Climate change in mountains around the globe: Elevation dependencies and contrasts to adjacent lowlands

2020 ◽  
Author(s):  
Enrico Arnone ◽  
Nick Pepin ◽  
Elisa Palazzi ◽  
Sven Kotlarski ◽  
Silvia Terzago ◽  
...  
Keyword(s):  
Climate Change ◽  
Meta Analysis ◽  
Global Climate Model ◽  
High Elevation ◽  
General Context ◽  
Mountain Regions ◽  
Temperature And Precipitation ◽  
Temperature Trends ◽  
Significant Difference ◽  
Precipitation Changes

<p>Mountain and high elevation regions often show distinct climate trends in temperature and precipitation, which can contrast those of adjacent lowland regions. In the context of temperature, this phenomenon is known as elevation-dependent warming (EDW). Past temperature trends can increase with elevation, but this is not always so, and they may peak in a critical elevation band, or show more complex elevation profiles. This is controlled by a variety of mechanisms which may be responsible for the observed patterns, including snow albedo feedback, vegetation change, cloud and moisture patterns, aerosol forcing and their interactions.</p><p>We here present a literature-based meta-analysis of elevation profiles in recent warming rates and, in a more general context, temperature change in mountain regions around the globe. For the recent historical period (~1960-2010) we find that when comparing like with like (i.e. high elevation regions with adjacent low elevation regions) warming rates are mostly stronger at higher elevations. Warming rates have also increased over time, with more recent decades showing stronger warming.<span> </span>On a global scale there is no significant difference between mean warming rates in mountains and in other areas. Thus, elevation-dependency within regions can be masked by differences in geographical location in global meta-analyses. Although there have been far fewer studies on vertical profiles of precipitation changes, we extend our meta-analysis to consider this parameter,<span>  </span>where information is available.</p><p>In addition to the meta-analysis, we compare past temperature and precipitation changes in mountain and lowland regions using global gridded observation-based and reanalysis datasets (e.g. CRU, ERA5, NCEP2) and global climate model simulations (CMIP5). Despite the uncertainties of these datasets (e.g. inhomogeneous underlying station coverage and related interpolation errors, biases, coarse spatial resolution), they allow us to compare different mountain regions globally with the same level of accuracy. There are only a few mountain areas that show distinct differences when their temperature trends are compared with lowland surroundings, but patterns vary by dataset and region. We also explore different extensions of adjacent lowlands, which may influence the quantification of differences in temperature and precipitation trends at high and low elevation.</p><p>This historical assessment is completed by an analysis of model projections (CMIP5) for studying the expected future evolution of climate change in mountains and contrasts to adjacent lowlands</p>

scholarly journals Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe

2006 ◽  
Vol 6 (4) ◽  
pp. 863-881 ◽  
Author(s):  
A. P. van Ulden ◽  
G. J. van Oldenborgh
Keyword(s):  
Climate Change ◽  
Central Europe ◽  
Large Scale ◽  
Global Climate Model ◽  
Late Summer ◽  
Geostrophic Flow ◽  
Temperature And Precipitation ◽  
Mean Temperature ◽  
Precipitation Changes ◽  
Circulation Changes

Abstract. The quality of global sea level pressure patterns has been assessed for simulations by 23 coupled climate models. Most models showed high pattern correlations. With respect to the explained spatial variance, many models showed serious large-scale deficiencies, especially at mid-latitudes. Five models performed well at all latitudes and for each month of the year. Three models had a reasonable skill. We selected the five models with the best pressure patterns for a more detailed assessment of their simulations of the climate in Central Europe. We analysed observations and simulations of monthly mean geostrophic flow indices and of monthly mean temperature and precipitation. We used three geostrophic flow indices: the west component and south component of the geostrophic wind at the surface and the geostrophic vorticity. We found that circulation biases were important, and affected precipitation in particular. Apart from these circulation biases, the models showed other biases in temperature and precipitation, which were for some models larger than the circulation induced biases. For the 21st century the five models simulated quite different changes in circulation, precipitation and temperature. Precipitation changes appear to be primarily caused by circulation changes. Since the models show widely different circulation changes, especially in late summer, precipitation changes vary widely between the models as well. Some models simulate severe drying in late summer, while one model simulates significant precipitation increases in late summer. With respect to the mean temperature the circulation changes were important, but not dominant. However, changes in the distribution of monthly mean temperatures, do show large indirect influences of circulation changes. Especially in late summer, two models simulate very strong warming of warm months, which can be attributed to severe summer drying in the simulations by these models. The models differ also significantly in the simulated warming of cold winter months. Finally, the models simulate rather different changes in North Atlantic sea surface temperature, which is likely to impact on changes in temperature and precipitation. These results imply that several important aspects of climate change in Central Europe are highly uncertain. Other aspects of the simulated climate change appear to be more robust. All models simulate significant warming all year round and an increase in precipitation in the winter half-year.

scholarly journals Temperature trends in Fiji: a clear signal of climate change

2013 ◽  
Vol 31 (1) ◽  
pp. 27 ◽  
Author(s):  
Ravind Kumar ◽  
Mark Stephens ◽  
Tony Weir
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Pacific Islands ◽  
Extreme Values ◽  
Maximum Temperature ◽  
Temperature Trends ◽  
Clear Signal ◽  
Rate Of Increase ◽  
Significant Difference ◽  
Using Data

This paper analyses trends in temperature in Fiji, using data from more stations (10) and longer periods (52-78 years) than previous studies. All the stations analysed show a statistically significant trend in both maximum and minimum temperature, with increases ranging from 0.08 to 0.23°C per decade. More recent temperatures show a higher rate of increase, particularly in maximum temperature (0.18 to 0.69°C per decade from 1989 to 2008). This clear signal of climate change is consistent with that found in previous studies of temperatures in Fiji and other Pacific Islands. Trends in extreme values show an even stronger signal of climate change than that for mean temperatures. Our preliminary analysis of daily maxima at 6 stations indicates that for 4 of them (Suva, Labasa, Vunisea and Rotuma) there has been a tripling in the number of days per year with temperature >32°C between 1970 and 2008. The correlations between annual mean maximum (minimum) temperature and year are mostly strong: for about half the stations the correlation coefficient exceeds 60% over 50+ years. Trends do not vary systematically with location of station. At all 7 stations for which both trends are available there is no statistically significant difference between the trends in maximum and minimum temperatures.

scholarly journals The changes of precipitation in Podgorica for period 1951-2010

2011 ◽  
Vol 91 (2) ◽  
pp. 51-70
Author(s):  
Vladan Ducic ◽  
Dragan Buric ◽  
Jelena Lukovic ◽  
Gorica Stanojevic
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Air Temperature ◽  
Temperature Variability ◽  
Interannual Variations ◽  
Temperature And Precipitation ◽  
Precipitation Changes ◽  
Climatic Elements

The global warming and climate change are the actual and challenging topics. Recently there is one question, frequently asked: whether today's climate is changing? The studies of this issues are mainly related to the two the most important climatic elements - air temperature and precipitation amounts. We have done research about temperature variability for Montenegro and the main aim of this paper is analysis precipitation changes for station Podgorica (Montenegro) in the period of sistematic observation - are there changes, to what extent and whether they are significant. According to the results, acumulated precipitation do not show significant changes for annual and seasonal values in the period 1951-2010. The interannual variations of the precipitation (which are characterictic for this climate element) do not show increases in recent times. The component trend shows some changes, but statisticaly insignigficant. The previous results for precipitation conditions in Podgorica are not in accordance with the concept of Intergovermental Panel on Climate Change (IPCC) which predicted a general decerease in precipitation and increase variability on this area.

scholarly journals Improved Bias Correction Techniques for Hydrological Simulations of Climate Change*

2015 ◽  
Vol 16 (6) ◽  
pp. 2421-2442 ◽  
Author(s):  
David W. Pierce ◽  
Daniel R. Cayan ◽  
Edwin P. Maurer ◽  
John T. Abatzoglou ◽  
Katherine C. Hegewisch
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Model ◽  
Global Climate Model ◽  
Cumulative Distribution ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Climate Change Signal ◽  
Daily Maximum ◽  
Temperature And Precipitation

Abstract Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 2°C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction preserves GCM changes in mean daily maximum temperature but not precipitation. An extension to EDCDFm termed PresRat is introduced, which generally preserves the GCM changes in mean precipitation. Another problem is that GCMs can have difficulty simulating variance as a function of frequency. To address this, a frequency-dependent bias correction method is introduced that is twice as effective as standard bias correction in reducing errors in the models’ simulation of variance as a function of frequency, and it does so without making any locations worse, unlike standard bias correction. Last, a preconditioning technique is introduced that improves the simulation of the annual cycle while still allowing the bias correction to take account of an entire season’s values at once.

scholarly journals Effects of Temperature and Precipitation on Breeding Migrations of Amphibian Species in Southeastern Norway

Scientifica ◽  
2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Børre K. Dervo ◽  
Kim Magnus Bærum ◽  
Jostein Skurdal ◽  
Jon Museth
Keyword(s):  
Climate Change ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Survival Rates ◽  
General Context ◽  
Amphibian Species ◽  
Temperature And Precipitation ◽  
Migration Phenology ◽  
Effects Of Temperature ◽  
Southern Norway

To reveal the effects of climate, a generalized linear mixed model was used to explore the variation in onset of spawning migration for the two newt speciesT. cristatusandL. vulgarisin southern Norway. Amphibians are highly influenced by the physical environment, such as temperature and rainfall. The first migrating newts were observed subsequently to the three first consecutive days with mean temperature close to or above 4°C. Further, migration ofL. vulgariswas facilitated at lower temperatures compared toT. cristatus, but the migration was dependent on higher precipitation levels. Northern populations ofT. cristatusandL. vulgarismay already benefit from a warmer climate due to increased recruitment and juvenile survival. However, an offset in the migration phenology due to climate change might further alter the recruitment and survival rates with either positive or negative outcome. Thus, variations in migration phenology for newts due to climate change may have implications for management and protection status in many systems. In a general context, we should increase emphasis on protecting newts and support increased populations and distribution.

scholarly journals Does the High Elevation Climate along Mt. Everest can be Represented by Lower Elevation Stations?

2021 ◽  
Vol 26 (2) ◽  
pp. 99-109
Author(s):  
Binod Dawadi ◽  
Shankar Sharma ◽  
Kalpana Hamal ◽  
Nitesh Khadka ◽  
Yam Prasad Dhital ◽  
...  
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Monsoon Season ◽  
High Elevation ◽  
High Mountain ◽  
Climate Data ◽  
Southern Slope ◽  
Mountain Areas ◽  
Temperature And Precipitation ◽  
Lower Elevation

Climate change studies of the high mountain areas of the central Himalayan region are mostly represented by the meteorological stations of the lower elevation. Therefore, to validate the climatic linkages, daily observational climate data from five automated weather stations (AWS) at elevations ranging from 2660 m to 5600 m on the southern slope of Mt. Everest were examined. Despite variations in the means and distribution of daily, 5-day, 10-day, and monthly temperature and precipitation between stations located at a higher elevation and their corresponding lower elevation, temperature records in the different elevations are highly correlated. In contrast, the precipitation data shows a comparatively weaker correlation. The slopes of the regression model (0.82–1.13) with (R2>0.74) for higher altitude (5050 m and 5600 m) throughout the year, 0.83–1.12 (R2>0.68) except late monsoon season for the station at 4260 m and 5050 m asl indicated the similar variability of the temperature between those stations. Similarly, Namche (3570 m) temperature changes by 0.81–1.32°C per degree change in corresponding lower elevation Lukla station (2660 m), except for monsoon season. However, inconsistent variation was observed between the station with a large altitudinal difference (2940 m) at Lukla and Kala Patthar (5600 m). In general, climate records from corresponding lower elevation can be used to quantitatively assess climatic information of the high elevation areas on the southern slope of Mt. Everest. However, corrections are necessary when absolute values of climatic factors are considered, especially in snow cover and snow-free areas. This study will be beneficial for understanding the high-altitude climate change and impact studies.

scholarly journals The Impact of Climate Change On Financing Cost of Heavy-Pollution Firms in China

2021 ◽  
Author(s):  
Kai Chang ◽  
Yixia Nie
Keyword(s):  
Climate Change ◽  
Firm Size ◽  
Impact Of Climate Change ◽  
Positive Effects ◽  
Financing Cost ◽  
Temperature And Precipitation ◽  
Financing Costs ◽  
Heavy Pollution ◽  
Precipitation Changes ◽  
The Impact

Abstract We examines the effects of climate change on the financing cost of heavy-pollution firms using firm-level panel data analysis. The empirical results demonstrate that the annual temperature and precipitation changes can significantly promote the financing costs of heavy-pollution firms, the positive impacts of annual temperature and precipitation changes on the financing costs of large, medium and small heavy-pollution firms has shown a gradual weakening trend with an increase of firm size, and the positive effects of annual temperature and precipitation changes on the financing costs of younger and older heavy-pollution firms has shown a decline trend with an increase of firm age. The evidences confirms that the impact of climate change on the financing costs of heavy-pollution firms exhibit a significant firm size and age discrimination of financing behaviors. Government decision-makers have to identify and optimize the transmission effect of climate change response on financing behavior decisions of heavy-pollution industries, financial institutions alleviate financial conflicts and credit discrimination behaviors and optimize the efficiency of financial resource allocation. Firms’ executives correct climate change strategy, optimize the climate- relevant operation, investment and financing activities, and alleviate unfavorable influences of climate changes for heavy-pollution firms.

scholarly journals Insects and recent climate change

2021 ◽  
Vol 118 (2) ◽  
pp. e2002543117 ◽  
Author(s):  
Christopher A. Halsch ◽  
Arthur M. Shapiro ◽  
James A. Fordyce ◽  
Chris C. Nice ◽  
James H. Thorne ◽  
...  
Keyword(s):  
Climate Change ◽  
Empirical Work ◽  
Climate Change Impacts ◽  
High Elevation ◽  
Population Declines ◽  
Climatic Fluctuations ◽  
Temperature And Precipitation ◽  
Recent Climate Change ◽  
Recent Climate

Insects have diversified through more than 450 million y of Earth’s changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.

Use of Integrated Global Climate Model Simulations and Statistical Time Series Forecasting to Project Regional Temperature and Precipitation

2021 ◽  
Author(s):  
Yuchuan Lai ◽  
David A. Dzombak
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Arima Model ◽  
Climate Change Signal ◽  
Temperature And Precipitation ◽  
Regional Temperature ◽  
Statistical Time

AbstractAn integrated technique combining global climate model (GCM) simulation results and a statistical time series forecasting model (the autoregressive integrated moving average ARIMA model) was developed to bring together the climate change signal from GCMs to city-level historical observations as an approach to obtain location-specific temperature and precipitation projections. This approach assumes that regional temperature and precipitation time series reflect a combination of an underlying climate change signal series and a regional-deviation-from-the-signal series. An ensemble of GCMs is used to describe and provide the climate change signal, and the ARIMA model is used to model and project the regional deviation. Qualitative and quantitative assessments were conducted for evaluating the projection performance of the hybrid GCM-ARIMA (G-ARIMA) model. The results indicate that the G-ARIMA model can provide projected city-specific daily temperature and precipitation series comparable to historical observations and can have improved projection accuracy for several assessed annual indices compared to a commonly used downscaled projection product. The G-ARIMA model is subject to some limitations and uncertainties from the GCM-provided climate change signal. A notable feature of the G-ARIMA model is the efficiency with which projections can be updated when new observations become available, thus facilitating updating of regional temperature and precipitations projections. Given the increasing need for and use of location-specific climate projections in practical engineering applications, the G-ARIMA model is an option for regional temperature and precipitation projection for such applications.

Climate Risk and Vulnerability Assessment in Azerbaijan’s mountain regions

2020 ◽  
Author(s):  
Marc Zebisch ◽  
Stefano Terzi ◽  
Alice Crespi ◽  
Ruth Sonnenschein ◽  
Stefan Steger
Keyword(s):  
Climate Change ◽  
Global Climate Model ◽  
Climate Risk ◽  
Mountain Regions ◽  
Qualitative Information ◽  
Hazard Exposure ◽  
Local Stakeholders ◽  
Climate Hazards ◽  
The Impact ◽  
Risk Processes

<p>Mountain regions are an important hotspot of vulnerability to climate change. These ecosystems are experiencing a higher warming rate than other areas in the world, with severe consequences on the environment, the economy and society. This is particularly relevant for Azerbaijan’s mountain regions, where the climate change impacts on water management could lead to severe consequences on the main local socio-economic activities such as agriculture and livestock farming.</p><p>For these reasons, the Impact Chains (ICs) methodology has been applied within two regions of Azerbaijan to understand and investigate cause-effect chains of current and future risk from different type of climate hazards following the approach proposed in the Fifth Assessment Report (AR5) of the International Panel on Climate Change (IPCC). ICs provide a consolidated scheme which helps to better understand, systemize and prioritize the factors driving climate impact related risks in a specific system and to perform climate risk assessments. It includes the underlying root-causes of climate risk, hazard, exposure and vulnerability factors and their interactions coming from quantitative and qualitative information.</p><p>Here we present the ICs study for Azerbaijan’s mountain regions accounting for flood, drought, erosion, heat stress and forest fires identified as the most relevant hazards in the country.</p><p>Climate conditions and future hazard components were assessed looking at future daily temperature and precipitation data until 2099 from two RCP (Representative Concentration Pathways) scenarios provided by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). The spatialized dataset is an ensemble of four global climate model simulations at a resolution of 0.5°x0.5°. In particular, the ISIMIP projections were exploited to extract the future evolution and spatial distribution over the region of relevant indicators for climate and climate hazards, including weather extremes and droughts.</p><p>The different levels of exposure and vulnerability were evaluated combining quantitative and qualitative information coming from spatial analysis, workshop discussion and questionnaires with local stakeholders and experts.</p><p>To finalize the risk assessment, the hazard, exposure and vulnerability components were combined through aggregation and normalisation techniques and risk indicators and hotspot maps for Azerbaijan’s mountain regions were developed.</p><p>The information provided by the ICs will be available to further analyse the risk processes and local dynamics, and to support local stakeholders in decision-making process and future investments on risk reduction and climate adaptation plans.</p>

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