The shifting of climate types: manifestation to phenology and ecosystems structure

2021 ◽  
Author(s):  
Gunta Kalvāne ◽  
Andis Kalvāns ◽  
Agrita Briede ◽  
Ilmārs Krampis ◽  
Dārta Kaupe ◽  
...  
Keyword(s):  
Climate Change ◽  
Breaking Point ◽  
Data Sets ◽  
Precipitation Regime ◽  
Climate Type ◽  
Data Set ◽  
Temperature And Precipitation ◽  
Spatial Changes ◽  
Temporal And Spatial ◽  
The Impact

<p>According to the Köppen climate classification, almost the entire area of Latvia belongs to the same climate type, Dfb, which is characterized by humid continental climates with warm (sometimes hot) summers and cold winters.  In the last decades whether conditions on the western coast of Latvia more characterized by temperate maritime climates. In this area there has been a transition (and still ongoing) to the climate type Cfb.</p><p>Temporal and spatial changes of temperature and precipitation regime have been examined in whole territory to identify the breaking point of climate type shifts. We used two type of climatological data sets: gridded daily temperature from the E-OBS data set version 21.0e (Cornes et al., 2018) and direct observations from meteorological stations (data source: Latvian Environment, Geology and Meteorology Centre). The temperature and precipitation regime have changed significantly in the last century - seasonal and regional differences can be observed in the territory of Latvia.</p><p>We have digitized and analysed more than 47 thousand phenological records, fixed by volunteers in period 1970-2018. Study has shown that significant seasonal changes have taken place across the Latvian landscape due to climate change (Kalvāne and Kalvāns, 2021). The largest changes have been recorded for the unfolding (BBCH11) and flowering (BBCH61) phase of plants – almost 90% of the data included in the database demonstrate a negative trend. The winter of 1988/1989 may be considered as breaking point, it has been common that many phases have begun sooner (particularly spring phases), while abiotic autumn phases have been characterized by late years.</p><p>Study gives an overview aboutclimate change (also climate type shift) impacts on ecosystems in Latvia, particularly to forest and semi-natural grasslands and temporal and spatial changes of vegetation structure and distribution areas.</p><p>This study was carried out within the framework of the Impact of Climate Change on Phytophenological Phases and Related Risks in the Baltic Region (No. 1.1.1.2/VIAA/2/18/265) ERDF project and the Climate change and sustainable use of natural resources institutional research grant of the University of Latvia (No. AAP2016/B041//ZD2016/AZ03).</p><p>Cornes, R. C., van der Schrier, G., van den Besselaar, E. J. M. and Jones, P. D.: An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets, J. Geophys. Res. Atmos., 123(17), 9391–9409, doi:10.1029/2017JD028200, 2018.</p><p>Kalvāne, G. and Kalvāns, A.(2021): Phenological trends of multi-taxonomic groups in Latvia, 1970-2018, Int. J. Biometeorol., doi:https://doi.org/10.1007/s00484-020-02068-8, 2021.</p>

scholarly journals Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yahya Albalawi ◽  
Jim Buckley ◽  
Nikola S. Nikolov
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Comprehensive Evaluation ◽  
Classification Problem ◽  
Data Sets ◽  
Word Embeddings ◽  
Data Set ◽  
Lower Accuracy ◽  
Health Related ◽  
The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

scholarly journals Response of altitudinal vegetation belts of the Tianshan Mountains in northwestern China to climate change during 1989–2015

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Zhang ◽  
Lu-yu Liu ◽  
Yi Liu ◽  
Man Zhang ◽  
Cheng-bang An
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Global Climate ◽  
Animal Husbandry ◽  
Forest Tree ◽  
Tianshan Mountains ◽  
Northwestern China ◽  
Temperature And Precipitation ◽  
Altitudinal Belts ◽  
The Impact

AbstractWithin the mountain altitudinal vegetation belts, the shift of forest tree lines and subalpine steppe belts to high altitudes constitutes an obvious response to global climate change. However, whether or not similar changes occur in steppe belts (low altitude) and nival belts in different areas within mountain systems remain undetermined. It is also unknown if these, responses to climate change are consistent. Here, using Landsat remote sensing images from 1989 to 2015, we obtained the spatial distribution of altitudinal vegetation belts in different periods of the Tianshan Mountains in Northwestern China. We suggest that the responses from different altitudinal vegetation belts to global climate change are different. The changes in the vegetation belts at low altitudes are spatially different. In high-altitude regions (higher than the forest belts), however, the trend of different altitudinal belts is consistent. Specifically, we focused on analyses of the impact of changes in temperature and precipitation on the nival belts, desert steppe belts, and montane steppe belts. The results demonstrated that the temperature in the study area exhibited an increasing trend, and is the main factor of altitudinal vegetation belts change in the Tianshan Mountains. In the context of a significant increase in temperature, the upper limit of the montane steppe in the eastern and central parts will shift to lower altitudes, which may limit the development of local animal husbandry. The montane steppe in the west, however, exhibits the opposite trend, which may augment the carrying capacity of pastures and promote the development of local animal husbandry. The lower limit of the nival belt will further increase in all studied areas, which may lead to an increase in surface runoff in the central and western regions.

scholarly journals The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

2015 ◽  
Vol 8 (1) ◽  
pp. 421-434 ◽  
Author(s):  
M. P. Jensen ◽  
T. Toto ◽  
D. Troyan ◽  
P. E. Ciesielski ◽  
D. Holdridge ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Data Sets ◽  
Central Plains ◽  
Data Set ◽  
Convective Systems ◽  
Convective Clouds ◽  
Quality Checks ◽  
Network Operations ◽  
The Impact

Abstract. The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentation used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.

scholarly journals Validation of the HIRHAM-Simulated Indian Summer Monsoon Circulation

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Stefan Polanski ◽  
Annette Rinke ◽  
Klaus Dethloff
Keyword(s):  
Summer Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Monsoon Circulation ◽  
Data Sets ◽  
Data Set ◽  
Topographic Features ◽  
Temperature And Precipitation ◽  
Simulated Precipitation

The regional climate model HIRHAM has been applied over the Asian continent to simulate the Indian monsoon circulation under present-day conditions. The model is driven at the lateral and lower boundaries by European reanalysis (ERA40) data for the period from 1958 to 2001. Simulations with a horizontal resolution of 50 km are carried out to analyze the regional monsoon patterns. The focus in this paper is on the validation of the long-term summer monsoon climatology and its variability concerning circulation, temperature, and precipitation. Additionally, the monsoonal behavior in simulations for wet and dry years has been investigated and compared against several observational data sets. The results successfully reproduce the observations due to a realistic reproduction of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded precipitation data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40.

Improving SAR Altimeter processing over the coastal zone and inland waters - the ESA HYDROCOASTAL project

2021 ◽  
Author(s):  
David Cotton ◽  
Keyword(s):  
Coastal Zone ◽  
Test Data ◽  
River Discharge ◽  
Altimeter Data ◽  
Inland Waters ◽  
Data Sets ◽  
Data Set ◽  
Discharge Data ◽  
Processing Algorithms ◽  
The Impact

<p><strong>Introduction</strong></p><p>HYDROCOASTAL is a two year project funded by ESA, with the objective to maximise exploitation of SAR and SARin altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process SAR and SARin data from CryoSat-2, and SAR altimeter data from Sentinel-3A and Sentinel-3B. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products.</p><p>New SAR and SARin processing algorithms for the coastal zone and inland waters will be developed and implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme will be implemented to generate global coastal zone and river discharge data sets.</p><p>A series of case studies will assess these products in terms of their scientific impacts.</p><p>All the produced data sets will be available on request to external researchers, and full descriptions of the processing algorithms will be provided</p><p> </p><p><strong>Objectives</strong></p><p>The scientific objectives of HYDROCOASTAL are to enhance our understanding  of interactions between the inland water and coastal zone, between the coastal zone and the open ocean, and the small scale processes that govern these interactions. Also the project aims to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea-level changes</p><p>The technical objectives are to develop and evaluate  new SAR  and SARin altimetry processing techniques in support of the scientific objectives, including stack processing, and filtering, and retracking. Also an improved Wet Troposphere Correction will be developed and evaluated.</p><p><strong>Project  Outline</strong></p><p>There are four tasks to the project</p><ul><li>Scientific Review and Requirements Consolidation: Review the current state of the art in SAR and SARin altimeter data processing as applied to the coastal zone and to inland waters</li> <li>Implementation and Validation: New processing algorithms with be implemented to generate a Test Data sets, which will be validated against models, in-situ data, and other satellite data sets. Selected algorithms will then be used to generate global coastal zone and river discharge data sets</li> <li>Impacts Assessment: The impact of these global products will be assess in a series of Case Studies</li> <li>Outreach and Roadmap: Outreach material will be prepared and distributed to engage with the wider scientific community and provide recommendations for development of future missions and future research.</li> </ul><p> </p><p><strong>Presentation</strong></p><p>The presentation will provide an overview to the project, present the different SAR altimeter processing algorithms that are being evaluated in the first phase of the project, and early results from the evaluation of the initial test data set.</p><p> </p>

scholarly journals Characteristics of Climate Change and Extreme Weather from 1951 to 2011 in China

2018 ◽  
Vol 15 (11) ◽  
pp. 2540 ◽  
Author(s):  
Chunli Zhao ◽  
Jianguo Chen ◽  
Peng Du ◽  
Hongyong Yuan
Keyword(s):  
Climate Change ◽  
Spatial Scale ◽  
Spatial Scales ◽  
Seasonal Fluctuation ◽  
Extreme Weather ◽  
Temperature And Precipitation ◽  
Weather Variation ◽  
Variation Characteristics ◽  
Established Fact ◽  
Temporal And Spatial

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.

scholarly journals Environmental Change Threatens Freshwater Insect Communities in Northwest Africa: A Meta-Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Nils Kaczmarek ◽  
Ralf B. Schäfer ◽  
Elisabeth Berger
Keyword(s):  
Climate Change ◽  
Water Temperature ◽  
Negative Binomial ◽  
Small Body ◽  
Future Research ◽  
Insect Communities ◽  
Data Set ◽  
Temperature Conductivity ◽  
Northwest Africa ◽  
The Impact

A climatic shift from temperate to arid conditions is predicted for Northwest Africa. Water temperature, salinity, and river intermittency are likely to increase, which may impact freshwater communities, ecosystem functioning, and related ecosystem services. Quantitative data and information on the impact of climate change on insect communities (e.g., richness, taxonomic and trait composition) are still scarce for Northwest Africa. In this study, we extracted information on freshwater insect occurrence and environmental variables in Northwest Africa from the results of a literature search to study potential consequences of changing climatic conditions for these communities. Our data set covered 96 families in 165 sites in Morocco and Algeria. We quantified the impact of several explanatoryvariables (climate, altitude, water temperature, conductivity, intermittency, flow, aridity, dams, and land cover) on richness, taxonomic and functional trait composition using negative binomial regression models and constrained ordination. Family richness in arid sites was on average 37 % lower than in temperate sites in association with flow, river regulation, cropland extent, conductivity, altitude, and water temperature. With 36 % of the studied temperate sites predicted to turn arid by the end of the century, a loss of insect families can be predicted for Northwest Africa, mainly affecting species adapted to temperate environments. Resistance and resilience traits such as small body size, aerial dispersal, and air breathing promote survival in arid climates. Future research should report insect occurrences on species level to allow for better predictions on climate change effects.

scholarly journals Six years of total ozone column measurements from SCIAMACHY nadir observations

2009 ◽  
Vol 2 (1) ◽  
pp. 87-98 ◽  
Author(s):  
C. Lerot ◽  
M. Van Roozendael ◽  
J. van Geffen ◽  
J. van Gent ◽  
C. Fayt ◽  
...  
Keyword(s):  
Cross Sections ◽  
Total Ozone ◽  
Large Scale ◽  
European Space Agency ◽  
Data Sets ◽  
Data Set ◽  
Ozone Data ◽  
Space Agency ◽  
German Aerospace ◽  
The Impact

Abstract. Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone data sets are found to agree within 2% on average. However, a negative trend of 0.2–0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.

scholarly journals Numerical simulations of the impact of climate variability and change on semiarid watershed response in central New Mexico

2009 ◽  
Vol 6 (1) ◽  
pp. 319-371
Author(s):  
E. R. Vivoni ◽  
C. A. Aragón ◽  
L. Malczynski ◽  
V. C. Tidwell
Keyword(s):  
Climate Change ◽  
New Mexico ◽  
Summer Precipitation ◽  
Climate Change Scenarios ◽  
Hydrologic Response ◽  
Watershed Model ◽  
Precipitation Regime ◽  
Hydrologic Processes ◽  
Precipitation Characteristics ◽  
The Impact

Abstract. Hydrologic processes in the semiarid regions of the southwest United States are considered to be highly susceptible to variations in temperature and precipitation characteristics due to the effects of climate change. Relatively little is known on the potential impacts of climate change on the basin hydrologic response, namely streamflow, evapotranspiration and recharge, in the region. In this study, we present the development and application of a continuous, semi-distributed watershed model for climate change studies in semiarid basins of the southwest US. Our objective is to capture hydrologic processes in large watersheds, while accounting for the spatial and temporal variations of climate forcing and basin properties in a simple fashion. We apply the model to the Río Salado basin in central New Mexico since it exhibits both a winter and summer precipitation regime and has a historical streamflow record for model testing purposes. Subsequently, we utilize a sequence of climate change scenarios that capture observed trends for winter and summer precipitation, as well as their interaction with higher temperatures, to perform long-term ensemble simulations of the basin hydrologic response. Results of the modeling exercise indicate that precipitation uncertainty is amplified in the hydrologic response, in particular for processes that depend on a soil saturation threshold. We obtained substantially different hydrologic sensitivities for winter and summer precipitation ensembles, indicating a greater sensitivity to more intense summer storms as compared to more frequent winter events. In addition, the impact of changes in precipitation characteristics overwhelmed the effects of increased temperature in the study basin. Nevertheless, combined trends in precipitation and temperature yield a more sensitive hydrologic response throughout the year.

Evaluating Infill Well Performance and Fracture Driven Interactions Using Intervention Based Distributed Fiber Optics

2021 ◽  
Author(s):  
Ahmed Attia ◽  
Matthew Lawrence
Keyword(s):  
Fiber Optics ◽  
Fracture Network ◽  
Data Sets ◽  
Well Performance ◽  
Design Strategies ◽  
Data Set ◽  
Geological Features ◽  
Production Output ◽  
Long Carbon Fiber ◽  
The Impact

Abstract Distributed Fiber Optics (DFO) technology has been the new face for unconventional well diagnostics. This technology focuses on measuring Distributed Acoustic Sensing (DAS) and Distrusted Temperature Sensing (DTS) to give an in-depth understanding of well productivity pre and post stimulation. Many different completion design strategies, both on surface and downhole, are used to obtain the best fracture network outcome; however, with complex geological features, different fracture designs, and fracture driven interactions (FDIs) effecting nearby wells, it is difficult to grasp a full understanding on completion design performance for each well. Validating completion designs and improving on the learnings found in each data set should be the foundation in developing each field. Capturing a data set with strong evidence of what works and what doesn't, can help the operator make better engineering decisions to make more efficient wells as well as help gauge the spacing between each well. The focus of this paper will be on a few case studies in the Bakken which vividly show how infill wells greatly interfered with production output. A DFO deployed with a 0.6" OD, 23,000-foot-long carbon fiber rod to acquire DAS and DTS for post frac flow, completion, and interference evaluation. This paper will dive into the DFO measurements taken post frac to further explain what effects are seen on completion designs caused by interferences with infill wells; the learnings taken from the DFO post frac were applied to further escalate the understanding and awareness of how infill wells will preform on future pad sites. A showcase of three separate data sets from the Bakken will identify how effective DFO technology can be in evaluating and making informed decisions on future frac completions. In this paper we will also show and discuss how DFO can measure real time FDI events and what measures can be taken to lessen the impact on negative interference caused by infill wells.

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