Methods in Short-Term Climate Prediction

2006 ◽  
Author(s):  
Huug van den Dool
Keyword(s):  
Annual Cycle ◽  
Climate Prediction ◽  
Periodic Part ◽  
Short Term ◽  
Annual Cycles ◽  
Annual Variations ◽  
External Forcings ◽  
Other Information ◽  
Earth’S Climate ◽  
Quantitative Explanation

The purpose of this chapter is to list the more common accepted methods used in short-term climate prediction, explain how they are designed, how they are supposed to work, what level of skill can be expected and the references to find more about them. The emphasis is on methodology but aspects of verification and cross-validation will be mentioned as well. Most methods will be accompanied by an example. We will also mention some of the less common methods, but with less detail. We even list some methods that are not used, to delineate which are acceptable and which are not. Sections 8.1–8.6 and 8.8 are easy to read, but Sections 8.7 and 8.9 are more difficult. It will become clear by the end of the climatology section (8.1), that only the departure from climatology, the so-called anomalies, are considered worthy forecast targets. The climatology itself, including such empirically established facts as “days are warmer than nights”, and “winters are colder than summer”, is considered too obvious to be a forecast target. This is not to say that a quantitative explanation of the Earth’s climate, including daily and annual cycle, is easy. But in professionally honest verification no points are given for forecasting a correct climatology. This chapter is thus about forecasting aspects of the geophysical system that are not so obvious and more difficult. The daily and annual cycle are periodic variations controlled by external forcings such as the solar heating. Implicit in identifying a periodic phenomenon as such is that the forecast of the phenomenon is easy out to infinity. This explains a widespread search for “cycles” in early meteorological research, but very little has been found other than the obvious daily and annual cycles. By removing a climatology that accounts for daily and annual variations we in effect remove the known easy periodic part of the system. In the absence of any other information climatology is the best information available. As many travelers can attest, somebody visiting an unfamiliar location 6 months from now is well served by inspecting climatological tables.

Empirical Methods in Short-Term Climate Prediction

2006 ◽  
Author(s):  
Huug van den Dool
Keyword(s):  
Climate Prediction ◽  
Empirical Orthogonal Functions ◽  
Data Sets ◽  
Seasonal Forecasts ◽  
Short Term ◽  
Orthogonal Functions ◽  
Ocean Atmosphere Interaction ◽  
Global Coverage ◽  
Atmosphere Interaction ◽  
Global Data

This clear and accessible text describes the methods underlying short-term climate prediction at time scales of 2 weeks to a year. Although a difficult range to forecast accurately, there have been several important advances in the last ten years, most notably in understanding ocean-atmosphere interaction (El Nino for example), the release of global coverage data sets, and in prediction methods themselves. With an emphasis on the empirical approach, the text covers in detail empirical wave propagation, teleconnections, empirical orthogonal functions, and constructed analogue. It also provides a detailed description of nearly all methods used operationally in long-lead seasonal forecasts, with new examples and illustrations. The challenges of making a real time forecast are discussed, including protocol, format, and perceptions about users. Based where possible on global data sets, illustrations are not limited to the Northern Hemisphere, but include several examples from the Southern Hemisphere.

scholarly journals Getting It Straight: Accommodating Rectilinear Behavior in Captive Snakes—A Review of Recommendations and Their Evidence Base

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1459
Author(s):  
Clifford Warwick ◽  
Rachel Grant ◽  
Catrina Steedman ◽  
Tiffani J. Howell ◽  
Phillip C. Arena ◽  
...  
Keyword(s):  
Scientific Evidence ◽  
Grey Literature ◽  
Evidence Base ◽  
Short Term ◽  
Absolute Minimum ◽  
Scientific Letter ◽  
General Welfare ◽  
Other Information ◽  
Enclosure Size ◽  
Current Guidance

Snakes are sentient animals and should be subject to the accepted general welfare principles of other species. However, they are also the only vertebrates commonly housed in conditions that prevent them from adopting rectilinear behavior (ability to fully stretch out). To assess the evidence bases for historical and current guidance on snake spatial considerations, we conducted a literature search and review regarding recommendations consistent with or specifying ≥1 × and <1 × snake length enclosure size. We identified 65 publications referring to snake enclosure sizes, which were separated into three categories: peer-reviewed literature (article or chapter appearing in a peer-reviewed journal or book, n = 31), grey literature (government or other report or scientific letter, n = 18), and opaque literature (non-scientifically indexed reports, care sheets, articles, husbandry books, website or other information for which originating source is not based on scientific evidence or where scientific evidence was not provided, n = 16). We found that recommendations suggesting enclosure sizes shorter than the snakes were based entirely on decades-old ‘rule of thumb’ practices that were unsupported by scientific evidence. In contrast, recommendations suggesting enclosure sizes that allowed snakes to fully stretch utilized scientific evidence and considerations of animal welfare. Providing snakes with enclosures that enable them to fully stretch does not suggest that so doing allows adequate space for all necessary normal and important considerations. However, such enclosures are vital to allow for a limited number of essential welfare-associated behaviors, of which rectilinear posturing is one, making them absolute minimum facilities even for short-term housing.

Changes in the Amplitude of the Temperature Annual Cycle in China and Their Implication for Climate Change Research

2011 ◽  
Vol 24 (20) ◽  
pp. 5292-5302 ◽  
Author(s):  
Cheng Qian ◽  
Congbin Fu ◽  
Zhaohua Wu
Keyword(s):  
Climate Change ◽  
Annual Cycle ◽  
Linear Trend ◽  
Surface Air Temperature ◽  
Mean Amplitude ◽  
Warming Trend ◽  
Ensemble Empirical Mode Decomposition ◽  
Surface Solar Radiation ◽  
Climate Change Research ◽  
Annual Cycles

Abstract Climate change is not only reflected in the changes in annual means of climate variables but also in the changes in their annual cycles (seasonality), especially in the regions outside the tropics. In this study, the ensemble empirical mode decomposition (EEMD) method is applied to investigate the nonlinear trend in the amplitude of the annual cycle (which contributes 96% of the total variance) of China’s daily mean surface air temperature for the period 1961–2007. The results show that the variation and change in the amplitude are significant, with a peak-to-peak annual amplitude variation of 13% (1.8°C) of its mean amplitude and a significant linear decrease in amplitude by 4.6% (0.63°C) for this period. Also identified is a multidecadal change in amplitude from significant decreasing (−1.7% decade−1 or −0.23°C decade−1) to significant increasing (2.2% decade−1 or 0.29°C decade−1) occurring around 1993 that overlaps the systematic linear trend. This multidecadal change can be mainly attributed to the change in surface solar radiation, from dimming to brightening, rather than to a warming trend or an enhanced greenhouse effect. The study further proposes that the combined effect of the global dimming–brightening transition and a gradual increase in greenhouse warming has led to a perceived warming trend that is much larger in winter than in summer and to a perceived accelerated warming in the annual mean since the early 1990s in China. It also notes that the deseasonalization method (considering either the conventional repetitive climatological annual cycle or the time-varying annual cycle) can also affect trend estimation.

Introduction

2006 ◽  
Author(s):  
Huug van den Dool
Keyword(s):  
Physical System ◽  
Weather Prediction ◽  
Climate Prediction ◽  
Lead Times ◽  
Prediction Methods ◽  
Data Sets ◽  
Short Term ◽  
Global Data Sets ◽  
Geophysical System

This is first and foremost a book about short-term climate prediction. The predictions we have in mind are for weather/climate elements, mainly temperature (T) and precipitation (P), at lead times longer than two weeks, beyond the realm of detailed Numerical Weather Prediction (NWP), i.e. predictions for the next month and the next seasons out to at most a few years. call this short-term climate so as to distinguish it from long-term climate change which is not the main subject of this book. A few decades ago “short-term climate prediction” was known as “longrange weather prediction”. In order to understand short-term climate predictions, their skill and what they reveal about the atmosphere, ocean and land, several chapters are devoted to constructing prediction methods. The approach taken is mainly empirical, which means literally that it is based in experience. We will use global data sets to represent the climate and weather humanity experienced (and measured!) in the past several decades. The idea is to use these existing data sets in order to construct prediction methods. In doing so we want to acknowledge that every measurement (with error bars) is a monument about the workings of Nature. We thought about using the word “statistical” instead of “empirical” in the title of the book. These two notions overlap, obviously, but we prefer the word “empirical” because we are driven more by intuition than by a desire to apply existing or developing new statistical theory. While constructing prediction methods we want to discover to the greatest extent possible how the physical system works from observations. While not mentioned in the title, diagnostics of the physical system will thus be an important part of the book as well. We use a variety of classical tools to diagnose the geophysical system. Some of these tools have been developed further and/or old tools are applied in novel ways. We do not intend to cover all diagnostics methods, only those that relate closely to prediction. There will be an emphasis on methods used in operational prediction. It is quite difficult to gain a comprehensive idea from existing literature about methods used in operational short-term climate prediction.

Precessional Forced Zonal Triple-Pole Anomalies in the Tropical Pacific Annual Cycle

2019 ◽  
Vol 32 (21) ◽  
pp. 7369-7402 ◽  
Author(s):  
Yue Wang ◽  
ZhiMin Jian ◽  
Ping Zhao ◽  
Kang Xu ◽  
Haowen Dang ◽  
...  
Keyword(s):  
Annual Cycle ◽  
Walker Circulation ◽  
Bjerknes Feedback ◽  
Central Pacific ◽  
Annual Cycles ◽  
Basin Scale ◽  
Pole Type ◽  
Air Flows ◽  
Winter Insolation ◽  
Sst Anomalies

Abstract Based on a transient simulation of the Community Earth System Model, we identified two anomalous “zonal triple-pole type” annual cycles in the equatorial Pacific sea surface temperature (SST), which were induced by precessional evolution of the summer-minus-winter insolation difference and the autumn-minus-spring insolation difference, respectively. For example, due to the increased summer–winter insolation contrast, a zonal positive–negative–positive pattern of equatorial SST anomalies was detected after subtracting basin-scale summer SST warming. The positive SST anomalies were associated with anomalous upward air flows over the western Pacific and eastern Pacific, whereas the negative SST anomalies in the central Pacific were coupled with anomalous downward air flows, oceanic upwelling, and thermocline cooling. These central Pacific anomalies were due to multiple air–sea interactions, particularly zonal advection feedback and Bjerknes feedback. This anomalous annual cycle also included winter equatorial air–sea coupled anomalies with similar spatial patterns but opposite signs. The annual mean equatorial rainfall was significantly increased west of 135°E but decreased between 135°E and 160°W in response to the moderately intensified Walker circulation west of 160°W. The autumn–spring insolation contrast induced similar seasonal reversed anomalies during autumn and spring, but the annual means were only weakly enhanced for the Walker circulation and the rainfall anomalies had smaller magnitudes east of 160°E. These distinct responses of the annual mean climate indicated different seasonal biases in terms of the equatorial SST and associated Walker circulation anomalies due to forcing by the two seasonal insolation contrasts, and these findings had meaningful implications for paleoceanographic studies.

scholarly journals Using Self-Organizing Maps to Identify Coherent CONUS Precipitation Regions

2019 ◽  
Vol 32 (22) ◽  
pp. 7747-7761 ◽  
Author(s):  
Leif M. Swenson ◽  
Richard Grotjahn
Keyword(s):  
Extreme Events ◽  
Annual Cycle ◽  
Large Scale ◽  
Robust Statistics ◽  
Grid Point ◽  
Future Application ◽  
Self Organizing Maps ◽  
Annual Cycles ◽  
Extreme Precipitation Events ◽  
Self Organizing

Abstract Extreme precipitation events have major societal impacts. These events are rare and can have small spatial scale, making statistical analysis difficult; both factors are mitigated by combining events over a region. A methodology is presented to objectively define “coherent” regions wherein data points have matching annual cycles. Regions are found by training self-organizing maps (SOMs) on the annual cycle of precipitation for each grid point across the contiguous United States (CONUS). Using the annual cycle for our intended application minimizes problems caused by consecutive dry periods and localized extreme events. Multiple criteria are applied to identify useful numbers of regions for our future application. Criteria assess these properties for each region: having many more events than experienced by a single grid point, good connectedness and compactness, and robustness to changing the number of regions. Our methodology is applicable across datasets and is tested here on both reanalysis and gridded observational data. Precipitation regions obtained align with large-scale geographical features and are readily interpretable. Useful numbers of regions balance two conflicting preferences: larger regions contain more events and thereby have more robust statistics, but more compact regions allow weather patterns associated with extreme events to be aggregated with confidence. For 6-h precipitation, 12–15 regions over the CONUS optimize our metrics. The regions obtained are compared against two existing region archetypes. For example, a popular set of regions, based on nine groups of states, has less coherent regions than defining the same number of regions with our SOM methodology.

scholarly journals Spatial and temporal variability of snowfall over Greenland from CloudSat observations

2019 ◽  
Vol 19 (12) ◽  
pp. 8101-8121 ◽  
Author(s):  
Ralf Bennartz ◽  
Frank Fell ◽  
Claire Pettersen ◽  
Matthew D. Shupe ◽  
Dirk Schuettemeyer
Keyword(s):  
Annual Cycle ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Spatial And Temporal Variability ◽  
Mean Values ◽  
Annual Cycles ◽  
Ground Clutter ◽  
Empirical Correction ◽  
Precipitation Events

Abstract. We use the CloudSat 2006–2016 data record to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high-snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200 m above the local topography as defined by IceBridge. We then use ground-based millimeter wavelength cloud radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z–S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z–S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34±7.5 cm yr−1 liquid equivalent (where the uncertainty is determined by the range in values between the three different Z–S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30 cm yr−1 liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24 cm yr−1, depending on the assumed snowpack density and from CloudSat 23±4.5 cm yr−1. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned underestimation during summer months.

scholarly journals Seasonal migrations, body temperature fluctuations, and infection dynamics in adult amphibians

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4698 ◽  
Author(s):  
David R. Daversa ◽  
Camino Monsalve-Carcaño ◽  
Luis M. Carrascal ◽  
Jaime Bosch
Keyword(s):  
Seasonal Variation ◽  
Body Temperature ◽  
Annual Cycle ◽  
Batrachochytrium Dendrobatidis ◽  
Effective Means ◽  
The Body ◽  
Infection Prevalence ◽  
Body Temperatures ◽  
Annual Cycles ◽  
Prediction And Prevention

Risks of parasitism vary over time, with infection prevalence often fluctuating with seasonal changes in the annual cycle. Identifying the biological mechanisms underlying seasonality in infection can enable better prediction and prevention of future infection peaks. Obtaining longitudinal data on individual infections and traits across seasons throughout the annual cycle is perhaps the most effective means of achieving this aim, yet few studies have obtained such information for wildlife. Here, we tracked spiny common toads (Bufo spinosus) within and across annual cycles to assess seasonal variation in movement, body temperatures and infection from the fungal parasite, Batrachochytrium dendrobatidis (Bd). Across annual cycles, toads did not consistently sustain infections but instead gained and lost infections from year to year. Radio-tracking showed that infected toads lose infections during post-breeding migrations, and no toads contracted infection following migration, which may be one explanation for the inter-annual variability in Bd infections. We also found pronounced seasonal variation in toad body temperatures. Body temperatures approached 0 °C during winter hibernation but remained largely within the thermal tolerance range of Bd. These findings provide direct documentation of migratory recovery (i.e., loss of infection during migration) and escape in a wild population. The body temperature reductions that we observed during hibernation warrant further consideration into the role that this period plays in seasonal Bd dynamics.

Recent Researches on the Short-Term Climate Prediction at IAP—A Brief Review

2001 ◽  
Vol 18 (5) ◽  
pp. 929-936 ◽  
Author(s):  
Wang Huijun ◽  
Zhou Guangqing ◽  
Lin Zhaohui ◽  
Zhao Yan ◽  
Guo Yufu ◽  
...  
Keyword(s):  
Climate Prediction ◽  
Short Term
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