Spatio-temporal variability of surface chlorophyll and pCO2 over the tropical Indian Ocean and its long-term trend using CMIP6 models

Under the global climate change scenario, ever-increasing ocean temperatures and elevated carbon dioxide (CO2) concentration levels in the ocean and atmosphere significantly affect ocean biogeochemistry. The spatiotemporal distribution of chlorophyll and partial pressure of CO2 (pCO2) over the Indian Ocean (IO) are investigated using satellite, in-situ, and simulations from eleven Coupled Model Inter-comparison Project phase 6 models. All the models show negative bias near the Somali region over the Arabian Sea (AS) during the southwest monsoon season. The CESMs and CanESM5 models show relatively less bias over the tropical IO except for the AS in all seasons compared to other models. The annual cycle of pCO2 shows a bimodal characteristic, with the first peak in May and the other in October over the northern IO, which the CanESM5, IPSL, and MPIs models reasonably well capture. All the models produce the phase of the annual cycle of pCO2 reasonably well for the southern IO. The pCO2 distribution and its trend decomposition are estimated using the multimodel mean from the CanESM5, IPSL-CM6A-LR, and MPIs models, suggesting that the increase in dissolved inorganic carbon is the dominant factor that contributes to about 70 % of the rise in the total pCO2 trend, and the total alkalinity and sea surface temperature have a secondary role. Region-wise analysis manifests that the southern IO and AS exhibit maximum susceptibility to the long-term variations in the pCO2 trend caused by the changes in dissolved inorganic carbon levels in the ocean. The study discusses substantive factors leading to the variability in the biogeochemical properties of the IO as simulated by these models and, thus, the possibilities for future improvements.

Topographic information improves simulated patterns of post-fire conifer regeneration in the southwest United States

The western United States is projected to experience more frequent and severe wildfires in the future due to drier and hotter climate conditions, exacerbating destructive wildfire impacts on forest ecosystems such as tree mortality and unsuccessful post-fire regeneration. While empirical studies have revealed strong relationships between topographical information and plant regeneration, ecological processes in ecosystem models have either not fully addressed topography-mediated effects on the probability of plant regeneration, or the probability is only controlled by climate-related factors, for example, water and light stresses. In this study, we incorporated seedling survival data based on a planting experiment in the footprint of the 2011 Las Conchas Fire into the Photosynthesis and EvapoTranspiration (PnET) extension of the LANDIS-II model by adding topographic and an additional climatic variable to the probability of regeneration. The modified algorithm included topographic parameters such as heat load index and ground slope and spring precipitation. We ran simulations on the Las Conchas Fire landscape for 2012-2099 using observed and projected climate data (i.e., Representative Concentration Pathway 4.5 and 8.5). Our modification significantly reduced the number of regeneration events of three common southwestern conifer tree species (piñon, ponderosa pine, and Douglas-fir), leading to decreases in aboveground biomass, regardless of climate scenario. The modified algorithm decreased regeneration at higher elevations and increased regeneration at lower elevations relative to the original algorithm. Regenerations of three species also decreased in eastern aspects. Our findings suggest that ecosystem models may overestimate post-fire regeneration events in the southwest United States. To better represent regeneration processes following wildfire, ecosystem models need refinement to better account for the range of factors that influence tree seedling establishment. This will improve model utility for projecting the combined effects of climate and wildfire on tree species distributions.

The Ocean Carbon Response to COVID-Related Emissions Reductions

The decline in global emissions of carbon dioxide due to the COVID-19 pandemic provides a unique opportunity to investigate the sensitivity of the global carbon cycle and climate system to emissions reductions. Recent efforts to study the response to these emissions declines has not addressed their impact on the ocean, yet ocean carbon absorption is particularly susceptible to changing atmospheric carbon concentrations. Here, we use ensembles of simulations conducted with an Earth system model to explore the potential detection of COVID-related emissions reductions in the partial pressure difference in carbon dioxide between the surface ocean and overlying atmosphere (ΔpCO2), a quantity that is regularly measured. We find a unique fingerprint in global-scale ΔpCO2 that is attributable to COVID, though the fingerprint is difficult to detect in individual model realizations unless we force the model with a scenario that has four times the observed emissions reduction.

Time of Emergence and Large Ensemble Intercomparison for Ocean Biogeochemical Trends

Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper-ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20-30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.

Climate change is projected to reduce carrying capacity and redistribute species richness in North Pacific pelagic marine ecosystems

Climate change is expected to impact all aspects of marine ecosystems, including fisheries. Here, we use output from a suite of 11 earth system models to examine projected changes in two ecosystem-defining variables: temperature and food availability. In particular, we examine projected changes in epipelagic temperature and, as a proxy for food availability, zooplankton density. We find that under RCP8.5, a high business-as-usual greenhouse gas scenario, increasing temperatures may alter the spatial distribution of tuna and billfish species richness across the North Pacific basin. Furthermore, warmer waters and declining zooplankton densities may act together to lower carrying capacity for commercially valuable fish by 2-5% per decade over the 21st century. These changes have the potential to significantly impact the magnitude, composition, and distribution of commercial fish catch across the pelagic North Pacific. Such changes will in turn ultimately impact commercial fisheries' economic value. Fishery managers should anticipate these climate impacts to ensure sustainable fishery yields and livelihoods.

Timing of the departure of ocean biogeochemical cycles from the preindustrial state

Changes in ocean chemistry and climate induced by anthropogenic CO₂ affect a broad range of ocean biological and biogeochemical processes; these changes are already well underway. Direct effects of CO₂ (e.g. on pH) are prominent among these, but climate model simulations with historical greenhouse gas forcing suggest that physical and biological processes only indirectly forced by CO₂ (via the effect of atmospheric CO₂ on climate) begin to show anthropogenically-induced trends as early as the 1920s. Dates of emergence of a number of representative ocean fields from the envelope of natural variability are calculated for global means and for spatial ‘fingerprints’ over a number of geographic regions. Emergence dates are consistent among these methods and insensitive to the exact choice of regions, but are generally earlier with more spatial information included. Emergence dates calculated for individual sampling stations are more variable and generally later, but means across stations are generally consistent with global emergence dates. The last sign reversal of linear trends calculated for periods of 20 or 30 years also functions as a diagnostic of emergence, and is generally consistent with other measures. The last sign reversal among 20 year trends is found to be a conservative measure (biased towards later emergence), while for 30 year trends it is found to have an early emergence bias, relative to emergence dates calculated by departure from the preindustrial mean. These results are largely independent of emission scenario, but the latest-emerging fields show a response to mitigation. A significant anthropogenic component of ocean variability has been present throughout the modern era of ocean observation.

Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison

Global and regional land carbon storage has been significantly affected by increasing atmospheric CO₂ concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO₂ concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO₂ concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.