The Effects of Surface Longwave Spectral Emissivity on Atmospheric Circulation and Convection over the Sahara and Sahel

AbstractThis study quantifies the impact of the inclusion of realistic surface spectral emissivity in the Sahara and Sahel on the simulated local climate and beyond. The surface emissivity in these regions can be as low as 0.6–0.7 over the infrared window band while close to unity in other spectral bands, but such spectral dependence has been ignored in current climate models. Realistic surface spectral emissivities over the Sahara and Sahel are incorporated into the Community Earth System Model (CESM) version 1.1.1, while treatments of surface emissivity for the rest of the globe remain unchanged. Both the modified and standard CESM are then forced with prescribed climatological SSTs and fixed present-day forcings for 35-yr simulations. The outputs from the last 30 years are analyzed. Compared to the standard CESM, the modified CESM has warmer surface air temperature, as well as a warmer and wetter planetary boundary layer over the Sahara and Sahel. The modified CESM thus favors more convection in these regions and has more convective rainfall, especially in the Sahara. The moisture convergence induced by such inclusion of surface spectral emissivity also contributes to the differences in simulated precipitation in the Sahel and the region south to it. Compared to observations, inclusion of surface spectral emissivity reduces surface temperature biases in the Sahara and precipitation biases in the Gulf of Guinea but exacerbates the wet biases in the Sahara. Such realistic representation of surface spectral emissivity can help unmask other factors contributing to regional biases in the original CESM.

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The impact of RCM formulation and resolution on simulated precipitation in Africa

10.5194/esd-2019-55 ◽

2019 ◽

Cited By ~ 2

Author(s):

Minchao Wu ◽

Grigory Nikulin ◽

Erik Kjellström ◽

Danijel Belušić ◽

Colin Jones ◽

...

Keyword(s):

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Horizontal Resolution ◽

Added Value ◽

Primary Control ◽

Model Formulation ◽

Simulated Precipitation ◽

Mean Climate ◽

The Impact

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs – SMHI-RCA4 and HCLIM38-ALADIN are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100 and 200 km. Additionally to the two RCMs, two different configurations of the same RCA4 are used. Contrasting different RCMs, configurations and resolutions it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle is completely controlled by model formulation (convection scheme) while its amplitude is a function of resolution. Although higher resolution in many cases leads to smaller biases in the time mean climate, the impact of higher resolution is mixed. An improvement in one region/season (e.g. reduction of dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). The experiments confirm a pronounced and well known impact of higher resolution – a more realistic distribution of daily precipitation. Even if the time-mean climate is not always greatly sensitive to resolution, what the time-mean climate is made up of, higher order statistics, is sensitive. Therefore, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and in general cannot be considered as an added value of downscaling.

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Can downwelling far-infrared radiances over Antarctica be estimated from mid-infrared information?

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-7927-2019 ◽

2019 ◽

Vol 19 (11) ◽

pp. 7927-7937

Author(s):

Christophe Bellisario ◽

Helen E. Brindley ◽

Simon F. B. Tett ◽

Rolando Rizzi ◽

Gianluca Di Natale ◽

...

Keyword(s):

Climate Models ◽

Far Infrared ◽

Mid Infrared ◽

Spectral Bands ◽

Noise Characteristics ◽

Infrared Spectral ◽

Infrared Radiances ◽

Spectrally Resolved ◽

Spectral Ranges ◽

The Impact

Abstract. Far-infrared (FIR: 100cm-1<wavenumber, ν<667 cm−1) radiation emitted by the Earth and its atmosphere plays a key role in the Earth's energy budget. However, because of a lack of spectrally resolved measurements, radiation schemes in climate models suffer from a lack of constraint across this spectral range. Exploiting a method developed to estimate upwelling far-infrared radiation from mid-infrared (MIR: 667cm-1<ν<1400 cm−1) observations, we explore the possibility of inferring zenith FIR downwelling radiances in zenith-looking observation geometry, focusing on clear-sky conditions in Antarctica. The methodology selects a MIR predictor wavenumber for each FIR wavenumber based on the maximum correlation seen between the different spectral ranges. Observations from the REFIR-PAD instrument (Radiation Explorer in the Far Infrared – Prototype for Application and Development) and high-resolution radiance simulations generated from co-located radio soundings are used to develop and assess the method. We highlight the impact of noise on the correlation between MIR and FIR radiances by comparing the observational and theoretical cases. Using the observed values in isolation, between 150 and 360 cm−1, differences between the “true” and “extended” radiances are less than 5 %. However, in spectral bands of low signal, between 360 and 667 cm−1, the impact of instrument noise is strong and increases the differences seen. When the extension of the observed spectra is performed using regression coefficients based on noise-free radiative transfer simulations the results show strong biases, exceeding 100 % where the signal is low. These biases are reduced to just a few percent if the noise in the observations is accounted for in the simulation procedure. Our results imply that while it is feasible to use this type of approach to extend mid-infrared spectral measurements to the far-infrared, the quality of the extension will be strongly dependent on the noise characteristics of the observations. A good knowledge of the atmospheric state associated with the measurements is also required in order to build a representative regression model.

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Utilization of Climate Files Predicting Future Weather in Dynamic Building Performance Simulation – A review

Journal of Physics Conference Series ◽

10.1088/1742-6596/2069/1/012070 ◽

2021 ◽

Vol 2069 (1) ◽

pp. 012070

Author(s):

C N Nielsen ◽

J Kolarik

Keyword(s):

Climate Change ◽

Climate Models ◽

Dynamical Downscaling ◽

Global Climate ◽

Global Climate Models ◽

Weather Data ◽

Building Performance ◽

Comprehensive Overview ◽

Local Climate ◽

The Impact

Abstract As the climate is changing and buildings are designed with a life expectancy of 50+ years, it is sensible to take climate change into account during the design phase. Data representing future weather are needed so that building performance simulations can predict the impact of climate change. Currently, this usually requires one year of weather data with a temporal resolution of one hour, which represents local climate conditions. However, both the temporal and spatial resolution of global climate models is generally too coarse. Two general approaches to increase the resolution of climate models - statistical and dynamical downscaling have been developed. They exist in many variants and modifications. The present paper aims to provide a comprehensive overview of future weather application as well as critical insights in the model and method selection. The results indicate a general trend to select the simplest methods, which often involves a compromise on selecting climate models.

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The Impact of Stratospheric Ozone Recovery on Tropopause Height Trends

Journal of Climate ◽

10.1175/2008jcli2215.1 ◽

2009 ◽

Vol 22 (2) ◽

pp. 429-445 ◽

Cited By ~ 55

Author(s):

Seok-Woo Son ◽

Lorenzo M. Polvani ◽

Darryn W. Waugh ◽

Thomas Birner ◽

Hideharu Akiyoshi ◽

...

Keyword(s):

Climate Change ◽

Southern Hemisphere ◽

Climate Models ◽

Stratospheric Ozone ◽

Reliable Estimate ◽

Intergovernmental Panel ◽

The Future ◽

Realistic Representation ◽

High Vertical Resolution ◽

The Impact

Abstract The evolution of the tropopause in the past, present, and future climate is examined by analyzing a set of long-term integrations with stratosphere-resolving chemistry climate models (CCMs). These CCMs have high vertical resolution near the tropopause, a model top located in the mesosphere or above, and, most important, fully interactive stratospheric chemistry. Using such CCM integrations, it is found that the tropopause pressure (height) will continue to decrease (increase) in the future, but with a trend weaker than that in the recent past. The reduction in the future tropopause trend is shown to be directly associated with stratospheric ozone recovery. A significant ozone recovery occurs in the Southern Hemisphere lower stratosphere of the CCMs, and this leads to a relative warming there that reduces the tropopause trend in the twenty-first century. The future tropopause trends predicted by the CCMs are considerably smaller than those predicted by the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) models, especially in the southern high latitudes. This difference persists even when the CCMs are compared with the subset of the AR4 model integrations for which stratospheric ozone recovery was prescribed. These results suggest that a realistic representation of the stratospheric processes might be important for a reliable estimate of tropopause trends. The implications of these finding for the Southern Hemisphere climate change are also discussed.

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Assessing the Impact of Projected Climate Change on Zoo Visitation in Toronto (Canada)

Journal of Geography and Geology ◽

10.5539/jgg.v8n2p30 ◽

2016 ◽

Vol 8 (2) ◽

pp. 30 ◽

Cited By ~ 4

Author(s):

Micah J. Hewer ◽

William A. Gough

Keyword(s):

Climate Change ◽

Climate Models ◽

Positive Impact ◽

Global Climate ◽

Global Climate Models ◽

Change Scenario ◽

Climate Change Scenarios ◽

Intergovernmental Panel ◽

Local Climate ◽

The Impact

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.

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Climate Impacts of the Southern Annular Mode Simulated by the CMIP3 Models

Journal of Climate ◽

10.1175/2009jcli2788.1 ◽

2009 ◽

Vol 22 (13) ◽

pp. 3751-3768 ◽

Cited By ~ 29

Author(s):

Alexey Yu Karpechko ◽

Nathan P. Gillett ◽

Gareth J. Marshall ◽

James A. Screen

Keyword(s):

Sea Ice ◽

Climate Models ◽

Temperature Response ◽

Coupled Model ◽

Surface Air Temperature ◽

Southern Annular Mode ◽

Climate Impacts ◽

Sea Ice Concentration ◽

Annular Mode ◽

Simulated Precipitation

Abstract The southern annular mode (SAM) has a well-established impact on climate in the Southern Hemisphere. The strongest response in surface air temperature (SAT) is observed in the Antarctic, but the SAM’s area of influence extends much farther, with statistically significant effects on temperature and precipitation being detected as far north as 20°S. Here the authors quantify the ability of the Coupled Model Intercomparison Project, phase 3 (CMIP3) coupled climate models to simulate the observed SAT, total precipitation, sea surface temperature (SST), and sea ice concentration responses to the SAM. The models are able to simulate the spatial pattern of response in SAT reasonably well; however, all models underestimate the magnitude of the response over Antarctica, both at the surface and in the free troposphere. This underestimation of the temperature response has implications for prediction of the future temperature changes associated with expected changes in the SAM. The models possess reasonable skill in simulating patterns of precipitation and SST response; however, some considerable regional deviations exist. The simulated precipitation and SST responses are less constrained by the observations than the SAT response, particularly in magnitude, as significant discrepancies are detected between the responses in the reference datasets. The largest problems are identified in simulating the sea ice response to the SAM, with some models even simulating a response that is negatively correlated with that observed.

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A multi-model analysis of ‘Little Ice Age’ climate over China

The Holocene ◽

10.1177/0959683618824761 ◽

2019 ◽

Vol 29 (4) ◽

pp. 592-605 ◽

Cited By ~ 2

Author(s):

Xuecheng Zhou ◽

Dabang Jiang ◽

Xianmei Lang

Keyword(s):

Little Ice Age ◽

Climate Models ◽

Surface Air Temperature ◽

Volcanic Eruptions ◽

Ice Age ◽

Last Millennium ◽

Orbital Parameters ◽

Community Earth System Model ◽

Intercomparison Project

Using the numerical experiments undertaken by nine climate models within the framework of the Paleoclimate Modeling Intercomparison Project Phase 3 (PMIP3), the ensemble simulations with the Community Earth System Model for the last millennium (CESM-LME), and proxy data, we investigate the climate over China during the ‘Little Ice Age’ (LIA; from 1450 to 1850 CE) against the background of the last millennium (from 850 to 1850 CE). The surface air temperature averaged over China generally decreased over time during the last millennium, with several multi-decadal to centennial variations superimposed on the long-term cooling. Relative to the climatology of the last millennium, the annual surface temperature during the LIA decreased over the country, with an average cooling of −0.07°C for the median of the PMIP3 models. Different magnitudes of cooling occurred in all seasons except spring. The cooling over China during the LIA was largely attributed to changes in volcanic eruptions and land use, while the change in orbital parameters played a role on a seasonal scale. The precipitation over China during the LIA decreased for the annual mean and summer and autumn but slightly increased in winter and spring. Model–data comparisons indicate that the models reproduced the colder and drier climate of the LIA reasonably, although there are some differences in certain aspects.

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The impact of regional climate model formulation and resolution on simulated precipitation in Africa

Earth System Dynamics ◽

10.5194/esd-11-377-2020 ◽

2020 ◽

Vol 11 (2) ◽

pp. 377-394 ◽

Cited By ~ 2

Author(s):

Minchao Wu ◽

Grigory Nikulin ◽

Erik Kjellström ◽

Danijel Belušić ◽

Colin Jones ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Horizontal Resolution ◽

Added Value ◽

Primary Control ◽

Model Formulation ◽

Simulated Precipitation ◽

Mean Climate ◽

The Impact

Abstract. We investigate the impact of model formulation and horizontal resolution on the ability of Regional Climate Models (RCMs) to simulate precipitation in Africa. Two RCMs (SMHI-RCA4 and HCLIM38-ALADIN) are utilized for downscaling the ERA-Interim reanalysis over Africa at four different resolutions: 25, 50, 100, and 200 km. In addition to the two RCMs, two different parameter settings (configurations) of the same RCA4 are used. By contrasting different downscaling experiments, it is found that model formulation has the primary control over many aspects of the precipitation climatology in Africa. Patterns of spatial biases in seasonal mean precipitation are mostly defined by model formulation, while the magnitude of the biases is controlled by resolution. In a similar way, the phase of the diurnal cycle in precipitation is completely controlled by model formulation (convection scheme), while its amplitude is a function of resolution. However, the impact of higher resolution on the time-mean climate is mixed. An improvement in one region/season (e.g. reduction in dry biases) often corresponds to a deterioration in another region/season (e.g. amplification of wet biases). At the same time, higher resolution leads to a more realistic distribution of daily precipitation. Consequently, even if the time-mean climate is not always greatly sensitive to resolution, the realism of the simulated precipitation increases as resolution increases. Our results show that improvements in the ability of RCMs to simulate precipitation in Africa compared to their driving reanalysis in many cases are simply related to model formulation and not necessarily to higher resolution. Such model formulation related improvements are strongly model dependent and can, in general, not be considered as an added value of downscaling.

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Modelagem do Impacto da Topografia Boreal no Clima Global (Modelling the Impact of Topography on Global Climate Boreal)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v4i2.232682 ◽

2011 ◽

Vol 4 (2) ◽

pp. 229

Author(s):

Bruno Lopes Faria ◽

Flavio Barbosa Justino

Keyword(s):

Climate Models ◽

Global Climate ◽

Coupled Model ◽

Local Climate ◽

The North ◽

Global Modelling ◽

Global And Local ◽

Wind Intensity ◽

The Impact ◽

Topographic Forcing

Foram realizadas simulações climáticas a partir de 2 experimentos de sensibilidade numérica conduzidos com um modelo acoplado de complexidade intermediária, LOVECLIM, estendendo-se para um período de 300 anos. Sendo que, neste experimento foi realizada a redução em 50% da topografia geral do hemisfério norte, um com modelo acoplado (oceano-atmosfera) e outro desacoplado (somente atmosfera). Nos resultados obtidos, foram observadas alterações no padrão de clima global e local, em especial a região da Ásia, relacionadas com aumento de temperatura do ar à superfície e intensidade do vento. Maiores alterações foram observados em regiões continentais no hemisfério norte. Isto mostra o maior impacto local causado pela forçante topográfica com o a redução da pela metade da topografia boreal. Palavras-chave: Topografia, Mudanças Climáticas, Modelos Climáticos, Forçante Climática Modelling the Impact of Topography on Global Climate Boreal ABSTRACTSimulations were conducted from two numerical sensitivity experiments conducted with a coupled model with intermediate complexity, LOVECLIM, extending for a period of 300 years. Since this experiment was carried out 50% reduction in the general topography of the northern hemisphere, with a coupled model (ocean-atmosphere) and the other uncoupled (atmosphere only). Their results have been observed changes in the pattern of global and local climate, particularly in Asia, linked to increase of air temperature and wind intensity. The biggest impacts were observed in continental regions in the north hemisphere. This shows the greater local impact caused by topographic forcing Keywords: Topography, Climate Change, Climate Models, Topographic Forcing

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Examining the Interaction of Growing Crops with Local Climate Using a Coupled Crop–Climate Model

Journal of Climate ◽

10.1175/2008jcli2494.1 ◽

2009 ◽

Vol 22 (6) ◽

pp. 1393-1411 ◽

Cited By ~ 34

Author(s):

Tom Osborne ◽

Julia Slingo ◽

David Lawrence ◽

Tim Wheeler

Keyword(s):

Climate Variability ◽

Crop Yield ◽

Land Surface ◽

Climate Models ◽

Climate Model ◽

Crop Growth ◽

Surface Fluxes ◽

Near Surface ◽

Local Climate ◽

The Impact

Abstract This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

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