scholarly journals Northern Russian chironomid-based modern summer temperature data set and inference models

2015 ◽  
Vol 134 ◽  
pp. 10-25 ◽  
Author(s):  
Larisa Nazarova ◽  
Angela E. Self ◽  
Stephen J. Brooks ◽  
Maarten van Hardenbroek ◽  
Ulrike Herzschuh ◽  
...  
2016 ◽  
Vol 12 (5) ◽  
pp. 1263-1280 ◽  
Author(s):  
Frazer Matthews-Bird ◽  
Stephen J. Brooks ◽  
Philip B. Holden ◽  
Encarni Montoya ◽  
William D. Gosling

Abstract. Presented here is the first chironomid calibration data set for tropical South America. Surface sediments were collected from 59 lakes across Bolivia (15 lakes), Peru (32 lakes), and Ecuador (12 lakes) between 2004 and 2013 over an altitudinal gradient from 150 m above sea level (a.s.l) to 4655 m a.s.l, between 0–17° S and 64–78° W. The study sites cover a mean annual temperature (MAT) gradient of 25 °C. In total, 55 chironomid taxa were identified in the 59 calibration data set lakes. When used as a single explanatory variable, MAT explains 12.9 % of the variance (λ1/λ2 =  1.431). Two inference models were developed using weighted averaging (WA) and Bayesian methods. The best-performing model using conventional statistical methods was a WA (inverse) model (R2jack =  0.890; RMSEPjack =  2.404 °C, RMSEP – root mean squared error of prediction; mean biasjack =  −0.017 °C; max biasjack =  4.665 °C). The Bayesian method produced a model with R2jack =  0.909, RMSEPjack =  2.373 °C, mean biasjack =  0.598 °C, and max biasjack =  3.158 °C. Both models were used to infer past temperatures from a ca. 3000-year record from the tropical Andes of Ecuador, Laguna Pindo. Inferred temperatures fluctuated around modern-day conditions but showed significant departures at certain intervals (ca. 1600 cal yr BP; ca. 3000–2500 cal yr BP). Both methods (WA and Bayesian) showed similar patterns of temperature variability; however, the magnitude of fluctuations differed. In general the WA method was more variable and often underestimated Holocene temperatures (by ca. −7 ± 2.5 °C relative to the modern period). The Bayesian method provided temperature anomaly estimates for cool periods that lay within the expected range of the Holocene (ca. −3 ± 3.4 °C). The error associated with both reconstructions is consistent with a constant temperature of 20 °C for the past 3000 years. We would caution, however, against an over-interpretation at this stage. The reconstruction can only currently be deemed qualitative and requires more research before quantitative estimates can be generated with confidence. Increasing the number, and spread, of lakes in the calibration data set would enable the detection of smaller climate signals.


2012 ◽  
Vol 119 ◽  
pp. 315-324 ◽  
Author(s):  
William L. Crosson ◽  
Mohammad Z. Al-Hamdan ◽  
Sarah N.J. Hemmings ◽  
Gina M. Wade

Author(s):  
Jay H. Lawrimore ◽  
Matthew J. Menne ◽  
Byron E. Gleason ◽  
Claude N. Williams ◽  
David B. Wuertz ◽  
...  

2016 ◽  
Vol 37 (7) ◽  
pp. 3209-3222 ◽  
Author(s):  
Branislava Jovanovic ◽  
Robert Smalley ◽  
Bertrand Timbal ◽  
Steven Siems

2011 ◽  
Vol 75 (3) ◽  
pp. 451-460 ◽  
Author(s):  
P.G. Langdon ◽  
C.J. Caseldine ◽  
I.W. Croudace ◽  
S. Jarvis ◽  
S. Wastegård ◽  
...  

AbstractFew studies currently exist that aim to validate a proxy chironomid-temperature reconstruction with instrumental temperature measurements. We used a reconstruction from a chironomid percentage abundance data set to produce quantitative summer temperature estimates since AD 1650 for NW Iceland through a transfer function approach, and validated the record against instrumental temperature measurements from Stykkishólmur in western Iceland. The core was dated through Pb-210, Cs-137 and tephra analyses (Hekla 1693) which produced a well-constrained dating model across the whole study period. Little catchment disturbance, as shown through geochemical (Itrax) and loss-on-ignition data, throughout the period further reinforce the premise that the chironomids were responding to temperature and not other catchment or within-lake variables. Particularly cold phases were identified between AD 1683–1710, AD 1765–1780 and AD 1890–1917, with relative drops in summer temperatures in the order of 1.5–2°C. The timing of these cold phases agree well with other evidence of cooler temperatures, notably increased extent of Little Ice Age (LIA) glaciers. Our evidence suggests that the magnitude of summer temperature cooling (1.5–2°C) was enough to force LIA Icelandic glaciers into their maximum Holocene extent, which is in accordance with previous modelling experiments for an Icelandic ice cap (Langjökull).


2008 ◽  
Vol 19 (2) ◽  
pp. 223-234
Author(s):  
Sandra K. Hanneman

Clinicians often need to know whether a new method of measurement is equivalent to an established one already in clinical use. This article reviews the methodology of a method-comparison study to assist the clinician with the conduct and evaluation of such studies. Temperature data from 1 subject are used to illustrate the procedures. Although one would not make decisions on the basis of the findings from 1 subject, the large number of paired measurements in the data set permits its use for illustrative purposes. Currently available software eliminates the need for tedious statistical computation but does not reduce the burden of understanding the concepts underlying a method-comparison study and accurate interpretation of the findings.


2017 ◽  
Author(s):  
David Morris ◽  
John Pinnegar ◽  
David Maxwell ◽  
Stephen Dye ◽  
Liam Fernand ◽  
...  

Abstract. The datasets described here bring together quality-controlled seawater temperature measurements, from over 130 years of Departmental government-funded marine science investigations in the UK (United Kingdom). Since before the foundation of a Marine Biological Association fisheries laboratory in 1902 and through subsequent evolutions as the Directorate of Fisheries Research and the current Centre for Environment Fisheries & Aquaculture Science, UK Government marine scientists and observers have been collecting seawater temperature data as part of oceanographic, chemical, biological, radiological, and other policy driven research and observation programmes in UK waters. These datasets start with a few tens of records per year, rise to hundreds from the early 1900s, thousands by 1959, hundreds of thousands by the 1980s, peaking with > 1 million for some years from 2000 onwards. The data source systems vary from time series at coastal monitoring stations or offshore platforms (buoys), through repeated research cruises or opportunistic sampling from ferry routes, to temperature extracts from CTD (Conductivity Temperature Depth) profiles, oceanographic, fishery and plankton tows, and data collected from recreational scuba divers or electronic devices attached to marine animals. The datasets described have not been included in previous seawater temperature collation exercises (e.g. International Comprehensive Ocean-Atmosphere Data Set, Met Office Hadley Centre Sea Surface Temperature data set, Centennial in situ Observation-Based Estimate Sea Surface Temperature data), although some summary data reside in the British Oceanographic Data Centre (BODC) archive, the Marine Environment Monitoring and Assessment National (MERMAN) database and the International Council for the Exploration of the Seas (ICES) Data Centre. We envisage the data primarily providing a biologically and ecosystem-relevant context for regional assessments of changing hydrological conditions around the British Isles, although cross matching with satellite derived data for surface temperatures at specific times and in specific areas is another area where the data could be of value (see e.g. Smit et al., 2013). Maps are provided indicating geographical coverage which is generally within and around UK Continental Shelf area, but occasionally extending north from Labrador and Greenland, to east of Svalbard, and southward to the Bay of Biscay. Example potential uses of the data are described using plots of data in four selected groups of 4 ICES Rectangles covering areas of particular fisheries interest. The full dataset enables extensive data synthesis, for example in the southern North Sea, where issues of spatial and numerical bias from a data source are explored. The full dataset also facilitates the construction of long-term temperature time series and an examination of changes in the phenology (seasonal timing) of ecosystem processes. This is done for a wide geographic area with an exploration of the limitations of data coverage over long periods. Throughout, we highlight and explore potential issues around the simple combination of data from the diverse and disparate sources collated here. The datasets are available on the Cefas Data Hub (https://www.cefas.co.uk/cefas-data-hub/).


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