scholarly journals Influences of Local and Remote Conditions on Tropical Precipitation and Its Response to Climate Change

2020 ◽  
Vol 33 (10) ◽  
pp. 4045-4063
Author(s):  
Marion Saint-Lu ◽  
Robin Chadwick ◽  
F. Hugo Lambert ◽  
Matthew Collins ◽  
Ian Boutle ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Pattern ◽  
General Circulation Models ◽  
Overturning Circulation ◽  
Surface Warming ◽  
Single Column ◽  
Precipitation Changes

AbstractBy comparing a single-column model (SCM) with closely related general circulation models (GCMs), precipitation changes that can be diagnosed from local changes in surface temperature (TS) and relative humidity (RHS) are separated from more complex responses. In the SCM setup, the large-scale tropical circulation is parameterized to respond to the surface temperature departure from a prescribed environment, following the weak temperature gradient (WTG) approximation and using the damped gravity wave (DGW) parameterization. The SCM is also forced with moisture variations. First, it is found that most of the present-day mean tropical rainfall and circulation pattern is associated with TS and RHS patterns. Climate change experiments with the SCM are performed, imposing separately surface warming and CO2 increase. The rainfall responses to future changes in sea surface temperature patterns and plant physiology are successfully reproduced, suggesting that these are direct responses to local changes in convective instability. However, the SCM increases oceanic rainfall too much, and fails to reproduce the land rainfall decrease, both of which are associated with uniform ocean warming. It is argued that remote atmospheric teleconnections play a crucial role in both weakening the atmospheric overturning circulation and constraining precipitation changes. Results suggest that the overturning circulation weakens, both as a direct local response to increased CO2 and in response to energy-imbalance driven exchanges between ascent and descent regions.

scholarly journals North Atlantic 20th century multidecadal variability in coupled climate models: sea surface temperature and ocean overturning circulation

Ocean Science ◽  
2011 ◽  
Vol 7 (3) ◽  
pp. 389-404 ◽  
Author(s):  
I. Medhaug ◽  
T. Furevik
Keyword(s):  
Surface Temperature ◽  
20Th Century ◽  
North Atlantic ◽  
General Circulation ◽  
General Circulation Models ◽  
Meridional Overturning Circulation ◽  
Overturning Circulation ◽  
Atlantic Sector ◽  
The North ◽  
The North Atlantic

Abstract. Output from a total of 24 state-of-the-art Atmosphere-Ocean General Circulation Models is analyzed. The models were integrated with observed forcing for the period 1850–2000 as part of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. All models show enhanced variability at multi-decadal time scales in the North Atlantic sector similar to the observations, but with a large intermodel spread in amplitudes and frequencies for both the Atlantic Multidecadal Oscillation (AMO) and the Atlantic Meridional Overturning Circulation (AMOC). The models, in general, are able to reproduce the observed geographical patterns of warm and cold episodes, but not the phasing such as the early warming (1930s–1950s) and the following colder period (1960s–1980s). This indicates that the observed 20th century extreme in temperatures are due to primarily a fortuitous phasing of intrinsic climate variability and not dominated by external forcing. Most models show a realistic structure in the overturning circulation, where more than half of the available models have a mean overturning transport within the observed estimated range of 13–24 Sverdrup. Associated with a stronger than normal AMOC, the surface temperature is increased and the sea ice extent slightly reduced in the North Atlantic. Individual models show potential for decadal prediction based on the relationship between the AMO and AMOC, but the models strongly disagree both in phasing and strength of the covariability. This makes it difficult to identify common mechanisms and to assess the applicability for predictions.

The Double-ITCZ Syndrome in Coupled General Circulation Models: The Role of Large-Scale Vertical Circulation Regimes

2010 ◽  
Vol 23 (5) ◽  
pp. 1127-1145 ◽  
Author(s):  
A. Bellucci ◽  
S. Gualdi ◽  
A. Navarra
Keyword(s):  
Surface Temperature ◽  
Systematic Error ◽  
General Circulation ◽  
Large Scale ◽  
Deep Convection ◽  
General Circulation Models ◽  
Intertropical Convergence Zone ◽  
Convergence Zone ◽  
Vertical Circulation ◽  
Coupled General Circulation Models

Abstract The double–intertropical convergence zone (DI) systematic error, affecting state-of-the-art coupled general circulation models (CGCMs), is examined in the multimodel Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) ensemble of simulations of the twentieth-century climate. The aim of this study is to quantify the DI error on precipitation in the tropical Pacific, with a specific focus on the relationship between the DI error and the representation of large-scale vertical circulation regimes in climate models. The DI rainfall signal is analyzed using a regime-sorting approach for the vertical circulation regimes. Through the use of this compositing technique, precipitation events are regime sorted based on the large-scale vertical motions, as represented by the midtropospheric Lagrangian pressure tendency ω500 dynamical proxy. This methodology allows partition of the precipitation signal into deep and shallow convective components. Following the regime-sorting diagnosis, the total DI bias is split into an error affecting the magnitude of precipitation associated with individual convective events and an error affecting the frequency of occurrence of single convective regimes. It is shown that, despite the existing large intramodel differences, CGCMs can be ultimately grouped into a few homogenous clusters, each featuring a well-defined rainfall–vertical circulation relationship in the DI region. Three major behavioral clusters are identified within the AR4 models ensemble: two unimodal distributions, featuring maximum precipitation under subsidence and deep convection regimes, respectively, and one bimodal distribution, displaying both components. Extending this analysis to both coupled and uncoupled (atmosphere only) AR4 simulations reveals that the DI bias in CGCMs is mainly due to the overly frequent occurrence of deep convection regimes, whereas the error on rainfall magnitude associated with individual convective events is overall consistent with errors already present in the corresponding atmosphere stand-alone simulations. A critical parameter controlling the strength of the DI systematic error is identified in the model-dependent sea surface temperature (SST) threshold leading to the onset of deep convection (THR), combined with the average SST in the southeastern Pacific. The models featuring a THR that is systematically colder (warmer) than their mean surface temperature are more (less) prone to exhibit a spurious southern intertropical convergence zone.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals Relative Humidity in the Troposphere with AIRS

2014 ◽  
Vol 71 (7) ◽  
pp. 2516-2533 ◽  
Author(s):  
Alexander Ruzmaikin ◽  
Hartmut H. Aumann ◽  
Evan M. Manning
Keyword(s):  
Relative Humidity ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
General Circulation ◽  
Large Scale ◽  
Statistical Significance ◽  
General Circulation Models ◽  
Positive Trend ◽  
Drying Time ◽  
Clear Sky

Abstract New global satellite data from the Atmospheric Infrared Sounder (AIRS) are applied to study the tropospheric relative humidity (RH) distribution and its influence on outgoing longwave radiation (OLR) for January and July in 2003, 2007, and 2011. RH has the largest maxima over 90% in the equatorial tropopause layer in January. Maxima in July do not arise above 60%. Seasonal variations of about 20% in zonally averaged RH are observed in the equatorial region of the low troposphere, in the equatorial tropopause layer, and in the polar regions. The seasonal variability in the recent decade has increased by about 5% relative to that in 1973–88, indicating a positive trend. The observed RH profiles indicate a moist bias in the tropical and subtropical regions typically produced by the general circulation models. The new data and method of evaluating the statistical significance of bimodality confirm bimodal probability distributions of RH at large tropospheric scales, notably in the ascending branch of the Hadley circulation. Bimodality is also seen at 500–300 hPa in mid- and high latitudes. Since the drying time of the air is short compared with the mixing time of moist and dry air, the bimodality reflects the large-scale distribution of sources of moisture and the atmospheric circulation. Analysis of OLR dependence on surface temperature shows a 0.2 W m−2 K−1 difference in sensitivities between clear-sky and all-sky OLR, indicating a positive longwave cloud radiative forcing. Diagrams of the clear-sky OLR as functions of percentiles of surface temperature and relative humidity in the tropics are designed to provide a new measure of the supergreenhouse effect.

A new method for assessing the performance of general circulation models based on their ability to simulate the response to observed forcing

2021 ◽  
pp. 1-52
Author(s):  
M.A. Altamirano del Carmen ◽  
F. Estrada ◽  
C. Gay-García
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
General Circulation ◽  
Statistical Tests ◽  
General Circulation Models ◽  
Warming Trend ◽  
Global Scale ◽  
Adequate Representation ◽  
Warming Rate

AbstractThe reliability of General Circulation Models (GCMs) is commonly associated with their ability to reproduce relevant aspects of observed climate and thus, the evaluation of GCMs performance has become a standard practice for climate change studies. As such, there is an ever-growing literature that focuses on developing and evaluating metrics to assess GCMs performance. In this paper it is shown that some commonly applied metrics provide little information for discriminating GCMs based on their performance, once uncertainty is included. A new methodology is proposed that differs from common approaches in that it focuses on evaluating GCMs ability to reproduce the observed response of surface temperature to changes in external radiative forcing (RF), while controlling for observed and simulated variability. It uses formal statistical tests to evaluate two aspects of the warming trend that are central for climate change studies: 1) if the response to RF produced by a particular GCM is compatible with observations and 2) if the magnitudes of the observed and simulated rates of warming are statistically similar. We illustrate the proposed methodology by evaluating the ability of 21 GCMs to reproduce the observed warming trend at the global scale and eight sub-continental land domains. Results show that most of the GCMs provide an adequate representation of the observed warming trend for the global scale and for domains located in the southern hemisphere. However, GCMs tend to overestimate the warming rate for domains in the northern hemisphere, particularly since the mid-1990s.

scholarly journals Climate Change Implications for Tropical Islands: Interpolating and Interpreting Statistically Downscaled GCM Projections for Management and Planning

2016 ◽  
Vol 55 (2) ◽  
pp. 265-282 ◽  
Author(s):  
Azad Henareh Khalyani ◽  
William A. Gould ◽  
Eric Harmsen ◽  
Adam Terando ◽  
Maya Quinones ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
General Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Model Averaging ◽  
General Circulation Models ◽  
Economic Effects ◽  
Drought Indices ◽  
Tropical Islands

AbstractThe potential ecological and economic effects of climate change for tropical islands were studied using output from 12 statistically downscaled general circulation models (GCMs) taking Puerto Rico as a test case. Two model selection/model averaging strategies were used: the average of all available GCMs and the average of the models that are able to reproduce the observed large-scale dynamics that control precipitation over the Caribbean. Five island-wide and multidecadal averages of daily precipitation and temperature were estimated by way of a climatology-informed interpolation of the site-specific downscaled climate model output. Annual cooling degree-days (CDD) were calculated as a proxy index for air-conditioning energy demand, and two measures of annual no-rainfall days were used as drought indices. Holdridge life zone classification was used to map the possible ecological effects of climate change. Precipitation is predicted to decline in both model ensembles, but the decrease was more severe in the “regionally consistent” models. The precipitation declines cause gradual and linear increases in drought intensity and extremes. The warming from the 1960–90 period to the 2071–99 period was 4.6°–9°C depending on the global emission scenarios and location. This warming may cause increases in CDD, and consequently increasing energy demands. Life zones may shift from wetter to drier zones with the possibility of losing most, if not all, of the subtropical rain forests and extinction risks to rain forest specialists or obligates.

Global monthly sea surface temperature and sea ice reconstruction for historical simulations

2020 ◽  
Author(s):  
Eric Samakinwa ◽  
Stefan Brönnimann
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
General Circulation Models ◽  
Sea Surface ◽  
Annual Variability ◽  
Instrumental Records

<p>Variability in Sea Surface Temperature (SST) is one of the prime sources of intra-annual variability, and also an important boundary condition for Atmospheric General Circulation Models (AGCMs). In many AGCM simulations, SST and Sea Ice Concentration (SIC) are prescribed. While SSTs are specified according to observations available in recent period of instrumental records (1850 – present), SIC depends on climatological averages with less variability prior to the inception of satellite measurements. This limits our understanding of large-scale climate variations in the past.</p><p>In this study, we augment multi-proxy reconstructed annual mean temperature of Neukom et al. (2019) with intra-annual variability from HadISST (v2.0), for 850 years (1000 – 1849). Intra-seasonal variability, such as the phase-locking of El-Nino Southern Oscillation, Indian Ocean Dipole and Tropical Atlantic SST indices to annual-cycle, are utilized. The intra-annual component of HadISST and SST indices estimated from the multi-proxy reconstructed annual mean, are used to develop grid-based multivariate linear regression models using the Frisch-Waugh-Lovell theorem, in a monthly stratified approach. Furthermore, we introduce a scaling technique to ensure homogeneous mean and variance, similar to that of the target. SST observations obtained from ship measurements by ICOADS before 1850, will be integrated in an off-line data assimilation approach.</p><p>Similarly, we reconstruct SIC via analogue resampling of HadISST SIC (1941 – 2000), for both hemispheres. We pool our analogues in four seasons, comprising of 3 months each, such that for each month within a season, there are 180 possible analogues. The best analogues are selected based on correlation coefficients between reconstructed SST and its target.</p>

Land–Ocean Shifts in Tropical Precipitation Linked to Surface Temperature and Humidity Change

2017 ◽  
Vol 30 (12) ◽  
pp. 4527-4545 ◽  
Author(s):  
F. Hugo Lambert ◽  
Angus J. Ferraro ◽  
Robin Chadwick
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
General Circulation Models ◽  
Specific Humidity ◽  
Near Surface ◽  
Tropical Precipitation ◽  
Humidity Change ◽  
Cmip5 Gcms

A compositing scheme that predicts changes in tropical precipitation under climate change from changes in near-surface relative humidity (RH) and temperature is presented. As shown by earlier work, regions of high tropical precipitation in general circulation models (GCMs) are associated with high near-surface RH and temperature. Under climate change, it is found that high precipitation continues to be associated with the highest surface RH and temperatures in most CMIP5 GCMs, meaning that it is the “rank” of a given GCM grid box with respect to others that determines how much precipitation falls rather than the absolute value of surface temperature or RH change, consistent with the weak temperature gradient approximation. Further, it is demonstrated that the majority of CMIP5 GCMs are close to a threshold near which reductions in land RH produce large reductions in the RH ranking of some land regions, causing reductions in precipitation over land, particularly South America, and compensating increases over ocean. Recent work on predicting future changes in specific humidity allows the prediction of the qualitative sense of precipitation change in some GCMs when land surface humidity changes are unknown. However, the magnitudes of predicted changes are too small. Further study, perhaps into the role of radiative and land–atmosphere feedbacks, is necessary.

scholarly journals Hurricane Sandy before 1900 and after 2100

2015 ◽  
Vol 96 (4) ◽  
pp. 547-560 ◽  
Author(s):  
Gary M. Lackmann
Keyword(s):  
Climate Change ◽  
New York ◽  
Life Cycle ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Hurricane Sandy ◽  
Coastal Development ◽  
Future Climate Change ◽  
The Bahamas

Abstract To what extent did large-scale thermodynamic climate change contribute to the intensity and unusual track of Hurricane Sandy, which affected the U.S. mid-Atlantic region in late October 2012? How much of an impact would projected future climate change have on a storm such as Sandy? These questions are investigated using an ensemble of high-resolution numerical simulations in conjunction with analyzed and projected changes from a suite of general circulation models (GCMs). Simulations initialized with current analyses from the midpoint of Sandy’s life cycle, while the system was centered near the Bahamas, adequately replicate the observed intensity and track of Sandy. Initial and boundary condition data are then altered with thermodynamic change fields obtained from a five-member GCM ensemble, allowing hypothetical replication of the synoptic weather pattern that accompanied Hurricane Sandy, but for large-scale thermodynamic conditions corresponding to the 1880s and for projections to the twenty-second century. The past ensemble produces a slightly weaker storm that makes landfall south of the observed location. The future ensemble depicts a significantly more intense system that makes landfall farther north, near Long Island, New York. Within the limitations of the methods used, it is suggested that climate change to date exerted only a modest influence on the intensity and track of Sandy. The strengthening in the simulations run with projected future warming is consistent with increased condensational heating; changes in the synoptic steering flow also appear to result from diabatic processes. The questions of how climate change affected Sandy’s genesis and early life cycle, changes in the frequency of this type of synoptic pattern, and changes in impacts related to coastal development and sea level rise are not considered here.

scholarly journals North American April tornado occurrences linked to global sea surface temperature anomalies

2019 ◽  
Vol 5 (8) ◽  
pp. eaaw9950 ◽  
Author(s):  
J.-E. Chu ◽  
A. Timmermann ◽  
J.-Y. Lee
Keyword(s):  
United States ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North American ◽  
General Circulation ◽  
Large Scale ◽  
Moisture Flux ◽  
General Circulation Models ◽  
The United States ◽  
Sea Surface

Annual tornado occurrences over North America display large interannual variability and a statistical linkage to sea surface temperature (SST) anomalies. However, the underlying physical mechanisms for this connection and its modulation in a rapidly varying seasonal environment still remain elusive. Using tornado data over the United States from 1954 to 2016 in combination with SST-forced atmospheric general circulation models, we show a robust dynamical linkage between global SST conditions in April, the emergence of the Pacific-North American teleconnection pattern (PNA), and the year-to-year tornado activity in the Southern Great Plains (SGP) region of the United States. Contrasting previous studies, we find that only in April SST-driven atmospheric circulation anomalies can effectively control the northward moisture-laden flow from the Gulf of Mexico, boosting low-level moisture flux convergence over the SGP. These strong large-scale connections are absent in other months because of the strong seasonality of the PNA and background moisture conditions.

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