Finding and analysing long-term climate data

2019 ◽  
pp. 29-36
Author(s):  
Mark D. Schwartz ◽  
Liang Liang
Keyword(s):  
Growth And Development ◽  
Vegetation Change ◽  
Spatial Scales ◽  
Weather Data ◽  
Terrestrial Vegetation ◽  
Climate Data ◽  
Related Data ◽  
The Impact ◽  
Derived Data

This chapter provides an overview of major sources of long-term climate and related data and gives some guidance and recommendations to help select the best data for specific research projects. Major long-term climate datasets are either station-based or gridded arrays (at different spatial resolutions). Terrestrial vegetation change can be monitored in real-time using satellite-derived data. Software tools have been developed that facilitate convenient retrieval and use of climate data for ecological research. Phenological models process weather data into indices directly related to growth and development of many plant species. A crucial consideration in any analysis of the relationships among climate data and biological activity is the period of influence, and downscaling can bridge spatial scales. Measurement issues, the impact of means or extremes, as well as variations in scale and time, are all important when pondering the best climate data for a specific study.

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

scholarly journals The Impact of Climate Change on the Water Balance of Oil Sands Reclamation Covers and Natural Soil Profiles

2018 ◽  
Vol 19 (11) ◽  
pp. 1731-1752 ◽  
Author(s):  
Md. Shahabul Alam ◽  
S. Lee Barbour ◽  
Amin Elshorbagy ◽  
Mingbin Huang
Keyword(s):  
Oil Sands ◽  
Weather Generator ◽  
First Century ◽  
Soil Profiles ◽  
Percentage Increase ◽  
Climate Data ◽  
Historical Climate ◽  
Twenty First Century ◽  
The Impact

Abstract The design of reclamation soil covers at oil sands mines in northern Alberta, Canada, has been conventionally based on the calibration of soil–vegetation–atmosphere transfer (SVAT) models against field monitoring observations collected over several years, followed by simulations of long-term performance using historical climate data. This paper evaluates the long-term water balances for reclamation covers on two oil sands landforms and three natural coarse-textured forest soil profiles using both historical climate data and future climate projections. Twenty-first century daily precipitation and temperature data from CanESM2 were downscaled based on three representative concentration pathways (RCPs) employing a stochastic weather generator [Long Ashton Research Station Weather Generator (LARS-WG)]. Relative humidity, wind speed, and net radiation were downscaled using the delta change method. Downscaled precipitation and estimated potential evapotranspiration were used as inputs to simulate soil water dynamics using physically based models. Probability distributions of growing season (April–October) actual evapotranspiration (AET) and net percolation (NP) for the baseline and future periods show that AET and NP at all sites are expected to increase throughout the twenty-first century regardless of RCP, time period, and soil profile. Greater increases in AET and NP are projected toward the end of the twenty-first century. The increases in future NP at the two reclamation covers are larger (as a percentage increase) than at most of the natural sites. Increases in NP will result in greater water yield to surface water and may accelerate the rate at which chemical constituents contained within mine waste are released to downstream receptors, suggesting these potential changes need to be considered in mine closure designs.

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.

The impact of climate on risk of mania

2016 ◽  
Vol 33 (S1) ◽  
pp. S74-S74
Author(s):  
C.R. Medici ◽  
C.H. Vestergaard ◽  
D. Hadzi-Pavlovic ◽  
P. Munk-Jørgensen ◽  
G. Parker
Keyword(s):  
Ultraviolet Radiation ◽  
Snow Cover ◽  
Climate Changes ◽  
Climate Data ◽  
Unobserved Component ◽  
Competing Interest ◽  
Unobserved Component Model ◽  
Danish Meteorological Institute ◽  
The Impact

IntroductionBipolar disorder varies with season: admissions for depression peak in winter and mania peak in summer. Sunlight presumably increases the risk of mania through suppression of melatonin. If so, we expect admissions for mania to vary in accordance with climate variations.ObjectivesTo investigate how climate and climate changes affects admissions for mania.AimsTo identify which climate variables – sunshine, ultraviolet radiation, rain and snow cover – affect admissions for mania.To examine whether year-to-year weather variation as well as long-term climate changes reflects the variation in number of admissions for mania.MethodsThis register-based nationwide cohort study covers all patients admitted for mania (ICD-10 code F31 or F30.0–F30.2) between 1995 and 2012 in Denmark. Climate data, obtained from the Danish Meteorological Institute, were merged with admission data and correlated using an Unobserved Component Model regression model.Preliminary resultsIn total, 8893 patients were admitted 24,313 times between 1995 and 2012: 6573 first-admissions and 17,740 readmissions. Linear regression shows significant association between admissions per day and hours of sunshine (P < 0.01) and ultraviolet radiation (UV) dose (P < 0.01). Average days with snow cover and rain were not significantly correlated with admissions. Analyses on year-to-year variation and long-term change are not yet available.Preliminary conclusionsAdmissions for mania are correlated with sunshine and UV, but not rain and snow cover. If more patients are admitted during very sunny summers compared with less sunny summers this implies a relation with light itself and not just season.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals There and back again, an organic carbon journey: mapping pathways and loops

2021 ◽  
Author(s):  
Maike Iris Esther Scheffold ◽  
Inga Hense
Keyword(s):  
Organic Carbon ◽  
Spatial Scales ◽  
Qualitative Model ◽  
Marine Systems ◽  
Additional Tool ◽  
General Pathway ◽  
Marine System ◽  
The Impact ◽  
Embedded Process

Abstract. Understanding and determining where organic carbon (OC) ends up in the ocean and how long it remains there is one of the most pressing tasks of our time, as the fate of OC in the ocean links to the climate system. To provide an additional tool to accomplish this and other related tasks, we map and conceptualize OC pathways in a qualitative model. The model is complementary to existing concepts of OC processes and pathways which are based mainly on quantifications and observations of current states and dominant processes. Our model, on the contrary, presents general pathway patterns and embedded processes without focusing on dominant processes or pathways or omitting rare ones. By mapping, comparing, and condensing pathways and involved spatial scales, we define three remineralization and two recalcitrant dissolved organic carbon loops that close within the marine systems. Pathways that exit the marine system comprise inorganic atmospheric, OC atmospheric, and long-term sediment loops. With the defined loops and the embedded process options, the model is flexible and can be adapted to different systems, changing understanding or changing mechanisms. As such, it can help tracking pathway changes and assessing the impact of human interventions on pathways, marine ecosystems, and the oceanic organic carbon cycle.

scholarly journals Large wood as a confounding factor in interpreting the width of spring-fed streams

2020 ◽  
Vol 8 (1) ◽  
pp. 195-210
Author(s):  
Dana Ariel Lapides ◽  
Michael Manga
Keyword(s):  
Unit Length ◽  
Channel Morphology ◽  
Large Wood ◽  
Climate Data ◽  
Stream Channels ◽  
Stream Width ◽  
Order Of Magnitude ◽  
High Resolution Satellite Imagery ◽  
The Impact

Abstract. Spring-fed streams throughout volcanic regions of the western United States exhibit larger widths than runoff-fed streams with similar discharge. Due to the distinctive damped hydrograph of spring-fed streams (as compared to large peaks visible in the hydrographs of runoff-fed streams), large wood is less mobile in spring-fed than runoff-fed stream channels, so wood is more likely to remain in place than form logjams as in runoff-fed streams. The consequent long residence time of wood in spring-fed streams allows wood to potentially have long-term impacts on channel morphology. We used high-resolution satellite imagery in combination with discharge and climate data from published reports and publicly available databases to investigate the relationship between discharge, wood length, and channel width in 38 spring-fed and 20 runoff-fed streams, additionally responding to a call for increased use of remote sensing to study wood dynamics and daylighting previously unpublished data. We identified an order of magnitude more logjams than single logs per unit length present in runoff-fed streams as compared to spring-fed streams. Histograms of log orientation in spring-fed streams additionally confirmed that single logs are immobile in the channel so that the impact of single logs on channel morphology could be pronounced in spring-fed streams. Based on these observed differences, we hypothesized that there should be a difference in channel morphology. A model for stream width in spring-fed streams based solely on length of wood is a better model than one derived from discharge or including both discharge and wood length. This study provides insights into controls on stream width in spring-fed streams.

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 SUSTAINABLE AGRICULTURE MANAGEMENTS TO CONTROL SOIL EROSION

2021 ◽  
Author(s):  
Artemi Cerdà ◽  
Enric Terol
Keyword(s):  
Soil Erosion ◽  
Sustainable Agriculture ◽  
Spatial Scales ◽  
Low Frequency ◽  
Traditional Management ◽  
Erosion Rates ◽  
Olive Groves ◽  
Simulated Rain ◽  
The Impact

High rates of soil erosion compromise sustainable agriculture. In rainfed agricultural fields, erosion rates several orders ofmagnitude higher than the erosion rates considered tolerable have been quantified. In Mediterranean rainfed crops suchas vineyards, almonds and olive groves, and in the new sloping citrus and persimmon plantations, the rates of soil lossmake it necessary to apply measures to reduce them to avoid collapse in agricultural production. Managements such asweeds, catch crops and mulches (straw and pruning remains) are viable options to achieve sustainability. This work appliesmeasurements through plots, simulated rainfall experiments and ISUM (Improved Stock-Unearhing method) to quantifythe loss of soil at different temporal and spatial scales in fields of traditional management (herbicide or tillage) and underalternative management (mulches and plant covers). The work carried out at the experimental station for the study of soilerosion in the Sierra de Enguera and those of Montesa and Les Alcusses provide information on erosion plots undernatural rain. Experiments carried out with simulated rain in fields of olive, almond, citrus, persimmon, vineyard and fruittrees report the hydrological and erosive response under low frequency and high intensity rains. And finally, the ISUMtopographic method report the impact of long-term management, from the plantation. The results indicate that the loss ofsoil is greater (x10-1000) in soils under traditional management (tillage and herbicide) due to the fact that they remain barefor most of the year. The use of straw mulch immediately reduces soil erosion by two orders of magnitude. Also mulchesfrom chipped pruned branches remains are very efficient but require more years to reduce soil loss. Weeds and catchcrops are very efficient in controlling erosion.

scholarly journals Impact of quality on improvement of business performance and customer satisfaction

2021 ◽  
Vol 11 (1) ◽  
pp. 20-28
Author(s):  
Milena Cvjetković ◽  
Marko Vasiljević ◽  
Milovan Cvjetković ◽  
Milica Josimović
Keyword(s):  
Customer Satisfaction ◽  
Growth And Development ◽  
Business Performance ◽  
Consumer Confidence ◽  
Efficient Manner ◽  
Mutual Relations ◽  
High Level ◽  
The Impact

In an immense market struggle, the only effective way to build a long-term competitive advantage is to provide a high level of quality. Offering quality to the market, the organization creates loyal consumers on the basis of which it achieves its profitability, growth and development. The research presented in this paper is aimed at determination of the impact of quality on improving business performance and customer satisfaction. Correlation analysis confirmed this influence on the basis of obtained statistically significant mutual relations between the analyzed variables. Quality was shown to have an impact on improving the business performance of the organization, primarily on profitability through the improvement of leadership and relationship management. The impact of quality on customer satisfaction was also confirmed, where the engagement of people and the management of mutual relations had the greatest impact on consumer confidence. The research confirmed that the training of employees in terms of quality had a statistically significant impact on improving customer satisfaction, if it is conducted in an efficient manner.

scholarly journals Reconciling Flagging Strategies for Multi-Sensor Satellite Soil Moisture Climate Data Records

2020 ◽  
Vol 12 (20) ◽  
pp. 3439
Author(s):  
Mendy van der Vliet ◽  
Robin van der Schalie ◽  
Nemesio Rodriguez-Fernandez ◽  
Andreas Colliander ◽  
Richard de Jeu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
European Space Agency ◽  
Data Availability ◽  
Climate Data ◽  
Mountainous Regions ◽  
Soil Moisture Data ◽  
Climate Records ◽  
The Individual ◽  
The Impact

Reliable soil moisture retrievals from passive microwave satellite sensors are limited during certain conditions, e.g., snow coverage, radio-frequency interference, and dense vegetation. In these cases, the retrievals can be masked using flagging algorithms. Currently available single- and multi-sensor soil moisture products utilize different flagging approaches. However, a clear overview and comparison of these approaches and their impact on soil moisture data are still lacking. For long-term climate records such as the soil moisture products of the European Space Agency (ESA) Climate Change Initiative (CCI), the effect of any flagging inconsistency resulting from combining multiple sensor datasets is not yet understood. Therefore, the first objective of this study is to review the data flagging system that is used within multi-sensor ESA CCI soil moisture products as well as the flagging systems of two other soil moisture datasets from sensors that are also used for the ESA CCI soil moisture products: The level 3 Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active/Passive (SMAP). The SMOS and SMAP soil moisture flagging systems differ substantially in number and type of conditions considered, critical flags, and data source dependencies. The impact on the data availability of the different flagging systems were compared for the SMOS and SMAP soil moisture datasets. Major differences in data availability were observed globally, especially for northern high latitudes, mountainous regions, and equatorial latitudes (up to 37%, 33%, and 32% respectively) with large seasonal variability. These results highlight the importance of a consistent and well-performing approach that is applicable to all individual products used in long-term soil moisture data records. Consequently, the second objective of the present study is to design a consistent and model-independent flagging strategy to improve soil moisture climate records such as the ESA CCI products. As snow cover, ice, and frozen conditions were demonstrated to have the biggest impact on data availability, a uniform satellite driven flagging strategy was designed for these conditions and evaluated against two ground observation networks. The new flagging strategy demonstrated to be a robust flagging alternative when compared to the individual flagging strategies adopted by the SMOS and SMAP soil moisture datasets with a similar performance, but with the applicability to the entire ESA CCI time record without the use of modelled approximations.

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