scholarly journals Variations in the Summertime Atmospheric Hydrologic Cycle Associated with Seasonal Precipitation Anomalies over the Southwestern United States

2006 ◽  
Vol 7 (4) ◽  
pp. 788-807 ◽  
Author(s):  
Bruce T. Anderson ◽  
Hideki Kanamaru ◽  
John O. Roads
Keyword(s):  
New Mexico ◽  
Large Scale ◽  
Moisture Flux ◽  
Hydrologic Cycle ◽  
Seasonal Precipitation ◽  
Model Simulations ◽  
Moisture Flux Convergence ◽  
Rainfall Season ◽  
Rainfall Anomalies ◽  
The Mean

Abstract This paper examines year-to-year variations in the large-scale summertime hydrologic cycle over the southwestern United States using a suite of regional model simulations and surface- and upper-air-based observations. In agreement with previous results, it is found that observed interannual precipitation variations in this region can be subdivided into two spatiotemporal regimes—one associated with rainfall variability over the southwestern portion of the domain centered on Arizona and the other associated with variations over the southeastern portion centered on western Texas and eastern New Mexico. Because of the limited duration of the model simulation data, it is possible to only investigate one positive rainfall season over the Arizona region and one negative rainfall season over the New Mexico region. From these investigations it appears that for the positive rainfall anomalies over Arizona excess seasonal precipitation is balanced by both enhanced evaporation and vertically integrated large-scale moisture flux convergence. Vertical profiles of these terms indicate that the anomalous large-scale moisture flux convergence is actually related to a decrease in the mean large-scale moisture flux divergence aloft; below 800 mb there is a decrease in the mean moisture flux convergence typically found at these levels, which in turn produces anomalous moisture divergence from the region. For the negative rainfall anomalies over New Mexico similar results, but of opposite sign, are found; one exception is that at the lowest levels there is an additional (negative) contribution to the vertically integrated moisture flux convergence anomaly related to a weakening of the mean low-level moisture flux convergence during the low-rainfall year. Further studies using two different model simulations with the same large-scale dynamic forcing but differing initial soil moisture values indicate that similar balances are also found for rainfall anomalies related to surface soil moisture changes within the domain, suggesting that the changes in large-scale moisture flux convergence described above can be attributed to both year-to-year variations in the regional land–atmosphere interactions as well as variations in the large-scale circulation patterns.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals Coupling of Precipitation and Cloud Structures in Oceanic Extratropical Cyclones to Large-Scale Moisture Flux Convergence

2018 ◽  
Vol 31 (23) ◽  
pp. 9565-9584 ◽  
Author(s):  
Sun Wong ◽  
Catherine M. Naud ◽  
Brian H. Kahn ◽  
Longtao Wu ◽  
Eric J. Fetzer
Keyword(s):  
Large Scale ◽  
Moisture Flux ◽  
Extratropical Cyclones ◽  
Flux Divergence ◽  
Moisture Flux Convergence ◽  
Convective Clouds ◽  
Moisture Advection ◽  
Deep Convective Clouds ◽  
Stratiform Clouds ◽  
High Level

Precipitation (from TMPA) and cloud structures (from MODIS) in extratropical cyclones (ETCs) are modulated by phases of large-scale moisture flux convergence (from MERRA-2) in the sectors of ETCs, which are studied in a new coordinate system with directions of both surface warm fronts (WFs) and surface cold fronts (CFs) fixed. The phase of moisture flux convergence is described by moisture dynamical convergence Qcnvg and moisture advection Qadvt. Precipitation and occurrence frequencies of deep convective clouds are sensitive to changes in Qcnvg, while moisture tendency is sensitive to changes in Qadvt. Increasing Qcnvg and Qadvt during the advance of the WF is associated with increasing occurrences of both deep convective and high-level stratiform clouds. A rapid decrease in Qadvt with a relatively steady Qcnvg during the advance of the CF is associated with high-level cloud distribution weighting toward deep convective clouds. Behind the CF (cold sector or area with polar air intrusion), the moisture flux is divergent with abundant low- and midlevel clouds. From deepening to decaying stages, the pre-WF and WF sectors experience high-level clouds shifting to more convective and less stratiform because of decreasing Qadvt with relatively steady Qcnvg, and the CF experiences shifting from high-level to midlevel clouds. Sectors of moisture flux divergence are less influenced by cyclone evolution. Surface evaporation is the largest in the cold sector and the CF during the deepening stage. Deepening cyclones are more efficient in poleward transport of water vapor.

Influence of mid-latitude oceanic fronts on the atmospheric water cycle

2020 ◽  
Author(s):  
Fumiaki Ogawa ◽  
Thomas Spengler
Keyword(s):  
Heat Exchange ◽  
Large Scale ◽  
Water Cycle ◽  
Moisture Flux ◽  
Convective Precipitation ◽  
Atmospheric Water ◽  
Moisture Flux Convergence ◽  
Sst Front ◽  
Oceanic Fronts ◽  
Sst Fronts

<p>      Midlatitude oceanic fronts play an important role in the air-sea coupled weather and climate system. Created by the confluence of warm and cool oceanic western boundary currents, the strong sea-surface temperature (SST) gradient is maintained throughout the year. The climatological mean turbulent air-sea heat exchange maximizes along these SST fronts and collocates with the major atmospheric storm tracks. A recent study identified that the air-sea heat exchange along the SST front mainly occurs on sub-weekly time scales, associated with synoptic atmospheric disturbances. This implies a crucial role of air-sea moisture exchange along the SST fronts on the atmospheric water cycle through the intensification of atmospheric cyclones and the associated precipitation.  </p><p>      In this study, we investigate this influence of the SST front on the atmospheric water cycle by analyzing the atmospheric response to different prescribed SST in the Atmospheric general circulation model For the Earth Simulator (AFES). Changing the latitude of the prescribed zonally symmetric SST in aqua-planet configuration, we find a distinctive response in convective and large-scale precipitation, surface latent and sensible heat fluxes, as well as diabatic heating and moistening with respect to the latitude of SST front. Upward surface latent heat flux and convective precipitation always maximize along the equatorward flank of SST front. On the other hand, large-scale precipitation is always located on the poleward flank of the SST front, in correspondence with the maximum atmospheric moisture flux convergence. The moisture flux convergence is mainly associated with midlatitude eddies and not with the time mean transport. This highlights the influence of mid-latitude SST fronts on the atmospheric water cycle through the organization of atmospheric storm track.</p>

scholarly journals Air, Sea, and Land Interactions of the Continental U.S. Hydroclimate

2009 ◽  
Vol 10 (2) ◽  
pp. 353-373 ◽  
Author(s):  
Vasubandhu Misra ◽  
P. A. Dirmeyer
Keyword(s):  
United States ◽  
General Circulation Model ◽  
General Circulation ◽  
Winter Season ◽  
Circulation Model ◽  
Moisture Flux ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Moisture Flux Convergence ◽  
The Mean

Abstract Multidecadal simulations over the continental United States by an atmospheric general circulation model coupled to an ocean general circulation model is compared with that forced by observed sea surface temperature (SST). The differences in the mean and the variability of precipitation are found to be larger in the boreal summer than in the winter. This is because the mean SST differences in the two simulations are qualitatively comparable between the two seasons. The analysis shows that, in the boreal summer season, differences in moisture flux convergence resulting from changes in the circulation between the two simulations initiate and sustain changes in precipitation between them. This difference in precipitation is, however, further augmented by the contributions from land surface evaporation, resulting in larger differences of precipitation between the two simulations. However, in the boreal winter season, despite differences in the moisture flux convergence between the two model integrations, the precipitation differences over the continental United States are insignificant. It is also shown that land–atmosphere feedback is comparatively much weaker in the boreal winter season.

scholarly journals Estimating the Influence of Evaporation and Moisture-Flux Convergence upon Seasonal Precipitation Rates. Part II: An Analysis for North America Based upon the NCEP–DOE Reanalysis II Model

2009 ◽  
Vol 10 (4) ◽  
pp. 893-911 ◽  
Author(s):  
Bruce T. Anderson ◽  
Alex C. Ruane ◽  
John O. Roads ◽  
Masao Kanamitsu
Keyword(s):  
Large Scale ◽  
Moisture Flux ◽  
Early Summer ◽  
Monsoon Circulation ◽  
Atmospheric Moisture ◽  
Storm Activity ◽  
Moisture Flux Convergence ◽  
Low Level ◽  
Low Level Jet ◽  
Northwestern Mexico

Abstract In this paper, a diagnostic metric—termed the local-convergence ratio—is used to analyze the contribution of evaporation and atmospheric moisture-flux convergence to model-based estimates of climatological precipitation over the North American continent. Generally, the fractional evaporative contribution is largest during spring and summer when evaporation is largest and decreases as evaporation decreases. However, there appears to be at least three regions with distinct spatiotemporal seasonal evolutions of this ratio. Over both the northern and western portions of the continent, the fractional evaporative contribution peaks in spring and early summer and decreases during fall and into winter. Over the northern portion, this fall decrease is related to an increase in atmospheric moisture-flux convergence associated with enhanced meridional moisture fluxes into the region; over the western coastal regions, the fall decrease in evaporative contribution is associated with a decrease in evaporation and an increase in total moisture-flux convergence, most likely associated with increased storm activity. In contrast, over the central portions of the continent, the fractional evaporative contribution to precipitation remains relatively low in spring—when enhanced low-level jet activity increases the low-level atmospheric moisture flux convergence into the region—and instead peaks in summer and fall—when the moisture-flux convergence associated with the low-level jet decreases and precipitation is balanced predominantly by local evaporation. Finally, over the southwestern United States and northwestern Mexico, the fractional evaporative contribution to precipitation is found to contain a wintertime minimum as well as a secondary minimum during summer. This latter feature is due to a substantial increase in low-level atmospheric moisture-flux convergence associated with the large-scale monsoon circulation that influences this region during this time.

scholarly journals Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations

2018 ◽  
Vol 11 (5) ◽  
pp. 1823-1847 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Seasonal Precipitation ◽  
Physical Mechanisms ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyse the sensitivity to air–sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ∼ 200, 90 and 40 km in the zonal direction at the equator, respectively) are analysed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China but improve with finer resolution and coupling. Empirical orthogonal teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air–sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal mean time series. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

Application of Statistical Models to the Prediction of Seasonal Rainfall Anomalies over the Sahel

2014 ◽  
Vol 53 (3) ◽  
pp. 614-636 ◽  
Author(s):  
Hamada S. Badr ◽  
Benjamin F. Zaitchik ◽  
Seth D. Guikema
Keyword(s):  
Statistical Models ◽  
Large Scale ◽  
Predictive Accuracy ◽  
Learning Algorithm ◽  
Surface Air Temperature ◽  
Principal Component ◽  
Seasonal Precipitation ◽  
Precipitation Prediction ◽  
Rainfall Anomalies ◽  
Sahel Region

AbstractRainfall in the Sahel region of Africa is prone to large interannual variability, and it has exhibited a recent multidecadal drying trend. The well-documented social impacts of this variability have motivated numerous efforts at seasonal precipitation prediction, many of which employ statistical techniques that forecast Sahelian precipitation as a function of large-scale indices of surface air temperature (SAT) anomalies, sea surface temperature (SST), surface pressure, and other variables. These statistical models have demonstrated some skill, but nearly all have adopted conventional statistical modeling techniques—most commonly generalized linear models—to associate predictor fields with precipitation anomalies. Here, the results of an artificial neural network (ANN) machine-learning algorithm applied to predict summertime (July–September) Sahel rainfall anomalies using indices of springtime (April–June) SST and SAT anomalies for the period 1900–2011 are presented. Principal component analysis was used to remove multicollinearity between predictor variables. Predictive accuracy was assessed using repeated k-fold random holdout and leave-one-out cross-validation methods. It was found that the ANN achieved predictive accuracy superior to that of eight alternative statistical methods tested in this study, and it was also superior to that of previously published predictive models of summertime Sahel precipitation. Analysis of partial dependence plots indicates that ANN skill is derived primarily from the ability to capture nonlinear influences that multiple major modes of large-scale variability have on Sahelian precipitation. These results point to the value of ANN techniques for seasonal precipitation prediction in the Sahel.

scholarly journals The Dominant Patterns of Intraseasonal Rainfall Variability in May–October and November–April over the Tropical Western Pacific

2019 ◽  
Vol 147 (8) ◽  
pp. 2941-2960 ◽  
Author(s):  
Sunil Kumar Pariyar ◽  
Noel Keenlyside ◽  
Bhuwan Chandra Bhatt ◽  
Nour-Eddine Omrani
Keyword(s):  
Rainfall Variability ◽  
Surface Wind ◽  
Daily Rainfall ◽  
Moisture Flux ◽  
Feedback Mechanism ◽  
Western Pacific ◽  
Moisture Flux Convergence ◽  
Low Level ◽  
Northward Propagation ◽  
Rainfall Anomalies

Abstract The space–time structure of intraseasonal (10–90 day) rainfall variability in the western tropical Pacific is studied using daily 3B42 TRMM and ERA-Interim reanalysis data for the period 1998–2014. Empirical orthogonal function (EOF) analysis of 10–90-day filtered daily rainfall anomalies identifies two leading modes in both May–October and November–April; together these modes explain about 11%–12% of the total intraseasonal variance over the domain in both seasons and up to 60% over large areas of the western Pacific in both climatological periods. The two leading modes in May–October are linearly related to each other and both are well correlated with the Madden–Julian oscillation (MJO) indices. Although the two leading EOF modes in November–April are linearly independent of each other, both show statistically significant correlations with the MJO. The phase composites of 30–80-day filtered data show that the two leading modes are associated with strong eastward and northward propagation of rainfall anomalies in May–October, and eastward and southward propagation of rainfall anomalies in November–April. The eastward propagation of rainfall anomalies in both seasons and southeastward propagation related with EOF2 in November–April is linked to the development of low-level moisture flux convergence ahead of the active convection. Similarly, the northward propagation in May–October is also connected with low-level moisture flux convergence, but surface wind and evaporation variations are also important. The wind–evaporation–SST feedback mechanism drives the southeastward propagation of rainfall anomalies associated with EOF1 in November–April. The different mechanisms for southeastward propagation associated with two leading modes in November–April suggest dynamically different relations with the MJO.

scholarly journals Drivers and physical processes of drought events over the State of São Paulo, Brazil

2022 ◽  
Author(s):  
Abayomi A. Abatan ◽  
Simon F. B. Tett ◽  
Buwen Dong ◽  
Christopher Cunningham ◽  
Conrado M. Rudorff ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Simulation ◽  
Moisture Flux ◽  
Sao Paulo ◽  
The State ◽  
Climatic Research Unit ◽  
Summer Drought ◽  
São Paulo ◽  
Physical Processes ◽  
Moisture Flux Convergence

AbstractThe State of São Paulo, Brazil (SSP) was impacted by severe water shortages during the intense austral summer drought of 2013/2014 and 2014/2015 (1415SD). This study seeks to understand the features and physical processes associated with these summer droughts in the context of other droughts over the region during 1961–2010. Thus, this study examines the spatio-temporal characteristics of anomalously low precipitation over SSP and the associated large-scale dynamics at seasonal timescales, using an observation-based dataset from the Climatic Research Unit (CRU) and model simulation outputs from the Met Office Hadley Centre Global Environment Model (HadGEM3-GA6 at N216 resolution). The study analyzes Historical and Natural simulations from the model to examine the role of human-induced climate forcing on droughts over SSP. Composites of large-scale fields associated with droughts are derived from ERA-20C and ERA-Interim reanalysis and the model simulations. HadGEM3-GA6 simulations capture the observed interannual variability of normalized precipitation anomalies over SSP, but with biases. Drought events over SSP are related to subsidence over the region. This is associated with reduced atmospheric moisture over the region as indicated by the analysis of the vertically integrated moisture flux convergence, which is dominated by reduced moisture flux convergence. The Historical simulations simulate the subsidence associated with droughts, but there are magnitude and location biases. The similarities between the circulation features of the severe 1415SD and other drought events over the region show that understanding of the dynamics of the past drought events over SSP could guide assessment of changes in risk of future droughts and improvements of model performance. The study highlights the merits and limitations of the HadGEM3-GA6 simulations. The model possesses the skills in simulating the large-scale atmospheric circulations modulating precipitation variability, leading to drought conditions over SSP.

scholarly journals Drivers and Physical Processes of Drought Events Over the State of São Paulo, Brazil

2021 ◽  
Author(s):  
Abayomi A. Abatan ◽  
Simon F. B. Tett ◽  
Buwen Dong ◽  
Christopher Cunningham ◽  
Conrado M. Rudorff ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Simulation ◽  
Moisture Flux ◽  
Sao Paulo ◽  
The State ◽  
Climatic Research Unit ◽  
Summer Drought ◽  
São Paulo ◽  
Physical Processes ◽  
Moisture Flux Convergence

Abstract The State of São Paulo, Brazil (SSP) was impacted by severe water shortages during the intense austral summer drought of 2013/2014 and 2014/2015 (1415SD). This study seeks to understand the features and physical processes associated with these summer droughts in the context of other droughts over the region during 1961 – 2010. Thus, this study examines the spatio-temporal characteristics of anomalously low precipitation over SSP and the associated large-scale dynamics at seasonal timescales, using an observation-based dataset from the Climatic Research Unit (CRU) and model simulation outputs from the Met Office Hadley Centre Global Environment Model (HadGEM3-GA6 at N216 resolution). The study analyzes Historical and Natural simulations from the model to examine the role of human-induced climate forcing on droughts over SSP. Composites of large-scale fields associated with droughts are derived from ERA-20C and ERAInterim reanalysis and the model simulations. HadGEM3-GA6 simulations capture the observed interannual variability of normalized precipitation anomalies over SSP, but with biases. Drought events over SSP are related to subsidence over the region. This is associated with reduced atmospheric moisture over the region as indicated by the analysis of the vertically integrated moisture flux convergence, which is dominated by reduced moisture flux convergence. The Historical simulations simulate the subsidence associated with droughts, but there are magnitude and location biases. The similarities between the circulation features of the severe 1415SD and other drought events over the region show that understanding of the dynamics of the past drought events over SSP could guide assessment of changes in risk of future droughts and improvements of model performance. In the model world, a modest human influence for the 2014/15 SSP meteorological drought is found. The study highlights the merits and limitations of the HadGEM3GA6 simulations. The model possesses the skills in simulating the large-scale atmospheric circulations modulating precipitation variability, leading to drought conditions over SSP.

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