term international program. The database that results will transform our collective ability to provide societally relevant research, analysis, and predictions in many weather- and climate-related application areas across much of the globe.

Open access
J. K. Andersen, Liss M. Andreassen, Emily H. Baker, Thomas J. Ballinger, Logan T. Berner, Germar H. Bernhard, Uma S. Bhatt, Jarle W. Bjerke, Jason E. Box, L. Britt, R. Brown, David Burgess, John Cappelen, Hanne H. Christiansen, B. Decharme, C. Derksen, D. S. Drozdov, Howard E. Epstein, L. M. Farquharson, Sinead L. Farrell, Robert S. Fausto, Xavier Fettweis, Vitali E. Fioletov, Bruce C. Forbes, Gerald V. Frost, Sebastian Gerland, Scott J. Goetz, Jens-Uwe Grooß, Edward Hanna, Inger Hanssen-Bauer, Stefan Hendricks, Iolanda Ialongo, K. Isaksen, Bjørn Johnsen, L. Kaleschke, A. L. Kholodov, Seong-Joong Kim, Jack Kohler, Zachary Labe, Carol Ladd, Kaisa Lakkala, Mark J. Lara, Bryant Loomis, Bartłomiej Luks, K. Luojus, Matthew J. Macander, G. V. Malkova, Kenneth D. Mankoff, Gloria L. Manney, J. M. Marsh, Walt Meier, Twila A. Moon, Thomas Mote, L. Mudryk, F. J. Mueter, Rolf Müller, K. E. Nyland, Shad O’Neel, James E. Overland, Don Perovich, Gareth K. Phoenix, Martha K. Raynolds, C. H. Reijmer, Robert Ricker, Vladimir E. Romanovsky, E. A. G. Schuur, Martin Sharp, Nikolai I. Shiklomanov, C. J. P. P. Smeets, Sharon L. Smith, Dimitri A. Streletskiy, Marco Tedesco, Richard L. Thoman, J. T. Thorson, X. Tian-Kunze, Mary-Louise Timmermans, Hans Tømmervik, Mark Tschudi, Dirk van As, R. S. W. van de Wal, Donald A. Walker, John E. Walsh, Muyin Wang, Melinda Webster, Øyvind Winton, Gabriel J. Wolken, K. Wood, Bert Wouters, and S. Zador
Free access