scholarly journals Forecasting of droughts and tree mortality under global warming: a review of causative mechanisms and modeling methods

2020 ◽  
Vol 11 (3) ◽  
pp. 600-632 ◽  
Author(s):  
Jeongwoo Han ◽  
Vijay P. Singh
Keyword(s):  
Global Warming ◽  
Tree Mortality ◽  
Drought Forecasting ◽  
Temperature Changes ◽  
Mortality Forecasting ◽  
Forecasting Models ◽  
Global Mean Temperature ◽  
Hydraulic Failure ◽  
Global Mean

Abstract Droughts of greater severity are expected to occur more frequently at larger space-time scales under global warming and climate change. Intensified drought and increased rainfall intermittency will heighten tree mortality. To mitigate drought-driven societal and environmental hazards, reliable long-term drought forecasting is critical. This review examines causative mechanisms for drought and tree mortality, and synthesizes stochastic, statistical, dynamical, and hybrid statistical-dynamical drought forecasting models as well as theoretical, empirical, and mechanistic tree mortality forecasting models. Since an increase in global mean temperature changes the strength of sea surface temperature (SST) teleconnections, forecasting models should have the flexibility to incorporate the varying causality of drought. Some of the statistical drought forecasting models, which have nonlinear and nonstationary natures, can be merged with dynamical models to compensate for their lack of stochastic structure in order to improve forecasting skills. Since tree mortality is mainly affected by a hydraulic failure under drought conditions, mechanistic forecasting models, due to their capacity to track the percentage of embolisms against available soil water, are adequate to forecast tree mortality. This study also elucidates approaches to improve long-term drought forecasting and regional tree mortality forecasting as a future outlook for drought studies.

scholarly journals Global warming and world soybean yields

2021 ◽  
Vol 23 (4) ◽  
pp. 367-374
Author(s):  
CAI CHENG-ZHI ◽  
LIAO CONG-JIAN ◽  
XIAO DAN ◽  
ZENG XIAO-SHAN ◽  
ZUO JIN
Keyword(s):  
Global Warming ◽  
Positive Impact ◽  
Arima Model ◽  
Yield Potential ◽  
Average Yield ◽  
Turn Point ◽  
Global Mean Temperature ◽  
Long Term Trend ◽  
Global Mean

The crop yield potential of world soybean from 2019 to 2028 has been projected using ARIMA model based on the yields from 1961 to 2018. Both annual global mean temperature and the yields of world soybean have been projected to rise during the ensuing decade 2019-2028. Projected average yields of world soybean varies from 2841 to 3276 kg ha-1 while 4324 to 4807 kg ha-1 in the case of top (national) yields of world soybean. Annual global mean temperatures may vary from 15.0 to 15.3oC and likely to exert positive impact on average yield (R squared = 0.80) while negative on top yield (R squared = 0.40) of world soybean. It may be concluded that for world soybean yields in 2019 to 2028, the opportunities for improving production should be dependent on both high and low-yielding countries as the yield remained between 30 and 70 per cent of potential limit i.e. in middle place around the turn-point of S-shaped curve in long-term trend partly affected by global warming.

scholarly journals Pacific variability reconciles observed and modelled global mean temperature increase since 1950

2020 ◽  
Author(s):  
Martin B. Stolpe ◽  
Kevin Cowtan ◽  
Iselin Medhaug ◽  
Reto Knutti
Keyword(s):  
Global Warming ◽  
Temperature Change ◽  
Temperature Increase ◽  
Global Temperature ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Pacific ◽  
Global Warming Hiatus ◽  
Warming Hiatus ◽  
Global Mean

Abstract Global mean temperature change simulated by climate models deviates from the observed temperature increase during decadal-scale periods in the past. In particular, warming during the ‘global warming hiatus’ in the early twenty-first century appears overestimated in CMIP5 and CMIP6 multi-model means. We examine the role of equatorial Pacific variability in these divergences since 1950 by comparing 18 studies that quantify the Pacific contribution to the ‘hiatus’ and earlier periods and by investigating the reasons for differing results. During the ‘global warming hiatus’ from 1992 to 2012, the estimated contributions differ by a factor of five, with multiple linear regression approaches generally indicating a smaller contribution of Pacific variability to global temperature than climate model experiments where the simulated tropical Pacific sea surface temperature (SST) or wind stress anomalies are nudged towards observations. These so-called pacemaker experiments suggest that the ‘hiatus’ is fully explained and possibly over-explained by Pacific variability. Most of the spread across the studies can be attributed to two factors: neglecting the forced signal in tropical Pacific SST, which is often the case in multiple regression studies but not in pacemaker experiments, underestimates the Pacific contribution to global temperature change by a factor of two during the ‘hiatus’; the sensitivity with which the global temperature responds to Pacific variability varies by a factor of two between models on a decadal time scale, questioning the robustness of single model pacemaker experiments. Once we have accounted for these factors, the CMIP5 mean warming adjusted for Pacific variability reproduces the observed annual global mean temperature closely, with a correlation coefficient of 0.985 from 1950 to 2018. The CMIP6 ensemble performs less favourably but improves if the models with the highest transient climate response are omitted from the ensemble mean.

Why Is Climate Sensitivity So Unpredictable?

Science ◽  
2007 ◽  
Vol 318 (5850) ◽  
pp. 629-632 ◽  
Author(s):  
Gerard H. Roe ◽  
Marcia B. Baker
Keyword(s):  
Climate Change ◽  
Atmospheric Carbon Dioxide ◽  
Probability Distributions ◽  
Analytic Form ◽  
Future Climate Change ◽  
Large Temperature ◽  
Global Mean Temperature ◽  
Simple Analytic Form ◽  
Global Mean

Uncertainties in projections of future climate change have not lessened substantially in past decades. Both models and observations yield broad probability distributions for long-term increases in global mean temperature expected from the doubling of atmospheric carbon dioxide, with small but finite probabilities of very large increases. We show that the shape of these probability distributions is an inevitable and general consequence of the nature of the climate system, and we derive a simple analytic form for the shape that fits recent published distributions very well. We show that the breadth of the distribution and, in particular, the probability of large temperature increases are relatively insensitive to decreases in uncertainties associated with the underlying climate processes.

scholarly journals Robustness of CMIP6 Historical Global Mean Temperature Simulations: Trends, Long‐Term Persistence, Autocorrelation, and Distributional Shape

2020 ◽  
Vol 8 (10) ◽  
Author(s):  
Simon Michael Papalexiou ◽  
Chandra Rupa Rajulapati ◽  
Martyn P. Clark ◽  
Flavio Lehner
Keyword(s):  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

On the Time of Emergence of Tropical Width Change

2018 ◽  
Vol 31 (18) ◽  
pp. 7225-7236 ◽  
Author(s):  
Xiao-Wei Quan ◽  
Martin P. Hoerling ◽  
Judith Perlwitz ◽  
Henry F. Diaz
Keyword(s):  
Global Warming ◽  
Interannual Variability ◽  
Reanalysis Data ◽  
Natural Variability ◽  
Strong Constraint ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Width Change ◽  
Global Mean ◽  
Emissions Scenario

The tropical belt is expected to expand in response to global warming, although most of the observed tropical widening since 1980, especially in the Northern Hemisphere, is believed to have mainly originated from natural variability. The view is of a small global warming signal relative to natural variability. Here we focus on the question whether and, if so when, the anthropogenic signal of tropical widening will become detectable. Analysis of two large ensemble climate simulations reveals that the forced signal of tropical width is strongly constrained by the forced signal of global mean temperature. Under a representative concentration pathway 8.5 (RCP8.5) emissions scenario, the aggregate of the two models indicates a regression of about 0.5° lat °C−1 during 1980–2080. The models also reveal that interannual variability in tropical width, a measure of noise used herein, is insensitive to global warming. Reanalysis data are therefore used to constrain the interannual variability, whose magnitude is estimated to be 1.1° latitude. Defining the time of emergence (ToE) for tropical width change as the first year (post-1980) when the forced signal exceeds the magnitude of interannual variability, the multimodel simulations of CMIP5 are used to estimate ToE and its confidence interval. The aforementioned strong constraint between the signal of tropical width change and global mean temperature change motivates using CMIP5-simulated global mean temperature changes to infer ToE. Our best estimate for the probable year for ToE, under an RCP8.5 emissions scenario, is 2058 with 10th–90th percentile confidence of 2047–68. Various sources of uncertainty in estimating the ToE are discussed.

scholarly journals Trends in Thailand’s Extreme Temperature Indices during 1955-2018 and Their Relationship with Global Mean Temperature Change

2020 ◽  
pp. 94-107
Author(s):  
Atsamon Limsakul
Keyword(s):  
Global Warming ◽  
Extreme Temperature ◽  
Local Scale ◽  
Maximum Temperature ◽  
Temperature Extremes ◽  
Global Mean Temperature ◽  
Temperature Distributions ◽  
Mean Temperature ◽  
Temperature Indices ◽  
Global Mean

Trends in Thailand’s extreme temperature indices and their relationship with global mean temperature (GMT) change are analyzed, based on longer quality controlled temperature data during 1955–2018. Widespread significant trends of extreme temperature indices with a clear warming evident in all indices are observed, consistent with the earlier results and general global warming. Changes associated with the upper tails of the minimum and maximum temperature distributions are the dominant feature of Thailand’s extreme temperature indices accounting for more than 65% of the total variance. Analysis of the probability distribution functions (PDFs) of combined extreme temperature indices further shows significant shifts in their distributions toward warmer conditions in the recent decades. The results suggest that daytime and nighttime temperatures in Thailand have become more extreme and that the changes are related to shifts in multiple aspects of the daily temperature distributions. With long-term temperature records, this study provides more confident and robust evidence of trends in Thailand’s temperature extremes occurred since the second half of 20th century. Another noteworthy finding is that most of Thailand’s extreme temperature indices show a distinct linear relationship with GMT, indicating that local-scale changes in temperatures and its extreme at local scale are related almost linearly to GMT change. The extrapolated values of the indices with strong linearity with GMT show substantial distinction with nearly 50% increase between 2 global warming levels set by Paris Agreement, highlighting that half a degree increase in GMT will lead to greatly increase in Thailand’s temperature extremes.

Overshooting warming targets – temperature reversibility and implications for impacts, adaptation needs and near-term mitigation

2021 ◽  
Author(s):  
Carl-Friedrich Schleussner ◽  
Quentin Lejeune ◽  
Philippe Ciais ◽  
Thomas Gasser ◽  
Joeri Rogelj ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Global Warming ◽  
Large Scale ◽  
Carbon Dioxide Removal ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Removal Technologies ◽  
Near Term ◽  
The Impact ◽  
Global Mean

<p>Limiting global mean temperature increase to politically agreed temperature limits such as the 1.5°C threshold in the Paris Agreement becomes increasingly challenging. This has given rise to a class of overshoot emissions pathways in the mitigation literature that limit warming to such thresholds only after allowing for a temporary overshoot. However, substantial biogeophysical uncertainties remain regarding the large-scale deployment of Carbon Dioxide Removal technologies required to potentially reverse global warming. Additionally, beyond global mean temperature very little is known about the benefits of declining temperatures on impacts and adaptation needs. Here we will provide an overview of the current state of understanding regarding the reversibility of global warming, as well as impacts and adaptation needs under overshoot pathways.</p><p>We highlight the characteristics of the overshoot scenarios from the literature, and especially those that are compatible with identified sustainability limits for Carbon Dioxide Removal deployment. We will compare those characteristics with uncertainties arising from the Earth System’s response which may complicate the efforts to achieve a decrease in Global Mean Temperature after peak warming is reached. This part will include latest results of the permafrost carbon feedback under stylized overshoot scenarios. Eventually, we will summarise the state-of-the-art knowledge and present new results regarding the impacts of overshoot scenarios for non-linear and time-lagged responses such as sea-level rise, permafrost and glaciers. This will allow for a preliminary assessment of the impact and adaptation benefits of early mitigation compatible with a no or low overshoot pathways.</p>

The Inevitable One

2021 ◽  
pp. 228-248
Author(s):  
Eelco J. Rohling
Keyword(s):  
Thermal Expansion ◽  
Global Warming ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheets ◽  
Ocean Warming ◽  
Global Mean Temperature ◽  
To Come ◽  
Global Mean ◽  
And Sea Level

This chapter considers processes we cannot reverse, at least in the short term: it is already too late. These are processes related to slow responses or feedbacks in the climate system, including ocean warming and sea-level rise, and they will continue to drive change whatever we do. As explained in the chapter, ocean warming operates on timescales of centuries and resulting changes in Earth’s major ice sheets take many centuries to millennia. Sea-level rise is caused by thermal expansion due to ocean warming and by reduction in the volume of land-based ice, due to global warming. Because of the timescales involved, the oceans will keep warming for centuries, dragging global mean temperature along with them, and sea level will also rise for many centuries to come. The chapter reviews the impacts of these processes, whose inevitability means that humanity has no choice but to adapt to them.

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