scholarly journals Long-Term Grass Biomass Estimation of Pastures from Satellite Data

2020 ◽  
Vol 12 (13) ◽  
pp. 2160
Author(s):  
Chiara Clementini ◽  
Andrea Pomente ◽  
Daniele Latini ◽  
Hideki Kanamaru ◽  
Maria Raffaella Vuolo ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Window ◽  
Geographic Location ◽  
Primary Source ◽  
Biomass Estimation ◽  
Climate Projections ◽  
African Region ◽  
Long Time ◽  
Grass Biomass

The general consensus on future climate projections poses new and increased concerns about climate change and its impacts. Droughts are primarily worrying, since they contribute to altering the composition, distribution, and abundance of species. Grasslands, for example, are the primary source for grazing mammals and modifications in climate determine variation in the available yields for cattle. To support the agriculture sector, international organizations such as the Food and Agriculture Organization (FAO) of the United Nations are promoting the development of dedicated monitoring initiatives, with particular attention for undeveloped and disadvantaged countries. The temporal scale is very important in this context, where long time series of data are required to compute consistent analyses. In this research, we discuss the results regarding long-term grass biomass estimation in an extended African region. The results are obtained by means of a procedure that is mostly automatic and replicable in other contexts. Zambia has been identified as a significant test area due to its vulnerability to the adverse impacts of climate change as a result of its geographic location, socioeconomic stresses, and low adaptive capacity. In fact, analysis and estimations were performed over a long time window (21 years) to identify correlations with climate variables, such as precipitation, to clarify sensitivity to climate change and possible effects already in place. From the analysis, decline in both grass quality and quantity was not currently evident in the study area. However, pastures in the considered area were found to be vulnerable to changing climate and, in particular, to the water shortages accompanying drought periods.

scholarly journals Impact of Climate Change on Livestock Returns and Rangeland Ecosystem Sustainability in the Southwest

2018 ◽  
Vol 47 (2) ◽  
pp. 336-356 ◽  
Author(s):  
Gregory L. Torell ◽  
Katherine D. Lee
Keyword(s):  
Climate Change ◽  
Current Method ◽  
Adaptive Methods ◽  
Livestock Grazing ◽  
Climate Projections ◽  
Stocking Rate ◽  
Forage Production ◽  
Temperature And Precipitation ◽  
Stocking Rates

Climate change will increase variability in temperature and precipitation on rangelands, impacting ecosystem services including livestock grazing. Facing uncertainty about future climate, managers must know if current practices will maintain rangeland sustainability. Herein, the future density of an invasive species, broom snakeweed, is estimated using a long-term ecological dataset and climate projections. We find that livestock stocking rates determined using a current method result in lower forage production, allowable stocking rate, and grazing value than an economically efficient stocking rate. Results indicate that using ecology and adaptive methods in management are critical to the sustainability of rangelands.

scholarly journals Water Quality Sustainability Evaluation under Uncertainty: A Multi-Scenario Analysis Based on Bayesian Networks

2019 ◽  
Vol 11 (17) ◽  
pp. 4764 ◽  
Author(s):  
Anna Sperotto ◽  
Josè Luis Molina ◽  
Silvia Torresan ◽  
Andrea Critto ◽  
Manuel Pulido-Velazquez ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Bayesian Networks ◽  
Climate Model ◽  
Future Climate Change ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Large Variability ◽  
Nutrient Loadings

With increasing evidence of climate change affecting the quality of water resources, there is the need to assess the potential impacts of future climate change scenarios on water systems to ensure their long-term sustainability. The study assesses the uncertainty in the hydrological responses of the Zero river basin (northern Italy) generated by the adoption of an ensemble of climate projections from 10 different combinations of a global climate model (GCM)–regional climate model (RCM) under two emission scenarios (representative concentration pathways (RCPs) 4.5 and 8.5). Bayesian networks (BNs) are used to analyze the projected changes in nutrient loadings (NO3, NH4, PO4) in mid- (2041–2070) and long-term (2071–2100) periods with respect to the baseline (1983–2012). BN outputs show good confidence that, across considered scenarios and periods, nutrient loadings will increase, especially during autumn and winter seasons. Most models agree in projecting a high probability of an increase in nutrient loadings with respect to current conditions. In summer and spring, instead, the large variability between different GCM–RCM results makes it impossible to identify a univocal direction of change. Results suggest that adaptive water resource planning should be based on multi-model ensemble approaches as they are particularly useful for narrowing the spectrum of plausible impacts and uncertainties on water resources.

scholarly journals kya jalavaayu parivartan saur badalaav se prabhaavit hota hai?

MAUSAM ◽  
2021 ◽  
Vol 65 (4) ◽  
pp. 585-590
Author(s):  
SUNILKUMAR PESHIN ◽  
DK CHAKRABORTY ◽  
SIDDHARTH SINGH
Keyword(s):  
Climate Change ◽  
Total Ozone ◽  
Total Solar Irradiance ◽  
Solar Flux ◽  
Global Temperature ◽  
Temperature Record ◽  
Slow Increase ◽  
Long Time ◽  
Temperature Records

At present, climate change is a matter of great concern to mankind. This change, which is due to the manmade activities, is changing global temperature and the concentration of CO2 and O3 in the atmosphere. But there are some changes in the sun also. Solar changes could be assessed by solar flux at 10.7cm wavelength. Climate change could be assessed by long time temperature records. In this study we have examined whether solar change has any effect on climate change? We have analyzed two sets of data, 10.7cm solar flux (TSI) and global temperature record, along with total ozone, UV-B flux at ground and satellite data of total solar irradiance. Global temperature anomaly curve (GTAC) shows a slow increase of temperature up to about 1975 and a rapid rise after this year. Solar flux at 10.7cm wavelength shows a decreasing trend up to about 1970 and an increasing trend after this year. It also has 11 year cycle. GTAC, total ozone, UV-flux at ground and TSI also show 11 year cycle and some trend, but none of them matches the long-term trend found in solar flux at 10.7cm wavelength.

scholarly journals Anthropocene and streamflow: Long-term perspective of streamflow variability and water rights

Elem Sci Anth ◽  
2019 ◽  
Vol 7 ◽  
Author(s):  
Pilar Barría ◽  
Maisa Rojas ◽  
Pilar Moraga ◽  
Ariel Muñoz ◽  
Deniz Bozkurt ◽  
...  
Keyword(s):  
Water Allocation ◽  
Time Window ◽  
Water Governance ◽  
Regional Climate ◽  
Water Rights ◽  
Climate Scenario ◽  
Climate Projections ◽  
Ungauged Catchments ◽  
Tree Ring Reconstruction

Since 1981, water allocation in Chile has been based on a water use rights (WURs) market, with limited regulatory and supervisory mechanisms. The volume to be granted as permanent and eventual WURs is calculated from streamflow records, if stream gauge data are available, or from hydrologic parameter transfer from gauged to ungauged catchments, usually with less than 50 years of record. To test the performance of this allocation system, while analyzing the long-term natural variability in water resources, we investigated a 400 year-long (1590–2015) tree-ring reconstruction of runoff and historical water rights for Perquilauquén at Quella catchment, a tributary to the Maule River in Central Chile (35°S–36°30S). Furthermore, we assess how the current legislation would perform under a projected climate scenario, based on historical climate simulations of runoff calibrated against observed data, and future projections. Our analyses indicate that the allocation methodology currently applied by the Water Authority in Chile is very sensitive to the time window of data used, which leads to an underestimation of variability and long-term trends. According to the WURs database provided by the Chilean Water Directorate, WURs at Perquilauquén at Quella are already over-allocated. Considering regional climate projections, this condition will be exacerbated in the future. Furthermore, serious problems regarding the access and quality of information on already-granted WURs and actual water usage have been diagnosed, which further encumber environmental strategies to deal with and adapt to climate change. We emphasize the urgent need for a review and revision of current water allocation methodologies and water law in Chile, which are not concordant with the dynamics and non-stationarity of hydrological processes. Water scarcity and water governance are two of the key issues to be faced by Chile in the Anthropocene.

scholarly journals Potential and Challenges of Harmonizing 40 Years of AVHRR Data: The TIMELINE Experience

2021 ◽  
Vol 13 (18) ◽  
pp. 3618
Author(s):  
Stefan Dech ◽  
Stefanie Holzwarth ◽  
Sarah Asam ◽  
Thorsten Andresen ◽  
Martin Bachmann ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Observation Time ◽  
Sensor Data ◽  
High Temporal Resolution ◽  
Statistical Parameters ◽  
Medium Resolution ◽  
Long Time ◽  
Earth Observation Satellite

Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.

scholarly journals Analysis of Long-Term Measured Exterior Air Temperature in Zilina

2018 ◽  
Vol 14 (2) ◽  
pp. 124-131 ◽  
Author(s):  
Daniela Jurasova
Keyword(s):  
Climate Change ◽  
Temperature Measurement ◽  
Air Temperature ◽  
Weather Data ◽  
Time Data ◽  
Long Time ◽  
Experimental Laboratory ◽  
Weather Stations ◽  
Selection Of

Abstract The climate change assumes nowadays on significance. Weather data may be available on various time scales – long-term, minutes, hours, days, periods, years. Measurements of air temperature are realized for a long time. Data in Slovakia are available from few weather stations of Slovak Hydrometeorological Institute (SHMI). For long-term and wide-ranging measurement of various parameters this can be complicated and expensive. This paper is focused on temperature measurement near the experimental laboratory. Estimation of daily, monthly and yearly mean temperatures is done in different ways. Results from experimental temperature measurement, in a way of selection of unusual extremes are presented. Shorter recording intervals describe the temperature courses in a more pertinent way.

scholarly journals Climate Hazard Assessment for Stakeholder Adaptation Planning in New York City

2011 ◽  
Vol 50 (11) ◽  
pp. 2247-2266 ◽  
Author(s):  
Radley M. Horton ◽  
Vivien Gornitz ◽  
Daniel A. Bader ◽  
Alex C. Ruane ◽  
Richard Goldberg ◽  
...  
Keyword(s):  
Climate Change ◽  
New York ◽  
New York City ◽  
York City ◽  
Extreme Event ◽  
Adaptation Planning ◽  
Climate Projections ◽  
Climate Services ◽  
Heat Events

AbstractThis paper describes a time-sensitive approach to climate change projections that was developed as part of New York City’s climate change adaptation process and that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well versed in risk management, helped to preselect the climate variables most likely to impact urban infrastructure and requested a projection range rather than a single “most likely” outcome. The climate projections approach is transferable to other regions and is consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 GCMs and three emissions scenarios to calculate monthly change factors based on 30-yr average future time slices relative to a 30-yr model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. On the basis of these methods, the current 1-in-10-year coastal flood is projected to occur more than once every 3 years by the end of the century and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme-event frequency are highly uncertain.

scholarly journals Vineyard-specific climate projections help growers manage risk and plan adaptation in the Paso Robles AVA

2022 ◽  
Vol 75 (3) ◽  
pp. 142-150
Author(s):  
Nicholas Babin ◽  
Jazlyn Guerrero ◽  
Diego Rivera ◽  
Ajay Singh
Keyword(s):  
Climate Change ◽  
Climate Adaptation ◽  
Climate Projections ◽  
Wine Grape ◽  
Support Tools ◽  
Plan Adaptation ◽  
The One ◽  
Dry Farming ◽  
Near Future

California's wine grape growers will face increasing challenges under a changing climate as most production occurs near the boundaries of current varieties' climatic thresholds. As part of this study, we developed a method for transforming downscaled climate information from the publicly available Cal-Adapt database into useful and useable climate projections for vineyard managers and advisors in the Paso Robles American Viticultural Area. We shared vineyard-specific projections during interviews of 20 managers and advisors. Overall, interviewees expressed trust in the projections and found them helpful in reducing their psychological distance from climate change. The projections prompted consideration of strategies for managing future climate risk and planning adaptation, with the majority of adaptations associated with long-term decisions such as row orientation, variety selection, dry farming, crop diversification and relocation. Agri-climatic decision support tools such as the one prototyped here may prove especially helpful for incorporating climate adaptation into the long-term business planning and vineyard redevelopment decisions facing managers and advisors in the near future. This approach could be extended to other California wine grape regions or to other perennial crops with expected vulnerabilities to climate change.

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