scholarly journals Coral-reef-derived dimethyl sulfide and the climatic impact of the loss of coral reefs

2021 ◽  
Vol 21 (8) ◽  
pp. 5883-5903
Author(s):  
Sonya L. Fiddes ◽  
Matthew T. Woodhouse ◽  
Todd P. Lane ◽  
Robyn Schofield

Abstract. Dimethyl sulfide (DMS) is a naturally occurring aerosol precursor gas which plays an important role in the global sulfur budget, aerosol formation and climate. While DMS is produced predominantly by phytoplankton, recent observational literature has suggested that corals and their symbionts produce a comparable amount of DMS, which is unaccounted for in models. It has further been hypothesised that the coral reef source of DMS may modulate regional climate. This hypothesis presents a particular concern given the current threat to coral reefs under anthropogenic climate change. In this paper, a global climate model with online chemistry and aerosol is used to explore the influence of coral-reef-derived DMS on atmospheric composition and climate. A simple representation of coral-reef-derived DMS is developed and added to a common DMS surface water climatology, resulting in an additional flux of 0.3 Tg yr−1 S, or 1.7 % of the global sulfur flux from DMS. By comparing the differences between both nudged and free-running ensemble simulations with and without coral-reef-derived DMS, the influence of coral-reef-derived DMS on regional climate is quantified. In the Maritime Continent–Australian region, where the highest density of coral reefs exists, a small decrease in nucleation- and Aitken-mode aerosol number concentration and mass is found when coral reef DMS emissions are removed from the system. However, these small responses are found to have no robust effect on regional climate via direct and indirect aerosol effects. This work emphasises the complexities of the aerosol–climate system, and the limitations of current modelling capabilities are highlighted, in particular surrounding convective responses to changes in aerosol. In conclusion, we find no robust evidence that coral-reef-derived DMS influences global and regional climate.

2020 ◽  
Author(s):  
Sonya L. Fiddes ◽  
Matthew T. Woodhouse ◽  
Todd P. Lane ◽  
Robyn Schofield

Abstract. Dimethyl sulfide (DMS) is a naturally occurring aerosol precursor gas which plays an important role in the global sulfur budget, aerosol formation and climate. While DMS is produced predominantly by phytoplankton, recent observational literature has suggested that corals and their symbionts produce a comparable amount of DMS, which is unaccounted for in models. It has further been hypothesised that the coral reef source of DMS may modulate regional climate. This hypothesis presents a particular concern given the current threat to coral reefs under anthropogenic climate change. In this paper, a global climate model with online chemistry and aerosol is used to explore the influence of coral reef-derived DMS on atmospheric composition and climate. A simple representation of coral reef-derived DMS is developed and added to a common DMS surface water climatology, resulting in an additional DMS flux of 0.3 Tg year−1 S, or 1.7 % of the global flux. By comparing the differences between both nudged and free running ensemble simulations with and without coral reef-derived DMS, the influence of coral reef-derived DMS on regional climate is quantified. In the Maritime Continent-Australian region, where the highest density of coral reefs exist, a small decrease in nucleation and Aitken mode aerosol number concentration and mass is found when coral reef DMS emissions are removed from the system. However, these small responses are found to have no robust effect on regional climate via direct and indirect aerosol effects. This work emphasises the complexities of the aerosol-climate system and the limitations of current modelling capabilities are highlighted, in particular surrounding convective responses to changes in aerosol. In conclusion we find no robust evidence that coral reef-derived DMS influences global and regional climate.


Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 622
Author(s):  
Tugba Ozturk ◽  
F. Sibel Saygili-Araci ◽  
M. Levent Kurnaz

In this study, projected changes in climate extreme indices defined by the Expert Team on Climate Change Detection and Indices were investigated over Middle East and North Africa. Changes in the daily maximum and minimum temperature- and precipitation- based extreme indices were analyzed for the end of the 21st century compared to the reference period 1971–2000 using regional climate model simulations. Regional climate model, RegCM4.4 was used to downscale two different global climate model outputs to 50 km resolution under RCP4.5 and RCP8.5 scenarios. Results generally indicate an intensification of temperature- and precipitation- based extreme indices with increasing radiative forcing. In particular, an increase in annual minimum of daily minimum temperatures is more pronounced over the northern part of Mediterranean Basin and tropics. High increase in warm nights and warm spell duration all over the region with a pronounced increase in tropics are projected for the period of 2071–2100 together with decrease or no change in cold extremes. According to the results, a decrease in total wet-day precipitation and increase in dry spells are expected for the end of the century.


2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.


Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 493 ◽  
Author(s):  
Leonard Druyan ◽  
Matthew Fulakeza

A prequel study showed that dynamic downscaling using a regional climate model (RCM) over Africa improved the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM: ModelE) simulation of June–September rainfall patterns over Africa. The current study applies bias corrections to the lateral and lower boundary data from the AOGCM driving the RCM, based on the comparison of a 30-year simulation to the actual climate. The analysis examines the horizontal pattern of June–September total accumulated precipitation, the time versus latitude evolution of zonal mean West Africa (WA) precipitation (showing monsoon onset timing), and the latitude versus altitude cross-section of zonal winds over WA (showing the African Easterly Jet and the Tropical Easterly Jet). The study shows that correcting for excessively warm AOGCM Atlantic sea-surface temperatures (SSTs) improves the simulation of key features, whereas applying 30-year mean bias corrections to atmospheric variables driving the RCM at the lateral boundaries does not improve the RCM simulations. We suggest that AOGCM climate projections for Africa should benefit from downscaling by nesting an RCM that has demonstrated skill in simulating African climate, driven with bias-corrected SST.


2013 ◽  
Vol 6 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF) model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM) to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.


2012 ◽  
Vol 279 (1740) ◽  
pp. 3098-3105 ◽  
Author(s):  
Alejandro Ruete ◽  
Wei Yang ◽  
Lars Bärring ◽  
Nils Chr. Stenseth ◽  
Tord Snäll

Assessment of future ecosystem risks should account for the relevant uncertainty sources. This means accounting for the joint effects of climate variables and using modelling techniques that allow proper treatment of uncertainties. We investigate the influence of three of the IPCC's scenarios of greenhouse gas emissions (special report on emission scenarios (SRES)) on projections of the future abundance of a bryophyte model species. We also compare the relative importance of uncertainty sources on the population projections. The whole chain global climate model (GCM)—regional climate model—population dynamics model is addressed. The uncertainty depends on both natural- and model-related sources, in particular on GCM uncertainty. Ignoring the uncertainties gives an unwarranted impression of confidence in the results. The most likely population development of the bryophyte Buxbaumia viridis towards the end of this century is negative: even with a low-emission scenario, there is more than a 65 per cent risk for the population to be halved. The conclusion of a population decline is valid for all SRES scenarios investigated. Uncertainties are no longer an obstacle, but a mandatory aspect to include in the viability analysis of populations.


2016 ◽  
Vol 16 (7) ◽  
pp. 1617-1622 ◽  
Author(s):  
Fred Fokko Hattermann ◽  
Shaochun Huang ◽  
Olaf Burghoff ◽  
Peter Hoffmann ◽  
Zbigniew W. Kundzewicz

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood-related losses can be expected in a future warmer climate. However, the general significance of the study was limited by the fact that outcome of only one global climate model (GCM) was used as a large-scale climate driver, while many studies report that GCMs are often the largest source of uncertainty in impact modelling. Here we show that a much broader set of global and regional climate model combinations as climate drivers show trends which are in line with the original results and even give a stronger increase of damages.


Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.


2012 ◽  
Vol 13 (2) ◽  
pp. 443-462 ◽  
Author(s):  
Marco Braun ◽  
Daniel Caya ◽  
Anne Frigon ◽  
Michel Slivitzky

Abstract The effect of a regional climate model’s (RCM’s) internal variability (IV) on climate statistics of annual series of hydrological variables is investigated at the scale of 21 eastern Canada watersheds in Quebec and Labrador. The analysis is carried out on 30-yr pairs of simulations (twins), performed with the Canadian Regional Climate Model (CRCM) for present (reanalysis and global climate model driven) and future (global climate model driven) climates. The twins differ only by the starting date of the regional simulation—a standard procedure used to trigger internal variability in RCMs. Two different domain sizes are considered: one comparable to domains used for RCM simulations over Europe and the other comparable to domains used for North America. Results for the larger North American domain indicate that mean relative differences between twin pairs of 30-yr climates reach ±5% when spectral nudging is used. Larger differences are found for extreme annual events, reaching about ±10% for 10% and 90% quantiles (Q10 and Q90). IV is smaller by about one order of magnitude in the smaller domain. Internal variability is unaffected by the period (past versus future climate) and by the type of driving data (reanalysis versus global climate model simulation) but shows a dependence on watershed size. When spectral nudging is deactivated in the large domain, the relative difference between pairs of 30-yr climate means almost doubles and approaches the magnitude of a global climate model’s internal variability. This IV at the level of the natural climate variability has a profound impact on the interpretation, analysis, and validation of RCM simulations over large domains.


2019 ◽  
Author(s):  
Inne Vanderkelen ◽  
Jakob Zschleischler ◽  
Lukas Gudmundsson ◽  
Klaus Keuler ◽  
Francois Rineau ◽  
...  

Abstract. Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future, preserving the co-variances between variables and the projected changes in variability. Here we present a new experimental design for studying climate change impacts on terrestrial ecosystems and apply it to the UHasselt Ecotron Experiment. The new methodology consists of generating climate forcing along a gradient representative of increasingly high global mean temperature anomalies and uses data derived from the best available regional climate model (RCM) projection. We first identified the best performing regional climate model (RCM) simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European Domain (EURO-CORDEX) ensemble with a 0.11° (12.5 km) resolution based on two criteria: (i) highest skill of the simulations compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. Our results reveal that no single RCM simulation has the best score for all possible combinations of the four meteorological variables and evaluation metrics considered. Out of the six best performing simulations, we selected the simulation with the lowest bias for precipitation (CCLM4-8-17/EC-EARTH), as this variable is key to ecosystem functioning and model simulations deviated the most for this variable, with values ranging up to double the observed values. The time window is subsequently selected from the RCM projection for each ecotron unit based on the global mean temperature of the driving Global Climate Model (GCM). The ecotron units are forced with 3-hourly output from the RCM projections of the five-year period spanning the year in which the global mean temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The gradient approach will allow to identify possible threshold and tipping points.


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