Solar radiation absorption by CO2, overlap with H2O, and a parameterization for general circulation models

1993 ◽  
Vol 98 (D4) ◽  
pp. 7255-7264 ◽  
Author(s):  
S. M. Freidenreich ◽  
V. Ramaswamy
2008 ◽  
Vol 65 (7) ◽  
pp. 2448-2457 ◽  
Author(s):  
Tarek Ayash ◽  
Sunling Gong ◽  
Charles Q. Jia

Abstract Proper quantification of the solar radiation budget and its transfer within the atmosphere is of utmost importance in climate modeling. The delta-four-stream (DFS) approximation has been demonstrated to offer a more accurate computational method of quantifying the budget than the simple two-stream approximations widely used in general circulation models (GCMs) for radiative-transfer computations. Based on this method, the relative improvement in the accuracy of solar flux computations is investigated in the simulations of the third-generation Canadian Climate Center atmosphere GCM. Relative to the computations of the DFS-modified radiation scheme, the GCM original-scheme whole-sky fluxes at the top of the atmosphere (TOA) show the largest underestimations at high latitudes of a winter hemisphere on the order of 4%–6% (monthly means), while the largest overestimations of the same order are found over equatorial regions. At the surface, even higher overestimations are found, exceeding 20% at subpolar regions of a winter hemisphere. Flux differences between original and DFS schemes are largest in the tropics and at high latitudes, where the monthly zonal means and their dispersions are within 5 W m−2 at the TOA and 10 W m−2 at the surface in whole sky, but differences may be as large as 20 and −40 W m−2. In clear sky, monthly zonal means and their dispersions remain within 2 W m−2, but may be as large as 25 and −12 W m−2. Such differences are found to be mostly determined by variations in cloud optical depth and solar zenith angle, and by aerosol loading in a clear sky.


2005 ◽  
Vol 360 (1463) ◽  
pp. 2095-2108 ◽  
Author(s):  
Christian Baron ◽  
Benjamin Sultan ◽  
Maud Balme ◽  
Benoit Sarr ◽  
Seydou Traore ◽  
...  

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level.


2020 ◽  
Vol 1 (2) ◽  
pp. 635-655
Author(s):  
Jack Giddings ◽  
Adrian J. Matthews ◽  
Nicholas P. Klingaman ◽  
Karen J. Heywood ◽  
Manoj Joshi ◽  
...  

Abstract. Chlorophyll absorbs solar radiation in the upper ocean, increasing the mixed layer radiative heating and sea surface temperatures (SST). Although the influence of chlorophyll distributions in the Arabian Sea on the southwest monsoon has been demonstrated, there is a current knowledge gap regarding how chlorophyll distributions in the Bay of Bengal influence the southwest monsoon. The solar absorption caused by chlorophyll can be parameterized as an optical parameter, h2, which expresses the scale depth of the absorption of blue light. Seasonally and spatially varying h2 fields in the Bay of Bengal were imposed in a 30-year simulation using an atmospheric general circulation model coupled to a mixed layer thermodynamic ocean model in order to investigate the effect of chlorophyll distributions on regional SST, the southwest monsoon circulation, and precipitation. There are both direct local upper-ocean effects, through changes in solar radiation absorption, and indirect remote atmospheric responses. The depth of the mixed layer relative to the perturbed solar penetration depths modulates the response of the SST to chlorophyll. The largest SST response of 0.5 ∘C to chlorophyll forcing occurs in coastal regions, where chlorophyll concentrations are high (> 1 mg m−3), and when climatological mixed layer depths shoal during the inter-monsoon periods. Precipitation increases significantly (by up to 3 mm d−1) across coastal Myanmar during the southwest monsoon onset and over northeast India and Bangladesh during the Autumn inter-monsoon period, decreasing model biases.


Author(s):  
S. Gray ◽  
S. Jackson ◽  
K. Taylor ◽  
C. Palmer ◽  
C. Fastie

There are few other regions where the influence of climate on basic ecosystem attributes has been as well documented as the Greater Yellowstone Ecosystem (GYE). Research has shown that elk, bison, and grizzly bear populations in the GYE are tightly linked to annual climate variation (Meagher 1976, Picton 1978). Authors have shown that the distribution of vegetation types in Grand Teton and Yellowstone National Parks is influenced by the seasonality of precipitation (Despain 1987, 1990). Natural disturbances, especially fires and insect outbreaks, are also known to coincide with specific climate scenarios in this region (Knight 1987, Balling et al. 1992). Therefore, understanding how climate can vary over time is essential for the proper management of these areas (Luckman 1996). Modem instrumental records have contributed greatly to our understanding of the current GYE climate system. In particular, work by Mock (1996) and Bartlein et al. (1997) has demonstrated how local manifestations of large-scale circulation patterns produce distinct climates within the GYE. In addition, studies using modem climate records and General Circulation Models by Balling et al. (1992) and Bartlein et al. (1997) have identified trends toward increasing aridity in the GYE and the potential for these trends to continue well into the future. Late Pleistocene and Holocene (18-1 kya) climate in the GYE is known mainly from lake­sediment cores. Work by Whitlock (1993), Whitlock and Bartlein (1993), and Thompson et al. (1993) indicates that after deglaciation, increased solar radiation during summer months led to a highly seasonal climate regime. As levels of solar radiation changed through the Holocene, GYE climate became increasingly more like today until the modem regime became established around 1500-1600 AD (Whitlock 1993, Elias 1997). While existing modem and paleoecological studies reveal important aspects of the GYE climate system, there is a distinct lack of high-resolution data for most of the last millennium. Lake sediments only record climate variation at a resolution of hundreds to thousands of years, and instrumental records do not exist before the 1890s. Dendroclimatology, the study of climate using patterns of tree-ring growth (Fritts 1976) is particularly well suited to fill this gap in our knowledge of GYE climate. Tree-rings have been used successfully for climate reconstructions worldwide, offer records spanning decades to millennia, and can provide annual resolution. Therefore, we are developing a network of tree-ring sites in the western Absaroka Mountains and eastern Bighorn Basin to fill important spatial (areas east of Yellowstone NP) and temporal (high resolution for the past 700-1,000+year) gaps in our knowledge of GYE climate.


2008 ◽  
Vol 21 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Soon-Il An ◽  
Jong-Seong Kug ◽  
Yoo-Geun Ham ◽  
In-Sik Kang

Abstract The multidecadal modulation of the El Niño–Southern Oscillation (ENSO) due to greenhouse warming has been analyzed herein by means of diagnostics of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs) and the eigenanalysis of a simplified version of an intermediate ENSO model. The response of the global-mean troposphere temperature to increasing greenhouse gases is more likely linear, while the amplitude and period of ENSO fluctuates in a multidecadal time scale. The climate system model outputs suggest that the multidecadal modulation of ENSO is related to the delayed response of the subsurface temperature in the tropical Pacific compared to the response time of the sea surface temperature (SST), which would lead a modulation of the vertical temperature gradient. Furthermore, an eigenanalysis considering only two parameters, the changes in the zonal contrast of the mean background SST and the changes in the vertical contrast between the mean surface and subsurface temperatures in the tropical Pacific, exhibits a good agreement with the CGCM outputs in terms of the multidecadal modulations of the ENSO amplitude and period. In particular, the change in the vertical contrast, that is, change in difference between the subsurface temperature and SST, turns out to be more influential on the ENSO modulation than changes in the mean SST itself.


2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.


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