Mars 2018 : Drivers of 2016 record Arctic warmth assessed using climate simulations subjected to Factual and Counterfactual forcing
https://www.sciencedirect.com/science/article/pii/S2212094717301019
Abstract
A suite of historical atmospheric model simulations is described that uses a hierarchy of global boundary forcings designed to inform research on the detection and attribution of weather and climate-related extremes. In addition to experiments forced by actual variations in sea surface temperature, sea ice concentration, and atmospheric chemical composition (so-called Factual experiments); additional (Counterfactual) experiments are conducted in which the boundary forcings are adjusted by removing estimates of long-term climate change. A third suite of experiments are identical to the Factual runs except that sea ice concentrations are set to climatological conditions (Clim-Polar experiments). These were used to investigate the cause for extremely warm Arctic surface temperature during 2016.
Much of the magnitude of surface temperature anomalies averaged poleward of 65°N in 2016 (3.2 ± 0.6 °C above a 1980–89 reference) is shown to have been forced by observed global boundary conditions. The Factual experiments reveal that at least three quarters of the magnitude of 2016 annual mean Arctic warmth was forced, with considerable sensitivity to assumptions of sea ice thickness change. Results also indicate that 30–40% of the overall forced Arctic warming signal in 2016 originated from drivers outside of the Arctic. Despite such remote effects, the experiments reveal that the extreme magnitude of the 2016 Arctic warmth could not have occurred without consideration of the Arctic sea ice loss. We find a near-zero probability for Arctic surface temperature to be as warm as occurred in 2016 under late-19th century boundary conditions, and also under 2016 boundary conditions that do not include the depleted Arctic sea ice. Results from the atmospheric model experiments are reconciled with coupled climate model simulations which lead to a conclusion that about 60% of the 2016 Arctic warmth was likely attributable to human-induced climate change.
Abstract
Rapid intensification (RI) of hurricanes is notoriously difficult to predict and can contribute to severe destruction and loss of life. While past studies examined the frequency of RI occurrence, changes in RI magnitude were not considered. Here we explore changes in RI magnitude over the 30‐year satellite period of 1986–2015. In the central and eastern tropical Atlantic, which includes much of the main development region, the 95th percentile of 24‐hr intensity changes increased at 3.8 knots per decade. In the western tropical Atlantic, encompassing the Caribbean Sea and the Gulf of Mexico, trends are insignificant. Our analysis reveals that warming of the upper ocean coinciding with the positive phase of Atlantic Multidecadal Oscillation, and associated changes in the large‐scale environment, has predominantly favored RI magnitude increases in the central and eastern tropical Atlantic. These results have substantial implications for the eastern Caribbean Islands, some of which were devastated during the 2017 hurricane season.
Le 18 mai 2018 :The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5°C rather than 2°C
http://science.sciencemag.org/content/360/6390/791
Abstract
In the Paris Agreement on Climate Change, the United Nations is pursuing efforts to limit global warming to 1.5°C, whereas earlier aspirations focused on a 2°C limit. With current pledges, corresponding to ~3.2°C warming, climatically determined geographic range losses of >50% are projected in ~49% of insects, 44% of plants, and 26% of vertebrates. At 2°C, this falls to 18% of insects, 16% of plants, and 8% of vertebrates and at 1.5°C, to 6% of insects, 8% of plants, and 4% of vertebrates. When warming is limited to 1.5°C as compared with 2°C, numbers of species projected to lose >50% of their range are reduced by ~66% in insects and by ~50% in plants and vertebrates.
Le 9 mai 2018 : Hurricane Harvey Links to Ocean Heat Content and Climate Change Adaptation
https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018EF000825
Abstract
While hurricanes occur naturally, human‐caused climate change is supercharging them and exacerbating the risk of major damage. Here using ocean and atmosphere observations, we demonstrate links between increased upper ocean heat content due to global warming with the extreme rainfalls from recent hurricanes. Hurricane Harvey provides an excellent case study as it was isolated in space and time. We show that prior to the beginning of northern summer of 2017, ocean heat content was the highest on record both globally and in the Gulf of Mexico, but the latter sharply decreased with hurricane Harvey via ocean evaporative cooling. The lost ocean heat was realized in the atmosphere as moisture, and then as latent heat in record‐breaking heavy rainfalls. Accordingly, record high ocean heat values not only increased the fuel available to sustain and intensify Harvey but also increased its flooding rains on land. Harvey could not have produced so much rain without human‐induced climate change. Results have implications for the role of hurricanes in climate. Proactive planning for the consequences of human‐caused climate change is not happening in many vulnerable areas, making the disasters much worse.
April average sea surface temperatures in the key monitoring regions of the tropical Pacific were cooler than average, but no longer cool enough to meet the threshold for La Niña. The La Niña-driven wind and rainfall anomalies have also subsided. Models are pointing to El Niño developing in fall/winter, but forecast uncertainty is high in the spring. The next update will be June 14.
Polar Science Center
Average Arctic sea ice volume in April 2018 was 22,250 km3. This value is the second lowest on record tied with 2016 and about 1500 km3 above the previous April record that was set in 2017 with 22,600 km3 . Ice volume was 32% below the maximum in 1979 and 19% below the mean value for 1979-2017. April 2018 ice volume sits right on the long term trend line.
https://www.sciencedirect.com/science/article/pii/S2212094717301019
Abstract
A suite of historical atmospheric model simulations is described that uses a hierarchy of global boundary forcings designed to inform research on the detection and attribution of weather and climate-related extremes. In addition to experiments forced by actual variations in sea surface temperature, sea ice concentration, and atmospheric chemical composition (so-called Factual experiments); additional (Counterfactual) experiments are conducted in which the boundary forcings are adjusted by removing estimates of long-term climate change. A third suite of experiments are identical to the Factual runs except that sea ice concentrations are set to climatological conditions (Clim-Polar experiments). These were used to investigate the cause for extremely warm Arctic surface temperature during 2016.
Much of the magnitude of surface temperature anomalies averaged poleward of 65°N in 2016 (3.2 ± 0.6 °C above a 1980–89 reference) is shown to have been forced by observed global boundary conditions. The Factual experiments reveal that at least three quarters of the magnitude of 2016 annual mean Arctic warmth was forced, with considerable sensitivity to assumptions of sea ice thickness change. Results also indicate that 30–40% of the overall forced Arctic warming signal in 2016 originated from drivers outside of the Arctic. Despite such remote effects, the experiments reveal that the extreme magnitude of the 2016 Arctic warmth could not have occurred without consideration of the Arctic sea ice loss. We find a near-zero probability for Arctic surface temperature to be as warm as occurred in 2016 under late-19th century boundary conditions, and also under 2016 boundary conditions that do not include the depleted Arctic sea ice. Results from the atmospheric model experiments are reconciled with coupled climate model simulations which lead to a conclusion that about 60% of the 2016 Arctic warmth was likely attributable to human-induced climate change.
 |
| Fig. 1. (Top) Time series of observed globally averaged annual SST (black curve; °C) and its 1880–2011 linear trend (red curve). (Bottom) Time series of annual Arctic sea ice extent (solid curve; 106 km2) and its 1979–1989 climatology (dashed curve). |
*****
Le 3 mai 2018 : Increasing Magnitude of Hurricane Rapid Intensification in the Central and Eastern Tropical Atlantic
Abstract
Rapid intensification (RI) of hurricanes is notoriously difficult to predict and can contribute to severe destruction and loss of life. While past studies examined the frequency of RI occurrence, changes in RI magnitude were not considered. Here we explore changes in RI magnitude over the 30‐year satellite period of 1986–2015. In the central and eastern tropical Atlantic, which includes much of the main development region, the 95th percentile of 24‐hr intensity changes increased at 3.8 knots per decade. In the western tropical Atlantic, encompassing the Caribbean Sea and the Gulf of Mexico, trends are insignificant. Our analysis reveals that warming of the upper ocean coinciding with the positive phase of Atlantic Multidecadal Oscillation, and associated changes in the large‐scale environment, has predominantly favored RI magnitude increases in the central and eastern tropical Atlantic. These results have substantial implications for the eastern Caribbean Islands, some of which were devastated during the 2017 hurricane season.
 |
| Hurricane track locations where rapid intensification (RI) occurred during (a) 1986–2000 and (b) 2001–2015. RI is defined as an intensity change of 25 knots or higher in 24 hr. Locations with RI magnitude between 25 and 35 knots are shown in green, between 35 and 50 knots are shown in yellow, and greater than 50 knots are shown in red. In panel (b), black stars indicate locations of RI during the 2016 hurricane season. Locations denoted by magenta diamonds are where hurricanes Harvey, Irma, Jose, and Maria underwent RI during the recent 2017 hurricane season. |
*****
Le 18 mai 2018 :The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5°C rather than 2°C
http://science.sciencemag.org/content/360/6390/791
Abstract
In the Paris Agreement on Climate Change, the United Nations is pursuing efforts to limit global warming to 1.5°C, whereas earlier aspirations focused on a 2°C limit. With current pledges, corresponding to ~3.2°C warming, climatically determined geographic range losses of >50% are projected in ~49% of insects, 44% of plants, and 26% of vertebrates. At 2°C, this falls to 18% of insects, 16% of plants, and 8% of vertebrates and at 1.5°C, to 6% of insects, 8% of plants, and 4% of vertebrates. When warming is limited to 1.5°C as compared with 2°C, numbers of species projected to lose >50% of their range are reduced by ~66% in insects and by ~50% in plants and vertebrates.
*****
Le 9 mai 2018 : Hurricane Harvey Links to Ocean Heat Content and Climate Change Adaptation
https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018EF000825
Abstract
While hurricanes occur naturally, human‐caused climate change is supercharging them and exacerbating the risk of major damage. Here using ocean and atmosphere observations, we demonstrate links between increased upper ocean heat content due to global warming with the extreme rainfalls from recent hurricanes. Hurricane Harvey provides an excellent case study as it was isolated in space and time. We show that prior to the beginning of northern summer of 2017, ocean heat content was the highest on record both globally and in the Gulf of Mexico, but the latter sharply decreased with hurricane Harvey via ocean evaporative cooling. The lost ocean heat was realized in the atmosphere as moisture, and then as latent heat in record‐breaking heavy rainfalls. Accordingly, record high ocean heat values not only increased the fuel available to sustain and intensify Harvey but also increased its flooding rains on land. Harvey could not have produced so much rain without human‐induced climate change. Results have implications for the role of hurricanes in climate. Proactive planning for the consequences of human‐caused climate change is not happening in many vulnerable areas, making the disasters much worse.
 |
| Ocean heat content anomalies for the monthly (black) and annual (red) for (a) the top 2,000 m for the global ocean and (b) for the top 160 m in the Gulf of Mexico (dashed box in Figure 2), in 108 J m−2. (c) The sea surface temperature anomalies in the Gulf of Mexico. For all time series, the last month is October 2017 and the last red dot is for January to October 2017. The baseline is 1961–1990. |
 |
Ocean heat content (OHC) and rainfall in the Gulf of Mexico with Harvey. OHC for upper 160 m as departures from the mean for 1961–1990 for (top) 1–20 August, (middle) 1–20 September, and (bottom) 1–20 September to 1–20 August 2017 in 108 J m−2. The tropical cyclone track for Harvey is included. The box indicates the region where the statistics related to the Gulf of Mexico in this study were computed. |
*****
ENSO
Le 29/05/2018 : climate.gov/enso
*****
GISS L-OTI anomalies de températures vs 1951-1980
29/05/2018 : data.giss.nasa.gov
 |
| Note: Gray areas signify missing data. Note: Ocean data are not used over land nor within 100km of a reporting land station. |
*****
Coral Reef Watch
 |
NOAA Coral Reef Watch's most recent Four-Month Coral Bleaching Heat Stress Outlook is below. This figure shows the distribution of the lowest heat stress levels predicted by at least 60% of the model ensemble members. In other words, there is a 60% chance that the displayed heat stress levels will occur.
|
*****
 |
| Global Tropics Benefits / Hazards |
*****
Polar Science Center
29/05/2018 : psc.apl.uw.edu
 |
| Fig.1 Arctic sea ice volume anomaly from PIOMAS updated once a month. Daily Sea Ice volume anomalies for each day are computed relative to the 1979 to 2017 average for that day of the year. Tickmarks on time axis refer to 1st day of year. The trend for the period 1979- present is shown in blue. Shaded areas show one and two standard deviations from the trend. Error bars indicate the uncertainty of the monthly anomaly plotted once per year. |
 |
| Fig. 2 Total Arctic sea ice volume from PIOMAS showing the volume of the mean annual cycle, and from 2010-2018. Shaded areas indicate one and two standard deviations from the mean. |
 |
| Fig.3 Monthly Sea Ice Volume from PIOMAS for April and Sep |
 |
| Fig 8 Comparison of Daily Sea Ice Volume anomalies relative to 1979-2016. |
*****
Arctic Data archive system (ADS)
29/05/2018 : ads.nipr.ac.jp
 |
| Arctic sea ice extent. |
 |
| Antarctic sea ice extent. |
*****
C'est si vrai, en riant avec What on earth? comics !
 |
| Il parait que 2018 s'annonce prometteuse en matière de cyclones, qui vivra verra (et tant pis pour les morts) |
 |
| Donald Trump, niveau 6 sur l'échelle de Saffir-Simpson. |
 |
| Une solution comme une autre. |
 |
| En France remplacer Pruitt par, au choix : Rittaud, Bardinet, Gervais, Allègre, Courtillot, etc. |
Aucun commentaire:
Enregistrer un commentaire