Atmospheric Model Intercomparison Project Models Research Articles

A Process Model for ITCZ Narrowing under Warming Highlights Clear-Sky Water Vapor Feedbacks and Gross Moist Stability Changes in AMIP Models

Abstract Tropical areas with mean upward motion—and as such the zonal-mean intertropical convergence zone (ITCZ)—are projected to contract under global warming. To understand this process, a simple model based on dry static energy and moisture equations is introduced for zonally symmetric overturning driven by sea surface temperature (SST). Processes governing ascent area fraction and zonal mean precipitation are examined for insight into Atmospheric Model Intercomparison Project (AMIP) simulations. Bulk parameters governing radiative feedbacks and moist static energy transport in the simple model are estimated from the AMIP ensemble. Uniform warming in the simple model produces ascent area contraction and precipitation intensification—similar to observations and climate models. Contributing effects include stronger water vapor radiative feedbacks, weaker cloud-radiative feedbacks, stronger convection-circulation feedbacks, and greater poleward moisture export. The simple model identifies parameters consequential for the inter-AMIP-model spread; an ensemble generated by perturbing parameters governing shortwave water vapor feedbacks and gross moist stability changes under warming tracks inter-AMIP-model variations with a correlation coefficient ∼0.46. The simple model also predicts the multimodel mean changes in tropical ascent area and precipitation with reasonable accuracy. Furthermore, the simple model reproduces relationships among ascent area precipitation, ascent strength, and ascent area fraction observed in AMIP models. A substantial portion of the inter-AMIP-model spread is traced to the spread in how moist static energy and vertical velocity profiles change under warming, which in turn impact the gross moist stability in deep convective regions—highlighting the need for observational constraints on these quantities. Significance Statement A large rainband straddles Earth’s tropics. Most, but not all, climate models predict that this rainband will shrink under global warming; a few models predict an expansion of the rainband. To mitigate some of this uncertainty among climate models, we build a simpler model that only contains the essential physics of rainband narrowing. We find several interconnected processes that are important. For climate models, the most important process is the efficiency with which clouds move heat and humidity out of rainy regions. This efficiency varies among climate models and appears to be a primary reason for why climate models do not agree on the rate of rainband narrowing.

Intermodel Spread in Walker Circulation Responses Linked to Spread in Moist Stability and Radiation Responses

AbstractThe response of the Pacific Walker circulation (WC) to long‐term warming remains uncertain. Here, we diagnose contributions to the WC response in comprehensive and idealized general circulation model (GCM) simulations. We find that the spread in WC response is substantial across both the Coupled Model Intercomparison Project (CMIP6) and the Atmospheric Model Intercomparison Project (AMIP) models, implicating differences in atmospheric models in the spread in projected WC strength. Using a moist static energy (MSE) budget, we evaluate the contributions to changes in the WC strength related to changes in gross moist stability (GMS), horizontal MSE advection, radiation, and surface fluxes. We find that the multimodel mean WC weakening is mostly related to changes in GMS and radiation. Furthermore, the spread in WC response is related to the spread in GMS and radiation responses. The GMS response is potentially sensitive to parameterized convective entrainment which can affect lapse rates and the depth of convection. We thus investigate the role of entrainment in setting the GMS response by varying the entrainment rate in an idealized GCM. The idealized GCM is run with a simplified Betts‐Miller convection scheme, modified to represent entrainment. The weakening of the WC with warming in the idealized GCM is dampened when higher entrainment rates are used. However, the spread in GMS responses due to differing entrainment rates is much smaller than the spread in GMS responses across CMIP6 models. Therefore, further work is needed to understand the large spread in GMS responses across CMIP6 and AMIP models.

It’s the Heat and the Humidity: The Complementary Roles of Temperature and Specific Humidity to Recent Changes in the Energy Content of the Near‐Surface Atmosphere

AbstractGlobal climate change is a change in the planetary energy (E) balance. It is usually expressed as a change in near‐surface air temperature (Ta), but changes in energy content due to Ta (ET) represent only part of the near‐surface energy balance, which also includes E changes due to specific humidity (ESH). We analyzed MERRA‐2 and ERA5 reanalysis data and 15 CMIP6 Atmospheric Model Intercomparison Project (AMIP) models from 1980 to 2014. Some 44%, 39%, and 50% of MERRA‐2 pixels showed significant increases in ET, ESH, and E, respectively. The average increase in ET (ESH) was 16.9 (13.6) J kg−1 year−1, but AMIP models estimated larger average ET (21.6 J kg−1 year−1) and ESH (16.7 J kg−1 year−1). Global Ta would have increased at nearly double the observed rate if energy was not partitioned into latent heat. Results demonstrate the critical role that specific humidity plays in recent climate changes.

Revisiting the Tropical Atlantic Influence on El Niño–Southern Oscillation

AbstractThe influence of the tropical Atlantic on El Niño–Southern Oscillation (ENSO) is examined using sensitivity experiments with the SINTEX-F general circulation model with prescribed sea surface temperature (SST) distributions based on observations for the period 1982–2018. In the control experiment (CTRL) observed SSTs are prescribed over the global oceans; in the sensitivity experiment observed SSTs are prescribed in the tropical Atlantic only, while in other regions the climatological annual cycle is prescribed. A composite analysis of the model output suggests that cold SST events in the northern tropical Atlantic during boreal spring are associated with near-surface wind changes over the equatorial and subtropical Pacific that are conducive to the development of El Niño, consistent with previous studies. The amplitude of these changes, however, is at most 20% of those observed during typical El Niño events. Likewise, warm events in the equatorial Atlantic produce only about 10% of the wind changes seen in the western equatorial Pacific during the developing phase of typical La Niña events. Similar results are obtained from a partial regression analysis performed on an ensemble of atmosphere-only simulations from phase 6 of the Atmospheric Model Intercomparison Project (AMIP) although the equatorial Atlantic influence is stronger in AMIP. Further analysis of the AMIP models indicates that model biases do not have a major impact on the Atlantic-to-Pacific influence. Overall, the results suggest that the tropical Atlantic has a rather weak influence on ENSO development and mostly acts to modulate ongoing events rather than initiate them.

Impact of the mean state on El Niño induced western North Pacific anomalous anticyclone during its decaying summer in AMIP models

AbstractThrough the diagnosis of 29 Atmospheric Model Inter-comparison Project (AMIP) experiments from the CMIP5 inter-comparison project, we investigate the impact of the mean state on simulated western North Pacific anomalous anticyclone (WNPAC) during El Niño decaying summer. The result indicates that the inter-model difference of the JJA mean precipitation in the Indo-western Pacific warm pool is responsible for the difference of the WNPAC. During the decaying summer of an Eastern Pacific (EP) type El Niño, a model that simulates excessive mean rainfall over the western North Pacific (WNP) reproduces a stronger WNPAC response, through an enhanced local convection-circulation-moisture feedback. The intensity of the simulated WNPAC during the decay summer of a Central Pacific (CP) type El Niño, on the other hand, depends on the mean precipitation over the tropical Indian Ocean. The distinctive WNPAC-mean precipitation relationships between the EP and CP El Niño result from different anomalous SST patterns in the WNP. While the local SST anomaly plays an active role in maintaining the WNPAC during the EP El Niño, it plays a passive role during the CP El Niño. As a result, only the mean-state precipitation/moisture field in the tropical Indian Ocean modulates the circulation anomaly in the WNP in the latter case.

Internal atmospheric variability of net surface heat flux in reanalyses and CMIP5 AMIP simulations

AbstractThe internal atmospheric variability (IAV) of the net surface heat flux (NHF) in the observed 20th/21st century atmosphere is estimated as the residual after removing the sea surface temperature (SST) and externally forced atmospheric response derived from the four atmospheric models of the Atmospheric Model Intercomparison Project (AMIP) simulations under phase 5 of the Coupled Model Intercomparison Project (CMIP5). The mean NHF of four atmospheric reanalysis datasets is an estimate of the observed NHF. Although the AMIP models are forced with the same SST and external forcing, the forced responses differ significantly among AMIP models, suggestive of uncertainty in the models. Besides, the uncertainty of IAV in the reanalyses could also arise from the uncertainty in reanalyses as observations contain errors and reanalysis includes interpolation by models. It is concluded that: (a) The SST/NHF and SST/forced NHF correlations are significantly negative over most of world ocean in the AMIP models, indicating damping of the SST anomalies by the NHF. (b) The IAV of the AMIP models is not correlated with SST, while the positive IAV/SST correlations in the reanalyses suggests the role of IAV in forcing the SST variability in the extra‐tropics. (c) The standard deviation (STD) of the IAV of AMIP models is indistinguishable from that of the mean reanalysis over a majority of world ocean, and the STD of the NHF of the AMIP models is larger than that of the mean reanalysis in the subtropics and midlatitudes. (d) The IAV in the mean reanalysis plays a role in forcing the SST variability in the extra‐tropics (e.g., Atlantic Multidecadal Variability), while it may not be an important forcing in the tropical oceans (e.g., ENSO).

Tropical Cyclone Characteristics in the MERRA‐2 Reanalysis and AMIP Simulations

AbstractThis study evaluates the tropical cyclone (TC) activity in two high‐resolution data sets—MERRA‐2 Reanalysis (Modern‐Era Retrospective Analysis for Research and Applications, Version 2) and MERRA‐2 AMIP (Atmospheric Model Intercomparison Project). These data sets use the same atmospheric model, the Goddard Earth Observing System Model, Version 5 (GEOS‐5) during the same period. However, while MERRA‐2 AMIP is a free‐running atmospheric simulation forced only with sea surface temperature (SST), MERRA‐2 Reanalysis uses an advanced data assimilation system to include a large variety of data sets. Thus, we analyze (1) the sensitivity of TC activity to the model forcing, (2) how well the TCs in both data sets replicate observed TC characteristics, (3) the sensitivity of these results to tracking schemes and thresholds. Standard diagnostics such as the number of tropical cyclones and their intensity distribution are very similar in the AMIP model and the reanalysis. TCs in both data sets are weaker than observed, as is typical for the spatial resolution of these global models. Overall, the use of data assimilation in the MERRA‐2 Reanalysis does not lead to a significantly better TC climatology than in AMIP. Furthermore, comparison of the MERRA‐2 Reanalysis to two other reanalysis data sets shows that MERRA‐2 generates fewer, but more intense TCs, than those reanalysis products.

Quantifying the Tropical Upper Tropospheric Warming Amplification Using Radio Occultation Measurements

AbstractIn the upper troposphere (UT), Global Navigation Satellite System (GNSS) Radio Occultations (ROs) provide accurate air temperatures (<0.5 K) every ∼200 m vertically. We use RO observations from 01/2002 until 12/2018 at 300, 250, and 200 hPa to quantify the tropical upper tropospheric amplification (defined as the ratio of temperature trends in the UT relative to the surface). We compare the RO‐derived results against Atmospheric Infrared Sounder (AIRS), Coupled Model Intercomparison Project Phase 6 (CMIP6) Atmospheric Model Intercomparison Project (AMIP) models, Modern‐Era Retrospective Analysis for Research and Applications version 2 (MERRA‐2), and European Center for Medium‐range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) data. We find that CMIP6 AMIP models show excellent agreement with independent AIRS and RO observations on the magnitude of the UT warming and show warming that is significantly faster than both reanalyses above 250 hPa. Additionally, AIRS and CMIP6 AMIP present excellent agreement with the RO‐measured tropical tropospheric amplification.

Understanding the bias in surface latent and sensible heat fluxes in contemporary AGCMs over tropical oceans

The performance of 20 models participating in the atmospheric model intercomparison project (AMIP) is evaluated concerning surface latent (QLH) and sensible (QSH) heat flux over the tropical oceans (30°S–30°N). Biases were calculated by comparing model fluxes to observations from moored buoys and the objectively analyzed air–sea fluxes (OAFlux) database. All 20 AMIP models overestimate QLH with an ensemble mean bias of 20 W m−2, and 18 of the 20 models overestimate QSH with an ensemble mean bias of 5 W m−2 when compared to OAFlux, implying a systematic positive bias over the tropical oceans. A comparison with buoy observations also showed similar biases. To obtain insights into the causes behind model bias, we quantified the contribution from near-surface winds, specific humidity, and temperatures. It is found that near-surface humidity contributes more to the bias in QLH than wind speed, while air temperature contributes more to bias in QSH than wind speed. On the other hand, the root mean squared error (RMSE) in QLH has contributions from both near-surface humidity and wind. The contribution from humidity to the mean bias in QLH is 13 W m−2, with RMSE of 15 W m−2, suggesting a systematic overestimation of sea-air humidity difference in models. The model ensemble, in general, simulates QLH and QSH better than individual models. Models with higher horizontal and vertical resolutions perform better than coarse resolution models.

Evaluation of Surface Radiative Fluxes over the Tropical Oceans in AMIP Simulations

The performance of 20 models from the Atmospheric Model Intercomparison Project (AMIP) was evaluated concerning surface radiation over the tropical oceans (30° S–30° N) from 1979 to 2000. The model ensemble mean of the net surface shortwave radiation (QSW) was underestimated compared to the International Satellite Cloud Climatology Project (ISCCP) data by 4 W m−2. On the other hand, net longwave radiation (QLW) was overestimated by 4 W m−2, leading to an underestimation of the net surface radiation (Qrad) by 8 W m−2. The most prominent bias in the Qrad appears to be over regions of low-level clouds in the off-equatorial eastern Pacific, eastern Atlantic, and the south-eastern Indian Ocean. The root means squared error of QLW was larger than that of QSW in 17 out of 20 AMIP models. Overestimation of the total cloud cover and atmospheric humidity contributed to the underestimation of Qrad. In general, models with higher horizontal resolutions performed slightly better than those with coarser horizontal resolutions, although some systematic bias persists in all models and in all seasons, in particular, in regions of low-level clouds for QLW, and high-level clouds for QSW. The ensemble mean performed better than most models, but two high-resolution models (GFDL-HIRAM-C180 and GFDL-HIRAM-C360) outperform the model ensemble.

Evaluation of Cloud Liquid Water Path Trends Using a Multi-Decadal Record of Passive Microwave Observations.

In this study, observed cloud liquid water path (LWP) trends from the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) dataset (1988 - 2014) are compared to trends computed from the temporally-coincident records of 16 global climate models (GCMs) participating in the Coupled Model Intercomparison Project 5 (CMIP5). For many regions, observed trend magnitudes are several times larger than the corresponding model mean trend magnitudes. Muted model mean trends are thought to be the result of cancellation effects arising from differing interannual variability characteristics and differences in model physics/dynamics. In most regions, the majority of modeled trends were statisically consistent with the observed trends. This was thought to be because of large estimated errors in both the observations and the models due to interannual variability. Over the southern oceans (south of 40S latitude), general agreement between the observed trend and virtually all GCM trends is also found (~ 1-2 g m-2 decade-1). Observed trends are also compared to those from the atmospheric model intercomparison project (AMIP). Like the CMIP5 models, the majority of modeled AMIP trends were statistically consistent with the observed trends. It was also found that, in regions where the AMIP model mean time series better captures observed interannual variability, it tends to better capture the magnitude of the observed trends.

Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble

The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model’s local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation.

Summer U.S. Surface Air Temperature Variability: Controlling Factors and AMIP Simulation Biases

Abstract This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental United States in the Atmospheric Model Intercomparison Project (AMIP) experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-yr period (1979–2008). Regions of high SAT variability are closely associated with midtropospheric highs, subsidence, and radiative heating accompanying clear-sky conditions. The land surface exerts a spatially variable influence on SAT through the sensible heat flux and is a second-order effect in the high-variability centers of action (COAs) in observational estimates. The majority of the AMIP models feature high SAT variability over the central United States, displaced south and/or west of observed COAs. SAT COAs in models tend to be concomitant and strongly coupled with regions of high sensible heat flux variability, suggesting that excessive land–atmosphere interaction in these models modulates U.S. summer SAT. In the central United States, models with climatological warm biases also feature less evapotranspiration than ERA-Interim but reasonably reproduce observed SAT variability in the region. Models that overestimate SAT variability tend to reproduce ERA-Interim SAT and evapotranspiration climatology. In light of potential model biases, this analysis calls for careful evaluation of the land–atmosphere interaction hot spot region identified in the central United States. Additionally, tropical sea surface temperatures play a role in forcing the leading EOF mode for summer SAT in models. This relationship is not apparent in observations.

Climate model simulation of the South Indian Ocean Convergence Zone: mean state and variability

Evaluation of climate model performance at regional scales is essential in determining confidence in simulations of present and future climate. Here we developed a process-based approach focussing on the South Indian Ocean Convergence Zone (SIOCZ), a large-scale, austral summer rainfall feature extending across southern Africa into the southwest Indian Ocean. Simulation of the SIOCZ was evaluated for the Coupled Model Intercomparison Project (CMIP5). Comparison was made between CMIP5 and Atmospheric Model Intercomparison Project (AMIP) models to diagnose sources of biases associated with coupled ocean-atmosphere processes. Models were assessed in terms of mean SIOCZ characteristics and processes of interannual variability. Most models simulated a SIOCZ feature, but were typically too zonally oriented. A systematic bias of excessive precipitation was found over southern Africa and the Indian Ocean, but not particularly along the SIOCZ. Excessive precipitation over the continent may be associated with excessively high low-level moisture flux around the Angola Low found in most models, which is almost entirely due to circulation biases in models. AMIP models represented precipitation more realistically over the Indian Ocean, implying a potential coupling error. Interannual variability in the SIOCZ was evaluated through empirical orthogonal function analysis, where results showed a clear dipole pattern, indicative of a northeast-southwest movement of the SIOCZ. The drivers of this shift were significantly related to the El Nino Southern Oscillation and the subtropical Indian Ocean dipole in observations. However, the models did not capture these teleconnections well, limiting our confidence in model representation of variability.

ENSO-Related Precipitation and Its Statistical Relationship with the Walker Circulation Trend in CMIP5 AMIP Models

Observational evidence shows that the Walker circulation (WC) in the tropical Pacific has strengthened in recent decades. In this study, we examine the WC trend for 1979–2005 and its relationship with the precipitation associated with the El Niño Southern Oscillation (ENSO) using the sea surface temperature (SST)-constrained Atmospheric Model Intercomparison Project (AMIP) simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. All of the 29 models show a strengthening of the WC trend in response to an increase in the SST zonal gradient along the equator. Despite the same SST-constrained AMIP simulations, however, a large diversity is found among the CMIP5 climate models in the magnitude of the WC trend. The relationship between the WC trend and precipitation anomalies (PRCPAs) associated with ENSO (ENSO-related PRCPAs) shows that the longitudinal position of the ENSO-related PRCPAs in the western tropical Pacific is closely related to the magnitude of the WC trend. Specifically, it is found that the strengthening of the WC trend is large (small) in the CMIP5 AMIP simulations in which the ENSO-related PRCPAs are located relatively westward (eastward) in the western tropical Pacific. Therefore, the zonal shift of the ENSO-related precipitation in the western tropical Pacific, which is associated with the climatological mean precipitation in the tropical Pacific, could play an important role in modifying the WC trend in the CMIP5 climate models.

ENSO Asymmetry in CMIP5 Models

Abstract The El Niño–La Niña asymmetry is evaluated in 14 coupled models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The results show that an underestimate of ENSO asymmetry, a common problem noted in CMIP3 models, remains a common problem in CMIP5 coupled models. The weaker ENSO asymmetry in the models primarily results from a weaker SST warm anomaly over the eastern Pacific and a westward shift of the center of the anomaly. In contrast, SST anomalies for the La Niña phase are close to observations. Corresponding Atmospheric Model Intercomparison Project (AMIP) runs are analyzed to understand the causes of the underestimate of ENSO asymmetry in coupled models. The analysis reveals that during the warm phase, precipitation anomalies are weaker over the eastern Pacific, and westerly wind anomalies are confined more to the west in most models. The time-mean zonal winds are stronger over the equatorial central and eastern Pacific for most models. Wind-forced ocean GCM experiments suggest that the stronger time-mean zonal winds and weaker asymmetry in the interannual anomalies of the zonal winds in AMIP models can both be a contributing factor to a weaker ENSO asymmetry in the corresponding coupled models, but the former appears to be a more fundamental factor, possibly through its impact on the mean state. The study suggests that the underestimate of ENSO asymmetry in the CMIP5 coupled models is at least in part of atmospheric origin.

The two interannual variability modes of the Western North Pacific Subtropical High simulated by 28 CMIP5–AMIP models

Using the output of the Atmospheric Model Intercomparison Project (AMIP) experiments of 28 models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), the models’ performances in the simulation of the two dominant interannual variability modes of the Western North Pacific Subtropical High (WNPSH) are investigated. In the observation, the positive phases of these two modes feature an anomalous anticyclone over the western North Pacific (WNP), but the first mode (M1) is closely connected with the sea surface temperature (SST) anomalies over the tropical Indian Ocean (TIO), the maritime continent (MC) and the equatorial central Pacific (CP), while the second mode (M2) is closely connected with the SST anomalies over the WNP. The M1 is well captured by the CMIP5–AMIP models forced by the historical SST, suggesting the M1 is an SST-forced mode. The CMIP5–AMIP models capture the close relationship of the M1 with the SST anomalies over the TIO, the MC and the CP. The forcing mechanisms of M1 in the CMIP5–AMIP models are consistent with the observation, including a Kelvin wave emanating from the TIO and a local Hadley circulation originating from the MC. Different from the high reproducibility of the M1, the M2 is only moderately reproduced by the multi-model ensemble (MME) mean of the CMIP5–AMIP models. The simulated anomalous WNPSH of the M2 is weaker and shifts southwestward in the MME and many individual models compared to the observation. Among the five anomalous WNPSH years associated with the M2, the MME captures the anomalous WNPSH only in 1993 and 1994 but not in 1980, 1981 and 1987. The partial reproducibility of the M2 by the CMIP5–AMIP models suggests the M2 is neither a pure atmospheric internal mode nor a pure SST-forced mode. The observed close relationship between the anomalous WNPSH and the WNP SST anomalies is underestimated by the CMIP5–AMIP models, suggesting the local SST–WNPSH relationship may depend on the air–sea interaction over the WNP.

Estimates of the Water Vapor Climate Feedback during El Niño–Southern Oscillation

Abstract The strength of the water vapor feedback has been estimated by analyzing the changes in tropospheric specific humidity during El Niño–Southern Oscillation (ENSO) cycles. This analysis is done in climate models driven by observed sea surface temperatures [Atmospheric Model Intercomparison Project (AMIP) runs], preindustrial runs of fully coupled climate models, and in two reanalysis products, the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) and the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA). The water vapor feedback during ENSO-driven climate variations in the AMIP models ranges from 1.9 to 3.7 W m−2 K−1, in the control runs it ranges from 1.4 to 3.9 W m−2 K−1, and in the ERA-40 and MERRA it is 3.7 and 4.7 W m−2 K−1, respectively. Taken as a group, these values are higher than previous estimates of the water vapor feedback in response to century-long global warming. Also examined is the reason for the large spread in the ENSO-driven water vapor feedback among the models and between the models and the reanalyses. The models and the reanalyses show a consistent relationship between the variations in the tropical surface temperature over an ENSO cycle and the radiative response to the associated changes in specific humidity. However, the feedback is defined as the ratio of the radiative response to the change in the global average temperature. Differences in extratropical temperatures will, therefore, lead to different inferred feedbacks, and this is the root cause of spread in feedbacks observed here. This is also the likely reason that the feedback inferred from ENSO is larger than for long-term global warming.

Twice wind onsets of monsoon over the western North Pacific and their simulations in AMIP models

AbstractThe absolute angle between wind vectors is used to investigate and describe the seasonal evolutions of wind direction, which is able to indicate the abrupt seasonal shift and stable seasonal state of winds. The results show that the wind directions over the western North Pacific (WNP, 10° –22.5°N, 125° –145°E) undergo two abrupt changes and three stable states from winter to summer. Here we name the phenomenon as twice wind onsets of monsoon. The first wind onset occurs near mid‐May at 15°N, and the second one happens with the wind direction shifting southwesterly in mid‐July and ends in late September. The variations of Outgoing Longwave Radiation (OLR) and rainfall in the northward 5° latitudes of the neighbouring region show similar abrupt features as those of the twice wind onsets. The western Pacific subtropical high (WPSH) retreats eastward in the second stable state (pentad 29 to 37), which differs from the first stable state (pentad 1 to 24). As the strong cross‐equator flows from the Southern Hemisphere reach the WNP, the eastward retreat of WPSH consequently triggers the first wind onset. Then the WPSH ridge suddenly jumps to 30°N and results in the second wind onset. Meanwhile, the propagation of the second wind onset is consistent with the migration of the WNP monsoon trough.Seven atmospheric general circulation models (AGCMs) of Atmospheric Model Intercomparison Project (AMIP) from Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are validated against the observations mentioned earlier. The results show that there are still notable shortcomings for the models to simulate the WNP summer monsoon, especially the twice onsets. There is no significant improvement for the simulation of multi‐models ensemble mean. Only MPI‐ECHAM5 captures partial characteristics of similar pattern. The poor simulation of the migration of the WPSH ridge and monsoon trough may be important factors for the shortcomings. Moreover, none of the models reproduces corresponding rainfall patterns over the WNP. Copyright © 2009 Royal Meteorological Society

Wind onset and withdrawal of Asian summer monsoon and their simulated performance in AMIP models

This study defines the concepts of wind onset and wind withdrawal to describe the abrupt seasonal variations of wind direction and circulation of the Asian monsoon. The patterns of wind onset and withdrawal show that the earliest wind onset in the tropical monsoon regions is found over equator around 70°–100°E and the southernmost South China Sea (SCS) and western Kalimantan, and the wind withdrawal shows a southward progression in tropics compared to the wind onset. A notable temporal boundary is found around 25°N in the subtropical western North Pacific (WNP), which may be related to the northward advance and southward retreat of the western Pacific subtropical high. The angle amplitudes of wind vectors in wind onset and withdrawal have distinct regional differences in Asian monsoon regions. Since the process of monsoon onset (withdrawal) may include several onsets of different variables without simultaneity, the relationships of the wind onset and withdrawal with the abrupt change of other variables (e.g. reversal of zonal wind, reversal of meridional wind, outgoing longwave radiation (OLR), precipitation) are investigated. The results indicate that the temporal discrepancies in different monsoon regions confirmed the asynchronous onsets. It also implies that the wind onset might be a good omen for monsoon precipitation in most regions since it is slightly earlier than rainy season onset. Seven Atmospheric Model Intercomparison Project (AMIP) models from Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are validated against observations mentioned above. Generally, the simulations of the multi-model ensemble mean are better than any individual model results. And the simulations of wind withdrawal are better than those of wind onset. For wind onset, IAP-FGOALS-1.0g, MIROC3.2 (medres) and MPI-ECHAM5 simulate reasonably well. For wind retreat, most models can capture the behaviors in tropics. However, there are still some discrepancies in a few models to simulate the dates of sudden change of monsoon wind direction. Moreover, most of models cannot reproduce the onset and withdrawal of both rainfall and OLR. The relationship between these discrepancies and the shortcomings of precipitation simulation is crucial for further investigating in the future.