Assessing the reliability of dynamical and historical climate forecasts in simulating hindcast pasture growth rates

2017 ◽  
Vol 57 (7) ◽  
pp. 1525 ◽  
Author(s):  
Matthew T. Harrison ◽  
Karen M. Christie ◽  
Richard P. Rawnsley
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Circulation Model ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Weather Data ◽  
Climate Data ◽  
Climate Forecasts ◽  
Farm Model ◽  
The Impact

A priori knowledge of seasonal pasture growth rates helps livestock farmers plan with pasture supply and feed budgeting. Longer forecasts may allow managers more lead time, yet inaccurate forecasts could lead to counterproductive decisions and foregone income. By using climate forecasts generated from historical archives or the global circulation model (GCM) called the Predictive Ocean Atmosphere Model for Australia (POAMA), we simulated pasture growth rates in a whole-farm model and compared growth-rate forecasts with growth-rate hindcasts (viz. retrospective forecasts). Hindcast pasture growth rates were generated using posterior weather data measured at two sites in north-western Tasmania, Australia. Forecasts were made on a monthly basis for durations of 30, 60 and 90 days. Across sites, forecasting approaches and durations, there were no significant differences between simulated growth-rate forecasts and hindcasts when our statistical inference was conducted using either the Kolmogorov–Smirnov statistic or empirical cumulative distribution functions. However, given that both of these tests were calculated by comparing growth-rate hindcasts with monthly distributions of forecasts, we also examined linear correlations between monthly hindcast values and median monthly growth-rate forecasts. Using this approach, we found a higher correlation between hindcasts and median monthly forecasts for 30 days than for 60 or 90 days, suggesting that monthly growth-rate forecasts provide more skilful predictions than forecast durations of 2 or 3 months. The range in monthly growth-rate forecasts at 30 days was less than that at 60 or 90 days, further reinfocing the aforementioned result. The strength of the correlation between growth-rate hindcasts and median monthly forecasts from the historical approach was similar to that generated using POAMA data. Overall, the present study found that (1) statistical methods of comparing forecast data with hindcast data are important, particularly if the former is a distribution whereas the latter is a single value, (2) 1-month growth-rate forecasts have less uncertainty than forecast durations of 2 or 3 months, and (3) there is little difference between pasture growth rates simulated using climate data from either historical records or from GCMs. To test the generality of these conclusions, the study should be extended to other dairy regions. Including more regions would both enable studies of sites with greater intra-seasonal climate variability, but also better highlight the impact of seasonal and regional variation in forecast skill of POAMA as applied in our forecasting methods.

scholarly journals Reconstruction of environmental histories to investigate patterns of larval radiated shanny (Ulvaria subbifurcata) growth and selective survival in a large bay of Newfoundland

2003 ◽  
Vol 60 (2) ◽  
pp. 243-258 ◽  
Author(s):  
Hannes Baumann ◽  
Pierre Pepin ◽  
Fraser J.M Davidson ◽  
Fran Mowbray ◽  
Dietrich Schnack ◽  
...  
Keyword(s):  
Environmental History ◽  
Growth Rates ◽  
Larval Growth ◽  
Circulation Model ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Zooplankton Abundance ◽  
Selective Survival ◽  
Capelin Mallotus Villosus ◽  
Environmental Histories

Abstract We used otolith microstructure analysis to reconstruct the growth histories of larval radiated shanny (Ulvaria subbifurcata) collected over a 2-week period in Trinity Bay, Newfoundland. A dynamic 3-dimensional, eddy-resolving circulation model of the region provided larval drift patterns, which were combined with measurements of temperature and zooplankton abundance to assess the environmental history of the larvae. The abundance of juvenile and adult capelin (Mallotus villosus), the dominant planktivorous fish in this area, was monitored using five hydroacoustic surveys. The goal was to determine whether environmental histories are helpful in explaining spatial and temporal differences in larval shanny growth, measured as cumulative distribution functions (CDF) of growth rates. We found evidence for a selective loss of slower growing individuals and recognized considerable spatial differences in the CDF of larval growth rates. Consistent patterns in capelin abundance suggested that faster growing survivors, sampled at the end of the 2-week period, developed in areas of low predator densities. A dome-shaped relationship between temperature and larval growth was observed, explaining a significant but small amount of the overall variability (14%). Effects of experienced prey concentrations on larval growth rates could not be demonstrated.

scholarly journals Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations

2021 ◽  
Vol 13 (6) ◽  
pp. 1096
Author(s):  
Soi Ahn ◽  
Sung-Rae Chung ◽  
Hyun-Jong Oh ◽  
Chu-Yong Chung
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Northeast Asia ◽  
Low Earth Orbit ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Radiometric Calibration ◽  
Climate Data ◽  
Error Statistics ◽  
Spatiotemporal Resolution

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.

scholarly journals Can We Measure a COVID-19-Related Slowdown in Atmospheric CO2 Growth? Sensitivity of Total Carbon Column Observations

2020 ◽  
Vol 12 (15) ◽  
pp. 2387 ◽  
Author(s):  
Ralf Sussmann ◽  
Markus Rettinger
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Measurement Precision ◽  
Annual Growth ◽  
Total Carbon ◽  
Mathematical Framework ◽  
Single Measurement ◽  
Synoptic Variability ◽  
Concentration Changes ◽  
The Impact

The COVID-19 pandemic is causing projected annual CO2 emission reductions up to −8% for 2020. This approximately matches the reductions required year on year to fulfill the Paris agreement. We pursue the question whether related atmospheric concentration changes may be detected by the Total Carbon Column Observing Network (TCCON), and brought into agreement with bottom-up emission-reduction estimates. We present a mathematical framework to derive annual growth rates from observed column-averaged carbon dioxide (XCO2) including uncertainties. The min–max range of TCCON growth rates for 2012–2019 was [2.00, 3.27] ppm/yr with a largest one-year increase of 1.07 ppm/yr for 2015/16 caused by El Niño. Uncertainties are 0.38 [0.28, 0.44] ppm/yr limited by synoptic variability, including a 0.05 ppm/yr contribution from single-measurement precision. TCCON growth rates are linked to a UK Met Office forecast of a COVID-19-related reduction of −0.32 ppm yr−2 in 2020 for Mauna Loa. The separation of TCCON-measured growth rates vs. the reference forecast (without COVID-19) is discussed in terms of detection delay. A 0.6 [0.4, 0.7]-yr delay is caused by the impact of synoptic variability on XCO2, including a ≈1-month contribution from single-measurement precision. A hindrance for the detection of the COVID-19-related growth rate reduction in 2020 is the ±0.57 ppm/yr uncertainty for the forecasted reference case (without COVID-19). Only assuming the ongoing growth rate reductions increasing year-on-year by −0.32 ppm yr−2 would allow a discrimination of TCCON measurements vs. the unperturbed forecast and its uncertainty—with a 2.4 [2.2, 2.5]-yr delay. Using no forecast but the max–min range of the TCCON-observed growth rates for discrimination only leads to a factor ≈2 longer delay. Therefore, the forecast uncertainties for annual growth rates must be reduced. This requires improved terrestrial ecosystem models and ocean observations to better quantify the land and ocean sinks dominating interannual variability.

scholarly journals THE IMPACT OF SPATIAL AND TEMPORAL RESOLUTIONS IN TROPICAL SUMMER RAINFALL DISTRIBUTION: PRELIMINARY RESULTS

2017 ◽  
Vol IV-4/W2 ◽  
pp. 183-191
Author(s):  
Q. Liu ◽  
L. S Chiu ◽  
X. Hao
Keyword(s):  
Climate Models ◽  
Hydrological Cycle ◽  
Probability Distributions ◽  
Summer Rainfall ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Statistical Parameters ◽  
Spatial And Temporal Scales ◽  
Gamma Distributions ◽  
The Impact

The abundance or lack of rainfall affects peoples’ life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models’ resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

scholarly journals The effects of microclimate and time resolution of meteorological data on hygrothermal analysis of wood frame building facades

2021 ◽  
Author(s):  
Wai Ki Wu
Keyword(s):  
Meteorological Data ◽  
Weather Data ◽  
Climate Data ◽  
Frame Building ◽  
Hourly Data ◽  
Average Water ◽  
Building Components ◽  
Wood Frame ◽  
Hygrothermal Analysis ◽  
The Impact

When performing hygrothermal analysis for building envelopes, climate data is required as boundary conditions. This study investigates the effect of the microclimatic conditions using Toronto Pearson Airport and downtown hourly data. The results showed that the average water content of the wood frame building façade were similar throughout the study period. The high moisture content peaks reduced to average within days. The arithmetic averaged hourly weather data may also affect the analysis’ results. 5-minute weather data is collected from the Ryerson weather network. The hourly data is constructed from the 5-minute data by arithmetic averaging. The simulation results from both dataset followed closely to each other throughout the study period. The averaging of hourly data removed some details form the raw meteorological data. However, it does not affect the overall trend of the climate condition and the impact to the hygrothermal analysis of building components is very limited.

scholarly journals Estimating Time-Varying Long-Run Growth Rate of Russian GDP in the ARX Model with Oil Prices

2020 ◽  
Vol 15 (1) ◽  
pp. 40-63 ◽  
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Oil Prices ◽  
Likelihood Method ◽  
Time Varying ◽  
Arx Model ◽  
Long Run ◽  
Unobserved Components Model ◽  
The Impact ◽  
Trend Growth

The paper estimates the path of trend growth rates for Russian GDP based on an autoregressive model with exogenous variables and with a time-varying parameter of trend growth, which, by assumption, is described by a random walk process. In conditions of a high dependence of the Russian economy on commodity exports, terms of trade are used as a control exogenous variable for GDP dynamics. For the purpose of econometric estimation, the ARX model is presented as an unobserved components model and estimated using the maximum likelihood method with the Kalman filter applied. It is shown that in the first half of the 2000s the trend growth rate was at 4%, which can be interpreted as recovery growth after a transformational recession. The higher growth rates actually achieved during this period are explained by the intensive growth of world oil prices. Later, the potential for recovery growth was exhausted, and after the crisis of 2008 the rates of trend growth were remaining at the level of 2% per year for a long period of time. However, following the 2014 crisis, trend growth rates began to decline steadily, and had reached about 1% per year by the beginning of 2019, which can be interpreted as the impact of sanctions and geopolitical uncertainty on the economic development of the Russian Federation. The results of an econometric analysis of the model on household consumption and investment data also suggest that the trend growth rate is approximately 1% per year at present.

Corona Virus Pandemic Impact on the Global Growth Rates. The Grant and the Distress Nine Selected Countries as Applied Examples

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Sayed Emara ◽  
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
The United States ◽  
Social Dimensions ◽  
Corona Virus ◽  
Advanced Economies ◽  
The World ◽  
Local Impact ◽  
The Impact ◽  
Global Growth

The study aimed to measure the effects of the Covid-19 epidemic on global growth rates in vital sectors around the world specially – Agriculture – Construction – Manufacturing – Mining -& Transport, because it is the sectors that most to the formation of the GDP and has been directly affected by the Corona pandemic, the study proved too that the Corona virus epidemic has affected, to varying levels and degrees, the economies of the countries of the world. In most different sectors, especially developing countries, but the regional and local impact of the COVID-19 crisis was highly variable, with important economic and social dimensions in addition to the implications for crisis management and political responses to deal with it... Therefore, this paper takes an in-depth look at the impact. Linked to the COVID-19 crisis, the global growth rate at the time of lockdown, which led to the emergence of very difficult fateful challenges in many economies in the world, especially the developed ones, as well as the surprise of the emergence of emerging economies that surfaced and showed positive and significant recovery in growth rates for many of their sectors Vitality at a time in which a number of advanced economies surprised us by achieving a negative growth rate in light of their enormous economic potential, so we were interested to choose a heterogeneous package from the countries of the world (9 countries )to represent the diversity required for the different impact of the Corona virus on the different world economies and the expectations which the world economy will be appear in the global growth rates after the end of this pandemic.. So we exclusively selected 9 countries: Egypt, Saudi Arabia, Ethiopia, India, China, Germany, France, the United States of America and Australia, as examples. Stratification on this research

Road mortality reduces survival and population growth rates of tammar wallabies on Garden Island, Western Australia

2010 ◽  
Vol 37 (7) ◽  
pp. 588 ◽  
Author(s):  
Brian Chambers ◽  
Roberta Bencini
Keyword(s):  
Growth Rate ◽  
Population Growth ◽  
Western Australia ◽  
Growth Rates ◽  
Survival Rates ◽  
Habitat Modification ◽  
Road Mortality ◽  
Population Growth Rates ◽  
The Impact ◽  
Naval Base

Context Although road mortality has the potential to affect the fate of populations, it is often confounded with other forms of environmental change. Therefore determining its impact separately from other factors is difficult because it requires an understanding of how road mortalities affect age- and sex-specific survival rates. Aims We determined the impact of high numbers of road-kills and habitat modification on the growth and survival of the population of tammar wallabies (Macropus eugenii) on Garden Island, off the coast of Western Australia. The increased supply of food from large areas of fertilised and irrigated lawns on a naval base was expected to increase the population growth rate (λ) and the road-kills were expected to offset the population response. Methods We conducted a mark-and-recapture study over three years to estimate rates of survival, reproduction and population growth rates in areas of the island that were either heavily affected by the presence of a naval base that included a network of roads and buildings, close enough to the naval base that animals could be affected by the disturbance there, and completely unaffected and lacking major roads or buildings. All road-kills were collected to estimate the impact of road mortality on the survival and growth rates of the population. Key results The growth rate, λ, for the population on the naval base was 1.02 ± 0.083 (s.e.) per year, which was much higher than in an area of adjacent bushland at 0.92 ± 0.065 per year and in undisturbed bushland at 0.93 ± 0.100 per year. When the impact of road mortality was removed, λ increased to 1.15 ± 0.101 per year on the naval base and 0.96 ± 0.076 per year in the bushland adjacent to the naval base. On the naval base road mortality reduced survival rates of one-year-old and adult animals by 0.14 ± 0.087 and 0.12 ± 0.012 per year (mean ± s.e.). Conclusions Road mortality counteracted the increase in the size of the tammar population caused by the habitat modification on the naval base. The impact of road mortality on the adjacent bushland population may result in its long-term decline, as the population may not be able to recover from the reduction in survival rates. Implications Road mortality has the potential to threaten susceptible populations but its impact should be quantified so that mitigation measures can be implemented where they will achieve the greatest benefits.

scholarly journals Effect of Temperature on Growth and Sporulation of US-22, US-23, and US-24 Clonal Lineages of Phytophthora infestans and Implications for Late Blight Epidemiology

2015 ◽  
Vol 105 (4) ◽  
pp. 449-459 ◽  
Author(s):  
Anna C. Seidl Johnson ◽  
Kenneth E. Frost ◽  
Douglas I. Rouse ◽  
Amanda J. Gevens
Keyword(s):  
Growth Rate ◽  
Late Blight ◽  
Phytophthora Infestans ◽  
Growth Rates ◽  
Weather Data ◽  
Effect Of Temperature ◽  
Clonal Lineage ◽  
Tomato Production ◽  
The Us ◽  
Lesion Growth

Epidemics of late blight, caused by Phytophthora infestans (Mont.) de Bary, have been studied by plant pathologists and regarded with great concern by potato and tomato growers since the Irish potato famine in the 1840s. P. infestans populations have continued to evolve, with unique clonal lineages arising which differ in pathogen fitness and pathogenicity, potentially impacting epidemiology. In 2012 and 2013, the US-23 clonal lineage predominated late blight epidemics in most U.S. potato and tomato production regions, including Wisconsin. This lineage was unknown prior to 2009. For isolates of three recently identified clonal lineages of P. infestans (US-22, US-23, and US-24), sporulation rates were experimentally determined on potato and tomato foliage and the effect of temperature on lesion growth rate on tomato was investigated. The US-22 and US-23 isolates had greater lesion growth rates on tomato than US-24 isolates. Sporulation rates for all isolates were greater on potato than tomato, and the US-23 isolates had greater sporulation rates on both tomato and potato than the US-22 and US-24 isolates. Experimentally determined correlates of fitness were input to the LATEBLIGHT model and epidemics were simulated using archived Wisconsin weather data from four growing seasons (2009 to 2012) to investigate the effect of isolates of these new lineages on late blight epidemiology. The fast lesion growth rates of US-22 and US-23 isolates resulted in severe epidemics in all years tested, particularly in 2011. The greater sporulation rates of P. infestans on potato resulted in simulated epidemics that progressed faster than epidemics simulated for tomato; the high sporulation rates of US-23 isolates resulted in simulated epidemics more severe than simulated epidemics of isolates of the US-22 and US-24 isolates and EC-1 clonal lineages on potato and tomato. Additionally, US-23 isolates consistently caused severe simulated epidemics when lesion growth rate and sporulation were input into the model singly or together. Sporangial size of the US-23 isolates was significantly smaller than that of US-22 and US-24 isolates, which may result in more efficient release of sporangia from the tomato or potato canopy. Our experimentally determined correlates of fitness and the simulated epidemics resulting from their incorporation into the LATEBLIGHT model suggest that US-23 isolates of P. infestans may have the greatest fitness among currently prevalent lineages and may be the most likely lineage to persist in the P. infestans population. The US-23 clonal lineage has been documented as the most prevalent lineage in recent years, indicating its overall fitness. In our work, US-23 had the highest epidemic potential among current genotypes. Given that epidemic potential is a component of fitness, this may, in part, explain the current predominance of the US-23 lineage.

scholarly journals Importance of pfkA for Rapid Growth ofEnterobacter cloacae during Colonization of Crop Seeds

2000 ◽  
Vol 66 (1) ◽  
pp. 87-91 ◽  
Author(s):  
D. P. Roberts ◽  
P. D. Dery ◽  
I. Yucel ◽  
J. S. Buyer
Keyword(s):  
Amino Acids ◽  
Growth Rate ◽  
Growth Rates ◽  
Rapid Growth ◽  
Sweet Corn ◽  
Natural Soil ◽  
Transposon Insertion ◽  
Carbon Compounds ◽  
The Impact

ABSTRACT Enterobacter cloacae A-11 is a prototrophic, glycolytic mutant of strain 501R3 with a single transposon insertion inpfkA. The populations of strain A-11 on cucumber and radish seeds were smaller than the populations of strain 501R3 in natural soil, but the populations of these two strains on pea, soybean, sunflower, and sweet corn seeds were similar (D. P. Roberts, P. D. Dery, I. Yucel, J. Buyer, M. A. Holtman, and D. Y. Kobayashi, Appl. Environ. Microbiol. 65:2513–2519, 1999). The net effect of the mutation in pfkA in vitro was a shift from rapid growth on certain carbohydrates detected in seed exudates to much slower growth on other carbohydrates, amino acids, and organic acids. The impact of the mutation in pfkA was greatest on the growth rate of E. cloacae on the seeds that released the smallest quantities of fructose, other carbohydrates, and amino acids. Corn, pea, soybean, and sunflower seeds released total amounts of carbohydrates and amino acids at rates that were approximately 10- to 100-fold greater than the rates observed with cucumber and radish seeds for the first 24 h after inhibition began. The growth rate of strain A-11 was significantly less (50% less) than the growth rate of strain 501R3 on radish seeds, and the growth rate of strain A-11 was too low to estimate on cucumber seeds in sterile sand for the first 24 h after inhibition began. The growth rate of strain A-11 was also significantly lower on soybean seeds, but it was only 17% lower than the growth rate of strain 501R3. The growth rates of strains 501R3 and A-11 were similar on pea, sunflower, and corn seeds in sterile sand for the first 30 h after imbibition began. Large reductions in the growth rates of strain A-11 on seeds were correlated with subsequent decreased levels of colonization of seeds compared to the levels of colonization of strain 501R3. The strain A-11 populations were significantly smaller than the strain 501R3 populations only on radish and cucumber seeds. The mutation in pfkA appears to decrease the level of colonization by E. cloacae for seeds that release small quantities of reduced carbon compounds by decreasing the size of the pool of compounds that support rapid growth by this bacterium.

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