The Global Character of the Flux of Downward Longwave Radiation

2012 ◽  
Vol 25 (7) ◽  
pp. 2329-2340 ◽  
Author(s):  
Graeme L. Stephens ◽  
Martin Wild ◽  
Paul W. Stackhouse ◽  
Tristan L’Ecuyer ◽  
Seiji Kato ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Cloud Base ◽  
Climate Data ◽  
Clear Sky ◽  
Downward Longwave Radiation

Abstract Four different types of estimates of the surface downwelling longwave radiative flux (DLR) are reviewed. One group of estimates synthesizes global cloud, aerosol, and other information in a radiation model that is used to calculate fluxes. Because these synthesis fluxes have been assessed against observations, the global-mean values of these fluxes are deemed to be the most credible of the four different categories reviewed. The global, annual mean DLR lies between approximately 344 and 350 W m−2 with an error of approximately ±10 W m−2 that arises mostly from the uncertainty in atmospheric state that governs the estimation of the clear-sky emission. The authors conclude that the DLR derived from global climate models are biased low by approximately 10 W m−2 and even larger differences are found with respect to reanalysis climate data. The DLR inferred from a surface energy balance closure is also substantially smaller that the range found from synthesis products suggesting that current depictions of surface energy balance also require revision. The effect of clouds on the DLR, largely facilitated by the new cloud base information from the CloudSat radar, is estimated to lie in the range from 24 to 34 W m−2 for the global cloud radiative effect (all-sky minus clear-sky DLR). This effect is strongly modulated by the underlying water vapor that gives rise to a maximum sensitivity of the DLR to cloud occurring in the colder drier regions of the planet. The bottom of atmosphere (BOA) cloud effect directly contrast the effect of clouds on the top of atmosphere (TOA) fluxes that is maximum in regions of deepest and coldest clouds in the moist tropics.

scholarly journals Observational Evidence Linking Arctic Supercooled Liquid Cloud Biases in CESM to Snowfall Processes

2017 ◽  
Vol 30 (12) ◽  
pp. 4477-4495 ◽  
Author(s):  
Elin A. McIlhattan ◽  
Tristan S. L’Ecuyer ◽  
Nathaniel B. Miller
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Global Climate ◽  
Longwave Radiation ◽  
Supercooled Liquid ◽  
Global Climate Models ◽  
The Arctic ◽  
Community Earth System Model

Clouds are a key regulator of Earth’s surface energy balance. The presence or absence of clouds, along with their macroscale and microscale characteristics, is the primary factor modulating the amount of radiation incident on the surface. Recent observational studies in the Arctic highlight the ubiquity of supercooled liquid-containing clouds (LCCs) and their disproportionately large impact on surface melt. Global climate models (GCMs) do not simulate enough Arctic LCCs compared to observations, and thus fail to represent the surface energy balance correctly. This work utilizes spaceborne observations from NASA’s A-Train satellite constellation to explore physical processes behind LCCs and surface energy biases in the Community Earth System Model Large Ensemble (CESM-LE) project output. On average CESM-LE underestimates LCC frequency by ~18% over the Arctic, resulting in a ~20 W m−2 bias in downwelling longwave radiation (DLR) over the ~18 × 106 km2 area examined. Collocated observations of falling snow and LCCs indicate that Arctic LCCs produce precipitation ~13% of the time. Conversely, CESM-LE generates snow in ~70% of LCCs. This result indicates that the Wegener–Bergeron–Findeisen (WBF) process—the growth of ice at the expense of supercooled liquid—may be too strong in the model, causing ice to scavenge polar supercooled cloud liquid too efficiently. Ground-based observations from Summit Station, Greenland, provide further evidence of these biases on a more local scale, suggesting that CESM-LE overestimates snow frequency in LCCs by ~52% at the center of the ice sheet leading to ~21% too few LCCs and ~24 W m−2 too little DLR.

scholarly journals The Global Energy Balance as represented in CMIP6 climate models  

2021 ◽  
Author(s):  
Martin Wild
Keyword(s):  
Energy Balance ◽  
Climate Models ◽  
Longwave Radiation ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
Global Energy ◽  
Global Energy Balance ◽  
Clear Sky ◽  
Downward Longwave Radiation ◽  
Global Mean

<p>A plausible simulation of the global energy balance is a first-order requirement for a credible climate model. In the present study I investigate the representation of the global energy balance in 40 state-of-the-art global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6). In the CMIP6 multi-model mean, the magnitudes of the energy balance components are often in better agreement with recent reference estimates compared to earlier model generations  such as CMIP5 on a global mean basis. However, the inter-model spread in the representation of many of the components remains substantial, often on the order of 10-20 Wm<sup>-2</sup> globally,  except for aspects of the shortwave clear-sky budgets, which are now more consistently simulated by the CMIP6 models. The substantial inter-model spread in the simulated global mean latent heat fluxes in the CMIP6 models, exceeding 20% (18 Wm<sup>-2</sup>),  further implies also large discrepancies in their representation of the global water balance. From a historic perspective of model development over the past decades, the largest adjustments in the magnitudes of the simulated present-day global mean energy balance components occurred in the shortwave atmospheric clear-sky absorption and the surface downward longwave radiation. Both components were gradually adjusted upwards over several model generations, on the order of 10 Wm<sup>-2</sup>, to reach 73 and 344 Wm<sup>-2</sup>, respectively in the CMIP6 multi-model means. Thereby, CMIP6 has become the first model generation that largely remediates long-standing model deficiencies related to an overestimation in surface downward shortwave and compensational underestimation in downward longwave radiation in its multi-model mean (Wild 2020).</p><p>Published in: Wild, M., 2020: The global energy balance as represented in CMIP6 climate models. Clim Dyn <strong>55, </strong>553–577. https://doi.org/10.1007/s00382-020-05282-7</p><p> </p>

scholarly journals A general framework for understanding the response of the water cycle to global warming over land and ocean

2013 ◽  
Vol 10 (12) ◽  
pp. 15263-15294 ◽  
Author(s):  
M. L. Roderick ◽  
F. Sun ◽  
W. H. Lim ◽  
G. D. Farquhar
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Specific Humidity ◽  
Water Vapour Content ◽  
Long Wave ◽  
Small Change

Abstract. Climate models project increases in globally averaged atmospheric specific humidity at the Clausius–Clapeyron (CC) value of around 7% K−1 whilst projections for precipitation (P) and evaporation (E) are somewhat muted at around 2% K−1. Such global projections are useful summaries but do not provide guidance at local (grid box) scales where impacts occur. To bridge that gap in spatial scale, previous research has shown that the following relation, Δ(P − E) ∝ P − E, holds for zonal averages in climate model projections. In this paper we first test whether that relation holds at grid box scales over ocean and over land. We find that the zonally averaged relation does not hold at grid box scales. We further find that the zonally averaged relation does not hold over land – it is specific to zonal averages over the ocean. As an alternative we tested whether the long-standing Budyko framework of catchment hydrology could be used to synthesise climate model projections over land. We find that climate model projections of Δ(P − E) out to the year 2100 conform closely to the Budyko framework. The analysis also revealed that climate models project little change in the net irradiance at the surface. To understand that result we examined projections of the key surface energy balance terms. In terms of global averages, we find the climate model projections are dominated by changes in only three terms of the surface energy balance; an increase in the incoming longwave irradiance while the responses are (mostly) restricted to the outgoing longwave irradiance with a small change in the evaporative flux. Because the change in outgoing longwave irradiance is a function of the change in surface temperature, we show that the precipitation sensitivity (i.e. 2% K−1) is an accurate summary of the partitioning of the greenhouse-induced surface forcing. With that we demonstrate that the precipitation sensitivity (2% K−1) is less than the CC value (7% K−1) because most of the greenhouse-induced surface forcing is partitioned into outgoing longwave irradiance (instead of evaporation). In essence, the models respond to elevated [CO2] by an increase in atmospheric water vapour content that increases the incoming long-wave irradiance at the surface. The surface response is dominated by a near equal increase in outgoing long-wave irradiance with only minor changes in other terms of the surface energy balance.

scholarly journals Prediction of the Long-Term Potential Distribution of Cryptorhynchus lapathi (L.) under Climate Change

Forests ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 5 ◽  
Author(s):  
Ya Zou ◽  
Linjing Zhang ◽  
Xuezhen Ge ◽  
Siwei Guo ◽  
Xue Li ◽  
...  
Keyword(s):  
Climate Change ◽  
North America ◽  
Potential Distribution ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Prevention Measures ◽  
Climate Data ◽  
Effective Prevention ◽  
Future Global Warming

The poplar and willow borer, Cryptorhynchus lapathi (L.), is a severe worldwide quarantine pest that causes great economic, social, and ecological damage in Europe, North America, and Asia. CLIMEX4.0.0 was used to study the likely impact of climate change on the potential global distribution of C. lapathi based on existing (1987–2016) and predicted (2021–2040, 2041–2080, and 2081–2100) climate data. Future climate data were simulated based on global climate models from Coupled Model Inter-comparison Project Phase 5 (CMIP5) under the RCP4.5 projection. The potential distribution of C. lapathi under historical climate conditions mainly includes North America, Africa, Europe, and Asia. Future global warming may cause a northward shift in the northern boundary of potential distribution. The total suitable area would increase by 2080–2100. Additionally, climatic suitability would change in large regions of the northern hemisphere and decrease in a small region of the southern hemisphere. The projected potential distribution will help determine the impacts of climate change and identify areas at risk of pest invasion in the future. In turn, this will help design and implement effective prevention measures for expanding pest populations, using natural enemies, microorganisms, and physical barriers in very favorable regions to impede the movement and oviposition of C. lapathi.

scholarly journals Can a coupled meteorology–chemistry model reproduce the historical trend in aerosol direct radiative effects over the Northern Hemisphere?

2015 ◽  
Vol 15 (17) ◽  
pp. 9997-10018 ◽  
Author(s):  
J. Xing ◽  
R. Mathur ◽  
J. Pleim ◽  
C. Hogrefe ◽  
C.-M. Gan ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Eastern China ◽  
Global Climate Models ◽  
Shortwave Radiation ◽  
Historical Trend ◽  
Clear Sky ◽  
Northern Pacific ◽  
Central Atlantic

Abstract. The ability of a coupled meteorology–chemistry model, i.e., Weather Research and Forecast and Community Multiscale Air Quality (WRF-CMAQ), to reproduce the historical trend in aerosol optical depth (AOD) and clear-sky shortwave radiation (SWR) over the Northern Hemisphere has been evaluated through a comparison of 21-year simulated results with observation-derived records from 1990 to 2010. Six satellite-retrieved AOD products including AVHRR, TOMS, SeaWiFS, MISR, MODIS-Terra and MODIS-Aqua as well as long-term historical records from 11 AERONET sites were used for the comparison of AOD trends. Clear-sky SWR products derived by CERES at both the top of atmosphere (TOA) and surface as well as surface SWR data derived from seven SURFRAD sites were used for the comparison of trends in SWR. The model successfully captured increasing AOD trends along with the corresponding increased TOA SWR (upwelling) and decreased surface SWR (downwelling) in both eastern China and the northern Pacific. The model also captured declining AOD trends along with the corresponding decreased TOA SWR (upwelling) and increased surface SWR (downwelling) in the eastern US, Europe and the northern Atlantic for the period of 2000–2010. However, the model underestimated the AOD over regions with substantial natural dust aerosol contributions, such as the Sahara Desert, Arabian Desert, central Atlantic and northern Indian Ocean. Estimates of the aerosol direct radiative effect (DRE) at TOA are comparable with those derived by measurements. Compared to global climate models (GCMs), the model exhibits better estimates of surface-aerosol direct radiative efficiency (Eτ). However, surface-DRE tends to be underestimated due to the underestimated AOD in land and dust regions. Further investigation of TOA-Eτ estimations as well as the dust module used for estimates of windblown-dust emissions is needed.

scholarly journals Impacts of topographic shading on direct solar radiation for valley glaciers in complex topography

2018 ◽  
Author(s):  
Matthew H. Olson ◽  
Summer B. Rupper
Keyword(s):  
Energy Balance ◽  
Solar Radiation ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Direct Solar Radiation ◽  
High Mountain ◽  
Clear Sky ◽  
Glacier Ice ◽  
North And South ◽  
Predictable Characteristics

Abstract. Topographic shading, including both shaded relief and cast shadowing, plays a fundamental role in determining direct solar radiation on glacier ice. However, this parameter has been oversimplified or incorrectly incorporated in surface energy balance models in some past studies. Here we develop a topographic solar radiation model to examine the variability in irradiance throughout the glacier melt season due to topographic shading and combined slope and aspect. We apply the model to multiple glaciers in High Mountain Asia (HMA), and test the sensitivity of shading to valley-aspect and latitude. Our results show that topographic shading significantly alters the potential direct clear-sky solar radiation received at the surface for valley glaciers in HMA, particularly for north- and south-facing glaciers. Additionally, we find that shading can be extremely impactful in the ablation zone. Cast shadowing is the dominant mechanism in determining total shading for valley glaciers in parts of HMA, especially at lower elevations. Although shading has some predictable characteristics, it is overall extremely variable between glacial valleys. Our results suggest that topographic shading is not only an important factor contributing to surface energy balance, but could also influence glacier response and mass balance estimates throughout HMA.

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

Persistence of in-stream waterholes in ephemeral rivers of tropical northern Australia and potential impacts of climate change

2014 ◽  
Vol 65 (12) ◽  
pp. 1131 ◽  
Author(s):  
David McJannet ◽  
Steve Marvanek ◽  
Anne Kinsey-Henderson ◽  
Cuan Petheram ◽  
Jim Wallace
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Landsat Imagery ◽  
Global Climate Models ◽  
Aquatic Biota ◽  
Water Resource Development ◽  
Northern Australia ◽  
Climate Data ◽  
Ephemeral Rivers ◽  
Impacts Of Climate Change

Many northern Australian rivers have limited or non-existent dry season flow and rivers tend to dry to a series of pools, or waterholes, which become particularly important refugial habitat for aquatic biota during the periods between streamflow events. The present study developed techniques to identify in-stream waterholes across large and inaccessible areas of the Flinders and Gilbert catchments using Landsat imagery. Application of this technique to 400 scenes between 2003 and 2010 facilitated the identification of key waterhole refugia that are likely to persist during all years. Relationships for predicting total waterhole area from streamflow characteristics were produced for four river reaches. Using these relationships and streamflow predictions based upon climate data scaled using 15 global climate models, the potential impacts of future climate on waterhole persistence was assessed. Reductions in waterhole area of more than 60% were modelled in some years under drier scenarios and this represents a large reduction in available habitat for areas that already have limited in-stream refugia. Conversely, under wetter future climates the total area of waterholes increased. The approach developed here has applicability in other catchments, both in Australia and globally, and for assessing the impacts of changed flow resulting from water resource development.

Internal variability and unforced trends of all-sky and clear-sky SSR: quantitative estimates using CMIP6

2021 ◽  
Author(s):  
Boriana Chtirkova ◽  
Doris Folini ◽  
Lucas Ferreira Correa ◽  
Martin Wild
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Grid Cell ◽  
Internal Variability ◽  
Global Climate Models ◽  
Geographical Region ◽  
Positive Trend ◽  
Surface Solar Radiation ◽  
Anthropogenic Effect ◽  
Clear Sky

<p>Quantifying trends in surface solar radiation (SSR) of unforced simulations is of substantial importance when one tries to quantify the anthropogenic effect in forced trends, as the net effect may be dampened or amplified by the internal variability of the system. In our analysis, we consider trends on different temporal scales (10, 30, 50 and 100 years) from 58 global climate models, participating in the Coupled Model Intercomparison Project - Phase 6 (CMIP6). We calculate the trends at the grid-box level for all-sky and clear-sky SSR using annual mean data of the multi-century pre-industrial control (piControl) experiments. The trends from both variables are found to depend strongly on the geographical region, as the most pronounced trends of the all-sky variable are observed in the Tropical Pacific, while the largest clear-sky trends are found in the large desert regions. Inspecting for each grid cell the statistical distribution of occurring N-year trends  shows that they are normally distributed in the majority of grid cells for both all-sky and clear-sky SSR. The 75-th percentile taken from these distributions (i.e. a positive trend with a 25 % chance of occurrence) varies with geographical region, taking values in the ranges 0.79 - 12.03 Wm<sup>-2</sup>/decade for 10-year trends, 0.15 - 2.05 Wm<sup>-2</sup>/decade for 30-year trends, 0.07 - 0.92 Wm<sup>-2</sup>/decade for 50-year trends and 0.02 - 0.29 Wm<sup>-2</sup>/decade for 100-year trends for all-sky SSR. The unforced trends become less significant on longer timescales – the trend medians, corresponding to the above ranges, are 3.18 Wm<sup>-2</sup>/decade, 0.62 Wm<sup>-2</sup>/decade, 0.29 Wm<sup>-2</sup>/decade, 0.10 Wm<sup>-2</sup>/decade respectively. The trends for clear-sky SSR are found to differ from the all-sky SSR by a factor of 0.16 on average, independent of the trend length. The model spread becomes greater at longer trend timescales, the differences being more substantial between large model families rather than between individual models. To elucidate the dominant causes of variability in different regions, we examine the correlations of the SSR variables with ambient aerosol optical thickness at 550 nm, atmosphere mass content of water vapour, cloud area fraction and albedo.</p>

scholarly journals A Comprehensive Intermediate-Term Drought Evaluation System and Evaluation of Climate Data Products over the Conterminous United States

2021 ◽  
Author(s):  
Zeyu Xue ◽  
Paul Ullrich
Keyword(s):  
Evaluation System ◽  
Climate Models ◽  
Global Climate ◽  
Statistical Significance ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Statistical Hypothesis ◽  
Climate Data ◽  
Statistical Hypothesis Testing

AbstractClimate models are frequently-used tools for adaptation planning in light of future uncertainty. However, not all climate models are equally trustworthy, and so model biases must be assessed to select models suitable for producing credible projections. Drought is a well-known and high-impact form of extreme weather, and knowledge of its frequency, intensity, and duration key for regional water management plans. Droughts are also difficult to assess in climate datasets, due to the long duration per event, relative to the length of a typical simulation. Therefore, there is a growing need for a standardized suite of metrics addressing how well models capture this phenomenon. In this study, we present a widely applicable set of metrics for evaluating agreement between climate datasets and observations in the context of drought. Two notable advances are made in our evaluation system: First, statistical hypothesis testing is employed for normalization of individual scores against the threshold for statistical significance. And second, within each evaluation region and dataset, principal feature analysis is used to select the most descriptive metrics among 11 metrics that capture essential features of drought. Our metrics package is applied to three characteristically distinct regions in the conterminous US and across several commonly employed climate datasets (CMIP5/6, LOCA and CORDEX). As a result, insights emerge into the underlying drivers of model bias in global climate models, regional climate models, and statistically downscaled models.

Sign in / Sign up

Export Citation Format

Share Document