66 research outputs found
Employing Relative Entropy Techniques for Assessing Modifications in Animal Behavior
In order to make quantitative statements regarding behavior patterns in animals, it is important to establish whether new observations are statistically consistent with the animal's equilibrium behavior. For example, traumatic stress from the presence of a telemetry transmitter may modify the baseline behavior of an animal, which in turn can lead to a bias in results. From the perspective of information theory such a bias can be interpreted as the amount of information gained from a new measurement, relative to an existing equilibrium distribution. One important concept in information theory is the relative entropy, from which we develop a framework for quantifying time-dependent differences between new observations and equilibrium. We demonstrate the utility of the relative entropy by analyzing observed speed distributions of Pacific bluefin tuna, recorded within a 48-hour time span after capture and release. When the observed and equilibrium distributions are Gaussian, we show that the tuna's behavior is modified by traumatic stress, and that the resulting modification is dominated by the difference in central tendencies of the two distributions. Within a 95% confidence level, we find that the tuna's behavior is significantly altered for approximately 5 hours after release. Our analysis reveals a periodic fluctuation in speed corresponding to the moment just before sunrise on each day, a phenomenon related to the tuna's daily diving pattern that occurs in response to changes in ambient light
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An Evaluation of the Performance of the Twentieth Century Reanalysis Version 3
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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On northern-hemisphere wave patterns associated with winter rainfall events in China
During extended winter (November-April) 43% of the intraseasonal rainfall variability in China is explained by three spatial patterns of temporally coherent rainfall. These patterns were identified with Empirical Orthogonal Teleconnection (EOT) analysis of observed 1982-2007 pentad rainfall anomalies and connected to midlatitude disturbances. However, examination of individual strong EOT events shows that there is substantial inter-event variability in their dynamical evolution, which implies that precursor patterns found in regressions cannot serve as useful predictors. To understand the physical nature and origins of the extratropical precursors, the EOT technique is applied to six simulations of the Met Office Unified Model at horizontal resolutions of 200--40 km and with and without air-sea coupling. All simulations reproduce the observed precursor patterns in regressions, indicating robust underlying dynamical processes. Further investigation into the dynamics associated with observed patterns shows that Rossby wave dynamics can explain the large inter-event variability. The results suggest that the apparently slowly evolving or quasi-stationary waves in regression analysis are a statistical amalgamation of more rapidly propagating waves with a variety of origins and properties
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Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2)
Accurate and precise forecasting of the Indian monsoon is important for the socio-economic security of India, with improvements in agriculture and associated sectors from prediction of the monsoon onset. In this study we establish the skill of the UK Met Office coupled initialized global seasonal forecasting system, GloSea5-GC2, in forecasting Indian monsoon onset. We build on previous work that has demonstrated the good skill of GloSea5 at forecasting interannual variations of the seasonal mean Indian monsoon using measures of large-scale circulation and local precipitation. We analyze the summer hindcasts from a set of three springtime start-dates in late April/early May for the 20-year hindcast period (1992-2011). The hindcast set features at least fifteen ensemble members for each year and is analyzed using five different objective monsoon indices. These indices are designed to examine large and local-scale measures of the monsoon circulation, hydrological changes, tropospheric temperature gradient, or rainfall for single value (area-averaged) or grid-point measures of the Indian monsoon onset. There is significant correlation between onset dates in the model and those found in reanalysis. Indices based on large-scale dynamic and thermodynamic indices are better at estimating monsoon onset in the model rather than local-scale dynamical and hydrological indices. This can be attributed to the model's better representation of large-scale dynamics compared to local-scale features. GloSea5 may not be able to predict the exact date of monsoon onset over India, but this study shows that the model has a good ability at predicting category-wise monsoon onset, using early, normal or late tercile categories. Using a grid-point local rainfall onset index, we note that the forecast skill is highest over parts of central India, the Gangetic plains, and parts of coastal India - all zones of extensive agriculture in India. El Niño Southern Oscillation (ENSO) forcing in the model improves the forecast skill of monsoon onset when using a large-scale circulation index, with late monsoon onset coinciding with El Niño conditions and early monsoon onset more common in La Niña years. The results of this study suggest that GloSea5's ensemble-mean forecast may be used for reliable Indian monsoon onset prediction a month in advance despite systematic model errors
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Comparison of a manual and an automated tracking method for Tibetan Plateau vortices
Tibetan Plateau vortices (TPVs) are mesoscale cyclones originating over the Tibetan Plateau (TP) during the extended summer season (April-September). Most TPVs stay on the TP while a small number can move off the TP to the east. TPVs are known to be one of the main precipitation-bearing systems on the TP and moving-off TPVs have been associated with heavy precipitation and flooding downstream of the TP (e.g. Sichuan province, Yangtze River Valley). Identifying and tracking TPVs is difficult both due to their comparatively small horizontal extent (400 – 800 km) and the limited availability of soundings over the TP, which, in turn, constitutes a challenge for short-term predictions of TPV-related impacts and for the climatological study of TPVs.
In this study, (i) manual tracking (MT) results using radiosonde data from a network over and downstream of the TP are compared with (ii) results obtained by an automated tracking (AT) algorithm applied to ERA-Interim reanalysis. Ten MT-TPV cases are selected based on method (i) and matched to and compared with the corresponding AT-TPVs identified with method (ii). Conversely, ten AT-TPVs are selected and compared with the corresponding MT-TPVs. In general, the comparison shows good results in cases where the underlying data are in good agreement, but considerable differences are also seen in some cases and explained in terms of differences in the tracking methods, data availability/coverage and disagreement between sounding and ERA-Interim data. Recommendations are given for future efforts in TPV detection and tracking, including in an operational weather forecasting context
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Changes in northern hemisphere temperature variability shaped by regional warming patterns
Global warming involves changes not only in the mean atmospheric temperature, but also in its variability and extremes. Here we use a feature-tracking technique to investigate the dynamical contribution to temperature anomalies in the northern hemisphere in CMIP5 climate-change simulations. We develop a simple theory to explain how temperature variance and skewness changes are generated dynamically from mean temperature gradient changes, and demonstrate the crucial role of regional warming patterns in shaping the distinct response of cold and warm anomalies. We also show that skewness changes must be taken into account, in addition to variance changes, in order to correctly capture the projected temperature variability response. These changes in variability may impact humans, agriculture and animals, as they experience not only a warmer mean climate, but also a new likelihood of temperature anomalies within that climate
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