scholarly journals Systematic biases in large-scale estimates of wetland methane emissions arising from water table formulations

2010 ◽  
Vol 37 (22) ◽  
pp. n/a-n/a ◽  
Author(s):  
Theodore J. Bohn ◽  
Dennis P. Lettenmaier
Keyword(s):  
Water Table ◽  
Large Scale ◽  
Methane Emissions ◽  
Systematic Biases

scholarly journals N-body Simulations to Test the Reliability of Two-point Correlation Functions of Galaxies

1992 ◽  
Vol 9 ◽  
pp. 703-704
Author(s):  
Yasushi Suto
Keyword(s):  
Correlation Functions ◽  
Large Scale ◽  
Sample Volume ◽  
Limited Data ◽  
Observable Universe ◽  
Large N ◽  
The Galaxy ◽  
Point Correlation ◽  
Systematic Biases ◽  
Redshift Survey

The shape and amplitude of the galaxy – galaxy correlation functions, ξgg(r), are among the most widely used measures of the large-scale structure in the universe (Totsuji & Kihara 1969). The estimates, however, might be seriously affected by the limited size of the sample volume, or equivalently, the limited number of available galaxies. In fact, while the observable universe extends c/H0 ~ 3000h-1Mpc, most observational works to map the distribution of galaxies so far have been mainly applied to samples within ~ 100h-1Mpc from us. Thus a CfA redshift survey slice, for example, of 8h < α < 17h, 26.5° < δ < 32.5°, and cz ≾ 15000km/sec (de Lapparent et al. 1986, 1988) represents merely ~ 2 x 10-5 of the total volume of the observable universe. This clearly illustrates the importance of examining possible systematic biases and variations in the estimates of two-point correlation functions from instrinsically limited data. We studied such sample-to-sample variations by analysing subsamples extracted from large N-body simulation data.

scholarly journals Multi-model ensemble simulations of olive pollen distribution in Europe in 2014

2017 ◽  
Author(s):  
Mikhail Sofiev ◽  
Olga Ritenberga ◽  
Roberto Albertini ◽  
Joaquim Arteta ◽  
Jordina Belmonte ◽  
...  
Keyword(s):  
Large Scale ◽  
Perfect Match ◽  
Ensemble Averaging ◽  
Skill Scores ◽  
Concentration Time Series ◽  
Systematic Biases ◽  
Pollen Distribution ◽  
The Individual ◽  
Olive Pollen ◽  
Weighting Coefficients

Abstract. A 6-models strong European ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run through the season of 2014 computing the olive pollen dispersion in Europe. The simulations have been compared with observations in 6 countries, members of the European Aeroallergen Network. Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimized combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season start was reported too early, by 8 days but for some models the error mounted to almost two weeks. For the season end, the disagreement between the models and the observations varied from a nearly perfect match up to two weeks too late. A series of sensitivity studies performed to understand the origin of the disagreements revealed crucial role of ambient temperature, especially systematic biases in its representation by meteorological models. A simple correction to the heat sum threshold eliminated the season shift but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous-days observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.

scholarly journals Evidence for a nonmonotonic relationship between ecosystem-scale peatland methane emissions and water table depth

2014 ◽  
Vol 119 (5) ◽  
pp. 826-835 ◽  
Author(s):  
Mathew G. Brown ◽  
Elyn R. Humphreys ◽  
Tim R. Moore ◽  
Nigel T. Roulet ◽  
Peter M. Lafleur
Keyword(s):  
Water Table ◽  
Methane Emissions ◽  
Water Table Depth

scholarly journals Subsidence and carbon loss in drained tropical peatlands

2012 ◽  
Vol 9 (3) ◽  
pp. 1053-1071 ◽  
Author(s):  
A. Hooijer ◽  
S. Page ◽  
J. Jauhiainen ◽  
W. A. Lee ◽  
X. X. Lu ◽  
...  
Keyword(s):  
Water Table ◽  
Land Subsidence ◽  
Large Scale ◽  
Average Rate ◽  
Water Levels ◽  
First Year ◽  
Carbon Loss ◽  
Long Term Storage ◽  
Tropical Peatlands ◽  
Average Loss

Abstract. Conversion of tropical peatlands to agriculture leads to a release of carbon from previously stable, long-term storage, resulting in land subsidence that can be a surrogate measure of CO2 emissions to the atmosphere. We present an analysis of recent large-scale subsidence monitoring studies in Acacia and oil palm plantations on peatland in SE Asia, and compare the findings with previous studies. Subsidence in the first 5 yr after drainage was found to be 142 cm, of which 75 cm occurred in the first year. After 5 yr, the subsidence rate in both plantation types, at average water table depths of 0.7 m, remained constant at around 5 cm yr−1. The results confirm that primary consolidation contributed substantially to total subsidence only in the first year after drainage, that secondary consolidation was negligible, and that the amount of compaction was also much reduced within 5 yr. Over 5 yr after drainage, 75 % of cumulative subsidence was caused by peat oxidation, and after 18 yr this was 92 %. The average rate of carbon loss over the first 5 yr was 178 t CO2eq ha−1 yr−1, which reduced to 73 t CO2eq ha−1 yr−1 over subsequent years, potentially resulting in an average loss of 100 t CO2eq ha−1 yr−1 over 25 yr. Part of the observed range in subsidence and carbon loss values is explained by differences in water table depth, but vegetation cover and other factors such as addition of fertilizers also influence peat oxidation. A relationship with groundwater table depth shows that subsidence and carbon loss are still considerable even at the highest water levels theoretically possible in plantations. This implies that improved plantation water management will reduce these impacts by 20 % at most, relative to current conditions, and that high rates of carbon loss and land subsidence are inevitable consequences of conversion of forested tropical peatlands to other land uses.

scholarly journals Characterization of Model Spread in PMIP2 Mid-Holocene Simulations of the African Monsoon

2013 ◽  
Vol 26 (4) ◽  
pp. 1192-1210 ◽  
Author(s):  
Weipeng Zheng ◽  
Pascale Braconnot
Keyword(s):  
Large Scale ◽  
West African Monsoon ◽  
Heat Fluxes ◽  
Coupled Models ◽  
African Monsoon ◽  
Systematic Biases ◽  
Intercomparison Project ◽  
Basic Features ◽  
Precipitation Changes

Abstract Simulations of the West African monsoon (WAM) for the present-day climate (0 ka) and the mid-Holocene (6 ka) using the coupled models from the Paleoclimate Modelling Intercomparison Project phase 2 (PMIP2) are assessed in this study. The authors first compare the ensemble simulations with modern observations and proxy estimates of past precipitation, showing that the PMIP2 model median captures the basic features of the WAM for 0 ka and the changes at 6 ka, despite systematic biases in the preindustrial (PI) simulations and underestimates of the northward extent and intensity of precipitation changes. The model spread is then discussed based on a classification of the monsoonal convective regimes for a subset of seven coupled models. Two major categories of model are defined based on their differences in simulating deep and moderate convective regimes in the PI simulations. Changes in precipitation at 6 ka are dominated by changes in the large-scale dynamics for most of the PMIP2 models and are characterized by a shift in the monsoonal circulation toward deeper convective regimes. Consequently, changes in the total precipitation at 6 ka depend on the changes in convective regimes and the characteristics of these regimes in the PI simulations. The results indicate that systematic model biases in simulating the radiation and heat fluxes could explain the damping of the meridional temperature gradient over West Africa and thereby the underestimation of precipitation in the Sahel–Sahara region.

Markets work in war: World War II reflected in the Zurich and Stockholm bond markets

2004 ◽  
Vol 11 (1) ◽  
pp. 51-67 ◽  
Author(s):  
BRUNO S. FREY ◽  
DANIEL WALDENSTRÖM
Keyword(s):  
World War Ii ◽  
Sovereign Debt ◽  
Large Scale ◽  
Historical Analysis ◽  
Stock Exchanges ◽  
Bond Markets ◽  
Quantitative Methodology ◽  
World War ◽  
Political Events ◽  
Systematic Biases

This article examines how trading on two geographically separate financial markets reflected political events before and during World War II. Specifically, we compare sovereign debt prices on the Zurich and Stockholm stock exchanges and find considerable (but not complete) symmetry in the price responses across the two markets in relation to turning points in the war, which suggests that markets worked efficiently. The use of a quantitative methodology on historical financial market data represents a useful complement to traditional historical analysis, offering large-scale evidence of individuals acting in their own pecuniary interest without producing any lasting systematic biases.

scholarly journals Climate predictions: the influence of nonlinearity and randomness

2012 ◽  
Vol 370 (1962) ◽  
pp. 1007-1011 ◽  
Author(s):  
J. Michael T. Thompson ◽  
Jan Sieber
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Large Scale ◽  
Statistical Properties ◽  
Gradual Change ◽  
Theme Issue ◽  
The Public ◽  
Systematic Biases ◽  
Earth’S Climate ◽  
Public Demand

The current threat of global warming and the public demand for confident projections of climate change pose the ultimate challenge to science: predicting the future behaviour of a system of such overwhelming complexity as the Earth's climate. This Theme Issue addresses two practical problems that make even prediction of the statistical properties of the climate, when treated as the attractor of a chaotic system (the weather), so challenging. The first is that even for the most detailed models, these statistical properties of the attractor show systematic biases. The second is that the attractor may undergo sudden large-scale changes on a time scale that is fast compared with the gradual change of the forcing (the so-called climate tipping).

scholarly journals Methane fluxes during the initiation of a large-scale water table manipulation experiment in the Alaskan Arctic tundra

2009 ◽  
Vol 23 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
D. Zona ◽  
W. C. Oechel ◽  
J. Kochendorfer ◽  
K. T. Paw U ◽  
A. N. Salyuk ◽  
...  
Keyword(s):  
Water Table ◽  
Large Scale ◽  
Arctic Tundra ◽  
Methane Fluxes ◽  
Alaskan Arctic ◽  
Manipulation Experiment
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