This study presents an analysis of daily temperature and precipitation extremes with return periods ranging from 2 to 50 years in phase 6 of the Coupled Model Intercomparison Project (CMIP6) ...multimodel ensemble of simulations. Judged by similarity with reanalyses, the new-generation models simulate the present-day temperature and precipitation extremes reasonably well. In line with previous CMIP simulations, the new simulations continue to project a large-scale picture of more frequent and more intense hot temperature extremes and precipitation extremes and vanishing cold extremes under continued global warming. Changes in temperature extremes outpace changes in global annual mean surface air temperature (GSAT) over most landmasses, while changes in precipitation extremes follow changes in GSAT globally at roughly the Clausius–Clapeyron rate of ∼7% °C−1. Changes in temperature and precipitation extremes normalized with respect to GSAT do not depend strongly on the choice of forcing scenario or model climate sensitivity, and do not vary strongly over time, but with notable regional variations. Over the majority of land regions, the projected intensity increases and relative frequency increases tend to be larger for more extreme hot temperature and precipitation events than for weaker events. To obtain robust estimates of these changes at local scales, large initial-condition ensemble simulations are needed. Appropriate spatial pooling of data from neighboring grid cells within individual simulations can, to some extent, reduce the needed ensemble size.
Phenylpropanoid biosynthesis in plants engenders a vast variety of aromatic metabolites critically important for their growth, development, and environmental adaptation. Some of these aromatic ...compounds have high economic value. Phenylalanine ammonia-lyase (PAL) is the first committed enzyme in the pathway; it diverts the central flux of carbon from the primary metabolism to the synthesis of myriad phenolics. Over the decades, many studies have shown that exquisite regulatory mechanisms at multiple levels control the transcription and the enzymatic activity of PALs. In this review, a current overview of our understanding of the complicated regulatory mechanisms governing the activity of PAL is presented; recent progress in unraveling its post-translational modifications, its metabolite feedback regulation, and its enzyme organization is highlighted.
Phenylalanine ammonia-lyase (PAL) is the first committed enzyme in phenylpropanoid biosynthesis pathway. It is controlled under a multitude of regulatory mechanisms. In this review, a current overview on our understanding of the complicated regulatory mechanisms governing the activity of PAL is presented.
This paper provides an updated analysis of observed changes in extreme precipitation using high-quality station data up to 2018. We examine changes in extreme precipitation represented by annual ...maxima of 1-day (Rx1day) and 5-day (Rx5day) precipitation accumulations at different spatial scales and attempt to address whether the signal in extreme precipitation has strengthened with several years of additional observations. Extreme precipitation has increased at about two-thirds of stations and the percentage of stations with significantly increasing trends is significantly larger than that can be expected by chance for the globe, continents including Asia, Europe, and North America, and regions including central North America, eastern North America, northern Central America, northern Europe, the Russian Far East, eastern central Asia, and East Asia. The percentage of stations with significantly decreasing trends is not different from that expected by chance. Fitting extreme precipitation to generalized extreme value distributions with global mean surface temperature (GMST) as a covariate reaffirms the statistically significant connections between extreme precipitation and temperature. The global median sensitivity, percentage change in extreme precipitation per 1 K increase in GMST is 6.6% (5.1% to 8.2%; 5%–95% confidence interval) for Rx1day and is slightly smaller at 5.7% (5.0% to 8.0%) for Rx5day. The comparison of results based on observations ending in 2018 with those from data ending in 2000–09 shows a consistent median rate of increase, but a larger percentage of stations with statistically significant increasing trends, indicating an increase in the detectability of extreme precipitation intensification, likely due to the use of longer records.
Linear trend analysis is commonly applied to quantify sea level change, often over short periods because of limited data availability. However, the linear trend computed over short periods is ...complicated by large‐scale climate variability which can affect regional sea level on interannual to inter‐decadal time scales. As a result, the meaning of a local linear sea level trend over the short altimeter era (since 1993; less than 20 years) is unclear, and it is not straightforward to distinguish the regional sea level changes associated with climate change from those associated with natural climate variability. In this study, we use continuous near‐global altimeter measurements since 1993 to attempt to separate interannual and decadal sea level variability in the Pacific from the sea level trend. We conclude that the rapid rates of sea level rise in the western tropical Pacific found from a single variable linear regression analysis are partially due to basin‐scale decadal climate variability. The negligible sea level rise, or even falling sea level, in the eastern tropical Pacific and US west coast is a result of the combination of decreasing of sea level associated with decadal climate variability and a positive sea level trend. The single variable linear regression analysis only accounts for slightly more than 20% of the observed variance, whereas a multiple variable linear regression including filtered indices of the El Nino‐Southern Oscillation and the Pacific Decadal Oscillation accounts for almost 60% of the observed variance.
Key Points
Sea level linear trend over short period is complicated by climate variability
We separate interannual and decadal sea level variability from trend in Pacific
Decadal sea level variability can be erroneously aliased into sea level trend
This paper presents projected changes in temperature and precipitation extremes in China by the end of the twenty-first century based on the Coupled Model Intercomparison Project phase 5 (CMIP5) ...simulations. The temporal changes and their spatial patterns in the Expert Team on Climate Change Detection and Indices (ETCCDI) indices under the RCP4.5 and RCP8.5 emission scenarios are analyzed. Compared to the reference period 1986–2005, substantial changes are projected in temperature and precipitation extremes under both emission scenarios. These changes include a decrease in cold extremes, an increase in warm extremes, and an intensification of precipitation extremes. The intermodel spread in the projection increases with time, with wider spread under RCP8.5 than RCP4.5 for most indices, especially at the subregional scale. The difference in the projected changes under the two RCPs begins to emerge in the 2040s. Analyses based on the mixed-effects analysis of variance (ANOVA) model indicate that by the end of the twenty-first century, at the national scale, the dominant contributor to the projection uncertainty of most temperature-based indices, and some precipitation extremes including maximum 1-day precipitation (RX1day) and maximum 5-day precipitation (RX5day), and total extremely wet day total amount (R95p), is the difference in emission scenarios. By the end of the twenty-first century, model uncertainty is the dominant factor at the regional scale and for the other indices. Natural variability can also play very important role.
The severe 2013/2014 cold winter has been examined in the context of the previous 55 winters using the National Centers for Environmental Prediction reanalysis data for the period 1960–2014. North ...America is dominated by pronounced cold anomalies over the Great Plains and Great Lakes in December 2013 and February 2014 but exhibits an east‐west contrast pattern with warm anomalies over most of the North American West in January 2014. A relevant temperature index, defined as land surface temperature anomalies averaged over (40°–60°N, 105°–80°W), reveals a warming trend as well as interannual variability with a significant power peak of 6.0 years. While 2013/2014 was the second coldest winter during 1960–2014, it is the coldest one in the linearly detrended series, with a negative anomaly of 2.63 standard deviations. This indicates that the long‐term warming has made the 2013/2014 winter less severe than it could have been. The temperature and circulation variability in association with the zonally symmetric variability of the polar vortex projects weakly on the corresponding anomalies in the 2013/2014 winter, whereas the variability associated with the principal mode of North American surface temperature projects strongly on the corresponding anomalies in the winter. This mode is associated with a sea surface temperature (SST) pattern of significant anomalies over the North Pacific and North Atlantic middle and high latitudes. The anomalous atmospheric circulation shows an anticyclonic anomaly over the Gulf of Alaska‐Bering Sea and a cyclonic anomaly downstream over North America. It bears resemblance to the North Pacific Oscillation/Western Pacific pattern and drives the SST in the North Pacific. Over western‐central Canada and the northern U.S., below‐average heights are associated with above‐normal precipitation, implying enhanced upward vertical motion and variation of local cloud forcing, leading to a variation of the surface energy budget dominated by surface longwave radiation anomalies. Over North America, there is less downwelling longwave radiation at the surface when the atmosphere is cold, which is offset by the corresponding reduction in outgoing longwave radiation.
Key Points
The cold winter is consistent with natural climate variability
The cold winter is weakly related to zonally symmetric variability of the polar vortex
The cold anomaly relates to oceanic and atmospheric anomalies in middle and high latitudes
The detection of anthropogenic influences on climate extremes at regional scale is important for the development of national climate change policy. Global climate simulations from phase 5 of the ...Coupled Model Intercomparison Project under the Representative Concentration Pathway 8.5 scenario are used to examine the time at which an anthropogenic influence becomes detectable in extreme precipitation over China and the change in probability of extreme precipitation with certain magnitudes when the changes are detectable. Anthropogenic influence is not significantly detected over China in the observational record or simulations from 1961 to 2012 based on the test of field significance. Simulations indicate that such change would become detectable in the future by around 2035. Large changes would already manifest by the time of signal detection; for example, extreme precipitation events that occur on average once every 20, 50, and 100 years in current (1986–2005) climate would reduce to about 15, 34, and 63 years on average by the time of detection around 2035.
Plain Language Summary
Understanding causes of changes in extreme precipitation can enhance our confidence in future projections of extreme precipitation. The attribution of cause in changes of extreme precipitation is not straightforward at regional scale, due to the presence of strong natural variability in Earth's climate and the lack of long‐term and reliable observational records. This work seeks the anthropogenic signal in extreme precipitation events within the current observational record. It also uses climate models to explore the time at which such a signal would emerge in the future and to assess the associated risks of extreme precipitation events over China. The findings help us to understand the future evolution of Earth's climate and provide useful information for the design and implementation of climate adaptation measures.
Key Points
Significant influence of anthropogenic on extreme precipitation events in China has not yet emerged within the observational record (1961‐2012)
An anthropogenic signal of changes in extreme precipitation events would be detectable by around 2035 under RCP8.5 scenario
Large changes would manifest by the time of signal detection; extreme precipitation events that occur once every 20, 50, and 100 years in the current (1986‐2005) climate will occur once every 15, 34, and 63 years by that time
This study evaluates global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) for their performance in simulating the climate extreme indices defined by the ...Expert Team on Climate Change Detection and Indices (ETCCDI). We compare global climatology patterns of the indices simulated by the CMIP6 models with those from HadEX3 and four reanalysis datasets and the CMIP5 multi-model ensemble using root-mean-square errors for the 1981–2000 period. Regional evaluations are conducted for 41 sub-regions, defined for the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, regional mean biases are analyzed for the 20-year return values (20RV) of the warmest day and coldest night temperatures (TXx and TNn) and annual maximum of daily precipitation (RX1day) using a Generalized Extreme Value (GEV) analysis. Results show that the CMIP6 models generally capture the observed global and regional patterns of temperature extremes with limited improvements compared to the CMIP5 models. Systematic biases like a cold bias in cold extremes over high-latitude regions remain even in stronger amplitudes. The CMIP6 model skills for the precipitation intensity and frequency indices are also largely comparable to those of CMIP5 models, but precipitation intensity simulations are found to be improved with reduced dry biases. The GEV analysis results indicate that the regional biases in 20RV of temperature extremes are dominated by GEV location parameter (related to mean intensity) with relatively small contribution from GEV scale/shape parameters (related to interannual variability). CMIP6-simulated 20RV of RX1day is characterized by dry biases over the tropics and subtropical rain band areas, as in the CMIP5 models, for which biases in both GEV location and scale/shape parameters are important.
Extremes of weather and climate can have devastating effects on human society and the environment. Understanding past changes in the characteristics of such events, including recent increases in the ...intensity of heavy precipitation events over a large part of the Northern Hemisphere land area, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature--and that atmospheric water content is increasing in accord with this theoretical expectation--it has been suggested that human-influenced global warming may be partly responsible for increases in heavy precipitation. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model-model comparisons. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming.
Abstract
Global climate models project the intensification of marine heatwaves in coming decades due to global warming. However, the spatial resolution of these models is inadequate to resolve ...mesoscale processes that dominate variability in boundary current regions where societal and economic impacts of marine heatwaves are substantial. Here we compare the historical and projected changes in marine heatwaves in a 0.1° ocean model with 23 coarser-resolution climate models. Western boundary currents are the regions where the models disagree the most with observations and among themselves in simulating marine heatwaves of the past and the future. The lack of eddy-driven variability in the coarse-resolution models results in less intense marine heatwaves over the historical period and greater intensification in the coming decades. Although the projected changes agree well at the global scale, the greater spatial details around western boundary currents provided by the high-resolution model may be valuable for effective adaptation planning.
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