scholarly journals Seamless climate change projections and seasonal predictions for bushfires in Australia

2020 ◽  
Vol 70 (1) ◽  
pp. 120
Author(s):  
Andrew J. Dowdy
Keyword(s):  
Climate Change ◽  
Long Range ◽  
Time Scales ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Data Sets ◽  
Fire Weather ◽  
Climate Change Projections ◽  
Different Time Scales

Spatio-temporal variations in fire weather conditions are presented based on various data sets, with consistent approaches applied to help enable seamless services over different time scales. Recent research on this is shown here, covering climate change projections for future years throughout this century, predictions at multi-week to seasonal lead times and historical climate records based on observations. Climate projections are presented based on extreme metrics with results shown for individual seasons. A seasonal prediction system for fire weather conditions is demonstrated here as a new capability development for Australia. To produce a more seamless set of predictions, the data sets are calibrated based on quantile-quantile matching for consistency with observations-based data sets, including to help provide details around extreme values for the model predictions (demonstrating the quantile matching for extremes method). Factors influencing the predictability of conditions are discussed, including pre-existing fuel moisture, large-scale modes of variability, sudden stratospheric warmings and climate trends. The extreme 2019–2020 summer fire season is discussed, with examples provided on how this suite of calibrated fire weather data sets was used, including long-range predictions several months ahead provided to fire agencies. These fire weather data sets are now available in a consistent form covering historical records back to 1950, long-range predictions out to several months ahead and future climate change projections throughout this century. A seamless service across different time scales is intended to enhance long-range planning capabilities and climate adaptation efforts, leading to enhanced resilience and disaster risk reduction in relation to natural hazards.

scholarly journals Climate change and U.S. agriculture: Accounting for multidimensional slope heterogeneity in panel data

2020 ◽  
Vol 11 (4) ◽  
pp. 1391-1429 ◽  
Author(s):  
Michael Keane ◽  
Timothy Neal
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Climate Models ◽  
Crop Yields ◽  
Greenhouse Gas Emission ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Spatial And Temporal Variation ◽  
Local Climate

We study potential impacts of future climate change on U.S. agricultural productivity using county‐level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spatial and temporal variation in the production process mapping weather to crop yields. We present a new panel data estimation technique, called mean observation OLS (MO‐OLS) that allows for spatial and temporal heterogeneity in all regression parameters (intercepts and slopes). Both forms of heterogeneity are important: We find strong evidence that production function parameters adapt to local climate, and also that sensitivity of yield to high temperature declined from 1950–89. We use our estimates to project corn yields to 2100 using 19 climate models and three greenhouse gas emission scenarios. We predict unmitigated climate change will greatly reduce yield. Our mean prediction (over climate models) is that adaptation alone can mitigate 36% of the damage, while emissions reductions consistent with the Paris targets would mitigate 76%.

scholarly journals Potential rice yields in future weather conditions in different parts of Asia.

1990 ◽  
Vol 38 (4) ◽  
pp. 661-680 ◽  
Author(s):  
D.M. Jansen
Keyword(s):  
Climate Change ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Air Humidity ◽  
Physiological Processes ◽  
Rice Yields ◽  
Use Efficiency ◽  
Co2 Level ◽  
Crop Growth Simulation

The effects of future climate change on potential yields of rice cv. IR36 grown at present and in 2020 and 2100 in China, India, Indonesia, Thailand and South Korea were estimated using the crop growth simulation model MACROS which combines the effects of temp., radiation, wind speed, air humidity and crop status on physiological processes. Historic weather data of these sites were adapted to possible changes in temp. and CO2 level, to mimic climate change. Simulated yields rose in low and middle temp. change scenarios, but decreased in the high temp. scenario. Water use efficiency decreased in the high temp. scenario irrespective of CO2 scenario, and increased otherwise. (Abstract retrieved from CAB Abstracts by CABI’s permission)

Time-scale dependence of climate-carbon cycle feedbacks for weak perturbations in CMIP5 models

2021 ◽  
Author(s):  
Guilherme Torres Mendonça ◽  
Julia Pongratz ◽  
Christian Reick
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Time Scales ◽  
Radiative Forcing ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
Ice Age ◽  
Cmip5 Models ◽  
Global Carbon ◽  
Different Time Scales

<p>The increase in atmospheric CO2 driven by anthropogenic emissions is the main radiative forcing causing climate change. But this increase is not only a result from emissions, but also from changes in the global carbon cycle. These changes arise from feedbacks between climate and the carbon cycle that drive CO2 into or out of the atmosphere in addition to the emissions, thereby either accelerating or buffering climate change. Therefore, understanding the contribution of these feedbacks to the global response of the carbon cycle is crucial in advancing climate research. Currently, this contribution is quantified by the α-β-γ framework (Friedlingstein et al., 2003). But this quantification is only valid for a particular perturbation scenario and time period. In contrast, a recently proposed generalization (Rubino et al., 2016) of this framework for weak perturbations quantifies this contribution for all scenarios and at different time scales. </p><p>Thereby, this generalization provides a systematic framework to investigate the response of the global carbon cycle in terms of the climate-carbon cycle feedbacks. In the present work we employ this framework to study these feedbacks and the airborne fraction in different CMIP5 models. We demonstrate (1) that this generalization of the α-β-γ framework consistently describes the linear dynamics of the carbon cycle in the MPI-ESM; and (2) how by this framework the climate-carbon cycle feedbacks and airborne fraction are quantified at different time scales in CMIP5 models. Our analysis shows that, independently of the perturbation scenario, (1) the net climate-carbon cycle feedback is negative at all time scales; (2) the airborne fraction generally decreases for increasing time scales; and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all time scales. This last result therefore emphasizes the need to improve our understanding of this particular feedback.</p><p><strong>References:</strong></p><p>P. Friedlingstein, J.-L. Dufresne, P. Cox, and P. Rayner. How positive is the feedback between climate change and the carbon cycle? Tellus B, 55(2):692–700, 2003.</p><p>M. Rubino, D. Etheridge, C. Trudinger, C. Allison, P. Rayner, I. Enting, R. Mulvaney, L. Steele, R. Langenfelds, W. Sturges, et al. Low atmospheric CO2 levels during the Little Ice Age due to cooling-induced terrestrial uptake. Nature Geoscience, 9(9):691–694, 2016.</p>

scholarly journals Development of a Global Fire Weather Database

2015 ◽  
Vol 15 (6) ◽  
pp. 1407-1423 ◽  
Author(s):  
R. D. Field ◽  
A. C. Spessa ◽  
N. A. Aziz ◽  
A. Camia ◽  
A. Cantin ◽  
...  
Keyword(s):  
Southeast Asia ◽  
Large Scale ◽  
Prediction Models ◽  
Dry Season ◽  
Weather Data ◽  
Data Sets ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Mato Grosso ◽  
Global Database

Abstract. The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5° latitude by 2/3° longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia, Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA-based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DC = 1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRA's precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphere–ocean controls on fire weather, and calibration of FWI-based fire prediction models.

scholarly journals Total organic carbon sensitivity to climate change from Lake Qinghai sediments at different time scales

2019 ◽  
Vol 31 (5) ◽  
pp. 1468-1478
Author(s):  
ZHANG Yao ◽  
◽  
WU Duo ◽  
ZHANG Huan ◽  
ZHOU Aifeng ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Total Organic Carbon ◽  
Time Scales ◽  
Lake Qinghai ◽  
Different Time Scales

scholarly journals An evaluation of the effect of future climate on runoff in the Dongjiang River basin, South China

2015 ◽  
Vol 368 ◽  
pp. 257-262
Author(s):  
K. Lin ◽  
W. Zhai ◽  
S. Huang ◽  
Z. Liu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Annual Runoff ◽  
Future Climate ◽  
Weather Data ◽  
Future Climate Change ◽  
Dongjiang River ◽  
The Future ◽  
The Impact

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.

The future of European floodplain wetlands under a changing climate

2011 ◽  
Vol 2 (2-3) ◽  
pp. 106-122 ◽  
Author(s):  
Christof Schneider ◽  
Martina Flörke ◽  
Gertjan Geerling ◽  
Harm Duel ◽  
Mateusz Grygoruk ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Scale ◽  
Future Climate Change ◽  
Anthropogenic Factors ◽  
Climate Modelling ◽  
Floodplain Wetlands ◽  
Potential Threat ◽  
Climate Change Projections ◽  
The Future ◽  
Floodplain Inundation

In the future, climate change may severely alter flood patterns over large regional scales. Consequently, besides other anthropogenic factors, climate change represents a potential threat to river ecosystems. The aim of this study is to evaluate the effect of climate change on floodplain inundation for important floodplain wetlands in Europe and to place these results in an ecological context. This work is performed within the Water Scenarios for Europe and Neighbouring States (SCENES) project considering three different climate change projections for the 2050s. The global scale hydrological model WaterGAP is applied to simulate current and future river discharges that are then used to: (i) estimate bankfull flow conditions, (ii) determine three different inundation parameters, and (iii) evaluate the hydrological consequences and their relation to ecology. Results of this study indicate that in snow-affected catchments (e.g. in Central and Eastern Europe) inundation may appear earlier in the year. Duration and volume of inundation are expected to decrease. This will lead to a reduction in habitat for fish, vertebrates, water birds and floodplain-specific vegetation causing a loss in biodiversity, floodplain productivity and fish production. Contradictory results occur in Spain, France, Southern England and the Benelux countries. This reflects the uncertainties of current climate modelling for specific seasons.

Sign in / Sign up

Export Citation Format

Share Document