Surface temperature sensitivities in a multiple cloud radiative-convective model with a constant and pressure dependent critical lapse rate

Tellus ◽  
1982 ◽  
Vol 34 (2) ◽  
pp. 203-208 ◽  
Author(s):  
John R. Hummel
Keyword(s):  
Surface Temperature ◽  
Lapse Rate ◽  
Convective Model

scholarly journals A New Methodology for Estimating the Surface Temperature Lapse Rate Based on Grid Data and Its Application in China

2018 ◽  
Vol 10 (10) ◽  
pp. 1617 ◽  
Author(s):  
Yun Qin ◽  
Guoyu Ren ◽  
Tianlin Zhai ◽  
Panfeng Zhang ◽  
Kangmin Wen
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
North China ◽  
Seasonal Pattern ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Vertical Gradient ◽  
Lapse Rate ◽  
Grid Data ◽  
Temperature Lapse Rate

Land surface temperature (LST) is an important parameter in the study of the physical processes of land surface. Understanding the surface temperature lapse rate (TLR) can help to reveal the characteristics of mountainous climates and regional climate change. A methodology was developed to calculate and analyze land-surface TLR in China based on grid datasets of MODIS LST and digital elevation model (DEM), with a formula derived on the basis of the analysis of the temperature field and the height field, an image enhancement technique used to calculate gradient, and the fuzzy c-means (FCM) clustering applied to identify the seasonal pattern of the TLR. The results of the analysis through the methodology showed that surface temperature vertical gradient inversion widely occurred in Northeast, Northwest, and North China in winter, especially in the Xinjiang Autonomous Region, the northern and the western parts of the Greater Khingan Mountains, the Lesser Khingan Mountains, and the northern area of Northwest and North China. Summer generally witnessed the steepest TLR among the four seasons. The eastern Tibetan Plateau showed a distinctive seasonal pattern, where the steepest TLR happened in winter and spring, with a shallower TLR in summer. Large seasonal variations of TLR could be seen in Northeast China, where there was a steep TLR in spring and summer and a strong surface temperature vertical gradient inversion in winter. The smallest seasonal variation of TLR happened in Central and Southwest China, especially in the Ta-pa Mountains and the Qinling Mountains. The TLR at very high altitudes (>5 km) was usually steeper than at low altitudes, in all months of the year.

scholarly journals Model-dependence of the CO<sub>2</sub> threshold for melting the hard Snowball Earth

2011 ◽  
Vol 7 (1) ◽  
pp. 17-25 ◽  
Author(s):  
Y. Hu ◽  
J. Yang ◽  
F. Ding ◽  
W. R. Peltier
Keyword(s):  
Surface Temperature ◽  
Greenhouse Effect ◽  
Surface Albedo ◽  
Snowball Earth ◽  
Pressure Broadening ◽  
Near Surface ◽  
Induced Absorption ◽  
Cloud Forcing ◽  
Clear Sky ◽  
Convective Model

Abstract. One of the critical issues of the Snowball Earth hypothesis is the CO2 threshold for triggering the deglaciation. Using Community Atmospheric Model version 3.0 (CAM3), we study the problem for the CO2 threshold. Our simulations show large differences from previous results (e.g. Pierrehumbert, 2004, 2005; Le Hir et al., 2007). At 0.2 bars of CO2, the January maximum near-surface temperature is about 268 K, about 13 K higher than that in Pierrehumbert (2004, 2005), but lower than the value of 270 K for 0.1 bar of CO2 in Le Hir et al. (2007). It is found that the difference of simulation results is mainly due to model sensitivity of greenhouse effect and longwave cloud forcing to increasing CO2. At 0.2 bars of CO2, CAM3 yields 117 Wm−2 of clear-sky greenhouse effect and 32 Wm−2 of longwave cloud forcing, versus only about 77 Wm−2 and 10.5 Wm−2 in Pierrehumbert (2004, 2005), respectively. CAM3 has comparable clear-sky greenhouse effect to that in Le Hir et al. (2007), but lower longwave cloud forcing. CAM3 also produces much stronger Hadley cells than that in Pierrehumbert (2005). Effects of pressure broadening and collision-induced absorption are also studied using a radiative-convective model and CAM3. Both effects substantially increase surface temperature and thus lower the CO2 threshold. The radiative-convective model yields a CO2 threshold of about 0.21 bars with surface albedo of 0.663. Without considering the effects of pressure broadening and collision-induced absorption, CAM3 yields an approximate CO2 threshold of about 1.0 bar for surface albedo of about 0.6. However, the threshold is lowered to 0.38 bars as both effects are considered.

A new approach for modeling near surface temperature lapse rate based on normalized land surface temperature data

2020 ◽  
Vol 242 ◽  
pp. 111746 ◽  
Author(s):  
Mohammad Karimi Firozjaei ◽  
Solmaz Fathololoumi ◽  
Seyed Kazem Alavipanah ◽  
Majid Kiavarz ◽  
Ali Reza Vaezi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temperature Data ◽  
Lapse Rate ◽  
Near Surface ◽  
New Approach ◽  
Temperature Lapse Rate ◽  
Surface Temperature Data

scholarly journals Anthropogenic and Natural Radiative Forcing: Positive Feedbacks

2018 ◽  
Vol 6 (4) ◽  
pp. 146 ◽  
Author(s):  
Jean-Louis Pinault
Keyword(s):  
Surface Temperature ◽  
Radiative Forcing ◽  
Rossby Waves ◽  
Temperature Response ◽  
Heat Fluxes ◽  
Lapse Rate ◽  
Positive Feedbacks ◽  
Long Period ◽  
Sea Surface Temperature Anomalies ◽  
The Impact

This article is based on recent work intended to estimate the impact of solar forcing mediated by long-period ocean Rossby waves that are resonantly forced—the ‘Gyral Rossby Waves’ (GRWs). Here, we deduce both the part of the anthropogenic and climate components within the instrumental surface temperature spatial patterns. The natural variations in temperature are estimated from a weighted sum of sea surface temperature anomalies in preselected areas of subtropical gyres representative of long-period GRWs. The temperature response to anthropogenic forcing is deduced by subtracting the climate component from the instrumental temperature. Depending on whether the inland regions are primarily impacted by latent or sensible heat fluxes from the oceans, positive feedbacks occur. This suggests that the lapse rate and the high troposphere cloud cover have a driving role in the amplification effect of anthropogenic climate forcing, while specifying the involved mechanisms.

scholarly journals The Key Physical Parameters Governing Frictional Dissipation in a Precipitating Atmosphere

2013 ◽  
Vol 70 (9) ◽  
pp. 2916-2929 ◽  
Author(s):  
A. M. Makarieva ◽  
V. G. Gorshkov ◽  
A. V. Nefiodov ◽  
D. Sheil ◽  
A. D. Nobre ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Atmospheric Circulation ◽  
Lapse Rate ◽  
Small Scale ◽  
Dynamic Power ◽  
True Value ◽  
Frictional Dissipation ◽  
The Mean ◽  
Degree Of Condensation ◽  
The Tropics

Abstract Precipitation generates small-scale turbulent air flows—the energy of which ultimately dissipates to heat. The power of this process has previously been estimated to be around 2–4 W m−2 in the tropics: a value comparable in magnitude to the dynamic power of global atmospheric circulation. Here it is suggested that the true value is approximately half the value of this previous estimate. The result reflects a revised evaluation of the mean precipitation pathlength HP. The dependence of HP on surface temperature, relative humidity, temperature lapse rate, and degree of condensation in the ascending air were investigated. These analyses indicate that the degree of condensation, defined as the relative change of the saturated water vapor mixing ratio in the region of condensation, is a major factor determining HP. From this theory the authors develop an estimate indicating that the mean large-scale rate of frictional dissipation associated with total precipitation in the tropics lies between 1 and 2 W m−2 and show empirical evidence in support of this estimate. Under terrestrial conditions frictional dissipation is found to constitute a minor fraction of the dynamic power of condensation-induced atmospheric circulation, which is estimated to be at least 2.5 times larger. However, because HP increases with increasing surface temperature Ts, the rate of frictional dissipation would exceed the power of condensation-induced dynamics, and thus block major circulation, at Ts ≳ 320 K in a moist adiabatic atmosphere.

scholarly journals Climate Forcings and Climate Sensitivities Diagnosed from Coupled Climate Model Integrations

2006 ◽  
Vol 19 (23) ◽  
pp. 6181-6194 ◽  
Author(s):  
Piers Mde F. Forster ◽  
Karl E. Taylor
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
Climate Forcing ◽  
Lapse Rate ◽  
Climate Feedback ◽  
Short Time Scale ◽  
Climate Change Scenarios ◽  
Climate Forcings

Abstract A simple technique is proposed for calculating global mean climate forcing from transient integrations of coupled atmosphere–ocean general circulation models (AOGCMs). This “climate forcing” differs from the conventionally defined radiative forcing as it includes semidirect effects that account for certain short time scale responses in the troposphere. First, a climate feedback term is calculated from reported values of 2 × CO2 radiative forcing and surface temperature time series from 70-yr simulations by 20 AOGCMs. In these simulations carbon dioxide is increased by 1% yr−1. The derived climate feedback agrees well with values that are diagnosed from equilibrium climate change experiments of slab-ocean versions of the same models. These climate feedback terms are associated with the fast, quasi-linear response of lapse rate, clouds, water vapor, and albedo to global surface temperature changes. The importance of the feedbacks is gauged by their impact on the radiative fluxes at the top of the atmosphere. Partial compensation is found between longwave and shortwave feedback terms that lessens the intermodel differences in the equilibrium climate sensitivity. There is also some indication that the AOGCMs overestimate the strength of the positive longwave feedback. These feedback terms are then used to infer the shortwave and longwave time series of climate forcing in twentieth- and twenty-first-century simulations in the AOGCMs. The technique is validated using conventionally calculated forcing time series from four AOGCMs. In these AOGCMs the shortwave and longwave climate forcings that are diagnosed agree with the conventional forcing time series within ∼10%. The shortwave forcing time series exhibit order of magnitude variations between the AOGCMs, differences likely related to how both natural forcings and/or anthropogenic aerosol effects are included. There are also factor of 2 differences in the longwave climate forcing time series, which may indicate problems with the modeling of well-mixed greenhouse gas changes. The simple diagnoses presented provides an important and useful first step for understanding differences in AOGCM integrations, indicating that some of the differences in model projections can be attributed to different prescribed climate forcing, even for so-called standard climate change scenarios.

scholarly journals MODELING THE IMPACT OF SURFACE CHARACTERISTICS ON THE NEAR SURFACE TEMPERATURE LAPSE RATE

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 395-399 ◽  
Author(s):  
M. K. Firozjaei ◽  
S. Fathololuomi ◽  
S. K. Alavipanah ◽  
M. Kiavarz ◽  
A. Vaezi ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Feature Space ◽  
Surface Characteristics ◽  
Lapse Rate ◽  
Landsat 8 ◽  
Near Surface ◽  
Temperature Lapse Rate ◽  
Topographic Characteristics ◽  
The Impact

Abstract. Modeling of Near-Surface Temperature Lapse Rate (NSTLR) is very important in various environmental applications. The Land Surface Temperature (LST) is influenced by many properties and conditions including surface biophysical and topographic characteristics. Some researches have considered the LST - Digital Elevation Model (DEM) feature space to model NSTLR. However, the influence of detailed surface characteristics is rare. This study investigated the impact of surface characteristics on the LST-DEM feature space for NSTLR modeling. A set of remote sensing data including Landsat 8 images, MODIS products, and surface features including DEM and land use of the Balikhli-Chay on 01/07/2018, 18/08/2018 and 03/09/2018 were collected and used in this study. First, Split Window (SW) algorithm was used to estimate LST, and spectral indices were employed to model surface biophysical characteristics. Owing to the impact of surface biophysical and topographic characteristics on the LST-DEM feature space, the NSTLR was calculated for different classes of surface biophysical characteristics, land use, and solar local incident angle. The modeled NSTLR values based on the LST-DEM feature space on 01/07/2018, 18/08/2018 and 03/09/2018 were 8.5, 1.5 and 2.4 °C Km−1; respectively. The NSTLR in different classes of surface biophysical characteristics, land use type and topographical parameters were variable between 0.5 to 14 °C Km−1. This clearly showed the dependence of NSTLR on topographic and biophysical conditions. This provides a new way of calculating surface characteristic specific NSTLR.

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