Institution
Bureau of Meteorology
Government•Melbourne, Victoria, Australia•
About: Bureau of Meteorology is a government organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Tropical cyclone & Climate change. The organization has 1145 authors who have published 2726 publications receiving 132030 citations. The organization is also known as: BOM & BoM.
Papers published on a yearly basis
Papers
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Bureau of Meteorology1, Monash University, Clayton campus2, Met Office3, Meteorological Service of Canada4, National Oceanic and Atmospheric Administration5, Royal Netherlands Meteorological Institute6, University of East Anglia7, Indian Institute of Tropical Meteorology8, National Institute of Water and Atmospheric Research9, University of Reading10, University of the West Indies11, University of Oxford12, China Meteorological Administration13, Facultad de Ciencias Exactas y Naturales14, National Autonomous University of Mexico15
TL;DR: A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed as discussed by the authors, and the results showed widespread significant changes in temperature extremes associated with warming.
Abstract: A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.
3,722 citations
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Goddard Space Flight Center1, National Center for Atmospheric Research2, Meteorological Service of Canada3, Hadley Centre for Climate Prediction and Research4, Geophysical Fluid Dynamics Laboratory5, Commonwealth Scientific and Industrial Research Organisation6, University of Reading7, Science Applications International Corporation8, Princeton University9, Bureau of Meteorology10, University of Tokyo11, Macquarie University12, University of California, Los Angeles13
TL;DR: A multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer indicates potential benefits of this estimation may include improved seasonal rainfall forecasts.
Abstract: Previous estimates of land-atmosphere interaction (the impact of soil moisture on precipitation) have been limited by a lack of observational data and by the model dependence of computational estimates. To counter the second limitation, a dozen climate-modeling groups have recently performed the same highly controlled numerical experiment as part of a coordinated comparison project. This allows a multimodel estimation of the regions on Earth where precipitation is affected by soil moisture anomalies during Northern Hemisphere summer. Potential benefits of this estimation may include improved seasonal rainfall forecasts.
2,522 citations
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TL;DR: A seasonally independent index for monitoring the Madden-Julian oscillation (MJO) is described in this paper, which is based on a pair of empirical orthogonal functions (EOFs) of the combined fields of near-equatorially averaged 850-hPa zonal wind, 200-hpa zonal winds, and satellite-observed outgoing longwave radiation (OLR) data.
Abstract: A seasonally independent index for monitoring the Madden–Julian oscillation (MJO) is described. It is based on a pair of empirical orthogonal functions (EOFs) of the combined fields of near-equatorially averaged 850-hPa zonal wind, 200-hPa zonal wind, and satellite-observed outgoing longwave radiation (OLR) data. Projection of the daily observed data onto the multiple-variable EOFs, with the annual cycle and components of interannual variability removed, yields principal component (PC) time series that vary mostly on the intraseasonal time scale of the MJO only. This projection thus serves as an effective filter for the MJO without the need for conventional time filtering, making the PC time series an effective index for real-time use. The pair of PC time series that form the index are called the Real-time Multivariate MJO series 1 (RMM1) and 2 (RMM2). The properties of the RMM series and the spatial patterns of atmospheric variability they capture are explored. Despite the fact that RMM1 and RMM...
2,491 citations
University of Exeter1, ETH Zurich2, Bureau of Meteorology3, Université catholique de Louvain4, China Meteorological Administration5, Iowa State University6, Met Office7, Joseph Fourier University8, South African Weather Service9, Climate Central10, University of Victoria11, Lawrence Berkeley National Laboratory12
TL;DR: The authors assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system.
Abstract: This chapter assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system. Changes are expressed with respect to a baseline period of 1986–2005, unless otherwise stated.
1,719 citations
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TL;DR: In this paper, an analytic model of the radial profiles of sea level pressure and winds in a hurricane is presented, which is shown to be generally superior to two other widely used models and is considered to be a valuable aid in operational forecasting and case studies.
Abstract: An analytic model of the radial profiles of sea level pressure and winds in a hurricane is presented. The equations contain two parameters which may be empirically estimated from observations in a hurricane or determined climatologically to define a standard hurricane; example are given. The model is shown to be generally superior to two other widely used models and is considered to be a valuable aid in operational forecasting, case studies and engineering work.
1,526 citations
Authors
Showing all 1181 results
Name | H-index | Papers | Citations |
---|---|---|---|
Chris Ryan | 95 | 971 | 34388 |
Ronald G. Prinn | 89 | 382 | 31857 |
Sonia M. Kreidenweis | 82 | 315 | 23612 |
Christopher J. White | 77 | 621 | 25767 |
Ashish Sharma | 75 | 909 | 20460 |
Haidong Kan | 71 | 405 | 44210 |
Neville Nicholls | 70 | 189 | 24459 |
John A. Church | 68 | 194 | 19430 |
Ying-Ping Wang | 66 | 276 | 17847 |
Lisa V. Alexander | 65 | 169 | 33861 |
Harry H. Hendon | 64 | 211 | 16701 |
Julie M. Arblaster | 60 | 112 | 26567 |
Stephen R. Rintoul | 59 | 146 | 12480 |
Yuqing Wang | 58 | 217 | 11256 |
William L. Smith | 57 | 451 | 12752 |