scholarly journals Future Projection of Drought Vulnerability over Northeast Provinces of Iran during 2021–2100

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1704
Author(s):  
Iman Babaeian ◽  
Atefeh Erfani Rahmatinia ◽  
Alireza Entezari ◽  
Mohammad Baaghideh ◽  
Mohammad Bannayan Aval ◽  
...  
Keyword(s):  
General Circulation ◽  
Census Data ◽  
Meteorological Data ◽  
Circulation Model ◽  
Vulnerability Index ◽  
Cmip5 Models ◽  
Future Projection ◽  
Drought Vulnerability ◽  
Adaptation Capacity ◽  
Taylor Diagram

Future projection of drought vulnerability is vital for northern provinces of Iran, including North Khorasan, Khorasan-Razavi, and South Khorasan, due to the highly dependent of their economy on agriculture. The study is motivated by the fact that no research has been conducted to project the future Drought Vulnerability Index (DVI). DVI consist of three components of exposure, sensitivity, and adaptation capacity. More exposure levels of drought, higher sensitivity value, and lower adaptation capacity lead to a higher amount of vulnerability. Combined ERA-Interim-observation meteorological data, CMIP5 models under RCP4.5 and RCP8.5 scenarios, and national census data are used to estimate DVI in the past and future periods. CanESM2, GFDL-ESM2M, and CNRM-CM5 General Circulation Model (GCM) are selected from CMIP5 based on Taylor diagram results. The delta-change technique was selected for statistical downscaling of GCM outputs because it is most widely used. The study period is regarded as 1986–2005 as observation and four future 20-years periods during 2021–2100. Results indicated that the dissipation of the class of “very low” vulnerability is eminent in the near future period of 2021–2040 under the RCP4.5 scenario, and all provinces would experience a new worse class of “very high” vulnerability at 2081–2100, both under RCP4.5 and RCP8.5 scenarios.

scholarly journals Identifying suitable general circulation model for future building cooling energy analysis

2019 ◽  
Vol 111 ◽  
pp. 06056
Author(s):  
Kuo-Tsang Huang ◽  
Yu-Teng Weng ◽  
Ruey-Lung Hwang
Keyword(s):  
General Circulation ◽  
Meteorological Data ◽  
Circulation Model ◽  
Building Energy ◽  
Building Simulation ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Global Circulation Models ◽  
The Future ◽  
Energy Use Intensity

These future building energy studies mainly stem from hourly based dynamic building simulation results with the future weather data. The reliability of the future building energy forecast heavily relies on the accuracy of these future weather data. The global circulation models (GCMs) provided by IPCC are the major sources for constructing future weather data. However, there are uncertainties existed among them even with the same climate change scenarios. There is a need to develop a method on how to select the suitable GCM for local application. This research firstly adopted principal component analysis (PCA) method in choosing the suitable GCM for application in Taiwan, and secondly the Taiwanese hourly future meteorological data sets were constructed based on the selected GCM by morphing method. Thirdly, the future cooling energy consumption of an actual office building in the near (2011-2040), the mid (2041-2070), and the far future (2071-2100), were analysed. The results show that NorESM1-M GCM has the lowest root mean square error (RMSE) as opposed to the other GCMs, and was identified as the suitable GCM for further future climate generation processing. The building simulation against the future weather datasets revealed that the average cooling energy use intensity (EUIc) in Taipei will be increased by 12%, 17%, and 34% in the 2020s, 2050s, and 2080s, respectively, as compared to the current climate.

scholarly journals Local Monitoring of Atmospheric Transparency from the NASA MERRA-2 Global Assimilation System

2019 ◽  
Vol 08 (04) ◽  
pp. 1950013
Author(s):  
A. Guyonnet ◽  
S. Dagoret-Campagne ◽  
N. Mondrik
Keyword(s):  
General Circulation ◽  
Meteorological Data ◽  
Percent Level ◽  
Circulation Model ◽  
Precipitable Water ◽  
Atmospheric Transmission ◽  
Atmospheric Transparency ◽  
Spatial Gradients ◽  
The Impact ◽  
Assimilation System

Ground-based astronomy has to correct astronomical observations from the impact of the atmospheric transparency and its variability. The current objective of several observatories is to achieve a sub-percent-level monitoring of atmospheric transmission. A promising approach has been to combine internal calibration of the observations with various external meteorological data sources, upon availability and depending on quality. In this paper we investigate the use of the NASA Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) which is a general circulation model (GCM) and data assimilation system that renders freely available for any given site, at any time, all the parameters constraining atmospheric transmission. This paper demonstrates the extraction of the relevant atmospheric parameters for optical astronomy at two sites: Mauna Kea in Hawaii and Cerro Tololo International Observatory in Chile. The temporal variability for the past eight years (annual, overnight, and hourly) as well as the spatial gradients of ozone, precipitable water vapor, and aerosol optical depth are presented and their respective impacts on the atmospheric transparency are analyzed.

scholarly journals Comparison of Various Reanalyses Gridded Data with Observed Data from Meteorological Stations over India

10.29007/c1sf ◽  
2018 ◽  
Author(s):  
Arnab Bandyopadhyay ◽  
Grace Nengzouzam ◽  
W. Rahul Singh ◽  
Nemtinkim Hangsing ◽  
Aditi Bhadra
Keyword(s):  
Observational Data ◽  
General Circulation ◽  
Promising Result ◽  
Meteorological Data ◽  
Circulation Model ◽  
India Meteorological Department ◽  
Gridded Data ◽  
Statistical Parameters ◽  
Data Product ◽  
Data Products

Meteorological data such as precipitation and temperature are important for hydrological modelling. In areas where there is sparse observational data, an alternate means for obtaining information for different impact modelling and monitoring activities is provided by reanalysis products. Evaluating their behaviour is crucial to know their uncertainties. Therefore, we evaluated two reanalyses gridded data products, viz., Coordinated Regional Climate Downscaling Experiment (CORDEX) and National Centers for Environment Predictors and GCM (General Circulation Model) predictor variables (NCEP); two station based gridded data products, viz., Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) and India Meteorological Department (IMD) gridded data; one satellite based gridded data product i.e., Tropical Rainfall Measuring Mission (TRMM); and one merged data product, i.e., Global Precipitation Climatology Project (GPCP). These products were compared with IMD observed station data for 1971 to 2010 to evaluate their behaviour in terms of fitness by using statistical parameters such as NSE, CRM and R2. APHRODITE and TRMM gridded data showed overall good results for precipitation followed by IMD, GPCP, CORDEX and NCEP. APHRODITE also showed good agreement for mean temperature. CORDEX and NCEP gave a promising result for minimum and maximum temperatures with NCEP better than CORDEX.

scholarly journals A new tool for model assessment in the frequency domain – Spectral Taylor Diagram : application to a global ocean general circulation model with tides

2018 ◽  
Author(s):  
Mabel Costa Calim ◽  
Paulo Nobre ◽  
Peter Oke ◽  
Andreas Schiller ◽  
Leo San Pedro Siqueira ◽  
...  
Keyword(s):  
Time Series ◽  
Frequency Domain ◽  
General Circulation Model ◽  
General Circulation ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Global Ocean ◽  
Model Assessment ◽  
Taylor Diagram ◽  
Ocean General Circulation

Abstract. We introduce a new tool – the Spectral Taylor Diagram (STD) – for the comparison of time series in the frequency domain. The STD provides a novel way of displaying the squared-coherence, power, amplitude, phase, and root-mean-squared difference of discrete frequencies of two time-series. Each STD summarises these quantities in a single plot, for multiple targeted frequencies. The versatility of STDs is demonstrated through a series of sea-level comparisons between observations from tide gauges, and model results from a global eddy-permitting ocean general circulation model with explicit tidal forcing.

scholarly journals Historical Variability And Future Changes In Seasonal Extreme Temperature Over Iran

2021 ◽  
Author(s):  
Azar Zarrin ◽  
Abbasali Dadashi-Roudbari ◽  
Samira Hassani
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Cmip5 Models ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Important Indicator ◽  
Taylor Diagram ◽  
Temperature Indices

Abstract The extreme temperature indices (ETI) are an important indicator of climate change, the detection of their changes over the next years can play an important role in the Climate Action Plan (CAP). In this study, four temperature indices (Mean of daily minimum temperature (TN), Mean of daily maximum temperature (TX), Cold-spell duration index (CSDI), and Warm-spell duration index (WSDI)) were defined by ETCCDI and two new indices of the Maximum number of consecutive frost days (CFD) and the Maximum number of consecutive summer days (CSU) were calculated to examine ETIs in Iran under climate change conditions. We used minimum and maximum daily temperature of five General circulation models (GCMs) including HadGEM2-ES, IPSL-CM5A-LR, GFDL-ESM2M, MIROC-ESM-CHEM, and NorESM1-M from the set of CMIP5 Bias-Correction models. We investigated Two Representative Concentration Pathway (RCP) scenarios of RCP4.5 and RCP8.5 – during the historical (1965-2005) and future (2021-2060 and 2061-2100) periods. The performance of each model was evaluated using the Taylor diagram on a seasonal scale. Among models, GFDL-ESM2M and HadGEM2-ES models showed the highest, and NorESM1-M and IPSL-CM5A-LR models showed the lowest performance in Iran. Then an ensemble model was generated using Independence Weighted Mean (IWM) method. The results of multi-model ensembles (MME) showed a higher performance compared to individual CMIP5 models in all seasons. Also, the uncertainty value was significantly reduced, and the correlation value of the MME model reached 0.95 in all seasons. Additionally, it is found that WSDI and CSU indices showed positive anomalies in future periods and CSDI and CFD showed negative anomalies throughout Iran. Also, at the end of the 21st century, no cold spells are projected in almost every part of Iran. The CSU index showed that Iran's summer days are increasing sharply, according to the results of the RCP8.5 scenario in spring (MAM) and autumn (SON), the CSU will increase by 18.79 and 20.51 days, respectively at the end of the 21st century. It is projected that in the future, the spring and autumn seasons will be shorter and, summers, will be much longer than before.

scholarly journals Sensitivity of Global Modeling Initiative chemistry and transport model simulations of radon-222 and lead-210 to input meteorological data

2005 ◽  
Vol 5 (4) ◽  
pp. 5325-5372 ◽  
Author(s):  
D. B. Considine ◽  
D. J. Bergmann ◽  
H. Liu
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Lower Stratosphere ◽  
Transport Model ◽  
Meteorological Data ◽  
Circulation Model ◽  
Convective Transport ◽  
Global Modeling ◽  
Upper Troposphere ◽  
Lead 210

Abstract. We have used the Global Modeling Initiative chemistry and transport model to simulate the radionuclides radon-222 and lead-210 using three different sets of input meteorological information: 1. Output from the Goddard Space Flight Center Global Modeling and Assimilation Office GEOS-STRAT assimilation; 2. Output from the Goddard Institute for Space Studies GISS II′ general circulation model; and 3. Output from the National Center for Atmospheric Research MACCM3 general circulation model. We intercompare these simulations with observations to determine the variability resulting from the different meteorological data used to drive the model, and to assess the agreement of the simulations with observations at the surface and in the upper troposphere/lower stratosphere region. The observational datasets we use are primarily climatologies developed from multiple years of observations. In the upper troposphere/lower stratosphere region, climatological distributions of lead-210 were constructed from ~25 years of aircraft and balloon observations compiled into the US Environmental Measurements Laboratory RANDAB database. Taken as a whole, no simulation stands out as superior to the others. However, the simulation driven by the NCAR MACCM3 meteorological data compares better with lead-210 observations in the upper troposphere/lower stratosphere region. Comparisons of simulations made with and without convection show that the role played by convective transport and scavenging in the three simulations differs substantially. These differences may have implications for evaluation of the importance of very short-lived halogen-containing species on stratospheric halogen budgets.

scholarly journals Climate variability and its impacts on runoff in the Kosasthaliyar sub-basin, India

2014 ◽  
Vol 18 (1) ◽  
pp. 45-49 ◽  
Author(s):  
Usha Balambal ◽  
B. V. Mudgal
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
General Circulation ◽  
Tamil Nadu ◽  
Climate Model ◽  
Meteorological Data ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Historical Period ◽  
Runoff Changes

<p>Research on the effect of climate variability/climate change on rainfall-runoff modeling is limited in humid tropical regions. Climate change has implications beyond the water resources sector, such as effects on agriculture and fisheries. Hence, such studies are becoming increasingly important. This study uses both historical data acquired in the field and future climate forecasts from General Circulation Model Hadley Centre Coupled Model, version 3 GCM HadCM3. These data are further downscaled using third generation of the Hadley Centre's regional climate model (HadRM3), with Providing REgional Climates for Impacts Studies (PRECIS) software under the three Quantifying Uncertainties in Model Projections (QUMPs). A horizontal resolution of 25 km X 25 km is used by the Centre for Climate Change and Adaptation Research, Anna University Chennai, for the state of Tamil Nadu. These downscaled data are used to study runoff changes due to climate change for the Kosasthaliyar sub-basin in South India. A trend analysis of the hydro-meteorological data for the sub-basin indicates that future rainfall is expected to decrease by approximately 10%, while the mean temperatures will increase by the year 2100. The runoff changes from 2011 to 2040 do not differ from those of the historical period of 1971 to 2000. This study is one of the first attempts to provide information on climate variability and its impacts on runoff in the Kosasthaliyar sub-basin.</p><p> </p><p><strong>Resumen</strong></p><div class="page" title="Page 1"><div class="section"><div class="layoutArea"><div class="column"><p><span>La investigación del efecto variabilidad climática/cambio climático en el modelo pluviosidad/escorrentía es limitada en regiones tropicales húmedas, donde el cambio climático tiene implicaciones tanto en los recursos acuíferos, como </span><span>en la agricultura y la pesca. Por lo tanto este tipo de estudios han incrementado su importancia. Este estudio utiliza tanto los datos adquiridos en este campo como las predicciones climáticas del Modelo General de Circulación de la Célula de Hadley, en su versión 3GCM HadCM3. Estos datos fueron reducidos luego al utilizar la tercera generación del modelo climático regional del Centro Hadley (HadRM3), con el programa de Estipulación de Climas Regionales para Estudios de Impacto (PRECIS, en inglés), bajo los tres modelos de Cuantificación de la Incertidumbre en Proyecciones (QUMPs, en inglés). El Centro para el Cambio Climático y la Investigación de Adaptación de la Universidad Anna, de Chennai, en el estado Tamil Nadu, utiliza una escala horizontal de 25 kilómetros por 25 kilómetros. Esta reducción de datos se utiliza para estudiar los cambios de escorrentía por el cambio climático en la subcuenca de Kosasthaliyar, al sur de la India. Un análisis de tendencia de los datos hidrometeorológicos en la subcuenca indica que en el futuro la pluviosidad caerá en un 10 %, mientras que la temperatura media se incrementará para el año 2100. Los cambios de escorrentía para el período 2011-2040 no difieren de los del período 1971-2000. Este estudio es uno de los primeros acercamientos para proveer información sobre la variabilidad climática y sus </span><span>impactos en la escorrentía de la subcuenca de Khosastaliyar. </span></p></div></div></div></div>

scholarly journals Sensitivity of Global Modeling Initiative chemistry and transport model simulations of radon-222 and lead-210 to input meteorological data

2005 ◽  
Vol 5 (12) ◽  
pp. 3389-3406 ◽  
Author(s):  
D. B. Considine ◽  
D. J. Bergmann ◽  
H. Liu
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Lower Stratosphere ◽  
Transport Model ◽  
Meteorological Data ◽  
Circulation Model ◽  
Convective Transport ◽  
Global Modeling ◽  
Upper Troposphere ◽  
Lead 210

Abstract. We have used the Global Modeling Initiative chemistry and transport model to simulate the radionuclides radon-222 and lead-210 using three different sets of input meteorological information: 1. Output from the Goddard Space Flight Center Global Modeling and Assimilation Office GEOS-STRAT assimilation; 2. Output from the Goddard Institute for Space Studies GISS II' general circulation model; and 3. Output from the National Center for Atmospheric Research MACCM3 general circulation model. We intercompare these simulations with observations to determine the variability resulting from the different meteorological data used to drive the model, and to assess the agreement of the simulations with observations at the surface and in the upper troposphere/lower stratosphere region. The observational datasets we use are primarily climatologies developed from multiple years of observations. In the upper troposphere/lower stratosphere region, climatological distributions of lead-210 were constructed from ~25 years of aircraft and balloon observations compiled into the US Environmental Measurements Laboratory RANDAB database. Taken as a whole, no simulation stands out as superior to the others. However, the simulation driven by the NCAR MACCM3 meteorological data compares better with lead-210 observations in the upper troposphere/lower stratosphere region. Comparisons of simulations made with and without convection show that the role played by convective transport and scavenging in the three simulations differs substantially. These differences may have implications for evaluation of the importance of very short-lived halogen-containing species on stratospheric halogen budgets.

scholarly journals Incorporation of Long Term Climate Changes in Hydrological Modelling

2019 ◽  
Vol 8 (10) ◽  
pp. 4521-4526
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
General Circulation ◽  
Global Climate ◽  
Circulation Model ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Statistical Downscaling Model ◽  
Intergovernmental Panel ◽  
Statistical Relationships

One of climate change's most important concerns at the moment is its impact on hydrology as it has direct links with agriculture, vegetation, and livelihood. This study tries to analyze potential future climate change in the Kumaradhara river basin. This study involved three steps: (1) acquiring and using general circulation model (GCM) to project future global climate scenarios; (2) establishing statistical relationships between GCM data and observed data using Statistical Downscaling Model (SDSM); (3) downscaling the second generation Canadian Earth system Model (CanESM2)GCM output based on the established statistical relationship. The statistical downscaling is carried out for three scenarios used in the fifth evaluation report of the recent Intergovernmental Panel on Climate Change (IPCC) viz., Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5. The statistical downscaling Model (SDSM) results showed that the mean annual daily precipitation is altered in the basin under all the scenarios but it will be different in different time periods depending on scenarios and the basin will experience the reduced precipitation levels in summer. Also the precipitation will marginally rise in all the time slices with reference to baseline data. We can conclude from the results that this region's climate will affect future farming as the availability of water is bound to change. This study should, however, be followed up by a larger study incorporating multiple CMIP5 models such that changes in hydrological-regimes can be examined appropriately.

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