Outsize Influence of Central American Orography on Global Climate
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Abstract Global Climate Models (GCMs) exhibit substantial biases in their simulation of tropical climate. One particularly problematic bias exists in GCMs' simulation of the tropical rainband known as the Intertropical Convergence Zone (ITCZ). Much of the precipitation on Earth falls within the ITCZ, which plays a key role in setting Earth's temperature by affecting global energy transports, and partially dictates dynamics of the largest interannual mode of climate variability: The El Niño‐Southern Oscillation (ENSO). Most GCMs fail to simulate the mean state of the ITCZ correctly, often exhibiting a “double ITCZ bias,” with rainbands both north and south rather than just north of the equator. These tropical mean state biases limit confidence in climate models' simulation of projected future and paleoclimate states, and reduce the utility of these models for understanding present climate dynamics. Adjusting GCM parameterizations of cloud processes and atmospheric convection can reduce tropical biases, as can artificially correcting sea surface temperatures through modifications to air‐sea fluxes (i.e., “flux adjustment”). Here, we argue that a significant portion of these rainfall and circulation biases are rooted in orographic height being biased low due to assumptions made in fitting observed orography onto GCM grids. We demonstrate that making different, and physically defensible, assumptions that raise the orographic height significantly improves model simulation of climatological features such as the ITCZ and North American rainfall as well as the simulation of ENSO. These findings suggest a simple, physically based, and computationally inexpensive method that can improve climate models and projections of future climate.Keywords:
Intertropical Convergence Zone
Orography
Orographic lift
Rainband
Convergence zone
Intertropical Convergence Zone
East Asian Monsoon
Convergence zone
Extratropical cyclone
Rainband
Forcing (mathematics)
Tropical monsoon climate
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Orography
Orographic lift
Convergence zone
Eddy
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Orographic influence on the formation of clouds and its associated precipitation amount and distribution is dramatic. The influence of orography was well recognized very early in human history and documented in numerous meteorological and climatological literatures. When a moist airflow impinges on a mountain, the dynamical and cloud microphysical characteristics of the airflow are modified by orographic lifting and blocking which may modify and/or trigger cloud and precipitation systems in the vicinity of the mountain. Figure 11.1 shows the mean annual precipitation for the period 1971–1990 over Western Europe. Areas of heavy precipitation are concentrated on the Alpine mountains. Note that precipitation over the Alps is produced by weather systems coming from different directions, in particular, from the northern and southern sides.
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Abstract Global Climate Models (GCMs) exhibit substantial biases in their simulation of tropical climate. One particularly problematic bias exists in GCMs' simulation of the tropical rainband known as the Intertropical Convergence Zone (ITCZ). Much of the precipitation on Earth falls within the ITCZ, which plays a key role in setting Earth's temperature by affecting global energy transports, and partially dictates dynamics of the largest interannual mode of climate variability: The El Niño‐Southern Oscillation (ENSO). Most GCMs fail to simulate the mean state of the ITCZ correctly, often exhibiting a “double ITCZ bias,” with rainbands both north and south rather than just north of the equator. These tropical mean state biases limit confidence in climate models' simulation of projected future and paleoclimate states, and reduce the utility of these models for understanding present climate dynamics. Adjusting GCM parameterizations of cloud processes and atmospheric convection can reduce tropical biases, as can artificially correcting sea surface temperatures through modifications to air‐sea fluxes (i.e., “flux adjustment”). Here, we argue that a significant portion of these rainfall and circulation biases are rooted in orographic height being biased low due to assumptions made in fitting observed orography onto GCM grids. We demonstrate that making different, and physically defensible, assumptions that raise the orographic height significantly improves model simulation of climatological features such as the ITCZ and North American rainfall as well as the simulation of ENSO. These findings suggest a simple, physically based, and computationally inexpensive method that can improve climate models and projections of future climate.
Intertropical Convergence Zone
Orography
Orographic lift
Rainband
Convergence zone
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Abstract This is one of the first case studies of a snowstorm at Lake Constance, located between Austria, Germany, and Switzerland, which assesses the influence of the lake and the orography on the generation of heavy precipitation. The analysis is based on surface and radar observations and numerical simulations with the Weather Research and Forecasting (WRF) Model. On 8 February 2013, a rather stationary and banded radar reflectivity pattern was observed during postfrontal conditions with northwesterly flow. The associated snowband affected the downstream shore and the adjacent mountainous region with 36 mm of precipitation within 5 h at the shore. Surface observations show a convergence in the wind field over the lake during the period of banded precipitation. The control simulation captures the formation of a convergence line and a snowband near the shoreline and over the downstream orography. A lake-induced, low-level conditionally unstable layer is essential for the snowband formation. Orographically and thermally induced convergence provides the lifting to release conditional instability and to trigger convection. Orographic enhancement of precipitation occurs downstream of the lake. Sensitivity experiments with modified orography, land use, and lake surface temperature show that the lake is a crucial factor controlling the amount and distribution of snowfall. However, neither the lake nor the orography alone would have been able to form a snowband. This study highlights the complex interaction between lake and orographic effects and shows that Lake Constance is large enough to impact the formation of precipitation.
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Winter storm
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Abstract We examine the influence of southern African orography on the Namibian stratocumulus deck, the South Atlantic ocean‐to‐atmosphere energy transport, and the Intertropical Convergence Zone (ITCZ), using an atmosphere‐only model and a coupled atmosphere‐ocean model. For both models, a control simulation with realistic orography is compared to a simulation where the orography in southern Africa was removed. As in the previous studies, the removal of orography results in thinning of the Namibian stratocumulus deck. In the coupled model, the increased sea surface temperature in the southern Atlantic due to the reduction of low clouds forces the Atlantic ITCZ to shift southward toward the warmer hemisphere. However, changes in the ocean circulation cool the South Atlantic atmosphere, lessening the ITCZ shift and changing the structure of precipitation. These results show the importance of orography on shaping Atlantic rainfall and highlight the role of dynamical ocean processes in atmospheric dynamics.
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Intertropical Convergence Zone
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Atmospheric models
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In recent years, the study of numerical weather prediction (NWP) in complex orographic areas has attracted a great deal of attention. Complex orography plays an important role in the occurrence and development of extreme rainfall events. In this study, the Yin–He Global Spectrum Model (YHGSM) was used, and the wave number truncation method was employed to decompose the orographic data to different resolutions. The obtained orographic data with different resolutions were used to simulate the extreme rainfall in Zhengzhou, Henan Province, China, to discuss the degree of influence and mechanism of the different orographic resolutions on the extreme rainfall. The results show that the simulation results of the YHGSM with high-resolution orography are better than those of the low-resolution orography in terms of the rainfall intensity and range. When the rainfall intensity is higher, the results of the low-resolution orography simulated the rainfall range of big heavy rainfall better. The orography mainly affected the rainfall by affecting the velocity of the updraft, but it had a limited influence on the maximum height that the updraft could reach. A strong updraft is one of the key factors leading to extreme rainfall in Henan Province. When the orographic resolution changes, the sensitivity of the vertical velocity of the updraft to the orographic resolution is the greatest, the sensitivity of the upper-air divergence and low-level vorticity to the orographic resolution is lower than that of the vertical velocity. In conclusion, the high-resolution orography is helpful in improving the model’s prediction of extreme rainfall, and when predicting extreme rainfall in complex orographic areas, forecasters may need to artificially increase rainfall based on model results.
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The interaction of a frontal system with the extreme orography of the Andes mountain range is examined for a case of intense precipitation in central Chile during June 2002. The heavy rainfall was associated with a synoptic scale rainband that moved slowly over central Chile during a 48 hour period. Numerical simulations with the WRF mesoscale model show that both the intensification of precipitation within the rainband, and its semi-stationary character, were fundamentally determined by interaction with the topography. It is suggested that the intensification of otherwise weak frontal zones by orographic flow deformation may be an important precipitation mechanism in central Chile.
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Mountain range (options)
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Orography strongly interacts with the atmospheric circulation, especially during frontal events, generating an enhanced spatial variability of the rainfall field. Regional models of extreme rainfall have to deal with these circumstances in order to provide good spatial estimation of the regionalized variable. We present a model for the regional estimation of the mean of the probability distribution of the annual daily rainfall maxima in a region (Campania, Southern Italy) with complex orography. In a recent work, we found that areas with enhanced variability of extreme rainfall, in the same region, correspond to a particular set of orographic objects, which had been classified through an automatic, GIS-based geomorphological procedure. Here, we propose an approach that considers the same orographic objects as building blocks for a regional model that is able to capture the amplification of extreme rainfall caused by orography. The regional model is then the product of a basic stationary random spatial process and an amplification factor, whose values are related to the topographic features of the orographic objects. This approach represents a step towards the improvement of the predictive ability of regional models of extreme rainfall within orographically complex areas.
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