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H. G. Hidalgo, T. Das, M. D. Dettinger, D. R. Cayan, D. W. Pierce, T. P. Barnett, G. Bala, A. Mirin, A. W. Wood, C. Bonfils, B. D. Santer, and T. Nozawa

Abstract

This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier “center” timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.

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N. Wanders, A. Bachas, X. G. He, H. Huang, A. Koppa, Z. T. Mekonnen, B. R. Pagán, L. Q. Peng, N. Vergopolan, K. J. Wang, M. Xiao, S. Zhan, D. P. Lettenmaier, and E. F. Wood

Abstract

Dry conditions in 2013–16 in much of the western United States were responsible for severe drought and led to an exceptional fire season in the Pacific Northwest in 2015. Winter 2015/16 was forecasted to relieve drought in the southern portion of the region as a result of increased precipitation due to a very strong El Niño signal. A student forecasting challenge is summarized in which forecasts of winter hydroclimate across the western United States were made on 1 January 2016 for the winter hydroclimate using several dynamical and statistical forecast methods. They show that the precipitation forecasts had a large spread and none were skillful, while anomalously high observed temperatures were forecasted with a higher skill and precision. The poor forecast performance, particularly for precipitation, is traceable to high uncertainty in the North American Multi-Model Ensemble (NMME) forecast, which appears to be related to the inability of the models to predict an atmospheric blocking pattern over the region. It is found that strong El Niño sensitivities in dynamical models resulted in an overprediction of precipitation in the southern part of the domain. The results suggest the need for a more detailed attribution study of the anomalous meteorological patterns of the 2015/16 El Niño event compared to previous major events.

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David W. Pierce, Tim P. Barnett, Hugo G. Hidalgo, Tapash Das, Céline Bonfils, Benjamin D. Santer, Govindasamy Bala, Michael D. Dettinger, Daniel R. Cayan, Art Mirin, Andrew W. Wood, and Toru Nozawa

Abstract

Observations show snowpack has declined across much of the western United States over the period 1950–99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D–A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean–atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D–A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols.

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J. Rémillard, A. M. Fridlind, A. S. Ackerman, G. Tselioudis, P. Kollias, D. B. Mechem, H. E. Chandler, E. Luke, R. Wood, M. K. Witte, P. Y. Chuang, and J. K. Ayers

Abstract

A case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.

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M. Rodell, H. K. Beaudoing, T. S. L’Ecuyer, W. S. Olson, J. S. Famiglietti, P. R. Houser, R. Adler, M. G. Bosilovich, C. A. Clayson, D. Chambers, E. Clark, E. J. Fetzer, X. Gao, G. Gu, K. Hilburn, G. J. Huffman, D. P. Lettenmaier, W. T. Liu, F. R. Robertson, C. A. Schlosser, J. Sheffield, and E. F. Wood

Abstract

This study quantifies mean annual and monthly fluxes of Earth’s water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.

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Steven C. Hardiman, Ian A. Boutle, Andrew C. Bushell, Neal Butchart, Mike J. P. Cullen, Paul R. Field, Kalli Furtado, James C. Manners, Sean F. Milton, Cyril Morcrette, Fiona M. O’Connor, Ben J. Shipway, Chris Smith, David N. Walters, Martin R. Willett, Keith D. Williams, Nigel Wood, N. Luke Abraham, James Keeble, Amanda C. Maycock, John Thuburn, and Matthew T. Woodhouse

Abstract

A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.

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Tristan S. L’Ecuyer, H. K. Beaudoing, M. Rodell, W. Olson, B. Lin, S. Kato, C. A. Clayson, E. Wood, J. Sheffield, R. Adler, G. Huffman, M. Bosilovich, G. Gu, F. Robertson, P. R. Houser, D. Chambers, J. S. Famiglietti, E. Fetzer, W. T. Liu, X. Gao, C. A. Schlosser, E. Clark, D. P. Lettenmaier, and K. Hilburn

Abstract

New objectively balanced observation-based reconstructions of global and continental energy budgets and their seasonal variability are presented that span the golden decade of Earth-observing satellites at the start of the twenty-first century. In the absence of balance constraints, various combinations of modern flux datasets reveal that current estimates of net radiation into Earth’s surface exceed corresponding turbulent heat fluxes by 13–24 W m−2. The largest imbalances occur over oceanic regions where the component algorithms operate independent of closure constraints. Recent uncertainty assessments suggest that these imbalances fall within anticipated error bounds for each dataset, but the systematic nature of required adjustments across different regions confirm the existence of biases in the component fluxes. To reintroduce energy and water cycle closure information lost in the development of independent flux datasets, a variational method is introduced that explicitly accounts for the relative accuracies in all component fluxes. Applying the technique to a 10-yr record of satellite observations yields new energy budget estimates that simultaneously satisfy all energy and water cycle balance constraints. Globally, 180 W m−2 of atmospheric longwave cooling is balanced by 74 W m−2 of shortwave absorption and 106 W m−2 of latent and sensible heat release. At the surface, 106 W m−2 of downwelling radiation is balanced by turbulent heat transfer to within a residual heat flux into the oceans of 0.45 W m−2, consistent with recent observations of changes in ocean heat content. Annual mean energy budgets and their seasonal cycles for each of seven continents and nine ocean basins are also presented.

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Curtis R. Wood, Samantha J. Arnold, Ahmed A. Balogun, Janet F. Barlow, Stephen E. Belcher, Rex E. Britter, Hong Cheng, Adrian Dobre, Justin J. N. Lingard, Damien Martin, Marina K. Neophytou, Fredrik K. Petersson, Alan G. Robins, Dudley E. Shallcross, Robert J. Smalley, James E. Tate, Alison S. Tomlin, and Iain R. White

In the event of a release of toxic gas in the center of London, emergency services personnel would need to determine quickly the extent of the area contaminated. The transport of pollutants by turbulent flow within the complex streets and building architecture of London, United Kingdom, is not straightforward, and we might wonder whether it is at all possible to make a scientifically reasoned decision. Here, we describe recent progress from a major U.K. project, Dispersion of Air Pollution and its Penetration into the Local Environment (DAPPLE; information online at www.dapple.org.uk). In DAPPLE, we focus on the movement of airborne pollutants in cities by developing a greater understanding of atmospheric flow and dispersion within urban street networks. In particular, we carried out full-scale dispersion experiments in central London from 2003 through 2008 to address the extent of the dispersion of tracers following their release at street level. These measurements complemented previous studies because 1) our focus was on dispersion within the first kilometer from the source, when most of the material was expected to remain within the street network rather than being mixed into the boundary layer aloft; 2) measurements were made under a wide variety of meteorological conditions; and 3) central London represents a European, rather than North American, city geometry. Interpretation of the results from the full-scale experiments was supported by extensive numerical and wind tunnel modeling, which allowed more detailed analysis under idealized and controlled conditions. In this article, we review the full-scale DAPPLE methodologies and show early results from the analysis of the 2007 field campaign data.

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L. C. Slivinski, G. P. Compo, P. D. Sardeshmukh, J. S. Whitaker, C. McColl, R. J. Allan, P. Brohan, X. Yin, C. A. Smith, L. J. Spencer, R. S. Vose, M. Rohrer, R. P. Conroy, D. C. Schuster, J. J. Kennedy, L. Ashcroft, S. Brönnimann, M. Brunet, D. Camuffo, R. Cornes, T. A. Cram, F. Domínguez-Castro, J. E. Freeman, J. Gergis, E. Hawkins, P. D. Jones, H. Kubota, T. C. Lee, A. M. Lorrey, J. Luterbacher, C. J. Mock, R. K. Przybylak, C. Pudmenzky, V. C. Slonosky, B. Tinz, B. Trewin, X. L. Wang, C. Wilkinson, K. Wood, and P. Wyszyński

Abstract

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a “best estimate” of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

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Yolande L. Serra, Jennifer S. Haase, David K. Adams, Qiang Fu, Thomas P. Ackerman, M. Joan Alexander, Avelino Arellano, Larissa Back, Shu-Hua Chen, Kerry Emanuel, Zeljka Fuchs, Zhiming Kuang, Benjamin R Lintner, Brian Mapes, David Neelin, David Raymond, Adam H. Sobel, Paul W. Staten, Aneesh Subramanian, David W. J. Thompson, Gabriel Vecchi, Robert Wood, and Paquita Zuidema
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