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At least 1,189 records · Page 66

Development of a four-dimensional variational analysis system using the adjoint method at GLA. I - Dynamics

Recent developments in the field of data assimilation have pointed to variational analysis (essentially least-squares fitting of a model solution to observed data) using the adjoint method as a new direction that holds the potential of major improvements over the current optimal interpolation method. This paper describes the initial effort in the development of a 4D variational analysis system. Although the development is based on the Goddard Laboratory for Atmospheres General Circulation Model (GCM), the methods and procedures described in this paper can be applied to any model. The adjoint code that computes the gradients needed in the analysis can be written directly from the GCM code. An easy error-detection technique was devised in the construction of the adjoint model. Also, a method of determining the weights and the preconditioning scales for the cases where model-generated data, which are error free, are used as observation is proposed. Two test experiments show that the dynamics part of the system has been successfully completed.

Chao, Winston C.↗

Validation and quantification of uncertainty in coupled climate models using network analysis

We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies. At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the ‘strength’ of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.

54 ENVIRONMENTAL SCIENCES↗

Tropical impacts of SST forcing: A case study for 1987 versus 1988

The response of the NASA/Goddard Institute for Space Studies general circulation model (GCM) to large tropical sea surface temperature (SST) anomalies is investigated by evaluating model simulations of the particularly contrasting summer monsoon seasons 1987 and 1988. These years are representative of the warm and cold phases, respectively, of a recent El Nino-Southern Oscillation (ENSO) event. An ensemble averaging the results of three simulations was considered for each season, using monthly mean observed SST anomalies for June-August 1987 and 1988 as lower boundary forcing. Consistent with the European Center for Medium Weather Forecast (ECMWF)-analyzed winds, the simulations based on 1988 as compared to 1987 SST exhibit stronger upper-tropospheric irrotational circulation between the monsoon regions and the Southern Hemispheric sub-tropical anticyclones, a stronger Pacific Walker cell and a weaker subtropical westerly jet over the South Pacific. In the same vein, the modeled precipitation, indicating a more northerly position of the Pacific Inter-Tropical Convergence Zone (ITCZ) in 1988 compared with 1987, is supported by satellite observations of outgoing longwave radiation and highly reflective clouds.

Druyan, Leonard M.↗

Linking Stochasticity of Convection to Large-Scale Vertical Velocity to Improve Indian Summer Monsoon Simulation in the NCAR CAM5

The Plant–Craig (PC) stochastic convective parameterization scheme is modified by linking the stochastic generation of convective clouds to the change of large-scale vertical pressure velocity at 500 hPa with time so as to better account for the relationship between convection and the large-scale environment. Three experiments using the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), are conducted: one with the default Zhang–McFarlane deterministic convective scheme, another with the original PC stochastic scheme, and a third with the modified PC stochastic scheme. Evaluation is focused on the simulation of the Indian summer monsoon (ISM), which is a long-standing challenge for all current global circulation models. Results show that the modified stochastic scheme better represents the annual cycle of the climatological mean rainfall over central India and the mean onset date of ISM compared to other simulations. Also, for the simulations of ISM intraseasonal variability for quasi-biweekly and 30–60-day modes, the modified stochastic parameterization produces more realistic propagation and magnitude, especially for the observed northeastward movement of the 30–60-day mode, for which the other two simulations show the propagation in the opposite direction. Causes are investigated through a moisture budget analysis. Compared to the other two simulations, the modified stochastic scheme with an appropriate representation of convection better represents the patterns and amplitudes of large-scale dynamical convergence and moisture advection and thus corrects the monsoon cycle associated with their covariation during the peaks and troughs of intraseasonal oscillation.

54 ENVIRONMENTAL SCIENCES↗

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗

Robust late twenty-first century shift in the regional monsoons in RegCM-CORDEX simulations

Abstract We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25 km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability.

54 ENVIRONMENTAL SCIENCES↗

Interactions between climate change mitigation and adaptation: The case of hydropower in Brazil

In this paper we perform a multi-model comparison to assess strategies for adaptation to climate change impacts in hydropower generation in Brazil under two Representative Concentration Pathways (RCPs 4.5 and 8.5). The approach used allows for evaluating the interactions between climate change mitigation and adaptation strategies under low and high impact scenarios through 2050. Climate change impact projections of sixteen General Circulation Models (GCMs) indicate that a global emissions trajectory of an RCP 8.5 scenario would likely yield more severe impacts on hydropower generation than an RCP 4.5 scenario. Adaptation modeling suggests that climate change impacts can be compensated by a wide range of alternatives, whose optimality will depend on the level of mitigation effort pursued. Our results show that climate change impacts would lead to even higher emissions in the absence of climate change mitigation policies. On the other hand, mitigation strategies to pursue lower emissions are maintained under climate change impact shocks, meaning that mitigation strategies are robust when faced with adaptation challenges. Mitigation efforts could yield a more diverse and less carbon intensive mix of technological options for adaptation. When including investment costs to adapt to climate change impacts, in some cases mitigation can lead to a lower total investment level.

Lucena, André F. P.↗

The Contribution of Dynamic Interannual Variability to Ozone Trends

At middle latitudes the total column ozone and the lower stratospheric ozone mixing ratio exhibit natural variability. Models and statistical analyses of observations such as SAGE ozone profiles and TOMS column measurements show that seasonal cycle, solar cycle, and interannual dynamical variability and dynamical phenomena such as the quasi- biennial oscillation all contribute to ozone variability. These must be accounted for when deriving ozone trends. Systematic or random changes in the atmospheric circulation may also contribute to ozone trends. It is presently unclear how much of the ozone trend derived from observations is due to changes in the chemical composition of the stratosphere and how much is due to changes in the atmospheric circulation. We are attempting to resolve this issue by comparing a twenty-five year simulation of ozone with fixed source gas boundary conditions with an identical simulation with time dependent source gas boundary conditions. Both simulations are driven with output from a general circulation model that produces realistic interannual variability in dynamical forcing. The model trend in ozone due to changes in composition is determined from the difference in these simulations. We compare these trends with trends determined from observations and model output using the same analysis techniques. Initial results emphasize the complications to attribution of observed ozone trends to dynamical and photochemical effects that are due to interrelationships between trends in transport, temperature, and photochemical effects. It may not be possible to describe the ozone trend as a superposition of dynamical and photochemical contributions.

Douglass, Anne↗

Ocean-Land Teleconnections and Chaotic Atmospheric Variability in Climate Models, with Implications for Real-World Behavior

This study introduces a unique approach to estimating a fundamental but unmeasurable property of Nature: ρo 2 , the fraction of the variance of a given meteorological variable that is determined by boundary forcing (specifically, SSTs) as opposed to chaotic atmospheric dynamics. Here, we focus on continental monthly-averaged near-surface air temperature, or T2M. Rather than determining the fractions of SST-explained T2M variance found for a specific atmospheric general circulation model (AGCM) and then assuming that these fractions also represent Nature, we perform an analysis that entails: (i) evaluating a specific AGCM’s ability to capture observed variability with an infinite number of ensemble members, (ii) quantifying the degree to which different modeling systems agree on SST-land teleconnections, and (iii) combining these results into our novel estimates of ρo 2 . The derived ρo 2 fields suggest, with caveats, that AGCMs tend to overestimate the fraction of explained T2M variance (the signal-to-total variance ratio) in the Tropics.

Randal D Koster↗

The KPP Boundary Layer Scheme for the Ocean: Revisiting Its Formulation and Benchmarking One‐Dimensional Simulations Relative to LES

Abstract We evaluate the Community ocean Vertical Mixing project version of the K‐profile parameterization (KPP) for modeling upper ocean turbulent mixing. For this purpose, one‐dimensional KPP simulations are compared across a suite of oceanographically relevant regimes against horizontally averaged large eddy simulations (LESs). We find the standard configuration of KPP consistent with LES across many forcing regimes, supporting its physical basis. Our evaluation also motivates recommendations for KPP best practices within ocean circulation models and identifies areas where further research is warranted. The original treatment of KPP recommends the matching of interior diffusivities and their gradients to the KPP‐predicted values computed in the ocean surface boundary layer (OSBL). However, we find that difficulties in representing derivatives of rapidly changing diffusivities near the base of the OSBL can lead to loss of simulation fidelity. To mitigate this difficulty, we propose and evaluate two computationally simpler approaches: (1) match to the internal predicted diffusivity alone and (2) set the KPP diffusivity to 0 at the OSBL base. We find the KPP entrainment buoyancy flux to be sensitive to vertical grid resolution and details of how to diagnose the KPP boundary layer depth. We modify the KPP turbulent shear velocity parameterization to reduce resolution dependence. Additionally, an examination of LES vertical turbulent scalar flux budgets shows that the KPP‐parameterized nonlocal tracer flux is incomplete due to the assumption that it solely redistributes the surface tracer flux. This result motivates further studies of the nonlocal flux parameterization.

54 ENVIRONMENTAL SCIENCES↗

U.S. Eastern Continental Shelf Carbon Cycling (USECoS): Modeling, Data Assimilation, and Analysis

Although the oceans play a major role in the uptake of fossil fuel CO2 from the atmosphere, there is much debate about the contribution from continental shelves, since many key shelf fluxes are not yet well quantified: the exchange of carbon across the land-ocean and shelf-slope interfaces, air-sea exchange of CO2, burial, and biological processes including productivity. Our goal is to quantify these carbon fluxes along the eastern U.S. coast using models quantitatively verified by comparison to observations, and to establish a framework for predicting how these fluxes may be modified as a result of climate and land use change. Our research questions build on those addressed with previous NASA funding for the USECoS (U.S. Eastern Continental Shelf Carbon Cycling) project. We have developed a coupled biogeochemical ocean circulation model configured for this study region and have extensively evaluated this model with both in situ and remotely-sensed data. Results indicate that to further reduce uncertainties in the shelf component of the global carbon cycle, future efforts must be directed towards 1) increasing the resolution of the physical model via nesting and 2) making refinements to the biogeochemical model and quantitatively evaluating these via the assimilation of biogeochemical data (in situ and remotely-sensed). These model improvements are essential for better understanding and reducing estimates of uncertainties in current and future carbon transformations and cycling in continental shelf systems. Our approach and science questions are particularly germane to the carbon cycle science goals of the NASA Earth Science Research Program as well as the U.S. Climate Change Research Program and the North American Carbon Program. Our interdisciplinary research team consists of scientists who have expertise in the physics and biogeochemistry of the U.S. eastern continental shelf, remote-sensing data analysis and data assimilative numerical models.

Mannino, Antonio↗

Predicting the climate change impacts on water-carbon coupling cycles for a loess hilly-gully watershed

Understanding the climate change impacts on water and carbon cycles is of great importance for comprehensive watershed management. Although many studies have been conducted on the future climate change impacts on either water cycle or carbon cycle, the potential impacts on water-carbon coupling cycles are still poorly understood. Here we used an integrated hydro-biochemical model (SWAT-DayCent) to quantitatively investigate the climate change impacts on water-carbon coupling cycles with a case study of typical loess hilly-gully watershed-the Jinghe River Basin (JRB) on the Loess Plateau. We used climate scenarios data derived under the three Representative Concentration Pathways (RCPs2.6, 4.5 and 8.5) by five downscaled Global Circulation Models (GCMs) and set two future periods of 2020–2049 (near future, NF) and 2070–2099 (far future, FF). It was projected that the annual precipitation would generally decrease slightly during the NF period but increase by 4–11% during the FF period, while the maximum/minimum air temperatures would increase significantly. The average annual streamflow would decrease (with up to 20.1% under RCP8.5) and evapotranspiration (ET) would remain almost unchanged during the NF period; however, both of them would increase during the FF period. The net primary production (NPP) would be generally higher due to the CO2 fertilization, whereas the soil organic carbon would decrease across all scenarios due to the warmer climate. The NPP-ET was projected to be closely coupled across all scenarios, and this coupling was mainly controlled by the inter-annual variability (IAV) of precipitation. Moreover, the precipitation IAV combined with NPP-ET coupling could also jointly control the NPP variability in the JRB. These projections in water-carbon coupling cycles can be useful to make better-informed decisions for future water resources and ecosystem management of the loess hilly-gully regions.

climate change↗

Utilizing Mars Global Reference Atmospheric Model (Mars-GRAM 2005) to Evaluate Entry Probe Mission Sites

The Mars Global Reference Atmospheric Model (Mars-GRAM 2005) is an engineering-level atmospheric model widely used for diverse mission applications. An overview is presented of Mars-GRAM 2005 and its new features. The "auxiliary profile" option is one new feature of Mars-GRAM 2005. This option uses an input file of temperature and density versus altitude to replace the mean atmospheric values from Mars-GRAM's conventional (General Circulation Model) climatology. Any source of data or alternate model output can be used to generate an auxiliary profile. Auxiliary profiles for this study were produced from mesoscale model output (Southwest Research Institute's Mars Regional Atmospheric Modeling System (MRAMS) model and Oregon State University's Mars mesoscale model (MMM5) model) and a global Thermal Emission Spectrometer (TES) database. The global TES database has been specifically generated for purposes of making Mars-GRAM auxiliary profiles. This data base contains averages and standard deviations of temperature, density, and thermal wind components, averaged over 5-by-5 degree latitude-longitude bins and 15 degree Ls bins, for each of three Mars years of TES nadir data. The Mars Science Laboratory (MSL) sites are used as a sample of how Mars-GRAM' could be a valuable tool for planning of future Mars entry probe missions. Results are presented using auxiliary profiles produced from the mesoscale model output and TES observed data for candidate MSL landing sites. Input parameters rpscale (for density perturbations) and rwscale (for wind perturbations) can be used to "recalibrate" Mars-GRAM perturbation magnitudes to better replicate observed or mesoscale model variability.

Justh, Hilary L.↗

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗

Applications of Mars Global Reference Atmospheric Model (Mars-GRAM 2005) Supporting Mission Site Selection for Mars Science Laboratory

The Mars Global Reference Atmospheric Model (Mars-GRAM 2005) is an engineering level atmospheric model widely used for diverse mission applications. An overview is presented of Mars-GRAM 2005 and its new features. One new feature of Mars-GRAM 2005 is the 'auxiliary profile' option. In this option, an input file of temperature and density versus altitude is used to replace mean atmospheric values from Mars-GRAM's conventional (General Circulation Model) climatology. An auxiliary profile can be generated from any source of data or alternate model output. Auxiliary profiles for this study were produced from mesoscale model output (Southwest Research Institute's Mars Regional Atmospheric Modeling System (MRAMS) model and Oregon State University's Mars mesoscale model (MMM5)model) and a global Thermal Emission Spectrometer(TES) database. The global TES database has been specifically generated for purposes of making Mars-GRAM auxiliary profiles. This data base contains averages and standard deviations of temperature, density, and thermal wind components,averaged over 5-by-5 degree latitude-longitude bins and 15 degree L(s) bins, for each of three Mars years of TES nadir data. Results are presented using auxiliary profiles produced from the mesoscale model output and TES observed data for candidate Mars Science Laboratory (MSL) landing sites. Input parameters rpscale (for density perturbations) and rwscale (for wind perturbations) can be used to "recalibrate" Mars-GRAM perturbation magnitudes to better replicate observed or mesoscale model variability.

Justh, Hilary L.↗

The impact of clouds on the shortwave radiation budget of the surface-atmosphere system - Interfacing measurements and models

Two datasets have been combined to demonstrate how the availability of more comprehensive datasets could serve to elucidate the shortwave radiative impact of clouds on both the atmospheric column and the surface. These datasets consist of two measurements of net downward shortwave radiation: one of near-surface measurements made at the Boulder Atmospheric Observatory tower, and the other of collocated top-of-the-atmosphere measurements from the Earth Radiation Budget Experiment. Output from the European Centre for Medium Range Weather Forecasts General Circulation Model also has been used as an aid in interpreting the data, while the data have in turn been employed to validate the model's shortwave radiation code as it pertains to cloud radiation properties. Combined, the datasets and model demonstrate a strategy for determining under what conditions the shortwave radiative impact of clouds leads to a heating or cooling of the atmospheric column. The datasets also show, in terms of a linear slope-offset algorithm for retrieving the net downward shortwave radiation at the surface from satellite measurements, that the clouds present during this study produced a modest negative bias in the retrieved surface flux relative to that inferred from a clear-sky algorithm.

Cess, Robert D.↗

Response of Indian summer monsoon rainfall to remote carbonaceous aerosols at short time scales: Teleconnections and feedbacks

The effect of atmospheric aerosols on Indian monsoon is one of the scientifically challenging and societally relevant research issues of the recent decades. Past studies have derived inferences mostly based on local emissions and their impacts thereupon. However, more recent studies have shown that the remote effects driven by aerosols elsewhere could also impact the monsoon system on different time scales. Our study using an atmospheric general circulation model (AGCM) shows that regional carbonaceous aerosol emissions (from North America, Europe and North Africa and Asia) can significantly alter Indian summer monsoon rainfall. It is interesting to note that the effects of remote aerosols are larger and bear a resemblance to each other in comparison to local emissions. Here, our study reveals that the modulation of large-scale circulation induced by regional warming by carbonaceous aerosols leads to teleconnection patterns around the globe, thereby changing the precipitation depending on the phase of these disturbances. We also find that the effects of remote carbonaceous aerosols are strengthened by modulation/feedback through natural dust aerosols over the Arabian Sea with subsequent increase in rainfall over India. The results signify that the changes in the aerosol emissions in one region could lead to the change in precipitation over other regions through global teleconnection and associated feedbacks induced by regional atmospheric warming and/or cooling.

Carbonaceous aerosols↗

Large Eddy Simulations of Upper-Ocean Turbulence Across the Equatorial Pacific Cold Tongue

Turbulence in the equatorial Pacific cold tongue plays multiple roles in the sea-surface temperature budget. However, observations of turbulence are limited to a handful of field experiments lasting from a few days to one month at 0 N , 140 W, and the key turbulent fluxes can only be inferred. Although explicit simulations of turbulence resolve these fluxes, the required large eddy simulations (LES) are costly and thus also limited to a few weeks. A two-fold hypothesis motivates this contribution to the PUMP pre-field modelling experiments in support of TPOS: 1) that there exist useful relationships between the surface wind, wave, and buoyancy forcing, oceanic shear and stratification, and turbulent mixing, but 2) these relationships differ between regions of equatorial dynamics (f~0) and higher latitudes, such that the state space is insufficiently sampled to understand these relationships and represent them in ocean general circulation models (OGCM). To address the lack of observations, we simulated 35 continuous days of upper ocean turbulence using LES during October-November 1985 at sites in two regions (70 days in total) of the cold tongue: 0 N, 140 W and 3 N, 140 W. The model reproduces many features of the observed turbulence at 0,140W, including the “deep-cycle” observed by Gregg et al. (1985) Nature and the turbulent pulses every few hours during the night and in the early morning. Furthermore, the results at 3 N support the hypothesis advanced by Cherian et al. (2021) JPO that strong, but intermittent deep-cycle turbulence is observed to the north of the equator in the presence of strong shear associated with Tropical Instability Waves. Comparisons with the K-profile parameterization (KPP) scheme show that additional tuning of the KPP parameters can reduce differences between the turbulent fluxes produced by KPP and LES at both sites. The results will suggest modifications to OGCMs and already emphasize the need for a more extensive measurements of vertical profiles of shear, stratification and turbulent mixing to reveal the spatio-temporal structure of turbulence and how it relates to forcing, shear and stratification across the equatorial Pacific Cold tongue.

Large Eddy Simulations↗