lundi 22 janvier 2018

Climactualités - janvier 2018

Actualité climatique du mois passé dans laquelle j'entrepose pêle-mêle les articles que j'ai trouvés intéressants (mais j'ai pu, et dû, en louper un certain nombre) ; comme je n'ai pas toute la journée à dédier à la tenue de ce blog je me dispenserai de traduire les articles en français, à chacun donc de se débrouiller avec la langue de Shakespeare en fonction de ses capacités (il y a au demeurant des outils de traduction en ligne assez performants...)

Comme je ne ferai aucun commentaire (sauf pour les dessins humoristiques), me contentant de reprendre quelques extraits ou graphiques des articles en question, les lecteurs qui m'accuseraient de cherry-picking verraient leur prose automatiquement envoyée à la poubelle sans forcément une explication de ma part ; je donnerai à chaque fois les liens donc toute personne n'ayant pas de poil dans la main sera capable d'aller consulter les sources dans leur totalité.


Le 22 décembre 2017 : Asylum applications respond to temperature fluctuations

International negotiations on climate change, along with recent upsurges in migration across the Mediterranean Sea, have highlighted the need to better understand the possible effects of climate change on human migration—in particular, across national borders. Here we examine how, in the recent past (2000–2014), weather variations in 103 source countries translated into asylum applications to the European Union, which averaged 351,000 per year in our sample. We find that temperatures that deviated from the moderate optimum (~20°C) increased asylum applications in a nonlinear fashion, which implies an accelerated increase under continued future warming. Holding everything else constant, asylum applications by the end of the century are predicted to increase, on average, by 28% (98,000 additional asylum applications per year) under representative concentration pathway (RCP) scenario 4.5 and by 188% (660,000 additional applications per year) under RCP 8.5 for the 21 climate models in the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP).


Le 12 janvier 2018 : The influence of internal variability on Earth's energy balance framework and implications for estimating climate sensitivity

Our climate is constrained by the balance between solar energy absorbed by the Earth and terrestrial energy radiated to space. This energy balance has been widely used to infer equilibrium climate sensitivity (ECS) from observations of 20th-century warming. Such estimates yield lower values than other methods and these have been influential in pushing down the consensus ECS range in recent assessments. Here we test the method using a 100-member ensemble of the MPI-ESM1.1 climate model simulations of the period 1850–2005 with known forcing. We calculate ECS in each ensemble member using energy balance, yielding values ranging from 2.1 to 3.9 K. The spread in the ensemble is related to the central hypothesis in the energy budget framework: that global average surface temperature anomalies are indicative of anomalies in outgoing energy (either of terrestrial origin or reflected solar energy). We find that assumption is not well supported over the historical temperature record in the model ensemble or more recent satellite observations. We find that framing energy balance in terms of 500-hPa tropical temperature better describes the planet's energy balance.


Le 17 janvier 2018 : Emergent constraint on equilibrium climate sensitivity from global temperature variability

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5–4.5 degrees Celsius for more than 25 years1. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2–3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship2 between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming3, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.


17/01/2018 :
Forecasters believe the ongoing weak-to-moderate La Niña is currently peaking and will weaken into the spring. The strength of an event isn't strongly linked to the strength of the impacts in the U.S., but strength does increase the likelihood that at least some level of the typical impacts will be felt. The next update will be on February 8.
Visualisation du phénomène ENSO sur le Pacifique Est en décembre 2017.


GISS L-OTI anomalies de températures vs 1951-1980
22/01/2018 :
Note: Gray areas signify missing data.
Note: Ocean data are not used over land nor within 100km of a reporting land station.
Note: Gray areas signify missing data.
Note: Ocean data are not used over land nor within 100km of a reporting land station.
Anomalies de températures de l'année 2017 selon la latitude.


Data Snapshots
22/01/2018 :
Average surface temperature in 2016 compared to the 1981-2010 average. NOAA map, adapted from Plate 2.1a in State of the Climate in 2016.
History of global surface temperature since 1880 ; source noaa
Atmospheric carbon dioxide concentrations in parts per million (ppm) for the past 800,000 years, based on EPICA (ice core) data. The peaks and valleys in carbon dioxide levels track the coming and going of ice ages (low carbon dioxide) and warmer interglacials (higher levels). Throughout these cycles, atmospheric carbon dioxide  was never higher than 300 ppm; in 2016, it reached 402.9 ppm (black dot). NOAA, based on EPICA Dome C data (Lüthi, D., et al., 2008) provided by NOAA NCEI Paleoclimatology Program.
Carbon dioxide concentrations. The bright red line (source data) shows monthly average carbon dioxide at NOAA's Mauna Loa Observatory on Hawai'i in parts per million (ppm): the number of carbon dioxide molecules per million molecules of dry air.  Over the course of the year, values are higher in Northern Hemisphere winter and lower in summer. The dark red line shows the annual trend, calculated as a 12-month rolling average.
(left vertical axis) The heating imbalance in watts per square meter relative to the year 1750 caused by all major human-produced greenhouse gases: carbon dioxide, methane, nitrous oxide, chlorofluorocarbons 11 and 12, and a group of 15 other minor contributors. Today's atmosphere absorbs about 3 extra watts of incoming solar energy over each square meter of Earth's surface. According to NOAA's Annual Greenhouse Gas Index (right axis) the combined heating influence of all major greenhouse gases has increased by 40% relative to 1990. NOAA graph, based on data from NOAA ESRL. 
This graph (source data) shows average area covered by snow in the Northern Hemisphere during March and April as the difference from the 1981-2010 average.
This graph shows monthly values of the Oceanic Niño Index from 1950 through present.
Location of the Niño regions for measuring sea surface temperature in the eastern and central tropical Pacific Ocean. The sea surface temperature in the Niño3.4 region, spanning from 120˚W to 170˚W longitude, when averaged over a 3-month period, forms NOAA’s official Oceanic Niño Index (the ONI). NOAA image by Fiona Martin.
Maps of sea surface temperature anomaly in the Pacific Ocean during a strong La Niña (top, December 1988) and El Niño (bottom, December 1997). Maps by NOAA, based on data provided by NOAA View. large versions La Niña | El Niño
The graph shows the average of a set of temperature simulations for the 20th century (black line), followed by projected temperatures for the 21st century based on a range of emissions scenarios (colored lines). The shaded areas around each line indicate the statistical spread (one standard deviation) provided by individual model runs. (Data processing by Jay Hnilo, CICS-NC, using data courtesy the Coupled Model Intercomparison Project, or CMIP3.)


Coral Reef Watch
This figure shows the regions currently experiencing high levels of heat stress that can cause coral bleaching.
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.

NOAA Coral Reef Watch's satellite Coral Bleaching Alert Area below shows the maximum heat stress during the Third Global Coral Bleaching Event. Regions that experienced the high heat stress that can cause coral bleaching, from June 1, 2014 to May 31, 2017, are displayed. Alert Level 2 heat stress indicates widespread coral bleaching and significant mortality. Alert Level 1 heat stress indicates significant coral bleaching. Lower levels of stress may have caused some bleaching as well. More than 70% of coral reefs around the world experienced the heat stress that can cause bleaching and/or mortality during the three-year long global event.


Climate Prediction Center
22/01/2018 :
Global Tropics Benefits/Hazards 
Last Updated: 01.16.18 Valid: 01.17.18 - 01.30.18
During the next two weeks, the current MJO signal is forecast to continue its eastward propagation. La Nina, the low frequency state, is expected to remain entrenched in the central and eastern Pacific. For Week-1, the RMM-index shows movement into Phase 4 for the MJO, moving the enhanced convective region over the Maritime Continent. The forecast shows deterioration in the amplitude of the signal over the next week and into the beginning of Week-2. This is most likely due to expected Rossby wave activity in the Pacific. Model guidance reflects this solution, though the GFS model forecasts a larger decay to the signal than the European model. Despite the weakening, eastward propagation into Phase 5 is expected for the MJO signal. The convective envelope of the MJO is likely to destructively interfere with the base state as it moves into the western Pacific. This is reflected in the shift of forecasted precipitation patterns for the Pacific from Week-1 to Week2.

Tropical cyclone activity is expected to continue in the South Indian basin during the next two weeks. Currently, the western South Indian Ocean is experiencing Tropical Cyclone Berguitta, which formed on 11 January. There is moderate confidence that this region will remain active in Week-1. The Kimberley Coast is also highlighted for possible tropical cyclone activity for Week-1, as the MJO enhanced convective envelope moves further east over the Maritime Continent. For Week-2, there is moderate confidence for tropical cyclone formation for the northern coast of Australia, near Darwin. This again falls in the enhanced convective region expected for the Phase 4 and 5 MJO signal. Model guidance shows a possibility for tropical cyclone formation in the South Pacific in Week-2, though confidence is low at this time.

Week-1 precipitation patterns follow a typical MJO Phase 4 pattern with effects from tropical cyclone activity. A swath of above-average rainfall is likely in the central South Indian Ocean, which has been an active region for tropical cyclone formation in the new year. There are regions of high confidence in the eastern South Indian Ocean, near the northern Australian coast and Java and north near the Philippines, which are forecast to receive above-average rainfall. This rainfall anomaly is supported by the dynamical model guidance and a Phase 4 MJO footprint. The below-average rains region typical of La Nina activity is reinforced by suppressed convection associated with MJO in Phase 4. The forecast for below-average rainfall in Brazil is also supported by both dynamical and statistical guidance. There is moderate confidence that the above-normal temperatures that plagued eastern Australia in the previous week are expected to return toward the end of Week-1.

For Week-2, the MJO is expected to move into Phase 5, propagating the convective envelope further east, toward the western Pacific. Regions over the Maritime Continent are expected to continue to experience above-average rains as the parts of the enhanced convective envelope will still remain over these regions. This solution is supported by the dynamical model guidance, though not as robust as the statistical guidance, resulting in moderate confidence. The area of persistent below-average rainfall in the tropical Pacific is likely to shift eastward, as the MJO convective signal moves into the western Pacific. An area of above-average precipitation north of this persistent dry region in the Pacific is expected, which is typical of a Phase 5 MJO event, as well as the La Nina base state. As the region of the enhanced convection moves east, an area of below-average is forecast for the central Indian Ocean. Model guidance and statistical tools are in agreement for this solution; however, with the current tropical cyclone activity in the South Indian basin, this forecast is only moderate confidence. The dry region for Week-1 in Brazil is likely to continue with below-average rainfall into Week-2. Model guidance was in disagreement for this region, though a Phase 5 MJO event has a strong dry signal in this region.

Forecasts over Africa are made in consultation with CPCs international desk, and can represent local-scale conditions in addition to global-scale variability.


Polar Science Center
22/01/2018 :
Average Arctic sea ice volume in October 2017 was 6100 km3 a 1100 km3  above the record of 2012 ( 5000 km3) and almost the same as  2010.  October 2017 volume was 65% below the maximum October ice volume in 1979,  50% below the 1979-2016 mean, and very close to the long term trend line.   While 2017 started well below prior years and remained so through May,  ice loss during June through October was less than previous years with July and August accounting for most of the “catch up”. This is shown in Fig 8 which compares daily ice volume anomalies for several recent years (base period 1979-2016). The difference between 2012 (the previous record) is notable. While 2017 started out with much lower sea ice volume, 2012 had a much more rapid sea ice loss through May and June. Both 2012 and 2017 have very similar anomaly progression through July. August and September 2017 by comparison was a months of reprieve relative to 2012.
Average ice thickness in October 2017 over the PIOMAS  domain increase a bit relative to September and is  10 cm above to the lowest on record (Fig 4.).   Note that the interpretation of average ice thickness needs to take into account that only areas with ice thickness greater than 15 cm are included so that years with less total volume can have a greater ice thickness. That’s why the average ice thickness can increase late in the year as thin regrown sea ice is added into the average.
Fig 8 Comparison of Daily Sea Ice Volume Anomalies relative to 1979-2016.
Fig 4.Average Arctic sea ice thickness over the ice-covered regions from PIOMAS for a selection of years. The average thickness is calculated for the PIOMAS domain by only including locations where ice is thicker than .15 m.
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 2016 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 2010-2017. Shaded areas indicate one and two standard deviations from the mean.
Fig.3 Monthly Sea Ice Volume from PIOMAS for April and Sep.
Fig 6. PIOMAS Ice Thickness Anomaly for October 2017 relative to 2000-2015.

Arctic Data archive system (ADS)
22/01/2018 :
Arctic sea ice extent.
Antarctic sea ice extent.

C'est si vrai, en riant avec What on earth? comics !

Le comité de rédaction du Wall Street Journal fait ses choix :
- En voici un de 229 scientifiques qui appellent à réduire les émissions de CO2.
Celui-ci est de 16 scientifiques. Il dit que le réchauffement climatique est un mensonge communiste.
C'est sur papier à en-tête d'Exxon Mobil. Chouette !
Ne nous aplatissons pas devant la majorité scientifique.

En arrière toutes ! (traduction libre)

C'est vrai quoi, assez de fake news comme ça !
The Trump administration has prohibited the CDC from saying "fetus" and "evidence-based" among other words ( ). The Environmental PROTECTION Agency is tearing up environmental regulations at an unprecedented pace ( ), and hired an oppo research firm to dig for dirt on the EPA's own staff ( ). Please tell me our country's current slide into Third World Dictatorship is only a bad dream.

2 commentaires:

  1. Ça semble super tout ça ....
    Mais je préfère la langue de Molière à celle de Shakespeare :)

    1. Désolé Daneel, mais traduire c'est du boulot, même avec les outils en ligne car il faut tout vérifier et se relire plusieurs fois afin d'éviter les faux-amis, les mots simplement mal traduits (choix d'un synonyme inapproprié par exemple) ainsi que les tournures de phrase alambiquées, quand ce n'est pas parfois l'oubli incompréhensible d'une partie du texte !

      Seule solution : se (re)mettre à l'anglais ;)