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Galina Guentchev, Joseph J. Barsugli, and Jon Eischeid

Abstract

Inhomogeneity in gridded meteorological data may arise from the inclusion of inhomogeneous station data or from aspects of the gridding procedure itself. However, the homogeneity of gridded datasets is rarely questioned, even though an analysis of trends or variability that uses inhomogeneous data could be misleading or even erroneous. Three gridded precipitation datasets that have been used in studies of the Upper Colorado River basin were tested for homogeneity in this study: that of Maurer et al., that of Beyene and Lettenmaier, and the Parameter–Elevation Regressions on Independent Slopes Model (PRISM) dataset of Daly et al. Four absolute homogeneity tests were applied to annual precipitation amounts on a grid cell and on a hydrologic subregion spatial scale for the periods 1950–99 and 1916–2006. The analysis detects breakpoints in 1977 and 1978 at many locations in all three datasets that may be due to an anomalously rapid shift in the Pacific decadal oscillation. One dataset showed breakpoints in the 1940s that might be due to the widespread change in the number of available observing stations used as input for that dataset. The results also indicated that the time series from the three datasets are sufficiently homogeneous for variability analysis during the 1950–99 period when aggregated on a subregional scale.

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K. M. Weickmann, S. J. S. Khalsa, and J. Eischeid

Abstract

Global-scale, Wind and outgoing longwave radiation anomalies are documented during the atmospheric angular-momentum (AAM) cycle associated with the Madden–Julian oscillation. Cross-spectral and compositing techniques are applied to 150- and 850-mb National Meteorological Center wind data and outgoing longwave radiation (OLR) data during ten northern winter and summer seasons. Coherent wind and OLR signals are found in the tropics and in the winter hemisphere and are dominated by zonal wavenumbers 0–2. At the time of zero AAM anomaly, anomalous zonal winds are found over the western hemisphere tropics (during northern winter), while convection anomalies tend to be collocated with the seasonal mean Australasian convection. Zonal-mean OLR anomalies are small. As the AAM anomaly increases, the anomalous zonal winds move eastward and poleward, while dipole convection anomalies become established over the oceanic warm pool and result in an east-west shift of the Australasian monsoon. Zonal-mean OLR anomalies tend to be large when the AAM anomalies are large. During northern winter, the inferred frictional torques peak near the time of maximum AAM anomalies suggesting that pressure torques may also help force the angular-momentum changes.

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Porathur V. Joseph, Jon K. Eischeid, and Robert J. Pyle

Abstract

The long-term mean date of the monsoon onset over Kerala (MOK) varies between 30 May and 2 June according to different estimates, with a standard deviation of 8–9 days. The earliest date of MOK, and the most delayed one, during the last 100 years differ by 46 days (7 May and 22 June, respectively). MOK switches on a spatially large and intense convective heat source over south Asia, lasting from June to September, whose moisture supply is made available through the cross-equatorial low-level jet stream.

Superposed epoch analysis of 10 years of outgoing longwave radiation (OLR) data shows that MOK is a significant stage in the evolution of the OLR field in the tropics of the eastern hemisphere. At the time of MOK there is increased convection in a band about 5–10 degrees wide meridionally, extending from the south Arabian Sea to south China, and convection is suppressed all around, particularly in the western Pacific Ocean. In 1983 when MOK was delayed by about 3 pentads, OLR data showed that the boreal spring-to-summer migration of the equatorial convective cloudiness maximum (ECCM), both westward and northward, was also delayed. The delayed MOK is accompanied by delays in the northwestward movement of ECCM and is confirmed by an analysis of long-term data of southwest Pacific tropical cyclones.

Of the 22 years between 1870–1989 when MOK was delayed by 8 days or more, 16 casts were associated with a moderate or strong El Niño. Of the 13 strong El Niños during the same period, 9 were associated with moderate-to-large delays in MOK. Delays preferentially occurred in the year +1 of an El Niño, where year 0 is the growing phase of the El Niño in sea surface temperature (SST).

Analysis of the SST field has shown that delayed MOK is associated with warm SST anomalies at and south of the equator in the Indian and Pacific oceans and cold SST anomalies in the tropical and subtropical oceans to the north during the season prior to the monsoon onset (i.e., March to May). It is hypothesized that such SST anomalies over the Indian and Pacific oceans (generally found associated with El Niño, either in year 0 or year +1 or in both) cause the interannual variability of the MOK through their action in affecting the timing of the northwestward movement of the ECCM.

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M. Hoerling, J. Barsugli, B. Livneh, J. Eischeid, X. Quan, and A. Badger

Abstract

Upper Colorado River basin streamflow has declined by roughly 20% over the last century of the instrumental period, based on estimates of naturalized flow above Lees Ferry. Here we assess factors causing the decline and evaluate the premise that rising surface temperatures have been mostly responsible. We use an event attribution framework involving parallel sets of global model experiments with and without climate change drivers. We demonstrate that climate change forcing has acted to reduce Upper Colorado River basin streamflow during this period by about 10% (with uncertainty range of 6%–14% reductions). The magnitude of the observed flow decline is found to be inconsistent with natural variability alone, and approximately one-half of the observed flow decline is judged to have resulted from long-term climate change. Each of three different global models used herein indicates that climate change forcing during the last century has acted to increase surface temperature (~+1.2°C) and decrease precipitation (~−3%). Using large ensemble methods, we diagnose the separate effects of temperature and precipitation changes on Upper Colorado River streamflow. Precipitation change is found to be the most consequential factor owing to its amplified impact on flow resulting from precipitation elasticity (percent change in streamflow per percent change in precipitation) of ~2. We confirm that warming has also driven streamflow declines, as inferred from empirical studies, although operating as a secondary factor. Our finding of a modest −2.5% °C−1 temperature sensitivity, on the basis of our best model-derived estimate, indicates that only about one-third of the attributable climate change signal in Colorado River decline resulted from warming, whereas about two-thirds resulted from precipitation decline.

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M. Hoerling, J. Eischeid, A. Kumar, R. Leung, A. Mariotti, K. Mo, S. Schubert, and R. Seager

Central Great Plains precipitation deficits during May–August 2012 were the most severe since at least 1895, eclipsing the Dust Bowl summers of 1934 and 1936. Drought developed suddenly in May, following near-normal precipitation during winter and early spring. Its proximate causes were a reduction in atmospheric moisture transport into the Great Plains from the Gulf of Mexico. Processes that generally provide air mass lift and condensation were mostly absent, including a lack of frontal cyclones in late spring followed by suppressed deep convection in the summer owing to large-scale subsidence and atmospheric stabilization.

Seasonal forecasts did not predict the summer 2012 central Great Plains drought development, which therefore arrived without early warning. Climate simulations and empirical analysis suggest that ocean surface temperatures together with changes in greenhouse gases did not induce a substantial reduction in sum mertime precipitation over the central Great Plains during 2012. Yet, diagnosis of the retrospective climate simulations also reveals a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade, most probably due to natural decadal variability. As a consequence, the probability of the severe summer Great Plains drought occurring may have increased in the last decade compared to the 1980s and 1990s, and the so-called tail risk for severe drought may have been heightened in summer 2012. Such an extreme drought event was nonetheless still found to be a rare occurrence within the spread of 2012 climate model simulations. The implications of this study's findings for U.S. seasonal drought forecasting are discussed.

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Jon K. Eischeid, Phil A. Pasteris, Henry F. Diaz, Marc S. Plantico, and Neal J. Lott

Abstract

The development of serially complete (no missing values) daily maximum–minimum temperatures and total precipitation time series over the western United States is documented. Several estimation techniques based on spatial objective analysis schemes are used to estimate daily values, with the &ldquost” estimate chosen as a missing value replacement. The development of a continuous and complete daily dataset will be useful in a variety of meteorological and hydrological research applications.

The spatial interpolation schemes are evaluated separately by interpolation method and calendar month. Cross validation of the results indicates a distinct seasonality to the efficiency (error) of the estimates, although no systematic bias in the estimation procedures was found. The resulting number of serially complete daily time series for the western United States (all states west of the Mississippi River) includes 2034 maximum–minimum temperature stations and 2962 total daily precipitation locations.

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Randall M. Dole, J. Ryan Spackman, Matthew Newman, Gilbert P. Compo, Catherine A. Smith, Leslie M. Hartten, Joseph J. Barsugli, Robert S. Webb, Martin P. Hoerling, Robert Cifelli, Klaus Wolter, Christopher D. Barnet, Maria Gehne, Ronald Gelaro, George N. Kiladis, Scott Abbott, Elena Akish, John Albers, John M. Brown, Christopher J. Cox, Lisa Darby, Gijs de Boer, Barbara DeLuisi, Juliana Dias, Jason Dunion, Jon Eischeid, Christopher Fairall, Antonia Gambacorta, Brian K. Gorton, Andrew Hoell, Janet Intrieri, Darren Jackson, Paul E. Johnston, Richard Lataitis, Kelly M. Mahoney, Katherine McCaffrey, H. Alex McColl, Michael J. Mueller, Donald Murray, Paul J. Neiman, William Otto, Ola Persson, Xiao-Wei Quan, Imtiaz Rangwala, Andrea J. Ray, David Reynolds, Emily Riley Dellaripa, Karen Rosenlof, Naoko Sakaeda, Prashant D. Sardeshmukh, Laura C. Slivinski, Lesley Smith, Amy Solomon, Dustin Swales, Stefan Tulich, Allen White, Gary Wick, Matthew G. Winterkorn, Daniel E. Wolfe, and Robert Zamora

Abstract

Forecasts by mid-2015 for a strong El Niño during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climate event and its impacts while the event was ongoing. Seizing this opportunity, the National Oceanic and Atmospheric Administration (NOAA) initiated an El Niño Rapid Response (ENRR), conducting the first field campaign to obtain intensive atmospheric observations over the tropical Pacific during El Niño.

The overarching ENRR goal was to determine the atmospheric response to El Niño and the implications for predicting extratropical storms and U.S. West Coast rainfall. The field campaign observations extended from the central tropical Pacific to the West Coast, with a primary focus on the initial tropical atmospheric response that links El Niño to its global impacts. NOAA deployed its Gulfstream-IV (G-IV) aircraft to obtain observations around organized tropical convection and poleward convective outflow near the heart of El Niño. Additional tropical Pacific observations were obtained by radiosondes launched from Kiritimati , Kiribati, and the NOAA ship Ronald H. Brown, and in the eastern North Pacific by the National Aeronautics and Space Administration (NASA) Global Hawk unmanned aerial system. These observations were all transmitted in real time for use in operational prediction models. An X-band radar installed in Santa Clara, California, helped characterize precipitation distributions. This suite supported an end-to-end capability extending from tropical Pacific processes to West Coast impacts. The ENRR observations were used during the event in operational predictions. They now provide an unprecedented dataset for further research to improve understanding and predictions of El Niño and its impacts.

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