scholarly journals Attribution of Recent Trends in Temperature Extremes over China: Role of Changes in Anthropogenic Aerosol Emissions over Asia

2019 ◽  
Vol 32 (21) ◽  
pp. 7539-7560 ◽  
Author(s):  
Wei Chen ◽  
Buwen Dong ◽  
Laura Wilcox ◽  
Feifei Luo ◽  
Nick Dunstone ◽  
...  
Keyword(s):  
Longwave Radiation ◽  
Northern China ◽  
Ocean Model ◽  
Shortwave Radiation ◽  
Temperature Extremes ◽  
Historical Trends ◽  
Anthropogenic Aerosol ◽  
Clear Sky ◽  
Emission Changes ◽  
Cold Extremes

ABSTRACT Observations indicate large changes in temperature extremes over China during the last four decades, exhibiting as significant increases in the amplitude and frequency of hot extremes and decreases in the amplitude and frequency of cold extremes. An ensemble of transient experiments with the fully coupled atmosphere–ocean model HadGEM3-GC2, including both anthropogenic forcing and natural forcing, successfully reproduces the spatial pattern and magnitude of observed historical trends in both hot and cold extremes. The model-simulated trends in temperature extremes primarily come from the positive trends in clear-sky longwave radiation, which is mainly due to the increases in greenhouse gases (GHGs). An ensemble of sensitivity experiments with Asian anthropogenic aerosol (AA) emissions fixed at their 1970s levels tends to overestimate the trends in temperature extremes, indicating that local AA emission changes have moderated the trends in these temperature extremes over China. The recent increases in Asian AA drive cooling trends over China by inducing negative clear-sky shortwave radiation directly through the aerosol–radiation interaction, which partly offsets the strong warming effect by GHG changes. The cooling trends induced by Asian AA changes are weaker over northern China during summer, which is due to the warming effect by the positive shortwave cloud radiative effect through the AA-induced atmosphere–cloud feedback. This accounts for the observed north–south gradients of the historical trends in some temperature extremes over China, highlighting the importance of local Asian AA emission changes on spatial heterogeneity of trends in temperature extremes.

Decomposing local and remote surface temperature impacts of Asian aerosols

2021 ◽  
Author(s):  
Joonas Merikanto ◽  
Kalle Nordling ◽  
Petri Räisänen ◽  
Jouni Räisänen ◽  
Declan O'Donnell ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Energy Transport ◽  
East Asian ◽  
Temperature Response ◽  
Longwave Radiation ◽  
Shortwave Radiation ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
Clear Sky ◽  
Temperature Responses

<p>We investigate how a regionally confined radiative forcing of South and East Asian aerosols translate into local and remote surface temperature responses across the globe. To do so, we carry out equilibrium climate simulations with and without modern day South and East Asian anthropogenic aerosols in two climate models with independent development histories (ECHAM6.1 and NorESM1).  We run the models with the same anthropogenic aerosol representations via MACv2-SP (a simple plume implementation of the 2<sup>nd</sup> version of the Max Planck Institute Aerosol Climatology). This leads to a near identical change in instantaneous direct and indirect aerosol forcing due to removal of Asian aerosols in the two models. We then robustly decompose and compare the energetic pathways that give rise to the global and regional surface temperature effects in the models by a novel temperature response decomposition method, which translated the changes in atmospheric and surface energy fluxes into surface temperature responses by using a concept of planetary emissivity.  </p><p>We find that the removal of South and East Asian anthropogenic aerosols leads to strong local warming  response from increased clear-sky shortwave radiation over the region, combined with opposing warming and cooling responses due to changes in cloud longwave and shortwave radiation. However, the local warming response is strongly modulated by the changes in horizontal atmospheric energy transport. Atmospheric energy transport and changes in clear-sky longwave radiation redistribute the surface temperature responses efficiently across the Northern hemisphere, and to a lesser extent also over the Southern hemisphere. The model-mean global surface temperature response to Asian anthropogenic aerosol removal is 0.26±0.04 °C (0.22±0.03 for ECHAM6.1 and 0.30±0.03 °C for NorESM1) of warming. Model-to-model differences in global surface temperature response mainly arise from differences in longwave cloud (0.01±0.01 for ECHAM6.1 and 0.05±0.01 °C for NorESM1) and shortwave cloud (0.03±0.03 for ECHAM6.1 and 0.07±0.02 °C for NorESM1) responses. The differences in cloud responses between the models also dominate the differences in regional temperature responses. In both models, the Northern hemispheric surface warming amplifies towards the Arctic, where the total temperature response is highly seasonal and modulated by seasonal changes in oceanic heat exchange and clear-sky longwave radiation.</p><p>We estimate that under a strong Asian aerosol mitigation policy tied with strong greenhouse gas mitigation (Shared Socioeconomic Pathway 1-1.9) the Asian aerosol reductions can add around 8 years’ worth of current day global warming during the next few decades.</p>

scholarly journals Estimation of Net Radiation using satellite based data inputs

2014 ◽  
Vol XL-8 ◽  
pp. 307-313 ◽  
Author(s):  
S. V. S. Sai Krishna ◽  
P. Manavalan ◽  
P. V. N. Rao
Keyword(s):  
Outgoing Longwave Radiation ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Net Radiation ◽  
Clear Sky ◽  
Statistical Measures ◽  
Indian Land ◽  
Radiation Fluxes

Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r<sup>2</sup> values of the order of 0.7 and RMS errors of the order of 8&ndash;16 w/m<sup>2</sup>.

Longwave Radiation Corrections for the OMNI Buoy Network

2021 ◽  
Keyword(s):  
Indian Ocean ◽  
Longwave Radiation ◽  
Field Measurements ◽  
North Indian Ocean ◽  
Shortwave Radiation ◽  
Data Logger ◽  
Clear Sky ◽  
The Difference ◽  
Radiation Measurements ◽  
Moored Buoy

Abstract The inception of a moored buoy network in the northern Indian Ocean in 1997 paved the way for systematic collection of longterm time series observations of meteorological and oceanographic parameters. This buoy network was revamped in 2011 with OMNI (Ocean Moored buoy Network for north Indian Ocean) buoys fitted with additional sensors to better quantify the air-sea fluxes. An inter-comparison of OMNI buoy measurements with the nearby WHOI mooring during the year 2015 revealed an overestimation of downwelling longwave radiation (LWR↓). Analysis of the OMNI and WHOI radiation sensors at a test station at NIOT during 2019 revealed that the accurate and stable amplification of the thermopile voltage records along with the customized data logger in the WHOI system results in better estimations of LWR↓. The offset in NIOT measured LWR↓ is estimated firstly by segregating the LWR↓ during clear sky conditions identified using the downwelling shortwave radiation measurements from the same test station, and secondly, finding the offset by taking the difference with expected theoretical clear sky LWR↓. The corrected LWR↓ exhibited good agreement with that of collocated WHOI measurements, with a correlation of 0.93. This method is applied to the OMNI field measurements and again compared with the nearby WHOI mooring measurements, exhibiting a better correlation of 0.95. This work has led to the revamping of radiation measurements in OMNI buoys and provides a reliable method to correct past measurements and improve estimation of air-sea fluxes in the Indian Ocean.

scholarly journals Historical trends and variability of temperature extremes in two climate vulnerable regions of Bangladesh

2018 ◽  
Vol 16 (2) ◽  
pp. 283-292
Author(s):  
Khalid Mahmud ◽  
Susmita Saha ◽  
Tanvir Ahmad ◽  
Ummay Saima Satu
Keyword(s):  
Kendall Test ◽  
Daily Maximum ◽  
Temperature Extremes ◽  
Upward Trend ◽  
Historical Trends ◽  
Rate Of Increase ◽  
Hot Days ◽  
Increasing Trend ◽  
Decadal Variations ◽  
Cold Extremes

Research on temperature extremes deserves more importance because it reacts sensitively to climate change. As elsewhere across the world, Bangladesh has already become a victim of temperature extremes. Hence, this study was conducted to assess the trends and variability of 11 temperature-related extreme indices based on daily maximum (TX) and daily minimum (TN) temperature recorded at Rajshahi and Barisal over the period 1976–2015. The indices were calculated on annual basis and their average annual and decadal trends were evaluated by non-parametric Mann-Kendall test and Sen’s slope estimate. Significant (p ≤ 0.01) upward trend was observed in some of the hot extremes, such as SU35: number of days with TX > 35°C and TR25: number of days with TN > 25°C, indicating that the number of days and nights with extreme hot temperature are increasing in both sites. Significant decreasing rate (-0.308 day/year) of SU25: number of days with TX > 25°C and increasing rate (1.00 day/year) of SU35 demonstrate that moderate hot days are converting to extreme hot days at Rajshahi. All cold indices showed significant (p ≤ 0.05) variations at Rajshahi implying that cold extremes are becoming severe in this area. Significant rising trend of diurnal temperature range (DTR) indicated the higher rate of increase in TX than in TN at Rajshahi. The increasing trend of all hot indices at Barisal, close to the coast, reveals more warming in hot extremes. However, no significant trends of cold indices were observed at Barisal. Significant average decadal variations of temperature indices were only observed for hot index TNx: annual maximum TN (0.372 °C/decade) and cold index CD25: number of days with TX < 25°C (4.70 days/decade) at Rajshahi and hot index SU35 (5.650 days/decade) at Barisal. So, the relatively dry western region of the country is vulnerable to both hot and cold extremes, whereas coastal area is susceptible to only hot extremes.J. Bangladesh Agril. Univ. 16(2): 283-292, August 2018

scholarly journals Projected near-term changes in three types of heat waves over China under RCP4.5

2020 ◽  
Author(s):  
Qin Su
Keyword(s):  
Climate Models ◽  
Heat Waves ◽  
Longwave Radiation ◽  
Ocean Model ◽  
Shortwave Radiation ◽  
Minor Role ◽  
Air Temperatures ◽  
Downward Longwave Radiation ◽  
Near Term ◽  
Projected Changes

&lt;p&gt;The changes in three aspects of frequency, intensity and duration of the compound, daytime and nighttime heat waves (HWs) over China during extended summer (May&amp;#8211;September) in a future period of the mid-21&lt;sup&gt;st&lt;/sup&gt; century (FP; 2045-2055) under RCP4.5 scenario relative to present day (PD; 1994-2011) are investigated by two models, MetUM-GOML1 and MetUM-GOML2, which comprise the atmospheric components of two state-of-the-art climate models coupled to a multi-level mixed-layer ocean model. The results show that in the mid-21&lt;sup&gt;st&lt;/sup&gt; century all three types of HWs in China will occur more frequently with strengthened intensity and elongated duration relative to the PD. The compound HWs will change most dramatically, with the frequency in the FP being 4&amp;#8211;5 times that in the PD, and the intensity and duration doubling those in the PD. The changes in daytime and nighttime HWs are also remarkable, with the changes of nighttime HWs larger than those of daytime HWs. The future changes of the three types of HWs in China in two models are similar in terms of spatial patterns and area-averaged quantities, indicating these projected changes of HWs over the China under RCP4.5 scenario are robust. Further analyses suggest that projected future changes in HWs over China are determined mainly by the increase in seasonal mean surface air temperatures with change in temperature variability playing a minor role. The seasonal mean temperature increase is due to the increase in surface downward longwave radiation and surface shortwave radiation. The increase in downward longwave radiation results from the enhanced greenhouse effect and increased water vapour in the atmosphere. The increase in surface shortwave radiation is the result of the decreased aerosol emissions, via direct aerosol-radiation interaction and indirect aerosol-cloud interaction over southeastern and northeastern China, and the reduced cloud cover related to a decrease in relative humidity.&lt;/p&gt;

scholarly journals Uncertainties of parameterized near-surface downward longwave and clear-sky direct radiation

2012 ◽  
Vol 12 (1) ◽  
pp. 3357-3407 ◽  
Author(s):  
S. Gubler ◽  
S. Gruber ◽  
R. S. Purves
Keyword(s):  
Mean Squared Error ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Total Output ◽  
Parameter Uncertainties ◽  
Near Surface ◽  
Clear Sky ◽  
Environmental Models

Abstract. As many environmental models rely on simulating the energy balance at the Earth's surface based on parameterized radiative fluxes, knowledge of the inherent uncertainties is important. In this study we evaluate one parameterization of clear-sky incoming shortwave radiation (SDR) and diverse parameterizations of clear-sky and all-sky incoming longwave radiation (LDR). In a first step, the clear-sky global SDR is estimated based measured input variables and mean parameter values for hourly time steps during the year 1996 to 2008, and validated using the high quality measurements of seven Alpine Surface Radiation Budget (ASRB) stations in Switzerland covering different elevations. Then, twelve clear-sky LDR parameterizations are fitted to the ASRB measurements. One of the best performing LDR parameterizations is chosen to estimate the all-sky LDR based on cloud transmissivity. Cloud transmissivity is estimated using measured and modeled global SDR during daytime. For the night, the performance of several interpolation methods is evaluated. Input variable and parameter uncertainties are assigned to estimate the total output uncertainty of the mentioned models, resulting in a mean relative uncertainty of 10% for the clear-sky direct, 15% for diffuse and 2.5% for global SDR, and 2.5% for the fitted all-sky LDR. Further, a function representing the uncertainty in dependence of the radiation is assigned for each model. Validation of the model outputs shows that direct SDR is underestimated (the mean error (ME) is around −33 W m−2), while diffuse radiation is overestimated (ME around 19 W m−2). The root mean squared error (RMSE) scatters around 60 W m−2 for direct, and 40 W m−2 for diffuse SDR. The best behaviour is found, due to the compensating effects of direct and diffuse SDR, for global SDR with MEs around −13 W m−2 and RMSEs around 40 W m−2. The ME of the fitted all-sky LDR is around ±10 W m−2, and the RMSE goes up to 40 W m−2. This is obtained by linearly interpolating the average of the cloud transmissivity of the four hours of the preceeding afternoon and the following morning.

scholarly journals Variability of Observed Energy Fluxes during Rain-on-Snow and Clear Sky Snowmelt in a Midlatitude Mountain Environment

2014 ◽  
Vol 15 (3) ◽  
pp. 1220-1237 ◽  
Author(s):  
J. Garvelmann ◽  
S. Pohl ◽  
M. Weiler
Keyword(s):  
Energy Balance ◽  
Longwave Radiation ◽  
Negative Energy ◽  
Spatiotemporal Variability ◽  
Shortwave Radiation ◽  
Positive Energy ◽  
Energy Fluxes ◽  
Area Index ◽  
Clear Sky ◽  
The Individual

Abstract Hourly observations of 65 snow monitoring stations were used to investigate the spatiotemporal variability of the surface energy balance during snowmelt in the Black Forest region of southwestern Germany. The study focuses on two rain-on-snow (ROS) events in December 2012 and a clear sky period at the beginning of March 2013 using the same study locations. ROS and clear sky were chosen since they are completely different snowmelt conditions in terms of energy exchanges and dynamics. The results show that snowmelt was dominated by turbulent exchanges at the open field sites and by both turbulent exchanges and net longwave radiation in the forest during ROS. The energy available for snowmelt can be almost identical at open and forest locations during ROS, and a constant energy flux even during night was directed toward the snowpack. During the clear sky conditions, net shortwave radiation was the dominating term in the open, whereas net shortwave and net longwave radiation were most important in the forest. A diurnal signal with positive energy balance during daylight and negative energy balance in the night was observed, with considerably reduced energy available for snowmelt in the forest. Furthermore, the stratified sampling design revealed the strong influence of the canopy and the topography at the locations on the observed energy fluxes. Elevation, aspect, and leaf area index (LAI) were the most important predictor variables during ROS, whereas aspect and LAI were most influential during the clear sky period. The study highlights the distinct spatial variability of the individual energy balance terms over a relatively small area during the differing snowmelt conditions.

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

scholarly journals A Simple Method for Converting 1-km Resolution Daily Clear-Sky LST into Real LST

2020 ◽  
Vol 12 (10) ◽  
pp. 1641
Author(s):  
Yunfei Zhang ◽  
Yunhao Chen ◽  
Jing Li ◽  
Xi Chen
Keyword(s):  
Land Surface ◽  
Missing Values ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Shortwave Radiation ◽  
Simple Method ◽  
The Real ◽  
Independent Variables ◽  
Clear Sky ◽  
Reconstruction Methods

Land-surface temperature (LST) plays a key role in the physical processes of surface energy and water balance from local through global scales. The widely used one kilometre resolution daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product has missing values due to the influence of clouds. Therefore, a large number of clear-sky LST reconstruction methods have been developed to obtain spatially continuous LST datasets. However, the clear-sky LST is a theoretical value that is often an overestimate of the real value. In fact, the real LST (also known as cloudy-sky LST) is more necessary and more widely used. The existing cloudy-sky LST algorithms are usually somewhat complicated, and the accuracy needs to be improved. It is necessary to convert the clear-sky LST obtained by the currently better-developed methods into cloudy-sky LST. We took the clear-sky LST, cloud-cover duration, downward shortwave radiation, albedo and normalized difference vegetation index (NDVI) as five independent variables and the real LST at the ground stations as the dependent variable to perform multiple linear regression. The mean absolute error (MAE) of the cloudy-sky LST retrieved by this method ranged from 3.5–3.9 K. We further analyzed different cases of the method, and the results suggested that this method has good flexibility. When we chose fewer independent variables, different clear-sky algorithms, or different regression tools, we also achieved good results. In addition, the method calculation process was relatively simple and can be applied to other research areas. This study preliminarily explored the influencing factors of the real LST and can provide a possible option for researchers who want to obtain cloudy-sky LST through clear-sky LST, that is, a convenient conversion method. This article lays the foundation for subsequent research in various fields that require real LST.

scholarly journals Effects of Ocean Biology on the Penetrative Radiation in a Coupled Climate Model

2006 ◽  
Vol 19 (16) ◽  
pp. 3973-3987 ◽  
Author(s):  
Patrick Wetzel ◽  
Ernst Maier-Reimer ◽  
Michael Botzet ◽  
Johann Jungclaus ◽  
Noel Keenlyside ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
Marine Biology ◽  
Climate Model ◽  
Global Climate ◽  
Ocean Model ◽  
Equatorial Pacific ◽  
Shortwave Radiation ◽  
Upper Ocean ◽  
Biogeochemical Model ◽  
Coupled Climate Model

Abstract The influence of phytoplankton on the seasonal cycle and the mean global climate is investigated in a fully coupled climate model. The control experiment uses a fixed attenuation depth for shortwave radiation, while the attenuation depth in the experiment with biology is derived from phytoplankton concentrations simulated with a marine biogeochemical model coupled online to the ocean model. Some of the changes in the upper ocean are similar to the results from previous studies that did not use interactive atmospheres, for example, amplification of the seasonal cycle; warming in upwelling regions, such as the equatorial Pacific and the Arabian Sea; and reduction in sea ice cover in the high latitudes. In addition, positive feedbacks within the climate system cause a global shift of the seasonal cycle. The onset of spring is about 2 weeks earlier, which results in a more realistic representation of the seasons. Feedback mechanisms, such as increased wind stress and changes in the shortwave radiation, lead to significant warming in the midlatitudes in summer and to seasonal modifications of the overall warming in the equatorial Pacific. Temperature changes also occur over land where they are sometimes even larger than over the ocean. In the equatorial Pacific, the strength of interannual SST variability is reduced by about 10%–15% and phase locking to the annual cycle is improved. The ENSO spectral peak is broader than in the experiment without biology and the dominant ENSO period is increased to around 5 yr. Also the skewness of ENSO variability is slightly improved. All of these changes lead to the conclusion that the influence of marine biology on the radiative budget of the upper ocean should be considered in detailed simulations of the earth’s climate.

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