scholarly journals The impact of global warming on seasonality of ocean primary production

2013 ◽  
Vol 10 (1) ◽  
pp. 1421-1450 ◽  
Author(s):  
S. Henson ◽  
H. Cole ◽  
C. Beaulieu ◽  
A. Yool
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Nitrate Concentration ◽  
Mixed Layer Depth ◽  
Climate Change Impacts ◽  
The Arctic ◽  
Layer Depth ◽  
Biogeochemical Models ◽  
Ocean Productivity ◽  
The Impact

Abstract. The seasonal cycle (i.e. phenology) of oceanic primary production (PP) is expected to change in response to climate warming. Here, we use output from 6 global biogeochemical models to examine the response in the seasonal amplitude of PP and timing of peak PP to the IPCC AR5 warming scenario. We also investigate whether trends in PP phenology may be more rapidly detectable than trends in PP itself. The seasonal amplitude of PP decreases by an average of 1–2% per year by 2100 in most biomes, with the exception of the Arctic which sees an increase of ~1% per year. This is accompanied by an advance in the timing of peak PP by ~0.5–1 months by 2100 over much of the globe, and particularly pronounced in the Arctic. These changes are driven by an increase in seasonal amplitude of sea surface temperature (where the maxima get hotter faster than the minima) and a decrease in the seasonal amplitude of the mixed layer depth and surface nitrate concentration. Our results indicate a transformation of currently strongly seasonal (bloom forming) regions, typically found at high latitudes, into weakly seasonal (non-bloom) regions, characteristic of contemporary subtropical conditions. On average, 36 yr of data are needed to detect a climate change-driven trend in the seasonal amplitude of PP, compared to 32 yr for mean annual PP. We conclude that analysis of phytoplankton phenology is not necessarily a shortcut to detecting climate change impacts on ocean productivity.

scholarly journals The impact of global warming on seasonality of ocean primary production

2013 ◽  
Vol 10 (6) ◽  
pp. 4357-4369 ◽  
Author(s):  
S. Henson ◽  
H. Cole ◽  
C. Beaulieu ◽  
A. Yool
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Mixed Layer Depth ◽  
Climate Change Impacts ◽  
The Arctic ◽  
Biogeochemical Models ◽  
Ocean Productivity ◽  
Phenological Changes ◽  
Resolution Model ◽  
The Impact

Abstract. The seasonal cycle (i.e. phenology) of oceanic primary production (PP) is expected to change in response to climate warming. Here, we use output from 6 global biogeochemical models to examine the response in the seasonal amplitude of PP and timing of peak PP to the IPCC AR5 warming scenario. We also investigate whether trends in PP phenology may be more rapidly detectable than trends in annual mean PP. The seasonal amplitude of PP decreases by an average of 1–2% per year by 2100 in most biomes, with the exception of the Arctic which sees an increase of ~1% per year. This is accompanied by an advance in the timing of peak PP by ~0.5–1 months by 2100 over much of the globe, and particularly pronounced in the Arctic. These changes are driven by an increase in seasonal amplitude of sea surface temperature (where the maxima get hotter faster than the minima) and a decrease in the seasonal amplitude of the mixed layer depth and surface nitrate concentration. Our results indicate a transformation of currently strongly seasonal (bloom forming) regions, typically found at high latitudes, into weakly seasonal (non-bloom) regions, characteristic of contemporary subtropical conditions. On average, 36 yr of data are needed to detect a climate-change-driven trend in the seasonal amplitude of PP, compared to 32 yr for mean annual PP. Monthly resolution model output is found to be inadequate for resolving phenological changes. We conclude that analysis of phytoplankton seasonality is not necessarily a shortcut to detecting climate change impacts on ocean productivity.

scholarly journals Is global warming already changing ocean productivity?

2009 ◽  
Vol 6 (6) ◽  
pp. 10311-10354 ◽  
Author(s):  
S. A. Henson ◽  
J. L. Sarmiento ◽  
J. P. Dunne ◽  
L. Bopp ◽  
I. Lima ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Global Warming ◽  
Primary Production ◽  
Decadal Variability ◽  
Warming Trend ◽  
Natural Variability ◽  
Biogeochemical Models ◽  
Ocean Productivity ◽  
The Impact

Abstract. Global warming is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on the global distribution of ocean productivity comes from satellite ocean colour data. Now that over ten years of SeaWiFS data have accumulated, can we begin to detect and attribute global warming trends in productivity? Here we compare recent trends in SeaWiFS data to longer-term records from three biogeochemical models (GFDL, IPSL and NCAR). We find that detection of real trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global warming. Instead, our analyses suggest that a time series of ~40 yr length is needed to distinguish a global warming trend from natural variability. Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the global warming trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

scholarly journals Regional variability of acidification in the Arctic: a sea of contrasts

2014 ◽  
Vol 11 (2) ◽  
pp. 293-308 ◽  
Author(s):  
E. E. Popova ◽  
A. Yool ◽  
Y. Aksenov ◽  
A. C. Coward ◽  
T. R. Anderson
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Arctic Ocean ◽  
Canadian Arctic ◽  
Atmospheric Co2 ◽  
The Arctic ◽  
Canadian Arctic Archipelago ◽  
Regional Variability ◽  
The Arctic Ocean ◽  
The Impact

Abstract. The Arctic Ocean is a region that is particularly vulnerable to the impact of ocean acidification driven by rising atmospheric CO2, with potentially negative consequences for calcifying organisms such as coccolithophorids and foraminiferans. In this study, we use an ocean-only general circulation model, with embedded biogeochemistry and a comprehensive description of the ocean carbon cycle, to study the response of pH and saturation states of calcite and aragonite to rising atmospheric pCO2 and changing climate in the Arctic Ocean. Particular attention is paid to the strong regional variability within the Arctic, and, for comparison, simulation results are contrasted with those for the global ocean. Simulations were run to year 2099 using the RCP8.5 (an Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) scenario with the highest concentrations of atmospheric CO2). The separate impacts of the direct increase in atmospheric CO2 and indirect effects via impact of climate change (changing temperature, stratification, primary production and freshwater fluxes) were examined by undertaking two simulations, one with the full system and the other in which atmospheric CO2 was prevented from increasing beyond its preindustrial level (year 1860). Results indicate that the impact of climate change, and spatial heterogeneity thereof, plays a strong role in the declines in pH and carbonate saturation (Ω) seen in the Arctic. The central Arctic, Canadian Arctic Archipelago and Baffin Bay show greatest rates of acidification and Ω decline as a result of melting sea ice. In contrast, areas affected by Atlantic inflow including the Greenland Sea and outer shelves of the Barents, Kara and Laptev seas, had minimal decreases in pH and Ω because diminishing ice cover led to greater vertical mixing and primary production. As a consequence, the projected onset of undersaturation in respect to aragonite is highly variable regionally within the Arctic, occurring during the decade of 2000–2010 in the Siberian shelves and Canadian Arctic Archipelago, but as late as the 2080s in the Barents and Norwegian seas. We conclude that, for future projections of acidification and carbonate saturation state in the Arctic, regional variability is significant and needs to be adequately resolved, with particular emphasis on reliable projections of the rates of retreat of the sea ice, which are a major source of uncertainty.

scholarly journals Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity

2010 ◽  
Vol 7 (2) ◽  
pp. 621-640 ◽  
Author(s):  
S. A. Henson ◽  
J. L. Sarmiento ◽  
J. P. Dunne ◽  
L. Bopp ◽  
I. Lima ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Primary Production ◽  
Global Climate Change ◽  
Decadal Variability ◽  
Global Climate ◽  
Warming Trend ◽  
Ocean Colour ◽  
Ocean Productivity ◽  
The Impact

Abstract. Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR). We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ~40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (~20–30 years). Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

A MODELING SYSTEM FOR CLIMATE CHANGE RISK ASSESSMENT, MANAGEMENT AND HEDGING IN COASTAL AREAS

2017 ◽  
Author(s):  
Sergei Soldatenko ◽  
Sergei Soldatenko ◽  
Genrikh Alekseev ◽  
Genrikh Alekseev ◽  
Alexander Danilov ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Coastal Areas ◽  
Mitigation Strategies ◽  
System Structure ◽  
The Arctic ◽  
Risk Modeling ◽  
Wide Range ◽  
Adverse Weather ◽  
The Impact

Every aspect of human operations faces a wide range of risks, some of which can cause serious consequences. By the start of 21st century, mankind has recognized a new class of risks posed by climate change. It is obvious, that the global climate is changing, and will continue to change, in ways that affect the planning and day to day operations of businesses, government agencies and other organizations and institutions. The manifestations of climate change include but not limited to rising sea levels, increasing temperature, flooding, melting polar sea ice, adverse weather events (e.g. heatwaves, drought, and storms) and a rise in related problems (e.g. health and environmental). Assessing and managing climate risks represent one of the most challenging issues of today and for the future. The purpose of the risk modeling system discussed in this paper is to provide a framework and methodology to quantify risks caused by climate change, to facilitate estimates of the impact of climate change on various spheres of human activities and to compare eventual adaptation and risk mitigation strategies. The system integrates both physical climate system and economic models together with knowledge-based subsystem, which can help support proactive risk management. System structure and its main components are considered. Special attention is paid to climate risk assessment, management and hedging in the Arctic coastal areas.

scholarly journals Thirty-Nine-Year Wave Hindcast, Storm Activity, and Probability Analysis of Storm Waves in the Kara Sea, Russia

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 648
Author(s):  
Stanislav Myslenkov ◽  
Vladimir Platonov ◽  
Alexander Kislov ◽  
Ksenia Silvestrova ◽  
Igor Medvedev
Keyword(s):  
Climate Change ◽  
Pareto Distribution ◽  
Linear Trend ◽  
Wind Waves ◽  
Kara Sea ◽  
The Arctic ◽  
Storm Events ◽  
Storm Activity ◽  
Significant Linear Trend ◽  
The Impact

The recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The period 2000–2010 is characterized by significant climate warming, a reduction of the sea ice in the Arctic. The main motivation of this research to assess the impact of climate change on storm activity over the past 39 years in the Kara Sea. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A wave model WAVEWATCH III is used to reconstruct wind wave fields for the period from 1979 to 2017. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. Analysis of the extreme storm events showed that the Pareto distribution is in the best agreement with the data. However, the extreme events with an SWH more than 6‒7 m deviate from the Pareto distribution.

scholarly journals Epidemic malaria and warmer temperatures in recent decades in an East African highland

2010 ◽  
Vol 278 (1712) ◽  
pp. 1661-1669 ◽  
Author(s):  
David Alonso ◽  
Menno J. Bouma ◽  
Mercedes Pascual
Keyword(s):  
Climate Change ◽  
East Africa ◽  
Nonlinear Response ◽  
Climate Change Impacts ◽  
Human Model ◽  
Recent Past ◽  
East African ◽  
Highly Nonlinear ◽  
The Impact

Climate change impacts on malaria are typically assessed with scenarios for the long-term future. Here we focus instead on the recent past (1970–2003) to address whether warmer temperatures have already increased the incidence of malaria in a highland region of East Africa. Our analyses rely on a new coupled mosquito–human model of malaria, which we use to compare projected disease levels with and without the observed temperature trend. Predicted malaria cases exhibit a highly nonlinear response to warming, with a significant increase from the 1970s to the 1990s, although typical epidemic sizes are below those observed. These findings suggest that climate change has already played an important role in the exacerbation of malaria in this region. As the observed changes in malaria are even larger than those predicted by our model, other factors previously suggested to explain all of the increase in malaria may be enhancing the impact of climate change.

Early Holocene ocean conditions off the Zachariæ Isstrøm, Northeast Greenland

2021 ◽  
Author(s):  
Joanna Davies ◽  
Anders Møller Mathiasen ◽  
Kristiane Kristensen ◽  
Christof Pearce ◽  
Marit-Solveig Seidenkrantz
Keyword(s):  
Climate Change ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Atlantic Water ◽  
The Arctic ◽  
Future Climate Change ◽  
Polar Regions ◽  
Ice Shelf ◽  
Outlet Glacier ◽  
The Impact

<p>The polar regions exhibit some of the most visible signs of climate change globally; annual mass loss from the Greenland Ice Sheet (GrIS) has quadrupled in recent decades, from 51 ± 65 Gt yr<sup>−1</sup> (1992-2001) to 211 ± 37 Gt yr<sup>−1</sup> (2002-2011). This can partly be attributed to the widespread retreat and speed-up of marine-terminating glaciers. The Zachariae Isstrøm (ZI) is an outlet glacier of the Northeast Greenland Ice Steam (NEGIS), one of the largest ice streams of the GrIS (700km), draining approximately 12% of the ice sheet interior. Observations show that the ZI began accelerating in 2000, resulting in the collapse of the floating ice shelf between 2002 and 2003. By 2014, the ice shelf extended over an area of 52km<sup>2</sup>, a 95% decrease in area since 2002, where it extended over 1040km<sup>2</sup>. Paleo-reconstructions provide an opportunity to extend observational records in order to understand the oceanic and climatic processes governing the position of the grounding zone of marine terminating glaciers and the extent of floating ice shelves. Such datasets are thus necessary if we are to constrain the impact of future climate change projections on the Arctic cryosphere.</p><p>A multi-proxy approach, involving grain size, geochemical, foraminiferal and sedimentary analysis was applied to marine sediment core DA17-NG-ST8-92G, collected offshore of the ZI, on  the Northeast Greenland Shelf. The aim was to reconstruct changes in the extent of the ZI and the palaeoceanographic conditions throughout the Early to Mid Holocene (c.a. 12,500-5,000 cal. yrs. BP). Evidence from the analysis of these datasets indicates that whilst there has been no grounded ice at the site over the last 12,500 years, the ice shelf of the ZI extended as a floating ice shelf over the site between 12,500 and 9,200 cal. yrs. BP, with the grounding line further inland from our study site. This was followed by a retreat in the ice shelf extent during the Holocene Thermal Maximum; this was likely to have been governed, in part, by basal melting driven by Atlantic Water (AW) recirculated from Svalbard or from the Arctic Ocean. Evidence from benthic foraminifera suggest that there was a shift from the dominance of AW to Polar Water at around 7,500 cal. yrs. BP, although the ice shelf did not expand again despite of this cooling of subsurface waters.</p>

scholarly journals Numerical investigation of the Arctic ice-ocean boundary layer; implications for air-sea gas fluxes

2016 ◽  
Author(s):  
A. Bigdeli ◽  
B. Loose ◽  
S. T. Cole
Keyword(s):  
Sea Ice ◽  
Water Column ◽  
Mixed Layer ◽  
Mixed Layer Depth ◽  
The Arctic ◽  
Layer Depth ◽  
Near Surface ◽  
Resolution Model ◽  
Simplifying Assumptions ◽  
Vertical Spacing

Abstract. In ice-covered regions it can be challenging to determine air-sea exchange – for heat and momentum, but also for gases like carbon dioxide and methane. The harsh environment and relative data scarcity make it difficult to characterize even the physical properties of the ocean surface. Here, we seek a mechanistic interpretation for the rate of air-sea gas exchange (k) derived from radon-deficits. These require an estimate of the water column history extending 30 days prior to sampling. We used coarse resolution (36 km) regional configuration of the MITgcm with fine near surface vertical spacing (2 m) to evaluate the capability of the model to reproduce conditions prior to sampling. The model is used to estimate sea-ice velocity, concentration and mixed-layer depth experienced by the water column. We then compared the model results to existing field data including satellite, moorings and Ice-tethered profilers. We found that model-derived sea-ice coverage is 88 to 98 % accurate averaged over Beaufort Gyre, sea-ice velocities have 78 % correlation which resulted in 2 km/day error in 30 day trajectory of sea-ice. The model demonstrated the capacity to capture the broad trends in the mixed layer although with a bias and model water velocities showed only 29 % correlation with actual data. Overall, we find the course resolution model to be an inadequate surrogate for sparse data, however the simulation results are a slight improvement over several of the simplifying assumptions that are often made when surface ocean geochemistry, including the use of a constant mixed layer depth and a velocity profile that is purely wind-driven.

scholarly journals Desertification in Forest, Range and Desert Landuses of Tehran Province, Under the Impact of Climate Change

2016 ◽  
Author(s):  
Hadi Eskandari Dameneh ◽  
Moslem Borji ◽  
Hassan Khosravi ◽  
Ali Salajeghe
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Net Primary Production ◽  
Degradation Process ◽  
Early Warning Systems ◽  
Land Uses ◽  
Emission Scenarios ◽  
Desert Ecosystems ◽  
Tehran Province ◽  
The Impact

Abstract. Persistence of widespread degradation in arid and semi-arid region of Iran necessitates using of monitoring and evaluation systems with appropriate accuracy to determine the degradation process and adoption of early warning systems; because after transition from some thresholds, effective reversible function of ecosystems will not be very easy. This paper tries to monitor the degradation and desertification trends in three land uses including range, forest and desert lands affected by climate change in Tehran province for 2000s and 2030s. For assessing climate changes of Mehrabad synoptic stations the data of two emission scenarios including A2 and B2 were used using statistical downscaling techniques and data generated by SDSM model. The index of net primary production resulting from MODIS satellite images was employed as an indicator of destruction from 2001 to 2010. The results showed that temperature is the most effective driver force which alters the net primary production in rangeland, forest and desert ecosystems of Tehran province. On the basis of monitoring findings under real conditions, in the 2000s, over 60 % of rangelands and 80 % of the forests have been below the average production in the province. On the other hand, the long-term average changes of NPP in rangeland and forests indicated the presence of relatively large areas of these land uses with production rate lower than the desert. The results also showed that, assuming the existence of circumstances of each emission scenarios, the desertification status will not improve significantly in the rangelands and forests of Tehran province.

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