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Linsey S. Passarella
and
Salil Mahajan

Abstract

We construct a novel multi-input multioutput autoencoder (MIMO-AE) to capture the nonlinear relationship of Southern California precipitation and tropical Pacific Ocean sea surface temperature. The MIMO-AE is trained on both monthly tropical Pacific sea surface temperature (TP-SST) and Southern California precipitation (SC-PRECIP) anomalies simultaneously. The covariability of the two fields in the MIMO-AE shared nonlinear latent space can be condensed into an index, termed the MIMO-AE index. We use a transfer learning approach to train a MIMO-AE on the combined dataset of 100 yr of output from a historical simulation with the Energy Exascale Earth Systems Model, version 1, and a segment of observational data. We further use long short-term memory networks to assess subseasonal predictability of SC-PRECIP using the MIMO-AE index. We find that the MIMO-AE index provides enhanced predictability of SC-PRECIP for a lead time of up to 4 months as compared with the Niño-3.4 index and the El Niño–Southern Oscillation longitudinal index.

Significance Statement

Traditional El Niño–Southern Oscillation indices, like the Niño-3.4 index, although well predicted themselves, fail to offer reliable subseasonal-to-seasonal predictions of western U.S. precipitation. Here, we use a machine learning approach called a multi-input, multioutput autoencoder to capture the relationship between tropical Pacific Ocean and Southern California precipitation and project it onto a new index, which we call the MIMO-AE index. Using machine learning–based time series predictions, we find that the MIMO-AE index offers enhanced predictability of Southern California precipitation up to a lead time of 4 months as compared with other ENSO indices.

Open access
Salil Mahajan
,
R. Saravanan
, and
Ping Chang

Abstract

The role of the wind–evaporation–sea surface temperature (WES) feedback in the low-frequency natural variability of the tropical Atlantic is studied using an atmospheric global climate model—the NCAR Community Climate Model, version 3 (CCM3)—thermodynamically coupled to a slab ocean model (SOM). The coupled model is modified to suppress the WES feedback and is compared to a control run. Singular value decomposition (SVD) analysis over the tropical Atlantic reveals that the coupled meridional mode of the Atlantic Ocean is amplified in the presence of the WES feedback. In its absence, the meridional mode still exists, but with a weaker amplitude. A feedback mechanism that involves the near-surface specific humidity is proposed to sustain the weaker Atlantic meridional mode in the absence of the WES feedback. Similar analysis of coupled model integrations when forced with an artificial El Niño–Southern Oscillation (ENSO)-like SST cycle in the Pacific reveals that in the presence of the WES feedback, the meridional mode is the preferred mode of response of the tropical Atlantic to ENSO forcing. In the absence of the WES feedback, the tropical Atlantic response is unlike the meridional mode and the effects of tropospheric warming and subsidence dominate. Regression analysis over the tropical Atlantic reveals that the meridional mode response to ENSO peaks in the spring and begins to decay in the fall in the coupled model in the presence of the WES feedback. The WES feedback also appears to be responsible for the northward migration of the ITCZ during ENSO events.

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Salil Mahajan
,
R. Saravanan
, and
Ping Chang

Abstract

The role of the wind–evaporation–sea surface temperature (WES) feedback in the propagation of the high-latitude cooling signal to the tropical oceans using the NCAR atmospheric Community Climate Model (CCM3) coupled thermodynamically to a slab-ocean model (SOM) is studied. Abruptly imposed additional Northern Hemispheric sea ice cover equivalent to the Last Glacial Maximum (LGM; 18 kyr BP) in the model causes a Northern Hemisphere–wide cooling, as well as the generation and amplification of an anomalous cross-equatorial meridional SST dipole associated with a southward migration of the intertropical convergence zone (ITCZ) stabilizing within a period of 5 yr. In experiments where the WES feedback is switched off explicitly by modifying the sensible and latent heat flux bulk aerodynamic formulations over the oceans in CCM3, imposed Northern Hemispheric sea ice also results in widespread northern cooling at the same rate as the unmodified run, suggesting that the WES feedback is not essential in the propagation of the high-latitude cooling signal to the deep tropics. However, the WES-off experiment generates a weaker cross-equatorial SST dipole with a modest southward movement of the ITCZ, suggesting that the WES feedback is responsible for amplifying SST and atmospheric anomalies in the deep tropics during their transition to the new equilibrium state. The propagation of high-latitude cooling to the deep tropics is proposed to be caused by the decrease of near-surface specific humidity in the northern tropics.

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Salil Mahajan
,
Rong Zhang
, and
Thomas L. Delworth

Abstract

The simulated impact of the Atlantic meridional overturning circulation (AMOC) on the low-frequency variability of the Arctic surface air temperature (SAT) and sea ice extent is studied with a 1000-year-long segment of a control simulation of the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1. The simulated AMOC variations in the control simulation are found to be significantly anticorrelated with the Arctic sea ice extent anomalies and significantly correlated with the Arctic SAT anomalies on decadal time scales in the Atlantic sector of the Arctic. The maximum anticorrelation with the Arctic sea ice extent and the maximum correlation with the Arctic SAT occur when the AMOC index leads by one year. An intensification of the AMOC is associated with a sea ice decline in the Labrador, Greenland, and Barents Seas in the control simulation, with the largest change occurring in winter. The recent declining trend in the satellite-observed sea ice extent also shows a similar pattern in the Atlantic sector of the Arctic in the winter, suggesting the possibility of a role of the AMOC in the recent Arctic sea ice decline in addition to anthropogenic greenhouse-gas-induced warming. However, in the summer, the simulated sea ice response to the AMOC in the Pacific sector of the Arctic is much weaker than the observed declining trend, indicating a stronger role for other climate forcings or variability in the recently observed summer sea ice decline in the Chukchi, Beaufort, East Siberian, and Laptev Seas.

Full access
Salil Mahajan
,
Qi Tang
,
Noel D. Keen
,
Jean-Christophe Golaz
, and
Luke P. van Roekel

Abstract

We evaluate the simulated teleconnection of El Niño–Southern Oscillation (ENSO) to winter season precipitation extremes over the United States in a long (98 years) 1950 control high-resolution version (HR; 25-km nominal atmosphere model horizontal resolution) of the U.S. Department of Energy’s (DOE) Energy Exascale Earth System Model version 1 (E3SMv1). The model bias and spatial pattern of ENSO teleconnections to mean and extreme precipitation in HR overall are similar to the low-resolution model’s (LR; 110 km) historical simulation (four-member ensemble, 1925–59). However, over the southeastern United States (SE-U.S.), HR produces stronger El Niño–associated extremes, reducing LR’s model bias. Both LR and HR produce weaker than observed increase in storm track activity during El Niño events there, but HR improves the ENSO-associated variability of moisture transport over SE-U.S. During El Niño, stronger vertical velocities in HR produce stronger large-scale precipitation, causing larger latent heating of the troposphere that pulls in more moisture from the Gulf of Mexico into the SE-U.S. This positive feedback also contributes to the stronger mean and extreme precipitation response in HR. Over the Pacific Northwest, LR’s bias of stronger than observed La Niña associated extremes is amplified in HR. Both models simulate stronger than observed moisture transport from the Pacific Ocean into the region during La Niña years. The amplified HR bias there is due to stronger orographically driven vertical updrafts that create stronger large-scale precipitation, despite weaker La Niña–induced storm track activity.

Significance Statement

New high-resolution Earth system models (ESMs) solve mathematical equations of fluid flow at much smaller spatial scales than prevalent ESMs, and thus are prohibitively expensive to compute. However, they can be useful for simulating accurate details of regional climate extremes that are driven by naturally occurring climate oscillations like El Niño–Southern Oscillation (ENSO). Here, we evaluate the simulation of ENSO-driven precipitation extremes over the United States in the high-resolution version of the U.S. Department of Energy’s new Energy Exascale Earth System Model version 1. We find that the high-resolution model improves upon its low-resolution counterpart over the southeastern United States by producing a better transport of moisture into the region from the Gulf of Mexico during El Niño. Over the U.S. Pacific Northwest, the high-resolution model simulates the atmospheric flow in more detail over the complex mountainous terrain. However, it also brings in more moisture from the Pacific Ocean just like the low-resolution model. This causes it to produce precipitation extremes during La Niña years there that are stronger than that observed in the real world.

Open access
Salil Mahajan
,
Katherine J. Evans
,
John E. Truesdale
,
James J. Hack
, and
Jean-François Lamarque

Abstract

A new high-resolution global tropospheric aerosol dataset with monthly resolution is generated using version 4 of the Community Atmosphere Model (CAM4) coupled to a bulk aerosol model and forced with recent estimates of surface emissions for the period 1961–2000 to identify tropospheric aerosol-induced interannual climate variations. The surface emissions dataset is constructed from phase 5 of the Coupled Model Intercomparison Project (CMIP5) decadal-resolution surface emissions dataset to include reanalysis of tropospheric chemical composition [40-yr Reanalysis of Tropospheric Chemical Composition (RETRO)] wildfire monthly emissions data. A four-member ensemble run is conducted using the spectral configuration of CAM4, forced with the new tropospheric aerosol dataset and prescribed with observed sea surface temperature, sea ice, and greenhouse gases. CAM4 only simulates the direct and semidirect effects of aerosols on the climate. The simulations reveal that variations in tropospheric aerosol levels can induce significant regional climate variability on the interannual time scales. Regression analyses over tropical Atlantic and Africa suggest that increasing dust aerosols can cool the North African landmass and shift convection southward from West Africa into the Gulf of Guinea in the spring season. Further, it is found that carbonaceous aerosols emanating from the southwestern African savannas can significantly cool the region and increase the marine stratocumulus cloud cover over the southeast tropical Atlantic Ocean by aerosol-induced diabatic heating of the free troposphere above the low clouds. Experiments conducted with CAM4 coupled to a slab ocean model suggest that present-day aerosols can cool the tropical North Atlantic and shift the intertropical convergence zone southward and can reduce the ocean mixed layer temperature beneath the increased marine stratocumulus clouds in the southeastern tropical Atlantic.

Full access
Salil Mahajan
,
Katherine J. Evans
,
James J. Hack
, and
John E. Truesdale

Abstract

The impacts of absorbing aerosols on global climate are not completely understood. This paper presents the results of idealized experiments conducted with the Community Atmosphere Model, version 4 (CAM4), coupled to a slab ocean model (CAM4–SOM) to simulate the climate response to increases in tropospheric black carbon aerosols (BC) by direct and semidirect effects. CAM4-SOM was forced with 0, 1×, 2×, 5×, and 10× an estimate of the present day concentration of BC while maintaining the estimated present day global spatial and vertical distribution. The top-of-atmosphere (TOA) radiative forcing of BC in these experiments is positive (warming) and increases linearly as the BC burden increases. The total semidirect effect for the 1 × BC experiment is positive but becomes increasingly negative for higher BC concentrations. The global-average surface temperature response is found to be a linear function of the TOA radiative forcing. The climate sensitivity to BC from these experiments is estimated to be 0.42 K W−1 m2 when the semidirect effects are accounted for and 0.22 K W−1 m2 with only the direct effects considered. Global-average precipitation decreases linearly as BC increases, with a precipitation sensitivity to atmospheric absorption of 0.4% W−1 m2. The hemispheric asymmetry of BC also causes an increase in southward cross-equatorial heat transport and a resulting northward shift of the intertropical convergence zone in the simulations at a rate of 4° PW−1. Global-average mid- and high-level clouds decrease, whereas the low-level clouds increase linearly with BC. The increase in marine stratocumulus cloud fraction over the southern tropical Atlantic is caused by increased BC-induced diabatic heating of the free troposphere.

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Judith Berner
,
Ulrich Achatz
,
Lauriane Batté
,
Lisa Bengtsson
,
Alvaro de la Cámara
,
Hannah M. Christensen
,
Matteo Colangeli
,
Danielle R. B. Coleman
,
Daan Crommelin
,
Stamen I. Dolaptchiev
,
Christian L. E. Franzke
,
Petra Friederichs
,
Peter Imkeller
,
Heikki Järvinen
,
Stephan Juricke
,
Vassili Kitsios
,
François Lott
,
Valerio Lucarini
,
Salil Mahajan
,
Timothy N. Palmer
,
Cécile Penland
,
Mirjana Sakradzija
,
Jin-Song von Storch
,
Antje Weisheimer
,
Michael Weniger
,
Paul D. Williams
, and
Jun-Ichi Yano

Abstract

The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined.

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