scholarly journals Glacier changes and climate trends derived from multiple sources in the data scarce Cordillera Vilcanota region, southern Peruvian Andes

2013 ◽  
Vol 7 (1) ◽  
pp. 103-118 ◽  
Author(s):  
N. Salzmann ◽  
C. Huggel ◽  
M. Rohrer ◽  
W. Silverio ◽  
B. G. Mark ◽  
...  
Keyword(s):  
Air Temperature ◽  
Specific Humidity ◽  
Spatial And Temporal Variability ◽  
Moderate Increase ◽  
Climate Data ◽  
Climate Trends ◽  
Multiple Sources ◽  
Mountain Areas ◽  
Peruvian Andes ◽  
Glacier Changes

Abstract. The role of glaciers as temporal water reservoirs is particularly pronounced in the (outer) tropics because of the very distinct wet/dry seasons. Rapid glacier retreat caused by climatic changes is thus a major concern, and decision makers demand urgently for regional/local glacier evolution trends, ice mass estimates and runoff assessments. However, in remote mountain areas, spatial and temporal data coverage is typically very scarce and this is further complicated by a high spatial and temporal variability in regions with complex topography. Here, we present an approach on how to deal with these constraints. For the Cordillera Vilcanota (southern Peruvian Andes), which is the second largest glacierized cordillera in Peru (after the Cordillera Blanca) and also comprises the Quelccaya Ice Cap, we assimilate a comprehensive multi-decadal collection of available glacier and climate data from multiple sources (satellite images, meteorological station data and climate reanalysis), and analyze them for respective changes in glacier area and volume and related trends in air temperature, precipitation and in a more general manner for specific humidity. While we found only marginal glacier changes between 1962 and 1985, there has been a massive ice loss since 1985 (about 30% of area and about 45% of volume). These high numbers corroborate studies from other glacierized cordilleras in Peru. The climate data show overall a moderate increase in air temperature, mostly weak and not significant trends for precipitation sums and probably cannot in full explain the observed substantial ice loss. Therefore, the likely increase of specific humidity in the upper troposphere, where the glaciers are located, is further discussed and we conclude that it played a major role in the observed massive ice loss of the Cordillera Vilcanota over the past decades.

scholarly journals Glacier changes and climate trends derived from multiple sources in the data scarce Cordillera Vilcanota region, Southern Peruvian Andes

2012 ◽  
Vol 6 (1) ◽  
pp. 387-426 ◽  
Author(s):  
N. Salzmann ◽  
C. Huggel ◽  
M. Rohrer ◽  
W. Silverio ◽  
B. G. Mark ◽  
...  
Keyword(s):  
Air Temperature ◽  
Specific Humidity ◽  
Spatial And Temporal Variability ◽  
Climate Data ◽  
Climate Trends ◽  
Multiple Sources ◽  
Mountain Areas ◽  
Peruvian Andes ◽  
The Past ◽  
Alpine Regions

Abstract. The role of glaciers as temporal water reservoirs is particularly pronounced in the (outer) tropics because of the very distinct wet-dry seasons. Rapid glacier retreat caused by climatic changes is thus a major concern and decision makers demand urgently for regional/local glacier evolution trends, ice mass estimates and runoff assessments. However, in remote mountain areas, spatial and temporal data coverage is typically very scarce and this is further complicated by a high spatial and temporal variability in regions with complex topography. Here, we present an approach on how to deal with these constraints. For the Cordillera Vilcanota (Southern Peruvian Andes), which is the second largest glacierised Cordillera in Peru (after the Cordillera Blanca) and also comprises the Quelccaya Ice Cap, we assimilate a comprehensive multi-decadal collection of available glacier and climate data from multiple sources (satellite images, meteorological station data and climate Reanalysis), and analyze them for respective changes in glacier area and volume and related trends in air temperature, precipitation and specific humidity. In general, the climate data show a moderate (compared to other alpine regions) increase in air temperature, weak and not significant trends for precipitation sums, and an increase in specific humidity at the 500 hPa level. The latter is consistent with observed increase in water vapour at the tropopause level during the past decades. It is likely that the increase in specific humidity played a major role in the observed massive ice loss of the Cordillera Vilcanota over the past decades.

scholarly journals Climate and basin drivers of seasonal river water temperature dynamics

2017 ◽  
Vol 21 (6) ◽  
pp. 3231-3247 ◽  
Author(s):  
Cédric L. R. Laizé ◽  
Cristian Bruna Meredith ◽  
Michael J. Dunbar ◽  
David M. Hannah
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Temporal Variability ◽  
Stream Water ◽  
Stream Temperature ◽  
Short Wave ◽  
Specific Humidity ◽  
Wave Radiation ◽  
Spatial And Temporal Variability ◽  
Wide Range

Abstract. Stream water temperature is a key control of many river processes (e.g. ecology, biogeochemistry, hydraulics) and services (e.g. power plant cooling, recreational use). Consequently, the effect of climate change and variability on stream temperature is a major scientific and practical concern. This paper aims (1) to improve the understanding of large-scale spatial and temporal variability in climate–water temperature associations, and (2) to assess explicitly the influence of basin properties as modifiers of these relationships. A dataset was assembled including six distinct modelled climatic variables (air temperature, downward short-wave and long-wave radiation, wind speed, specific humidity, and precipitation) and observed stream temperatures for the period 1984–2007 at 35 sites located on 21 rivers within 16 basins (Great Britain geographical extent); the study focuses on broad spatio-temporal patterns, and hence was based on 3-month-averaged data (i.e. seasonal). A wide range of basin properties was derived. Five models were fitted (all seasons, winter, spring, summer, and autumn). Both site and national spatial scales were investigated at once by using multi-level modelling with linear multiple regressions. Model selection used multi-model inference, which provides more robust models, based on sets of good models, rather than a single best model. Broad climate–water temperature associations common to all sites were obtained from the analysis of the fixed coefficients, while site-specific responses, i.e. random coefficients, were assessed against basin properties with analysis of variance (ANOVA). All six climate predictors investigated play a role as a control of water temperature. Air temperature and short-wave radiation are important for all models/seasons, while the other predictors are important for some models/seasons only. The form and strength of the climate–stream temperature association vary depending on season and on water temperature. The dominating climate drivers and physical processes may change across seasons and across the stream temperature range. The role of basin permeability, size, and elevation as modifiers of the climate–water temperature associations was confirmed; permeability has the primary influence, followed by size and elevation. Smaller, upland, and/or impermeable basins are the most influenced by atmospheric heat exchanges, while larger, lowland and permeable basins are the least influenced. The study showed the importance of accounting properly for the spatial and temporal variability of climate–stream temperature associations and their modification by basin properties.

scholarly journals Climate and basin drivers of seasonal river water temperature dynamics

2016 ◽  
Author(s):  
C. L. R. Laizé ◽  
C. Bruna Meredith ◽  
M. Dunbar ◽  
D. M. Hannah
Keyword(s):  
Water Temperature ◽  
Air Temperature ◽  
Temporal Variability ◽  
Stream Water ◽  
Spatial Scales ◽  
Stream Temperature ◽  
Random Coefficients ◽  
Specific Humidity ◽  
Spatial And Temporal Variability ◽  
Wide Range

Abstract. Stream water temperature is a key control of many river processes (e.g. ecology, biogeochemistry, hydraulics) and services (e.g. power plant cooling, recreational use). Consequently, the effect of climate change and variability on stream temperature is a major scientific and practical concern. This paper aimed (1) to improve the understanding of large-scale spatial and temporal variability in climate–water temperature associations, and (2) to assess explicitly the influence of basin properties as modifiers of these relationships. A dataset was assembled including six distinct modelled climatic variables (air temperature, downward shortwave and longwave radiation, wind speed, specific humidity, and precipitation) and observed stream temperatures for the period 1984–2007 at 35 sites located on 21 rivers within 16 basins (Great Britain geographical extent); the study focused on broad spatio-temporal patterns hence was based on three-month averaged data (i.e. seasonal). A wide range of basin properties was derived. Five models were fitted (all seasons, winter, spring, summer, and autumn). Both site and national spatial scales were investigated at once by using multi-level modelling with linear multiple regressions. Model selection used Multi-Model Inference, which provides more robust models, based on sets of good models, rather than a single best model. Broad climate-water temperature associations common to all sites were obtained from the analysis of the fixed coefficients, while site-specific responses, i.e. random coefficients, were assessed against basin properties with ANOVA. All six climate predictors investigated play a role as a control of water temperature. Air temperature and shortwave radiation are important for all models/seasons, while the other predictors are important for some models/seasons only. The form and strength of the climate-stream temperature association vary depending on season and on water temperature. The dominating climate drivers and physical processes may change across seasons, and across the stream temperature range. The role of basin permeability, size, and elevation as modifiers of the climate-water temperature associations was confirmed; permeability has the primary influence, followed by size and elevation. Smaller, upland, and/or impermeable basins are the most influenced by atmospheric heat exchanges, while larger, lowland and permeable basins are least influenced. The study showed the importance of accounting properly for the spatial and temporal variability of climate-stream temperature associations and their modification by basin properties.

scholarly journals Evaluating CMIP5 models using AIRS tropospheric air temperature and specific humidity climatology

2013 ◽  
Vol 118 (1) ◽  
pp. 114-134 ◽  
Author(s):  
Baijun Tian ◽  
Eric J. Fetzer ◽  
Brian H. Kahn ◽  
Joao Teixeira ◽  
Evan Manning ◽  
...  
Keyword(s):  
Air Temperature ◽  
Specific Humidity ◽  
Cmip5 Models

scholarly journals Extreme Warming in the Kara Sea and Barents Sea during the Winter Period 2000–16

2017 ◽  
Vol 30 (22) ◽  
pp. 8913-8927 ◽  
Author(s):  
Svenja H. E. Kohnemann ◽  
Günther Heinemann ◽  
David H. Bromwich ◽  
Oliver Gutjahr
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Barents Sea ◽  
Kara Sea ◽  
The Arctic ◽  
Winter Period ◽  
Limited Area ◽  
Spatial And Temporal Variability ◽  
Large Variability ◽  
Air Temperatures

The regional climate model COSMO in Climate Limited-Area Mode (COSMO-CLM or CCLM) is used with a high resolution of 15 km for the entire Arctic for all winters 2002/03–2014/15. The simulations show a high spatial and temporal variability of the recent 2-m air temperature increase in the Arctic. The maximum warming occurs north of Novaya Zemlya in the Kara Sea and Barents Sea between March 2003 and 2012 and is responsible for up to a 20°C increase. Land-based observations confirm the increase but do not cover the maximum regions that are located over the ocean and sea ice. Also, the 30-km version of the Arctic System Reanalysis (ASR) is used to verify the CCLM for the overlapping time period 2002/03–2011/12. The differences between CCLM and ASR 2-m air temperatures vary slightly within 1°C for the ocean and sea ice area. Thus, ASR captures the extreme warming as well. The monthly 2-m air temperatures of observations and ERA-Interim data show a large variability for the winters 1979–2016. Nevertheless, the air temperature rise since the beginning of the twenty-first century is up to 8 times higher than in the decades before. The sea ice decrease is identified as the likely reason for the warming. The vertical temperature profiles show that the warming has a maximum near the surface, but a 0.5°C yr−1 increase is found up to 2 km. CCLM, ASR, and also the coarser resolved ERA-Interim data show that February and March are the months with the highest 2-m air temperature increases, averaged over the ocean and sea ice area north of 70°N; for CCLM the warming amounts to an average of almost 5°C for 2002/03–2011/12.

scholarly journals Estimation of atmospheric mixing layer height from radiosonde data

2014 ◽  
Vol 7 (6) ◽  
pp. 1701-1709 ◽  
Author(s):  
X. Y. Wang ◽  
K. C. Wang
Keyword(s):  
North America ◽  
Potential Temperature ◽  
Mixing Layer ◽  
Specific Humidity ◽  
Radiosonde Data ◽  
Consistent Estimate ◽  
Climate Data ◽  
Layer Height ◽  
Temperature And Humidity ◽  
Mixing Layer Height

Abstract. Mixing layer height (h) is an important parameter for understanding the transport process in the troposphere, air pollution, weather and climate change. Many methods have been proposed to determine h by identifying the turning point of the radiosonde profile. However, substantial differences have been observed in the existing methods (e.g. the potential temperature (θ), relative humidity (RH), specific humidity (q) and atmospheric refractivity (N) methods). These differences are associated with the inconsistency of the temperature and humidity profiles in a boundary layer that is not well mixed, the changing measurability of the specific humidity and refractivity with height, the measurement error of humidity instruments within clouds, and the general existence of clouds. This study proposes a method to integrate the information of temperature, humidity and cloud to generate a consistent estimate of h. We apply this method to high vertical resolution (~ 30 m) radiosonde data that were collected at 79 stations over North America during the period from 1998 to 2008. The data are obtained from the Stratospheric Processes and their Role in Climate Data Center (SPARC). The results show good agreement with those from N method as the information of temperature and humidity contained in N; however, cloud effects that are included in our method increased the reliability of our estimated h. From 1988 to 2008, the climatological h over North America was 1675 ± 303 m with a strong east–west gradient: higher values (generally greater than 1800 m) occurred over the Midwest US, and lower values (usually less than 1400 m) occurred over Alaska and the US West Coast.

scholarly journals Influência de Mudanças Climáticas no Balanço Hídrico da Amazônia Ocidental (Influence of Climate Change on Water Budget of Western Amazonia)

2011 ◽  
Vol 3 (3) ◽  
pp. 170 ◽  
Author(s):  
Ailton Marcolino Liberato ◽  
José Ivaldo B. De Brito
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Air Temperature ◽  
Water Budget ◽  
Fire Risk ◽  
Climate Index ◽  
Climate Trends ◽  
Climatological Data ◽  
Temperature And Precipitation

A presente pesquisa teve por objetivo investigar possíveis alterações em componentes do balanço hídrico climático, associadas a diferentes cenários (A2 e B2) das mudanças climáticas do IPCC, para a Amazônia Ocidental (Acre, Amazonas, Rondônia e Roraima). Os dados climatológicos de temperatura do ar e totais de precipitação pluvial usados como referência neste estudo, são oriundos do INMET (1961-2005), da CEPLAC (1983-1999) e da reanálise do NCEP/NCAR (1983-1995). O método utilizado na elaboração do balanço hídrico é o de Thornthwaite e Mather (1957) modificado por Krishan (1980). Os resultados das projeções mostram tendência de clima mais seco, diminuição na umidade do solo, redução na vazão dos rios, aumento no risco de incêndio e diminuição no escoamento superficial e sub-superficial para a Amazônia Ocidental até 2100.Palavras-chave: cenários, índices climáticos, Amazônia. Influence of Climate Change on Water Budget of Western Amazonia ABSTRACTThe main objective of this study was investigate possible alterations in the climatic water budget components associated with different scenarios (A2 and B2) of the IPCC to Amazonian Western (Acre, Amazonas, Rondônia and Roraima). The climatological data of air temperature and precipitation from the INMET (1961-2005), CEPLAC (1983-1999) and NCEP/NCAR reanalysis (1983-1995) were used in the present study. The Thornthwaite and Mather (1955) method was used in the elaboration of the climatic water budget modified by Krishan (1980). The results of the projections show drier climate trends and decrease of the soil moisture, reduction in the rivers discharge, increase in the fire risk and decrease in the runoff for the Amazonian Western up to 2100. Keywords: scenarios, climate index, Amazonian.

scholarly journals Correlation and Causation Analysis Between COVID-19 and Environmental Factors in China

2021 ◽  
Vol 3 ◽  
Author(s):  
Zuofang Zheng ◽  
Junxia Dou ◽  
Conglan Cheng ◽  
Hua Gao
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Regional Climate ◽  
Climate Impact ◽  
Control Measures ◽  
Specific Humidity ◽  
Human Society ◽  
Causality Test ◽  
Low Wind Speed ◽  
Causation Analysis

Coronavirus disease 2019 (COVID-19) is seriously threatening and altering human society. Although prevention and control measures play an important role in preventing the transmission of severe acute respiratory syndrome coronavirus, signals of climate impact can still be detected globally. In this paper, the data of 265 cities in China were analyzed. The results show that the correlations between COVID-19 and air quality index (AQI) and PM2.5 concentration were very weak and that the correlations between COVID-19 and meteorological factors were significantly different in different climate backgrounds. So, a fixed model is not enough to describe the correlations. Overall, high humidity, low wind speed, and relatively lower air temperature are conducive to the spread of COVID-19. The climate background suitable for the spread of COVID-19 in China is air temperature 0~15°C, specific humidity <3 g kg−1, and wind speed <3 m s−1. The Granger causality test shows that there is a causal relationship between daily average air temperature and the number of COVID-19 confirmed cases in some cities of China, and air temperature is indicative of the number of confirmed cases the next day. However, this phenomenon is not universal due to regional climate differences.

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