scholarly journals The Caribbean Low-Level Jet and Its Relationship with Precipitation in IPCC AR4 Models

2011 ◽  
Vol 24 (22) ◽  
pp. 5935-5950 ◽  
Author(s):  
Elinor R. Martin ◽  
Courtney Schumacher

Abstract A census of 19 coupled and 12 uncoupled model runs from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) shows that all models have the ability to simulate the location and height of the Caribbean low-level jet (CLLJ); however, the observed semiannual cycle of the CLLJ magnitude was a challenge for the models to reproduce. In particular, model means failed to capture the strong July CLLJ peak as a result of the lack of westward and southward expansion of the North Atlantic subtropical high (NASH) between May and July. The NASH was also found to be too strong, particularly during the first 6 months of the year in the coupled model runs, which led to increased meridional sea level pressure gradients across the southern Caribbean and, hence, an overly strong CLLJ. The ability of the models to simulate the correlation between the CLLJ and regional precipitation varied based on season and region. During summer months, the negative correlation between the CLLJ and Caribbean precipitation anomalies was reproduced in the majority of models, with uncoupled models outperforming coupled models. The positive correlation between the CLLJ and the central U.S. precipitation during February was more challenging for the models, with the uncoupled models failing to reproduce a significant relationship. This may be a result of overactive convective parameterizations raining out too much moisture in the Caribbean meaning less is available for transport northward, or due to incorrect moisture fluxes over the Gulf of Mexico. The representation of the CLLJ in general circulation models has important consequences for accurate predictions and projections of future climate in the Caribbean and surrounding regions.

2010 ◽  
Vol 23 (6) ◽  
pp. 1477-1494 ◽  
Author(s):  
Kerry H. Cook ◽  
Edward K. Vizy

Abstract The easterly Caribbean low-level jet (CLLJ) is a prominent climate feature over the Intra-America Seas, and it is associated with much of the water vapor transport from the tropical Atlantic into the Caribbean Basin. In this study, the North American Regional Reanalysis (NARR) is analyzed to improve the understanding of the dynamics of the CLLJ and its relationship to regional rainfall variations. Horizontal momentum balances are examined to understand how jet variations on both diurnal and seasonal time scales are controlled. The jet is geostrophic to the first order. Its previously documented semidiurnal cycle (with minima at about 0400 and 1600 LT) is caused by semidiurnal cycling of the meridional geopotential height gradient in association with changes in the westward extension of the North Atlantic subtropical high (NASH). A diurnal cycle is superimposed, associated with a meridional land–sea breeze (solenoidal circulation) onto the north coast of South America, so that the weakest jet velocities occur at 1600 LT. The CLLJ is present throughout the year, and it is known to vary in strength semiannually. Peak magnitudes in July are related to the seasonal cycle of the NASH, and a second maximum in February is caused by heating over northern South America. From May through September, zonal geopotential gradients associated with summer heating over Central America and Mexico induce meridional flow. The CLLJ splits into two branches, including a southerly branch that connects with the Great Plains low-level jet (GPLLJ) bringing moisture into the central United States. During the rest of the year, the flow remains essentially zonal across the Caribbean Basin and into the Pacific. A strong (weak) CLLJ is associated with reduced (enhanced) rainfall over the Caribbean Sea throughout the year in the NARR. The relationship with precipitation over land depends on the season. Despite the fact that the southerly branch of the CLLJ feeds into the meridional GPLLJ in May through September, variations in the CLLJ strength during these months do not impact U.S. precipitation, because the CLLJ strength is varying in response to regional-scale forcing and not to changes in the large-scale circulation. During the cool season, there are statistically significant correlations between the CLLJ index and rainfall over the United States. When the CLLJ is strong, there is anomalous northward moisture transport across the Gulf of Mexico into the central United States and pronounced rainfall increases over Louisiana and Texas. A weak jet is associated with anomalous westerly flow across the southern Caribbean region and significantly reduced rainfall over the south-central United States. No connection between the intensity of the CLLJ and drought over the central United States is found. There are only three drought summers in the NARR period (1980, 1988, and 2006), and the CLLJ was extremely weak in 1988 but not in 1980 or 2006.


2009 ◽  
Vol 16 (4) ◽  
pp. 453-473 ◽  
Author(s):  
J. Boucharel ◽  
B. Dewitte ◽  
B. Garel ◽  
Y. du Penhoat

Abstract. El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability in the Pacific, having socio-economic impacts on surrounding regions. ENSO exhibits significant modulation on decadal to inter-decadal time scales which is related to changes in its characteristics (onset, amplitude, frequency, propagation, and predictability). Some of these characteristics tend to be overlooked in ENSO studies, such as its asymmetry (the number and amplitude of warm and cold events are not equal) and the deviation of its statistics from those of the Gaussian distribution. These properties could be related to the ability of the current generation of coupled models to predict ENSO and its modulation. Here, ENSO's non-Gaussian nature and asymmetry are diagnosed from in situ data and a variety of models (from intermediate complexity models to full-physics coupled general circulation models (CGCMs)) using robust statistical tools initially designed for financial mathematics studies. In particular α-stable laws are used as theoretical background material to measure (and quantify) the non-Gaussian character of ENSO time series and to estimate the skill of ``naïve'' statistical models in producing deviation from Gaussian laws and asymmetry. The former are based on non-stationary processes dominated by abrupt changes in mean state and empirical variance. It is shown that the α-stable character of ENSO may result from the presence of climate shifts in the time series. Also, cool (warm) periods are associated with ENSO statistics having a stronger (weaker) tendency towards Gaussianity and lower (greater) asymmetry. This supports the hypothesis of ENSO being rectified by changes in mean state through nonlinear processes. The relationship between changes in mean state and nonlinearity (skewness) is further investigated both in the Zebiak and Cane (1987)'s model and the models of the Intergovernmental Panel for Climate Change (IPCC). Whereas there is a clear relationship in all models between ENSO asymmetry (as measured by skewness or nonlinear advection) and changes in mean state, they exhibit a variety of behaviour with regard to α-stability. This suggests that the dynamics associated with climate shifts and the occurrence of extreme events involve higher-order statistical moments that cannot be accounted for solely by nonlinear advection.


2009 ◽  
Vol 10 (2) ◽  
pp. 413-430 ◽  
Author(s):  
Mark R. Jury

Abstract This study examines the spatial variability of mean annual rainfall in the Caribbean in the satellite era 1979–2000. Intercomparisons of gridded rainfall fields from conventional stations, satellite estimators, reanalysis products, and coupled general circulation models (CGCMs) are made, with a focus on the Antilles island chain and their land–sea transitions. The rainfall products are rated for their ability to capture a number of key features, including (i) topographically enhanced precipitation over the larger western Antilles islands of Cuba, Jamaica, Hispanola, and Puerto Rico; (ii) the rain shadow west of Hispanola; (iii) the two dry zones where SSTs are low: north of Venezuela and north of the Lesser Antilles; and (iv) the wet axis extending north of Trinidad. The various monitoring and modeling systems produce gridded rainfall fields at resolutions from 50 to 280 km, from station reconstructions, satellite estimates, blended and reanalysis products, and CGCM climatologies with respect to surface forcing fields. Wet and dry biases were found in many of the reanalysis and satellite products, respectively—either over the whole Caribbean or in a certain sector. The intercomparison found some measure of consensus, but no single product is without discrepancy. High-resolution passive microwave satellite rainfall estimates [Climate Prediction Center’s multisaltellite passive microwave, IR morphed product (cMOR)] appear “most representative”; however, the climatology is short (2003–07) and the field is generally drier than the consensus. Of the conventional products, decadal variability of climate interpolated rain gauges (DEKL), World Climate Research Programme’s (WCRP) blended rain gauges, the Comprehensive Ocean–Atmosphere Data Set (COADS), and an operational climate anomaly monitoring system of NCEP (CAMS) perform well. Among the satellite estimators, the Global Precipitation Climatology Project’s blended gauge and IR satellite (GPCP) and outgoing longwave radiation (OLR) capture the key features and ocean–island transitions. The Center for Ocean–Land–Atmosphere Studies [COLA; the coupled model, part of the Coupled Model Intercomparison Project (CMIP, phase 3)] and the climate forecast system of the NCEP (CFS) models perform reasonably, but NCAR’s Parallel Climate Model (PCM; the CGCM’s historical run of CMIP3) fares poorly. The version 2 hindcast of the operational Medium-Range Forecast (MRF) weather prediction model (REAN) captures the smaller wet zones and topographically enhanced features, but it does not handle the broad oceanic dry zones well, as the input from the operational climate data assimilation system of NCEP (CDAS) has a wet bias. Of the various key rainfall features, high rainfall over southern Cuba and the rain shadow west of Hispanola are poorly handled by most products. The wet axis north of Trinidad and the dry zone north of Venezuela are well represented in many climatologies.


2011 ◽  
Vol 24 (11) ◽  
pp. 2771-2783 ◽  
Author(s):  
Ruth Cerezo-Mota ◽  
Myles Allen ◽  
Richard Jones

Abstract Key mechanisms important for the simulation and better understanding of the precipitation of the North American monsoon (NAM) were analyzed in this paper. Three experiments with the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model, the Hadley Centre Regional Model version 3P (HadRM3P), driven by different boundary conditions were carried out. After a detailed analysis of the moisture and low-level winds derived from the models, the authors conclude that the Gulf of Mexico (GoM) moisture and the Great Plains low-level jet (GPLLJ) play an important role in the northern portion of the NAM. Moreover, the realistic simulation of these features is necessary for a better simulation of precipitation in the NAM. Previous works suggest that the influence of moisture from the GoM in Arizona–New Mexico (AZNM) takes place primarily via the middle- and upper-tropospheric flow (above 700 mb). However, it is shown here that if the GoM does not supply enough moisture and the GPLLJ at lower levels (below 700 mb) does not reach the AZNM region, then a dry westerly flow dominates that area and the summer precipitation is below normal. The implications of these findings for studies of climate change are demonstrated with the analysis of two general circulation models (GCMs) commonly used for climate change prediction, which are shown not to reproduce correctly the GPLLJ intensity nor the moisture in the GoM. This implies that the precipitation in AZNM would not be correctly represented by a regional model driven by these GCMs.


2007 ◽  
Vol 20 (6) ◽  
pp. 1093-1107 ◽  
Author(s):  
Muyin Wang ◽  
James E. Overland ◽  
Vladimir Kattsov ◽  
John E. Walsh ◽  
Xiangdong Zhang ◽  
...  

Abstract There were two major multiyear, Arctic-wide (60°–90°N) warm anomalies (>0.7°C) in land surface air temperature (LSAT) during the twentieth century, between 1920 and 1950 and again at the end of the century after 1979. Reproducing this decadal and longer variability in coupled general circulation models (GCMs) is a critical test for understanding processes in the Arctic climate system and increasing the confidence in the Intergovernmental Panel on Climate Change (IPCC) model projections. This study evaluated 63 realizations generated by 20 coupled GCMs made available for the IPCC Fourth Assessment for their twentieth-century climate in coupled models (20C3M) and corresponding control runs (PIcntrl). Warm anomalies in the Arctic during the last two decades are reproduced by all ensemble members, with considerable variability in amplitude among models. In contrast, only eight models generated warm anomaly amplitude of at least two-thirds of the observed midcentury warm event in at least one realization, but not its timing. The durations of the midcentury warm events in all the models are decadal, while that of the observed was interdecadal. The variance of the control runs in nine models was comparable with the variance in the observations. The random timing of midcentury warm anomalies in 20C3M simulations and the similar variance of the control runs in about half of the models suggest that the observed midcentury warm period is consistent with intrinsic climate variability. Five models were considered to compare somewhat favorably to Arctic observations in both matching the variance of the observed temperature record in their control runs and representing the decadal mean temperature anomaly amplitude in their 20C3M simulations. Seven additional models could be given further consideration. Results support selecting a subset of GCMs when making predictions for future climate by using performance criteria based on comparison with retrospective data.


2016 ◽  
Vol 97 (12) ◽  
pp. 2305-2328 ◽  
Author(s):  
Paquita Zuidema ◽  
Ping Chang ◽  
Brian Medeiros ◽  
Ben P. Kirtman ◽  
Roberto Mechoso ◽  
...  

Abstract Well-known problems trouble coupled general circulation models of the eastern Atlantic and Pacific Ocean basins. Model climates are significantly more symmetric about the equator than is observed. Model sea surface temperatures are biased warm south and southeast of the equator, and the atmosphere is too rainy within a band south of the equator. Near-coastal eastern equatorial SSTs are too warm, producing a zonal SST gradient in the Atlantic opposite in sign to that observed. The U.S. Climate Variability and Predictability Program (CLIVAR) Eastern Tropical Ocean Synthesis Working Group (WG) has pursued an updated assessment of coupled model SST biases, focusing on the surface energy balance components, on regional error sources from clouds, deep convection, winds, and ocean eddies; on the sensitivity to model resolution; and on remote impacts. Motivated by the assessment, the WG makes the following recommendations: 1) encourage identification of the specific parameterizations contributing to the biases in individual models, as these can be model dependent; 2) restrict multimodel intercomparisons to specific processes; 3) encourage development of high-resolution coupled models with a concurrent emphasis on parameterization development of finer-scale ocean and atmosphere features, including low clouds; 4) encourage further availability of all surface flux components from buoys, for longer continuous time periods, in persistently cloudy regions; and 5) focus on the eastern basin coastal oceanic upwelling regions, where further opportunities for observational–modeling synergism exist.


2012 ◽  
Vol 5 (2) ◽  
pp. 837-871 ◽  
Author(s):  
F. J. Bragg ◽  
D. J. Lunt ◽  
A. M. Haywood

Abstract. The Pliocene Model Intercomparison Project (PlioMIP) project is a sub-project of the Paleoclimate Modelling Intercomparison Project (PMIP) whose objective is to compare predictions of the mid-Pliocene climate from the widest possible range of general circulation models. The mid-Pliocene (3.3–3.0 Ma) is the most recent sustained period of greater warmth and atmospheric carbon dioxide concentration than the pre-industrial times and as such has potential to inform predictions of our warming climate in the coming century. This paper describes the UK contribution to PlioMIP using the Hadley Centre Model both in atmosphere-only mode (HadAM3, PlioMIP Experiment 1) and atmosphere-ocean coupled mode (HadCM3, PlioMIP Experiment 2). The coupled model predicts a greater overall warming (3.3 °C) relative to the control than the atmosphere-only (2.5 °C). The Northern Hemisphere latitudinal temperature gradient is greater in the coupled model with a warmer equator and colder Arctic than the atmosphere-only model, which is constrained by sea surface temperatures from Pliocene proxy reconstructions. The atmosphere-only model predicts a reduction in equatorial precipitation and south Asian monsoon intensity whereas the coupled models shows and increase in the intensity of these systems. Sensitivity studies using alternative boundary conditions for both the Pliocene and the control simulations are presented, which indicate the sensitivity of the mid-Pliocene warming to uncertainties in both pre-industrial and mid-Pliocene climate.


2019 ◽  
Vol 11 (4) ◽  
pp. 1355-1369 ◽  
Author(s):  
Guodong Sun ◽  
Fei Peng

Abstract Runoff is an important water flux that is difficult to simulate and predict due to lacking observation. Meteorological forcing data are a key factor in causing the uncertainty of predicted runoff. In this study, climate projections from ten general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5) with high resolution under the Representative Concentration Pathway (RCP) 4.5 scenario are employed to estimate the future uncertainty range of predicted runoff in the North–South Transect of Eastern China (NSTEC) from 2011 to 2100. It is found that the range of future annual runoff is from 268.9 mm (Meteorological Research Institute coupled GCM, MRI-CGCM3) to 544.2 mm (Model for Interdisciplinary Research on Climate, MIROC5). The precipitation and the annual actual evapotranspiration are two key factors that affect the variation of runoff. The low annual runoff for the MRI-CGCM3 model may be caused by low precipitation and high annual actual evapotranspiration (466.9 mm). However, the high annual runoff for the MIROC5 may be caused by the high precipitation, although there is high annual actual evapotranspiration (544.2 mm). The above results imply that the forcing data and the model physics are important factors in the numerical simulation and prediction about runoff.


2021 ◽  
Author(s):  
Rui Ren ◽  
Xuemei Li ◽  
Lanhai Li ◽  
Yiyu Huang

Abstract The general circulation models (GCMs) from the coupled model intercomparison project phase 5 (CMIP5) were used to evaluate the simulation capabilities of rainfall-to-precipitation ratio (RPR) from 1961 to 2018 at 28 meteorological stations in the Tianshan Mountains region (TMR). Moreover, it was estimated the change of RPR in the months experiencing freezing-thawing transitions from 2011 to 2100 under three representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5. The results indicated that the simulated air temperature from CMIP5 was highly correlated with the observed values, while the performance for precipitation was poor. Therefore, it is feasible to forecast the future RPR employing the temperature provided by CMIP5 and the observed meteorological factors by the BP neural network (BNN). Under three emission scenarios, the RPR in the months experiencing freezing-thawing transitions during 2011-2100 will increase compared to that during the baseline period (1981-2010). Under the same emission scenario, values of RPR will increase as the time goes on. Besides, in terms of spatial variation, values of RPR in the south slope will be larger than that in the north slope under three emission scenarios. Furthermore, values of RPR exhibit different variation characteristics under different emission scenarios. Under the RCP2.6 emission scenario, as the time goes on, values of RPR at more stations will change slightly. Under the RCP4.5 emission scenario, the increase of RPR will occur in the whole TMR and stabilize in the north slope by the end of this century. However, values of RPR will increase significantly through 21st century in the whole TMR under the RCP8.5 emission scenario.


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