scholarly journals Comparison of elevation-dependent warming and its drivers in the tropical and subtropical Andes

2021 ◽  
Author(s):  
Osmar Toledo ◽  
Elisa Palazzi ◽  
Iván Mauricio Cely Toro ◽  
Luca Mortarini
Keyword(s):  
Minimum Temperature ◽  
Regional Climate ◽  
Longwave Radiation ◽  
Maximum Temperature ◽  
Mountain Range ◽  
Positive Temperature ◽  
Tropical Zone ◽  
Temperature Changes ◽  
Downward Longwave Radiation ◽  
The Tropics

AbstractMountain regions have been recognized to be more sensitive to climate and environmental changes, and in particular to global warming. Several studies report on elevation-dependent warming (EDW), i.e., when warming rates are different in different altitude ranges, particularly focusing on the enhancement of warming rates with elevation. The Andean chain proved to be a relevant climate change hot-spot with positive temperature trends and a widespread glacier retreat over the recent decades. To assess and to better understand elevation dependent warming in this mountain region and to identify its possible dependence on latitude, the Andean Cordillera was split into five domains, three pertaining to the tropical zone and two pertaining to the Subtropics. Further, for each area the eastern and western faces of the mountain range were separately analyzed. An ensemble of regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX), consisting of one RCM nested into eight different global climate models from the CMIP5 ensemble was considered in this study. EDW was assessed by calculating the temperature difference between the end of the century (2071–2100) and the period 1976–2005 and relating it to the elevation. Future projections refer to the RCP 8.5 high-emission scenario. Possible differences in EDW mechanisms were identified using correlation analyses between temperature changes and all the variables identified as possible EDW drivers. For the maximum temperatures, a positive EDW signal (i.e. enhancement of warming rates with elevation) was identified in each side of both the tropical and subtropical Andes and in all seasons. For the minimum temperatures, on the contrary, while a positive EDW was identified in the Subtropics (particularly evident in the western side of the chain), the Tropics are characterized by a negative EDW throughout the year. Therefore, the tropical boundary marks a transition between discordant EDW behaviours in the minimum temperature. In the Tropics and particularly in the inner Tropics, different EDW drivers were identified for the minimum temperature, whose changes are mostly associated with changes in downward longwave radiation, and for the maximum temperature, whose changes are mainly driven by changes in downward shortwave radiation. This might explain the opposite EDW signal found in the tropical Andes during daytime and nighttime. Changes in albedo are an ubiquitous driver for positive EDW in the Subtropics, for both the minimum and the maximum temperature. Changes in longwave radiation and humidity are also EDW drivers in the Subtropics but with different relevance throughout the seasons and during daytime and nighttime. Also, the western and eastern sides of the Cordillera might be influenced by different EDW drivers.

scholarly journals The performance of CORDEX-EA-II simulations in simulating seasonal temperature and elevation-dependent warming over the Tibetan Plateau

2021 ◽  
Author(s):  
Xiaorui Niu ◽  
Jianping Tang ◽  
Deliang Chen ◽  
Shuyu Wang ◽  
Tinghai Ou ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Radiative Forcing ◽  
Regional Climate ◽  
Great Influence ◽  
Longwave Radiation ◽  
Cumulus Parameterization ◽  
The Tibetan Plateau ◽  
Seasonal Temperature ◽  
Temperature Changes ◽  
Downward Longwave Radiation

AbstractTo explore the driving mechanisms of elevation-dependent warming (EDW) over the Tibetan Plateau (TP), the output from a suite of numerical experiments with different cumulus parameterization schemes (CPs) under the Coordinated Regional Climate Downscaling Experiments-East Asia (CORDEX-EA-II) project is examined. Results show that all experiments can broadly capture the observed temperature distributions over the TP with consistent cold biases, and the spread in temperature simulations commonly increases with elevation with the maximum located around 4000–5000 m. Such disagreements among the temperature simulations could to a large extent be explained by their spreads in the surface albedo feedback (SAF). All the experiments reproduce the observed EDW below 5000 m in winter but fail to capture the observed EDW above 4500 m in spring. Further analysis suggests that the simulated EDW during winter is mainly caused by the SAF, and the clear-sky downward longwave radiation (LWclr) plays a secondary role in shaping EDW. The models’ inability in simulating EDW during spring is closely related to the SAF and the surface cloud radiative forcing (CRFs). Furthermore, the magnitude and structure of the simulated EDW are sensitive to the choice of CPs. Different CPs generate diverse snow cover fractions, which can modulate the simulated SAF and its effect on EDW. Also, the CPs show great influence on the LWclr via altering the low-level air temperature. Additionally, the mechanism for different temperature changes among the experiments varies with altitudes during summer and autumn, as the diverse temperature changes appear to be caused by the LWclr for the low altitudes while by the SAF for the middle-high altitudes.

scholarly journals On the Suitability of Current Atmospheric Reanalyses for Regional Warming Studies over China

2017 ◽  
Author(s):  
Chunlüe Zhou ◽  
Yanyi He ◽  
Kaicun Wang
Keyword(s):  
Regional Climate ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Regional Climate Change ◽  
Precipitation Frequency ◽  
Regional Warming ◽  
Downward Longwave Radiation ◽  
In Situ Observations ◽  
Mean Differences

Abstract. Reanalyses have been widely used because they add value to the routine observations by generating physically/dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies have extensively discussed their temporal suitability in global change study. This study moves forward on their suitability for regional climate change study where land–atmosphere interactions play a more important role. Here, surface air temperature (Ta) from 12 current reanalysis products were investigated, focusing on spatial patterns of Ta trends, using homogenized Ta from 1979 to 2010 at ~ 2200 meteorological stations in China. Results show that ~ 80 % of the Ta mean differences between reanalyses and in-situ observations are attributed to station and model-grid elevation differences, denoting good skill in Ta climatology and rebutting the previously reported Ta biases. However, the Ta trend biases in reanalyses display spatial divergence (standard deviation = 0.15–0.30 °C/decade at 1° × 1° grids). The simulated Ta trend biases correlate well with those of precipitation frequency, surface incident solar radiation (Rs), and atmospheric downward longwave radiation (Ld) among the reanalyses (r = −0.83, 0.80 and 0.77, p 

scholarly journals Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Yellow River ◽  
Control Variable ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Runoff Change ◽  
Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

scholarly journals Future climate uncertainty and spatial variability over Tamilnadu State, India

2015 ◽  
Vol 17 (1) ◽  
pp. 175-185
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Minimum Temperature ◽  
Climate Models ◽  
Regional Climate ◽  
Future Climate ◽  
Maximum Temperature ◽  
Projection Data ◽  
Climate Uncertainty

<div> <p>The present study analyses future climate uncertainty for the 21st century over Tamilnadu state for six weather parameters: solar radiation, maximum temperature, minimum temperature, relative humidity, wind speed and rainfall. The climate projection data was dynamically downscaled using high resolution regional climate models, PRECIS and RegCM4 at 0.22&deg;x0.22&deg; resolution. PRECIS RCM was driven by HadCM3Q ensembles (HQ0, HQ1, HQ3, HQ16) lateral boundary conditions (LBCs) and RegCM4 driven by ECHAM5 LBCs for 130 years (1971-2100). The deviations in weather variables between 2091-2100 decade and the base years (1971-2000) were calculated for all grids of Tamilnadu for ascertaining the uncertainty. These deviations indicated that all model members projected no appreciable difference in relative humidity, wind speed and solar radiation. The temperature (maximum and minimum) however showed a definite increasing trend with 1.8 to 4.0&deg;C and 2.0 to 4.8&deg;C, respectively. The model members for rainfall exhibited a high uncertainty as they projected high negative and positive deviations (-379 to 854 mm). The spatial representation of maximum and minimum temperature indicated a definite rhythm of increment from coastal area to inland. However, variability in projected rainfall was noticed.</p> </div> <p>&nbsp;</p>

Trend Analysis and ARIMA Modeling to Assess Meteorological and Surface Parameters In Ranchi, India During Pre-Monsoon Months

GIS Business ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 69-87
Author(s):  
Poulomi Chakravarty ◽  
Manoj Kumar
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Land Surface ◽  
Regional Climate ◽  
Arima Model ◽  
Sensible Heat Flux ◽  
Shortwave Radiation ◽  
Maximum Temperature ◽  
Positive Temperature ◽  
Surface Parameters

The assessment of the human-induced climate change on a global level can be carried out only after the study of local and regional climate change patterns. This study was an attempt to establish a link between regional climate and the surface parameters. The study was carried out for Ranchi, India to assess the changes in climatic pattern over the years (1901-2016) and applied Mann-Kendall Trend analysis test. The pre-monsoon period was chosen due to high intensity and number of thunderstorms taking place in the study area. Maximum temperature (Tmax), minimum temperature (Tmin), rainfall (P) &diurnal temperature range (DTR) for the months (March, April & May) were studied, and a significant negative trend in Tmax and DTR was observed. Autoregressive Integrated Moving Average (ARIMA) model was applied to fit the datasets and predict 5 values for the meteorological parameters, and the model depicted positive temperature trends and negative rainfall and DTR trends in the future. Land surface process parameters such as sensible heat flux, momentum flux, frictional velocity, shortwave radiation, longwave radiation, and net radiation for Ranchi were also fit into the ARIMA model, and the fitness of the model and predictions were determined.

On-Line Monitoring of Charge Unit by Using Fiber Bragg Grating Temperature Sensors

2012 ◽  
Vol 503-504 ◽  
pp. 1672-1678
Author(s):  
Zhao Yang ◽  
Xiao Ping Xu ◽  
Chuan Li ◽  
Yan Chen ◽  
Jiang Chun Xu ◽  
...  
Keyword(s):  
Ambient Temperature ◽  
Fiber Bragg Grating ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Bragg Grating ◽  
Temperature Changes ◽  
Temperature Range ◽  
On Line

The charge unit supply power when the power is cut off. It has been the necessary components in every type of substations to ensure the continuous operations of electric relays, automatic devices and circuit breakers. By using contacting electrical insulating Fiber Bragg Grating temperature sensor, the monitored equipment can be measured and controlled under the safe temperature. The temperatures of three fans and environment have been surveyed since June 6, 2010, in the charge unit of Yanjin substation’s main control room. The real-time monitoring of 24-hours indicates that the temperature changes in the range of 1°C. At the long-term of 479 days, the average daily minimum temperature range of three fans is 12.48°C, and the maximum range is 23.07°C. The maximum temperature is 39.14°C on April 30, 2011, and the minimum temperature is 23.98°C on January 10, 2011. The daily average of ambient temperature range is 12.04 °C, the maximum temperature is 38.38 °C on July 16, 2010, and the minimum temperature is 26.34 °C on January 9, 2011. The maximum difference between the temperature of fan and the ambient temperature is 7.60 °C on October 23, 2010. According to the relevant standards and monitoring results, the maximum threshold of fan temperature is defined to 85°C, and the threshold of temperature rise is 20°C.

scholarly journals Autumn–winter minimum temperature changes in the southern Sikhote-Alin mountain range of northeastern Asia since 1529 AD

2018 ◽  
Vol 14 (1) ◽  
pp. 57-71 ◽  
Author(s):  
Olga N. Ukhvatkina ◽  
Alexander M. Omelko ◽  
Alexander A. Zhmerenetsky ◽  
Tatyana Y. Petrenko
Keyword(s):  
Solar Activity ◽  
Minimum Temperature ◽  
Southern Oscillation ◽  
Russian Far East ◽  
Far East ◽  
Winter Season ◽  
Mountain Range ◽  
Sikhote Alin ◽  
Northeastern Asia ◽  
Temperature Changes

Abstract. The aim of our research was to reconstruct climatic parameters (for the first time for the Sikhote-Alin mountain range) and to compare them with global climate fluctuations. As a result, we have found that one of the most important limiting factors for the study area is the minimum temperatures of the previous autumn–winter season (August–December), and this finding perfectly conforms to that in other territories. We reconstructed the previous August–December minimum temperature for 485 years, from 1529 to 2014. We found 12 cold periods (1535–1540, 1550–1555, 1643–1649, 1659–1667, 1675–1689, 1722–1735, 1791–1803, 1807–1818, 1822–1827, 1836–1852, 1868–1887, 1911–1925) and seven warm periods (1560–1585, 1600–1610, 1614–1618, 1738–1743, 1756–1759, 1776–1781, 1944–2014). These periods correlate well with reconstructed data for the Northern Hemisphere and the neighboring territories of China and Japan. Our reconstruction has 3-, 9-, 20-, and 200-year periods, which may be in line with high-frequency fluctuations in El Niño–Southern Oscillation (ENSO), the short-term solar cycle, Pacific Decadal Oscillation (PDO) fluctuations, and the 200-year solar activity cycle, respectively. We suppose that the temperature of the North Pacific, expressed by the PDO may make a major contribution to regional climate variations. We also assume that the regional climatic response to solar activity becomes apparent in the temperature changes in the northern part of Pacific Ocean and corresponds to cold periods during the solar minimum. These comparisons show that our climatic reconstruction based on tree ring chronology for this area may potentially provide a proxy record for long-term, large-scale past temperature patterns for northeastern Asia. The reconstruction reflects the global traits and local variations in the climatic processes of the southern territory of the Russian Far East for more than the past 450 years.

scholarly journals A Long-Term, 1-km Resolution Daily Meteorological Dataset for Modeling and Mapping Permafrost in Canada

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1363
Author(s):  
Yu Zhang ◽  
Budong Qian ◽  
Gang Hong
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Longwave Radiation ◽  
Historical Period ◽  
Air Temperatures ◽  
Downward Longwave Radiation ◽  
High Emission ◽  
Climate Station

Climate warming is causing permafrost thaw and there is an urgent need to understand the spatial distribution of permafrost and its potential changes with climate. This study developed a long-term (1901–2100), 1-km resolution daily meteorological dataset (Met1km) for modeling and mapping permafrost at high spatial resolutions in Canada. Met1km includes eight climate variables (daily minimum, maximum, and mean air temperatures, precipitation, vapor pressure, wind speed, solar radiation, and downward longwave radiation) and is suitable to drive process-based permafrost and other land-surface models. Met1km was developed based on four coarser gridded meteorological datasets for the historical period. Future values were developed using the output of a new Canadian regional climate model under medium-low and high emission scenarios. These datasets were downscaled to 1-km resolution using the re-baselining method based on the WorldClim2 dataset as spatial templates. We assessed Met1km by comparing it to climate station observations across Canada and a gridded monthly anomaly time-series dataset. The accuracy of Met1km is similar to or better than the four coarser gridded datasets. The errors in long-term averages and average seasonal patterns are small. The error occurs mainly in day-to-day fluctuations, thus the error decreases significantly when averaged over 5 to 10 days. Met1km, as a data generating system, is relatively small in data volume, flexible to use, and easy to update when new or improved source datasets are available. The method can also be used to generate similar datasets for other regions, even for the entire global landmass.

scholarly journals On the suitability of current atmospheric reanalyses for regional warming studies over China

2018 ◽  
Vol 18 (11) ◽  
pp. 8113-8136 ◽  
Author(s):  
Chunlüe Zhou ◽  
Yanyi He ◽  
Kaicun Wang
Keyword(s):  
Spatial Patterns ◽  
Southern China ◽  
Regional Climate ◽  
Longwave Radiation ◽  
Northern China ◽  
Atmospheric Model ◽  
Precipitation Frequency ◽  
Regional Warming ◽  
Ensemble Technique ◽  
Downward Longwave Radiation

Abstract. Reanalyses are widely used because they add value to routine observations by generating physically or dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies include extensive discussions of the temporal suitability of reanalyses in studies of global change. This study adds to this existing work by investigating the suitability of reanalyses in studies of regional climate change, in which land–atmosphere interactions play a comparatively important role. In this study, surface air temperatures (Ta) from 12 current reanalysis products are investigated; in particular, the spatial patterns of trends in Ta are examined using homogenized measurements of Ta made at  ∼  2200 meteorological stations in China from 1979 to 2010. The results show that  ∼  80 % of the mean differences in Ta between the reanalyses and the in situ observations can be attributed to the differences in elevation between the stations and the model grids. Thus, the Ta climatologies display good skill, and these findings rebut previous reports of biases in Ta. However, the biases in theTa trends in the reanalyses diverge spatially (standard deviation  =  0.15–0.30 °C decade−1 using 1°  ×  1° grid cells). The simulated biases in the trends in Ta correlate well with those of precipitation frequency, surface incident solar radiation (Rs) and atmospheric downward longwave radiation (Ld) among the reanalyses (r = −0.83, 0.80 and 0.77; p < 0.1) when the spatial patterns of these variables are considered. The biases in the trends in Ta over southern China (on the order of −0.07 °C decade−1) are caused by biases in the trends in Rs, Ld and precipitation frequency on the order of 0.10, −0.08 and −0.06 °C decade−1, respectively. The biases in the trends in Ta over northern China (on the order of −0.12 °C decade−1) result jointly from those in Ld and precipitation frequency. Therefore, improving the simulation of precipitation frequency and Rs helps to maximize the signal component corresponding to regional climate. In addition, the analysis of Ta observations helps represent regional warming in ERA-Interim and JRA-55. Incorporating vegetation dynamics in reanalyses and the use of accurate aerosol information, as in the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), would lead to improvements in the modelling of regional warming. The use of the ensemble technique adopted in the twentieth-century atmospheric model ensemble ERA-20CM significantly narrows the uncertainties associated with regional warming in reanalyses (standard deviation  =  0.15 °C decade−1).

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