scholarly journals Atmospheric tropical modes are important drivers of Sahelian springtime heatwaves

2020 ◽  
Author(s):  
Kiswendsida H. Guigma ◽  
Françoise Guichard ◽  
Martin Todd ◽  
Philippe Peyrille ◽  
Yi Wang
Keyword(s):  
Large Scale ◽  
Geographic Location ◽  
Longwave Radiation ◽  
Potential Predictability ◽  
Modes Of Variability ◽  
Physical Mechanisms ◽  
Hot Air ◽  
Western Sahel ◽  
Maximum Temperatures ◽  
Sahel Region

AbstractHeatwaves pose a serious threat to human health worldwide but remain poorly documented over Africa. This study uses mainly the ERA5 dataset to investigate their large-scale drivers over the Sahel region during boreal spring, with a focus on the role of tropical modes of variability including the Madden–Julian Oscillation (MJO) and the equatorial Rossby and Kelvin waves. Heatwaves were defined from daily minimum and maximum temperatures using a methodology that retains only intraseasonal scale events of large spatial extent. The results show that tropical modes have a large influence on the occurrence of Sahelian heatwaves, and, to a lesser extent, on their intensity. Depending on their convective phase, they can either increase or inhibit heatwave occurrence, with the MJO being the most important of the investigated drivers. A certain sensitivity to the geographic location and the diurnal cycle is observed, with nighttime heatwaves more impacted by the modes over the eastern Sahel and daytime heatwaves more affected over the western Sahel. The examination of the physical mechanisms shows that the modulation is made possible through the perturbation of regional circulation. Tropical modes thus exert a control on moisture and the subsequent longwave radiation, as well as on the advection of hot air. A detailed case study of a major event, which took place in April 2003, further supports these findings. Given the potential predictability offered by tropical modes at the intraseasonal scale, this study has key implications for heatwave risk management in the Sahel.

scholarly journals The Dynamical Influence of the Atlantic Multidecadal Oscillation on Continental Climate

2017 ◽  
Vol 30 (18) ◽  
pp. 7213-7230 ◽  
Author(s):  
Christopher H. O’Reilly ◽  
Tim Woollings ◽  
Laure Zanna
Keyword(s):  
Atmospheric Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Surface Air Temperature ◽  
Atlantic Multidecadal Oscillation ◽  
The North ◽  
Sst Variability ◽  
Western Sahel ◽  
Prediction Systems ◽  
Sahel Region

Abstract The Atlantic multidecadal oscillation (AMO) in sea surface temperature (SST) has been shown to influence the climate of the surrounding continents. However, it is unclear to what extent the observed impact of the AMO is related to the thermodynamical influence of the SST variability or the changes in large-scale atmospheric circulation. Here, an analog method is used to decompose the observed impact of the AMO into dynamical and residual components of surface air temperature (SAT) and precipitation over the adjacent continents. Over Europe the influence of the AMO is clearest during the summer, when the warm SAT anomalies are interpreted to be primarily thermodynamically driven by warm upstream SST anomalies but also amplified by the anomalous atmospheric circulation. The overall precipitation response to the AMO in summer is generally less significant than the SAT but is mostly dynamically driven. The decomposition is also applied to the North American summer and the Sahel rainy season. Both dynamical and residual influences on the anomalous precipitation over the Sahel are substantial, with the former dominating over the western Sahel region and the latter being largest over the eastern Sahel region. The results have potential implications for understanding the spread in AMO variability in coupled climate models and decadal prediction systems.

scholarly journals Implication of the Madden–Julian Oscillation in the 40-Day Variability of the West African Monsoon

2009 ◽  
Vol 22 (13) ◽  
pp. 3769-3785 ◽  
Author(s):  
Benjamin Pohl ◽  
Serge Janicot ◽  
Bernard Fontaine ◽  
Romain Marteau
Keyword(s):  
Large Scale ◽  
West African Monsoon ◽  
Longwave Radiation ◽  
Rain Gauge ◽  
West African ◽  
Mode Analysis ◽  
Local Mode ◽  
The West ◽  
African Monsoon ◽  
Sahel Region

Abstract Madden–Julian oscillations (MJOs) are extracted over the Indo-Pacific basin using a local mode analysis. The convective perturbations are then projected over a larger domain to evaluate their remote consequences over the West African monsoon (WAM) intraseasonal variability. Rather weak (4–6 W m−2) convective fluctuations occurring in phase with those over the southern Indian basin are found over Africa, confirming the results of Matthews. In reverse, 40-day fluctuations in the WAM, similarly detected and projected over a widened area, demonstrate that a large majority of these events are embedded in the larger-scale patterns of the MJO. The regional amplitude of intraseasonal perturbations of the West African convection is not statistically associated with the amplitude of the MJO over the Indian basin but is instead closely related to background vertical velocity anomalies over Africa, possibly embedded in changes in the regional Walker-type circulation. Subsiding motion over Africa is recorded during the most energetic convective perturbations in the WAM. Composites analyses over the MJO life cycle, as depicted by the real-time daily indices developed by Wheeler and Hendon, show that positive outgoing longwave radiation (OLR) anomalies during the dry phase are of larger amplitude and spatially more coherent than negative anomalies during the wet phase, especially over the Sahel region. Over West Africa, the phase of suppressed convection is thus of greater importance for the region than the phase of enhanced convection. Rain gauge records fully confirm these results. The MJO appears to be significantly involved in the occurrences of dry spells during the monsoon over the Sahel, whereas large-scale convective clusters are only restricted to the equatorial latitudes and thus affect the Guinean belt, which experiences its short dry season at this time of the year.

scholarly journals Estimating the Earth’s Outgoing Longwave Radiation Measured from a Moon-Based Platform

2021 ◽  
Vol 13 (11) ◽  
pp. 2201
Author(s):  
Hanlin Ye ◽  
Huadong Guo ◽  
Guang Liu ◽  
Jinsong Ping ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Outgoing Longwave Radiation ◽  
Large Scale ◽  
Single Point ◽  
Longwave Radiation ◽  
Earth Observation ◽  
Artificial Satellites ◽  
Earth Observations ◽  
The Earth ◽  
Observation Geometry ◽  
Global Mean

Moon-based Earth observations have attracted significant attention across many large-scale phenomena. As the only natural satellite of the Earth, and having a stable lunar surface as well as a particular orbit, Moon-based Earth observations allow the Earth to be viewed as a single point. Furthermore, in contrast with artificial satellites, the varied inclination of Moon-based observations can improve angular samplings of specific locations on Earth. However, the potential for estimating the global outgoing longwave radiation (OLR) from the Earth with such a platform has not yet been fully explored. To evaluate the possibility of calculating OLR using specific Earth observation geometry, we constructed a model to estimate Moon-based OLR measurements and investigated the potential of a Moon-based platform to acquire the necessary data to estimate global mean OLR. The primary method of our study is the discretization of the observational scope into various elements and the consequent integration of the OLR of all elements. Our results indicate that a Moon-based platform is suitable for global sampling related to the calculation of global mean OLR. By separating the geometric and anisotropic factors from the measurement calculations, we ensured that measured values include the effects of the Moon-based Earth observation geometry and the anisotropy of the scenes in the observational scope. Although our results indicate that higher measured values can be achieved if the platform is located near the center of the lunar disk, a maximum difference between locations of approximately 9 × 10−4 W m−2 indicates that the effect of location is too small to remarkably improve observation performance of the platform. In conclusion, our analysis demonstrates that a Moon-based platform has the potential to provide continuous, adequate, and long-term data for estimating global mean OLR.

scholarly journals Cluster analysis of midlatitude oceanic cloud regimes: mean properties and temperature sensitivity

2010 ◽  
Vol 10 (13) ◽  
pp. 6435-6459 ◽  
Author(s):  
N. D. Gordon ◽  
J. R. Norris
Keyword(s):  
Large Scale ◽  
Longwave Radiation ◽  
Cloud Fraction ◽  
Climate System ◽  
Radiative Properties ◽  
Upper Troposphere ◽  
Low Level ◽  
Increasing Temperature ◽  
Cloud Regimes ◽  
Cloud Response

Abstract. Clouds play an important role in the climate system by reducing the amount of shortwave radiation reaching the surface and the amount of longwave radiation escaping to space. Accurate simulation of clouds in computer models remains elusive, however, pointing to a lack of understanding of the connection between large-scale dynamics and cloud properties. This study uses a k-means clustering algorithm to group 21 years of satellite cloud data over midlatitude oceans into seven clusters, and demonstrates that the cloud clusters are associated with distinct large-scale dynamical conditions. Three clusters correspond to low-level cloud regimes with different cloud fraction and cumuliform or stratiform characteristics, but all occur under large-scale descent and a relatively dry free troposphere. Three clusters correspond to vertically extensive cloud regimes with tops in the middle or upper troposphere, and they differ according to the strength of large-scale ascent and enhancement of tropospheric temperature and humidity. The final cluster is associated with a lower troposphere that is dry and an upper troposphere that is moist and experiencing weak ascent and horizontal moist advection. Since the present balance of reflection of shortwave and absorption of longwave radiation by clouds could change as the atmosphere warms from increasing anthropogenic greenhouse gases, we must also better understand how increasing temperature modifies cloud and radiative properties. We therefore undertake an observational analysis of how midlatitude oceanic clouds change with temperature when dynamical processes are held constant (i.e., partial derivative with respect to temperature). For each of the seven cloud regimes, we examine the difference in cloud and radiative properties between warm and cold subsets. To avoid misinterpreting a cloud response to large-scale dynamical forcing as a cloud response to temperature, we require horizontal and vertical temperature advection in the warm and cold subsets to have near-median values in three layers of the troposphere. Across all of the seven clusters, we find that cloud fraction is smaller and cloud optical thickness is mostly larger for the warm subset. Cloud-top pressure is higher for the three low-level cloud regimes and lower for the cirrus regime. The net upwelling radiation flux at the top of the atmosphere is larger for the warm subset in every cluster except cirrus, and larger when averaged over all clusters. This implies that the direct response of midlatitude oceanic clouds to increasing temperature acts as a negative feedback on the climate system. Note that the cloud response to atmospheric dynamical changes produced by global warming, which we do not consider in this study, may differ, and the total cloud feedback may be positive.

A Large Scale Cross-Validation of Second-Order Personality Structure Defined by the 16PF

1986 ◽  
Vol 59 (2) ◽  
pp. 683-693 ◽  
Author(s):  
Samuel E. Krug ◽  
Edgar F. Johns
Keyword(s):  
Large Scale ◽  
Common Factor ◽  
Geographic Location ◽  
Second Order ◽  
Personality Factor ◽  
Personality Factor Questionnaire ◽  
Normal Males ◽  
Definition Of ◽  
High Degree ◽  
Factor Estimation

The second-order factors structure of the 16 Personality Factor Questionnaire (16PF) was cross-validated on a large sample ( N = 17,381) of normal males and females. Subjects were sampled across a broad range of ages, socioeconomic levels, education, geographic location, and ethnicity. The purposes of this investigation were (1) to provide a precise definition of 16PF second-order factor structure, (2) to shed additional light on the nature of two second-order factors that have been previously identified but described as “unstable” and “poorly reproduced,” and (3) to determine the extent to which common factor estimation formulas for men and women would prove satisfactory for applied work. The resulting solutions were congruent with previous studies and showed a high degree of simple structure. Support was provided for one, but not both, of the two additional second-order factors. Results also supported the use of simplified estimation formulas for applied use.

scholarly journals Seasonal forecasts of the Saharan heat low characteristics: a multi-model assessment

2021 ◽  
Vol 2 (3) ◽  
pp. 893-912
Author(s):  
Cedric G. Ngoungue Langue ◽  
Christophe Lavaysse ◽  
Mathieu Vrac ◽  
Philippe Peyrillé ◽  
Cyrille Flamant
Keyword(s):  
West African Monsoon ◽  
Seasonal Forecast ◽  
Lead Times ◽  
Model Assessment ◽  
Seasonal Forecasts ◽  
Weather Forecasts ◽  
Modes Of Variability ◽  
Forecast Models ◽  
Sahel Region ◽  
Heat Low

Abstract. The Saharan heat low (SHL) is a key component of the West African Monsoon system at the synoptic scale and a driver of summertime precipitation over the Sahel region. Therefore, accurate seasonal precipitation forecasts rely in part on a proper representation of the SHL characteristics in seasonal forecast models. This is investigated using the latest versions of two seasonal forecast systems namely the SEAS5 and MF7 systems from the European Center of Medium-Range Weather Forecasts (ECMWF) and Météo-France respectively. The SHL characteristics in the seasonal forecast models are assessed based on a comparison with the fifth ECMWF Reanalysis (ERA5) for the period 1993–2016. The analysis of the modes of variability shows that the seasonal forecast models have issues with the timing and the intensity of the SHL pulsations when compared to ERA5. SEAS5 and MF7 show a cool bias centered on the Sahara and a warm bias located in the eastern part of the Sahara respectively. Both models tend to underestimate the interannual variability in the SHL. Large discrepancies are found in the representation of extremes SHL events in the seasonal forecast models. These results are not linked to our choice of ERA5 as a reference, for we show robust coherence and high correlation between ERA5 and the Modern-Era Retrospective analysis for Research and Applications (MERRA). The use of statistical bias correction methods significantly reduces the bias in the seasonal forecast models and improves the yearly distribution of the SHL and the forecast scores. The results highlight the capacity of the models to represent the intraseasonal pulsations (the so-called east–west phases) of the SHL. We notice an overestimation of the occurrence of the SHL east phases in the models (SEAS5, MF7), while the SHL west phases are much better represented in MF7. In spite of an improvement in prediction score, the SHL-related forecast skills of the seasonal forecast models remain weak for specific variations for lead times beyond 1 month, requiring some adaptations. Moreover, the models show predictive skills at an intraseasonal timescale for shorter lead times.

Predictability of U.S. Regional Extreme Precipitation Occurrence Based on Large-Scale Meteorological Patterns (LSMPs)

2021 ◽  
pp. 1-61
Author(s):  
Xiang Gao ◽  
Shray Mathur
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Warm Season ◽  
Prediction Skill ◽  
Large Set ◽  
Synoptic Scale ◽  
Potential Predictability ◽  
Precipitation Occurrence ◽  
Skill Scores ◽  
Analogue Method

AbstractIn this study, we use analogue method and Convolutional Neural Networks (CNNs) to assess the potential predictability of extreme precipitation occurrence based on Large-Scale Meteorological Patterns (LSMPs) for the winter (DJF) of Pacific Coast California (PCCA) and the summer (JJA) of Midwestern United States (MWST). We evaluate the LSMPs constructed with a large set of variables at multiple atmospheric levels and quantify the prediction skill with a variety of complementary performance measures. Our results suggest that LSMPs provide useful predictability of daily extreme precipitation occurrence and its interannual variability over both regions. The 14-year (2006-2019) independent forecast shows Gilbert Skill Scores (GSS) in PCCA range from 0.06 to 0.32 across 24 CNN schemes and from 0.16 to 0.26 across 4 analogue schemes, in contrast to those from 0.1 to 0.24 and from 0.1 to 0.14 in MWST. Overall, CNN is shown to be more powerful in extracting the relevant features associated with extreme precipitation from the LSMPs than analogue method, with several single-variate CNN schemes achieving more skillful prediction than the best multi-variate analogue scheme in PCCA and more than half of CNN schemes in MWST. Nevertheless, both methods highlight the Integrated Vapor Transport (IVT, or its zonal and meridional components) enables higher skills than other atmospheric variables over both regions. Warm-season extreme precipitation in MWST presents a forecast challenge with overall lower prediction skill than in PCCA, attributed to the weak synoptic-scale forcing in summer.

A Stochastic Parameter Perturbation Method to Represent Uncertainty in a Microphysics Scheme

2021 ◽  
Author(s):  
Gregory Thompson ◽  
Judith Berner ◽  
Maria Frediani ◽  
Jason A. Otkin ◽  
Sarah M. Griffin
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Random Perturbation ◽  
Longwave Radiation ◽  
Parameter Uncertainties ◽  
Microphysics Scheme ◽  
Convective Systems ◽  
Temporal Correlations ◽  
Precipitation Characteristics ◽  
The Impact

AbstractCurrent state-of-the art regional numerical weather forecasts are run at horizontal grid spacings of a few kilometers, which permits medium to large-scale convective systems to be represented explicitly in the model. With the convection parameterization no longer active, much uncertainty in the formulation of subgrid-scale processes moves to other areas such as the cloud microphysical, turbulence, and land-surface parameterizations. The goal of this study is to investigate experiments with stochastically-perturbed parameters (SPP) within a microphysics parameterization and the model’s horizontal diffusion coefficients. To estimate the “true” uncertainty due to parameter uncertainty, the magnitudes of the perturbations are chosen as realistic as possible and not with purposeful intent of maximal forecast impact as some prior work has done. Spatial inhomogeneities and temporal persistence are represented using a random perturbation pattern with spatial and temporal correlations. The impact on the distributions of various hydrometeors, precipitation characteristics, and solar/longwave radiation are quantified for a winter and summer case. In terms of upscale error growth, the impact is relatively small and consists primarily of triggering atmospheric instabilities in convectively unstable regions. In addition, small in situ changes with potentially large socio-economic impacts are observed in the precipitation characteristics such as maximum hail size. Albeit the impact of introducing physically-based parameter uncertainties within the bounds of aerosol uncertainties is small, their influence on the solar and longwave radiation balances may still have important implications for global model simulations of future climate scenarios.

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