Barcikowska, Monika, Sarah B Kapnick, and Lakshmi Krishnamurthy, et al., February 2020: Changes in the future summer Mediterranean climate: contribution of teleconnections and local factors. Earth System Dynamics, 11(1), DOI:10.5194/esd-11-161-2020. Abstract
This study analyzes future climate for the Mediterranean region projected with the high-resolution coupled CM2.5 model, which incorporates a new and improved land model (LM3). The simulated climate changes suggest pronounced warming and drying over most of the region. However, the changes are distinctly smaller than those of the CMIP5 multi-model ensemble. In addition, the changes over much of southeast and central Europe indicate very modest warming compared to the CMIP5 projections and also a tendency toward wetter conditions. These differences indicate a possible role of factors such as land surface–atmospheric interactions in these regions. Our analysis also highlights the importance of correctly projecting the magnitude of changes in the summer North Atlantic Oscillation, which has the capacity to partly offset anthropogenic warming and drying over the western and central Mediterranean. Nevertheless, the projections suggest a decreasing influence of local atmospheric dynamics and teleconnections in maintaining the regional temperature and precipitation balance, in particular over arid regions like the eastern and southern Mediterranean, which show a local maximum of warming and drying. The intensification of the heat low in these regions rather suggests an increasing influence of warming land surface on the local surface atmospheric circulation and progressing desertification.
Positive precipitation biases over western North America have remained a pervasive problem in the current generation of coupled global climate models. These biases are substantially reduced, however, in a version of the Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution (FLOR) coupled climate model with systematic sea surface temperature (SST) biases artificially corrected through flux adjustment. This study examines how the SST biases in the Atlantic and Pacific Oceans contribute to the North American precipitation biases. Experiments with the FLOR model in which SST biases are removed in the Atlantic and Pacific are carried out to determine the contribution of SST errors in each basin to precipitation statistics over North America. Tropical and North Pacific SST biases have a strong impact on northern North American precipitation, while tropical Atlantic SST biases have a dominant impact on precipitation biases in southern North America, including the western United States. Most notably, negative SST biases in the tropical Atlantic in boreal winter induce an anomalously strong Aleutian low and a southward bias in the North Pacific storm track. In boreal summer, the negative SST biases induce a strengthened North Atlantic Subtropical High and Great Plains low-level jet. Each of these impacts contributes to positive annual mean precipitation biases over western North America. Both North Pacific and North Atlantic SST biases induce SST biases in remote basins through dynamical pathways, so a complete attribution of the effects of SST biases on precipitation must account for both the local and remote impacts.
The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July–August–September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications for highly vulnerable nations in the region.
Unprecedented high intensity flooding induced by extreme precipitation was reported over Chennai in India during November-December of 2015, which led to extensive damage to human life and property. It is of utmost importance to determine the odds of occurrence of such extreme floods in future and the related climate phenomena, for planning and mitigation purposes. Here, we make use of a suite of simulations from GFDL high-resolution coupled climate models to investigate the odds of occurrence of extreme floods induced by extreme precipitation over Chennai and the role of radiative forcing and/or large-scale SST forcing in enhancing the probability of such events in future. Climate of 20th century experiments with large ensembles suggest that the radiative forcing may not enhance the probability of extreme floods over Chennai. Doubling of CO2 experiments also fail to show evidence for increase of such events in a global warming scenario. Further, this study explores the role of SST forcing from the Indian and Pacific Oceans on the odds of occurrence of Chennai-like floods. Neither an El Niño nor La Niña enhances the probability of extreme floods over Chennai. However, warm Bay of Bengal tends to increase the odds of occurrence of extreme Chennai-like floods. The atmospheric condition such as a tropical depression over Bay of Bengal favoring the transport of moisture from warm Bay of Bengal is conducive for intense precipitation.
Krishnamurthy, Lakshmi, and V Krishnamurthy, March 2017: Indian monsoon's relation with the decadal part of PDO in observations and NCAR CCSM4. International Journal of Climatology, 37(4), DOI:10.1002/joc.4815. Abstract
This study has investigated the influence of the decadal component of the Pacific Decadal Oscillation (PDO) on the Indian monsoon in observations and coupled climate model. A major part of the conventionally defined PDO is shown to be dominated by interannual variability. By extracting the pure decadal part of the North Pacific variability, this study has shown that the Indian monsoon rainfall exhibits different relations with the conventionally defined PDO and the pure decadal component of the PDO. This result may have implications for decadal prediction of the monsoon. The analysis suggests that the warm (cold) phase of pure decadal variability of PDO is associated with deficit (excess) rainfall over the west central part of India. In contrast, the conventional warm (cold) PDO index is associated with deficit (excess) rainfall over most of India. The warm phase of the pure decadal PDO opposes the moisture flow beyond 20°N over the Indian monsoon region via the meridional winds extending from the North Pacific and leads to reduced rainfall over west central India. The Community Climate System Model version 4 of the National Center for Atmospheric Research shows reasonable simulation of the decadal PDO mode in both the North Pacific sea surface temperature and the Indian monsoon rainfall and the relation between them. Further, the observed and simulated PDO–monsoon relation is substantiated through a regionally de-coupled experiment. The coupled model experiment also provides supporting evidence for the mechanism involving the intermediary role played by the tropical Pacific Ocean in the PDO–monsoon relation.
Krishnamurthy, Lakshmi, and V Krishnamurthy, January 2016: Decadal and interannual variability of the Indian Ocean SST. Climate Dynamics, 46(1), DOI:10.1007/s00382-015-2568-3. Abstract
The variability of the Indian Ocean on interannual and decadal timescales is investigated in observations, coupled model simulation and model experiment. The Indian Ocean Dipole (IOD) mode was specifically analyzed using a data-adaptive method. This study reveals one decadal mode and two interannual modes in the sea surface temperature (SST) of the IOD. The decadal mode in the IOD is associated with the Pacific Decadal Oscillation (PDO) of the North Pacific SST. The two interannual modes are related to the biennial and canonical components of El Niño-Southern Oscillation (ENSO), consistent with previous studies. This study hypothesizes that the relation between the Indian Ocean and the North Pacific on decadal scale may be through the northerly winds from the western North Pacific. The long simulation of Community Climate System Model version 4 also indicates the presence of IOD modes associated with the decadal PDO and canonical ENSO modes. However, the model fails to simulate the biennial ENSO mode in the Indian Ocean. The relation between the Indian Ocean and North Pacific Ocean is further supported by the regionally de-coupled model experiment.
Krishnamurthy, Lakshmi, and V Krishnamurthy, April 2016: Teleconnections of Indian monsoon rainfall with AMO and Atlantic tripole. Climate Dynamics, 46(7-8), DOI:10.1007/s00382-015-2701-3. Abstract
The teleconnections between the decadal modes in the Indian monsoon rainfall (IMR) and the North Atlantic sea surface temperature are investigated. The two decadal modes of variability in the North Atlantic, the Atlantic multidecadal oscillation (AMO) and the Atlantic tripole, have opposite relation with the two decadal modes of IMR. The AMO has positive correlation with the monsoon rainfall while the Atlantic tripole has negative correlation. This study has put forward hypotheses for the mechanisms involved in the teleconnections of the AMO and the Atlantic tripole with the IMR. The warm phase of AMO may influence the monsoon through the summer North Atlantic Oscillation (SNAO) and further through the equatorial zonal winds which increase the moisture flow over India by enhancing the southwesterly flow. The warm phase of Atlantic tripole may impact the monsoon through the all-season NAO, leading to decreased moisture flow over India through the equatorial wind pattern. The observed relations between the decadal modes in the North Atlantic and the Indian monsoon are explored in the simulations of National Center for Atmospheric Research Community Climate System Model version 4 (CCSM4) model. Although the model supports the observed decadal teleconnection between the Atlantic Ocean and Indian monsoon, it has limitations in capturing the details of the spatial pattern associated with the teleconnection. The teleconnections of AMO and Atlantic tripole with the Indian monsoon is further demonstrated through an experiment with CCSM4 by decoupling the North Atlantic Ocean. The hypotheses for the mechanisms of the Atlantic teleconnections are also explored in the CCSM4 simulation.
Tropical cyclone (TC) activity in the North Pacific and North Atlantic Oceans is known to be affected by the El Niño Southern Oscillation (ENSO). This study uses GFDL FLOR model, which has relatively high-resolution in the atmosphere, as a tool to investigate the sensitivity of TC activity to the strength of ENSO events. We show that TCs exhibit a non-linear response to the strength of ENSO in the tropical eastern North Pacific (ENP) but a quasi-linear response in the tropical western North Pacific (WNP) and tropical North Atlantic. Specifically, stronger El Niño results in disproportionate inhibition of TCs in the ENP and North Atlantic, and leads to an eastward shift in the location of TCs in the southeast of the WNP. However, the character of the response of TCs in the Pacific is insensitive to the amplitude of La Niña events. The eastward shift of TCs in the southeast of the WNP in response to a strong El Niño is due to an eastward shift of the convection and of the associated environmental conditions favorable for TCs. The inhibition of TC activity in the ENP and Atlantic during El Niño is attributed to the increase in the number of days with strong vertical wind shear during stronger El Niño events. These results are further substantiated with coupled model experiments. Understanding of the impact of strong ENSO on TC activity is important for present and future climate as the frequency of occurrence of extreme ENSO events is projected to increase in future.
This study demonstrates skillful seasonal prediction of 2m air temperature and precipitation over land in a new high-resolution climate model developed by Geophysical Fluid Dynamics Laboratory, and explores the possible sources of the skill. We employ a statistical optimization approach to identify the most predictable components of seasonal mean temperature and precipitation over land, and demonstrate the predictive skill of these components. First, we show improved skill of the high-resolution model over the previous lower-resolution model in seasonal prediction of NINO3.4 index and other aspects of interest. Then we measure the skill of temperature and precipitation in the high-resolution model for boreal winter and summer, and diagnose the sources of the skill. Lastly, we reconstruct predictions using a few most predictable components to yield more skillful predictions than the raw model predictions. Over three decades of hindcasts, we find that the two most predictable components of temperature are characterized by a component that is likely due to changes in external radiative forcing in boreal winter and summer, and an ENSO-related pattern in boreal winter. The most predictable components of precipitation in both seasons are very likely ENSO-related. These components of temperature and precipitation can be predicted with significant correlation skill at least 9 months in advance. The reconstructed predictions using only the first few predictable components from the model show considerably better skill relative to observations than raw model predictions. This study shows that the use of refined statistical analysis and a high-resolution dynamical model leads to significant skill in seasonal predictions of 2m air temperature and precipitation over land.
This study investigates the seasonality of the relationship between the Great Plains low-level jet (GPLLJ) and the Pacific Ocean from spring to summer, using observational analysis and coupled model experiments. The observed GPLLJ and El Niño-Southern Oscillation (ENSO) relation undergoes seasonal changes with a stronger GPLLJ associated with La Niña in boreal spring and El Niño in boreal summer. The ability of the GFDL FLOR global coupled climate model, which has the high-resolution atmospheric and land components, to simulate the observed seasonality in the GPLLJ-ENSO relationship is assessed. The importance of simulating the magnitude and phase-locking of ENSO accurately in order to better simulate its seasonal teleconnections with the Intra-Americas Seas (IAS) is demonstrated. This study explores the mechanisms for seasonal changes in the GPLLJ-ENSO relation in model and observations. It is hypothesized that ENSO affects the GPLLJ variability through the Caribbean low-level jet (CLLJ) during the summer and spring seasons. These results suggest that climate models with improved ENSO variability would advance our ability to simulate and predict seasonal variations of the GPLLJ and their associated impacts on the United States.
Krishnamurthy, Lakshmi, and V Krishnamurthy, May 2014: Influence of PDO on South Asian summer monsoon and monsoon–ENSO relation. Climate Dynamics, 42(9-10), DOI:10.1007/s00382-013-1856-z. Abstract
This study has investigated the possible relation between the Indian summer monsoon and the Pacific Decadal Oscillation (PDO) observed in the sea surface temperature (SST) of the North Pacific Ocean. Using long records of observations and coupled model (NCAR CCSM4) simulation, this study has found that the warm (cold) phase of the PDO is associated with deficit (excess) rainfall over India. The PDO extends its influence to the tropical Pacific and modifies the relation between the monsoon rainfall and El Niño-Southern Oscillation (ENSO). During the warm PDO period, the impact of El Niño (La Niña) on the monsoon rainfall is enhanced (reduced). A hypothesis put forward for the mechanism by which PDO affects the monsoon starts with the seasonal footprinting of SST from the North Pacific to the subtropical Pacific. This condition affects the trade winds, and either strengthens or weakens the Walker circulation over the Pacific and Indian Oceans depending on the phase of the PDO. The associated Hadley circulation in the monsoon region determines the impact of PDO on the monsoon rainfall. We suggest that knowing the phase of PDO may lead to better long-term prediction of the seasonal monsoon rainfall and the impact of ENSO on monsoon.
Krishnamurthy, Lakshmi, and V Krishnamurthy, July 2014: Decadal scale oscillations and trend in the Indian monsoon rainfall. Climate Dynamics, 43(1-2), DOI:10.1007/s00382-013-1870-1. Abstract
The emerging need for extended climate prediction requires a consideration of the relative roles of climate change and low-frequency natural variability on decadal scale. Addressing this issue, this study has shown that the variability of the Indian monsoon rainfall (IMR) consists of three decadal scale oscillations and a nonlinear trend during 1901–2004. The space–time structures of the decadal oscillations are described. The IMR decadal oscillations are shown to be associated with Atlantic Multidecadal Oscillation (AMO), Atlantic tripole oscillation and Pacific Decadal Oscillation (PDO). The sea surface temperatures (SSTs) of the North Pacific and North Atlantic Oceans are also resolved as nonlinear decadal oscillations. The SST AMO mode has high positive correlation with IMR while the SST tripole mode and SST PDO have negative correlation. The trend in IMR increases during the first half of the period and decreases during the second half. The IMR trend is modified when combined with the three decadal oscillations.
Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system, therefore understanding and predicting TC location, intensity and frequency is of both societal and scientific significance. Methodologies exist to predict basin-wide, seasonally-aggregated TC activity months, seasons and even years in advance. We show that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basin-wide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal timescales, and is comprised of high-resolution (50km×50km) atmosphere and land components, and more moderate resolution (~100km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux-adjustment.” We perform a suite of 12-month duration retrospective forecasts over the 1981-2012 period, after initializing the climate model to observationally-constrained conditions at the start of each forecast period – using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basin-wide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally-aggregated regional TC activity months in advance are feasible.