Geophysical Fluid Dynamics Laboratory Climate Research Articles

Optimal Precursors for Central Pacific El Niño Events in GFDL CM2p1

Abstract Compared to the canonical eastern Pacific El Niño, the understanding and ability to predict the central Pacific (CP)-type event still need further improvement. In this study, the principal component analysis–based particle swarm optimization algorithm (PPSO) is applied in Geophysical Fluid Dynamics Laboratory Climate Model version 2p1 (GFDL CM2p1) to obtain the optimal precursors (OPRs) for CP El Niño events, based on the conditional nonlinear optimal perturbation (CNOP) method. For this, three normal years with neither El Niño nor La Niña events, i.e., three cases, are chosen as the reference states. The obtained OPRs for these cases exhibit a consistent positive sea surface temperature (SST) perturbation distribution in the subtropical North Pacific (20°–40°N, 175°E–140°W), which is further proven to be crucial for the evolution of CP El Niño based on the Northern and Southern Hemisphere significance test results. Mechanically, these positive SST perturbations are enhanced and reach the equatorial Pacific via wind–evaporation–SST (WES) feedback to evolve into a CP El Niño at the end of the year. The nonlinear approach is adopted to investigate the predictability of CP El Niño events and can shed some light on future studies.

Yeşilırmak Havzasında İklim Değişim Senaryoları Altında Gelecekteki Sediment Verimi ve Sediment Tutma Kapasitesinin InVEST Model ile Değerlendirilmesi

Climate change is expected to cause more severe environmental problems, including soil erosion. This study aims to examine the effects of climate change on the sediment yield and sediment retention capacity through soil erosion in the Yeşilırmak Basin with the InVEST sediment delivery ratio model. RCP4.5 and RCP8.5 scenarios of the GFDL-CM3 (Geophysical Fluid Dynamics Laboratory Climate Model Version III) general circulation model were used to examine the effects of climate change on soil erosion. Decreases in the sediment yield and sediment retention rates of Yeşilırmak Basin were projected up to 9.48% and 12.47% in 2070, respectively. The main reason for the decrease in soil erosion rates is the decrease in rainfall erosivity resulting from the decrease in precipitation amounts, and the effect of this decrease is predicted to have a positive impact on wetland systems and agricultural lands. In addition, this research points to the advantages of the InVEST model approach in spatial and temporal estimation of the possible effects of future climate change on soil erosion.

The most sensitive initial error modes modulating intensities of CP- and EP- El Niño events

The two types of El Niño events simulated by the Geophysical Fluid Dynamics Laboratory Climate Model version 2p1 (GFDL CM2p1) model and its “spring predictability barrier” (SPB) associations are examined. By conducting the ensemble hindcast experiments related to the sea temperature on the whole Pacific, both of the predictions for CP- and EP-El Niño show a significant SPB phenomenon, but the CP-El Niño features a much weaker SPB compared to the EP-El Niño. Further analyses revealed that, for CP-El Niño events, the initial sea temperature errors of the North Pacific with triple-like shape, referred to as negative Victoria Mode (VM) induces the largest prediction errors in Niño4 areas and modulates the intensities of CP-El Niño events. While for EP-El Niño events, the initial sea temperature errors in the subsurface layer of the western equatorial Pacific and the upper layer of the Southeast Pacific (15–30ºS) with the meridional mode induce the largest prediction errors in Niño3 areas and modulates the intensities of EP-El Niño events. Obviously, results stress that, in order to reduce final prediction errors and obtain better predictions in terms of intensity on the two types of El Niño events, we should mainly focus on initial sea temperature accuracy in not only the subsurface layer of the west equatorial Pacific but also the surface layer of southeast Pacific and the region covered by the VM-like mode in the North Pacific.

Korea Institute of Ocean Science and Technology Earth System Model and Its Simulation Characteristics

We document the performance of a new earth system model developed at Korea Institute of Ocean Science and Technology, called the KIOST-ESM, based on a low-resolution (~ 200 km for the atmosphere, ~ 100 km for the ocean) version of the Geophysical Fluid Dynamics Laboratory Climate Model 2.5. The main changes made to the base model include adopting a unified convection scheme for cumulus convection and an ocean mixed layer parameterization considering Langmuir circulation, which improve the model fidelity significantly. In addition, the KIOST-ESM adopts a new soil respiration scheme in the dynamic vegetation process of its land component. The performance of the KIOST-ESM was assessed in pre-industrial and historical simulations that are made as part of its participation in the Coupled Model Intercomparison Project phase 6 (CMIP6). The response of the earth system to increasing greenhouse gas concentrations was analyzed in the ScenarioMIP simulations. An abrupt quadrupling of CO2 experiment suggests that the equilibrium climate sensitivity of KIOST-ESM is 3.36 K—very close to the averaged one obtained from CMIP5 simulations. Although the KIOST-ESM showed a notable cold bias in the Northern Hemisphere and the double Inter-Tropical Convergence Zone bias, the KIOST-ESM outperforms the base model in simulating the mean sea surface temperature over the Southern Ocean and over the cold tongue in the tropical Pacific. The KIOST-ESM can also simulate the dominant tropical variability in intraseasonal (Madden–Julian Oscillation) and interannual (El Nino-Southern Oscillation) timescales more realistically.

Exploring Inland Tropical Cyclone Rainfall and Tornadoes under Future Climate Conditions through a Case Study of Hurricane Ivan

AbstractThe overarching purpose of this study is to investigate the impacts of anthropogenic climate change both on the rainfall and tornadoes associated with tropical cyclones (TCs) making landfall in the U.S. Atlantic basin. The “pseudo–global warming” (PGW) approach is applied to Hurricane Ivan (2004), a historically prolific tropical cyclone tornado (TCT)-producing storm. Hurricane Ivan is simulated under its current climate forcings using the Weather Research and Forecasting Model. This control simulation (CTRL) is then compared with PGW simulations in which the current forcings are modified by climate-change differences obtained from the Community Climate System Model, version 4 (NCAR); Model for Interdisciplinary Research on Climate, version 5 (MIROC); and Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL). Changes in TC intensity, TC rainfall, and TCT production, identified for the PGW-modified Ivan, are documented and analyzed. Relative to CTRL, all three PGW simulations show an increase in TC intensity and generate substantially more accumulated rainfall over the course of Ivan’s progression over land. However, only one of the TCs under PGW (MIROC) produced more TCTs than CTRL. Evidence is provided that, in addition to favorable environmental conditions, TCT production is related to the TC track length and to the strength of the interaction between the TC and an environmental midlevel trough. Enhanced TCT generation at landfall for MIROC and GFDL is attributed to increased values of convective available potential energy, low-level shear, and storm-relative environmental helicity.

Dynamical Downscaling for Southeast Alaska: Historical Climate and Future Projections

AbstractWarming temperatures across southeast Alaska are affecting the region’s energy and transportation sectors, marine ecosystems, and forest health. More frequent above-freezing temperatures lead a transition from snow- to rain-dominant precipitation regimes, accelerating glacial mass balance loss and a leading to a greater risk for warm-season drought. Southeast Alaska has steep topographical gradients, which necessitate the use of downscaled climate information to study historical and projected periods. This study used regional dynamical downscaling at 4-km spatial resolution with the Weather Research and Forecasting Model to assess historical (1981–2010) and projected (2031–60) climate states for southeast Alaska. These simulations were driven by one reanalysis (i.e., the Climate Forecast System Reanalysis) and two climate models (i.e., the Geophysical Fluid Dynamics Laboratory Climate Model, version 3, and the NCAR Community Climate System Model, version 4), which each included a historical simulation and a projected simulation. The future simulations used the representative concentration pathway 8.5 emissions scenario. Bias-corrected projections (2031–60 minus 1981–2010) indicated seasonal warming of 1°–3°C, increased precipitation during autumn (4%–12%) and winter (7%–12%), and decreased snowfall in all seasons (up to 60% in autumn). The average number of days annually with a minimum temperature below freezing dropped by more than 30. The average annual maximum consecutive 3-day precipitation amounts increased by 11%–16%, but analogous extreme snowfall amounts dropped by 5%–11%. The most substantial snow losses occurred at low-elevation and coastal locations; at many high elevations (e.g., above 1000 m), extreme snowfall amounts increased.

The Optimal Precursor of El Niño in the GFDL CM2p1 Model

AbstractBy applying the principal component analysis‐based particle swarm optimization algorithm, the conditional nonlinear optimal perturbation is firstly calculated in the Geophysical Fluid Dynamics Laboratory Climate Model version 2p1 (GFDL CM2p1) to identify the optimal precursor (OPR) of El Niño. Specifically, through optimizing the initial perturbation, the OPRs that have the largest nonlinear evolution (i.e., mature state of El Niño) for two reference states are obtained, which are then confirmed according to the validation test. The results indicate that both OPRs show positive sea surface temperature perturbation in the west (2°N–2°S, 135.5–165.5°E). For the subsurface component, they exhibit positive subsurface temperature perturbation (STP) in the whole mixed layer of the west and negative STP in the upper layer of the east (i.e., 0‐ to 85‐m depth, 2°N–2°S, 79.5–109.5°W). Further analyses of the evolution of the sea surface temperature perturbation, STP, and surface wind perturbation suggest that the development of the OPRs in the model is consistent with the recognized mechanism for El Niño‐Southern Oscillation development, that is, through the Bjerknes positive feedback. The results indicate that the model can realistically capture the dominant processes for El Niño development, and the principal component analysis‐based particle swarm optimization algorithm is a practical solution for calculating the conditional nonlinear optimal perturbation in a complicated numerical model such as the GFDL CM2p1. They both shed a light on guiding the realistic observing systems.

Assessment of the JMA Serial Observation Lines in the Northwestern Pacific in OSSE Studies with the GFDL Ensemble Coupled Data Assimilation System

AbstractTwo major serial observational positions (137°E and 165°E, operated by the Japan Meteorological Agency [JMA] in the Northwestern Pacific) were assessed using observation system simulation experiments (OSSEs) with the Geophysical Fluid Dynamics Laboratory (GFDL) ensemble coupled data assimilation system. In the OSSEs, the “True Ocean” is a simulation time series of the fully coupled GFDL climate model (CM2.1), and the “control ocean” is defined as the same CM2.1 simulation result using different initial conditions and ensemble members. The sea surface temperature, subsurface temperature, and salinity data that were drawn from the “truth” were assimilated into the “control.” The degree by which the assimilation recovers the “truth” is an assessment of the representation of the serial observation lines for regional circulations and their variability in the Northwestern Pacific. Results show that the assimilation effect of sea surface temperature is maintained to the deeper ocean by adjusting the interannual variability of the ocean temperature in the Northwestern Pacific. The root mean square error in the western area of each observational system was much lower than that in the eastern area. This is closely related to the anomalous geostrophic clockwise flow pattern strengthened throughout the assimilation process of the JMA data. We confirmed this result using a reverse bias experiment. Therefore, the assimilation effect of 165°E appearing larger western areas is also stronger than 137°E. However, the assimilation performances of the two observation systems were not significantly different in the long‐term simulations of more than 25 years in the Northwestern Pacific.

Anticipated changes to the snow season in Alaska: Elevation dependency, timing and extremes

AbstractSnowfall and snow season length across Alaska control the surface hydrology and underlying soil properties and also influence near‐surface air temperature by changing the energy balance. Current projections of warming suggest that considerable change will occur to key snow parameters, possibly contributing to extensive infrastructure damage from thawing permafrost, an increased frequency of rain‐on‐snow events and reduced soil recharge in the spring due to shallow end‐of‐winter snowpack. This study investigates projected changes to mean annual snowfall, dates of snow onset and snowmelt and extreme snowfall for Alaska, using dynamically downscaled reanalysis and climate model simulations. These include the ERA‐Interim reanalysis from 1981 to 2010, and two Coupled Model Intercomparison Project Phase 5 models: Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL‐CM3) from 1981 to 2100. The analysis is presented in 30‐year periods (i.e., 1981–2010, 2011–2040, 2041–2070 and 2071–2100) with the future scenarios from Representative Concentration Pathway 8.5. Late‐century projections of average annual snowfall at low elevations (0–1,000 m) show decreases of 41.3 and 40.6% for CCSM4 and GFDL‐CM3, respectively. At high elevations (1,000–2,000 m), the reductions are smaller at 13.5 and 14.2%, respectively. End‐of‐winter snow‐water equivalent displays reductions at all elevations in the future periods. Snow season length is shortened due to later snow onset and earlier snowmelt; many locations in southwest Alaska no longer experience continuous winter snowpack by the late‐century period. Maximum 2‐day snowfall amounts are projected to decrease near Anchorage and Nome, while Fairbanks and Utqiaġvik (Barrow) show no significant trend.

Indian Ocean Dipole-related Predictability Barriers Induced by Initial Errors in the Tropical Indian Ocean in a CGCM

Using GFDL CM2p1 (Geophysical Fluid Dynamics Laboratory Climate Model, version 2p1), the effects of initial sea temperature errors on the predictability of the Indian Ocean Dipole (IOD) are explored. When initial temperature errors are superimposed on the tropical Indian Ocean, a winter predictability barrier (WPB) and a summer predictability barrier (SPB) exist in IOD predictions. The existence of the WPB has a close relation with El Ni?o-Southern Oscillation (ENSO) in the winter of the growing phase of positive IOD events. That is, when ENSO exists in winter, no WPB appears in IOD predictions, and vice versa. In contrast, there is no inherent connection between the existence of the SPB and ENSO. Only the dominant spatial pattern of SPB-related initial errors is studied in this paper, which presents a significant west-east dipole pattern in the tropical Indian Ocean and is similar to that of WPB-related initial errors in previous studies. The SPB-related initial errors superimposed on the tropical Indian Ocean induce the sea surface temperature (SST) and wind anomalies in the tropical Pacific Ocean. Then, under the interaction between the Indian and Pacific oceans through the atmospheric bridge and Indonesian Throughflow, a west-east dipole pattern of SST errors appears in summer, which is further strengthened under the Bjerknes feedback and yields a significant SPB.

Simulated Dust Aerosol Impacts on Western Sahelian Rainfall: Importance of Ocean Coupling

AbstractNorth Africa is the world’s largest source of mineral dust, and this dust has potentially significant impacts on precipitation. Yet there is no consensus in published studies regarding the sign or magnitude of dust impacts on rainfall in either the highly climate-sensitive Sahel region of North Africa or the neighboring tropical Atlantic Ocean. Here the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model 2 (GFDL CM2.0) with Modular Ocean Model, version 4.1 (MOM4.1), run at coarse resolution (CM2Mc) is applied to investigate one poorly characterized aspect of dust–precipitation dynamics: the importance of sea surface temperature (SST) changes in mediating the atmospheric response to dust. Two model experiments were performed: one comparing Dust-On to Dust-Off simulations in the absence of ocean–atmosphere coupling, and the second comparing Dust-On to Dust-Off with the ocean fully coupled. Results indicate that SST changes in the coupled experiment reduce the magnitude of dust impacts on Sahel rainfall and flip the sign of the precipitation response over the nearby ocean. Over the Sahel, CM2Mc simulates a net positive impact of dust on monsoon season rainfall, but ocean–atmosphere coupling in the presence of dust decreases the inflow of water vapor, reducing the amount by which dust enhances rainfall. Over the tropical Atlantic Ocean, dust leads to SST cooling in the coupled experiment, resulting in increased static stability that overrides the warming-induced increase in convection observed in the uncoupled experiment and yields a net negative impact of dust on precipitation. These model results highlight the potential importance of SST changes in dust–precipitation dynamics in North Africa and neighboring regions.

Roles of the Ocean Mesoscale in the Horizontal Supply of Mass, Heat, Carbon, and Nutrients to the Northern Hemisphere Subtropical Gyres

AbstractHorizontal transport at the boundaries of the subtropical gyres plays a crucial role in providing the nutrients that fuel gyre primary productivity, the heat that helps restratify the surface mixed layer, and the dissolved inorganic carbon that influences air‐sea carbon exchange. Mesoscale eddies may be an important component of these horizontal transports; however, previous studies have not quantified the horizontal tracer transport due to eddies across the subtropical gyre boundaries. Here we assess the physical mechanisms that control the horizontal transport of mass, heat, nutrients, and carbon across the North Pacific and North Atlantic subtropical gyre boundaries using the eddy‐rich ocean component of a climate model (Geophysical Fluid Dynamics Laboratory Climate Model version 2.6) coupled to a simple biogeochemical model (mini‐BLING). Our results suggest that horizontal transport across the gyre boundaries supplies a substantial amount of mass and tracers to the ventilated layer of both Northern Hemisphere subtropical gyres, with the Kuroshio and Gulf Stream acting as main exchange gateways. Mass, heat, and dissolved inorganic carbon supply is principally driven by the time‐mean circulation, whereas nutrient transport differs markedly from the other tracers, as nutrients are mainly supplied to both subtropical gyres by downgradient eddy mixing across gyre boundaries. A budget analysis further reveals that the horizontal nutrient transport, combining the roles of both mean and eddy components, is responsible for more than three quarters of the total nutrient supply into the subtropical gyres, surpassing a recent estimate based on a coarse‐resolution model and thus further highlighting the importance of horizontal nutrient transport.

Agro-Climate Projections for a Warming Alaska

Abstract Climate warming is expected to disproportionately affect crop yields in the southern United States due to excessive heat stress, while presenting new farming opportunities through a longer growing season farther north. Few studies have investigated the impact of this warming on agro-climate indices that link meteorological data with important field dates in northern regions. This study employs regional dynamical downscaling using the Weather Research and Forecasting (WRF) Model to assess changes in growing season length (GSL), spring planting dates, and occurrences of plant heat stress (PHS) for five regions in Alaska. Differences between future representative concentration pathway 8.5 (RCP8.5; 2011–40, 2041–70, 2071–2100) and historical (1981–2010) periods are obtained using boundary forcing from the Geophysical Fluid Dynamics Laboratory Climate Model, version 3, and the NCAR Community Climate System Model, version 4. The model output is bias corrected using ERA-Interim. Median GSL shows increases of 48–87 days by 2071–2100, with the largest changes in northern Alaska. Similarly, by 2071–2100, planting dates advance 2–4 weeks, and PHS days increase from near 0 to 5–10 instances per summer in the hottest areas. The largest GSL changes occur in the mid- (2041–70) and late century (2071–2100), when a warming signal emerges from the historical interannual variability. These periods coincide with the greatest divergence of the RCPs, suggesting that near-term decision-making may affect substantial future changes. Early-century (2011–40) projections show median GSL increases of 8–27 days, which is close to the historical standard deviation of GSL. Thus, internal variability will remain an important source of uncertainty into the midcentury, despite a trend for longer growing seasons.

The Climatological Effect of Saharan Dust on Global Tropical Cyclones in a Fully Coupled GCM

AbstractClimate in the tropical North Atlantic and West Africa is known to be sensitive to both the atmospheric burden and optical properties of aerosolized mineral dust. We investigate the global climatic response to an idealized perturbation in atmospheric burden of Saharan‐born mineral dust, comparable to the observed changes between the 1960s and 1980s, using simulations with the high‐resolution, fully coupled Geophysical Fluid Dynamics Laboratory Climate Model 2.5, Forecast‐oriented Low Ocean Resolution version, across a range of realistic optical properties, with a specific focus on tropical cyclones. The direct radiative responses at the top of the atmosphere and at the surface along with regional hydrologic and thermodynamic responses are in agreement with previous studies, depending largely on the amount of aerosol absorption versus scattering. In all simulations, dust causes a decrease in tropical cyclone activity across the North Atlantic Ocean, as determined by a tropical cyclone tracking scheme, with the largest response occurring in the most absorbing and scattering optical regimes. These changes are partially corroborated by common local genesis potential indices. However, no clear‐cut explanation can be developed upon inspection of their constituent variables. There are also nonnegligible anomalies in the North Pacific and Indian Oceans in these simulations. A relationship between accumulated cyclone energy and top of the atmosphere radiative flux anomalies is used to explain the North Atlantic anomalies, while analogy to known climate variations can help us understand the far‐field response to the dust forcing.

Response of the Tropical Indian Ocean to Greenhouse Gases and Aerosol Forcing in the GFDL CM3 Coupled Climate Model

ABSTRACTThe response of the tropical Indian Ocean (TIO) to greenhouse gases (GHGs) and aerosols are investigated based on historical single-forcing and all-forcing simulations using the Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3). Results reveal a positive Indian Ocean Dipole (pIOD)-like pattern in GHG forcing but a negative Indian Ocean Dipole (nIOD)-like pattern in aerosol forcing. The GHG-induced pIOD-like pattern features less (more) sea surface temperature (SST) warming over the southeastern (western) TIO, accompanied by equatorial easterly anomalies, as well as a shallower thermocline off Sumatra. The aerosol-induced nIOD-like pattern displays the reverse features, characterized by less (more) SST cooling over the southeastern (western) TIO, anomalous equatorial westerlies, and a deeper thermocline off Sumatra. Although the aerosol-induced pattern appears to resemble a reversal of the GHG-induced pattern, there is a strong asymmetry in the SST changes over the southeastern TIO, where the cooling responding to aerosol forcing exceeds the warming in response to GHG forcing, and a negative SST residual is thus produced. A mixed-layer heat budget analysis suggests that the negative SST residual results mainly from asymmetric responses of shortwave radiation, zonal advection, and diffusion to GHGs and aerosols. For comparison, the formation processes for the negative SST skewness over the southeastern TIO between the internal pIOD and nIOD are also discussed.

The Impact of Climate Change on Hazardous Convective Weather in the United States: Insight from High-Resolution Dynamical Downscaling

This study explores the potential impact anthropogenic climate change may have upon hazardous convective weather (HCW; i.e., tornadoes, large hail, and damaging wind gusts) in the United States. Utilizing the Weather Research and Forecasting (WRF) Model, high-resolution (4 km) dynamically downscaled simulations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), are produced for a historical (1971–2000) and future (2071–2100) period. Synthetic HCW day climatologies are created using upward vertical velocity (UVV) exceeding 22 m s−1 as a proxy for HCW occurrence and subsequently compared to the environmental approach of estimating changes in daily frequency of convective environments favorable for HCW (NDSEV) from the driving climate model. Results from the WRF simulations demonstrate that the proxy for HCW becomes more frequent by the end of the twenty-first century, with the greatest absolute increases in daily frequency occurring during the spring and summer. Compared to NDSEV from GFDL CM3, both approaches suggest a longer HCW season, perhaps lengthening by more than a month. The change in environmental estimates are 2–4 times larger than that gauged from WRF; further analyses show that the conditional probability of HCW given NDSEV declines during summer for much of the central United States, a result that may be attributed to both an increase in the magnitude of convective inhibition (CIN) and decreased forcing for ascent, hindering convective initiation. Such an outcome supports the motivation for continued use of dynamical downscaling to overcome the limitations of the GCM-based environmental analysis.

Projections of Twenty-First-Century Climate Extremes for Alaska via Dynamical Downscaling and Quantile Mapping

AbstractClimate change is expected to alter the frequencies and intensities of at least some types of extreme events. Although Alaska is already experiencing an amplified response to climate change, studies of extreme event occurrences have lagged those for other regions. Forced migration due to coastal erosion, failing infrastructure on thawing permafrost, more severe wildfire seasons, altered ocean chemistry, and an ever-shrinking season for snow and ice are among the most devastating effects, many of which are related to extreme climate events. This study uses regional dynamical downscaling with the Weather Research and Forecasting (WRF) Model to investigate projected twenty-first-century changes of daily maximum temperature, minimum temperature, and precipitation over Alaska. The forcing data used for the downscaling simulations include the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; 1981–2010), Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), historical (1976–2005), and GFDL CM3 representative concentration pathway 8.5 (RCP8.5; 2006–2100). Observed trends of temperature and sea ice coverage in the Arctic are large, and the present trajectory of global emissions makes a continuation of these trends plausible. The future scenario is bias adjusted using a quantile-mapping procedure. Results indicate an asymmetric warming of climate extremes; namely, cold extremes rise fastest, and the greatest changes occur in winter. Maximum 1- and 5-day precipitation amounts are projected to increase by 53% and 50%, which is larger than the corresponding increases for the contiguous United States. When compared with the historical period, the shifts in temperature and precipitation indicate unprecedented heat and rainfall across Alaska during this century.

Causes of Enhanced SST Variability over the Equatorial Atlantic and Its Relationship to the Atlantic Zonal Mode in CMIP5

A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model, version 2.1. The SBEV is especially pronounced in boreal spring owing to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. The SBEV is a common bias in phase 5 of the Coupled Model Intercomparison Project (CMIP5), found in 14 out of 23 models. The SBEV in CMIP5 is associated with the atmospheric thermal forcing and the oceanic vertical upwelling, similar to GFDL CM2.1. While the tropical North Atlantic variability is only weakly correlated with the Atlantic zonal mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its prediction

Using the Geophysical Fluid Dynamics Laboratory Climate Model version 2p1, we explored the precursory disturbances that are most likely to develop into a positive Indian Ocean Dipole (IOD). The dominant spatial patterns of these precursors are defined as the optimal precursors (OPRs) of positive IOD as they are more inclined to cause a positive IOD than other superimposed initial perturbations in the experiments. Specifically, there are two types of OPRs with opposite patterns; the surface component of OPR-1 (OPR-2) is an indistinctive west–east dipole pattern, with a small area of negative (positive) perturbations to the coast of Sumatra and Java. Correspondingly, there is a significant west–east dipole pattern in the subsurface component of the OPRs, with the largest values located in the eastern equatorial Indian Ocean. The dominant mode of the time-dependent evolutions of the precursors features rapid development of positive IOD. Furthermore, the OPRs are similar to the optimally growing initial errors (OGEs) associated with IOD predictions that have been presented in previous studies. The shortwave radiation, latent heat flux and westward Rossby waves play an important role in the time-dependent evolution of OGEs. Moreover, the large values of the OPRs are located in the same areas as the sensitive areas of targeted observations identified by the OGEs. This infers that intensive observations over these areas would not only reduce initial errors, improve the accuracy of initial fields and decrease the prediction errors, but would also detect the precursory signals in advance, which substantially improves the forecast skill of IOD. This article is protected by copyright. All rights reserved.

Multidecadal wind‐driven shifts in northwest Pacific temperature, salinity, O2, and PO4

AbstractThe North Pacific gyre boundaries are characterized by stark contrasts in physical and biogeochemical properties. Meridional movement of gyre boundaries, influenced by climate change, can therefore exert a large influence not only on marine ecosystems but also on climate. We examine the evidence for wind‐driven southward shifts in subsurface temperature, salinity, PO4, and O2 within the northwest Pacific from the 1950s to the 2000s. Gyre boundary shifts can explain 30–60% of temperature and salinity trends zonally averaged in the northwest Pacific and observed PO4 and O2 trends along the 137°E and 144°E meridians. The close tie between the wind‐driven shifts in gyre boundaries and the tracer distributions is further supported by results from an eddy‐resolving (0.1° × 0.1°) Geophysical Fluid Dynamics Laboratory climate model, suggesting that the physical and biogeochemical properties averaged within the northwest Pacific gyre boundaries closely follow the latitude changes of the zero Sverdrup stream function with lags of 0 to 3 years. The gyre shift effect on tracer distribution is poorly represented in a coarse resolution (1° × 1°) model due partly to poor representations of fronts and eddies. This study suggests that future changes in northwest Pacific PO4 and O2 content may depend not only on ocean temperature and stratification but also on the ocean gyre response to winds.