Geomorphic feedbacks on the moraine record

2020 ◽  
Author(s):  
Leif Anderson ◽  
Dirk Scherler
Keyword(s):  
Climate Change ◽  
Numerical Modeling ◽  
Global Scale ◽  
Past Climate ◽  
Mountain Ranges ◽  
Mountain Glaciers ◽  
Term Evolution ◽  
Debris Cover ◽  
Mountain Landscapes

<p>Glacial moraines represent one of the most spatially diverse climate archives on earth. Moraine dating and numerical modeling are used to effectively reconstruct past climate from mountain ranges at the global scale. But because moraines are often located downvalley from steep mountain headwalls, it is possible that debris-covered glaciers emplaced many moraines preserved in the landscape today.</p><p>Before we can understand the effect of debris cover on the moraine recored we need to understand how debris modulates glacier response to climate change. To help address this need, we developed a numerical model that links feedbacks between mountain glaciers, climate change, hillslope erosion, and landscape evolution. Our model uses parameters meant to represent glaciers in the Khumbu region of Nepal, though the model physics are relevant for mountain glaciers elsewhere.</p><p>We compare simulated debris-covered and debris-free glaciers and their length evolution. We explore the effect of climate-dependent hillslope erosion. We also allow temperature change to control frost cracking and permafrost in the headwall above simulated glaciers. Including these effects holds special implications for glacial evolution during deglaciation and the long-term evolution of mountain landscapes.</p><p>Because debris cover suppresses melt, debris-covered glaciers can advance independent of climate change. When debris cover is present during cold periods, moraine emplacement can lag debris-free glacier moraine emplacement by hundreds of years. We develop a suite of tools to help determine whether individual moraines were formed by debris-covered glaciers. Our analyses also point to how we might interpret moraine ages and estimate past climate states from debris-perturbed settings.</p>

scholarly journals Shared socioeconomic pathways for climate change research in Finland: co-developing extended SSP narratives for agriculture

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Heikki S. Lehtonen ◽  
Jyrki Aakkula ◽  
Stefan Fronzek ◽  
Janne Helin ◽  
Mikael Hildén ◽  
...  
Keyword(s):  
Climate Change ◽  
National Level ◽  
Global Scale ◽  
Change Scenario ◽  
Policy Makers ◽  
Climate Change Research ◽  
Food And Agriculture ◽  
Agriculture And Food ◽  
Farm Subsidies

AbstractShared socioeconomic pathways (SSPs), developed at global scale, comprise narrative descriptions and quantifications of future world developments that are intended for climate change scenario analysis. However, their extension to national and regional scales can be challenging. Here, we present SSP narratives co-developed with stakeholders for the agriculture and food sector in Finland. These are derived from intensive discussions at a workshop attended by approximately 39 participants offering a range of sectoral perspectives. Using general background descriptions of the SSPs for Europe, facilitated discussions were held in parallel for each of four SSPs reflecting very different contexts for the development of the sector up to 2050 and beyond. Discussions focused on five themes from the perspectives of consumers, producers and policy-makers, included a joint final session and allowed for post-workshop feedback. Results reflect careful sector-based, national-level interpretations of the global SSPs from which we have constructed consensus narratives. Our results also show important critical remarks and minority viewpoints. Interesting features of the Finnish narratives compared to the global SSP narratives include greater emphasis on environmental quality; significant land abandonment in SSPs with reduced livestock production and increased plant-based diets; continued need for some farm subsidies across all SSPs and opportunities for diversifying domestic production under scenarios of restricted trade. Our results can contribute to the development of more detailed national long-term scenarios for food and agriculture that are both relevant for local stakeholders and researchers as well as being consistent with global scenarios being applied internationally.

scholarly journals Soil salinization under different climate change scenarios: A global scale analysis

2021 ◽  
Author(s):  
Nima Shokri ◽  
Amirhossein Hassani ◽  
Adisa Azapagic
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Soil Salinity ◽  
Global Scale ◽  
Soil Salinization ◽  
Water Evaporation ◽  
Climate Change Scenarios ◽  
Spatio Temporal ◽  
Salt Affected Soils

<p>Population growth and climate change is projected to increase the pressure on land and water resources, especially in arid and semi-arid regions. This pressure is expected to affect all driving mechanisms of soil salinization comprising alteration in soil hydrological balance, sea salt intrusion, wet/dry deposition of wind-born saline aerosols — leading to an increase in soil salinity. Soil salinity influences soil stability, bio-diversity, ecosystem functioning and soil water evaporation (1). It can be a long-term threat to agricultural activities and food security. To devise sustainable action plan investments and policy interventions, it is crucial to know when and where salt-affected soils occur. However, current estimates on spatio-temporal variability of salt-affected soils are majorly localized and future projections in response to climate change are rare. Using Machine Learning (ML) algorithms, we related the available measured soil salinity values (represented by electrical conductivity of the saturated paste soil extract, EC<sub>e</sub>) to some environmental information (or predictors including outputs of Global Circulation Models, soil, crop, topographic, climatic, vegetative, and landscape properties of the sampling locations) to develop a set of data-driven predictive tools to enable the spatio-temporal predictions of soil salinity. The outputs of these tools helped us to estimate the extent and severity of the soil salinity under current and future climatic patterns at different geographical levels and identify the salinization hotspots by the end of the 21<sup>st</sup> century in response to climate change. Our analysis suggests that a soil area of 11.73 Mkm<sup>2</sup> located in non-frigid zones has been salt-affected in at least three-fourths of the 1980 - 2018 period (2). At the country level, Brazil, Peru, Sudan, Colombia, and Namibia were estimated to have the highest rates of annual increase in the total area of soils with an EC<sub>e</sub> ≥ 4 dS m<sup>-1</sup>. Additionally, the results indicate that by the end of the 21<sup>st</sup> century, drylands of South America, southern and Western Australia, Mexico, southwest United States, and South Africa will be the salinization hotspots (compared to the 1961 - 1990 period). The results of this study could inform decision-making and contribute to attaining the United Nation’s Sustainable Development Goals for land and water resources management.</p><p>1. Shokri-Kuehni, S.M.S., Raaijmakers, B., Kurz, T., Or, D., Helmig, R., Shokri, N. (2020). Water Table Depth and Soil Salinization: From Pore-Scale Processes to Field-Scale Responses. Water Resour. Res., 56, e2019WR026707. https://doi.org/ 10.1029/2019WR026707</p><p>2. Hassani, A., Azapagic, A., Shokri, N. (2020). Predicting Long-term Dynamics of Soil Salinity and Sodicity on a Global Scale, Proc. Nat. Acad. Sci., 117, 52, 33017–33027. https://doi.org/10.1073/pnas.2013771117</p>

Global long-term land surface temperature for NOAA AVHRR: extension from 1981-2000 to 1981-2020

2021 ◽  
Author(s):  
Jin Ma ◽  
Ji Zhou
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Global Scale ◽  
Mean Bias Error ◽  
Bias Error ◽  
Important Indicator ◽  
Noaa Avhrr

<p>As an important indicator of land-atmosphere energy interaction, land surface temperature (LST) plays an important role in the research of climate change, hydrology, and various land surface processes. Compared with traditional ground-based observation, satellite remote sensing provides the possibility to retrieve LST more efficiently over a global scale. Since the lack of global LST before, Ma et al., (2020) released a global 0.05 ×0.05  long-term (1981-2000) LST based on NOAA-7/9/11/14 AVHRR. The dataset includes three layers: (1) instantaneous LST, a product generated based on an ensemble of several split-window algorithms with a random forest (RF-SWA); (2) orbital-drift-corrected (ODC) LST, a drift-corrected version of RF-SWA LST at 14:30 solar time; and (3) monthly averages of ODC LST. To meet the requirement of the long-term application, e.g. climate change, the period of the LST is extended from 1981-2000 to 1981-2020 in this study. The LST from 2001 to 2020 are retrieved from NOAA-16/18/19 AVHRR with the same algorithm for NOAA-7/8/11/14 AVHRR. The train and test results based on the simulation data from SeeBor and TIGR atmospheric profiles show that the accuracy of the RF-SWA method for the three sensors is consistent with the previous four sensors, i.e. the mean bias error and standard deviation less than 0.10 K and 1.10 K, respectively, under the assumption that the maximum emissivity and water vapor content uncertainties are 0.04 and 1.0 g/cm<sup>2</sup>, respectively. The preliminary validation against <em>in-situ</em> LST also shows a similar accuracy, indicating that the accuracy of LST from 1981 to 2020 are consistent with each other. In the generation code, the new LST has been improved in terms of land surface emissivity estimation, identification of cloud pixel, and the ODC method in order to generate a more reliable LST dataset. Up to now, the new version LST product (1981-2020) is under generating and will be released soon in support of the scientific research community.</p>

Non-linear, long-term evolution of sea surface temperature across the World Ocean

2020 ◽  
Author(s):  
Benjamin Martinez-Lopez
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
World Ocean ◽  
Sea Surface ◽  
Second Derivative ◽  
Term Evolution ◽  
The World ◽  
Non Linear

<p>Sea surface temperature (SST) is the only oceanic parameter on which depend heat fluxes between ocean and atmosphere and, therefore, SST is one of the key factors that influence climate and its variability. Over the twentieth century, SSTs have significantly increased around the global ocean, warming that has been attributed to anthropogenic climate change, although it is not yet clear how much of it is related to natural causes and how much is due to human activities. A considerable part of available literature regarding climate change has been built based on the global or hemispheric analysis of surface temperature trends. There are, however, some key open questions that need to be answered and for this task estimates of long-term SST trend patterns represent a source of valuable information. Unfortunately, long-term SST trend patterns have large uncertainties and although SST constitutes one of the most-measured ocean variables of our historic records, their poor spatial and temporal sampling, as well as inhomogeneous measurements technics, hinder an accurate determination of long-term SST trends, which increases their uncertainty and, therefore, limit their physical interpretation as well as their use in the verification of climate simulations.<br>Most of the long-term SST trend patterns have been built using linear techniques, which are very usefull when they are used to extract information of measurements satisfying two key assumptions: linearity and stationarity. The global warming resulting of our economic activities, however, affect the state of the World Ocean and the atmosphere inducing changes in the climate that may result in oscillatory modes of variability of different frequencies, which may undergo non-stationary and non-linear evolutions. In this work, we construct long-term SST trend patterns by using non-linear techniques to extract non-linear, long-term trends in each grid-point of two available global SST datasets: the National Oceanic and Atmospheric Administration Extended Reconstructed SST (ERSST) and from the Hadley Centre sea ice and SST (HadISST). The used non-linear technique makes a good job even if the SST data are non-linear and non-stationary. Additionally, the nonlinearity of the extracted trends allows the use of the first and second derivative to get more information about the global, long-term evolution of the SST fields, favoring thus a deeper understanding and interpretation of the observed changes in SST. Particularly, our results clearly show, in both ERSST and HadISST datasets, the non-uniform warming observed in the tropical Pacific, which seems to be related to the enhanced vertical heat flux in the eastern equatorial Pacific and the strengthening of the warm pool in the western Pacific. By using the second derivative of the nonlinear SST trends, emerges an interesting pattern delimiting several zones in the Pacific Ocean which have been responded in a different way to the impose warming of the last century.</p>

scholarly journals Not all biodiversity rich spots are climate refugia

2021 ◽  
Vol 18 (24) ◽  
pp. 6567-6578
Author(s):  
Ádám T. Kocsis ◽  
Qianshuo Zhao ◽  
Mark J. Costello ◽  
Wolfgang Kiessling
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Global Scale ◽  
Absolute Temperature ◽  
Elevated Risk ◽  
Anthropogenic Climate Change ◽  
Range Shifts ◽  
Future Warming ◽  
Almost All

Abstract. Anthropogenic climate change is increasingly threatening biodiversity on a global scale. Rich spots of biodiversity, regions with exceptionally high endemism and/or number of species, are a top priority for nature conservation. Terrestrial studies have hypothesized that rich spots occur in places where long-term climate change was dampened relative to other regions. Here we tested whether biodiversity rich spots are likely to provide refugia for organisms during anthropogenic climate change. We assessed the spatial distribution of both historic (absolute temperature change and climate change velocities) and projected climate change in terrestrial, freshwater, and marine rich spots. Our analyses confirm the general consensus that global warming will impact almost all rich spots of all three realms and suggest that their characteristic biota is expected to witness similar forcing to other areas, including range shifts and elevated risk of extinction. Marine rich spots seem to be particularly sensitive to global warming: they have warmed more, have higher climate velocities, and are projected to experience higher future warming than non-rich-spot areas. However, our results also suggest that terrestrial and freshwater rich spots will be somewhat less affected than other areas. These findings emphasize the urgency of protecting a comprehensive and representative network of biodiversity-rich areas that accommodate species range shifts under climate change.

scholarly journals Climate change and outbreaks of amphibian chytridiomycosis in a montane area of Central Spain; is there a link?

2006 ◽  
Vol 274 (1607) ◽  
pp. 253-260 ◽  
Author(s):  
Jaime Bosch ◽  
Luís M Carrascal ◽  
Luis Durán ◽  
Susan Walker ◽  
Matthew C Fisher
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Batrachochytrium Dendrobatidis ◽  
Global Scale ◽  
Amphibian Species ◽  
The North ◽  
Natural Park ◽  
Circulation Patterns ◽  
The North Atlantic Oscillation

Amphibian species are declining at an alarming rate on a global scale in large part owing to an infectious disease caused by the chytridiomycete fungus, Batrachochytrium dendrobatidis . This disease of amphibians has recently emerged within Europe, but knowledge of its effects on amphibian assemblages remains poor. Importantly, little is known about the environmental envelope that is associated with chytridiomycosis in Europe and the potential for climate change to drive future disease dynamics. Here, we use long-term observations on amphibian population dynamics in the Peñalara Natural Park, Spain, to investigate the link between climate change and chytridiomycosis. Our analysis shows a significant association between change in local climatic variables and the occurrence of chytridiomycosis within this region. Specifically, we show that rising temperature is linked to the occurrence of chytrid-related disease, consistent with the chytrid-thermal-optimum hypothesis. We show that these local variables are driven by general circulation patterns, principally the North Atlantic Oscillation. Given that B. dendrobatidis is known to be broadly distributed across Europe, there is now an urgent need to assess the generality of our finding and determine whether climate-driven epidemics may be expected to impact on amphibian species across the wider region.

A new method of PWV retrieval over land with remote sensing data: a case of AMSR2

2020 ◽  
Author(s):  
Nan Jiang ◽  
Yan Xu ◽  
Tianhe Xu
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Global Climate ◽  
Weather Prediction ◽  
Remote Sensing Data ◽  
Precipitable Water ◽  
Global Scale ◽  
Brightness Temperatures ◽  
Climate Studies

<p>Precipitable water vapor (PWV) is an important parameter reflecting the amount of solid water in the atmosphere, which is widely utilized in the studies of numerical weather prediction (NWP) and climate change. The microwave radiance measurements made by the space-based remote sensing satellites give us the opportunity to make the climate studies on a global scale. So far, PWV retrieval over the ocean has a long data record and the technology is very mature, but in the case of PWV retrieval over land, it is more challenging to isolate the atmospheric signals from the varied surface signals. In this study, we will apply a new retrieval method over land based on the dual-polarized difference (vertical and horizontal) at 19 GHz and 23 GHz using the brightness temperatures from the Global Change Observation Mission-Water (GCOM-W)/Advanced Microwave Scanning Radiometer 2 (AMSR2). We found polarization difference in brightness temperatures has an exponential relation on the amount of PWV. The validation results of the PWV retrieval from the ground-based GNSS stations show that the proposed method has a mean accuracy of 3.9 mm. Thus, the proposed method can give a possibility to improve the accuracy of data assimilation in the NWP applications and is useful for the studies of global climate change with the long-term data records.</p>

scholarly journals Multi-Temporal Variabilities of Evapotranspiration Rates and Their Associations with Climate Change and Vegetation Greening in the Gan River Basin, China

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2568 ◽  
Author(s):  
Meng Bai ◽  
Bing Shen ◽  
Xiaoyu Song ◽  
Shuhong Mo ◽  
Lingmei Huang ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Human Activities ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Long Term Evolution ◽  
Interactive Effects ◽  
Positive Effects ◽  
Term Evolution

Understanding the spatial-temporal dynamics of evapotranspiration in relation to climate change and human activities is crucial for the sustainability of water resources and ecosystem security, especially in regions strongly influenced by human impact. In this study, a process-based evapotranspiration (ET) model in conjunction with the Global Land Surface Satellite (GLASS) LAI dataset was used to characterize the spatial-temporal pattern of evapotranspiration from 1982 to 2016 over the Gan River basin (GRB), the largest sub-basin of the Poyang Lake catchment, China. The results showed that the actual annual ET (ETa) weakly increased with an annual trend of 0.88 mm year−2 from 1982 to 2016 over the GRB, along with a slight decline in annual potential ET (ETp). On an ecosystem scale; however, only the evergreen broadleaved forest and cropland presented a positive ETa trend, while the rest of the ecosystems demonstrated negative trends of ETa. Both correlation analysis and sensitivity analysis revealed a close relationship between ETa inter-annual variability and energy availability. Attribution analysis illustrated that contributions of climate change and vegetation greening on the ETa trend were −0.48 mm year−2 and 1.36 mm year−2, respectively. Climate change had a negative impact on the ETa trend over the GRB. However, the negative effects have been offset by the positive effects of vegetation greening, which mainly resulted from the large-scale revegetation in forestland and agricultural practices in cropland. It is concluded that large-scale afforestation and agricultural management were the main drivers of the long-term evolution of water consumption over the GRB. This study can improve our understanding of the interactive effects of climate change and human activities on the long-term evolution of water cycles.

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